Reviewer #2 (Public review):

Summary:

The authors investigate miRNA miR-195 in the context of B-cell development. They demonstrate that ectopic expression of miR-195 in hematopoietic progenitor cells can, to a considerable extent, override the consequences of deletion of Ebf1, a central B-lineage defining transcription factor, in vitro and upon short-term transplantation into immunodeficient mice in vivo. In addition, the authors demonstrate that the reverse experiment, genetic deletion of miR-195, has virtually no effect on B-cell development. Mechanistically, the authors identify Foxo1 phosphorylation as one pathway partially contributing to the rescue effect of miR-195. An additional analysis of epigenetics by ATACseq adds potential additional factors that might also contribute to the effect of ectopic expression of miR-195.

Strengths:

The authors employ a robust assay system, Ebf1-KO HPC, to test for B-lineage promoting factors. The manuscript overall takes on an interesting perspective rarely employed for analysis of miRNA by overexpressing the miRNA of interest. Ideally, this approach may reveal, if not the physiological function of this miRNA, the role of distinct pathways in developmental processes.

Weaknesses:

At the same time, this approach constitutes a major weakness: It does not reveal information on the physiological role of miR-195. In fact, the authors themselves demonstrate in their KO approach, that miR-195 has virtually no role in B-cell development, as has been demonstrated already in 2020 by Hutter and colleagues. While the authors cite this paper, unfortunately, they do so in a different context, hence omitting that their findings are not original.

Conceptually, the authors stress that a predominant function of miRNA (in contrast to transcription factors, as the authors suggest) lies in fine-tuning. However, there appears to be a misconception. Misregulation of fine tuning of gene expression may result in substantial biological effects, especially in developmental processes. The authors want to highlight that miR-195 is somewhat an exception in that regard, but this is clearly not the case. In addition to miR-150, as referenced by the authors, also the miR-17-92 or miR-221/222 families play a significant role in B-cell development, their absence resulting in stage-specific developmental blocks, and other miRNAs, such as miR-155, miR-142, miR-181, and miR-223 are critical regulators of leukocyte development and function. Thus, while in many instances a single miRNA moderately affects gene expression at the level of an individual target, quite frequently targets converge in common pathways, hence controlling critical biological processes.

The paper has some methodological weaknesses as well: For the most part, it lacks thorough statistical analysis and only representative FACS plots are provided. Many bar graphs are based on heavy normalization making the T-tests employed inapplicable. No details are provided regarding statistical analysis of microarrays. Generation of the miR-195-KO mice is insufficiently described and no validation of deletion is provided. Important controls are missing as well, the most important one being a direct rescue of Ebf1-KO cells by re-expression of Ebf1. This control is critical to quantify the extent of override of Ebf1-deficiency elicited by miR-195 and should essentially be included in all experiments. A quantitative comparison is essential to support the authors' main conclusion highlighted in the title of the manuscript. As the manuscript currently stands, only negative controls are provided, which, given the profound role of Ebf1, are insufficient, because many experiments, such as assessment of V(D)J recombination, IgM surface expression, or class-switch recombination, are completely negative in controls. In addition, the authors should also perform long-term reconstitution experiments. While it is somewhat surprising that the authors obtain splenic IgM+ B cells after just 10 days, these experiments would certainly be much more informative after longer periods of time. Using "classical" mixed bone marrow chimeras using a combination of B-cell defective (such as mb1/mb1) bone marrow and reconstituted Ebf1-KO progenitors would permit much more refined analyses.

With regard to mechanism, the authors show that the Foxo1 phosphorylation pathway accounts for the rescue of CD19 expression, but not of other factors, and mentioned in the discussion. The authors then resort to epigenetic analysis, but their rationale remains somewhat vague. It remains unclear how miR-195 is linked to epigenetic changes.

Reviewer #3 (Public review):

Summary:

In this study, Miyatake et al. present the interesting finding that ectopic expression of miR-195 in EBF1-deficient hematopoietic progenitor cells can partially rescue their developmental block and allows B cells to progress to a B220+ CD19+ cells stage. Notably, this is accompanied by an upregulation of B cell specific genes and, correspondingly, a downregulation of T, myeloid and NK lineage-related genes, suggesting that miR-195 expression is at least in part equivalent to EBF1 activity in orchestrating the complex gene regulatory network underlying B cell development. Strengthening this point, ATAC sequencing of miR-195-expressing EBF1-deficient B220+CD19+ cells and a comparison of these data to public datasets of EBF1-deficient and -proficient cells suggest that miR-195 indirectly regulates gene expression and chromatin accessibility of some, but not all regions regulated by EBF1.

Mechanistically, the authors identify a subset of potential target genes of miR-195 involved in MAPK and PI3K signalling. Dampening of these pathways has previously been demonstrated to activate FOXO1, a key transcription factor for early B cells downstream of EBF1. Accordingly, the authors hypothesize that miR-195 exerts its function through FOXO1. Supporting this claim, also exogenous FOXO1 expression is able to promote the development of EBF1-deficient cells to the B220+CD19+ stage and thus recapitulates the miR-195 phenotype.

Strengths:

The strength of the presented study is the detailed assessment of the altered chromatin accessibility in response to ectopic miR-195 expression. This provides insight into how miR-195 impacts on the gene regulatory network that governs B cell development and allows the formation of mechanistic hypotheses.

Weaknesses:

The key weakness of this study is that its findings are based on the artificial and ectopic expression of a miRNA out of its normal context, which in my opinion strongly limits the biological relevance of the presented work.

While the authors performed qPCRs for miR-195 on different B cell populations and show that its relative expression peaks in early B cells, it remains unclear whether the absolute miR-195 expression is sufficiently high to have any meaningful biological activity. In fact, other miRNA expression data from immune cells (e.g. DOI 10.1182/blood-2010-10-316034 and DOI 10.1016/j.immuni.2010.05.009) suggest that miR-195 is only weakly, if at all, expressed in the hematopoietic system.<br /> Update to this part after revision: The authors now state in the discussion that their study does not aim to uncover and characterize a physiological role of miR-195 in lymphocytes development, but rather reveals "the potential of miR-195 to compensate for EBF1 deficiency". However, in my opinion, the absence of any physiological context still limits this study's relevance.

The authors support their finding by a CRISPR-derived miR-195 knockout mouse model which displays mild but significant differences in the hematopoietic stem cell compartment and in B cell development. However, they fail to acknowledge and discuss a lymphocyte-specific miR-195 knockout mouse that does not show any B cell defects in the bone marrow or spleen and thus contradicts the authors' findings (DOI 10.1111/febs.15493). Of note, B-1 B cells in particular have been shown to be elevated upon loss of miR-15-16-1 and/or miR-15b-16-2, which contradicts the data presented here for loss of the family member miR-195.

A second weakness is that some claims by the authors appear overstated or at least not fully backed up by the presented data. In particular, the findings that miR-195-expressing cells can undergo VDJ recombination, express the pre-BCR/BCR and can class switch need to be strengthened. It would be beneficial to include additional controls to these experiments, e.g. a RAG-deficient mouse as a reference/negative control for the ddPCR and the surface IgM staining, and cells deficient in class switching for the IgG1 flow cytometric staining.

Moreover, the manuscript would be strengthened by a more thorough investigation of the hypothesis that miR-195 promotes the stabilization and activity of FOXO1, e.g. by comparing the authors' ATACseq data to the FOXO1 signature.

Author response:

The following is the authors’ response to the original reviews.

eLife assessment 

This useful study reports that the exogenous expression of the microRNA miR-195 can partially compensate in early B cell development for the loss of EBF1, one of the key transcription factors in B cells. While this finding will be of interest to those studying lymphocyte development, the evidence, particularly with regard to the molecular mechanisms that underpin the effect of miR-195, is currently incomplete. 

Public Reviews: 

Reviewer #1 (Public review):

Summary: 

Here, the authors are proposing a role for miR-196, a microRNA that has been shown to bind and enhance the degradation of mRNA targets in the regulation of cell processes, and has a novel role in allowing the emergence of CD19+ cells in cells in which Ebf1, a critical B-cell transcription factor, has been genetically removed. 

Strengths: 

That over-expression of mR-195 can allow the emergence of CD19+ cells missing Ebf1 is somewhat novel. 

Their data does perhaps support to a degree the emergence of a transcriptional network that may bypass the absence of Ebf1, including the FOXO1 transcription factor, but this data is not strong or definitive. 

Weaknesses: 

It is unclear whether this observation is in fact physiological. When the authors analyse a knockout model of miR-195, there is not much of a change in the B-cell phenotype. Their findings may therefore be an artefact of an overexpression system. 

The authors have provided insufficient data to allow a thorough appraisal of the stepwise molecular changes that could account for their observed phenotype. 

Reviewer #2 (Public review): 

Summary: 

The authors investigate miRNA miR-195 in the context of B-cell development. They demonstrate that ectopic expression of miR-195 in hematopoietic progenitor cells can, to a considerable extent, override the consequences of deletion of Ebf1, a central Blineage defining transcription factor, in vitro and upon short-term transplantation into immunodeficient mice in vivo. In addition, the authors demonstrate that the reverse experiment, genetic deletion of miR-195, has virtually no effect on B-cell development. Mechanistically, the authors identify Foxo1 phosphorylation as one pathway partially contributing to the rescue effect of miR-195. An additional analysis of epigenetics by ATACseq adds potential additional factors that might also contribute to the effect of ectopic expression of miR-195. 

Strengths: 

The authors employ a robust assay system, Ebf1-KO HPC, to test for B-lineage promoting factors. The manuscript overall takes on an interesting perspective rarely employed for the analysis of miRNA by overexpressing the miRNA of interest. Ideally, this approach may reveal, if not the physiological function of this miRNA, the role of distinct pathways in developmental processes. 

Weaknesses: 

At the same time, this approach constitutes a major weakness: It does not reveal information on the physiological role of miR-195. In fact, the authors themselves demonstrate in their KO approach, that miR-195 has virtually no role in B-cell development, as has been demonstrated already in 2020 by Hutter and colleagues. While the authors cite this paper, unfortunately, they do so in a different context, hence omitting that their findings are not original. 

Conceptually, the authors stress that a predominant function of miRNA (in contrast to transcription factors, as the authors suggest) lies in fine-tuning. However, there appears to be a misconception. Misregulation of fine-tuning of gene expression may result in substantial biological effects, especially in developmental processes. The authors want to highlight that miR-195 is somewhat of an exception in that regard, but this is clearly not the case. In addition to miR-150, as referenced by the authors, also the miR-17-92 or miR-221/222 families play a significant role in B-cell development, their absence resulting in stage-specific developmental blocks, and other miRNAs, such as miR-155, miR-142, miR-181, and miR-223 are critical regulators of leukocyte development and function. Thus, while in many instances a single miRNA moderately affects gene expression at the level of an individual target, quite frequently targets converge in common pathways, hence controlling critical biological processes. 

The paper has some methodological weaknesses as well: For the most part, it lacks thorough statistical analysis, and only representative FACS plots are provided. Many bar graphs are based on heavy normalization making the T-tests employed inapplicable. No details are provided regarding the statistical analysis of microarrays. Generation of the miR-195-KO mice is insufficiently described and no validation of deletion is provided. Important controls are missing as well, the most important one being a direct rescue of Ebf1-KO cells by re-expression of Ebf1. This control is critical to quantify the extent of override of Ebf1-deficiency elicited by miR-195 and should essentially be included in all experiments. A quantitative comparison is essential to support the authors' main conclusion highlighted in the title of the manuscript. As the manuscript currently stands, only negative controls are provided, which, given the profound role of Ebf1, are insufficient, because many experiments, such as assessment of V(D)J recombination, IgM surface expression, or class-switch recombination, are completely negative in controls. In addition, the authors should also perform long-term reconstitution experiments. While it is somewhat surprising that the authors obtained splenic IgM+ B cells after just 10 days, these experiments would be certainly much more informative after longer periods of time. Using "classical" mixed bone marrow chimeras using a combination of B-cell defective (such as mb1/mb1) bone marrow and reconstituted Ebf1-KO progenitors would permit much more refined analyses. 

With regard to mechanism, the authors show that the Foxo1 phosphorylation pathway accounts for the rescue of CD19 expression, but not for other factors, as mentioned in the discussion. The authors then resort to epigenetics analysis, but their rationale remains somewhat vague. It remains unclear how miR-195 is linked to epigenetic changes. 

Reviewer #3 (Public review): 

Summary: 

In this study, Miyatake et al. present the interesting finding that ectopic expression of miR-195 in EBF1-deficient hematopoietic progenitor cells can partially rescue their developmental block and allow B cells to progress to a B220+ CD19+ cells stage. Notably, this is accompanied by an upregulation of B-cell-specific genes and, correspondingly, a downregulation of T, myeloid, and NK lineage-related genes, suggesting that miR-195 expression is at least in part equivalent to EBF1 activity in orchestrating the complex gene regulatory network underlying B cell development. Strengthening this point, ATAC sequencing of miR-195-expressing EBF1-deficient B220+CD19+ cells and a comparison of these data to public datasets of EBF1-deficient and -proficient cells suggest that miR-195 indirectly regulates gene expression and chromatin accessibility of some, but not all regions regulated by EBF1. 

Mechanistically, the authors identify a subset of potential target genes of miR-195 involved in MAPK and PI3K signaling. Dampening of these pathways has previously been demonstrated to activate FOXO1, a key transcription factor for early B cells downstream of EBF1. Accordingly, the authors hypothesize that miR-195 exerts its function through FOXO1. Supporting this claim, also exogenous FOXO1 expression is able to promote the development of EBF1-deficient cells to the B220+CD19+ stage and thus recapitulates the miR-195 phenotype. 

Strengths: 

The strength of the presented study is the detailed assessment of the altered chromatin accessibility in response to ectopic miR-195 expression. This provides insight into how miR-195 impacts the gene regulatory network that governs B-cell development and allows the formation of mechanistic hypotheses. 

Weaknesses: 

The key weakness of this study is that its findings are based on the artificial and ectopic expression of a miRNA out of its normal context, which in my opinion strongly limits the biological relevance of the presented work. 

While the authors performed qPCRs for miR-195 on different B cell populations and show that its relative expression peaks in early B cells, it remains unclear whether the absolute miR-195 expression is sufficiently high to have any meaningful biological activity. In fact, other miRNA expression data from immune cells (e.g. DOI

10.1182/blood-2010-10-316034 and DOI 10.1016/j.immuni.2010.05.009) suggest that miR-195 is only weakly, if at all, expressed in the hematopoietic system. 

The authors support their finding by a CRISPR-derived miR-195 knockout mouse model which displays mild, but significant differences in the hematopoietic stem cell compartment and in B cell development. However, they fail to acknowledge and discuss a lymphocyte-specific miR-195 knockout mouse that does not show any B cell defects in the bone marrow or spleen and thus contradicts the authors' findings (DOI

10.1111/febs.15493). Of note, B-1 B cells in particular have been shown to be elevated upon loss of miR-15-16-1 and/or miR-15b-16-2, which contradicts the data presented here for loss of the family member miR-195. 

A second weakness is that some claims by the authors appear overstated or at least not fully backed up by the presented data. In particular, the findings that miR-195expressing cells can undergo VDJ recombination, express the pre-BCR/BCR and class switch needs to be strengthened. It would be beneficial to include additional controls to these experiments, e.g. a RAG-deficient mouse as a reference/negative control for the ddPCR and the surface IgM staining, and cells deficient in class switching for the IgG1 flow cytometric staining. 

Moreover, the manuscript would be strengthened by a more thorough investigation of the hypothesis that miR-195 promotes the stabilization and activity of FOXO1, e.g. by comparing the authors' ATACseq data to the FOXO1 signature. 

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors): 

Miyatake et al., present a manuscript that explores the role of miR-195 in B cell development. 

Their data suggests a role for this microRNA: 

Using an Ebf1 fetal liver knockout of B-cell differentiation that a small population of CD19 expressing with some evidence of V(D)J recombination capable of class switch can be derived by transduction of miR-195. 

In the emergent CD19+ Ebf1-/- cells, the authors provide some evidence that Mapk and Akt3 may be miR-195 targets that are downregulated allowing FOXO1 transcription factor pathway may be involved in the emergent CD19+ cells arising from miR-195 transduction. 

Perhaps less compelling data is provided with regards to a role for miR-195 in normal Bcell development through analysis of a miR-195 knockout model. 

While there are some interesting preliminary data presented for a role for miR-195 in the context of Ebf1-/- cells, there are some questions I think the authors could consider. 

Comments: 

(1-1) It is difficult to ascertain the potential role of miR-195 transduction in allowing the emergence of CD19+ cells from the data provided. miR-195 has been generally shown to destabilize mRNA transcripts by 3' UTR binding that targets mRNA transcripts for degradation. The effect of transduction of miR-195 would therefore be expected to be related to the degradation of factors opposing aspects of B-lineage specification or maintenance. I would be particularly interested in transcriptional or epigenetic regulators that may be modified in this way, at an mRNA as well as protein level.

We appreciate the reviewerʼs thoughtful comments and agree that miRNAs often exert their effects through the degradation or translational repression of mRNAs encoding regulatory factors. In our study, we attempted to address this point by combining predictive analysis (using TargetScan and starBase) with luciferase reporter assays and qPCR to validate several potential targets of miR-195, including Mapk3 and Akt3. We acknowledge that this is not a comprehensive mechanistic analysis. We agree that a broader and systematic identification of direct targets of miR-195, particularly those involved in transcriptional and epigenetic regulation, would further clarify the mechanisms involved. However, due to limitations in resources and time, we are currently unable to perform global proteomic or ChIP-based validations. Nevertheless, our ATAC-seq and microarray data indicate that miR-195 overexpression leads to increased accessibility and expression of several key B-lineage transcription factors (Pax5, Runx1, Irf8), suggesting that miR-195 indirectly activates transcriptional programs relevant to B cell commitment. We have now clarified this limitation in the revised Discussion section (lines 505‒524), and we emphasize that our current findings represent the potential of miR-195 rather than its physiological role. We hope that this clarification addresses the concern.

(1-2) While I acknowledge the authors have undertaken TargetScan and starBase analysis to try and predict miR-195 interactions, they do not provide a comprehensive list of putative targets that can be referenced against their cDNA data. Though they postulate Mapk3 and Akt3 as putative miR-195 targets and assay these in luciferase reporter systems (Figure 4), these were not clearly differentially regulated in the microarray data they provided (Figure 1E) as being downregulated on miR-195 transduction in Ebf1-/- cells.

We thank the reviewer for pointing out the need for a more comprehensive list of predicted miR-195 targets. In response, we have now included a supplementary table 4 (human) and 5 (mouse) listing all putative miR-195 targets predicted by TargetScan and starBase. As noted, Mapk3 expression was indeed downregulated upon miR-195 transduction, consistent with our luciferase reporter and qPCR results. For Akt3, we observed variability in the microarray data depending on the probe used, resulting in inconsistent expression levels. We acknowledge this and have added a clarification in the revised manuscript (lines 335‒339), noting that the regulation of Akt3 by miR-195 is potentially probe-dependent and may require further validation. We hope this clarification resolves the concern.

(1-3) The authors should provide a more comprehensive analysis of transcriptional changes induced by miR-195 Ebf1-/- specifically in the preproB cell stage of development in Ebf1-/- and miR-195 Ebf1-/- cells. The differentially expressed gene list should be provided as a supplemental file. The gene expression data should be provided for the different B-cell differentiation stages, eg. Ebf1-/- preproB cells, and Ebf1-/- miR-195 preproB cells, CD19+ cells and more differentiated subsets induced by miR-195 transduction.

We appreciate the reviewerʼs suggestion to provide a more comprehensive transcriptomic analysis at different B-cell differentiation stages. Unfortunately, due to the limited availability of cells and technical constraints, we were unable to perform RNA-seq on miR-195 transduced Ebf1^−/− pre-pro-B or CD19+ cells. However, to address this point, we referenced publicly available RNA-seq data (GEO accession: GSE92434), which includes transcriptomic profiles of Ebf1^−/− pro-B cells and wild-type controls. By comparing our microarray data from miR-195 transduced Ebf1^−/− cells with this dataset, we found partial restoration of expression for several key B-lineage genes, such as Pax5, Runx1, and Irf8, which are normally downregulated in the absence of EBF1. This comparison supports the notion that miR-195 partially reactivates the transcriptional network essential for B cell development. We have added this interpretation to the Discussion section (lines 528‒533).

(1-4) More replicates (at least 3 of each genotype) are required for their Western Blots for FOXO1 and pFOXO1 (Fig 4C, D). Western blots should also be provided for other known B-lineage transcriptional regulators such as PAX5 and ERG.

We thank the reviewer for these valuable suggestions. In response, we have now quantified and added the relative band intensities of FOXO1 and pFOXO1 from three independent experiments in the revised Figure 4C, and we include statistical analysis to support the reproducibility of these results. Additionally, as requested, we performed western blotting for PAX5 and ERG using the same samples. The results showed no significant change in these protein levels between miR-195-transduced and control Ebf1^−/− cells, consistent with the modest upregulation observed in our microarray data. We have included the PAX5 and ERG western blot images in Supplementary Figure S3 and have revised the text in the Results section (lines 351‒35)

(1-5) The authors have not shown a transcriptional binding by ChIPseq or other methods such as cut and tag/ cut and run for FOXO1 binding to B-lineage genes in their Ebf1-/- miR-195 CD19+ cells to be able to definitively show this TF is critical for the emergence of the C19+ cell phenotype by demonstrating direct binding to "upregulated" genes cis-regulatory regions in the Ebf1-/- miR-195 CD19+ cells

We appreciate the reviewerʼs suggestion regarding the use of ChIP-seq or related methods to demonstrate direct FOXO1 binding to cis-regulatory regions of B-lineage genes in Ebf1^−/− miR-195 CD19⁺ cells. We agree that such data would provide definitive evidence of FOXO1's direct involvement in promoting the B cell-like transcriptional program. However, due to current technical limitations, including the scarcity of CD19⁺ cells derived from Ebf1^−/− miR-195 transduction and the requirement for large cell numbers in ChIP-seq or CUT&RUN protocols, we were unable to perform these assays in this study. Nevertheless, our current data provide multiple lines of indirect evidence supporting the involvement of FOXO1:

miR-195 transduction leads to reduced phosphorylation and increased accumulation of FOXO1 protein (Fig. 4C).

Overexpression of FOXO1 in Ebf1^−/− HPCs partially recapitulates the miR-195 phenotype (Fig. 4D).

ATAC-seq data show increased chromatin accessibility at known FOXO1 target gene loci (e.g., Pax5, Runx1, Irf8) in miR-195-induced CD19⁺ cells, many of which overlap with FOXO1 motifs(Fig.5)

These observations collectively suggest that FOXO1 activity is functionally important for the emergence of CD19⁺ cells, even though direct binding has not been confirmed. We have added this limitation to the Discussion (lines 531‒537), and we note that future studies using FOXO1 CUT&RUN in this system would be valuable to further define the underlying mechanism.

(1-6) The authors have not shown significant upregulation of expression of other critical B-cell regulatory transcription factors in their Ebf1-/- miR-195 CD19+ cells that could account for the emergence of these cells such as Pax5 or Erg. The legend in Figure 1E suggests for example the change in expression of Pax5 is modest if anything at best as no LogFC or western blot data is presented. 

We thank the reviewer for raising this point. In our microarray analysis (Figure 1D, original Figure 1E), we observed that both Pax5 and Erg mRNA levels were upregulated in Ebf1^−/− cells upon miR-195 transduction. Specifically, Pax5 showed an increase of approximately log₂FC 1.2, and Erg was also consistently elevated across biological replicates. These changes, although modest, were statistically significant and consistent with the upregulation of other B-lineage-associated transcription factors, such as Runx1 and Irf8. We agree that the magnitude of Pax5 upregulation is not as high as typically seen during full B cell commitment, and therefore may not have been immediately apparent in Figure 1D (original Figure 1E). To clarify this point, we have now revised the text in the Results section (lines 170‒174) to highlight the observed changes in Pax5 and Erg expression. We believe that the upregulation of these transcription factors, together with increased FOXO1 activity and changes in chromatin accessibility (Figure 5), contributes to the partial reactivation of the B cell gene regulatory network in the absence of EBF1.

(1-7) Which V(D)J transcripts have been produced? A more detailed analysis other than ddPCR is required to help understand the emergence of this population that can presumably proceed through the preBCR and BCR checkpoints.

We appreciate the reviewerʼs interest in understanding the nature of the V(D)J rearrangements in Ebf1^−/− miR-195 CD19⁺ cells. As noted, our current data rely on droplet digital PCR (ddPCR), which was used to detect rearranged VH-JH segments in the bone marrow of engrafted mice. While this approach does not allow for detailed mapping of specific V, D, or J gene usage, it provides a sensitive and quantitative measure of V(D)J recombination activity. The detection of rearranged VH-JH fragments in miR-195-transduced Ebf1^−/− cells suggests that at least partial recombination of the immunoglobulin heavy chain locus is occurring̶an essential checkpoint for progression past the pro-B cell stage. Given the lack of such rearrangements in control-transduced Ebf1^−/− cells, we interpret this as evidence that miR-195 enables cells to initiate the recombination process. We acknowledge the limitations of ddPCR and agree that a more detailed analysis using VDJ-seq or singlecell RNA-seq would be valuable in determining the diversity and completeness of the V(D)J transcripts produced. This is a direction we intend to pursue in future work. We have added this limitation to the Discussion section (lines 538‒543).

(1-8) The authors reveal that the Foxo1 transduced Ebf1-/- cells (Fig. 4D) do not persist in vitro or be detected via transplant assay (line 256) and therefore does not represent a truly "rescued" B cell, suggesting that CD19+ cells Ebf1-/- miR-195 transduced cells have more B-cell potential. Further characterisation is therefore warranted of this cell population. For instance, can these cells be induced to undergo myeloid differentiation in myeloid cytokine conditions? What other B-lineage transcriptional regulators are expressed in this cell population that could account for VDJ recombination and expression of a B-lineage transcriptional program (see comments 1, 3, and 5) that allow transition through preBCR and BCR checkpoints as well as undergo class switching?

We thank the reviewer for this insightful comment. We agree that the persistence and lineage potential of the CD19⁺ cells emerging from Ebf1^−/− miR-195-transduced progenitors deserve further characterization. Although we were unable to perform additional lineage re-direction assays, our current data provide several lines of evidence suggesting that these cells are stably committed toward the B-lineage:

Gene expression profiling revealed upregulation of multiple B cell transcriptional regulators, including Pax5, Runx1, and Irf8.

ATAC-seq analysis showed increased chromatin accessibility at B cell‒specific loci and enrichment of motifs bound by key B-lineage factors such as FOXO1 and E2A.

The cells express surface IgM and undergo class switch recombination to IgG1 upon stimulation, indicating successful transition through the pre-BCR and BCR checkpoints and acquisition of mature B cell functions.

Importantly, no upregulation of myeloid- or T-lineage genes was detected in the microarray analysis, arguing against multipotency at this stage.We acknowledge that functional tests for lineage plasticity under altered cytokine conditions would provide important insights and plan to address this question in future studies. This limitation has now been noted in the revised Discussion (lines 544‒550).

(1-9) In the original Ebf1-/- miR-195 CD19+ experiments, a wild-type control should be provided for each experiment. 

We appreciate the reviewerʼs suggestion to include wild-type controls in all experiments. While we did not include wild-type samples side-by-side in every assay, we carefully designed our experiments to include biologically appropriate and informative comparisons. For example, in the bone marrow transplantation experiments (Figure 2), Ebf1^−/− cells transduced with empty vector served as negative controls, clearly lacking CD19 expression, V(D)J recombination, IgM surface expression, and class switch capability. This allowed us to specifically assess the gain-of-function effects of miR-195 in the EBF1-deficient background. In several analyses̶such as the ATAC-seq and microarray comparisons̶we did incorporate or refer to existing wild-type datasets (e.g., GSE92434), providing context for the extent of recovery toward a WT-like profile. We agree, however, that including parallel WT controls across all experimental platforms would enhance interpretability.

(1-10) For ATACseq data, a comparison between Ebf1-/- preproB cells and Ebf1-/- miR-195 CD19+ cells should be undertaken.

We thank the reviewer for this important point. As suggested, we have performed a direct comparison of chromatin accessibility between Ebf1_−/− pre-pro-B‒like cells (CD19_-, control transduction) and Ebf1_−/− miR-195‒transduced CD19⁺ cells. This comparison is shown in green in Figure 5B and represents the ATAC-seq peaks differentially accessible between these two populations.  

(1-11) I cannot agree with the authors with some of their statements such as Line 242 - "therefore miR-195 considered to have similar function with EBF1 to some extent" - how can this be the case when miR-195 is a miRNA and EBF1 is a transcription factor with pioneering transcriptional activity? Surely the effects of miR-195 must be secondary.

We thank the reviewer for pointing out the inappropriateness of comparing miR-195 to EBF1 in terms of functional similarity. We agree that miR-195, as a microRNA, operates through post-transcriptional regulation and does not possess the pioneering transcriptional activity characteristic of EBF1. To avoid confusion or overstatement, we have removed the sentence in line 242 ("therefore miR-195 is considered to have similar function with EBF1 to some extent").

(1-12) It is unclear whether this observation is in fact physiological. When the authors analyse a knockout model of miR-195, there is not much of a change in the B-cell phenotype. Their findings may therefore be an artefact of an overexpression system. The authors should comment on this observation in their discussion.  

We thank the reviewer for this important observation. We agree that the mild phenotype observed in our miR-195 knockout mice suggests that miR-195 is not essential for B cell development under steady-state physiological conditions. Accordingly, we do not claim a physiological requirement for miR-195. Rather, our study demonstrates that miR-195 possesses the potential to activate a B-lineage program in the absence of EBF1 when ectopically expressed. This functional potential̶rather than its endogenous necessity̶ is the main focus of our work. We have now clarified this distinction in the revised Discussion section (lines 551‒560), and we emphasize that our findings highlight an alternative regulatory pathway that can be artificially engaged under specific conditions.

(1-13) I recommend the authors check spelling and grammar throughout their manuscript.

We thank the reviewer for the suggestion. In response, we have carefully reviewed the manuscript for spelling, grammar, and clarity. Minor corrections have been made throughout the text to improve readability and ensure consistency. We hope that the revised version addresses any language-related concerns. In addition, the manuscript has been reviewed by professional editing service to improve the language quality.

(1-14) In general, I recommend more comprehensive primary data be presented in the manuscript or supplementary files to add value to their submission.

We thank the reviewer for this helpful suggestion. In response, we have revised the manuscript and supplementary materials to include additional primary data wherever possible. The bar graphs have been updated to include individual data points to show variability and replicate information. Uncropped western blot images are now provided in Supplementary Figure S2. We hope these additions provide greater transparency and value to the manuscript. 

Reviewer #2 (Recommendations for the authors): 

I have a number of suggestions with regard to inclusion of details and controls: 

(2-1) The authors need to provide more details on in vitro differentiation, especially culture times. 

Thank you for your comment. The culture conditions for in vitro differentiation of Ebf1^−/− hematopoietic progenitor cells are described in the Methods section (lines 648‒ 649) under “Culture of lineage-negative (Lin‒) cells from the fetal liver.” As stated, cells were cultured more than 7 days under the specified conditions.

(2-2) In Figure 1E, the authors need to provide information on statistics (FDR or similar). 

I thank the reviewer for the suggestion. In Figure 1D (Original Figure 1E) (the microarray analysis), only two biological replicates were available for each condition (n = 2 per group). Due to this limited sample size, we did not perform statistical testing, as the power would be insufficient to produce reliable p-values or adjusted FDRs. Instead, we focused on genes with consistent and biologically meaningful changes in expression, and presented representative examples based on fold change values.

(2-3) For in vivo experiments (Figure 2) the authors should comment on their use of two different recipient mouse strains despite very low n numbers. As described above, classical mixed BM chimeras would be much more informative. In these experiments, the authors should also show the formation of other lymphoid lineages. This would answer the question of whether miR-195 redirects cells to the B lineage. Most importantly, absolute numbers need to be provided, especially in conjunction with Ebf1 rescue as described above. 

We thank the reviewer for the thoughtful and detailed suggestions regarding our in vivo experiments. Regarding the use of different recipient mouse strains, our initial intention was to perform the transplantations in BRG mice; however, due to facility restrictions and animal husbandry considerations, we had to switch to NOG mice. All in vivo experiments were performed with n = 3 per group, in accordance with ethical guidelines and efforts to minimize animal use while still ensuring reproducibility. With respect to the suggestion of mixed bone marrow chimeras, we agree that this approach can provide valuable information on lineage competitiveness. However, in our system, miR-195 confers only a very limited B cell developmental potential in Ebf1^−/− progenitors. In such a setting, the inclusion of wild-type competitor cells would overwhelmingly dominate the B cell compartment, likely masking any measurable effect of miR-195. Therefore, we opted to assess the gain-of-function potential of miR-195 in a noncompetitive setting. Regarding the assessment of other lymphoid lineages, we focused our analysis on the emergence of B-lineage cells, as the frequency of CD19⁺ cells induced by miR-195 is quite low. Given this low efficiency, we consider it unlikely that miR-195 significantly alters the development of non-B lineages, and thus did not observe substantial lineage diversion effects. Our aim was not to demonstrate lineage redirection, but rather to show that miR-195 can confer partial B cell potential in the absence of EBF1.

