Review coordinated by Life Science Editors Foundation Reviewed by: Dr. Angela Andersen, Life Science Editors Foundation & Life Science Editors Potential Conflicts of Interest: None

PUNCHLINE This preprint reveals a novel mechanism by which nitric oxide (NO) regulates lipid uptake in endothelial cells through nitrosation of the fatty acid transporter CD36. In conditions where endothelial NO is elevated, CD36 is modified at key cysteine residues, which prevents its localization to the plasma membrane and thus inhibits lipid uptake. This nitrosation-based regulation protects endothelial cells from lipid overload while increasing circulating serum lipids. The findings establish a dynamic and reversible regulatory axis—Cav1 → NO → CD36—that links vascular signaling to metabolic control.

BACKGROUND Endothelial cells (ECs), which line the blood vessels, are uniquely positioned as gatekeepers of metabolic exchange—controlling the delivery of nutrients, including fatty acids, from the bloodstream into peripheral tissues. In the setting of metabolic syndrome, a state of chronic nutrient excess, this finely tuned lipid transport system becomes dysregulated. Excessive lipid uptake by ECs leads to lipid accumulation, mitochondrial dysfunction, and progressive endothelial impairment, which in turn contributes to the pathogenesis of cardiovascular and metabolic diseases.

While ECs appear to possess intrinsic protective mechanisms to buffer against lipid overload, the molecular basis of these protective responses is poorly understood. The authors sought to uncover how ECs might actively limit lipid uptake under stress, and what upstream signals trigger this protective state.

QUESTIONS ADDRESSED How do endothelial cells protect themselves from lipid-induced dysfunction during nutrient excess? What regulatory mechanisms allow them to limit lipid uptake under stress?

SUMMARY Reduced endothelial Cav1 leads to increased NO production and, in turn, nitrosation of CD36. This modification prevents CD36 from reaching the plasma membrane, blocking lipid uptake into ECs. As a result, circulating serum lipids increase, but endothelial function is preserved. These findings define NO-mediated nitrosation as a new mechanism of post-translational regulation of CD36, with implications for endothelial health in metabolic disease.

KEY RESULTS Cav1 is downregulated in endothelial cells in obesity Figures 1A–F, Supplementary Fig. 1A–F Goal: Identify genes affected by obesity that regulate endothelial lipid uptake. Outcome: Single-cell RNA-seq of mouse and human adipose tissues reveals consistent downregulation of Cav1 in all endothelial subtypes during obesity (Fig. 1A–F). Supplementary Fig. 1 shows quality control, cell-type identification, and confirmation of downregulated Cav1 expression in both species (Supp. Fig. 1A–F).

Loss of Cav1 increases circulating lipids and decreases EC lipid uptake Figures 2A–K, Supplementary Fig. 2A–E Goal: Determine the physiological effect of Cav1 loss on lipid homeostasis. Outcome: EC-specific Cav1 knockout mice have elevated serum triglycerides, cholesterol, and LDL (Fig. 2E–G), but reduced lipid droplet accumulation in ECs (Fig. 2J). They maintain normal weight and show improved glucose tolerance (Fig. 2H–L). Supplementary Fig. 2 confirms successful endothelial deletion of Cav1 (Supp. Fig. 2A–C) and shows that hyperlipidemia is not due to differences in dietary intake or lipid absorption (Supp. Fig. 2D–E).

Loss of Cav1 elevates NO and suppresses lipid uptake Figures 3A–J, 4A–F, Supplementary Fig. 3A–E Goal: Test whether elevated NO mediates lipid uptake defects. Outcome: Cav1 knockout increases serum nitrate/nitrite (Fig. 3J), reflecting elevated NO. Pharmacologic NO inhibition with L-NAME restores lipid uptake in HAMECs (Fig. 4A) and mouse aorta (Fig. 4B), and reduces serum lipids (Fig. 4C–D). Deletion of eNOS in ECs—but not in RBCs—rescues the phenotype (Fig. 4E–F). Supplementary Fig. 3 shows that Cav1 knockout does not impair vasodilatory responses to acetylcholine and confirms NO elevation by multiple readouts (Supp. Fig. 3A–E).