Finally, we acknowledge the importance of presenting absolute cell numbers. However, the cell number collected from the mice were so few that we did not get the reliable results, we described it in the manuscript. (lines 498-501)

(2-4) The statistics in Figure 3 are inadequate. No S.D. is provided for WT. How then was normalization performed? Student's T-test cannot be applied to ratios. 

We thank the reviewer for highlighting the need for more appropriate statistical analysis. Due to considerable inter-batch variability in absolute measurements, we normalized the KO values to their paired WT counterparts from the same experimental batch. Specifically, for each replicate, we calculated the KO/WT ratio to control for batch-specific variation. We then applied a one-sample t-test (against a null hypothesis of ratio = 1) to determine statistical significance. We have now revised the figure to show individual ratio values for each replicate and updated the legend and Methods to clearly explain the statistical approach. We hope this addresses the concern and improves the clarity and rigor of the analysis.

(2-5) In Figure 4A, the authors should comment on the strong repression of the Akt3UTR. 

We appreciate the reviewerʼs observation regarding the strong repression observed with the Akt3 3'UTR construct. Indeed, we also noted that luciferase activity was markedly reduced in the presence of the Akt3 3'UTR, even in cells transduced with a control vector. We hypothesize that the Akt3 3'UTR contains strong post-transcriptional regulatory elements̶such as AU-rich elements or binding sites for endogenous miRNAs or RNA-binding proteins̶which may suppress mRNA stability or translation independent of miR-195. Alternatively, the secondary structure or length of the UTR may inherently reduce luciferase expression. We have added this limitation to the Discussion section (lines 561‒569).

(2-6) The Western blot in Figure 4C is of insufficient quality. The authors need to provide unspliced versions of the bands including markers. 

We thank the reviewer for this important comment. In response, we have included the unprocessed, full-length Western blot images corresponding to Figure 4C as Fig. S2. This provides a transparent view of the original data and addresses the concern about image cropping.

(2-7) The ATACseq experiment in Figure 5 is difficult to comprehend. A simpler design including Ebf1 rescue controls would clearly improve this part. 

We thank the reviewer for this valuable feedback. We agree that the original presentation of the ATAC-seq data may have been difficult to interpret. To address this, we have included a clear interpretation of the overlapping regions in the revised figure legend (lines 1018-1022). We hope this improves the clarity of the data and facilitates understanding of the chromatin changes mediated by EBF1 and miR-195.

(2-8) The miR-195 KO mouse lacks validation (RT-PCR, genomic PCR) as well as a clear description of the deleted region and whether miR-497 is affected. In addition, the genetic background and number of backcrosses for the removal of potential off-target effects need to be mentioned. 

We thank the reviewer for this important comment. The miR-195 knockout mouse was generated via CRISPR/Cas9, and Sanger sequencing confirmed a 628 bp deletion on chromosome 11 (GRCm38/mm10 chr11:70,234,425‒70,235,103). This deletion includes the entire miR-497 locus and part of the miR-195 precursor sequence. Although we do not show PCR gel images, the deletion was validated by sequencing, and the results are now clearly described in the revised Methods section (lines 607619). All transgenic mice in this study were backcrossed to the C57BL/6 background for at least eight generations.

(2-9) The manuscript requires extensive editing for language. 

We appreciate the reviewerʼs comment. The manuscript has now been revised and professionally edited for language by a native English-speaking editor. We believe clarity and readability have been significantly improved.

Reviewer #3 (Recommendations for the authors): 

(3-1) What is the expression level of miR-195 after viral overexpression? In Figure 4B, the authors show a 2.5-fold increase, but this appears very low for the experimental system (expression through the MDH1 retroviral construct) and the observed repressive effects (e.g. Figure 4A and B). 

We thank the reviewer for this insightful comment. We agree that the apparent ~2.5fold increase in miR-195 levels (Figure 4B) may seem modest in the context of retroviral overexpression and the associated functional effects. However, due to the high sequence similarity within the miR-15/16/195/497 family, it is technically challenging to measure mature miR-195 levels with complete specificity. The baseline signal observed in control samples likely reflects cross-reactivity with endogenous miRNAs such as miR-497 or miR-16, which share similar seed sequences. Therefore, the reported fold-change may underestimate the true level of ectopic miR-195 expression. Despite this, we observed robust repression of validated targets (e.g., Mapk3, Akt3) in both qPCR and luciferase assays, indicating that functionally effective levels of miR-195 were achieved. We have now clarified this limitation and interpretation in the revised Results sections (lines 332‒335).

(3-2) In alignment with the transparency of the data, I would encourage the authors to display the individual data points for all bar graphs. 

We thank the reviewer for this helpful suggestion. In the revised manuscript, we have updated bar graphs to include individual data points to increase transparency and allow better visualization of data variability. In the ddPCR experiments, we provided the raw data in Fig. S1 for full transparency. In Fig. 1A, we have confirmed miR-195 expression profiles using the deposit data which the reviewer suggested, but miR-195 expression was very lower than we expected. We also performed scRNA-seq using hematopoietic lineage cells in 8-week-old C57BL/6 mice, but we could not get the reproducibility of miR-195 expression profiles. Therefore, we determined that this is an artifact caused by the miR-195 probe used for qPCR, and deleted Fig. 1A.

(3-3) The references appear to be compromised. For example, the authors state that "The Ebf1−/+ mouse was originally generated by R. Grosschedl (39)" (line 297), but this is not the respective paper. Likewise, the knockout mouse was generated "based on the CRISPR/Cas9 system established by C. Gurumurthy (40)" (line 299), but he/she is not involved in the referenced study. 

We thank the reviewer for pointing out the discrepancies in the reference citations. Upon revising the Methods section to integrate it with the main text, the reference numbering became misaligned. We have corrected the reference in the revised manuscript, and we thank the reviewer for bringing this to our attention.

(3-4) Given that the miRNA Taqman assays the authors used here have difficulties to discriminate closely related miRNAs such as e.g. miR-16 (highly expressed in the hematopoietic system) and miR-195, I would suggest that the authors test their qPCR in an appropriate setup, e.g. in their knockout mouse model. In this context, did the authors use another small RNA as a reference for the qPCR analysis? In the methods, only GAPDH is mentioned, but in my opinion, another RNA that uses the same stemloop-based cDNA synthesis protocol would be better suited.

We thank the reviewer for this valuable and technically insightful comment.

As correctly pointed out, TaqMan-based qPCR assays for miRNAs such as miR-195 can show cross-reactivity with closely related family members, particularly miR-16, which is abundantly expressed in hematopoietic cells. Indeed, due to this limitation, we do not treat the qPCR results shown in the original Figures 1A and 4B as definitive quantification of miR-195 expression. Rather, these data are used to provide a suggestion and a rough estimate of overexpression efficiency, while our core functional analyses rely on phenotypic and molecular outcomes such as target gene repression and lineage emergence. With this in mind, although we acknowledge that a small RNA reference based on the same stem-loop cDNA synthesis would offer a more compatible normalization in principle, the inherent variability and lack of absolute specificity in such assays also limits their interpretive value. Therefore, we used GAPDH as a normalization control for consistency with other qPCR analyses in the manuscript. We have now clarified this rationale and limitation in the revised Methods sections (lines 712‒716), and we thank the reviewer again for highlighting this important technical consideration.

(3-5) The Western blot data used to support the hypothesis that FOXO1 phosphorylation is reduced upon overexpression of miR-195 are not convincing. The authors should not crop everything but the band. 

We thank the reviewer for the helpful comment. In response, we have now provided the full-length, uncropped Western blot images corresponding to Figure 4C, including both total FOXO1 and phospho-FOXO1 blots. These images are included in Fig. S2.

Reviewer #1 (Public review):

Summary:

Rahmani et al. utilize the TurboID method to characterize global proteome changes in the worm's nervous system induced by a salt-based associative learning paradigm. Altogether, they uncover 706 proteins tagged by the TurboID method in worms that underwent the memory-inducing protocol. Next, the authors conduct a gene enrichment analysis that implicates specific molecular pathways in salt-associative learning, such as MAP kinase and cAMP-mediated pathways, as well as specific neuronal classes including pharyngeal neurons, and specific sensory neurons, interneurons, and motor neurons. The authors then screen a representative group of hits from the proteome analysis. They find that mutants of candidate genes from the MAP kinase pathway, namely dlk-1 and uev-3, do not affect performance in the learning paradigm. Instead, multiple acetylcholine signaling mutants, as well as a protein-kinase-A mutant, significantly affected performance in the associative memory assay (e.g., acc-1, acc-3, lgc-46, and kin-2). Finally, the authors demonstrate that protein-kinase-A mutants, as well as acetylcholine signaling mutants, do not exhibit a phenotype in a related but distinct conditioning paradigm-aversive salt conditioning-suggesting their effect is specific to appetitive salt conditioning.

Overall, the authors addressed the concerns raised in the previous review round, including the statistics of the chemotaxis experiments and the systems-level analysis of the neuron class expression patterns of their hits. I also appreciate the further attempt to equalize the sample size of the chemotaxis experiments and the transparent reporting of the sample size and statistics in the figure captions and Table S9. The new results from the panneuronal overexpression of the kin-2 gain-of-function allele also contribute to the manuscript. Together, these make the paper more compelling.

Author response:

The following is the authors’ response to the original reviews

Comment from the editors at eLife:

You could consider further strengthening the manuscript with the incorporation of new relevant public datasets for network modeling, but that is entirely your choice.

We thank the editors and reviewers for their thoughtful and positive feedback on our article. We are particularly appreciative of the eLife assessment describing our work as valuable with a convincing methodology.

As suggested, we have expanded our neuron class analysis by incorporating transcriptomic data from young adult animals (Kaletsky et al., 2016 Nature; Ghaddar et al., 2023 Science Advances; St Ange et al., 2024 Cell Genomics) to complement our existing analysis of larval stage 4 (L4) animals.

In addition, we have updated Table S1 to include the outcross status of all strains used in this study, providing clearer information on the genotypes tested. We have also corrected the typographical errors noted by the reviewers. Please note that page and line numbers below refer to the MS Word Document with tracked changes set to ‘simple markup’.

We greatly appreciate the reviewers’ input and hope these revisions further enhance the value and clarity of our study.

Public Reviews:

Reviewer #1 (Public review):

Summary:

Rahmani et al. utilize the TurboID method to characterize global proteome changes in the worm's nervous system induced by a salt-based associative learning paradigm. Altogether, they uncover 706 proteins tagged by the TurboID method in worms that underwent the memory-inducing protocol. Next, the authors conduct a gene enrichment analysis that implicates specific molecular pathways in salt-associative learning, such as MAP kinase and cAMP-mediated pathways, as well as specific neuronal classes including pharyngeal neurons, and specific sensory neurons, interneurons, and motor neurons. The authors then screen a representative group of hits from the proteome analysis. They find that mutants of candidate genes from the MAP kinase pathway, namely dlk-1 and uev-3, do not affect performance in the learning paradigm. Instead, multiple acetylcholine signaling mutants, as well as a protein-kinase-A mutant, significantly affected performance in the associative memory assay (e.g., acc-1, acc-3, lgc-46, and kin-2). Finally, the authors demonstrate that protein-kinase-A mutants, as well as acetylcholine signaling mutants, do not exhibit a phenotype in a related but distinct conditioning paradigm-aversive salt conditioning-suggesting their effect is specific to appetitive salt conditioning.

Overall, the authors addressed the concerns raised in the previous review round, including the statistics of the chemotaxis experiments and the systems-level analysis of the neuron class expression patterns of their hits. I also appreciate the further attempt to equalize the sample size of the chemotaxis experiments and the transparent reporting of the sample size and statistics in the figure captions and Table S9. The new results from the panneuronal overexpression of the kin-2 gain-of-function allele also contribute to the manuscript. Together, these make the paper more compelling. The additional tested hits provide a comprehensive analysis of the main molecular pathways that could have affected learning. However, the revised manuscript includes more information and analysis, raising additional concerns.

Major comments:

As reviewer 4 noted, and as also shown to be relevant for C30G12.6 presented in Figure 6, the backcrossing of the mutants is important, as background mutations may lead to the observed effects. Could the authors add to Table 1, sheet 1, the outcrossing status of the tested mutants?

We appreciate this important point. A column has now been added to Table S1 to indicate the outcross status of all strains used in this study. Additionally, we have updated the table legend on page 77 to clarify how to interpret the information provided in this column.

It is important to validate that the results of the positive hits (where learning was affected), such as acc-1, acc-3, and lgc-46, do not stem from background mutations.

While we agree that confirming the absence of background mutations is important, we have taken alternative steps to address this concern:

- The outcross status of each strain is now clearly indicated in Table S1.

- Observed phenotypes were consistent across multiple biological replicates over extended periods (months, sometimes years), reducing the likelihood that results stem from background mutations.

We believe these measures provide confidence in the validity of our findings.

The fold change in the number of hits for different neurons in the CENGEN-based rank analysis requires a statistical test (discussed on pages 17-19 and summarized in Table S7). Similar to the other gene enrichment analyses presented in the manuscript, the new rank analysis also requires a statistical test. Since the authors extensively elaborate on the results from this analysis, I think a statistical analysis is especially important for its interpretation. For example, if considering the IL1 neurons, which ranked highest, and assuming random groups of genes-each having the same size as those of the ranked neurons (209 genes in total for IL1 in Table S7)-how common would it be to get the calculated fold change of 1.38 or higher? Such bootstrapping analysis is common for enrichment analysis. Perhaps the authors could consult with an institutional expert (Dr. Pawel Skuza, Flinders University) for the statistical aspects of this analysis.

We appreciate the suggestion and agree that statistical testing can be valuable for enrichment analyses. However, implementing additional tests such as bootstrapping is beyond the scope of this study. Our aim was to provide a descriptive overview rather than inferential statistics. To ensure transparency and interpretability, we have:

- Clearly reported fold changes and rankings in Table S7.

- Discussed the limitations of this approach in the manuscript text (page 18, lines 17–20).

- Clearly outlined the methods used to perform this analysis (pages 53–54).

We believe this descriptive analysis provides sufficient context for interpreting these results.

The learning phenotypes from Figure S8, concerning acc-1, acc-3, and lgc-46 mutants, are summarized in a scheme in Figure 4; however, the chemotaxis results are found in the supplemental Figure S8. Perhaps I missed the reasoning, but for transparency, I think the relevant Figure S8 results should be shown together with their summary scheme in Figure 4.

Thank you for this suggestion to improve clarity. We have now moved the panels corresponding to cholinergic signalling components from Figure S8 into Figure 4 on page 21, so that the summary scheme and underlying data are presented together. The figure legends and main text have been updated accordingly to reflect the correct figure numbers.

Reviewer #2 (Public review):

Summary:

In this study by Rahmani in colleagues, the authors sought to define the "learning proteome" for a gustatory associative learning paradigm in C. elegans. Using a cytoplasmic TurboID expressed under the control of a pan-neuronal promoter, the authors labeled proteins during the training portion of the paradigm, followed by proteomics analysis. This approach revealed hundreds of proteins potentially involved in learning, which the authors describe using gene ontology and pathway analysis. The authors performed functional characterization of over two dozen of these genes for their requirement in learning using the same paradigm. They also compared the requirement for these genes across various learning paradigms and found that most hits they characterized appear to be specifically required for the training paradigm used for generating the "learning proteome".

Strengths:

The authors have thoughtfully and transparently designed and reported the results of their study. Controls are carefully thought-out, and hits are ranked as strong and weak. By combining their proteomics with behavioral analysis, the authors also highlight the biological significance of their proteomics findings, and support that even weak hits are meaningful.

The authors display a high degree of statistical rigor, incorporating normality tests into their behavioral data which is beyond the field standard.

The authors include pathway analysis that generates interesting hypotheses about processes involved learning and memory

The authors generally provide thoughtful interpretations for all of their results, both positive and negative, as well as any unexpected outcomes.

Weaknesses:

- The authors use the Cengen single cell-transcriptomic atlas to predict where the proteins in the "learning proteome" are likely to be expressed and use this data to identify neurons that are likely significant to learning, and building hypothetical circuit. This is an excellent idea; however, the Cengen dataset only contains transcriptomic data from juvenile L4 animals, while the authors performed their proteome experiments in Day 1 Adult animals. It is well documented that the C. elegans nervous system transcriptome is significant different between these two stages (Kaletsky et al., 2016, St. Ange et al., 2024), so the authors might be missing important expression data, resulting in inaccurate or incomplete networks. The adult neuronal single-cell atlas data (https://cestaan.princeton.edu/) would be better suited to incorporate into neuronal expression analysis.

Thank you for highlighting this important point. We have now incorporated transcriptomic data from young adult animals to complement the L4-based CeNGEN dataset. Specifically, we integrated data from CeSTAAN (https://cestaan.princeton.edu/, including St. Ange et al., 2024) and WormSeq (https://wormseq.org/, including Ghaddar et al., 2023), as outlined below. Importantly, CeSTAAN and WormSeq provide data for 79 and 104 neuron classes, respectively (compared to 128 from CeNGEN); for this reason, the main analysis focuses on CeNGEN due to its broader coverage, with additional datasets noted in brackets for completeness. This is stated on page 18, lines 15–17 to ensure transparency regarding our rationale.

The main text has been updated to describe these datasets and their integration into our analysis (pages 18–20), and further details on how these resources were used have been added to the Experimental Procedures (pages 53–54).

We also incorporated data from Kaletsky et al. (2016) and St. Ange et al. (2024) into our neuron identity checks for all assigned and unassigned hits (page 16, lines 8–19). This analysis shows that the nervous system is highly represented in our proteome data: 75–87% of assigned hits and 75–83% of all hits correspond to neuron-enriched genes identified by St. Ange et al. and Kaletsky et al.

In addition, we used several transcriptomic databases to confirm that learning regulators identified in this study through TurboID and validation experiments are expressed in the same neuron classes as suggested by CenGEN (page 36).

- The authors offer many interpretations for why mutants in "learning proteome" hits have no detectable phenotype, which is commendable. They are however overlooking another important interpretation, it is possible that these changes to the proteome are important for memory, which is dependent upon translation and protein level changes, and is molecularly distinct from learning. It is well established in the field mutating or knocking down memory regulators in other paradigms will often have no detectable effect on learning. Incorporating this interpretation into the discussion and highlighting it as an area for future exploration would strengthen the manuscript.

Thank you for this suggestion. We have incorporated this interpretation into the Results section (page 31, lines 17–23), specifying the potential role of these proteomic changes in memory encoding and retention, which are molecularly distinct from learning.

- A minor weakness - In the discussion, the authors state that the Lakhina, et al 2015 used RNA-seq to assess memory transcriptome changes. This study used microarray analysis.

This has been corrected on page 38, line 5.

Significance:

The approach used in this study is interesting and has the potential to further our knowledge about the molecular mechanisms of associative behaviors. There have been multiple transcriptomic studies in the worm looking at gene expression changes in the context of behavioral training. This study compliments and extends those studies, by examining how the proteome changes in a different training paradigm. This approach here could be employed for multiple different training paradigms, presenting a new technical advance for the field. This paper would be of interest to the broader field of behavioral and molecular neuroscience. Though it uses an invertebrate system, many findings in the worm regarding learning and memory translate to higher organisms, making this paper of interest and significant to the broader field of behavioral neuroscience.

Reviewer #4 (Public review):

Summary:

In this manuscript, authors used a learning paradigm in C. elegans; when worms were fed in a saltless plate, its chemotaxis to salt is greatly reduced. To identify learning-related proteins, authors employed nervous system-specific transcriptome analysis to compare whole proteins in neurons between high-salt-fed animals and saltless-fed animals. Authors identified "learning-specific proteins" which are observed only after saltless feeding. They categorized these proteins by GO analyses, pathway analyses and expression site analyses, and further stepped forward to test mutants in selected genes identified by the proteome analysis. They find several mutants that are defective or hyper-proficient for learning, including acc-1/3 and lgc-46 acetylcholine receptors, F46H5.3 putative arginine kinase, and kin-2, a cAMP pathway gene. These mutants were not previously reported to have abnormality in the learning paradigm.

Concerns:

Upon revision, authors addressed all concerns of this reviewer, and the results are now presented in a way that facilitates objective evaluation. Authors' conclusions are supported by the results presented, and the strength of the proteomics approach is persuasively demonstrated.

Thank you, we appreciate this positive feedback.

Significance:

(1) Total neural proteome analysis has not been conducted before for learning-induced changes, though transcriptome analysis has been performed for odor learning (Lakhina et al., http://dx.doi.org/10.1016/j.neuron.2014.12.029). This warrants the novelty of this manuscript, because for some genes, protein levels may change even though mRNA levels remain the same. Although in a few reports TurboID has been used in C. elegans, this is the first report of a systematic analysis of tissue-specific differential proteomics.

(2) Authors found five mutants that have abnormality in the salt learning. These genes have not been described to have the abnormality, providing novel knowledge to the readers, especially those who work on C. elegans behavioural plasticity. Especially, involvement of acetylcholine neurotransmission has not been addressed before. Although transgenic rescue experiments have not been performed except kin-2, and the site of action (neurons involved) has not been tested in this manuscript, it will open the venue to further determine the way in which acetylcholine receptors, cAMP pathway etc. influences the learning process.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

The authors stated in their response to reviewers that "referring to a phenotype as both a trend and non-significant may confuse readers, which was originally stated in the manuscript in two locations," and that such sentences were removed. Unfortunately, in the new text (page 28, lines 18-19), the authors write: "uev-3 mutants showed a lower average CI after training compared with wild-type, but this did not reach statistical significance." As stated before, I find such sentences confusing and not interpretable. If the changes are not significant, then the lower average CI is not informative.

Thank you for pointing this out. This has been corrected to improve clarity – we say instead that “trained phenotypes between wild-type and uev-3 mutants were not statistically significant” (page 29, lines 21–22).

In response to reviewers' comments, the authors added more information about the biotinylation efficiency of the experiment, which is also described in the text:

Page 8, line 27: "we found that biotin exposure increased the signal 1.3-fold for non-Tg and 1.7-fold for TurboID C. elegans."

Page 10, line 4: "Quantification of the signal within entire lanes showed a 1.1-fold increase in the 'TurboID, control' lane compared with the 'non-Tg, control' lane, and a 1.9-fold increase in the 'TurboID, trained' lane compared with the 'non-Tg, trained' lane."

Is it common in this field not to show the actual raw quantified numbers? I was expecting either a bar graph or instead that the measured values would appear in the text alongside the fold-change information.

Table S2 (and its table legend on page 77) have been edited to include raw area values.

Figure 5: Typo? - "pan neuronal expression of ..." The allele number is written as 139, but I believe it should be 179, as in the rest of the paper.

The typo has been corrected on page 25.

The results describing the absence of a learning phenotype in backcrossed C30G12.6 are presented in the main figure. If the authors believe this is an important result, I understand keeping it in the main figure; however, I find this uncommon.

Thank you for your comment. We consider the absence of a learning phenotype in backcrossed C30G12.6 to be an important control for interpreting the original findings, which is why we have retained it in the main figure.

Reviewer #4 (Recommendations for the authors):

I noted a few typos.

(1) In Fig 5B, the transgene is depicted kin-2(ce139) but it is probably kin-2(ce179).

The typo has been corrected on page 25.

(2) In text, R97C and ce179 are used interchangeably, but in fact there is no description that they are identical.

We now state the following in the manuscript: “We tested worms with the ce179 mutant allele in kin-2, in which a conserved residue in the inhibitory domain (which normally functions to keep PKA turned off in the absence of cAMP) is mutated to cause an R92C amino acid change – this results in increased PKA activity (Schade et al., 2005).” (page 25, lines 1–3),

(3) p31 line 7, Figure S7 -> Fig S9 C-E

We apologise for this typographical error. This figure number is meant to correspond to salt associative learning assay data (Fig. S8), not salt aversive learning (Fig. S9). Since the data from Fig. S8 was moved to Fig. 4, the figure citation has been changed from Fig. S7 (which was incorrect) to Fig. 4 (page 32, line 17).

(4) p45 line 11, Fig S9 -> Fig S6

The typo has been corrected (page 47, line 12).

Reviewer #2 (Public review):

Summary:

In the manuscript entitled "The PPE2 protein of Mycobacterium tuberculosis is responsible for the development of hyperglycemia and insulin resistance during tuberculosis" the authors identify PPE2, a secretory protein of Mycobacterium tuberculosis, as a modulator of adipose function. They show that PPE2 treatment in mice causes fat loss, immune cell infiltration into adipose, reduced gene expression of PPAR-γ, C/EBP-α, and adiponectin, and glucose intolerance. Overall, the authors link PPE2 with adipose tissue perturbation and insulin resistance following infection with M. tuberculosis. PPE2, a secretory protein of Mycobacterium tuberculosis, is a modulator of adipose function. They show that PPE2 treatment in mice causes fat loss, immune cell infiltration into adipose, reduced gene expression of PPAR-γ, C/EBP-α, and adiponectin, and glucose intolerance. Overall, the authors link PPE2 with adipose tissue perturbation and insulin resistance following infection with M. tuberculosis.

Strengths:

While it is known that M. tuberculosis persists in adipose, the mycobacterial factors contributing to adipose dysfunction are unknown. The study uses multiple mechanisms, including recombinant purified protein, non-pathogenic mycobacterium expressing PPE2, and a clinical strain of M. tuberculosis depleted of PPE2, to show that PPE2 may play an important role in causing fat loss, lipolysis, and insulin resistance following infection. The authors show that PPE2, through unknown mechanisms, decreases gene expression of proteins involved in adipogenesis. Although the mechanisms are unclear, this study advances the field as it is the first to identify a secreted factor (PPE2) from M. tuberculosis to play a role in disrupting adipose tissue.

Weaknesses:

There is a lack of completeness amongst the figures that greatly diminishes the claims and impact of the manuscript. For example, in Figures 2 and 5, the authors measure adipocyte area in H&E-stained adipose tissue to show adipose hypertrophy. However, this was not completed in Figures 3 and 4 despite the authors claiming that treatment with rPPE2 induces adipose hypertrophy. It is unclear why the adipocyte area was not measured in these figures, and having this included would support the author's claim and strengthen the manuscript. The same is true for immune cell infiltration, where the authors say there is increased immune cell infiltration following PPE2 treatment. This is based on H&E staining, but the data supporting this is limited. Although the authors measure CD3+ T cell infiltration in adipose tissue from mice infected with the clinical strain where PPE was depleted, staining was performed in only this experiment. Completing these experiments by showing data to support that PPE2 induces immune cell infiltration would greatly strengthen the manuscript.

The authors state that a Student's t-test was performed to calculate the significance between two samples. However, there is no discussion of what statistical method was used when there were more than 2 groups, which occurs throughout the manuscript, such as in Figure 5, where 4 groups are analyzed. Having the appropriate statistical analysis is important for the impact of the manuscript.

Reviewer #3 (Public review):

Summary:

In this manuscript titled "The PPE protein of Mycobacterium tuberculosis is responsible for the development of hyperglycemia and insulin resistance during tuberculosis", Bisht et al describe that PPE2 protein from Mtb is a key modulator of adipose tissue physiology that contributes to the development of insulin resistance. The authors have used 3T3-L1 preadipocyte cell lines, M. smegmatis overexpression strain, mice model, and genetically modified Mtb deletion strains to demonstrate that PPE promotes persistence in adipose tissue and regulates glucose homeostasis. Using qPCR and RNA-seq experiments, the authors demonstrate that PPE2 regulates the expression of key genes involved in adipogenesis.

Strengths:

Using purified protein, the authors show that PPE2 regulates adipose tissue physiology, and this effect was neutralised in the presence of anti-PPE2. The expression of several adipogenic markers was also reduced in 3TL-1 adipocytes treated with rPPE2 and in mice infected with M. smegmatis strains overexpressing PPE2. Using a mouse model of infection, the authors show that PPE2 contributes to enhanced mycobacterial survival within fat tissues. The authors also show infiltration of immune cells in the fat tissues of mice infected with wild-type and ppe2-complemented strains compared to the ppe2 KO strain. In order to gain a better mechanistic understanding of how PPE2 regulates adipogenesis, the authors employed an RNA-seq approach and identified 191 genes that were significantly differentially expressed in the fat tissues of mice infected with wild-type and ppe2 KO Mtb strains. The differentially expressed genes included transcripts encoding for proteins involved in chemokine/cytokine signalling, ER stress response. The expression of a few of these markers was also validated by qPCR and western blot analysis. Finally, the authors also show that PPE2 promotes lipolysis by reducing phosphodiesterase levels and activating PKA-HSL signalling. The experimental design is overall reasonable, and the methods used are reliable. Overall, the current study did provide some new information on the contribution of PPE2 in regulating adipose tissue physiology.

Weaknesses:

(1) The authors have used several methodologies to show that PPE2 regulates adipose tissue physiology and glucose homeostasis. But the exact mechanism is still not clear.

(2) Mtb encodes several PE/PPE proteins? The authors have used PPE2 for their study. Will secretory PPE2 homologs also regulate similar cellular processes?

(3) How do the authors rule out that the differences observed in the fat tissues of mice infected with wild-type and mutant strains are not associated with reduced bacterial burdens? Is it possible to include another Mtb attenuated strain as a control in mice experiments for few critical experiments?

Author response:

Public Reviews:

Reviewer #1 (Public review):

Summary:

In this manuscript, Bisht et al. investigate the role of PPE2, a Mycobacterium tuberculosis (Mtb) secreted virulence factor, in adipose tissue physiology during tuberculosis (TB) infection. Previous work by this group established the significance of PPE proteins in Mtb virulence and their role in modulating the innate immune response. Here, the authors present compelling evidence that PPE2 regulates host cell adipogenesis and lipolysis, thereby establishing a link to the development of insulin resistance during TB infection. These fundamental findings demonstrate, for the first time, that a bacterial virulence factor is directly involved in the profound body fat loss, or "wasting," which is a long-established clinical symptom of active TB.

Key Strengths:

The confidence in the major findings of this study is significantly strengthened by the authors' comprehensive approach. They judiciously employ multiple experimental systems, including:

(1) Purified PPE2 protein.

(2) A non-pathogenic Mycobacterium strain engineered to express PPE2.

(3) A pathogenic clinical Mtb strain (CDC1551) utilizing a targeted PPE2 deletion mutant.

(4) While the presence of Mtb in adipose tissues in human and animal models is well-documented, this study is groundbreaking in demonstrating that an Mtb virulence-associated factor actively modulates host fatty acid metabolism within the adipose tissue.

We thank the reviewer for his appreciation that in this work we demonstrated for the first time that an Mtb virulent factor is directly linked to TB-associated wasting.

Weakness:

Although the manuscript provides solid evidence associating the presence of PPE2 with transcriptional changes in host fatty acid machinery within the adipose tissue, the underlying mechanistic details remain elusive. A focused, deep mechanistic follow-up study will be essential to fully appreciate the complex biological implications of the findings reported here.

We agree with the reviewer that a deep-focused, mechanistic follow-up study is necessary to further elucidate the complex biological implications of PPE2 actions. However, we believe that we have uncovered at least one of the possible mechanisms by which PPE2 increases lipolysis and circulating free fatty acids during infection by targeting cAMP-PKA-HSL pathway (Figure 7). In future studies we will aim to dissect out the mechanisms by which PPE2 triggers hyperglycaemia and insulin resistance.

Reviewer #2 (Public review):

Summary:

In the manuscript entitled "The PPE2 protein of Mycobacterium tuberculosis is respon,sible for the development of hyperglycemia and insulin resistance during tuberculosis" the authors identify PPE2, a secretory protein of Mycobacterium tuberculosis, as a modulator of adipose function. They show that PPE2 treatment in mice causes fat loss, immune cell infiltration into adipose, reduced gene expression of PPAR-γ, C/EBP-α, and adiponectin, and glucose intolerance. Overall, the authors link PPE2 with adipose tissue perturbation and insulin resistance following infection with M. tuberculosis. PPE2, a secretory protein of Mycobacterium tuberculosis, is a modulator of adipose function. They show that PPE2 treatment in mice causes fat loss, immune cell infiltration into adipose, reduced gene expression of PPAR-γ, C/EBP-α, and adiponectin, and glucose intolerance. Overall, the authors link PPE2 with adipose tissue perturbation and insulin resistance following infection with M. tuberculosis.

Strengths:

While it is known that M. tuberculosis persists in adipose, the mycobacterial factors contributing to adipose dysfunction are unknown. The study uses multiple mechanisms, including recombinant purified protein, non-pathogenic mycobacterium expressing PPE2, and a clinical strain of M. tuberculosis depleted of PPE2, to show that PPE2 may play an important role in causing fat loss, lipolysis, and insulin resistance following infection. The authors show that PPE2, through unknown mechanisms, decreases gene expression of proteins involved in adipogenesis. Although the mechanisms are unclear, this study advances the field as it is the first to identify a secreted factor (PPE2) from M. tuberculosis to play a role in disrupting adipose tissue.

We thank the reviewer for his appreciation of our findings presented in the manuscript.

Weaknesses:

(1) There is a lack of completeness amongst the figures that greatly diminishes the claims and impact of the manuscript. For example, in Figures 2 and 5, the authors measure adipocyte area in H&E-stained adipose tissue to show adipose hypertrophy. However, this was not completed in Figures 3 and 4 despite the authors claiming that treatment with rPPE2 induces adipose hypertrophy. It is unclear why the adipocyte area was not measured in these figures, and having this included would support the author's claim and strengthen the manuscript. The same is true for immune cell infiltration, where the authors say there is increased immune cell infiltration following PPE2 treatment. This is based on H&E staining, but the data supporting this is limited. Although the authors measure CD3+ T cell infiltration in adipose tissue from mice infected with the clinical strain where PPE was depleted, staining was performed in only this experiment. Completing these experiments by showing data to support that PPE2 induces immune cell infiltration would greatly strengthen the manuscript.

As per the suggestion of the esteemed reviewer, in the revised manuscript we will attempt to analyse adipocyte area in both Figures 3 and 4. In the original manuscript, immune cell infiltration analyses (H&E staining and CD3+ staining) was restricted to only M. tuberculosis-mouse infection model, which best reflects the human tuberculosis pathology.  In other experiments involving infection with M. smegmatis expressing PPE2, immune cell infiltration studies will be carried out.

(2) The authors state that a Student's t-test was performed to calculate the significance between two samples. However, there is no discussion of what statistical method was used when there were more than 2 groups, which occurs throughout the manuscript, such as in Figure 5, where 4 groups are analyzed. Having the appropriate statistical analysis is important for the impact of the manuscript.

We agree with the reviewer that we missed to include ANOVA in the statistical analyses. We will include one-way ANOVA analysis where more than two groups are present and mention the statistical methods in the figure legends as well in the text of the revised manuscript.

Reviewer #3 (Public review):

Summary:

In this manuscript titled "The PPE protein of Mycobacterium tuberculosis is responsible for the development of hyperglycemia and insulin resistance during tuberculosis", Bisht et al describe that PPE2 protein from Mtb is a key modulator of adipose tissue physiology that contributes to the development of insulin resistance. The authors have used 3T3-L1 preadipocyte cell lines, M. smegmatis overexpression strain, mice model, and genetically modified Mtb deletion strains to demonstrate that PPE promotes persistence in adipose tissue and regulates glucose homeostasis. Using qPCR and RNA-seq experiments, the authors demonstrate that PPE2 regulates the expression of key genes involved in adipogenesis.

Strengths:

Using purified protein, the authors show that PPE2 regulates adipose tissue physiology, and this effect was neutralised in the presence of anti-PPE2. The expression of several adipogenic markers was also reduced in 3TL-1 adipocytes treated with rPPE2 and in mice infected with M. smegmatis strains overexpressing PPE2. Using a mouse model of infection, the authors show that PPE2 contributes to enhanced mycobacterial survival within fat tissues. The authors also show infiltration of immune cells in the fat tissues of mice infected with wild-type and ppe2-complemented strains compared to the ppe2 KO strain. In order to gain a better mechanistic understanding of how PPE2 regulates adipogenesis, the authors employed an RNA-seq approach and identified 191 genes that were significantly differentially expressed in the fat tissues of mice infected with wild-type and ppe2 KO Mtb strains. The differentially expressed genes included transcripts encoding for proteins involved in chemokine/cytokine signalling, ER stress response. The expression of a few of these markers was also validated by qPCR and western blot analysis. Finally, the authors also show that PPE2 promotes lipolysis by reducing phosphodiesterase levels and activating PKA-HSL signalling. The experimental design is overall reasonable, and the methods used are reliable. Overall, the current study did provide some new information on the contribution of PPE2 in regulating adipose tissue physiology.

We thank the reviewer for encouraging comments about the manuscript.

Weaknesses:

(1) The authors have used several methodologies to show that PPE2 regulates adipose tissue physiology and glucose homeostasis. But the exact mechanism is still not clear.

We have clearly demonstrated that PPE2 inhibit PPAR-γ and C/EBP-α expression to block adipogenic differentiation. Further, we demonstrated a possible mechanism by which PPE2 trigger lipolysis via activation of the ER stress and cAMP/PKA/HSL pathway which is responsible for increasing free fatty acids in circulation (Figure 7) as confirmed by our observation that PPE2KO (ppe2 knock-out) Mtb infected mice had lower NEFA as compared to the those infected with wild-type Mtb (Figure 7F). Crucially, we showed that this mechanism is clinically relevant since NEFA levels in the sera of TB patients were higher as compared to the healthy controls (Figure 7G) confirming presence of dyslipidemia in TB patients which is an established risk factor for insulin resistance (Karpe et al., 2011; Bhattacharya et al., 2007), As increased free fatty acids have been shown to be linked to development of insulin resistance in several studies, this mechanism links PPE2 with the regulation of glucose homeostasis.

(2) Mtb encodes several PE/PPE proteins? The authors have used PPE2 for their study. Will secretory PPE2 homologs also regulate similar cellular processes?

It is known that Mtb encodes several PE/PPE family proteins and some of these have been implicated to play a role in host–pathogen interactions (Mukhopadhyay and Balaji, 2011; Dahiya et al., 2025). However, so far only PPE2 is shown to be present in the circulation (Bisht et al., 2023) which is the main reason we chose it for this study. Presence of PPE2 homologues in the circulation is not known so far.

(3) How do the authors rule out that the differences observed in the fat tissues of mice infected with wild-type and mutant strains are not associated with reduced bacterial burdens? Is it possible to include another Mtb attenuated strain as a control in mice experiments for few critical experiments?

We agree with the reviewer that the differences in bacterial burden can influence host tissue responses.  Precisely for this reason, we did not rely on just one infection model alone. We used a multi-pronged approach to de-couple the effects of PPE2 from the effects of bacterial load, like;

(1) In vitro Model using recombinantly purified PPE2 protein (rPPE2) (Figure 1): In cultured 3T3-L1 adipocytes, purified rPPE2 protein directly inhibited adipogenesis by downregulating important factors like PPAR-g,C/EBP-α and Fatty acid synthase (which play a critical role in triglyceride metabolism) demonstrating a direct effect of PPE2 in the complete absence of infection.

(2) Recombinant Protein Injection (Figure 3): By injecting recombinantly purified PPE2 protein (rPPE2) into mice, we observed similar metabolic perturbations (fat loss, impaired glucose tolerance) in the complete absence of any bacteria, demonstrating that PPE2 can drive these phenotypes independent of bacterial burden. Further study of rescuing of PPE2 action in rPPE2-immunized mice strongly confirm the specific role of PPE2 in establishing hyperglycaemia and insulin resistance (Figure 4).

While the Mtb aerosol model can be questioned for bacterial load effects, it provides crucial in vivo validation that PPE2 function is relevant in the context of mycobacterial infection.

References

Bhattacharya S, Dey D, Roy SS. Molecular mechanism of insulin resistance. J Biosci. 2007 Mar;32(2):405-13. doi: 10.1007/s12038-007-0038-8. PMID: 17435330.

Bisht MK, Pal R, Dahiya P, Naz S, Sanyal P, Nandicoori VK, Ghosh S, Mukhopadhyay S. The PPE2 protein of Mycobacterium tuberculosis is secreted during infection and facilitates mycobacterial survival inside the host. Tuberculosis (Edinb). 2023 Dec;143:102421. doi: 10.1016/j.tube.2023.102421. Epub 2023 Oct 12. PMID: 37879126.

Dahiya P, Bisht MK, Mukhopadhyay S. Role of PE family of proteins in mycobacterial virulence: Potential on anti-TB vaccine and drug design. Int Rev Immunol. 2025; 44(4):213-228. doi: 10.1080/08830185.2025.2455161. Epub 2025 Jan 31. PMID: 39889764.

Karpe F, Dickmann JR, Frayn KN. Fatty acids, obesity, and insulin resistance: time for a reevaluation. Diabetes. 2011 Oct;60(10):2441-9. doi: 10.2337/db11-0425. PMID: 21948998; PMCID: PMC3178283.

Mukhopadhyay S, Balaji KN. The PE and PPE proteins of Mycobacterium tuberculosis. Tuberculosis (Edinb). 2011 Sep;91(5):441-7. doi: 10.1016/j.tube.2011.04.004. Epub 2011 May 6. PMID: 21527209.

English — heterozygous (thorough explanation)

1) What heterozygous means (core idea)

Heterozygous describes a genotype in which an organism has two different alleles for the same gene.

Heterozygous = two different alleles (e.g., Aa)

Each allele comes from a different parent.

2) How heterozygous genotypes work

• Genes come in pairs (alleles)
• In a heterozygous genotype, one allele is different from the other
• Often written as one capital letter and one lowercase letter

Example:

• A = dominant allele
• a = recessive allele
• Aa = heterozygous

3) Trait expression in heterozygous individuals

In simple dominance:

• The dominant allele determines the phenotype
• The recessive allele is present but not expressed

Example:

• Genotype: Aa
• Phenotype: dominant trait

📌 The recessive allele can still be passed to offspring.

4) Heterozygous vs homozygous (important comparison)

| Term | Alleles | Example | Trait shown | | ------------------------ | --------- | ------- | ------------------ | | Heterozygous | Different | Aa | Dominant (usually) | | Homozygous dominant | Same | AA | Dominant | | Homozygous recessive | Same | aa | Recessive |

5) Heterozygous in Punnett squares (Science 10 focus)

Punnett squares show how heterozygous parents pass on alleles.

Example: Aa × Aa

Possible offspring:

• AA
• Aa
• Aa
• aa

Genotype ratio:

• 1 AA : 2 Aa : 1 aa

📌 Half the offspring are heterozygous (Aa).

6) Why heterozygous matters

Heterozygous individuals:

• Increase genetic variation
• Can be carriers of recessive traits
• Help explain why traits may skip generations
• Are important in evolution and population genetics

One-sentence exam summary

Heterozygous means having two different alleles for a gene.

中文 — heterozygous（杂合子 / 杂合） 详细解释

1) 什么是杂合（核心概念）

Heterozygous（杂合）指的是： 同一性状的两个等位基因不相同。

杂合 = 两个不同的等位基因

常见形式：

• Aa

2) 杂合基因型如何表现

• 一个等位基因来自父亲
• 一个来自母亲
• 通常是 一个显性 + 一个隐性

例子：

• Aa → 显性性状表现
• 隐性基因被“隐藏”，但仍可遗传

3) 杂合 vs 纯合（重点对比）

| 类型 | 等位基因 | 示例 | | ---- | ---- | -- | | 杂合 | 不同 | Aa | | 纯合显性 | 相同 | AA | | 纯合隐性 | 相同 | aa |

4) 潘尼特方格中的杂合

父母：Aa × Aa

后代可能为：

• AA（纯合显性）
• Aa（杂合）
• aa（纯合隐性）

比例：1 : 2 : 1

一句话考试版总结

杂合指一个性状的两个等位基因不同。

如果你愿意，我可以把 heterozygous / homozygous / dominant / recessive / Punnett squares 整理成 Science 10 中英对照闪卡或互动练习，直接用于复习或课堂教学。

English — genotype (thorough explanation)

1) What genotype means (core idea)

A genotype is an organism’s genetic makeup for a specific trait — the combination of alleles it has.

Genotype = the alleles an organism carries

Genotypes are usually written as letter pairs, such as:

• AA
• Aa
• aa

These letters represent genes, not physical appearance.

2) Where genotypes come from

• One allele comes from the mother
• One allele comes from the father
• Together, they form the genotype

Genotypes are found on homologous chromosomes at the same gene location (locus).

3) Common genotype types (Science 10 focus)

Homozygous

• Both alleles are the same
• Examples: AA, aa

Heterozygous

• Alleles are different
• Example: Aa

4) Genotype vs phenotype (very important)

| Term | What it means | Example | | ------------- | ---------------- | ---------- | | Genotype | Genetic makeup | Bb | | Phenotype | Observable trait | Brown eyes |

📌 You inherit the genotype, but you observe the phenotype.

5) Genotype in Punnett squares

Punnett squares are used to predict possible genotypes of offspring.

Example: Parents: Aa × Aa

Possible genotypes:

• AA
• Aa
• Aa
• aa

Genotype ratio:

• 1 AA : 2 Aa : 1 aa

6) Why genotype matters

Genotype:

• Determines which traits can appear
• Explains why recessive traits can be hidden
• Helps predict inheritance patterns
• Is the basis of genetics and evolution

One-sentence exam summary

Genotype is the genetic makeup of an organism, represented by its allele combinations.

中文 — genotype（基因型） 详细解释

1) 什么是基因型（核心概念）

基因型（genotype）是指生物体在某一性状上所拥有的等位基因组合。

基因型 = 拥有的基因组合

常见表示方式：

• AA
• Aa
• aa

2) 基因型从哪里来

• 一个等位基因来自母亲
• 一个来自父亲
• 位于同源染色体的相同位置

3) 基因型的类型（考试重点）

纯合（homozygous）

• AA、aa

杂合（heterozygous）

• Aa

4) 基因型 vs 表现型（必考）

| 项目 | 含义 | | --- | ------- | | 基因型 | 基因组合 | | 表现型 | 实际表现的性状 |

📌 基因型决定潜力，表现型是结果。

5) 潘尼特方格中的基因型

父母：Aa × Aa

后代可能的基因型：

• AA（25%）
• Aa（50%）
• aa（25%）

一句话考试版总结

基因型是生物体所携带的等位基因组合。

如果你愿意，我可以把 allele → genotype → phenotype → Punnett square 整理成 Science 10 中英对照速记卡 / 课堂练习 / HTML 互动内容，方便你系统复习。

English — phenotype (thorough explanation)

1) What phenotype means (core idea)

A phenotype is the observable characteristics of an organism—what you can see or measure.

Phenotype = the physical expression of genes

Examples include:

• Eye color
• Height
• Blood type
• Flower color
• Ability to roll the tongue (in simple genetics examples)

2) What determines phenotype

A phenotype is shaped by two factors:

1. Genotype (the genetic makeup)
2. Environment (external conditions)

Phenotype = genotype + environment

📌 This is why people with the same genes can sometimes look different.

3) Phenotype vs genotype (must-know distinction)

| Term | Meaning | Example | | ------------- | --------------------------- | ---------- | | Genotype | The alleles an organism has | Bb | | Phenotype | The trait that appears | Brown eyes |

You inherit the genotype, but you observe the phenotype.

4) Phenotype in Punnett squares (Science 10 focus)

Punnett squares predict possible phenotypes of offspring.

Example:

• B = brown eyes (dominant)
• b = blue eyes (recessive)

Possible genotypes → phenotypes:

• BB → brown eyes
• Bb → brown eyes
• bb → blue eyes

📌 Phenotype ratios often differ from genotype ratios.

5) Environmental effects on phenotype

Even with the same genotype, environment can change phenotype:

• Height → genes + nutrition
• Skin color → genes + sunlight
• Muscle size → genes + exercise

This shows phenotype is not fixed by genes alone.

6) Why phenotype matters

Phenotypes:

• Explain variation among individuals
• Are what natural selection acts on
• Help scientists study inheritance patterns

One-sentence exam summary

Phenotype is the observable traits of an organism resulting from the interaction of genes and environment.

中文 — phenotype（表现型） 详细解释

1) 什么是表现型（核心概念）

表现型（phenotype）是指生物能够被观察到的性状或特征。

表现型 = 基因表现出来的外在结果

例如：

• 眼睛颜色
• 身高
• 血型
• 花的颜色

2) 表现型由什么决定

表现型由两部分共同决定：

1. 基因型（genotype）
2. 环境因素

表现型 = 基因型 + 环境

3) 基因型 vs 表现型（必考）

| 概念 | 含义 | | --- | -------- | | 基因型 | 拥有的等位基因 | | 表现型 | 实际表现出的性状 |

4) 潘尼特方格中的表现型

潘尼特方格用来预测：

• 后代可能出现的表现型
• 各性状出现的概率

5) 环境对表现型的影响

• 营养影响身高
• 阳光影响肤色
• 训练影响肌肉

一句话考试版总结

表现型是基因与环境共同作用下表现出来的性状。

如果你愿意，我可以把 genotype / phenotype / allele / Punnett square 整理成 Science 10 中英对照闪卡或互动练习，方便系统复习。

English — codominance (thorough explanation)

1) What codominance means (core idea)

Codominance is a pattern of inheritance in which both alleles in a heterozygous individual are fully and equally expressed.

Codominance = both alleles show at the same time

Neither allele is dominant or recessive over the other.

2) How codominance looks (key idea)

In codominance:

• You do not get a blend
• You see both traits clearly and separately

📌 This is different from incomplete dominance, where traits blend.

3) Classic examples of codominance (Science 10 favorites)

A) Roan cattle

• Red allele + White allele
• Result: Roan coat with both red hairs and white hairs
• Not pink → red and white are both visible

B) Human blood type (AB)

• Alleles: IA and IB
• Genotype: IAIB
• Phenotype: AB blood type
• Both A and B antigens appear on red blood cells

4) Codominance vs incomplete dominance (very important)

| Feature | Codominance | Incomplete Dominance | | ----------------- | -------------------- | -------------------------- | | Allele expression | Both fully expressed | Blended | | Appearance | Both traits visible | Mixed/intermediate | | Example | AB blood type | Pink flowers (red × white) |

📌 AB blood type = codominance 📌 Pink flowers = incomplete dominance

5) Codominance in Punnett squares

Codominance still uses Punnett squares, but:

• Heterozygous offspring show both traits
• No allele “hides” the other

Example:

• Alleles: R (red), W (white)
• RW → red + white hairs

6) Why codominance matters

Codominance:

• Explains traits that don’t follow simple dominant/recessive rules
• Increases visible genetic variation
• Is important in medical genetics (blood transfusions)

One-sentence exam summary

Codominance occurs when both alleles in a heterozygous individual are fully expressed at the same time.

中文 — codominance（共显性） 详细解释

1) 什么是共显性（核心概念）

共显性（codominance）指的是： 两个不同的等位基因在杂合体中都会完全表现出来。

共显性 = 两个等位基因同时、完整地表现

2) 共显性的表现特点

• 不会混合
• 两种性状同时清楚可见

📌 和不完全显性不同，共显性没有中间型。

3) 常见例子（考试常考）

A) 花牛（roan cattle）

• 红色等位基因 + 白色等位基因
• 结果：红毛和白毛同时存在

B) 人类 AB 血型

• 等位基因：IA 和 IB
• 基因型：IAIB
• 表现型：AB 型血
• A 抗原和 B 抗原同时存在

4) 共显性 vs 不完全显性（重点对比）

| 特点 | 共显性 | 不完全显性 | | -- | ------- | ----- | | 表现 | 两种性状都出现 | 性状混合 | | 结果 | 同时可见 | 中间型 | | 例子 | AB 血型 | 红×白→粉 |

5) 共显性在潘尼特方格中的体现

• 杂合体表现两种性状
• 没有“显性压制隐性”

一句话考试版总结

共显性是指杂合体中两个等位基因同时完全表现的遗传方式。

如果你愿意，我可以把 dominance / incomplete dominance / codominance 整理成 Science 10 中英对照表或互动练习题，非常适合考试快速区分。

English — alleles (thorough explanation)

1) What alleles are (core idea)

Alleles are different versions of the same gene. They control variations of a trait, such as eye color or flower color.

Allele = one version of a gene

Each gene can have two or more alleles, but an individual organism usually carries two alleles per gene (one from each parent).

2) Where alleles are found

• Genes are located on chromosomes
• Alleles sit at the same position (locus) on homologous chromosomes
• One allele comes from the mother
• One allele comes from the father

📌 This is why offspring show traits from both parents.

3) Example of alleles (simple)

Trait: Seed color

• Y = yellow
• y = green

Possible allele combinations:

• YY
• Yy
• yy

These combinations affect the trait that appears.

4) Dominant vs recessive alleles (Science 10 focus)

Dominant allele

• Shown with a capital letter (A)
• Expressed if at least one copy is present

Recessive allele

• Shown with a lowercase letter (a)
• Expressed only if two copies are present

📌 Example:

• Aa → dominant trait shows
• aa → recessive trait shows

5) Alleles, genotype, and phenotype (key relationship)

| Term | Meaning | Example | | --------- | ------------------ | ---------- | | Allele | Version of a gene | A or a | | Genotype | Allele combination | Aa | | Phenotype | Physical trait | Brown eyes |

Alleles determine the genotype, which determines the phenotype.

6) Alleles in Punnett squares

Punnett squares:

• Show how alleles from parents combine
• Predict possible offspring genotypes
• Estimate trait probabilities

📌 Example: Parents: Aa × Aa

• Possible offspring: AA, Aa, Aa, aa

7) Why alleles are important

Alleles:

• Explain variation within a species
• Help predict inheritance patterns
• Are the basis of genetics and evolution
• Allow populations to adapt over time

One-sentence exam summary

Alleles are different versions of the same gene that determine variations in traits.

中文 — alleles（等位基因） 详细解释

1) 什么是等位基因（核心概念）

等位基因（alleles）是指同一基因的不同版本，决定同一性状的不同表现。

等位基因 = 同一基因的不同形式

2) 等位基因在哪里

• 基因位于染色体上
• 等位基因位于同源染色体的相同位置
• 一个来自母亲，一个来自父亲

3) 等位基因举例

性状：豌豆高度

• T = 高
• t = 矮

组合可能是：

• TT
• Tt
• tt

4) 显性与隐性等位基因（必考）

• 显性等位基因：只要有一个就会表现
• 隐性等位基因：必须两个都有才表现

📌 Tt → 显性性状 📌 tt → 隐性性状

5) 等位基因与性状的关系

• 等位基因 → 基因型
• 基因型 → 表现型

一句话考试版总结

等位基因是控制同一性状的不同基因形式。

如果你愿意，我可以把 alleles → genotype → phenotype → Punnett squares 整理成 Science 10 中英对照闪卡或互动练习，直接用于复习或教学。

English — strands (thorough explanation)

1) What “strands” means (core idea)

Strands are long, thin lines or threads of material. In science, the word is often used to describe structures that are stretched out rather than clumped or round.

Strand = a long, thin piece of something

2) “Strands” in biology (Science 10 focus)

A) DNA strands

DNA is made of two strands that twist together to form a double helix.

• Each strand is a long chain of nucleotides
• The two strands are held together by base pairing
• The strands run in opposite directions (antiparallel)

📌 One strand is not enough for stable DNA → two strands are needed.

B) RNA strand

RNA usually has only one strand.

• Single-stranded structure
• Made of nucleotides like DNA
• Used to carry and translate genetic information

📌 This is why RNA is more flexible but less stable than DNA.

C) Protein strands (fibers)

Some proteins form strand-like fibers, such as:

• Muscle proteins
• Collagen fibers
• Keratin in hair and nails

3) “Strands” outside biology (quick examples)

• Hair strands → individual hairs
• Fiber strands → threads in fabric or rope
• Data strands → sequences of information (metaphorical use)

4) Strand vs chain vs helix (common confusion)

| Term | Meaning | | ------------ | ---------------------------- | | Strand | One long, thin line | | Chain | Many units linked together | | Double helix | Two strands twisted together |

📌 In DNA:

• Each strand is a chain
• Two strands form a double helix

5) Why strands matter in genetics

• The order of bases along a strand carries information
• Complementary strands allow accurate copying
• Strand separation is essential for replication and transcription

One-sentence exam summary

Strands are long, thin chains; DNA has two strands, while RNA usually has one.

中文 — strands（链 / 丝状结构） 详细解释

1) “strands”的基本含义

Strands 指的是 细长、线状的结构。

Strand = 一条细长的链或丝

2) 生物学中的 strands（重点）

A) DNA 链

DNA 由 两条链（两条 strand）组成：

• 每条链由核苷酸连接而成
• 两条链通过碱基配对结合
• 共同形成 双螺旋结构

B) RNA 链

RNA 通常是 单链结构：

• 只有一条 strand
• 用于传递和执行遗传信息

C) 蛋白质纤维

某些蛋白质呈丝状结构：

• 肌肉纤维
• 胶原蛋白
• 角蛋白（头发）

3) strand 与相关词的区别

| 英文 | 中文 | 说明 | | ------------ | --- | ------- | | strand | 链 | 一条细长结构 | | chain | 链条 | 多个单位连接 | | double helix | 双螺旋 | 两条链扭在一起 |

一句话考试版总结

DNA 是双链结构，RNA 通常是单链结构。

如果你愿意，我可以把 strand → nucleotide → base pairing → double helix 做成 Science 10 中英对照概念图或互动闪卡，直接用于复习或教学。

English — Sugar in DNA (thorough explanation)

1) What the sugar in DNA is

The sugar found in DNA is called deoxyribose. It is a five-carbon sugar (a pentose) and is one of the three essential parts of a DNA nucleotide.

DNA sugar = deoxyribose

Each DNA nucleotide contains:

1. A phosphate group
2. Deoxyribose sugar
3. A nitrogenous base (A, T, C, or G)

2) Why it’s called deoxyribose

• “Deoxy-” means missing an oxygen
• Deoxyribose has one less oxygen atom than ribose (the sugar in RNA)

📌 This small difference makes DNA:

• More stable
• Better for long-term information storage

3) What the sugar does in DNA (key functions)

A) Forms the backbone

• Deoxyribose links to phosphate groups
• Together they form the sugar–phosphate backbone
• This backbone gives DNA its shape and strength

B) Connects to bases

• Each sugar attaches to one nitrogenous base
• The sequence of bases carries genetic information
• The sugar itself does not code information, but holds it in place

4) How sugars link DNA together

• The sugar of one nucleotide bonds to the phosphate of the next
• This creates a long chain called a polynucleotide
• The bonds are called phosphodiester bonds

Two sugar–phosphate backbones twist together to form the double helix.

5) DNA sugar vs RNA sugar (common exam comparison)

| Feature | DNA | RNA | | ------------------- | ------------------ | ------------------ | | Sugar | Deoxyribose | Ribose | | Oxygen at 2′ carbon | ❌ Missing | ✅ Present | | Stability | More stable | Less stable | | Function | Store genetic info | Help make proteins |

6) Why sugar matters (big picture)

Without the sugar:

• DNA nucleotides could not link
• DNA would fall apart
• Genetic information could not be stored or copied

Sugar = the structural “frame” that holds DNA together

One-sentence exam summary

The sugar in DNA is deoxyribose, which forms the sugar–phosphate backbone and supports the structure of the DNA molecule.

中文 — DNA 中的糖（详细解释）

1) DNA 中的糖是什么

DNA 中的糖叫 脱氧核糖（deoxyribose），是一种五碳糖。

DNA 的糖 = 脱氧核糖

每个 DNA 核苷酸由三部分组成：

1. 磷酸基团
2. 脱氧核糖
3. 含氮碱基（A、T、C、G）

2) 为什么叫“脱氧”核糖

• “脱氧”表示 少一个氧原子
• 脱氧核糖比 RNA 中的核糖 少一个氧

📌 这使 DNA：

• 更稳定
• 适合长期储存遗传信息

3) 糖在 DNA 中的作用（重点）

① 构成骨架

• 脱氧核糖与磷酸交替连接
• 形成 糖—磷酸骨架
• 为 DNA 提供支撑和形状

② 连接碱基

• 每个糖连接一个碱基
• 碱基顺序决定遗传信息
• 糖本身不存信息，但固定信息

4) DNA 是如何连成链的

• 一个核苷酸的糖
• 与下一个核苷酸的磷酸相连
• 形成 磷酸二酯键

两条这样的链相互缠绕，形成 DNA 双螺旋结构。

5) DNA 糖 vs RNA 糖（常考对比）

| 项目 | DNA | RNA | | --- | ------ | ----- | | 糖 | 脱氧核糖 | 核糖 | | 氧原子 | 少一个 | 多一个 | | 稳定性 | 高 | 低 | | 功能 | 储存遗传信息 | 蛋白质合成 |

一句话考试版总结

DNA 中的糖是脱氧核糖，它与磷酸一起形成 DNA 的骨架结构。

如果你需要，我可以把 nucleotide → sugar → phosphate → DNA backbone 做成 中英对照闪卡或可交互 HTML 图解，直接用于 Science 10 复习或教学。

English — algal (thorough explanation)

1) What algal means (core idea)

Algal is an adjective that means related to or caused by algae.

Algal = having to do with algae

It is used to describe things like algal cells, algal growth, or algal blooms.

2) What algae are (quick reminder)

Algae are mostly aquatic, photosynthetic organisms. They can be:

• Microscopic (single-celled)
• Macroscopic (large seaweeds)

Algae are not true plants, but many behave like plants because they:

• Contain chlorophyll
• Perform photosynthesis

3) Common uses of “algal” in science (Science 10 focus)

Algal growth

• Increase in algae due to sunlight and nutrients

Algal bloom

• A rapid increase in algae population
• Often turns water green
• Can reduce oxygen in water and harm animals

Algal cells

• Individual algae cells seen under a microscope

Algal mats

• Thick layers of algae covering water surfaces or rocks

4) Algal blooms — important ecological example

Algal blooms often occur when:

• Nutrients (nitrogen, phosphorus) are high
• Water is warm
• Sunlight is abundant

Effects:

• Block sunlight for other plants
• Reduce dissolved oxygen
• May produce toxins (in some species)

📌 This process is linked to eutrophication.

5) Why algal organisms are important

Algal organisms:

• Are primary producers
• Form the base of many aquatic food chains
• Produce a large amount of Earth’s oxygen
• Support ecosystems like ponds, lakes, and oceans

6) Grammar note

• Algae → noun (plural)
• Alga → noun (singular)
• Algal → adjective

📌 Example:

Algal growth increases in warm, nutrient-rich water.

中文 — algal（藻类的 / 与藻类有关的） 详细解释

1) “algal”的基本含义

Algal 是一个形容词，意思是 “与藻类有关的”。

Algal = 藻类的

2) 藻类是什么（简单回顾）

藻类是大多生活在水中的能进行光合作用的生物，可以是：

• 单细胞（显微藻类）
• 多细胞（大型海藻）

3) “algal”的常见科学用法（考试常见）

• 藻类生长（algal growth）
• 藻华 / 藻类暴发（algal bloom）
• 藻类细胞（algal cells）
• 藻毯（algal mats）

4) 藻华（重点）

藻华通常发生在：

• 养分多
• 温度高
• 光照强

影响：

• 水体缺氧
• 鱼类死亡
• 水质恶化

5) 藻类的重要性

• 是水生生态系统的生产者
• 是食物链的基础
• 产生大量氧气

6) 词性总结（考试加分点）

• alga：单数，藻
• algae：复数，藻类
• algal：形容词，藻类的

一句话考试版总结

Algal means related to algae, especially in aquatic ecosystems. Algal 指与藻类有关的事物。

如果你需要，我可以把 alga / algae / algal 做成 Science 10 中英对照速记卡或易错点练习题，非常适合考试复习。

English — amoebas (thorough explanation)

1) What amoebas are (core idea)

Amoebas are microscopic, single-celled protists that usually live in water or moist environments. They are famous for their constantly changing shape.

Amoeba = one cell that changes shape to move and eat

2) Where amoebas live

Amoebas are commonly found in:

• Ponds and lakes
• Wet soil
• Slow-moving freshwater
• Inside other organisms (some species)

Most amoebas are free-living and harmless, but a few can cause disease.

3) How amoebas move — pseudopodia

Amoebas move using pseudopodia (“false feet”).

• The cell membrane pushes outward
• Cytoplasm flows into the extension
• The cell slowly pulls itself forward

This movement is called amoeboid movement.

4) How amoebas eat (ingestion by phagocytosis)

Amoebas are heterotrophic (they must eat food).

Steps:

1. Amoeba surrounds food with pseudopodia
2. Food is engulfed
3. A food vacuole forms
4. Enzymes digest the food
5. Nutrients enter the cytoplasm
6. Waste is released

This feeding method is called phagocytosis.

5) Important cell structures (Science 10 focus)

| Structure | Function | | ------------------- | -------------------------- | | Pseudopodia | Movement and feeding | | Cell membrane | Controls entry and exit | | Cytoplasm | Site of chemical reactions | | Nucleus | Controls cell activities | | Food vacuole | Digestion | | Contractile vacuole | Pumps out excess water |

6) Water balance (very important)

Because amoebas live in freshwater:

• Water constantly enters the cell by osmosis
• The contractile vacuole removes extra water
• This prevents the cell from bursting

7) How amoebas reproduce

• Reproduce by binary fission
• One cell divides into two identical cells
• This is asexual reproduction

8) Why amoebas are important

• Feed on bacteria → help control populations
• Part of aquatic food webs
• Used in biology to study cell movement and feeding
• Show how one cell can perform all life functions

One-sentence exam summary

Amoebas are single-celled protists that move and eat using pseudopodia.

中文 — amoebas（变形虫） 详细解释

1) 变形虫是什么（核心概念）

变形虫（amoebas）是生活在水或潮湿环境中的单细胞原生生物。 它们最显著的特点是形状不断变化。

变形虫 = 靠改变形状来运动和进食的单细胞生物

2) 变形虫的生活环境

• 池塘
• 湖泊
• 潮湿土壤
• 其他生物体内

大多数变形虫对人类无害。

3) 变形虫如何运动 —— 伪足

变形虫通过伪足运动：

• 细胞向前伸出伪足
• 细胞质流入
• 整个细胞向前移动

这种方式叫 变形运动。

4) 变形虫如何进食（吞噬作用）

变形虫是异养生物，进食过程如下：

1. 伪足包围食物
2. 食物被吞入
3. 形成食物泡
4. 消化酶分解食物
5. 营养进入细胞质
6. 废物排出

这种方式称为 吞噬作用（phagocytosis）。

5) 重要结构（考试重点）

| 结构 | 功能 | | --- | ------- | | 伪足 | 运动、捕食 | | 细胞膜 | 控制物质进出 | | 细胞质 | 生命活动场所 | | 细胞核 | 控制细胞 | | 食物泡 | 消化 | | 伸缩泡 | 排水、防止胀破 |

6) 一句话考试版总结

变形虫是通过伪足运动和进食的单细胞原生生物。

如果你需要，我可以把 Amoeba / Paramecium / Euglena 做成 Science 10 中英对照比较表或互动闪卡，非常适合系统复习与课堂讲解。

English — Protists (thorough explanation)

1) What protists are (core idea)

Protists are a diverse group of mostly microscopic, eukaryotic organisms that do not fit into the plant, animal, or fungi kingdoms.