CD36 mediates endothelial lipid uptake and is regulated by NO Figures 5A–F, Supplementary Fig. 4A–D Goal: Identify whether CD36 is necessary and sufficient for NO-regulated lipid uptake. Outcome: CD36 localizes to Cav1-enriched domains (Fig. 5A) and is required for lipid uptake (Fig. 5C). NO donors suppress CD36-mediated lipid uptake in HEK293T cells (Fig. 5D), and NO induces CD36 nitrosation (Fig. 5E). Pharmacologic CD36 inhibition abolishes the effect of eNOS deletion (Fig. 5F). Supplementary Fig. 4 confirms that CD36 expression is unaltered by NO or Cav1 loss, suggesting the effect is post-translational (Supp. Fig. 4A–D).

CD36 is nitrosated at cysteines 3 and 466, disrupting palmitoylation and lipid uptake Figures 6A–D, 7A–F, Supplementary Fig. 5A–C Goal: Identify the functional nitrosation sites and their impact on trafficking. Outcome: CD36 is nitrosated at C3 and C466. Mutating these residues abolishes nitrosation and restores lipid uptake despite NO exposure (Fig. 6C–D). Nitrosation prevents palmitoylation of CD36 (Fig. 7D), explaining the loss of plasma membrane localization (Fig. 7B–F). Supplementary Fig. 5 shows quantification of CD36 localization shifts (Supp. Fig. 5A–C).

Nitrosation restricts CD36 to the ER and blocks its trafficking Figures 7A–F, Supplementary Fig. 6A–D Goal: Understand the subcellular localization of nitrosated CD36. Outcome: In Cav1-deficient or NO-treated ECs, CD36 remains in the endoplasmic reticulum (ER) (Fig. 7B, 7E). L-NAME restores membrane localization (Fig. 7C, 7F). Supplementary Fig. 6 provides further co-localization data with ER and Golgi markers and quantifies trafficking defects (Supp. Fig. 6A–D).

NO protects ECs from lipid-induced mitochondrial dysfunction and impaired vasodilation Figures 8A–C, Supplementary Fig. 7A–E Goal: Determine the physiological consequence of NO-CD36 signaling. Outcome: Lipid exposure combined with L-NAME leads to mitochondrial dysfunction (Fig. 8A) and impaired vasodilation (Fig. 8C), both rescued by NO. Supplementary Fig. 7 shows full mitochondrial stress test profiles and validation of mitochondrial protein levels (Supp. Fig. 7A–E).

STRENGTHS Defines a novel mechanism linking Cav1, NO, and CD36 to lipid homeostasis

Broadens our understanding of endothelial metabolic self-regulation

Identifies post-translational nitrosation as a reversible toggle on lipid uptake

Uses elegant genetic models, in vivo functional assays, and biochemical rigor

Links vascular NO signaling to metabolic adaptation

Highly relevant to metabolic syndrome, lipedema, and vascular disease

FUTURE WORK & EXPERIMENTAL DIRECTIONS Investigate whether modulating CD36 nitrosation could be therapeutic in hyperlipidemia

Study whether this mechanism contributes to sex differences in metabolic disease

Explore its role in other vascular beds and tissue-specific lipid handling

Test implications for lipedema, a fat-distribution disorder involving endothelial dysfunction

Define how palmitoylation and nitrosation are balanced or dynamically regulated

AUTHORSHIP NOTE This review was drafted with the assistance of ChatGPT (OpenAI) to help organize and articulate key ideas clearly and concisely. I provided detailed prompts, interpretations, and edits to ensure the review reflects an expert understanding of the biology and the paper’s contributions. The final version has been reviewed and approved by me.