Protists = mostly single-celled eukaryotes that are not plants, animals, or fungi

Key point for Science 10:

• They have a nucleus and membrane-bound organelles
• Most live in water or moist environments

2) Why protists are grouped together

Protists are grouped not because they are similar, but because they are eukaryotes that don’t belong elsewhere.

They are extremely diverse in:

• Shape
• Size
• Movement
• Nutrition

3) Main types of protists (exam-friendly categories)

A) Animal-like protists (Protozoa)

• Heterotrophic (must ingest food)
• Often move to find food

Examples:

• Amoeba → moves using pseudopods (“false feet”)
• Paramecium → moves using cilia

📌 These protists ingest other organisms.

B) Plant-like protists (Algae)

• Autotrophic (do photosynthesis)
• Contain chlorophyll
• Important producers in aquatic ecosystems

Examples:

• Green algae
• Diatoms
• Kelp (large multicellular algae)

📌 Algae produce oxygen and form the base of many food chains.

C) Fungus-like protists

• Heterotrophic
• Often decomposers
• Absorb nutrients from dead or decaying matter

Examples:

• Slime molds
• Water molds

4) Where protists are found

Protists usually live in:

• Ponds and lakes
• Oceans
• Wet soil
• Inside other organisms

Anywhere there is water, protists can usually thrive.

5) Why protists are important

Protists play major roles in ecosystems:

• Producers (algae) → photosynthesis
• Consumers → feed on bacteria and other protists
• Decomposers → recycle nutrients
• Part of aquatic food webs
• Some cause diseases (e.g., malaria)

Even though they are microscopic, they have huge ecological impact.

6) Protists vs bacteria (common confusion)

| Feature | Protists | Bacteria | | ---------- | ---------- | ----------- | | Cell type | Eukaryotic | Prokaryotic | | Nucleus | ✅ Yes | ❌ No | | Size | Larger | Smaller | | Organelles | Present | Absent |

One-sentence exam summary

Protists are mostly microscopic eukaryotic organisms that live in water and do not belong to the plant, animal, or fungi kingdoms.

中文 — Protists（原生生物） 详细解释

1) 什么是原生生物（核心概念）

原生生物（Protists）是一类大多为单细胞的真核生物，它们既不是植物、也不是动物或真菌。

原生生物 = 不属于植物、动物、真菌的真核生物

关键点：

• 有细胞核
• 多生活在水或潮湿环境

2) 为什么要把它们归为一类

原生生物被归在一起，并不是因为它们相似，而是因为：

• 它们是真核生物
• 又不适合归入其他界

3) 原生生物的三大类型（考试常考）

A) 类动物原生生物（原生动物）

• 异养（需要摄食）
• 通常可以运动

例子：

• 变形虫：用伪足移动和捕食
• 草履虫：用纤毛运动

B) 类植物原生生物（藻类）

• 自养
• 进行光合作用
• 是水生生态系统的重要生产者

C) 类真菌原生生物

• 异养
• 多为分解者
• 从腐烂有机物中吸收养分

4) 原生生物生活在哪里

• 池塘
• 湖泊
• 海洋
• 潮湿土壤
• 其他生物体内

只要有水，就可能发现原生生物。

5) 原生生物的重要性

• 藻类提供氧气
• 是食物链的基础
• 帮助分解和循环养分
• 有些会引起疾病

一句话考试版总结

原生生物是主要生活在水中的单细胞真核生物。

如果你需要，我可以把 Protists / Bacteria / Fungi 做成 Science 10 中英对照对比表或互动闪卡，直接用于考试复习或课堂教学。

English — thrive (thorough explanation)

1) What “thrive” means (core idea)

Thrive means to grow well, stay healthy, and do better than just surviving. When something thrives, it is strong, active, and successful in its environment.

Thrive = grow and do very well

2) Thrive vs survive (important contrast)

These two words are often compared:

• Survive → stay alive, but possibly weak or stressed
• Thrive → grow, reproduce, and function at a high level

📌 Example:

• A plant that barely stays alive in poor soil survives
• A plant that grows tall, produces flowers, and spreads thrives

3) How “thrive” is used in biology (Science 10 focus)

In biology and ecology, thrive means an organism has:

• Enough food
• Suitable temperature
• Enough water
• Proper space
• Few limiting factors

📌 Example sentence:

Fish thrive in clean, oxygen-rich water.

4) Thrive in ecosystems

An organism thrives when:

• It is well adapted to its habitat
• Abiotic factors (light, water, temperature) are ideal
• Biotic factors (food availability, low competition) are favorable

When many organisms thrive, the ecosystem is healthy.

5) Everyday uses of “thrive”

“Thrive” is not only for biology:

• People can thrive in supportive environments
• Businesses can thrive when conditions are good
• Ideas can thrive with encouragement

中文 — thrive（茁壮成长 / 蓬勃发展） 详细解释

1) “thrive”的基本含义

Thrive 指的是 生长良好、状态健康、不只是勉强活着。

Thrive = 茁壮成长、发展得很好

2) thrive 与 survive 的区别（重点）

• Survive（生存）：只是活着，可能状态不好
• Thrive（茁壮成长）：生长旺盛、繁殖良好、状态优秀

📌 例子：

• 条件差的植物只是“活着” → survive
• 条件好的植物长得高、开花结果 → thrive

3) 生物学中的 thrive（考试常见）

在生态学中，生物要“茁壮成长”，需要：

• 足够的食物
• 合适的温度
• 充足的水分
• 合适的空间
• 较少限制因素

📌 例句：

青蛙在湿润的池塘环境中茁壮成长。

4) 生态系统中的 thrive

当生物适应环境、资源充足时：

• 个体会茁壮成长
• 种群数量稳定或增加
• 生态系统保持健康和平衡

一句话考试版总结

To thrive means to grow well and be healthy, not just survive. Thrive 指的是在良好条件下茁壮成长，而不仅仅是生存。

如果你需要，我可以把 thrive / survive / adapt 做成 Science 10 中英对照速记卡或互动闪卡，非常适合考试复习。

English — ponds (thorough explanation)

1) What “ponds” are (core idea)

Ponds are small, shallow bodies of freshwater. They are usually shallower than lakes, so sunlight can reach the bottom, allowing plants to grow throughout much of the pond.

Pond = small, shallow freshwater ecosystem

2) Key characteristics of ponds

• Freshwater (not salty)
• Shallow depth → light reaches the bottom
• Often warmer than lakes
• Can be natural or human-made
• Support rich biodiversity

Because light reaches the bottom, ponds often have many plants.

3) Living things found in ponds

Ponds support many forms of life:

Plants

• Algae
• Duckweed
• Water lilies
• Reeds and cattails

Animals

• Frogs and tadpoles
• Fish (small species)
• Insects (dragonflies, water beetles)
• Snails
• Birds (ducks, herons)

4) Pond food chain (Science 10 focus)

A simple pond food chain:

• Producers → algae, aquatic plants
• Primary consumers → insects, snails, tadpoles
• Secondary consumers → small fish, frogs
• Top predators → larger fish, birds

Energy flows from the Sun → plants → animals.

5) Abiotic (non-living) factors in ponds

Important non-living factors include:

• Sunlight
• Water temperature
• Dissolved oxygen
• Nutrients
• Mud or sediment at the bottom

Changes in these factors affect pond life.

6) Seasonal changes in ponds

Ponds change with the seasons:

• Spring: increased plant growth, breeding season
• Summer: warm water, high biological activity
• Autumn: dying plants add nutrients to the bottom
• Winter: surface may freeze, but life continues below

Shallow ponds may freeze more easily than lakes.

7) Why ponds are important

Ponds:

• Provide habitat for many species
• Support breeding of amphibians
• Help filter water naturally
• Increase local biodiversity

Even small ponds play a big role in ecosystems.

中文 — ponds（池塘） 详细解释

1) “ponds”的基本含义

池塘（ponds）是较小、较浅的淡水水体。 由于水浅，阳光可以照到水底，因此植物可以在池塘各处生长。

池塘 = 小型、浅水的淡水生态系统

2) 池塘的主要特征

• 淡水
• 水浅
• 水温通常比湖泊高
• 可以是天然或人工
• 生物种类丰富

3) 池塘中的生物

植物

• 藻类
• 浮萍
• 睡莲
• 芦苇

动物

• 青蛙和蝌蚪
• 小型鱼类
• 昆虫（蜻蜓幼虫）
• 蜗牛
• 鸟类（鸭子、苍鹭）

4) 池塘中的食物链（考试重点）

简单的池塘食物链：

• 生产者：藻类、水生植物
• 初级消费者：昆虫、蜗牛、蝌蚪
• 次级消费者：小鱼、青蛙
• 顶级捕食者：大鱼、鸟类

能量来源于太阳。

5) 池塘中的非生物因素

• 阳光
• 水温
• 水中溶氧
• 养分
• 底部泥沙

这些因素会影响池塘生态平衡。

6) 池塘的季节变化

• 春季：生物繁殖，植物生长旺盛
• 夏季：水温高，生命活动活跃
• 秋季：植物死亡，营养回到水中
• 冬季：表面结冰，水下生物仍可存活

一句话考试版总结

Ponds are small, shallow freshwater ecosystems that support a wide variety of plants and animals. 池塘是浅水淡水生态系统，支持多样的动植物生存。

如果你需要，我可以把 ponds / lakes / wetlands 做成 Science 10 对比表或互动闪卡，方便系统复习。

English — limbs (thorough explanation)

1) What “limbs” means (core idea)

Limbs are movable body parts that extend from the main body of an animal. They are mainly used for movement, support, and interaction with the environment.

In humans, the limbs are:

• Arms (upper limbs)
• Legs (lower limbs)

Limbs = body extensions used for movement and function

2) Main functions of limbs

Limbs can have different roles depending on the organism:

• Movement: walking, running, swimming, flying
• Support: holding up body weight
• Manipulation: grasping, holding, using tools (hands)
• Feeding: catching or handling food
• Defense: claws, kicks, strikes

3) Types of limbs (with examples)

1) Upper limbs (forelimbs)

• Humans: arms (hands, fingers)
• Animals: front legs, wings (birds), flippers (whales)

2) Lower limbs (hindlimbs)

• Humans: legs (feet, toes)
• Animals: back legs (frogs, horses)

3) Modified limbs Limbs can evolve to serve special purposes:

• Wings → flying (birds, bats)
• Flippers → swimming (seals, dolphins)
• Claws → catching prey
• Hooves → fast running

4) Limbs in vertebrates (Science 10 focus)

Most vertebrates share a similar limb bone structure, even if the limbs look different.

Common bones include:

• One upper bone (e.g., humerus)
• Two lower bones (e.g., radius & ulna)
• Wrist/ankle bones
• Fingers or toes

This similarity shows common ancestry and is evidence of evolution.

5) Limbs vs appendages (quick clarification)

• Limbs: arms, legs, wings, flippers (main movement parts)
• Appendages: a broader term that can include antennae, tails, etc.

All limbs are appendages, but not all appendages are limbs.

中文 — limbs（四肢 / 肢体） 详细解释

1) “limbs”的基本含义

Limbs（肢体、四肢）是指从动物身体主干伸出的、可以活动的部分。

在人类中：

• 上肢：手臂
• 下肢：腿

Limbs = 用来运动和操作的身体部分

2) 肢体的主要功能

不同动物的肢体功能不同，包括：

• 运动：行走、奔跑、游泳、飞行
• 支撑：支撑身体重量
• 操作：抓握、使用工具
• 进食：抓取食物
• 防御：攻击或保护自己

3) 肢体的类型

1) 前肢（上肢）

• 人类：手臂
• 动物：前腿、翅膀、鳍状肢

2) 后肢（下肢）

• 人类：腿
• 动物：后腿

3) 变态肢体（特殊功能）

• 翅膀：飞行
• 鳍肢：游泳
• 爪：捕食
• 蹄：快速奔跑

4) 生物学重点（考试常考）

许多脊椎动物的肢体内部结构相似，即使外形不同。 这说明它们有共同祖先，是进化的证据。

一句话记忆

Limbs are movable body parts used for movement and interaction. 肢体是用于运动和与环境互动的可活动身体部位。

如果你需要，我可以把 limbs / joints / muscles / bones 做成 Science 10 中英对照速记卡或互动闪卡，非常适合考试复习。

English — ingest (thorough explanation)

1) What “ingest” means (core idea)

Ingest means to take food or another substance into the body, usually through the mouth.

In biology, it is the first step of nutrition.

Ingest = take in (eat or swallow)

2) Ingest vs digest vs absorb (very important distinction)

These words are often confused, but they mean different steps:

1. Ingest → taking food into the body
2. Digest → breaking food down into smaller molecules
3. Absorb → moving nutrients into the bloodstream or cells

📌 Example:

• You ingest an apple
• Your stomach and intestines digest it
• Your intestines absorb the nutrients

3) How ingestion happens in animals

• Humans & animals: ingest food through the mouth
• Teeth, tongue, and saliva help prepare food for digestion
• Food then moves to the stomach and intestines

4) Ingest in simple organisms

Some organisms do not have a mouth like humans:

• Amoeba ingests food by engulfing it

• This process is called phagocytosis

• The food is trapped inside a food vacuole

5) Ingest in food chains (Science 10 focus)

• Herbivores ingest plants
• Carnivores ingest animals
• Omnivores ingest both plants and animals

Energy flows through ecosystems because organisms ingest other organisms.

6) “Ingest” in non-biological use

• Humans can ingest medicine, water, or chemicals
• In computing, “ingest data” means taking data into a system

中文 — ingest（摄入 / 吃进） 详细解释

1) “ingest”的基本意思

Ingest 指的是 把食物或物质摄入体内，通常是通过口腔。

在生物学中，它是营养过程的第一步。

Ingest = 吃进 / 摄入

2) ingest、digest、absorb 的区别（重点）

这三个词代表不同阶段：

1. Ingest（摄入）：把食物吃进体内
2. Digest（消化）：把食物分解成小分子
3. Absorb（吸收）：把营养吸收到血液或细胞中

📌 例子：

• 吃苹果 → ingest
• 胃和肠分解苹果 → digest
• 营养进入血液 → absorb

3) 动物如何摄入食物

• 人类和大多数动物通过嘴巴摄入食物
• 牙齿和舌头帮助咀嚼
• 食物进入消化系统继续处理

4) 单细胞生物中的 ingest

一些简单生物（如变形虫）：

• 没有真正的嘴
• 通过包围食物的方式摄入
• 形成食物泡

5) 食物链中的 ingest（考试常考）

• 草食动物摄入植物
• 肉食动物摄入其他动物
• 杂食动物两者都摄入

能量通过“摄入”在生态系统中传递。

一句话记忆

Ingest = take food into the body Ingest = 把食物吃进体内

如果你愿意，我可以把 ingest / digest / absorb 做成 中英对照表或 Science 10 闪卡，非常适合考试快速区分。

English — Photosynthesis (thorough explanation)

1) What photosynthesis is (core idea)

Photosynthesis is the process by which green plants, algae, and some bacteria use light energy to make food (glucose) from carbon dioxide and water.

In simple terms:

Photosynthesis = using sunlight to make sugar

This process is the foundation of almost all life on Earth, because it produces:

• Food (chemical energy)
• Oxygen for respiration

2) The word itself (helpful for exams)

• Photo = light
• Synthesis = putting together

So photosynthesis literally means:

“Putting things together using light.”

3) The photosynthesis equation (must-know)

[ 6CO_2 + 6H_2O + \text{light energy} \rightarrow C_6H_{12}O_6 + 6O_2 ]

Left side (inputs):

• Carbon dioxide (from air)
• Water (from roots)
• Light energy (from the Sun)

Right side (outputs):

• Glucose (food for the plant)
• Oxygen (released into the air)

4) Where photosynthesis happens

Photosynthesis occurs in chloroplasts, which are found mainly in leaf cells.

Inside a chloroplast:

• Thylakoids → where light reactions happen
• Stroma → where sugar is made

Chlorophyll, the green pigment in chloroplasts, absorbs sunlight.

5) Two main stages of photosynthesis

Stage 1: Light-dependent reactions

Location: Thylakoid membranes Needs light: ✅ Yes

What happens:

• Light energy is absorbed by chlorophyll

• Water is split into:

• Oxygen (released)

• Hydrogen (used later)
• Energy carriers (ATP and NADPH) are produced

Key idea: 👉 This stage captures energy from sunlight

Stage 2: Calvin Cycle (light-independent reactions)

Location: Stroma Needs light directly: ❌ No (but depends on Stage 1)

What happens:

• Carbon dioxide is taken from the air
• Energy from Stage 1 is used
• Glucose (sugar) is produced

Key idea: 👉 This stage builds sugar

6) Why photosynthesis is so important

Photosynthesis:

• Provides food for plants (and all food chains)
• Produces oxygen for animals and humans
• Removes carbon dioxide from the atmosphere
• Stores sunlight as chemical energy

Without photosynthesis:

❌ No plants → ❌ no animals → ❌ no humans

7) Factors that affect photosynthesis (exam favorite)

• Light intensity (more light → faster rate, up to a limit)
• Carbon dioxide concentration
• Temperature (enzymes work best in a certain range)
• Water availability

中文 — 光合作用（Photosynthesis） 详细解释

1) 什么是光合作用（核心概念）

光合作用是指绿色植物、藻类和某些细菌利用光能，把二氧化碳和水合成葡萄糖的过程。

一句话记忆：

光合作用 = 用阳光制造食物

光合作用不仅制造食物，还产生氧气，是地球生命的基础。

2) 光合作用这个词怎么理解

• Photo（光）
• Synthesis（合成）

意思是：

利用光把物质合成在一起

3) 光合作用总反应式（必考）

[ 6CO_2 + 6H_2O + 光能 \rightarrow C_6H_{12}O_6 + 6O_2 ]

原料（左边）：

• 二氧化碳（来自空气）
• 水（来自根）
• 光能（来自太阳）

产物（右边）：

• 葡萄糖（植物的食物）
• 氧气（释放到空气中）

4) 光合作用发生在哪里

光合作用发生在叶绿体中，主要位于叶片细胞。

叶绿体内部：

• 类囊体：进行光反应
• 基质：制造葡萄糖

叶绿素负责吸收光能，因此植物呈绿色。

5) 光合作用的两个阶段

第一阶段：光反应

位置： 类囊体膜 是否需要光： ✅ 需要

过程：

• 叶绿素吸收光能
• 水被分解
• 释放氧气
• 产生能量物质（ATP、NADPH）

👉 作用：收集并储存光能

第二阶段：暗反应（卡尔文循环）

位置： 叶绿体基质 是否直接需要光： ❌ 不需要

过程：

• 利用二氧化碳
• 使用第一阶段提供的能量
• 合成葡萄糖

👉 作用：制造糖类

6) 为什么光合作用如此重要

光合作用：

• 为植物制造食物
• 是所有食物链的起点
• 产生氧气供人类和动物呼吸
• 减少空气中的二氧化碳

没有光合作用：

❌ 没有植物 → ❌ 没有动物 → ❌ 没有人类

7) 影响光合作用速率的因素（常考）

• 光照强度
• 二氧化碳浓度
• 温度
• 水分供应

一句话考试版总结

Photosynthesis uses light energy to convert CO₂ and water into glucose and oxygen. 光合作用利用光能把二氧化碳和水转化为葡萄糖和氧气。

如果你需要，我可以把这部分整理成 Science 10 考试速记卡 / 中英对照表 / HTML 互动闪卡，直接接进你现在的学习系统。

English (thorough explanation with images)

1) What homologous means (core idea)

Homologous means similar in structure and corresponding in position, but not necessarily identical.

In biology, the term is most commonly used in “homologous chromosomes.”

2) Homologous chromosomes (main usage)

Homologous chromosomes are a pair of chromosomes—one from the mother, one from the father—that:

• Have the same length and shape
• Carry the same genes in the same order (same loci)
• May carry different versions of those genes (alleles)

Example:

• Gene for eye color is at the same location on both chromosomes
• One allele may be brown, the other blue

👉 Same genes, possibly different alleles.

3) Homologous ≠ identical (very important)

Homologous chromosomes are not identical.

| Term | Meaning | | -------------------------- | --------------------------------------------------------------- | | Homologous chromosomes | Same genes, may have different alleles | | Sister chromatids | Identical copies of the same chromosome (after DNA replication) |

This distinction is a common exam trap.

4) Role of homologous chromosomes in meiosis

Homologous chromosomes are essential for meiosis:

Meiosis I (key stage)

• Homologous chromosomes pair up (called synapsis)
• They may exchange segments through crossing over
• This increases genetic variation

Meiosis II

• Sister chromatids separate (not homologous chromosomes)

5) Crossing over (why homologous matters)

During crossing over:

• Only homologous chromosomes can pair accurately
• Corresponding DNA regions swap pieces
• Results in new allele combinations

This explains why siblings are genetically similar but not identical.

6) One-sentence exam definition

Homologous chromosomes are a matching pair of chromosomes with the same genes in the same order, one inherited from each parent.

中文（配图·深入讲解）

1）同源（homologous）是什么意思

同源指的是： 结构相似、位置对应、功能相关，但不一定完全相同。

在生物学中，最常见的用法是 “同源染色体”。

2）什么是同源染色体

同源染色体是一对染色体：

• 一条来自 母亲
• 一条来自 父亲

它们具有：

• 相同的长度和形态
• 相同的基因排列顺序
• 但可能有 不同的等位基因

👉 基因相同，版本可能不同。

3）同源 ≠ 完全一样（考试重点）

很多同学容易混淆：

| 概念 | 含义 | | ---------- | ------------- | | 同源染色体 | 基因相同，等位基因可能不同 | | 姐妹染色单体 | 完全相同的复制品 |

⚠️ 同源染色体 不是复制品。

4）同源染色体在减数分裂中的作用

减数分裂 I（关键）

• 同源染色体发生 联会
• 可能发生 交叉互换
• 产生 遗传多样性

减数分裂 II

• 分离的是 姐妹染色单体
• 同源染色体已在第一次分裂中分开

5）为什么“同源”对遗传很重要

• 只有同源染色体才能 准确配对
• 才能进行 交叉互换
• 才能产生新的基因组合

这正是人类个体差异的来源之一。

6）一句话考试版总结

同源染色体是指来自父母的一对染色体，基因位置相同但等位基因可能不同。

如果你愿意，我可以：

• 把 homologous vs sister chromatids 做成 对照速记表
• 或整理 减数分裂 I / II 高频考点图
• 或直接生成 中英双语 flashcards / HTML 学习卡

this is always how it feels after you nap

The core beliefs about confucianism is helping others and doing whats right. Confucianism is also about helping and supporting your family. This belief seem to be kept in many Asian cultures. When I lived in Asia I was not taught confucianism but instead just the traits.

This section focuses on how ethical frameworks don't always guarantee moral right, but they are what we should know as tools for understanding certain situations. From this we can see that in complex contexts using many different frameworks is critical especially for technology and social media, because these are not always as clear.

Offering general summaries of ethics does provide a general of the framework itself, but in practice is a different story. John Locke by philosophical beliefs disagreed with slavery, but in practice he had direct involvement in enslavement. Additionally, Thomas Jefferson was a slave owner of over 600 in Monticello and wrote that while slavery was abhorrent, that Black individuals are still inferior to White individuals. Ethics have done a lot of good, but it should be remembered that it has also been used to justify racism, misogyny, ableism, etc. by dehumanizing minorities through violent language (ex. "All men are created equal" -> Black people were not seen as "fully human" from an evolutionary standpoint, therefore excludes them).

The only thing that differentiates winners and losers is their work, not their goals. everyone obviously wants to succeed but because the winners spend more time into taking care of their self improvement and being consistent it got them their win.

I highly agree sometimes goals can distract us from achieving what we want

I agree because you can win, but you need a good system to continue to be successful. Without a good system. the success will not last.

• BBC Future article by Laurie Clarke explores whether core personality traits can be intentionally shifted in a short period, drawing on new research in personality psychology and the Big Five model (openness, conscientiousness, extraversion, agreeableness, neuroticism).
• The author starts from a personal history of high neuroticism (frequent anxiety, panic, rumination) and uses an online Big Five assessment to benchmark herself, finding she scores higher than 85% of people on neuroticism.
• Prompted by her editor, she undertakes a six-week experiment to change aspects of her personality, guided by studies suggesting people can nudge traits through sustained, goal-directed behavior rather than viewing them as fixed.
• The Big Five framework is presented as the most empirically supported way to describe personality, with each broad trait broken into narrower facets (for example, neuroticism into worry and emotional instability; extraversion into sociability and assertiveness).
• The article emphasizes that personality change usually involves repeatedly acting “as if” one already had the desired trait, turning new behaviors into habits that gradually shift trait levels rather than producing instant transformation.
• Research cited in the broader literature suggests people most often aim to reduce neuroticism and increase conscientiousness and extraversion, typically for reasons related to emotional stability, social ease, and life outcomes.
• Clarke’s experiment reflects this pattern, focusing on reducing anxiety in social situations and increasing more outgoing, engaged behavior, while acknowledging that some degree of neuroticism and introversion can be adaptive.
• The piece situates her experience within a wider debate: personality shows early-life continuity and biological roots, but there is growing evidence that deliberate, structured efforts over weeks or months can produce measurable, if modest, trait shifts.

Hacker News Discussion

• Many commenters argue that you do not literally change core traits like extraversion or neuroticism in a few weeks, but you can strongly change behaviors, skills, and how you manage your existing temperament (e.g., better social skills, stress management frameworks, planning to avoid triggers).
• Several users stress that Big Five traits are not “stats to maximize”: high extraversion and agreeableness can encourage conformity; low neuroticism can reduce necessary risk awareness; high conscientiousness can become rigidity; and every trait has trade-offs depending on context.
• A recurring theme is that environments matter: neurotic or introverted people may function poorly in settings demanding constant sociability and standardized behavior, but can thrive where vigilance, self-awareness, or depth of focus are valued.
• One popular top-level comment reframes personality “change” as working with what you already have—building systems (schedules, checklists, deliberate exposure) to get the upsides of your traits while minimizing downsides, rather than trying to become a fundamentally different person.
• Multiple comments question whether six weeks is long enough to judge lasting trait change and note humans are bad at self-assessment; they suggest longer-term follow-up would be needed to know if any shifts persist.
• Discussion also touches on Alcoholics Anonymous and 12-step programs as examples of structured processes that can reorganize aspects of personality and behavior, though some argue these work more like spiritual or behavioral frameworks than true trait rewiring.
• Others push back on the cultural bias that treats extroversion as universally preferable, arguing that introversion and even higher neuroticism can be beneficial in specific historical or personal contexts (for example, noticing danger earlier or planning more cautiously).
• Overall, commenters see value in intentional self-experimentation and habit change, but remain skeptical of strong claims about rapid, deep personality transformation, preferring a nuanced view that integrates biology, context, and long-term practice.

perhaps that is the ultimate benefit we get from algogens: no need to ask someone else a) bc we don't really like asking for help or b) we fear interrupting a colleague. And it probably nicely mimicks busywork too.

This passage introduces the topic of the paper while providing background information and data. It also states what the researchers will be running the experiments on. The authors purpose of the introduction was to introduce the topic and then give background information to the reader and to clearly state what will be researched.

https://web.archive.org/web/20260105192105/https://www.office.com/

#2026/01/05 the day that Office was renamed to 'Microsoft 365 Copilot app' Meanwhile a billion PC owners are holding out on even Windows 11. [[Windows 10 is out of support, but 1 billion PCs still haven’t upgraded]] And MS CEO asks all to pretty please don't talk about slop or Microslop.... [[Microsoft CEO Begs Users to Stop Calling It Slop]]

This passage covers the main topic of the article. This passage stood out to me because it describes the topic of the paper and provides some background information on the processes that cause the issue. It also provides data as to why this article is important.

Dwight D. Eisenhower, Remarks at the National Defense Executive Reserve Conference Online by Gerhard Peters and John T. Woolley, The American Presidency Project https://www.presidency.ucsb.edu/node/233951

Meiosis（减数分裂）— with appropriate images

English (thorough explanation)

1) What meiosis is (core idea)

Meiosis is a special type of cell division that produces gametes (sex cells) with half the number of chromosomes of the parent cell. It is essential for sexual reproduction and genetic diversity.

👉 Meiosis = making sex cells with half the chromosomes

2) Why meiosis is necessary

Meiosis:

• Reduces chromosome number (diploid → haploid)
• Prevents chromosome numbers from doubling every generation
• Creates genetic variation, which supports evolution

Human example:

• Body cells: 46 chromosomes (2n)
• Gametes: 23 chromosomes (n)
• Fertilization restores 46 (n + n → 2n)

3) Two divisions, one DNA replication

DNA is copied once (during interphase), but the cell divides twice:

• Meiosis I – reduction division
• Meiosis II – separation of sister chromatids

4) Meiosis I (reduction division — the key stage)

Meiosis I reduces the chromosome number by half.

Major events:

• Prophase I:

• Homologous chromosomes pair (synapsis)

• Crossing over occurs (DNA exchange)

• Metaphase I:

• Homologous pairs line up at the equator

• Anaphase I:

• Homologous chromosomes separate

• Telophase I:

• Two haploid cells form (chromosomes still duplicated)

5) Meiosis II (similar to mitosis)

Meiosis II separates sister chromatids.

Result:

• Four haploid cells
• All are genetically different

6) Sources of genetic variation

Meiosis creates variation through:

1. Crossing over (Prophase I)
2. Independent assortment of chromosomes
3. Random fertilization

This is why siblings are genetically unique.

7) Meiosis vs mitosis (common exam comparison)

| Feature | Meiosis | Mitosis | | ----------------- | ------------------- | --------------- | | Divisions | 2 | 1 | | Daughter cells | 4 | 2 | | Chromosome number | Half (n) | Same (2n) | | Genetic makeup | Different | Identical | | Purpose | Sexual reproduction | Growth & repair |

中文（详细解释）

1）什么是减数分裂（Meiosis）

减数分裂是一种形成性细胞（精子和卵子）的细胞分裂方式，其结果是染色体数目减半。

👉 减数分裂 = 产生单倍体性细胞

2）为什么需要减数分裂

减数分裂的作用：

• 将染色体数减半
• 防止染色体数代代翻倍
• 产生遗传多样性

人类例子：

• 体细胞：46 条染色体
• 配子：23 条
• 受精后恢复为 46 条

3）一次复制，两次分裂

• DNA 只复制 一次
• 细胞分裂 两次（减 I、减 II）

4）减数分裂 I（最关键）

减数分裂 I 的主要特点是同源染色体分离。

关键过程：

• 前期 I： 同源染色体配对，发生交叉互换
• 中期 I： 同源染色体对排列在中央
• 后期 I： 同源染色体分离
• 末期 I： 形成两个单倍体细胞

5）减数分裂 II

过程类似于有丝分裂：

• 姐妹染色单体分离
• 形成 4 个单倍体细胞
• 每个细胞的遗传信息都不同

6）遗传多样性的来源

• 交叉互换
• 自由组合
• 随机受精

7）减数分裂 vs 有丝分裂（考试重点）

| 项目 | 减数分裂 | 有丝分裂 | | ---- | ---- | ----- | | 分裂次数 | 2 | 1 | | 子细胞数 | 4 | 2 | | 染色体数 | 减半 | 不变 | | 遗传信息 | 不同 | 相同 | | 作用 | 生殖 | 生长、修复 |

一句话总结（双语）

• Meiosis = cell division that produces haploid gametes
• 减数分裂 = 产生单倍体性细胞并增加遗传多样性的分裂方式

如果你愿意，我可以继续帮你做 ✔️ PMAT × 2（减 I / 减 II）速记图 ✔️ Biology 10/11 高频判断题 ✔️ 可打印或交互式示意图

Crossing over（交叉互换）— with appropriate images

English (thorough explanation)

1) What crossing over is (core idea)

Crossing over is the exchange of DNA segments between homologous chromosomes during prophase I of meiosis.

In simple terms: 👉 Crossing over = swapping DNA between matching chromosomes

This process creates new combinations of genes, increasing genetic variation.

2) When and where it happens

• Occurs during Prophase I of Meiosis I
• Happens after homologous chromosomes pair up (synapsis)
• The paired structure is called a tetrad (4 chromatids total)

The visible crossover points are called chiasmata (singular: chiasma).

3) How crossing over works (step-by-step)

1. Homologous chromosomes pair closely along their lengths
2. Non-sister chromatids touch at matching gene regions
3. DNA breaks and rejoins, exchanging equivalent segments
4. Chromosomes separate with new allele combinations

⚠️ Only non-sister chromatids exchange DNA—not sister chromatids.

4) Why crossing over is important

Crossing over:

• Increases genetic diversity among gametes
• Produces offspring that are genetically unique
• Helps proper alignment and separation of homologous chromosomes

Without crossing over:

• Less variation
• Higher risk of chromosome separation errors

5) Crossing over vs independent assortment (don’t confuse)

• Crossing over → recombination within a chromosome pair
• Independent assortment → random separation of different chromosome pairs

Both contribute to genetic diversity, but in different ways.

6) Common exam mistakes

• Saying it occurs in mitosis ❌
• Saying it happens in meiosis II ❌
• Mixing up homologous chromosomes with sister chromatids ❌

Correct statement: ✔️ Crossing over occurs between non-sister chromatids of homologous chromosomes during prophase I.

中文（详细解释）

1）什么是交叉互换（Crossing over）

交叉互换是指在减数分裂 I 的前期（Prophase I）， 同源染色体之间交换 DNA 片段的过程。

一句话： 👉 交叉互换 = 同源染色体之间“交换基因片段”

2）发生的时间和位置

• 发生在减数分裂 I 的前期
• 同源染色体配对后发生
• 四条染色单体形成一个四分体
• 交叉点称为交叉点 / 交叉节（chiasmata）

3）交叉互换如何进行（步骤）

1. 同源染色体紧密配对
2. 非姐妹染色单体在相同基因位置接触
3. DNA 断裂并重新连接
4. 形成新的等位基因组合

⚠️ 发生交换的是非姐妹染色单体，不是姐妹染色单体。

4）交叉互换的重要性

交叉互换可以：

• 增加遗传多样性
• 使每个配子都独一无二
• 帮助同源染色体正确分离

5）交叉互换 vs 自由组合（易混点）

• 交叉互换：同一对染色体内部交换
• 自由组合：不同染色体对随机分配

二者都是遗传多样性的来源。

6）考试常见错误

❌ 发生在有丝分裂 ❌ 发生在减数分裂 II ❌ 姐妹染色单体之间交换

✔️ 正确表述： 交叉互换发生在减数分裂 I 前期的同源染色体非姐妹染色单体之间

一句话总结（双语）

• Crossing over = exchange of DNA between homologous chromosomes
• 交叉互换 = 同源染色体之间的基因交换

如果你需要，我可以继续帮你做 ✔️ Crossing over vs independent assortment 对照表 ✔️ Biology 10/11 常考判断题 ✔️ 可打印或交互式标注示意图

Homologous（同源的／同源染色体）— with appropriate images

English (thorough explanation)

1) What homologous means (core idea)

Homologous means corresponding or matching in structure and function because of shared origin.

In genetics, it most commonly refers to homologous chromosomes:

• A pair of chromosomes, one inherited from the mother and one from the father
• They carry the same genes in the same order, but may have different alleles

In simple terms: 👉 Homologous = same type, same genes, different versions possible

2) Homologous chromosomes explained

A pair of homologous chromosomes:

• Are the same size and shape
• Have the same centromere position
• Carry genes for the same traits
• Can have different alleles (e.g., A vs a)

Example:

• One chromosome may carry brown-eye allele
• The other may carry blue-eye allele

They are homologous because they control the same trait, even if the versions differ.

3) Homologous vs sister chromatids (very common confusion)

| Feature | Homologous Chromosomes | Sister Chromatids | | --------------- | -------------------------------------- | ----------------------------- | | Origin | One from each parent | Copies of the same chromosome | | Genetic content | Same genes, possibly different alleles | Identical DNA | | When paired | Meiosis I | After DNA replication | | Separate during | Meiosis I | Mitosis & Meiosis II |

👉 Homologous ≠ identical

4) Role of homologous chromosomes in meiosis

Homologous chromosomes are crucial in meiosis I:

• They pair up (synapsis)
• Crossing over occurs (exchange of DNA)
• They separate into different cells

This process:

• Reduces chromosome number by half
• Creates genetic variation

5) Homologous structures (broader meaning)

Outside genetics, homologous can also mean:

• Structures with shared evolutionary origin

Examples:

• Human arm & whale flipper
• Bat wing & human hand

They look different but come from the same ancestral structure.

中文（详细解释）

1）什么是Homologous（同源的）

homologous 的意思是： 👉 来源相同、结构和功能相对应

在遗传学中，最常见的是同源染色体：

• 一条来自母亲
• 一条来自父亲
• 控制相同的性状
• 但可能携带不同等位基因

一句话： 👉 同源 = 基因位置相同，但版本可能不同

2）同源染色体是什么

一对同源染色体具有：

• 相同的大小和形状
• 相同的着丝点位置
• 控制相同的性状
• 等位基因可能不同

例子：

• 一条带棕眼基因
• 一条带蓝眼基因

3）同源染色体 vs 姐妹染色单体（考试重点）

| 对比 | 同源染色体 | 姐妹染色单体 | | -------- | ------ | -------------- | | 来源 | 父母各一条 | 同一条染色体复制 | | DNA 是否相同 | 不一定 | 完全相同 | | 出现阶段 | 减数分裂 I | 复制后 | | 分离阶段 | 减数分裂 I | 有丝分裂 / 减数分裂 II |

⚠️ 同源 ≠ 相同

4）同源染色体在减数分裂中的作用

在减数分裂 I中：

• 同源染色体配对
• 发生交叉互换
• 被分到不同子细胞中

这是遗传多样性的关键来源。

5）homologous 的扩展含义

在进化生物学中，homologous 还指：

• 同源结构（起源相同）

例子：

• 人类的手臂
• 鲸鱼的鳍
• 蝙蝠的翅膀

一句话总结（双语）

• Homologous = same type, same genes, different versions
• 同源 = 控制相同性状，但基因版本可能不同

如果你需要，我可以继续帮你做 ✔️ homologous vs analogous vs sister chromatids 对比表 ✔️ Biology 10/11 易错点练习 ✔️ 双语闪卡（定义 + 判断题）

Meiosis（减数分裂）— with appropriate images

English (thorough explanation)

1) What meiosis is (core idea)

Meiosis is a special type of cell division that produces gametes (sex cells) with half the number of chromosomes of the parent cell.

• Occurs in ovaries and testes
• Produces sperm and eggs
• Creates genetic diversity

In simple terms: 👉 Meiosis = making sex cells with half the chromosomes

2) Why meiosis is necessary

Meiosis is essential because:

• It halves the chromosome number
• Prevents chromosome numbers from doubling every generation
• Creates variation, which is important for evolution

Example (humans):

• Body cells: 46 chromosomes
• Gametes: 23 chromosomes
• Fertilization: 23 + 23 = 46

3) Two divisions: Meiosis I and Meiosis II

Meiosis has two rounds of division, but DNA is copied only once (before meiosis begins).

4) Meiosis I (reduction division)

This division reduces chromosome number.

Key events:

• Homologous chromosomes pair up

• Crossing over occurs

• Exchange of DNA between homologous chromosomes

• Homologous chromosomes separate

Result after Meiosis I:

• Two cells
• Each has half the chromosomes, but chromosomes are still duplicated

5) Meiosis II (similar to mitosis)

This division separates sister chromatids.

Key events:

• Chromosomes line up individually
• Sister chromatids separate
• Four cells are produced

Result after Meiosis II:

• Four haploid cells
• All genetically different

6) Sources of genetic variation

Meiosis creates variation through:

1. Crossing over (Prophase I)
2. Independent assortment of chromosomes
3. Random fertilization

This is why siblings (except identical twins) are genetically unique.

7) Meiosis vs mitosis (very common comparison)

| Feature | Meiosis | Mitosis | | ----------------- | ------------------- | --------------- | | Divisions | 2 | 1 | | Daughter cells | 4 | 2 | | Chromosome number | Half | Same | | Genetic makeup | Different | Identical | | Purpose | Sexual reproduction | Growth & repair |

中文（详细解释）

1）什么是减数分裂（Meiosis）

减数分裂是一种形成性细胞（精子和卵细胞）的细胞分裂方式，其结果是染色体数量减半。

一句话： 👉 减数分裂 = 产生染色体数量减半的性细胞

2）为什么需要减数分裂

减数分裂的作用包括：

• 将染色体数量减半
• 保证代代相同的染色体数
• 增加遗传多样性

人类例子：

• 体细胞：46 条染色体
• 性细胞：23 条
• 受精后恢复为 46 条

3）减数分裂的两次分裂

减数分裂包含：

• 减数分裂 I
• 减数分裂 II

DNA 只复制一次，但细胞分裂两次。

4）减数分裂 I（关键阶段）

这是最重要的一次分裂。

主要特点：

• 同源染色体配对
• 发生交叉互换
• 同源染色体分离
• 染色体数减半

5）减数分裂 II

过程类似于有丝分裂。

主要特点：

• 姐妹染色单体分离
• 形成 4 个单倍体细胞
• 每个细胞都不同

6）遗传多样性的来源

• 交叉互换
• 自由组合
• 随机受精

这是后代差异的根本原因。

7）减数分裂 vs 有丝分裂（考试重点）

| 项目 | 减数分裂 | 有丝分裂 | | ---- | ---- | ----- | | 分裂次数 | 2 | 1 | | 子细胞数 | 4 | 2 | | 染色体数 | 减半 | 不变 | | 遗传信息 | 不同 | 相同 | | 作用 | 生殖 | 生长、修复 |

一句话总结（双语）

• Meiosis = cell division for sexual reproduction
• 减数分裂 = 形成性细胞并产生遗传多样性的分裂方式

如果你需要，我可以继续帮你做 ✔️ PMAT × 2（Meiosis I / II）对照表 ✔️ Biology 10/11 常考比较题 ✔️ 交互式“染色体移动”动画讲解

Interphase（间期）— with appropriate images

English (thorough explanation)

1) What interphase is (core idea)

Interphase is the longest stage of the cell cycle, when a cell is not dividing but is actively growing, copying DNA, and preparing for division.

In simple terms: 👉 Interphase = preparation time before cell division

2) The three parts of interphase

Interphase has three sub-phases:

A) G₁ phase (Gap 1) — growth

• Cell grows in size
• Makes proteins and organelles
• Performs normal cell functions

B) S phase (Synthesis) — DNA replication

• DNA is copied
• Each chromosome becomes two sister chromatids
• This step is essential for accurate cell division

C) G₂ phase (Gap 2) — final preparation

• More growth
• Checks DNA for errors
• Produces materials needed for mitosis

3) What the cell looks like during interphase

• DNA is in the form of chromatin (long, thin, uncoiled)
• Chromosomes are not visible under a light microscope
• Nuclear membrane is intact
• Cell appears “normal,” but is very active internally

4) Interphase vs mitosis (common confusion)

| Feature | Interphase | Mitosis | | -------------------- | ---------------- | -------------- | | Purpose | Prepare | Divide nucleus | | DNA | Copied (S phase) | Separated | | Length | Longest | Short | | Chromosomes visible? | ❌ No | ✅ Yes |

⚠️ Interphase is part of the cell cycle but NOT part of mitosis

5) Why interphase is important

Interphase ensures:

• DNA is copied correctly
• Cell is large and ready to divide
• Daughter cells receive complete genetic information

If interphase is rushed or errors aren’t fixed, it can lead to:

• Mutations
• Cell malfunction
• Cancer

中文（详细解释）

1）什么是间期（Interphase）

间期是细胞周期中时间最长的阶段。 在这个阶段，细胞不进行分裂，而是在生长、复制 DNA，并为分裂做准备。

一句话： 👉 间期 = 细胞分裂前的准备阶段

2）间期的三个阶段

间期分为三部分：

（1）G₁ 期（生长阶段）

• 细胞体积增大
• 合成蛋白质和细胞器
• 正常进行生命活动

（2）S 期（合成阶段）

• DNA 复制
• 每条染色体复制成两条姐妹染色单体
• 为分裂做好遗传准备

（3）G₂ 期（准备阶段）

• 继续生长
• 检查 DNA 是否出错
• 合成分裂所需物质

3）间期时细胞的样子

• DNA 以染色质形式存在（细而散）
• 看不到明显染色体
• 核膜完整
• 外观看似“安静”，内部活动非常活跃

4）间期 vs 有丝分裂（考试重点）

| 对比项 | 间期 | 有丝分裂 | | ----- | -- | ---- | | 作用 | 准备 | 核分裂 | | DNA | 复制 | 分离 | | 时间 | 最长 | 较短 | | 染色体可见 | 否 | 是 |

⚠️ 间期属于细胞周期，但不属于有丝分裂

5）为什么间期很重要

间期可以：

• 确保 DNA 准确复制
• 让细胞充分生长
• 保证子细胞获得完整遗传信息

如果间期出错，可能导致：

• 基因突变
• 细胞功能异常
• 癌症

一句话总结（双语）

• Interphase = growth and DNA replication stage of the cell cycle
• 间期 = 细胞生长和 DNA 复制的准备阶段

如果你需要，我可以继续帮你做 ✔️ Biology 10/11 细胞周期速记表 ✔️ interphase vs mitosis 对比练习 ✔️ 标注版流程图或交互式 HTML 图示

Perspectives（视角／观点）— with appropriate images

English (thorough explanation)

1) What “perspectives” means (core idea)

Perspectives are the ways people see, understand, or interpret a situation, issue, or event. They are shaped by a person’s background, experiences, knowledge, culture, values, and goals.

In simple terms: 👉 Perspectives = how different people see the same thing differently

2) Why perspectives differ

People can have different perspectives because of:

• Personal experiences
• Cultural background
• Education and knowledge
• Age and generation
• Role or position (student, teacher, scientist, parent)
• Interests or values

🔹 Example: A new school policy may look helpful to teachers but stressful to students.

3) Perspectives vs opinions (important distinction)

• Perspective → a broader way of seeing shaped over time
• Opinion → a specific belief about one issue

A perspective often influences many opinions, not just one.

4) Perspectives in reading & literature

In literature, perspective often refers to:

• Point of view (first-person, third-person, omniscient)
• Narrator’s bias or limitations
• How much information the reader receives

🔹 Example: The same event feels different when told by a child versus an adult.

5) Perspectives in science & social issues

Understanding multiple perspectives helps people:

• Evaluate ethical issues
• Interpret scientific claims
• Make fair decisions

Example:

• Scientists focus on data
• Communities focus on daily impact
• Governments focus on policy and cost

All are valid perspectives, but they emphasize different concerns.

6) Why considering multiple perspectives matters

• Promotes critical thinking
• Reduces misunderstanding
• Encourages empathy
• Leads to better problem-solving

Ignoring perspectives can result in bias or unfair conclusions.

中文（详细解释）

1）什么是“Perspectives（视角 / 观点）”

Perspectives 指的是人们看待、理解和解释事物的方式。 它受到个人的经历、文化、教育、价值观和身份角色影响。

一句话： 👉 视角 = 看问题的角度

2）为什么会有不同视角

不同的人之所以有不同视角，是因为：

• 生活经历不同
• 文化背景不同
• 知识和教育不同
• 年龄和角色不同
• 价值观和关注点不同

🔹 例子： 考试制度在老师、学生和家长眼中，意义可能完全不同。

3）视角 vs 观点（易混点）

• 视角：长期形成的看问题方式
• 观点：针对某个问题的具体看法

视角往往决定一个人会形成什么观点。

4）文学中的视角

在文学作品中，视角通常指：

• 叙述视角（第一人称、第三人称等）
• 叙述者的立场和局限

不同视角会影响读者对人物和事件的理解。

5）科学与社会议题中的视角

考虑不同视角有助于：

• 理解伦理问题
• 评估科学主张
• 做出更公平的判断

例子：

• 科学家的视角关注数据
• 普通公众关注生活影响
• 政府关注成本与政策

6）为什么要理解多种视角

• 提高批判性思维
• 减少偏见
• 培养同理心
• 改善决策质量

一句话总结（双语）

• Perspectives = different ways of seeing the same situation
• 视角 = 看同一件事的不同角度

如果你需要，我可以继续帮你做 ✔️ ENGL / Socials 常考“多视角分析”模板 ✔️ perspective vs bias vs opinion 对照表 ✔️ 双语闪卡 + 情境练习

Punnett square（潘尼特方格）— with appropriate images

English (thorough explanation)

1) What a Punnett square is (core idea)

A Punnett square is a diagram used to predict the possible genetic outcomes of a cross between two parents.

It shows:

• Which alleles parents can pass on
• All possible allele combinations in the offspring
• The probability of each genotype and phenotype

In simple terms: 👉 Punnett square = a tool to predict inherited traits

2) Why Punnett squares are used

Punnett squares help us:

• Understand inheritance patterns
• Predict offspring traits
• Calculate genetic probabilities
• Visualize dominant and recessive traits

They are widely used in Biology 9–11 and genetics problems.

3) Basic terms you must know

• Gene: a segment of DNA controlling a trait
• Allele: different versions of a gene (e.g., A or a)
• Genotype: genetic makeup (AA, Aa, aa)
• Phenotype: observable trait (tall, short)
• Dominant allele: expressed if present
• Recessive allele: expressed only if both alleles are recessive

4) How to make a simple Punnett square (monohybrid cross)

A monohybrid cross looks at one trait.

Example:

Let A = dominant, a = recessive Both parents are heterozygous (Aa)

Steps:

1. Draw a 2 × 2 grid
2. Put one parent’s alleles across the top (A, a)
3. Put the other parent’s alleles down the side (A, a)
4. Fill in the boxes by combining alleles

Results:

• AA
• Aa
• Aa
• aa

Genotype ratio: 1 AA : 2 Aa : 1 aa

Phenotype ratio: 3 dominant : 1 recessive

5) Dihybrid Punnett square (two traits)

A dihybrid cross tracks two traits at once.

• Uses a 4 × 4 grid
• Each parent produces four types of gametes
• More combinations → more variation

Example traits:

• Seed color
• Seed shape

This is more advanced but follows the same logic.

6) Probability and Punnett squares

Punnett squares show likelihood, not certainty.

Example:

• 25% chance of aa
• 50% chance of Aa
• 25% chance of AA

Each offspring is an independent event, like flipping a coin.

7) Common mistakes (exam tips)

• Mixing up genotype vs phenotype
• Forgetting that dominant ≠ common
• Writing alleles incorrectly (capital vs lowercase)
• Thinking probabilities guarantee outcomes

中文（详细解释）

1）什么是潘尼特方格（Punnett square）

潘尼特方格是一种用来预测父母杂交后代遗传结果的表格图示。

它可以显示：

• 父母可能传递的等位基因
• 后代所有可能的基因组合
• 每种结果出现的概率

一句话： 👉 潘尼特方格 = 预测遗传性状的工具

2）潘尼特方格有什么用

潘尼特方格可以帮助我们：

• 理解遗传规律
• 预测后代性状
• 计算遗传概率
• 区分显性与隐性

是中学遗传学的核心工具。

3）必须掌握的基础术语

• 基因：控制性状的 DNA 片段
• 等位基因：同一基因的不同版本
• 基因型：基因组合（AA、Aa、aa）
• 表现型：外在性状
• 显性：只要有就表现
• 隐性：必须两个都有才表现

4）单因子杂交（最常见）

单因子杂交只研究一个性状。

例子：

A = 显性 a = 隐性 父母都是 Aa

步骤：

1. 画一个 2 × 2 方格
2. 父母的等位基因分别放在上方和左侧
3. 依次填格子

结果：

• AA
• Aa
• Aa
• aa

基因型比例： 1 AA : 2 Aa : 1 aa

表现型比例： 3 显性 : 1 隐性

5）双因子杂交（进阶）

双因子杂交研究两个性状：

• 使用 4 × 4 方格
• 每个亲本产生 4 种配子
• 组合更多，变化更大

6）概率的意义

潘尼特方格显示的是概率，不是保证。

即使概率是 25%， 也不代表四个孩子一定有一个是这种性状。

7）常见考试错误

• 混淆基因型和表现型
• 认为“显性”=“更常见”（错误）
• 大小写不规范
• 把概率当作必然结果

一句话总结（双语）

• Punnett square = a tool to predict genetic outcomes
• 潘尼特方格 = 预测遗传结果的表格工具

如果你愿意，我可以下一步帮你做： ✔️ Biology 10 常考题逐步演示 ✔️ 单因子 vs 双因子对照表 ✔️ 可打印 / 可交互的 Punnett square 模板

Ethical（伦理的／道德的）— with appropriate images

English (thorough explanation)

1) What “ethical” means (core idea)

Ethical describes actions, decisions, or standards that are morally right, fair, and responsible according to accepted principles of right and wrong.

In simple terms: 👉 Ethical = doing what is right, not just what is legal or convenient

2) Ethics vs. morals (common confusion)

• Ethics → formal rules, principles, or codes (often set by professions or societies)
• Morals → personal beliefs about right and wrong

Example:

• A doctor’s ethics come from professional guidelines
• A person’s morals come from upbringing or beliefs

3) What makes an action ethical

Ethical actions usually involve:

• Fairness (no unjust advantage or harm)
• Respect (for people, rights, and dignity)
• Responsibility (considering consequences)
• Honesty (truthfulness and transparency)
• Care / non-harm (avoiding unnecessary harm)

4) Ethical decision-making (how people judge actions)

When deciding if something is ethical, people often ask:

• Who might be helped or harmed?
• Are people informed and consenting?
• Is it fair to everyone involved?
• Would it still seem right if everyone did this?

5) Ethics in science & medicine (very common in exams)

Ethics is crucial when decisions affect others’ lives.

Examples:

• Medical ethics: patient consent, privacy, end-of-life care
• Scientific research ethics: no falsifying data, protecting participants
• Genetics ethics: DNA testing, gene editing, cloning

6) Ethical vs. legal (important distinction)

• Legal → allowed by law
• Ethical → morally right

Something can be:

• Legal but unethical
• Illegal but ethically justified (in rare cases)

中文（详细解释）

1）什么是“伦理的 / 道德的（Ethical）”

ethical 指的是：行为、决定或规则符合道德原则，是公平、负责、尊重他人的。

一句话： 👉 伦理的 = 做正确的事，而不只是合法的事

2）Ethics 与 Morals 的区别（常考）

• Ethics（伦理）：社会或职业制定的规则与标准
• Morals（道德）：个人内心的对错判断

例子：

• 医生遵守的是职业伦理
• 个人遵循的是道德信念

3）什么样的行为是伦理的

通常包括：

• 公平
• 尊重他人权利与尊严
• 承担后果
• 诚实
• 不伤害他人

4）伦理判断的常见问题

判断是否符合伦理时，常问：

• 是否会对他人造成伤害或利益？
• 是否取得了知情同意？
• 是否对所有人公平？
• 如果大家都这么做，会怎样？

5）科学与医学中的伦理

伦理在涉及生命和权利时尤为重要。

例子：

• 医学伦理：病人隐私、知情同意
• 科研伦理：数据真实、保护受试者
• 基因伦理：基因检测、基因编辑

6）伦理与法律的区别

• 合法 ≠ 伦理
• 伦理关注的是“应不应该”，而不只是“可不可以”

一句话总结（双语）

• Ethical = morally right and responsible
• 伦理的 = 符合道德、公平与责任的

如果你需要，我可以继续帮你做 ✔️ ethics vs morals vs law 对照表 ✔️ Biology / Science 10 常考伦理案例 ✔️ 双语闪卡（定义＋情境判断）

DNA（脱氧核糖核酸）— with appropriate images

English (thorough explanation)

1) What DNA is (core idea)

DNA (deoxyribonucleic acid) is the molecule that stores genetic information in almost all living organisms. It contains the instructions that tell cells how to grow, function, and reproduce.

In short: 👉 DNA = the biological instruction manual of life

2) DNA’s structure (what it looks like)

DNA has a double-helix shape—like a twisted ladder.

• Sides of the ladder: sugar–phosphate backbone
• Rungs of the ladder: pairs of nitrogenous bases

Each DNA molecule is made of many nucleotides, and each nucleotide has:

• a phosphate group
• a deoxyribose sugar
• a nitrogenous base

3) The four DNA bases & complementary pairing

DNA uses four bases:

• A = Adenine
• T = Thymine
• C = Cytosine
• G = Guanine

Complementary base pairing rules:

• A pairs with T
• C pairs with G

These pairs are held together by hydrogen bonds, which keep the structure stable but allow it to unzip when needed.

4) How DNA stores information

The sequence of bases (A, T, C, G) stores information—similar to letters forming words.

Example:

• ATGCCGTA…

Different sequences → different genes → different traits (e.g., eye color, enzymes, height potential)

5) DNA replication (copying DNA)

Before a cell divides:

1. The DNA double helix unzips
2. Each strand acts as a template
3. New complementary bases are added
4. Two identical DNA molecules are formed

This ensures genetic continuity from cell to cell.

6) DNA → traits (gene expression)

DNA itself doesn’t build structures directly. Instead:

• DNA → RNA (transcription)
• RNA → protein (translation)

Proteins then:

• Build cell structures
• Control chemical reactions
• Determine observable traits

7) Why DNA is important

DNA:

• Explains inheritance
• Allows variation and evolution
• Is used in medicine, forensics, and biotechnology

中文（详细解释）

1）什么是 DNA（核心概念）

DNA（脱氧核糖核酸）是储存遗传信息的分子，几乎存在于所有生物体中。 它包含指导细胞生长、运作和繁殖的全部信息。

一句话： 👉 DNA = 生命的说明书

2）DNA 的结构（长什么样）

DNA 呈现为双螺旋结构，就像一把扭转的梯子。

• 梯子的两边：糖–磷酸骨架
• 梯子的横档：碱基对

DNA 由大量核苷酸组成，每个核苷酸包括：

• 磷酸
• 脱氧核糖
• 含氮碱基

3）DNA 的四种碱基与互补配对

DNA 只有四种碱基：

• A（腺嘌呤）
• T（胸腺嘧啶）
• C（胞嘧啶）
• G（鸟嘌呤）

互补配对规则：

• A ↔ T
• C ↔ G

碱基之间通过氢键连接，既稳定又可分离。

4）DNA 如何储存信息

DNA 的信息由碱基排列顺序决定。

不同排列 → 不同基因 → 不同性状 （如外貌、代谢能力、身高潜力）

5）DNA 复制（细胞分裂前）

DNA 复制过程：

1. 双螺旋解开
2. 每条旧链作为模板
3. 按互补原则合成新链
4. 形成两条完全相同的 DNA

6）DNA 如何决定性状

DNA 本身不“工作”，而是通过：

• 转录：DNA → RNA
• 翻译：RNA → 蛋白质

蛋白质负责：

• 构建身体结构
• 催化反应
• 表现性状

7）DNA 为什么重要

DNA：

• 解释遗传现象
• 促进进化
• 应用于医学、法医学、生物技术

一句话总结（双语）

• DNA = the molecule that carries genetic information
• DNA = 储存并传递遗传信息的分子

如果你需要，我可以继续帮你做 ✔️ DNA → RNA → Protein 流程图 ✔️ Biology 10 / 11 考试版关键词卡 ✔️ 双语 Q/A 闪卡或交互式 HTML 图示

Organism（生物体）— with appropriate images

English (thorough explanation)

1) What “organism” means (core definition)

An organism is any individual living thing. It can be very small (like a bacterium) or very large (like a tree or a whale), but it must be able to carry out life processes on its own.

In simple terms: 👉 Organism = one living individual

2) What makes something an organism (characteristics of life)

To be considered an organism, it must show most or all of these traits:

• Made of one or more cells
• Uses energy (metabolism)
• Grows and develops
• Responds to its environment
• Maintains internal balance (homeostasis)
• Reproduces (on its own or as a species)

If something cannot perform life functions independently, it is not an organism.

3) Types of organisms

A) Unicellular organisms (one cell)

• Bacteria
• Amoeba
• Yeast

One cell performs all life functions.

B) Multicellular organisms (many cells)

• Animals
• Plants
• Most fungi

Different cells specialize, but together they form one organism.

4) Levels of organization (important concept)

In multicellular organisms, structure is organized as:

Cells → Tissues → Organs → Organ systems → Organism

🔹 Example (human):

• Muscle cell → muscle tissue → heart → circulatory system → human organism

The organism is the highest living level that functions as a complete individual.

5) Organism vs population vs species (common confusion)

• Organism → one individual (one frog)
• Population → group of the same species in one area (all frogs in a pond)
• Species → all organisms that can reproduce with each other

6) Why the concept of organism matters

• Biology studies life one organism at a time
• Health and survival depend on how an organism interacts with its habitat
• Evolution acts on populations, but selection happens to organisms

中文（详细解释）

1）什么是“生物体（Organism）”

生物体指的是单个、完整的生命个体。 它可以非常微小（如细菌），也可以非常巨大（如树或鲸鱼），但它必须能独立完成生命活动。

一句话： 👉 生物体 = 一个完整的生命个体

2）生物体必须具备的特征

一个生物体通常具有以下生命特征：

• 由一个或多个细胞构成
• 需要能量
• 能生长和发育
• 能对环境作出反应
• 能维持体内稳定（内稳态）
• 具有繁殖能力（个体或种群层面）

如果不能独立进行生命活动，就不算生物体。

3）生物体的类型

（1）单细胞生物

• 细菌
• 变形虫
• 酵母

一个细胞就能完成全部生命功能。

（2）多细胞生物

• 动物
• 植物
• 多数真菌

不同细胞分工合作，组成一个生物体。

4）结构层次（考试重点）

多细胞生物的结构层次为：

细胞 → 组织 → 器官 → 器官系统 → 生物体

🔹 人类例子： 肌肉细胞 → 肌肉组织 → 心脏 → 循环系统 → 人（生物体）

5）常见易混概念对比

• 生物体：一个个体（一只青蛙）
• 种群：同一区域的同种生物（一池塘青蛙）
• 物种：能相互繁殖的一类生物

6）为什么“生物体”很重要

• 生物学研究的基本单位
• 生物体与栖息地相互作用
• 自然选择直接作用于生物体

一句话总结（双语）

• Organism = an individual living thing
• 生物体 = 独立存在并能进行生命活动的个体

如果你愿意，我可以继续帮你做 ✔️ Biology 10 关键词对照表 ✔️ organism vs cell vs ecosystem 对比图 ✔️ 双语闪卡（定义 / 例子 / 易错点）

Stumbling（绊倒／磕磕绊绊）— with appropriate images

English (thorough explanation)

1) Literal meaning (physical)

Stumbling literally means losing balance while walking—often because your foot hits an obstacle (a rock, step, root), causing you to almost fall or take awkward steps.

• Example: He stumbled on the uneven pavement.

2) Figurative meaning (very common)

Figuratively, stumbling means having difficulty or making mistakes while trying to do something.

• Stumbling over words → speaking hesitantly or making verbal mistakes

• Stumbling through a task → progressing with errors or uncertainty

• Stumbling block → an obstacle that prevents progress

• Example: She stumbled at first, but improved with practice.

3) Grammar & forms

• Verb: stumble / stumbled / stumbling
• Noun: stumble (a mistake or misstep)
• Phrase: stumble upon → find something by accident

Examples:

• I stumbled upon an old photo. (unexpected discovery)
• The plan hit a major stumbling block.

4) Tone and nuance

• Usually mild and human, not harsh
• Often implies temporary difficulty, not failure
• Suggests learning, adjustment, or growth

Compare:

• Fail → final, strong
• Stumble → momentary, recoverable

5) Common collocations

• stumble over words / a step
• stumble through a presentation
• stumble upon an idea
• a stumbling block to success

中文（详细解释）

1）字面意思（身体动作）

stumbling 的本意是走路时被绊到、失去平衡，可能差点摔倒，但不一定真的摔倒。

• 例句：他在不平的路面上绊了一下。

2）引申意思（非常常见）

在比喻意义上，stumbling 指： 👉 做事不顺、说话卡壳、遇到困难或犯小错

常见用法：

• stumble over words → 说话结巴、卡壳

• stumble through something → 磕磕绊绊地完成

• stumbling block → 阻碍、绊脚石

• 例句：一开始他有点不顺，但慢慢就好了。

3）词形变化

• 动词：stumble / stumbled / stumbling
• 名词：stumble（失误）
• 短语：stumble upon → 偶然发现

例子：

• 我偶然发现了一张老照片。
• 这是成功路上的一个绊脚石。

4）语气与含义

• 语气 温和、人性化
• 强调 暂时的困难
• 常暗示 还能恢复、还能进步

对比：

• fail（失败） → 结果性、严重
• stumble（绊了一下） → 过程性、可调整

5）一句话总结（双语）

• Stumbling = temporary difficulty, not total failure
• stumbling = 一时不顺，而不是彻底失败

如果你愿意，我可以再补充 ✔️ ENGL/考试常见搭配表 ✔️ “stumble vs fail vs struggle” 对比 ✔️ 课堂用情境句子练习

Habitat（栖息地）— with appropriate images

English (thorough explanation)

1) What “habitat” means (core definition)

A habitat is the natural place where an organism lives. It provides everything the organism needs to survive, grow, and reproduce, including:

• Food
• Water
• Shelter
• Space
• Suitable conditions (temperature, light, moisture)

In short: Habitat = an organism’s home in nature.

2) What makes up a habitat

A habitat includes both living (biotic) and non-living (abiotic) factors.

• Biotic factors: plants, animals, fungi, bacteria
• Abiotic factors: sunlight, temperature, water, soil, air, nutrients

🔹 Example: A pond habitat includes algae and insects (biotic) and water depth, oxygen level, and sunlight (abiotic).

3) Habitat vs. niche (important distinction)

• Habitat: Where an organism lives
• Niche: How it lives (its role, diet, interactions)

🔹 Example:

• Frog’s habitat → pond
• Frog’s niche → insect eater, prey for birds, part of the food web

Many species can share a habitat, but each has a different niche.

4) Types of habitats (common categories)

Terrestrial (land):

• Forest
• Grassland
• Desert
• Tundra

Aquatic (water):

• Freshwater (ponds, lakes, rivers)
• Marine (oceans, coral reefs)

Each habitat has specific conditions, so only organisms with suitable adaptations can live there.

5) Adaptations and habitat

Organisms have features that help them survive in their habitats.

Examples:

• Polar bear: thick fur and fat → cold Arctic habitat
• Cactus: thick stem and spines → dry desert habitat
• Fish: gills → aquatic habitat

If conditions change too much, the organism may struggle or die.

6) Why habitats matter

• Support biodiversity
• Maintain food webs
• Provide ecosystem services (clean water, oxygen, soil stability)

Habitat destruction (deforestation, pollution, urbanization) is one of the biggest threats to species survival.