FINAL TAKEAWAY This preprint reframes endothelial cells as active regulators of systemic metabolism. By showing that nitrosation of CD36 suppresses lipid uptake and preserves endothelial function under metabolic stress, the authors reveal a previously unrecognized mechanism of cellular protection. This discovery expands our understanding of how ECs maintain homeostasis in nutrient-rich environments and opens new directions for treating lipid-associated diseases like obesity, lipedema, and atherosclerosis.

Review coordinated by Life Science Editors Foundation Reviewed by: Dr. Angela Andersen, Life Science Editors Foundation & Life Science Editors Potential Conflicts of Interest: None

PUNCHLINE Evo 2 is a biological foundation model trained on 9.3 trillion DNA bases across all domains of life. It predicts the impact of genetic variation—including in noncoding and clinically relevant regions—without requiring task-specific fine-tuning. Evo 2 also generates genome-scale sequences and epigenomic architectures guided by predictive models. By interpreting its internal representations using sparse autoencoders, the model is shown to rediscover known biological features and uncover previously unannotated patterns with potential functional significance. These capabilities establish Evo 2 as a generalist model for prediction, annotation, and biological design.

BACKGROUND A foundation model is a large-scale machine learning model trained on massive and diverse datasets to learn general features that can be reused across tasks. Evo 2 is such a model for genomics: it learns from raw DNA sequence alone—across bacteria, archaea, eukaryotes, and bacteriophage—without explicit labels or training on specific tasks. This enables it to generalize to a wide range of biological questions, including predicting the effects of genetic variants, identifying regulatory elements, and generating genome-scale sequences or chromatin features.

Evo 2 comes in two versions: one with 7 billion parameters (7B) and a larger version with 40 billion parameters (40B). These numbers reflect the number of trainable weights in the model and influence its capacity to learn complex patterns. Both models were trained using a context window of up to 1 million tokens—where each token is a nucleotide—allowing the model to capture long-range dependencies across entire genomic regions.

Evo 2 learns via self-supervised learning, a method in which the model learns to predict masked or missing DNA bases in a sequence. Through this simple but powerful objective, the model discovers statistical patterns that correspond to biological structure and function, without being told what those patterns mean.

QUESTION ADDRESSED Can a large-scale foundation model trained solely on genomic sequences generalize across biological tasks—such as predicting mutational effects, modeling gene regulation, and generating realistic genomic sequences—without supervision or task-specific tuning?

SUMMARY The authors introduce Evo 2, a foundational model for genomics that generalizes across DNA, RNA, and protein tasks. Without seeing any biological labels, Evo 2 learns the sequence rules governing coding and noncoding function, predicts variant effects—including in BRCA1/2 and splicing regions—and generates full-length genomes and epigenome profiles. It also enables epigenome-aware sequence design by coupling sequence generation with predictive models of chromatin accessibility.

To probe what the model has learned internally, the authors use sparse autoencoders (SAEs)—a technique that compresses the model’s internal activations into a smaller set of interpretable features. These features often correspond to known biological elements, but importantly, some appear to capture novel, uncharacterized patterns that do not match existing annotations but are consistently associated with genomic regions of potential functional importance. This combination of rediscovery and novelty makes Evo 2 a uniquely powerful tool for exploring both the known and the unknown genome.

KEY RESULTS Evo 2 trains on vast genomic data using a novel architecture to handle long DNA sequences Figures 1 + S1 Goal: Build a model capable of representing entire genomic regions (up to 1 million bases) from any organism. Outcome: Evo 2 was trained on 9.3 trillion bases using a hybrid convolution-attention architecture (StripedHyena 2). The model achieves long-context recall and strong perplexity scaling with increasing sequence length and model size.

Evo 2 predicts the impact of mutations across DNA, RNA, and protein fitness Figures 2A–J + S2–S3 Goal: Assess whether Evo 2 can identify deleterious mutations without supervision across diverse organisms and molecules. Outcome: Evo 2 assigns lower likelihoods to biologically disruptive mutations—e.g., frameshifts, premature stops, and non-synonymous changes—mirroring evolutionary constraint. Predictions correlate with deep mutational scanning data and gene essentiality assays. Evo 2 embeddings also support highly accurate exon-intron classifiers.

Clarification: “Generalist performance across DNA, RNA, and protein tasks” means that Evo 2 can simultaneously make accurate predictions about the functional impact of genetic variants on transcription, splicing, RNA stability, translation, and protein structure—without being specifically trained on any of these tasks.

Evo 2 achieves state-of-the-art performance in clinical variant effect prediction Figures 3A–I + S4 Goal: Evaluate Evo 2's ability to predict pathogenicity of human genetic variants. Outcome: Evo 2 matches or outperforms specialized models on coding, noncoding, splicing, and indel variants. It accurately classifies BRCA1/2 mutations and generalizes to novel variant types. When paired with supervised classifiers using its embeddings, it achieves state-of-the-art accuracy on BRCA1 variant interpretation.

Evo 2 representations reveal both known and novel biological features through sparse autoencoders Figures 4A–G + S5–S7 Goal: Understand what Evo 2 has learned internally. Outcome: Sparse autoencoders decompose Evo 2’s internal representations into distinct features—many of which align with well-known biological elements such as exon-intron boundaries, transcription factor motifs, protein secondary structure, CRISPR spacers, and mobile elements. Importantly, a subset of features do not correspond to any known annotations, yet appear repeatedly in biologically plausible contexts. These unannotated features may represent novel regulatory sequences, structural motifs, or other functional elements that remain to be characterized experimentally.

Note: Sparse autoencoders are neural networks that reduce high-dimensional representations to a smaller set of features, enforcing sparsity so that each feature ideally captures a distinct biological signal. This approach enables mechanistic insight into what the model “knows” about sequence biology.

Evo 2 generates genome-scale sequences with realistic structure and content Figures 5A–L + S8 Goal: Assess whether Evo 2 can generate complete genome sequences that resemble natural ones. Outcome: Evo 2 successfully generates mitochondrial genomes, minimal bacterial genomes, and yeast chromosomes. These sequences contain realistic coding regions, tRNAs, promoters, and structural features. Predicted proteins fold correctly and recapitulate functional domains.

Evo 2 enables design of DNA with targeted epigenomic features Figures 6A–G + S9 Goal: Use Evo 2 to generate DNA sequences with user-defined chromatin accessibility profiles. Outcome: By coupling Evo 2 with predictors like Enformer and Borzoi, the authors guide generation to match desired ATAC-seq profiles. Using a beam search strategy—where the model explores and ranks multiple possible output sequences—it generates synthetic DNA that encodes specific chromatin accessibility patterns, such as writing “EVO2” in open/closed chromatin space.

STRENGTHS First large-scale, open-source biological foundation model trained across all domains of life

Performs well across variant effect prediction, genome annotation, and generative biology

Demonstrates mechanistic interpretability via sparse autoencoders

Learns both known and novel biological features directly from raw sequence

Unsupervised learning generalizes to clinical and functional genomics

Robust evaluation across species, sequence types, and biological scales

FUTURE WORK & EXPERIMENTAL DIRECTIONS Expand training to include viruses that infect eukaryotic hosts: Evo 2 currently excludes these sequences, in part to reduce potential for misuse and due to their unusual nucleotide structure and compact coding. As a result, Evo 2 performs poorly on eukaryotic viral sequence prediction and generation. Including these genomes could expand its applications in virology and public health.

Empirical validation of novel features: Use CRISPR perturbation, reporter assays, or conservation analysis to test Evo 2-derived features that don’t align with existing annotations.

Targeted mutagenesis: Use Evo 2 to identify high-impact or compensatory variants in disease-linked loci, and validate using genome editing or saturation mutagenesis.

Epigenomic editing: Validate Evo 2-designed sequences for chromatin accessibility using ATAC-seq or synthetic enhancer assays.

Clinical applications: Fine-tune Evo 2 embeddings to improve rare disease variant interpretation or personalized genome annotation.