中文（详细解释）

1）什么是“栖息地（Habitat）”

栖息地是指生物自然生活的地方。 它为生物提供生存所需的一切条件，包括：

• 食物
• 水
• 庇护所
• 活动空间
• 合适的环境条件（温度、光照、湿度等）

一句话： 👉 栖息地 = 生物在自然界中的“家”

2）栖息地的组成

栖息地由生物因素和非生物因素共同构成。

• 生物因素： 植物、动物、真菌、细菌
• 非生物因素： 阳光、温度、水、空气、土壤、养分

🔹 例子： 池塘栖息地不仅有鱼和水草，还有水温、含氧量和光照条件。

3）栖息地 vs 生态位（考试常考）

• 栖息地： 生物住在哪里
• 生态位： 生物如何生存、扮演什么角色

🔹 例子：

• 青蛙的栖息地 → 池塘
• 青蛙的生态位 → 捕食昆虫、被鸟类捕食

4）常见栖息地类型

陆地栖息地：

• 森林
• 草原
• 沙漠
• 苔原

水生栖息地：

• 淡水（湖泊、河流、池塘）
• 海洋（海洋、珊瑚礁）

每种栖息地都有独特环境条件。

5）栖息地与适应

生物具有适应其栖息地的特征。

例子：

• 北极熊：厚毛和脂肪 → 寒冷地区
• 仙人掌：肉质茎和刺 → 干旱沙漠
• 鱼类：鳃 → 水生环境

环境变化过大，生物可能无法生存。

6）为什么栖息地很重要

• 维持生物多样性
• 支撑食物网
• 提供生态系统服务

栖息地破坏是物种灭绝的重要原因之一。

一句话总结（双语）

• Habitat = where an organism lives
• 栖息地 = 生物生活的自然环境

如果你需要，我可以把 habitat 整理成 ✔️ 双语闪卡（定义 / 对比 / 易错点） ✔️ Habitat vs niche 对照表 ✔️ 适合 Biology 10 的练习题与图片标注

Unity（统一性）— with appropriate images

English (thorough explanation)

1) What “unity” means (core idea)

Unity means everything works together as a whole. Different parts may vary, but they feel connected, consistent, and purposeful, not random or chaotic.

Unity answers the question: 👉 “Do all parts belong together?”

2) Unity in art & design (most common use)

In art, design, and visual composition, unity refers to how elements combine to create a cohesive visual experience.

Unity is achieved through:

• Repetition (same colors, shapes, fonts)
• Consistency (style, spacing, alignment)
• Proximity (related items placed close together)
• Alignment (elements line up logically)
• Harmony (elements complement rather than clash)

🔹 Example: A poster using one color palette, one font family, and repeated shapes feels unified.

Unity ≠ sameness Unity allows variety, but within a shared structure.

3) Unity vs. variety (important distinction)

• Unity = togetherness
• Variety = differences that add interest

Good design balances both:

• Too much unity → boring
• Too much variety → chaotic

🔹 Think of a song: Different notes and rhythms, but one key and mood.

4) Unity in biology

In biology, unity refers to how different parts function together to support life.

Examples:

• An organism: organs → systems → whole body
• An ecosystem: producers, consumers, decomposers working together
• Unity of life: all living things share DNA, cells, and basic biochemical processes

🔹 Example: Heart, lungs, and blood vessels are different, but form one circulatory system.

5) Unity in chemistry

In chemistry, unity describes how atoms bond to form a stable molecule.

Examples:

• Individual atoms are meaningless alone
• Together, they form compounds with new properties (e.g., H₂O)

Unity here means:

• Fixed ratios
• Predictable structure
• Shared electron systems

6) Unity in writing & thinking

In writing or arguments, unity means:

• Every paragraph supports one central idea
• No irrelevant details
• Clear logical flow

A unified essay:

• One thesis
• All evidence connects back to it

中文（详细解释）

1）什么是“统一性（Unity）”

统一性指的是：各个部分共同组成一个整体。 虽然每个部分可能不同，但它们之间相互联系、协调一致。

统一性回答的问题是： 👉 “这些部分是否属于同一个整体？”

2）艺术与设计中的统一性

在艺术、平面设计、网页设计中，统一性指画面是否整体协调、不杂乱。

实现统一性的方式包括：

• 重复（颜色、形状、字体）
• 一致性（风格、大小、间距）
• 接近性（相关元素靠近）
• 对齐（有清晰的排列逻辑）
• 和谐（不冲突）

🔹 例子： 一个网站如果颜色、按钮样式、字体统一，看起来就专业、清晰。

3）统一性 vs 多样性（考试常考）

• 统一性 → 整体感
• 多样性 → 变化与趣味

好的作品需要二者平衡：

• 只有统一 → 单调
• 只有变化 → 混乱

4）生物学中的统一性

在生物学中，统一性强调不同结构协同运作。

例子：

• 器官 → 系统 → 个体
• 生态系统中的不同物种相互依存
• 生命的统一性：所有生物都有细胞、DNA、相似代谢过程

🔹 例子： 心脏、肺、血管功能不同，但共同维持生命。

5）化学中的统一性

在化学中，统一性体现在：

• 原子通过化学键形成稳定整体
• 形成的新物质具有整体性质

🔹 例子： 氢和氧单独存在与结合成水，性质完全不同。

6）写作与思维中的统一性

在写作中，统一性意味着：

• 所有段落服务于同一个中心思想
• 没有跑题内容
• 逻辑清晰、层次分明

一句话总结（双语）

• Unity = many parts, one whole
• 统一性 = 多个部分，构成一个整体

如果你愿意，我可以把 unity 做成 ✔️ 考试用关键词对照表 ✔️ 艺术 / 生物 / 化学对比图 ✔️ 双语闪卡（定义 + 例子 + 易错点）

If I understood things correctly, she would normally not be selling at the market, right? She would be selling to a middle-man. Where things get a bit muddled for me is when she starts doing her fancy martial arts in what -- by definition -- has to be a public place, even if nobody happens to be there at the moment. What this tells me is that her martial arts skills and equipment are commonplace enough such that revealing them to passersby is no biggy. But I don't think that's what you're going for, right?

Could this be more effective if the scene were set in the temple? Is it actually necessary for it to happen at the market?

This is a huge plot point (Jovadao being a double-agent) that is revealed so nonchalantly. At this stage, I feel like we've seen to little to get invested in the political dimension or even quite understand it. That is fine, but I'd be worried this major revelation would get missed in the shuffle. Also, it's such a good juicy reveal I'm surprised you're giving away the opportunity. Of course, I know too much, and I'm curious to see how things unfold.

Reviewer #1 (Public review):

Summary:

Syed et al. investigate the circuit underpinnings for leg grooming in the fruit fly. They identify two populations of local interneurons in the right front leg neuromere of ventral nerve cord, i.e. 62 13A neurons and 64 13B neurons. Hierarchical clustering analysis identifies each 10 morphological classes for both populations. Connectome analysis reveals their circuit interactions: these GABAergic interneurons provide synaptic inhibition either between the two subpopulations, i.e. 13B onto 13A, or among each other, i.e. 13As onto other 13As, and/or onto leg motoneurons, i.e. 13As and 13Bs onto leg motoneurons. Interestingly, 13A interneurons fall into two categories with one providing inhibition onto a broad group of motoneurons, being called "generalists", while others project to few motoneurons only, being called "specialists". Optogenetic activation and silencing of both subsets strongly effects leg grooming. As well activating or silencing subpopulations, i.e. 3 to 6 elements of the 13A and 13B groups has marked effects on leg grooming, including frequency and joint positions and even interrupting leg grooming. The authors present a computational model with the four circuit motifs found, i.e. feed-forward inhibition, disinhibition, reciprocal inhibition and redundant inhibition. This model can reproduce relevant aspects of the grooming behavior.

Strengths:

The authors succeeded in providing evidence for neural circuits interacting by means of synaptic inhibition to play an important role in the generation of a fast rhythmic insect motor behavior, i.e. grooming of the body using legs. Two populations of local interneurons in the fruit fly VNC comprise four inhibitory circuit motifs of neural action and interaction: feed-forward inhibition, disinhibition, reciprocal inhibition and redundant inhibition. Connectome analysis identifies the similarities and differences between individual members of the two interneuron populations. Modulating the activity of small subsets of these interneuron populations markedly affects generation of grooming behavior thereby exemplifying their relevance. The authors carefully discuss strengths and limitations of their approaches and place their findings into the broader context of motor control.

Weaknesses:

Effects of modulating activity in the interneuron populations by means of optogenetics were conducted in the so-called "closed-loop" condition. This does not allow to differentiate between direct and secondary effects of the experimental modification in neural activity, as feedforward and feedback effects cannot be disentangled. To do so open loop experiments, e.g. in deafferented conditions, would be needed. Given that many members of the two populations of interneurons do not show one, but two or more circuit motifs, it remains to be disentangled which role the individual circuit motif plays in the generation of the motor behavior in intact animals.

Comments on revisions:

The authors have carefully revised the manuscript. I have no further suggestions or criticisms.

Author response:

The following is the authors’ response to the previous reviews.

Public Reviews:

Reviewer #1 (Public review):

Summary:

Syed et al. investigate the circuit underpinnings for leg grooming in the fruit fly. They identify two populations of local interneurons in the right front leg neuromere of ventral nerve cord, i.e. 62 13A neurons and 64 13B neurons. Hierarchical clustering analysis identifies each 10 morphological classes for both populations. Connectome analysis reveals their circuit interactions: these GABAergic interneurons provide synaptic inhibition either between the two subpopulations, i.e. 13B onto 13A, or among each other, i.e. 13As onto other 13As, and/or onto leg motoneurons, i.e. 13As and 13Bs onto leg motoneurons. Interestingly, 13A interneurons fall into two categories with one providing inhibition onto a broad group of motoneurons, being called "generalists", while others project to few motoneurons only, being called "specialists". Optogenetic activation and silencing of both subsets strongly effects leg grooming. As well activating or silencing subpopulations, i.e. 3 to 6 elements of the 13A and 13B groups has marked effects on leg grooming, including frequency and joint positions and even interrupting leg grooming. The authors present a computational model with the four circuit motifs found, i.e. feed-forward inhibition, disinhibition, reciprocal inhibition and redundant inhibition. This model can reproduce relevant aspects of the grooming behavior.

Strengths:

The authors succeeded in providing evidence for neural circuits interacting by means of synaptic inhibition to play an important role in the generation of a fast rhythmic insect motor behavior, i.e. grooming. Two populations of local interneurons in the fruit fly VNC comprise four inhibitory circuit motifs of neural action and interaction: feed-forward inhibition, disinhibition, reciprocal inhibition and redundant inhibition. Connectome analysis identifies the similarities and differences between individual members of the two interneuron populations. Modulating the activity of small subsets of these interneuron populations markedly affects generation of the motor behavior thereby exemplifying their important role for generating grooming. The authors carefully discuss strengths and limitations of their approaches and place their findings into the broader context of motor control.

We thank the reviewer for their thoughtful and constructive evaluation of our work.

Weaknesses:

Effects of modulating activity in the interneuron populations by means of optogenetics were conducted in the so-called closed-loop condition. This does not allow to differentiate between direct and secondary effects of the experimental modification in neural activity, as feedforward and feedback effects cannot be disentangled. To do so open loop experiments, e.g. in deafferented conditions, would be important. Given that many members of the two populations of interneurons do not show one, but two or more circuit motifs, it remains to be disentangled which role the individual circuit motif plays in the generation of the motor behavior in intact animals.

Our optogenetic experiments show a role for 13A/B neurons in grooming leg movements – in an intact sensorimotor system - but we cannot yet differentiate between central and reafferent contributions. Activation of 13As or 13Bs disinhibits motor neurons and that is sufficient to induce walking/grooming. Therefore, we can show a role for the disinhibition motif.

Proprioceptive feedback from leg movements could certainly affect the function of these reciprocal inhibition circuits. Given the synapses we observe between leg proprioceptors and 13A neurons, we think this is likely.

Our previous work (Ravbar et al 2021) showed that grooming rhythms in dusted flies persist when sensory feedback is reduced, indicating that central control is possible. In those experiments, we used dust to stimulate grooming and optogenetic manipulation to broadly silence sensory feedback. We cannot do the same here because we do not yet have reagents to separately activate sparse subsets of inhibitory neurons while silencing specific proprioceptive neurons. More importantly, globally silencing proprioceptors would produce pleiotropic effects and severely impair baseline coordination, making it difficult to distinguish whether observed changes reflect disrupted rhythm generation or secondary consequences of impaired sensory input. Therefore, the reviewer is correct – we do not know whether the effects we observe are feedforward (central), feedback sensory, or both. We have included this in the revised results and discussion section to describe these possibilities and the limits of our current findings.

Additionally, we have used a computational model to test the role of each motif separately and we show that in the results.  

Comments on revisions:

The careful revision of the manuscript improved the clarity of presentation substantially.

Reviewer #2 (Public review):

Summary:

This manuscript by Syed et al. presents a detailed investigation of inhibitory interneurons, specifically from the 13A and 13B hemilineages, which contribute to the generation of rhythmic leg movements underlying grooming behavior in Drosophila. After performing a detailed connectomic analysis, which offers novel insights into the organization of premotor inhibitory circuits, the authors build on this anatomical framework by performing optogenetic perturbation experiments to functionally test predictions derived from the connectome. Finally, they integrate these findings into a computational model that links anatomical connectivity with behavior, offering a systems-level view of how inhibitory circuits may contribute to grooming pattern generation.

Strengths:

(1) Performing an extensive and detailed connectomic analysis, which offers novel insights into the organization of premotor inhibitory circuits.

(2) Making sense of the largely uncharacterized 13A/13B nerve cord circuitry by combining connectomics and optogenetics is very impressive and will lay the foundation for future experiments in this field.

(3) Testing the predictions from experiments using a simplified and elegant model.

Thank you for the positive assessment of our work.

Weaknesses:

(1) In Figure 4-figure supplement 1, the inclusion of walking assays in dusted flies is problematic, as these flies are already strongly biased toward grooming behavior and rarely walk. To assess how 13A neuron activation influences walking, such experiments should be conducted in undusted flies under baseline locomotor conditions.

We agree that there are better ways to assay potential contributions of 13A/13B neurons to walking. We intended to focus on how normal activity in these inhibitory neurons affects coordination during grooming, and we included walking because we observed it in our optogenetic experiments and because it also involves rhythmic leg movements. The walking data is reported in a supplementary figure because we think this merits further study with assays designed to quantify walking specifically. We will make these goals clearer in the revised manuscript and we are happy to share our reagents with other research groups more equipped to analyze walking differences.

(2) Regarding Fig 5: The 70ms on/off stimulation with a slow opsin seems problematic. CsChrimson off kinetics are slow and unlikely to cause actual activity changes in the desired neurons with the temporal precision the authors are suggesting they get. Regardless, it is amazing the authors get the behavior! It would still be important for authors to mention the optogentics caveat, and potentially supplement the data with stimulation at different frequencies, or using faster opsins like ChrimsonR.

We were also intrigued by the behavioral consequences of activating these inhibitory neurons with CsChrimson. We appreciate the reviewer’s point that CsChrimson’s slow off-kinetics limit precise temporal control. To address this, we repeated our frequency analysis using a range of pulse durations (10/10, 50/50, 70/70, 110/110, and 120/120 ms on/off) and compared the mean frequency of proximal joint extension/flexion cycles across conditions. We found no significant difference in frequency (LLMS, p > 0.05), suggesting that the observed grooming rhythm is not dictated by pulse period but instead reflects an intrinsic property of the premotor circuit once activated. We now include these results in ‘Figure 5—figure supplement 1’ and clarify in the text that we interpret pulsed activation as triggering, rather than precisely pacing, the endogenous grooming rhythm. We continue to note in the manuscript that CsChrimson’s slow off-kinetics may limit temporal precision. We will try ChrimsonR in future experiments.

Overall, I think the strengths outweigh the weaknesses, and I consider this a timely and comprehensive addition to the field.

Reviewer #3 (Public review):

Summary:

The authors set out to determine how GABAergic inhibitory premotor circuits contribute to the rhythmic alternation of leg flexion and extension during Drosophila grooming. To do this, they first mapped the ~120 13A and 13B hemilineage inhibitory neurons in the prothoracic segment of the VNC and clustered them by morphology and synaptic partners. They then tested the contribution of these cells to flexion and extension using optogenetic activation and inhibition and kinematic analyses of limb joints. Finally, they produced a computational model representing an abstract version of the circuit to determine how the connectivity identified in EM might relate to functional output. The study makes important contributions to the literature.

The authors have identified an interesting question and use a strong set of complementary tools to address it:

They analysed serial‐section TEM data to obtain reconstructions of every 13A and 13B neuron in the prothoracic segment. They manually proofread over 60 13A neurons and 64 13B neurons, then used automated synapse detection to build detailed connectivity maps and cluster neurons into functional motifs.

They used optogenetic tools with a range of genetic driver lines in freely behaving flies to test the contribution of subsets of 13A and 13B neurons.

They used a connectome-constrained computational model to determine how the mapped connectivity relates to the rhythmic output of the behavior.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

I still have the following specific suggestions and questions, which need the attention of the authors:

P5, 2nd para, li 1: shouldn't "(Figures 1E and 1E')" be (Figures 1G and 1H)?

P7, last para, li 3: shouldn't "(Figures 2C and 2D)" be (Figures 2A and 2B)?

P19, para 2, last 2li: "...we observe that optogenetic activation......triggers grooming movements." I could not find the place in the text or a figure, where this was reported or shown. Please specify

P19, last para: "... shows that 13A neurons can generate rhyhtmic movements....." Given that the experiments were conducted in closed-loop, i.e. including the loop through the leg and its movements, the following formulation appears more justified: "....shows that 13A neurons significantly contribute to the generation of rhythmic movements,....."

P28, para 1, li 3 from bottom: "...themselves, rather than solely between antagonistsic motor neurons." While the authors are correct that in the stick insect and locust alternating inhibitory synaptic drive to flexor and extensor motoneurons has been shown to underly alternating activity of these two antagonistic motoneuron pools the previous studies have not shown or claimed that these synaptic inputs arise from direct interactions between these motoneuron pools. Based on this this text should be moved to the part "feed-forward inhibition" on page 27.

P28: "redundant inhibition": this motif has been shown to be instrumental in the locust flight CPG, e.g. Robertson & Pearson, 1985, Fig. 16.

P28: "reciprocal inhibition" The reviewer agrees with the authors that this motif has been shown for the mouse spinal cord, but also for other CPGs in vertebrates and invertebrates, e.g. clione, leech, xenopus - see the initial comment "(3) Intro and Discussion"

Thank you, we have incorporated the suggested corrections and clarifications into the revised manuscript.

Reviewer #2 (Recommendations for the authors):

I'm satisfied with the revised version

Reviewer #3 (Recommendations for the authors):

The authors have made a substantial effort to address my original points. They corrected the title, expanded Discussion and Methods sections, reran statistical tests using mixed models, added modelling clarifications and constraints, and fixed or removed confusing figure panels. Those changes have improved clarity and reduced some of the claims that I thought were exaggerated.

That said, some of my concerns remain only partially addressed, which could be fixed with relatively small tweaks. The authors should:

(1) Explicitly separate empirical findings from modelling inferences throughout the manuscript, including the Abstract, Results and Discussion (i.e., label claims of "intrinsic rhythmogenesis" as model-based inferences, not direct experimental demonstrations)

(2) Provide supplemental information on modelling to quantify the role of the black-box input (e.g., quantitative coordination/phase/frequency metrics for full model vs constant-input vs no black box), show pre- vs post-fine-tuning weight changes and the exact tuning constraints/optimization details (I could not find these details)

(3) To ensure results are reproducible, provide a supplemental table mapping each split line to EM-identified neuron(s) with NBLAST/morphological scores for each match;

(4) Fully document the statistical models (exact LMM/GLMM formulas, software/packages, etc);

(5) Deposit model code, trained weights and analysis scripts in a public repository.

We have updated the GitHub repository with the full statistical analysis documentation and model code, including trained weights and scripts.

We clarified olfactory epithelium here, but not retina. We might want to clarify both as we have not defined retina yet and some students may be unfamiliar with the term.

Author response:

The following is the authors’ response to the original reviews

Reviewer #1:

(1) As such amount of work has been put into developing this community tool, it would be worth thinking about how it could serve other multiplex-immunofluorescence methods (such as immunoSABER, 4i, etc). Adding an extra tab where the particular method that uses those reagents is mentioned. This would also help as IBEX itself and related methods evolve in the future.

We agree and currently support six other methods beyond the original ”IBEX2D Manual”, with the most generic being ”Multiplexed 2D Imaging”: standard, single cycle (non-iterative) imaging method applied to thin, 2D (5-30 micron) tissue sections. Descriptions of supported methods are given in the reagent glossary. We plan to evolve to include multiplex IF methods such as Immuno-SABER, 4i, Cell DIVE, etc. The current structure of the reagent resources table can support other immunofluorescence methods without modifications. The table contains information for IBEX and related methods. The particular method for which a reagent validation was evaluated is specified in the column titled ”Method”. Descriptions of supported methods are given in the reagent glossary.

(2) It has a rather minimal description of the software. In particular, there is software that has not been developed for IBEX specifically but that could be used for IBEX datasets (ASHLAR, WSIReg, VALIS, WARPY, and QuPath, etc). It would be nice if there was mention of those.

ASHLAR, WSIReg, VALIS, and Warpy have been added to the Knowledge-Base. These software components are specifically relevant for iterative imaging protocols which require image alignment. With respect to QuPath, Fiji, Napari and other general microscopy image analysis frameworks, these are not listed. Such frameworks provide a wide range of operations relevant for many microscopy image analysis tasks and are likely already familiar to researchers who are interested in the information contained in the Knowledge-Base.

(3) There is a concern about how the negative data information will be added, as no publication or peer-review process can back it up. Perhaps the particular conditions of the experiment should be very well described to allow future users to assess the validity.

We agree with this observation and have added the following language to the contribute page:

”When reporting information that has not appeared in a peer-reviewed publication, both negative and positive results, include more details with respect to experimental conditions and provide sample images as part of the supporting material files. In all cases, peer reviewed or not, we encourage providing additional details in the supporting material that you deem important and are not part of the csv file structure. These include, but are not limited to, lot numbers, versioned protocols used in the work, and any other information which will facilitate validation reproducibility.”

(4) The proposed scheme where a reagent can be validated or recommended against by up to 4 different labs should be good. It may be good to make sure that researchers who validate belong to different labs and are not only different ORCID that belong to the same group. Similar to making a case of recommendations against a reagent.

We generally support this recommendation. Based on our experience, even members within the same laboratory encounter challenges when attempting to validate reagents contributed by current or former colleagues. Additionally, research labs often experience significant personnel turnover, with minimal overlap over a five year span.

To address these concerns, we have updated the instructions on the contribute page as follows: ”We only accept up to 5 ORCID additions in the Agree or Disagree columns. This means that the original contributor’s work was replicated by up to 4 individuals or refuted by up to 5 people. Priority is given to contributions from individuals in laboratories distinct from the original source.”

(5) It is very interesting to keep track of the protocol versions used. Perhaps users should be able to validate independent versions and it will be important to know how information is kept.

Thank you for your suggestion. We encourage members of the community to cite the latest version of the Knowledge-Base in the “Citing the Knowledge-Base” section.

(6) The final point I would make is that the need to form a GitHub repository may deter some people from submitting data. For sporadic contributions, authors could think that users could either reach out to main developers and/or provide a submission form that can help less experienced users of command-line and GitHub programming, but still promote the contribution from the community.

We have given this significant thought and now support a secondary path for contributing that does not require familiarity with git or GitHub. This path involves downloading a zip file, modifying the contents of the csv files and providing supporting material text files and images. Once the work is completed, the contributor contacts the Knowledge-Base maintainers and we complete the submission together, with the maintainers dealing with the usage of git and GitHub. This information has been added to the notes which are listed at the top of the Contribute page. We have recently completed the first contribution that followed this new workflow.

We still encourage researchers to familiarize themselves with git and the GitHub repository hosting service. These tools have been shown to be useful for collaborative and reproducible laboratory research.

Reviewer #2:

(1) The potential impact of IBEX KB is very clear. However, the paper would benefit by also discussing more on KB maintenance and outreach, and how higher participation could be incentivized.

We have added the following details to the discussion:

The KB is actively maintained by its chairs, who meet bi-weekly to ensure its continued development and maintenance. In addition to these regular meetings, we engage with both current and prospective community members to gather feedback, encourage contributions, and expand the collective knowledge supporting the KB. To broaden outreach and foster sustained engagement, the IBEX community will collaborate with synergistic initiatives such as the HuBMAP Affinity Reagents Working Group, the European Society for Spatial Biology (ESSB), and the Global Alliance for Spatial Technologies (GESTALT).

As a further incentive for participation, we intend to launch an annual “Reagent Validation Week”, a community driven event inspired by software hackathons. During this dedicated week, researchers would focus on validating or reproducing validation for selected reagents and contribute their findings to the KB. We have also discussed hosting an “Around the World” symposium, featuring presentations from both junior and senior scientists across the community, to showcase diverse perspectives and foster global collaboration.

(2) Use of resources like GitHub may limit engagement from non-coding members of the scientific community. Will there be alternative options like a user-friendly web interface to contribute more easily?

We agree with this observation and have addressed it. Please see detailed response to point 6 from Reviewer 1.

Reviewer #3:

(1) IBEX is a specific immunofluorescence method. However, the utility of the Knowledge base is not limited to the specific IBEX method. Therefore, I suggest removing the unnecessary branding of the term IBEX from the KB and citing potentially other similar cyclic immunofluorescence methods in the manuscript (e.g. CycIF Lin et al 2018). This would also emphasize the wider impact and applicability of the KB to the wider imaging community.

For now, we have decided to keep the original reference to the IBEX method in the resource name and re-brand it in the next development phase. In that phase we intend to solicit reagent validations for methods unrelated to IBEX. We have added the reference to the CycIF publication. The manuscript text now reads: “We are optimistic that future versions will include extension of the IBEX method to other tissues and species and we intend to solicit contributions of reagent validations for other multiplexed imaging techniques such as CycIF Lin et al. (2015). At that point in time we expect to re-brand the KB as the IBEX++ Knowledge-Base...”

(2) I believe reporting negative results with reagents is highly valuable. However, the way to report antibodies must include more details. To ensure data quality, every report should be linked to a specific protocol + images (or doc with the standard document variations, and sample information. This should be a mandatory requirement.

We agree that this information is desirable, but we do not agree that it should be mandatory. In the contribution instructions we now explicitly list lot numbers and versioned protocols as examples of details that we encourage contributors to include in their supporting material files. We believe that requiring this information for a contribution sets the bar too high and will deter many from contributing information that can benefit others.

(3) While cross-validation among researchers is beneficial, even if five individuals fail to reproduce results with a given antibody, their findings may be influenced by techniquespecific factors. It is also important to consider whether these researchers come from the same group, institution, or geographical region, as this could impact reproducibility. Additionally, entries that have not been reproduced at least five times using the same protocol should still be considered valuable information. To address this, an ”insufficient validation data” flag could be implemented, ensuring that incomplete but useful findings remain accessible.

The contribution instructions now state that ”Priority is given to contributions from individuals in laboratories distinct from the original source”.

While our goal is to support reproducing reagent validations, we do not expect these type of contributions be the rule as the only incentive we can provide to encourage this behavior is co-authorship on the authoritative dataset. As a result, it is likely that many of the validations will have a single endorser, the original contributor. These results are valuable information and we do not think they should be singled out (insufficient validation label). We leave it up to the users of the KB to decide whether they trust recommendations with multiple endorsers or if endorsement by a single highly trusted contributor is sufficient for them. In all cases, issues with contributions can be rasied and discussed on the KB discussion forum.

The rationale for limiting the number of reproduction studies to five was that this is a minimal, yet sufficiently large, number that provides confidence in the results. Placing an upper limit ensures that researchers do not provide reproduction results for widely used and well established reagents just because these results are readily available to them.

(4) This system could flag reagents with inconsistent reports, highlight potential techniquespecific issues, and suggest alternative reagents with stronger validation records. Furthermore, a validation confidence ranking could be introduced, taking into account the number of independent confirmations, protocol consistency, and reproducibility data. These measures would help refine the reporting process while maintaining transparency and scientific rigor.

We agree that the functionality described here is desirable, but this is not part of the KB. At its core the KB is a dataset and we do not envision developing dedicated tools to perform these tasks. Instead, we foresee using the KB as context for interacting with AI agents. Providing the KB as context to an AI, one can currently use it to answer domain specific questions and perform related tasks such as designing imaging panels (under subject matter expert supervision). This was added to the sample usecases in the manuscript with a transcript from interaction with an AI model using the website as context provided as supplemental material.

(5) Regarding image formats for results reporting, while JPG files are convenient due to their small size, TIFF files offer significant advantages, such as preserving metadata and maintaining the integrity of real data values. Proper signal adjustments may not always be applied by researchers, making TIFF crucial for accurate data analysis. I suggest in this regard making available the possibility of including a link to the original TIFF data

The goal of the supporting material image is similar to that of an image used in a manuscript and it should not be used for data analysis purposes. This is the reason we chose the JPG format. Sharing these images is not intended to be a substitute for publicly sharing the original images and their associated metadata. This is now noted in the contributing instructions.

(6) Homepage:

Include a brief summary of the knowledge base’s purpose and tabs to provide clarity for new users. The current homepage is a bit misleading for newcomers.

The homepage has been modified to include information about the Knowledge-Base, contents and how to use it including as context for interaction with AI agents.

(7) Reagent Resources Section: Enable users to search for a target name directly, rather than filtering through dropdown options.

The dropdown menu explicitly shows all available targets and also allows for direct search of target name. To use it for direct search, once the dropdown is selected start typing the name of the target and the focus will jump to it. Thus, if looking for ”Zrf1” there is no need to scroll through all targets in the dropdown. This also facilitates easy clearing of a filter, select the dropdown and start typing the word ”clear”, then press enter when it is highlighted. This information has been added to the page.

Provide an option to download the dataset as a CSV file. This feature will be highly valued by non-computational researchers.

Links to download the reagent resources csv file and the whole Knowledge-Base have been added.

Add the same column documentation here as in the contributor instructions. For example, you need to make clear the distinctions between ”Recommend,” ”Agree,” and ”Disagree” ratings, as they may be misleading to those who have not visited the rules to contribute.

A link to the column documentation in the contributor instructions has been added here. Information on the website is displayed in one location and linked as needed. Duplicated display of information creates uncertainty for users and results in more complex instructions when referring to the information.

Include additional details in the dataset, such as lot numbers, or the date of the contribution, that could be relevant in different settings.

Please see response to point 2.

(8) Data & Software Section:

Add filtering options in the table based on organism and tissue availability

This data is not encoded in the available information in an independent manner so we do not directly enable filtering. It is usually included in the ”Details” free form text. This text is duplicated from the original dataset descriptions. One can still search this page using the browsers search functionality to achieve behavior similar to filtering. While the ”Details” text may not be visible due to the usage of the accordion user interface, it is still searchable and will automatically expand when the search text is found under the collapsed accordion button.

(9) Contributor Section:

Incorporate figures from the manuscript to make it more visual and improve understanding of rules and standards.

Figure 4 from the manuscript was added to this page.

I believe reporting negative results with reagents is highly valuable. However, to ensure data quality, every report should be linked to a specific protocol and sample information. This should be a mandatory requirement. To streamline the process, warnings for certain reagents could be implemented, but a reagent should not be outright labeled as ineffective without proper validation.

Please see response to point 2.

Cross-validation among researchers is beneficial, but even if five individuals fail to reproduce results with a given antibody, it may still be due to technique-specific factorsparticularly for non-routine antibodies.

We agree with this observation and have modified the contribution instructions accordingly:

When overturning previously reported results, the number of ORCIDs in the Disagree column becomes greater than those in the Agree column, we will open the contribution for public discussion on the Knowledge-Base forum before accepting it.

The intent is to increase the community’s confidence in the results, particularly when dealing with non-routine antibodies. This allows the original contributor and other members of the community to engage with the researchers who were unable to replicate a specific validation, possibly helping them to replicate the original results by adding missing details to the KB, or explicitly identifying and documenting issues with the original work.

Regarding image formats, JPG files are convenient due to their small size, but TIFF offers significant advantages, such as preserving metadata and maintaining the integrity of real data values. Proper signal adjustments may not always be applied by researchers, making TIFF crucial for accurate data analysis.

Please see response to point 5.

Reviewer #2 (Public review):

Summary:

The paper introduces the IBEX Knowledge-Base (KB), a shared online resource designed to help scientists working with immunofluorescence imaging. It acts as a central hub where researchers can find and share information about reagents, protocols, and imaging methods. The KB is not static like traditional publications; instead, it evolves as researchers contribute new findings and refinements. A key highlight is that it includes results of both successful and unsuccessful experiments, helping scientists avoid repeating failed experiments and saving time and resources. The platform is built on open-access tools ensuring that the information remains available to everyone. Overall, the KB aims to collaboratively accelerate research, improve reproducibility, and reduce wasted effort in imaging experiments.

Strengths:

(1) The IBEX KB is built entirely on open-source tools, ensuring accessibility and long-term sustainability. This approach aligns with FAIR data principles and ensures that the KB remains adaptable to future advancements.

(2) The KB also follows strict data organization standards, ensuring that all information about reagents and protocols is clearly documented and easy to find with little ambiguity.

(3) The KB allows scientists to report both positive and negative results, reducing duplication of effort and speeds up the research process.