Synthetic evolution: Explore whether Evo 2 can generate synthetic genomes with tunable ecological or evolutionary features, enabling testing of evolutionary hypotheses.

AUTHORSHIP NOTE This review was drafted with support from ChatGPT (OpenAI) to help organize and articulate key ideas clearly and concisely. I provided detailed prompts, interpretations, and edits to ensure the review reflects an expert understanding of the biology and the paper’s contributions. The final version has been reviewed and approved by me.

FINAL TAKEAWAY Evo 2 is a breakthrough in foundation models for biology—offering accurate prediction, functional annotation, and genome-scale generation, all learned from raw DNA sequence. By capturing universal patterns across life, and identifying both well-characterized and unknown sequence features, Evo 2 opens powerful new directions in evolutionary biology, genomics, and biological design. Its open release invites widespread use and innovation across the life sciences.

Review coordinated by Life Science Editors Foundation Reviewed by: Dr. Angela Andersen, Life Science Editors Foundation & Life Science Editors. Potential Conflicts of Interest: None.

PUNCHLINE: Fucoidan, a dietary polysaccharide derived from brown seaweed, is identified as a dual-function activator of SIRT6, enhancing both deacetylase and mono-ADP-ribosylation (mADPr) activity. In aged mice, fucoidan supplementation extends lifespan in males, reduces frailty in both sexes, and restores youthful chromatin and immune profiles through SIRT6-dependent mechanisms—highlighting its potential as a natural longevity therapeutic.

BACKGROUND: SIRT6 is a chromatin-associated enzyme that safeguards genomic integrity, represses retrotransposons like LINE1, and modulates inflammation and metabolism—functions tightly linked to aging. While overexpression of SIRT6 extends lifespan in mice, loss-of-function causes rapid aging and early death. Safe, pharmacologically tractable SIRT6 activators have been limited, and none have been shown to activate both major SIRT6 enzymatic functions. Fucoidan, a sulfated polysaccharide from brown algae consumed widely in high-longevity populations like Japan and South Korea, was previously shown to enhance SIRT6 deacetylase activity in vitro. This study explores its in vivo efficacy, enzymatic specificity, and potential to slow aging through chromatin and immune system rejuvenation.

QUESTION ADDRESSED:

Can a safe, natural compound be used to activate SIRT6 in vivo and, through this activation, extend lifespan and healthspan?

SUMMARY: The authors demonstrate that fucoidan robustly activates SIRT6 enzymatic functions, uniquely enhancing both deacetylation and mono-ADP-ribosylation (mADPr) activity—the latter previously associated with enhanced longevity in human centenarians. In aged wild-type mice, midlife fucoidan supplementation significantly extends lifespan in males and slows frailty progression in both sexes without affecting body weight. Fucoidan reduces epigenetic age, suppresses LINE1 retrotransposons, and restores immune homeostasis via increased lymphoid cell fractions and reduced inflammatory cytokines—effects absent in SIRT6 knockout mice. Multi-omic profiling reveals transcriptional and epigenetic changes resembling SIRT6 overexpression and opposing aging trajectories, particularly in male tissues.

KEY RESULTS

Fucoidan is a rare natural compound that activates both of SIRT6’s key enzymatic activities—unlike other known activators.

Figure 1 + Figure S1A–B: Fucoidan is a dual-function activator of SIRT6

In vitro assays demonstrated that fucoidan robustly stimulates SIRT6 deacetylase and mono-ADP-ribosylation (mADPr) activity.

Among various small molecules tested, only fucoidan enhanced both functions—L-fucose (its monomer) was ineffective.

F. vesiculosus extract showed the strongest activation, with effects saturating between 0.2–0.5 mg/mL.

Other known SIRT6 deacetylase activators (e.g., MDL-800) either had no effect or inhibited mADPr activity, underscoring fucoidan’s unique dual role.

Midlife fucoidan treatment increases lifespan in male mice and slows frailty in both sexes without affecting body weight.