(4) The KB is helpful for all researchers, but even more so for scientists in resource-limited settings. It provides guidance on finding affordable alternatives to expensive or discontinued reagents, making it easier for researchers with fewer resources to perform high-quality experiments.

(5) The KB includes a community discussion forum where scientists can ask for advice, share troubleshooting tips, and collaborate with others facing similar challenges.

(6) The authors discuss plans for active maintenance of the database and also to incentivize higher participation from the community.

(7) Even those unfamiliar with Github may contribute with the help of the database maintenance team.

Note: The authors have addressed my comments on the previous version of the article and the current version has been strengthened as a result.

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

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Reply to the reviewers

Manuscript number: RC-2025-02932

Corresponding author(s): Amit Tzur

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Reviewer #1 (Evidence, reproducibility and clarity (Required)):

The study highlights a dephosphorylation switch mediated by PP2A as a critical mechanism for coupling E2F7/8 degradation to mitotic exit and G1 phase. The study is clear and experiments are well conducted with appropriate controls

I have some concerns highlighted below:

Point 1. In this sentence: This intricate network of feedback mechanisms ensures the orderly progression of the cell cycle. What feedback mechanism are the authors referring to?

Thank you for pointing this out. We aimed for a general comment. The original line was replaced with: “The intricate network of (de)phosphorylation and (de)ubiquitination events in cycling cells establishes feedback mechanisms that ensure orderly cell cycle progression.”

Point 2. Characterization of disorder in the N-terminal segments of E2F7 and E2F8

What does it mean disorder in this title?

“Disorder” is a structural biology term for describing an unstructured (floppy) region in a protein. We suggest the following title in hope to improve clarity: “The N-terminal segments of E2F7 and E2F8 are intrinsically unstructured”

Point 3. In the paragraph on the untimely degradation of E2F8 the authors keep referring to APC/C Cdc20, however the degradation is triggered by the Ken box which is specifically recognised by APC/C Cdh1. Can it be due to another ligase not APC/C?

In our anaphase-like system, Cdh1 cannot associate with the APC/C due to persistently high Cdk1 activity, maintained by the presence of non-degradable Cyclin B1. While the KEN-box is classically recognized as a Cdh1-specific motif, previous studies have also clearly demonstrated that APC/C-Cdc20 can mediate the degradation of KEN-box substrates. For example, BubR1 interacts with Cdc20 via two KEN-box motifs (PMIDs: 25383541, 27939943 and 17406666). Nek2A is targeted for degradation by the APC/C in mitotic egg extracts lacking Cdh1, in a manner that depends on both D-box and KEN-box motifs (PMID: 11742988). CENP-F degradation in Cdh1-null cells has been shown to be dependent on both Cdc20 and a KEN-motif (PMID: 20053638). Thus, the most simple explanation for our results is that degradation is KEN box dependent and controlled by Cdc20.

Regarding alternative E3 ligases, KEN-box mutant variants of non-phosphorylatable E2F8 remained stable in APC/CCdc20-active extracts, suggesting that this degradation is indeed APC/C-specific.

Please also see our response to Reviewer #3, Point 3.

Point 4. The assays to detect dephosphorylation are rather indirect so it is difficult to establish whether phosphorylation of CDK1 and dephosphorylation by PP2A on the fragments is direct.

First, the phosphorylation sites analyzed in this study conform to the full and most canonical Cdk1 consensus motif: S/TPxK/R. While recognizing that other kinases are proline directed as well, the cell cycle dependent manner of this control, and presence of a similar CDK-dependent mechanism for Cdc6, points us towards considering the role of CDKs.

Second, consistent with the direct role of CDK1 in this regulation, NMR experiments demonstrate conformational shifts of recombinant E2F8 following incubation with Cdk1–Cyclin B1 (not included in manuscript, but shown here for reviewer consideration); see Figure below. We have not yet established equivalent biochemical systems for PP2A.

Figure legend: NMR-based monitoring of E2F7 (a-c) and E2F8 (d-f) phosphorylation by Cdk1.

a(d). 15N,1H-HSQC spectrum of E2F7(E2F8) prior to addition of Cdk1. Threonine residues of interest, T45 (T20) conforming to the consensus sequence (followed by a proline), and T84 (T60) lacking the signature sequence are annotated. b(e). Strips from the 3D-HNCACB spectrum used for assigning E2F7(E2F8) residues. Black (green) peaks indicate a correlation with the 13Cα (13Cβ) of the same and previous residues. The chemical shifts assigned to T45 (T20) and T84 (T60) match the expected values for K44(K19) and P83(P59), thereby confirming the assignment. c(f). Top, overlay of subspectra before adding Cdk1 (black) and after 16 h of activity (red) at 298 K. Bottom, change in intensities of the T45/T84 in E2F7 and T20/T60 in E2F8 showing how NMR monitors phosphorylation and distinguishes between various threonine residues.

Third, PP2A is likely the principal phosphatase counteracting Cdk1-mediated phosphorylation during mitotic exit, targeting numerous APC/C substrates (PMID: 31494926). In light of our findings and the extensive literature, it is therefore reasonable to propose that E2F7 and E2F8 may also be direct PP2A targets.

Fourth, we cannot fully exclude the possibility that dephosphorylation of E2F7 and E2F8 by PP2A occurs indirectly. Nevertheless, indirect studies of PP2A substrate identification in the literature often rely on similar genetic perturbations, chemical inhibition, cell-free systems (coupled with immunodepletion, inhibitory peptides/proteins, and small-molecule inhibitors), and phosphoproteomics. Moreover, more direct assays are not without caveats, as they lack the cellular stoichiometric context, an important limitation for relatively promiscuous enzymes such as phosphatases.

Importantly, repeated attempts (conventional [Co-IP] and less conventional [affinity microfluidics]) to detect interactions between PP2A and E2F7 and E2F8 were unsuccessful. This result was unfortunate but not surprising, given that transient substrate–phosphatase interactions are often challenging to capture experimentally.

Given our evidence showing the regulation of E2F7 and E2F8 degradation in a manner that depends on Cdk1 and PP2A, the title of the manuscript remains appropriate: "Cdk1 and PP2A constitute a molecular switch controlling orderly degradation of atypical E2Fs.”

Please also see our response to Reviewer #3 Point 1.

Point 5. Although there seems to be a control by phosphorylation and dephosphorylation (which could be indirect), it is difficult to establish the functional consequences of this observation. The authors propose a feedback mechanism which regulates the temporal activation inactivation of E2F7/8 however, there are no evidence in support of this.

The components being studied here have been extensively characterized, as have the direct and indirect interactions that connect them and ensure orderly cell cycle progression. For example: i) The E2F1–E2F7/8 transcriptional circuitry functions as a negative feedback loop; ii) Cdk1 and PP2A counteract one another’s activity; iii) E2F1 promotes the disassembly of APC/CCdh1; iv) E2F7 and E2F8 are APC/C substrates with cell cycle-relevant degradation patterns; and v) Loss of Cdh1 leads to premature S-phase entry.

Our study brings these components together into a coherent regulatory module operating in cycling cells, revealed through cell-free biochemistry and newly developed methodologies with broad applicability to signaling research. We believe that advancing mechanistic understanding at this level of central regulators is impactful. And notably, this is a model, which we expect others in the field to test. We stand behind the result of each individual experiment and based on those findings are proposing a feedback circuit.

To address your suggestion, we incorporated phenotypic analyses (see Figure on the next page). Although modest and variable due to transient overexpression, these data align with the mechanistic model proposed in our study.

In Panel a, overexpression of E2F7 or E2F8 reduces E2F1 and its target Plk1, consistent with the established negative feedback within the E2F1–E2F7/8 transcriptional circuitry. A broader impact on cell cycle progression was also evident: G1-phase cells increased and S-phase cells decreased (Panel b), hinting at a delayed G1–S transition when E2F1, an essential driver of S-phase and mitotic entry, is downregulated by excess E2F7 or E2F8.

We next examined the effects of hyper- vs. hypo-phosphorylation–mimicking mutants of E2F7 and E2F8 on E2F1 and Plk1 (Panels c and d). Both raw data (top) and quantification (bottom) are shown. Despite ectopic overexpression, our experimental conditions highlighted the diffenrential outcome of the two phospho-mutant variants. Speificially, E2F1 and Plk1 levels were consistently higher upon expression of non-phosphorylatable variants of E2F7 (T45A/T68A) and E2F8 (T45D/T68D) relative to their phophomimetic counterparts (T45D/T68D; T20D/T44D). These findings suggest that E2F1 downregulation is more pronounced when E2F7/E2F8 are hyper-phosphorylated at Cdk1-regulated sites that control their half-lives. Furthermore, the proportion of S-phase cells was consistently lower for the phospho-mimicking mutants compared with the non-phosphorylatable variants, with complementary, though less pronounced, shifts in G1-phase cells (Panel e).

Figure legend: Evidence for cell cycle control linked to Cdk1–PP2A regulation of the E2F1–E2F7/E2F8 axis.

a) Immunoblot analysis showing reduced E2F1 and its target protein Plk1 upon E2F7/E2F8 overexpression. Antibodies used for immunoblotting (IB) are indicated. b) Cell cycle phase distribution after E2F7/E2F8 overexpression, based on DNA content. Left: representative histograms. Right: quantification of G1- and S-phase cells. Means (x) with individual biological replicates (color-coded; N = 4) are shown. c,d) Top: E2F1 and Plk1 protein levels in cells expressing phosphomimetic (TT-DD) or non-phosphorylatable (TT-AA) E2F7 (c) or E2F8 (d) variants. Antibodies used are indicated (*distorted signal excluded). Bottom: quantification relative to loading controls. Means (x) with individual values (N = 3/4) are shown. e) Cell cycle phase distribution following expression of E2F7/E2F8 phospho-mutant variants. Means (x) with individual values (N = 4) are shown. All experiments were performed in HEK293T cells. Cells were fixed 40–44 h post-transfection. DNA content was assessed using propidium iodide (PI). Mutation sites: T45/T68 (E2F7); T20/T44 (E2F8. Statistical significance was determined by two-tailed Student’s t-test; P-values are indicated.

Taken together, these results support a model in which Cdk1-site (de)phosphorylation modulates the stability of E2F7 and E2F8, thereby shaping E2F1 output and influencing cell cycle preogresion.

Point 6. Reviewer #1 (Significance (Required)):

The study is a good and well conducted work to understand the mechanisms regulating degradation of E2F7/8 by APC/C. This is crucial to establish coordinated cell cycle progression. While the hypothesis that disruption of this mechanism is likely responsible for altered cell cycle progression, there are no evidence this is just a back up pathway, whose functional significance could be limited to lack of APC/C Cdh1 activity. These experiments are rather difficult but the authors could comment on the limitation of the study and emphasise the hypothetical alterations which could result from the alterations of the described feedback loop

We thank Reviewer #1 for this comment. Accordingly, we have expanded the discussion to further elaborate on the potential molecular outcomes and limitations of our study.

Reviewer #2 (Evidence, reproducibility, and clarity (Required)):

Summary: The authors provide strong biochemical evidence that the regulation of E2F7 and E2F8 by APC is affected by CDK1 phosphorylation and potentially by PP2A dependent dephosphorylation. The authors use both full length and N-terminal fragments of E2F8 in cell-free systems to monitor protein stability during mitotic exit. The detailed investigation of the critical residues in the N-terminal domain of E2F8 (T20/T44) is well supported by the combination of biochemical and cell biology approaches.

We thank Reviewer #2 for their encouraging feedback.

Point 1. Major: It is unclear how critical the APC-dependent destruction of E2F7 and E2F8 is for cell cycle progression or other cellular processes. Prior studies have reported that Cyclin F regulation of E2F7 is critical for DNA repair and G2-phase progression. This study would be improved if the authors could provide a cellular phenotype caused by the lack of APC dependent regulation of E2F8 and/or E2F7.

We thank Reviewers #2 and #1 for this comment, which prompted substantial revisions. Below, we reiterate our response to Reviewer #1.

The molecular components examined in this study are well established in the literature. Key principles include: (i) the reciprocal regulation between E2F1 and its repressors, E2F7 and E2F8, which forms a transcriptional feedback loop; (ii) the opposing activities of Cdk1 and PP2A; (iii) the capacity of E2F1 to attenuate APC/CCdh1 activity; (iv) the fact that E2F7 and E2F8 are APC/C substrates with defined cell cycle–dependent degradation patterns; and (v) the requirement for Cdh1 to prevent premature S-phase entry.

Our study integrates these elements into a unified framework operating in proliferating cells. This framework is supported by biochemical reconstitution experiments and newly developed methodological tools, which we anticipate will be broadly applicable for dissecting signaling pathways. We view this type of mechanistic synthesis as valuable for the field. Importantly, we do not present this as a definitive model, but rather as a testable regulatory circuit constructed from robust individual findings.

In response to your request, we incorporated additional phenotypic analyses (see Figure, next page). Although modest and variable due to transient overexpression, the results are consistent with the regulatory architecture we propose.

In panel a, elevating E2F7 or E2F8 levels reduces E2F1 and its downstream target Plk1, consistent with the established inhibitory feedback exerted by E2F7 and E2F8 on E2F1. Additionally, we observed an increase in G1-phase cells and a decrease in S-phase cells (Panel b), hinting at a delayed G1–S transition when E2F1, a key transcriptional engine of S- and M-phase entry, is downregulated by excess E2F7 or E2F8.

Figure legend: Evidence for cell cycle control linked to Cdk1–PP2A regulation of the E2F1–E2F7/E2F8 axis.

a) Immunoblot analysis showing reduced E2F1 and its target protein Plk1 upon E2F7/E2F8 overexpression. Antibodies used for immunoblotting (IB) are indicated. b) Cell cycle phase distribution after E2F7/E2F8 overexpression, based on DNA content. Left: representative histograms. Right: quantification of G1- and S-phase cells. Means (x) with individual biological replicates (color-coded; N = 4) are shown. c,d) Top: E2F1 and Plk1 protein levels in cells expressing phosphomimetic (TT-DD) or non-phosphorylatable (TT-AA) E2F7 (c) or E2F8 (d) variants. Antibodies used are indicated (*distorted signal excluded). Bottom: quantification relative to loading controls. Means (x) with individual values (N = 3/4) are shown. e) Cell cycle phase distribution following expression of E2F7/E2F8 phospho-mutant variants. Means (x) with individual values (N = 4) are shown. All experiments were performed in HEK293T cells. Cells were fixed 40–44 h post-transfection. DNA content was assessed using propidium iodide (PI). Mutation sites: T45/T68 (E2F7); T20/T44 (E2F8. Statistical significance was determined by two-tailed Student’s t-test; P-values are indicated.

We next examined how phospho-regulation of E2F7 and E2F8 influences cell cycle control by comparing the effects of phospho-mimetic and non-phosphorylatable variants on E2F1 levels and cell cycle distribution (panels c and d). Both the raw data and the corresponding quantitative analyses are presented. Despite exogenous overexpression, we identified conditions that distinguish the behaviors of the two mutant classes. Cells expressing the phospho-mimetic variants consistently exhibited lower E2F1 and Plk1 levels than those expressing the non-phosphorylatable forms. This pattern supports a model in which phosphorylation of key Cdk1 sites in E2F7 and E2F8 elevates their stability, thereby enhancing their ability to suppress E2F1. Panel e extends these observations to cell cycle behavior: compared with the non-phosphorylatable variants, The phospho-mimetic forms of E2F7 and E2F8 consistently lower the proportion of S-phase cells, accompanied by corresponding shifts in the G1 population.

The central aim of this manuscript is to define how the Cdk1–PP2A axis is integrated into the APC/C–E2F1 regulatory network controlling cell cycle progression. Collectively, our findings support a model in which Cdk1/PP2A-dependent (de)phosphorylation modulates the stability of E2F7 and E2F8, thereby fine-tuning E2F1 activity and cell cycle progression.

Point 2. Minor: All optional: It would have been interesting to see the T20A/T44A/KM in the live cell experiment (Figure 3F).

This is an excellent point. Following Reviewer #2’s request, we generated a stable cell line expressing a KEN-box mutant variant of E2F8-T20A/T44A (N80 fragment). The figure below demonstrates the impact of the KEN-box mutation on the dynamics of N80-E2F8-T20A/T44A in HeLa cells. Together, our data from both cellular and cell-free systems show that the temporal dynamics of both wild-type and non-phosphorylatable variants of E2F8 depends on the KEN degron. Please note that due to differences in the flow cytometer settings used for acquiring the original measurements and those newly generated at the Reviewer’s request, the numeric data for N80-E2F8-T20A/T44A-KEN mutant will not be integrated into the original plots shown in the original Figure 3c–e in the manuscript.

Figure legend: Dynamics of mutant variants of N80-E2F8-EGFP in HeLa cells.

Top: Bivariate plots showing DNA content (DAPI) vs. EGFP fluorescence, with G1/G1-S phases and G2/M phases highlighted (black and gray frames, respectively). Bottom: Histograms showing EGFP signal distributions within these cell cycle phases. Blue arrows highlight subpopulations of G2/M cells with relatively low EGFP levels. The data was generated by flow cytometry.

Point 3. Figure 4C-D - include the corresponding blots for the WT E2F7.

This is a good point, which we previously overlooked. The requested data will be integrated in the revised manuscript.

Point 4. It is unclear how selective or potent the PP2A inhibitors are that are used in Figure 5. Is it possible to include known targets of PP2A (positive controls for PP2A inhibition) in the analysis performed in Figure 5?

Thank you for this helpful suggestion. Following Reviewer #2’s comment, we performed gel-shift assays of Cdc20 and C-terminal fragment of KIF4 (Residues: 732-1232), both known targets of PP2A (PMIDs: 26811472; 27453045). See data below.

__Figure legend: PP2A inhibitor LB-100 block protein dephosphorylation in G1-like extracts. __

Time-dependent gel shifts of mitotically phosphorylated Cdc20 and the C-terminal fragment of KIF4 (residues 732–1232) following incubation in G1 extracts supplemented with LB-100 or okadaic acid (OA; positive control). Substrates (IVT, 35S-labeled) were resolved by PhosTag SDS–PAGE and autoradiography.

Point 5. Is the APC still active in LB-100 or OA treated conditions? Is it possible to demonstrate the APC is active using known substrates in this assay (e.g., Securin (Cdc20) and Geminin (Cdh1) or similar).

This is an excellent point and we should have clarified this previously. Importantly, treatment with 250 µM LB-100 does not abolish APC/C-mediated degradation (otherwise, the assay would not be viable), but it does attenuate degradation kinetics. This is reflected by the prolonged half-lives of Securin and Geminin relative to mock-treated extracts (see below). Consistently, we noted in the manuscript: “Although APC/C-mediated degradation is also affected, it remains efficient, allowing us to measure relative half-lives of APC/C targets that cannot undergo PP2A-mediated dephosphorylation.” Following this comment, and one by Reviewer #3, these data will be included in the revised manuscript.

__Figure legend: APC/C-specific activity in cell extracts treated with LB-100. __

Time-dependent degradation of EGFP–Geminin (N-terminal fragment of 110 amino acids) and Securin in extracts supplemented with LB-100 and/or UbcH10 (recombinant). A control reaction contained dominant-negative (DN) UbcH10. Proteins (IVT, 35S-labeled) were resolved by SDS-PAGE and autoradiography.

Reviewer #2 (Significance (Required)): Advance: A detailed analysis is provided for the critical N-terminal residues in E2F7 and E2F8 that when phosphorylated are capable of restricting APC destruction. The work builds on prior work that had identified the APC regulation of E2F7 and E2F8.

Point 6. Audience: The manuscript would certainly appeal to a broad basic research audience that is interested in the regulation of APC substrates and/or E2F axis control via E2F7 & E2F8. The study could have a broader interest if the destruction of E2F7 or E2F8 could be shown to be biologically relevant (e.g., critical for cell fate decision G1 vs G0, G1 length, timely S-phase onset, or expression of E2F1 target genes in the subsequent cell cycle).

To clarify, we subdivided Reviewers’ comments into separate points. Reviewer #2’s Points 1 and 6 address essentially the same issue; our detailed response is therefore provided under Point 1. We again thank Reviewer #2 for raising this concern, which led to substantial revisions to both the manuscript text and the supporting data.

We thank Reviewer #2 for their constructive comments and criticism.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

This manuscript presents a well-structured study on the regulatory interplay between Cdk and Phosphatase in controlling the degradation of atypical E2Fs, E2F7 and E2F8. The work is relevant in the field of cell cycle regulation and provides new mechanistic insights into how phosphorylation and dephosphorylation govern APC/C-mediated degradation. The use of complementary cell-based and in vitro approaches strengthens the study, and the findings have significant implications for understanding the timing of transcriptional regulation in cell cycle progression.

Point 1. However, several points in this paper require further clarification for it to have a meaningful impact on the research community. The characterization of the phosphatase is unclear to me. The use of OA is necessary to guide the research, but it is not precise enough to rule out PP1 and then identify which PP2A is involved - PP2A-B55 or PP2A-B56. To clarify this, the regulatory subunits should either be eliminated or inhibited using the inhibitors developed by Jakob Nilsson's team.

We are grateful for this comment, which prompted an extensive series of experiments that have undoubtedly strengthened our manuscript.

First, we wish to clarify that LB-100, unlike okadaic acid (OA), is not considered a PP1 inhibitor.

Second, we have conducted a large set of experiments to address this important question of the strict identity of the phosphatase involved in the dephosphorylation of atypical E2Fs.

I. We initially attempted to immunodeplete the catalytic subunit of PP2A (α) from G1 extracts as a means to validate PP2A-dependent dephosphorylation. In retrospect, this was a naïve approach given the protein’s high abundance; although immunoprecipitation was successful, immunodepletion was inefficient, preventing us from using this strategy (see Panel a in the figure below). As an alternative, we incubated immunopurified PP2A-Cα with mitotic phosphorylated E2F7 and E2F8 fragments (illustrated in Panel b). A time-dependent gel-shift assay demonstrated enhanced dephosphorylation in the presence of immunopurified PP2A-Cα (Panel c) compared to immunopurified Plk1 (control reaction), suggesting that mitotically phosphorylated E2F7 and E2F8 are targeted by PP2A.

Figure legend: Immunopurified PP2A-Cα facilitates dephosphorylation of E2F7 and E2F8 in cell extracts. a) Inefficient immunodepletion (ID) of the catalytic subunit α of PP2A (PP2A-Cα) from cell extracts despite three rounds of immunopurification, as detected by immunoblotting (IB) with anti-PP2A-Cα and anti-BIP (loading control; LC) antibodies (BD bioscience, Cat#: 610555; Cell Signaling Technology, Cat#: 3177). Briefly, G1 cell extracts were diluted to ~10 mg/mL in a final volume of 65 μL. Anti-PP2A-Cα antibodies (3 μg) were coupled to protein G magnetic DynabeadsTM (15 μL; Novex, Cat#: 10004D) for 20 min at 20 °C. For each depletion round, antibody-coupled beads were incubated with cell extracts for 15 min at 20 °C. Cell extracts and beads were sampled after each step to assess immunodepletion and immunopurification (IP) efficiency. Equivalent immunopurification steps are shown for Plk1 (bottom). b) Schematic of the dephosphorylation assay using mitotically phosphorylated in vitro translated (IVT) targets and immuno-purified PP2A-Cα/Plk1. c) Dephosphorylation of mitotically phosphorylated E2F7 and E2F8 fragments, detected by electrophoretic mobility shifts in Phos-Tag SDS-PAGE. Immunopurified Plk1 was used for control reactions (antibodies: Santa Cruz Biotechnology: Cat#: SC-17783). *Image was altered to improve visualization of mobility shifts.

II. Next, we used pan-B55-specific antibodies for immunodepletion of all B55-type subunits. This approach was unsuccessful despite five rounds of immunopurification (see Panel a in the figure below). Both suboptimal binding and the high abundance of endogenous B55 subunits likely contributed to this outcome. Thus, dephosphorylation in B55-depleted extracts could not be tested.

Figure legend: PP2A-B55 facilitates dephosphorylation of E2F7 and E2F8 fragments.

a) __Immunodepletion (ID) of B55 subunits in G1 extracts is inefficient despite five rounds of immunopurification; assessed by immunoblotting (IB) using anti-pan-B55 and anti-Cdk1 (loading control; LC) antibodies (see previous figure for more details). Cell extracts and beads were sampled after each round to monitor immunodepletion and immunopurification efficiency. b) Schematic of a dephospho-rylation assay using immuno-purified B55 subunits. __c) __Dephosphorylation of mitotically phosphorylated E2F7 and E2F8 fragments by immuno-purified B55. Control reactions performed with immuno-purified Plk1. d) __Schematic of a dephosphorylation assay performed in G1 cell extracts supplemented with B55-interacting (B55i) or control peptides (see peptide sequence on next page). RO-3306 was added to limit Cdk1 activity. __e) __Dephosphorylation of E2F7 and E2F8 fragments (mitotically phosphorylated) in G1 extracts supplemented with B55-interacting/control peptides. __f) __Schematic of the dephosphorylation assay using in vitro–translated B55/B56 subunits (unlabeled). __g) __Dephosphorylation of mitotically phosphorylated E2F7 (top) and E2F8 (bottom) fragments in reticulocyte lysate containing B55/B56 subunits. Dephosphorylation was assessed by electrophoretic mobility shifts in Phos-Tag SDS-PAGE. Panels marked with an asterisk were adjusted to improve visualization of gel-shifts. Arrowheads denote distinct, time-dependent mobility-shifted forms of E2F7 and E2F8 fragments. Antibodies used: anti-pan-B55 (ProteinTech, Cat#: 13123-1-AP); anti-Plk1 (Santa Cruz Biotechnology, Cat#: SC-17783); anti-Cdk1 (Santa Cruz Biotechnology, Cat#: SC-53217). Dynabeads™ (Novex, Cat#: 10004D) were used for immunopurification.

As with PP2A-Cα, we incubated immunoprecipitated B55 subunits with mitotically phosphorylated E2F7 and E2F8 fragments (illustrated in Panel b). The results were less definitive compared to PP2A-Cα; nevertheless, they demonstrated accelerated dephosphorylation in the presence of immunopurified B55 subunits (Panel c) relative to Plk1 (control). These results hint at B55-mediated dephosphorylation of E2F7 and E2F8.

III. Given that PP2A-B55 could be immunodepleted satisfactorily, despite successful immunoprecipitation, we ordered the B55-specific peptide and corresponding control peptide reported recently by Jakob Nilsson’s team as PP2A-B55 inhibitors (see below).

Figure legend: Adapted from Kruse, T., et al., 2024; ____Science Advances. Figure 3, Panel B. ____PMID: 39356758.

Despite our long-anticipated wait for these peptides to arrive, this line of experimentation proved disappointing. We wish to elaborate:

The study by Kruse et al. (PMID: 39356758) is an elegant integration of classical enzymology, performed at the highest level, with structural insight into the conserved PP2A-B55 binding pocket that governs substrate specificity. Their work identified a consensus peptide that binds PP2A-B55 specifically with nanomolar affinity.

Kruse et al. provide compelling evidence for a direct and specific interaction between their reported B55 inhibitor (B55i) and PP2A-B55. Their data show that the engineered inhibitor disrupts the binding of helical elements that underlie substrate recognition by PP2A-B55.

However, we could not find direct evidence of PP2A-B55 enzymatic inhibition by the B55i peptide; for example, a B55-specific in vitro dephosphorylation assay demonstrating sensitivity to B55i in a dose-dependent manner. To the best of our understanding, the sole functional consequence described by Kruse et al. was the delay in mitotic exit observed upon expression of YFP-tagged B55i peptides in cells. However, this approach is indirect, given the long interval between cell manipulation and analysis and the complexity of mitotic exit. Furthermore, we assumed that the requested reagents had been validated in cell-free extracts; however, Kruse et al. do not report any experiments performed in these systems. We, in fact, became uncertain whether we had correctly understood Reviewer #3’s request to use these reagents and therefore sought clarification from the Editor.

In vitro, Kruse et al. reported nanomolar binding affinities for B55i (Figure S14). In our cell extracts, however, we required concentrations of approximately 250 μM to detect an effect on dephosphorylation, evident as altered electrophoretic mobility of both E2F7 and E2F8 (Panel e). At this concentration, the peptide also caused nonspecific effects, rendering the extracts highly viscous (‘gooey’), at times preventing part of the reaction mixture from passing through a 10 μL pipette tip.

The gel-shift assays shown in Panel e (Page 16) do demonstrate delayed dephosphorylation in extracts treated with the B55i peptide relative to the control peptide. Nevertheless, we prefer to exclude these data because the peptide concentrations required for the assay compromised extract integrity. Moreover, we believe that the PP2A-B55–specific peptide described by Nilsson et al. requires additional validation before it can be considered a reliable functional inhibitor in cell-free systems or in vivo. Accordingly, we are unable to directly address the experiments as suggested.

IV. In the final set of experiments (Page 16, Panels f and g), we supplemented dephosphorylation reactions with in vitro–translated B55/B56 subunits (illustrated in Panel f). Although the expected concentration of in vitro–translated proteins in reticulocyte lysate is relatively low (100–400 nM), we reasoned that supplementing the reactions with excess of regulatory B subunits (non-radioactive) could still promote dephosphorylation in a differential manner that reflects the B55/B56 preference of E2F7 and E2F8.

We cloned and in vitro expressed all nine B55/B56 regulatory subunits. While the exact amount of each subunit introduced into the reaction cannot be precisely determined, their expression levels were reasonably uniform (see figure below).

__Figure legend: Expression of B55/B56 subunits in reticulocyte lysate. __B55/B56 subunits were cloned into the pCS2 vector and expressed in reticulocyte lysate supplemented with ³⁵S-Methionin. Proteins were resolved by SDS–PAGE and autoradiography.

Returning to Panel g (Page 16), B55 subunits facilitated the accumulation of lower–electrophoretic mobility forms of both E2F7 and E2F8 fragments to the greatest extent. This is evident from the distinct lower–mobility species that emerge over time (marked by arrowheads) and the smear intensity corresponding to the buildup of dephosphorylated forms. Among the tested subunits, B55β exerted the strongest effect on both substrates, suggesting that mitotically phosphorylated E2F7 and E2F8 display a heightened preference for the PP2A-B55β holoenzyme. Control reactions with reticulocyte lysate are also shown.

Taken together, our original and newly added data indicate that PP2A, specifically PP2A-B55, counteracts Cdk1-dependent phosphorylation during mitotic exit. Importantly, cell cycle regulators such as Cdc20 can be targeted by both PP2A-B55 and PP2A-B56 holoenzymes. Thus, while we are confident in concluding that mitotically phosphorylated E2F7 and E2F8 are targeted by PP2A-B55, we cannot rule out the possibility of functional interactions between E2F7/E2F8 and PP2A-B56.

V. Last, but certainly not least, we used AlphaFold 3 to model interactions between the N-terminal fragments of E2F7 and E2F8 and the PP2A regulatory subunits. To clarify: for us, AlphaFold 3 remains very much a computational “black box,” and although this may sound like an overstatement, we did not anticipate obtaining meaningful or interpretable output.

According to the AlphaFold 3 developer guidelines, the Interface Predicted Template Modeling (IPTM) score is the primary confidence metric for protein–protein interaction predictions. IPTM values above 0.8 indicate high-confidence predictions, whereas values below 0.6 likely reflect failed interaction predictions. In our models, none of the predicted interactions exceeded 0.6 (see figure below). Nevertheless, for both E2F7 and E2F8 fragments, IPTM scores were consistently higher for B55 subunits than for B56 subunits, with B55β yielding the highest scores (each interaction was modeled five times).

__Figure legend: AlphaFold 3 predicts preferential interactions between E2F7 and E2F8 and PP2A-B55β. __Protein–protein interaction predictions between N-terminal fragments of E2F7 and E2F8 and B55/B56 regulatory subunits of PP2A were generated using AlphaFold 3 (AF3). The plot shows IPTM scores from five models per protein pair.

Even if one assumes a scenario in which AlphaFold 3 scores are inaccurate or effectively random, such non-specific behavior would not be expected to produce: (i) a reproducible preference of two distinct substrates for B55β and B55γ, in that order (the modeled fragments of E2F7 and E2F8 share The ability of AlphaFold 3, and specifically the IPTM metric, to predict bona fide PP2A B55/B56–substrate interactions remains unvalidated. Accordingly, we do not rely on these predictions as experimental evidence. Nonetheless, in retrospect, the IPTM scores for the E2F7 and E2F8 fragments proved, unexpectedly, to be highly informative. While we are not the first to explore AlphaFold in the context of PP2A phosphatases (e.g., Kruse et al.), at this early stage of AlphaFold 3 these observations are compelling and may ultimately have implications for PP2A-mediated signaling that extend well beyond the cell-cycle field.

Point 2. It would also be valuable for this study to investigate the mechanisms underlying this regulation. In particular, is it exclusive to E2F7-8 or could other substrates contribute to the generalisation of this regulatory process?

Assuming Reviewer #3 is referring to the cell cycle mechanism regulating E2F7 and E2F8 half-life via conditional degrons, we wish to clarify that the temporal dynamics of APC/C targets regulated by dephosphorylation has been demonstrated previously. Examples include KIFC1, CDC6, and Aurora A (PMIDs: 24510915; 16153703; 12208850, respectively).

Point 3. The observation that Cdc20 may target E2F8 is interesting but needs to be further clarified to ensure that weak Cdh1 activity does not contribute to this degradation. Elimination of Cdc20 would be necessary to support the authors' conclusion.

We gratefully acknowledge this input. The newly implemented experiment and corresponding findings are presented on the next page. The immunodepletion (ID) procedure (Panel a) achieved >60% reduction of Cdc20 and Plk1 in mitotic extracts (Panel b), as confirmed by immunoblotting (IB). Plk1-depleted extracts were used to validate extract-specific activity after successive rounds of immunodepletion at 20°C. Bead-bound Cdc20 and Plk1 were also analyzed by IB for validation (Panel b, right).

As expected, the phospho-mimetic E2F8 fragment (T20D/T44D) remained stable in Plk1- and Cdc20-depleted mitotic extracts, serving as negative control (Panel c). In contrast, degradation of the non-phosphorylatable variant (T20A/T44A), as well as the APC/CCdc20 substrate Securin (positive control), was strongly hampered in Cdc20-depleted extracts compared to Plk1-depleted extracts. These results confirm that the untimely degradation of the non-phosphorylatable E2F8 in mitotic extracts is Cdc20-dependent.

Figure legend: Untimely degradation of the non-phosphorylatable E2F8 in mitotic extracts is Cdc20-dependent.____a) Schematic of the immunodepletion (ID) protocol; additional technical details are provided below. b) Plk1 (top) and Cdc20 (bottom) levels in NDB mitotic extracts before and after three rounds of immunodepletion, as detected by immunoblotting (IB). Plk1 and Cdc20 levels were normalized to Tubulin and Cdk1, respectively. Both normalized and raw values are presented as percentages. Immunoprecipitation (IP) efficiency is shown on the right. c) Degradation profiles of phospho-mutant E2F8 variants and Securin (positive control) in NDB mitotic extracts depleted of Plk1 (control) or Cdc20.

__ ---__

Point 4. This study focuses on two proteins of the E2F family. These two proteins share similar domains, phosphorylation sites and a KEN box. However, their sensitivity to APC is different. What might explain this difference? Are there any inhibitory sequences for E2F7? Or why is the KEN box functional in E2F8 but not in E2F7?

This is an excellent question. Here are our thoughts: The processivity of polyubiquitination by the APC/C varies between substrates in ways that influence degradation rate and timing (PMID: 16413484). Although E2F7 and E2F8 are related, their sequence identity is below

50%, and their C-terminal domains differ substantially (see below) [FIGURE]. These structural differences likely contribute to differences in APC/C-mediated processivity and, consequently, to variations in protein half-lives. Additionally, E2F8 contains two functional KEN-boxes involved in its degradation, whereas E2F7 has only one. This may increase the kon rate of E2F8 for the APC/C, further enhancing its recognition and ubiquitination. Furthermore, re-examining the study by de Bruin and Westendorp (PMID: 26882548, Figure 2f; copied below), we note that the dynamic of inducibly expressed EGFP-tagged E2F7 in cells exiting mitosis is milder compared to E2F8 (see the black lines in both charts). This, as well as the oversensitivity of E2F7 degradation to Cdh1 downregulation accord with E2F7 being less potent substrate of APC/CCdh1.

Figure legend: Adapted from Boekhout et al., 2016; ____EMBO Reports. Figure 2, Panel F. ____PMID: 26882548.

The stability of the E2F7 fragment in cells and extracts was unexpected. We initially hypothesized that the unique N-terminal tail of E2F7 masks the KEN-box, functioning as an inhibitory sequence. However, removal of this region did not restore degradation (original manuscript; Figure 1e). Furthermore, extending the fragment by 20 additional residues failed to confer degradation (original manuscript; Figure S2). These observations suggest that E2F7 may require a distal or modular docking site for APC/C recognition. We did not pursue this question further.

Point 5. An additional element that could strengthen this work would be referencing the study by Catherine Lindon: J Cell Biol, 2004 Jan 19;164(2):233-241. doi: 10.1083/jcb.200309035. In Figure 1 of this article, there is a degradation kinetics analysis of APC/C complex substrates such as Aurora-A/B, Plk1, cyclin B1, and Cdc20. This could help position the degradation of E2F7/8 relative to known APC/C targets. This can be achieved by synchronizing cells with nocodazole and then removing the drug to allow cells to progress and complete mitosis.

This is an interesting point and one we should have clarified better previously. The temporal dynamics of E2F8 in synchronized HeLa S3 cells, relative to three known APC/C substrates, were reported in our previous study (PMID: 31995441; Figure 1a, copied on the right). Specifically, protein levels were measured for Cyclin B1, Securin, and Kifc1. Unlike Cyclin B1 and Securin, which are targeted by both APC/CCdc20 and APC/CCdh1, Kifc1 is degraded exclusively by APC/CCdh1. Cells were released from a thymidine–nocodazole block.

Following Reviewer #3’s comment, we re-blotted the original HeLa S3 synchronous extracts. The new data [FIGURE] can be incorporated into the revised manuscript if requested.

Point 6. Minor points: Does phosphorylation of E2F7-8 proteins alter their NMR profile? This could help understand how phosphorylation/dephosphorylation affects their sensitivity to the APC/C complex.

Excellent suggestion. Indeed, we had originally aimed to include a more extensive set of NMR data in this manuscript. Our goal was to monitor E2F7 and E2F8 fragments in cell extracts and assess structural changes induced by phosphorylation and dephosphorylation during mitosis and mitotic exit. However, purifying the E2F7 fragment proved more challenging than anticipated. In addition, the extract-to-substrate ratio requires further optimization: Substrate concentrations must be high enough for reliable NMR detection, but below levels that would saturate the enzymatic activity in the extracts.

That said, the short answer to the reviewer’s question is Yes: NMR profiles of E2F7 and E2F8 fragment do change following incubation with recombinant Cdk1–Cyclin B1 (see next page). If possible, we wish to exclude these NMR data from the manuscript.

Point 7. Do these substrates bind to the APC/C complex before degradation? Does E2F7 bind better than E2F8?

We were unable to detect interactions between endogenous E2F7 and E2F8 and the APC/C complex. In general, detecting endogenous E2F8, and especially E2F7, by immunoblotting proved challenging, making co-immunoprecipitation (Co-IP) even more difficult.

Figure legend: NMR-based monitoring of E2F7 (a-c) and E2F8 (d-f) phosphorylation by Cdk1.

a(d). 15N,1H-HSQC spectrum of E2F7(E2F8) prior to addition of Cdk1. Threonine residues of interest, T45 (T20) conforming to the consensus sequence (followed by a proline), and T84 (T60) lacking the signature sequence are annotated. b(e). Strips from the 3D-HNCACB spectrum used for assigning E2F7(E2F8) residues. Black (green) peaks indicate a correlation with the 13Cα (13Cβ) of the same and previous residues. The chemical shifts assigned to T45 (T20) and T84 (T60) match the expected values for K44(K19) and P83(P59), thereby confirming the assignment. c(f). Top, overlay of subspectra before adding Cdk1 (black) and after 16 h of activity (red) at 298 K. Bottom, change in intensities of the T45/T84 in E2F7 and T20/T60 in E2F8 showing how NMR monitors phosphorylation and distinguishes between various threonine residues.

However, interactions between EGFP-tagged E2F7 snd E2F8 and Cdh1 have been demonstrated previously (PMID: 26882548, Figure 2e). In contrast, only the N-terminal fragment of E2F8, but not the corresponding fragment of E2F7, was found to bind Cdh1 (see figure on the right). This observation is consistent with the stability of the E2F7 fragment in APC/C-active extracts.

__Figure legend: N-terminal fragment of E2F8 but not E2F7 binds Cdh1. __

Co-Immunoprecipitation (IP) was performed in HEK293 cells transfected with EGFP-tagged E2F7/E2F8 fragments, using GFP-Trap® (Chromotek, Cat#: GTMA-20). Antibodies used for immunoblotting: ant-GFP (Santa Cruz Biotechnology: Cat#: SC-9996); anti-Cdh1 (Sigma-Aldrich, Cat#: MABT1323).

Point 8. Why do the authors state that 250 µM of LB-100 has little effect on APC/C activity?

We thank Reviewers #2 and 3 for raising this point. As shown in the manuscript, treatment with 250 µM LB-100 does not abolish APC/C-mediated degradation (otherwise, the assay would not be viable). However, it does attenuate degradation kinetics, as reflected by the prolonged half-lives of Securin and Geminin (see figure below).

__Figure legend: APC/C-specific activity in cell extracts treated with LB-100. __

Time-dependent degradation of EGFP–Geminin (N-terminal fragment of 110 amino acids) and Securin in extracts supplemented with LB-100 and/or UbcH10 (recombinant). A control reaction contained dominant-negative (DN) UbcH10. Proteins (IVT, 35S-labeled) were resolved by SDS-PAGE and autoradiography.

Point 9. How can E2F8 be a substrate for both the SCF and APC/C complexes? (If I understood correctly.)

This can happen because they are degraded by different E3 at different times during the cell cycle. To clarify further, certain proteins can be targeted by both the APC/C and SCF complexes, reflecting distinct regulatory needs. A classic example is CDC25A, as shown by M. Pagano and A. Hershko in 2002 (PMID: 12234927). Additional examples include the APC/C inhibitor EMI1 (PMIDs: 12791267 [SCF] and 29875408 [APC/C]).

Reviewer #3 (Significance (Required)): This manuscript presents a well-structured study on the regulatory interplay between Cdk and Phosphatase in controlling the degradation of atypical E2Fs, E2F7 and E2F8. The work is relevant in the field of cell cycle regulation and provides new mechanistic insights into how phosphorylation and dephosphorylation govern APC/C-mediated degradation. The use of complementary cell-based and in vitro approaches strengthens the study, and the findings have significant implications for understanding the timing of transcriptional regulation in cell cycle progression.

We wish to thank Reviewer #3 for their positive and encouraging view of our work.

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Referee #3

Evidence, reproducibility and clarity

This manuscript presents a well-structured study on the regulatory interplay between Cdk and Phosphatase in controlling the degradation of atypical E2Fs, E2F7 and E2F8. The work is relevant in the field of cell cycle regulation and provides new mechanistic insights into how phosphorylation and dephosphorylation govern APC/C-mediated degradation. The use of complementary cell-based and in vitro approaches strengthens the study, and the findings have significant implications for understanding the timing of transcriptional regulation in cell cycle progression.

• However, several points in this paper require further clarification for it to have a meaningful impact on the research community. The characterization of the phosphatase is unclear to me. The use of OA is necessary to guide the research, but it is not precise enough to rule out PP1 and then identify which PP2A is involved - PP2A-B55 or PP2A-B56. To clarify this, the regulatory subunits should either be eliminated or inhibited using the inhibitors developed by Jakob Nilsson's team. It would also be valuable for this study to investigate the mechanisms underlying this regulation. In particular, is it exclusive to E2F7-8 or could other substrates contribute to the generalisation of this regulatory process?

• The observation that Cdc20 may target E2F8 is interesting, but needs to be further clarified to ensure that weak Cdh1 activity does not contribute to this degradation. Elimination of Cdc20 would be necessary to support the authors' conclusion.

• This study focuses on two proteins of the E2F family. These two proteins share similar domains, phosphorylation sites and a KEN box. However, their sensitivity to APC is different. What might explain this difference? Are there any inhibitory sequences for E2F7? Or why is the KEN box functional in E2F8 but not in E2F7?

• An additional element that could strengthen this work would be referencing the study by Catherine Lindon: J Cell Biol, 2004 Jan 19;164(2):233-241. doi: 10.1083/jcb.200309035. In Figure 1 of this article, there is a degradation kinetics analysis of APC/C complex substrates such as Aurora-A/B, Plk1, cyclin B1, and Cdc20. This could help position the degradation of E2F7/8 relative to known APC/C targets. This can be achieved by synchronizing cells with nocodazole and then removing the drug to allow cells to progress and complete mitosis.

Minor points:

• Does phosphorylation of E2F7-8 proteins alter their NMR profile? This could help understand how phosphorylation/dephosphorylation affects their sensitivity to the APC/C complex.

• Do these substrates bind to the APC/C complex before degradation? Does E2F7 bind better than E2F8?

• Why do the authors state that 250 µM of LB-100 has little effect on APC/C activity?

• How can E2F8 be a substrate for both the SCF and APC/C complexes? (If I understood correctly.)

Significance

This manuscript presents a well-structured study on the regulatory interplay between Cdk and Phosphatase in controlling the degradation of atypical E2Fs, E2F7 and E2F8. The work is relevant in the field of cell cycle regulation and provides new mechanistic insights into how phosphorylation and dephosphorylation govern APC/C-mediated degradation. The use of complementary cell-based and in vitro approaches strengthens the study, and the findings have significant implications for understanding the timing of transcriptional regulation in cell cycle progression.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Referee #1

Evidence, reproducibility and clarity

The study highlights a dephosphorylation switch mediated by PP2A as a critical mechanism for coupling E2F7/8 degradation to mitotic exit and G1 phase. The study is clear and experiments are well conducted with appropriate controls

I have some concerns highlighted below :

1. In this sentence : This intricate network of feedback mechanisms ensures the orderly progression of the cell cycle. What feedback mechanism are the authors referring to?

2. Characterization of disorder in the N-terminal segments of E2F7 and E2F8

What does it mean disorder in this title?

1. In the paragraph on the untimely degradation of E2F8 the authors keep referring to APC/C Cdc20, however the degradation is triggered by the Ken box which is specifically recognised by APC/C Cdh1. Can it be due to another ligase not APC/C?

2. The assays to detect dephosphorylation are rather indirect so it is difficult to establish whether phosphorylation of CDK1 and dephosphorylation by PP2A on the fragments is direct.

3. Although there seems to be a control by phosphorylation and dephosphorylation (which could be indirect), it is difficult to establish the functional consequences of this observation. The authors propose a feedback mechanism which regulates the temporal activation inactivation of E2F7/8 however, there are no evidence in support of this.

Significance

The study is a good and well conducted work to understand the mechanisms regulating degradation of E2F7/8 by APC/C. This is crucial to establish coordinated celll cycle progression. While the hypothesis that disruption of this mechanism is likely responsible for altered cell cycle progression, there are no evidence this is just a back up pathway, whose functional significance could be limited to lack of APC/C Cdh1 activity. These experiments are rather difficult but the authors could comment on the limitation of the study and emphasise the hypothetical alterations which could result from the alterations of the described feedback loop

Two important aspects:

• programming skills (that most people don't have). In the age of vibe coding and LLM-assisted coding, this might finally be possible to change
• most software is closed source. We could demand differently. But actually, "closed source" is less of an issue than a software architecture with open APIs and event hooks.

Reviewer #1 (Public review):

Summary:

The authors assess the impact of E-cigarette smoke exposure on mouse lungs using single-cell RNA sequencing. Air was used as control and several flavors (fruit, menthol, tobacco) were tested. Differentially expressed genes (DEGs) were identified for each group and compared against the air control. Changes in gene expression in either myeloid or lymphoid cells were identified for each flavor and the results varied by sex. The scRNAseq dataset will be of interest to the lung immunity and e-cig research communities, and some of the observed effects could be important. Unfortunately, the revision did not address the reviewers' main concerns about low replicate numbers and lack of validations. The study remains preliminary and no solid conclusions could be drawn about the effects of E-cig exposure as a whole or any flavor-specific phenotypes.

Strengths:

The study is the first to use scRNAseq to systematically analyze the impact of e-cigarettes on the lung. The dataset will be of broad interest.

Weaknesses:

This study had only N=1 biological replicates for the single-cell sequencing data per sex per group and some sex-dependent effects were observed. This could have been remedied by validating key observations from the study using traditional methods such as flow cytometry and qPCR, but the limited number of validation experiments did not support the conclusions of the scRNAseq analysis. An important control group (PG:VG) had extremely low cell numbers and therefore could not be used to derive meaningful conclusions. Statistical analysis is lacking in almost all figures. Overall, this is a preliminary study with some potentially interesting observations.

(1) The only new validation experiment for this revision is the immunofluorescent staining of neutrophils in Figure 4. The images are very low resolution and low quality and it is not clear which cells are neutrophils. S100A8 (calprotectin) is highly abundant in neutrophils but not strictly neutrophil-specific. It's hard to distinguish positive cells from autofluorescence in both ly6g and S100a8 channels. No statistical analysis is presented for the quantified data from this experiment.

(2) The relevance of Fig. 3A and B are unclear since these numbers only reflect the number of cells captured in the scRNAseq experiment and the biological meaning of this data is not explained. Flow cytometry quantification is presented as cell counts but percentage of cells from the CD45+ gate should be shown. No statistical analysis is shown, and flow cytometry results do not support the conclusions of scRNAseq data.

Author response:

The following is the authors’ response to the previous reviews.

Public Reviews:

Reviewer #1 (Public review):

The authors assess the impact of E-cigarette smoke exposure on mouse lungs using single cell RNA sequencing. Air was used as control and several flavors (fruit, menthol, tobacco) were tested. Differentially expressed genes (DEGs) were identified for each group and compared against the air control. Changes in gene expression in either myeloid or lymphoid cells were identified for each flavor and the results varied by sex. The scRNAseq dataset will be of interest to the lung immunity and e-cig research communities and some of the observed effects could be important. Unfortunately, the revision did not address the reviewers' main concerns about low replicate numbers and lack of validations. The study remains preliminary, and no solid conclusions could be drawn about the effects of E-cig exposure as a whole or any flavor-specific phenotypes.

Strengths:

The study is the first to use scRNAseq to systematically analyze the impact of e-cigarettes on the lung. The dataset will be of broad interest.

Weaknesses:

scRNAseq studies may have low replicate numbers due to the high cost of studies but at least 2 or 3 biological replicates for each experimental group is required to ensure rigor of the interpretation. This study had only N=1 per sex per group and some sex-dependent effects were observed. This could have been remedied by validating key observations from the study using traditional methods such as flow cytometry and qPCR, but the limited number of validation experiments did not support the conclusions of the scRNA seq analysis. An important control group (PG:VG) had extremely low cell numbers and was basically not useful. Statistical analysis is lacking in almost all figures. Overall, this is a preliminary study with some potentially interesting observations, but no solid conclusions can be made from the data presented.

The only new validation experiment is the immunofluorescent staining of neutrophils in Figure 4. The images are very low resolution and low quality and it is not clear which cells are neutrophils. S100A8 (calprotectin) is highly abundant in neutrophils but not strictly neutrophil-specific. It's hard to distinguish positive cells from autofluorescence in both Ly6g and S100a8 channels. No statistical analysis in the quantification.

We thank the reviewer for identifying the strengths of this study and pointing out the gaps in knowledge. Overall, our purpose to present this data is to provide the scRNA seq results as a resource to a wider community. We have used techniques like flow cytometry, multianalyte cytokine array and immunofluorescence to validate some of the results. We agree with the reviewer that we were unable to rightly point out the significance of our findings with the immunofluorescent stain in the previous edit. We have revised the manuscript and included the quantification for both Ly6G+ and S100A8+ cells in e-cig aerosol exposed and control lung tissues. Briefly, we identified a marked decrease in the staining for S100A8 (marker for neutrophil activation) in tobacco-flavored e-cig exposed mouse lungs as compared to controls. Upon considering the corroborating evidence from scRNA seq and flow cytometry with regards to increased neutrophil percentages in experimental group and lowered staining for active neutrophils using immunofluorescence, we speculate that exposure to e-cig (tobacco) aerosols may alter the neutrophil dynamics within the lungs. Also, co-immunofluorescence identified a more prominent co-localization of the two markers in control samples as compared to the treatment group which points towards some changes in the innate immune milieu within the lungs upon exposures. Future work is required to validate these speculations.

We have now discussed all the above-mentioned points in the Discussion section of the revised manuscript and toned down our conclusions regarding sex-dependent changes from scRNA seq data.

It is unclear what the meaning of Fig. 3A and B is, since these numbers only reflect the number of cells captured in the scRNAseq experiment and are not biologically meaningful. Flow cytometry quantification is presented as cell counts, but the percentage of cells from the CD45+ gate should be shown. No statistical analysis is shown, and flow cytometry results do not support the conclusions of scRNAseq data.

We thank the reviewer for this question. However, we would like to highlight that scRNA seq and flow cytometry may show similar trends but cannot be identical as one relies on cell surface markers (protein) for identification of cell types, while other is dependent on the transcriptomic signatures to identify the cell types. In our data, for the myeloid cells (alveolar macrophages and neutrophils), the scRNA and flow cytometry data match in trend. However, the trends do not match with respect to the lymphoid cells being studied (CD4 and CD8 T cells). The possible explanation for such a finding could be possible high gene dropout rates in scRNA seq, different analytical resolution for the two techniques and pooling of samples in our single cell workflow. We realize these shortcomings in our analyses and mention it clearly in the discussion as limitation of our work. It is important to note also that cell frequencies identified in scRNA seq just provide wide and indistinct indications which need to be further validated, which we tried to accomplish in our work to some degree. Our flow-based results clearly highlight the sex-specific variations in the immune cell percentages (something we could not have anticipated earlier). In future studies, we will include more replicates to tease out sex-based variations upon acute and chronic exposure to e-cig aerosols.

We have now replotted the graphs in Fig 3A and B and plotted the flow quantification as the percentage of total CD45+ cells. The gating strategy for the flow plots is also included as Figure S6 in the revised manuscript.

Reviewer #2 (Public review):

This study provides some interesting observations on how different flavour e-cigarettes can affect lung immunology; however, there are numerous flaws, including a low replicate number and a lack of effective validation methods, meaning findings may not be repeated. This is a revised article but several weaknesses remain related to the analysis and interpretation of the data.

Strengths:

The strength of the study is the successful scRNA-seq experiment which gives some preliminary data that can be used to create new hypotheses in this area.

Weaknesses:

Although some text weaknesses have been addressed since resubmission, other specific weaknesses remain: The major weakness is the n-number and analysis methods. Two biological n per group is not acceptable to base any solid conclusions. Any validatory data was too little (only cell % data) and not always supporting the findings (e.g. figure 3D does not match 3B/4A). Other examples include:

There aren't enough cells to justify analysis - only 300-1500 myeloid cells per group with not many of these being neutrophils or the apparent 'Ly6G- neutrophils'.

We thank the reviewer for the comment, but we disagree with the reviewer in terms of the justification of analyses. All the flavored e-cig aerosol groups were compared with air controls to deduce the outcomes in the current study. We already acknowledge low sample quality for PGVG group and have only included the comparisons with PGVG upon reviewer’s request which is open to interpretation by the reader.

By that measure, each treatment group (except PGVG group) has over 1000 cells with 24777 genes being analyzed for each cell type, which by the standards of single cell is sufficient. We understand that this strategy should not be used for detection of rare cell populations, which was neither the purpose of this manuscript nor was attempted. We conduct comparisons of broader cell types and mention more samples need to be added in the Discussion section of the revised manuscript.

As for the Ly6G neutrophil category, we don’t only base our results on scRNA analyses but also perform co-immunofluorescence and multi-analyte analyses and use evidence from previous literature to back our outcome. To avoid over-stating our results we have revamped the whole manuscript and ensured to tone down our results with relation to the presence of Ly6G- neutrophils. We do understand that more work is required in the future, but our work clearly shows the shift in neutrophil dynamics upon exposure which should be reported, in our opinion.

The dynamic range of RNA measurement using scRNAseq is known to be limited - how do we know whether genes are not expressed or just didn't hit detection? This links into the Ly6G negative neutrophil comments, but in general the lack of gene expression in this kind of data should be viewed with caution, especially with a low n number and few cells. The data in the entire paper is not strong enough to base any solid conclusion - it is not just the RNA-sequencing data.

We acknowledge this to be a valid point and have revamped the manuscript and toned down our conclusions. However, such limitations exist with any scRNA seq dataset and so must be interpreted accordingly by the readers. We do understand that due to the low cell counts and the limitations with scRNA seq we should not perform DESeq2 analyses for Ly6G+ versus Ly6G- neutrophil categories, which was never attempted at the first place. However, our results with co-immunofluorescence, multianalyte assay and scRNA expression analyses in myeloid cluster do point towards a shift in neutrophil activation which needs to be further investigated. Furthermore, Ly6G deficiency has been linked to immature neutrophils in many previous studies and is not an unlikely outcome that needs to be treated with immense skepticism.

We wish to make this dataset available as a resource to influence future research. We are aware of its limitations and have been transparent with regards to our experimental design, capture strategy, the quality of obtained results, and possible caveats to make it is open for discussion by the readers.

There is no data supporting the presence of Ly6G negative neutrophils. In the flow cytometry only Ly6G+ cells are shown with no evidence of Ly6G negative neutrophils (assuming equal CD11b expression). There is no new data to support this claim since resubmission and the New figures 4C and D actually show there are no Ly6G negative cells - the cells that the authors deem Ly6G negative are actually positive - but the red overlay of S100A8 is so strong it blocks out the green signal - looking to the Ly6G single stains (green only) you can see that the reported S100A8+Ly6G- cells all have Ly6G (with different staining intensities).

We thank the reviewer for this query and do understand the skepticism. We have now quantified the data to provide more clarity for interpretation. As we were using paraffin embedded tissues, some autofluorescence is expected which could explain some of reviewer’s concerns. However we expect that the inclusion of better quality images and quantification must address some of the concerns raised by the reviewer.

Eosinophils are heavily involved in lung macrophage biology, but are missing from the analysis - it is highly likely the RNA-sequence picked out eosinophils as Ly6G- neutrophils rather than 'digestion issues' the authors claim

We thank the reviewer for raising a valid concern. However, the Ly6G- cluster cannot be eosinophils in our case. Literature suggests SiglecF as an important biomarker of eosinophils which was absent in the Ly6G- cluster our in scRNA seq analyses as shown in File S18 and Figure 6B of the revised manuscript. We have now provided a detailed explanation (Lines 476-488; 503-506) of the observed results pertaining to eosinophil population in the revised manuscript to further address some of the concerns raised by this reviewer.

After author comments, it appears the schematic in Figure 1A is misleading and there are not n=2/group/sex but actually only n=1/group/sex (as shown in Figure 6A). Meaning the n number is even lower than the previous assumption.

We concur with reviewers’ valid concern and so are willing to provide this data as a resource for a wider audience to assist future work. Pooling of samples have been practiced by many groups previously to save resources and expense. We did it for the very same reason. It may not be the preferred approach, but it still has its merit considering the vast amount of cell-specific data generated using this strategy. To avoid overstating our results we have ensured to maintain transparency in our reporting and acknowledge all the limitations of this study.

We do not believe that the strength of scRNA seq lies in drawing conclusive results, but to tease our possible targets and direction that need to be validated with more work. In that respect, our study does identify the target cell types and biological processes which could be of importance for future studies.

Reviewer #3 (Public review):

This work aims to establish cell-type specific changes in gene expression upon exposure to different flavors of commercial e-cigarette aerosols compared to control or vehicle. Kaur et al. conclude that immune cells are most affected, with the greatest dysregulation found in myeloid cells exposed to tobacco-flavored e-cigs and lymphoid cells exposed to fruit-flavored e-cigs. The up- and down-regulated genes are heavily associated with innate immune response. The authors suggest that a Ly6G-deficient subset of neutrophils is found to be increased in abundance for the treatment groups, while gene expression remains consistent, which could indicate impaired function. Increased expression of CD4+ and CD8+ T cells along with their associated markers for proliferation and cytotoxicity is thought to be a result of activation following this decline in neutrophil-mediated immune response.

Strengths:

Single cell sequencing data can be very valuable in identifying potential health risks and clinical pathologies of lung conditions associated with e-cigarettes considering they are still relatively new.

Not many studies have been performed on cell-type specific differential gene expression following exposure to e-cig aerosols.

The assays performed address several factors of e-cig exposure such as metal concentration in the liquid and condensate, coil composition, cotinine/nicotine levels in serum and the product itself, cell types affected, which genes are up- or down-regulated and what pathways they control.

Considerations were made to ensure clinical relevance such as selecting mice whose ages corresponded with human adolescents so that data collected was relevant.

Weaknesses:

The exposure period of 1 hour a day for 5 days is not representative of chronic use and this time point may be too short to see a full response in all cell types. The experimental design is not well-supported based on the literature available for similar mouse models. Clinical relevance of this short exposure remains unclear.

We thank the reviewer for this query. However, we would like to emphasize that chronic exposure was never the intention of this study. We wished to design a study for acute nose-only exposure owing to which the study duration was left shorter. Shorter durations limit the stress and discomfort to the animal. The in vivo study using nose-only exposure regimen is still developing with multiple exposure regimen being used by different groups. To our knowledge there is no gold standard of e-cig aerosol exposure which is widely accepted other than the CORESTA recommendations, which we followed. Also, we show in our study how the daily exposure to leached metals vary in a flavor-dependent manner thus validating that exposure regime does need more attention in terms of equal dosing, particle distribution and composition- something we have started doing in our future studies. We have included all the explanations in the revised manuscript (Lines 82-85, 425-435, 648-654).

Several claims lack supporting evidence or use data that is not statistically significant. In particular, there were no statistical analyses to compare results across sex, so conclusions stating there is a sex bias for things like Ly6G+ neutrophil percentage by condition are observational.

We agree with reviewer’s comment and have taken this into consideration. We have now revamped the whole manuscript and toned down most of the sex-based conclusions stated in this work. Having said that, it is important to note that most of the work relying solely on scRNA seq, as is the case for this study, is observational in nature and needs to be assessed bearing this in mind.

Overall, the paper and its discussion are relatively surface-level and do not delve into the significance of the findings or how they fit into the bigger picture of the field. It is not clear whether this paper is intended to be used as a resource for other researchers or as an original research article.

We have now reworked on the Discussion and tried to incorporate more in-depth discussion and the results providing our insights regarding the observations, discrepancies and the possible explanations. We have also made it clear that this paper is intended to be used as a resource by other researchers (Lines 577-579)

The manuscript has some validation of findings but not very comprehensive.

We have now revamped the manuscript. We have Included quantification for immunofluorescence data with better representation of the GO analyses. We have worked on the Results and Discussion sections to make this a useful resource for the scientific community.

This paper provides a strong foundation for follow-up experiments that take a closer look at the effects of e-cig exposure on innate immunity. There is still room to elaborate on the differential gene expression within and between various cell types.

We thank the reviewer for pointing out the strength of this paper. The reason why we refrained from elaborating of the differential gene expressions within and between various cell types was due to low sample number and sequencing depth for this study. However the raw data will be provided with the final publication, which should be freely accessible to the public to re-analyze the data set as they deem fit.

Comments on revisions:

The reviewers have addressed major concerns with better validation of data and improved organization of the paper. However, we still have some concerns and suggestions pertaining to the statistical analyses and justifications for experimental design.

We appreciate the nuance of this experimental design, and the reviewers have adequately commented on why they chose nose-only exposure over whole body exposure. However, the justification for the duration of the exposure, and the clinical relevance of a short exposure, have not been addressed in the revised manuscript.

We thank the editor for this query. We have now addressed this query briefly in Lines 82-85, 425-435, 648-654 of the revised manuscript. We would like to add, however, that we intend to design a study for acute nose-only exposure for this project. Shorter durations limit the stress and discomfort to the animal, owing to which a duration of 1hour per day was chosen. The in vivo study using nose-only exposure regimen is still developing with multiple exposure regimen being used by different groups. Ours is one such study in that direction just intended to identify cell-specific changes upon exposure. Considering our results in Figure 1B showing variations in the level of metals leached in each flavor per day, the appropriate exposure regimen to design a controlled, reproducible experiment needs to be discussed. There could be room for improvement in our strategy, but this was the best regimen that we found to be appropriate per the literature and our prior knowledge in the field.

The presentation of cell counts should be represented by a percentage/proportion rather than a raw number of cells. Without normalization to the total number of cells, comparisons cannot be made across groups/conditions. This comment applies to several figures.

We thank the editor for this comment and have now made the requested change in the revised manuscript.

We appreciate that the authors have taken the reviewers' advice to validate their findings. However, we have concerns regarding the immunofluorescent staining shown in Figure 4. If the red channel is showing a pan-neutrophil marker (S100A8) and the green channel is showing only a subset of neutrophils (LY6G+), then the green channel should have far less signal than the red channel. This expected pattern is not what is shown in the figure, with the Ly6G marker apparently showing more expression than S100A8. Additionally, the FACS data states that only 4-5% of cells are neutrophils, but the red channel co-localizes with far more than 4-5% of the DAPI stain, meaning this population is overrepresented, potentially due to background fluorescence (noise). In addition, some of the shapes in the staining pattern do not look like true neutrophils, although it is difficult to tell because there remains a lot of background staining. The authors need to verify that their S100A8 and Ly6G antibodies work and are specific to the populations they intend to target. It is possible that only the brightest spots are truly S100A8+ or Ly6G+.

We thank the editor for this comment and acknowledge that we may have made broad generalizations in our interpretation of our data previously. We have now revisited the data and quantified the two fluorescence for better interpretation of our results. We have also reassessed our conclusions from this data and reworded the manuscript accordingly. Briefly we believe that Ly6G deficiency could be an indication of the presence of immature neutrophils in the lungs. This is a common process of neutrophil maturation. An active neutrophil population has Ly6G and should also express S100A8 indicating a normal neutrophilic response against stressors. However, our results, despite some autofluorescence which is common with lung tissues, shows a marked decline in the S100A8+ cells in the lung of tobacco-flavored e-cig aerosol exposed mice as compared to air controls. We also do not see prominent co-localization of the two markers in exposed group thus proving a shift in neutrophil dynamics which requires further investigation. We would also like to mention here that S100A8 is predominantly expressed in neutrophils, but is also expressed by monocytes and macrophages, so that could explain the over-representation of these cells in our immunofluorescence results. We have now included this in the Discussion section (Lines 489- 538) of the revised manuscript.