Figure 2A–D + Figure S1A–B + Figure S2A–B: Fucoidan extends male lifespan and reduces frailty in both sexes

Male mice showed a 13% increase in median lifespan (p = 0.009); the effect in females was not significant.

Monthly frailty scoring revealed slower frailty progression in both males (p = 0.046) and females (p = 0.006), with improvements seen across multiple organ systems.

Epigenetic clock analysis at 26 months confirmed reduced biological age in treated mice (p = 0.037).

Body mass was unaffected, ruling out calorie restriction as a confounding factor.

No benefit was observed in SIRT6 knockout mice (Figure S2A), confirming the effects are SIRT6-dependent.

H3K9 acetylation, a SIRT6 target, was reduced in treated lung and liver tissues (Figure S2B).

Fucoidan reprograms the immune landscape in aging males, increasing lymphoid cell fractions and suppressing pro-inflammatory cytokines.

Figure 3A–E + Figure S3A–D: Fucoidan modulates immune composition and suppresses inflammation—especially in males

In 22-month-old male mice, blood RNA-seq showed 2,272 genes downregulated and 926 upregulated; females showed no significant changes.

Downregulated pathways included interferon signaling, myeloid activation, and coagulation, while upregulated genes promoted B and T cell differentiation and RNA processing.

Plasma cytokines (TNFα, IL-6, IL-1β, IFNγ) were significantly lower in treated males, but increased slightly in females, suggesting a sex-specific immune modulation.

Immune cell deconvolution showed increased lymphoid and decreased myeloid populations in males—indicating reversal of the age-related myeloid skew.

In male tissues, fucoidan induces gene expression programs that mirror SIRT6 overexpression and oppose aging trajectories.

Figure 4A–F + Figure S4A–B + Figure S5A–D: Fucoidan mimics SIRT6 overexpression and counteracts aging-related gene expression in males

In male lungs, fucoidan’s transcriptomic effects were negatively correlated with aging signatures from Tabula Muris Senis, particularly in protein folding genes.

In male livers, gene expression changes were positively correlated with those from SIRT6 overexpression studies.

Key inflammatory genes like Saa1/2 and Orm2 were strongly downregulated, matching systemic reductions in inflammatory cytokines.

In female tissues, fucoidan either mimicked aging or had minimal effects, reinforcing the male-specific efficacy of the intervention.

Fucoidan represses transposable elements and protects against oxidative stress through enhanced LINE1 silencing and reduced p21 expression.

Figure 5A–C + Figure S5E: Fucoidan suppresses LINE1 transposons and protects against genotoxic stress

In lungs, multi-omic profiling (RNA-seq, ATAC-seq, MeDIP-seq) showed widespread LINE1 repression at the transcriptional, chromatin accessibility, and methylation levels.

In livers, the pattern was less consistent across data types.

In a paraquat-induced oxidative stress model, fucoidan-fed mice showed blunted LINE1 reactivation and reduced expression of p21 (CDKN1a)—a marker of DNA damage response—highlighting improved stress resilience via chromatin stabilization.

STRENGTHS:

First study to demonstrate dual enzymatic activation of SIRT6 by a natural compound.

Shows lifespan and healthspan extension in aged animals with midlife intervention.

Integrates multi-omics, chromatin biology, inflammation, and organismal physiology.

Robust sex-specific analysis, revealing differential molecular and systemic responses.

Confirms SIRT6 dependency using knockout models and known substrates.

FUTURE WORK:

What are the minimal active structures in fucoidan responsible for SIRT6 activation?

Can SIRT6-mediated chromatin remodeling by fucoidan reverse age-related disease phenotypes?

Could selective derivatives be developed to target specific SIRT6 activities?

Would clinical trials in elderly humans show benefits in frailty, LINE1 expression, or epigenetic aging?

How do sex hormones or metabolic differences modulate the fucoidan response?

FINAL TAKEAWAY: This study establishes fucoidan as a natural and potent dual-activator of SIRT6 that enhances chromatin stability, represses transposable elements, and improves aging phenotypes in vivo. The work elegantly links SIRT6 enzymatic activity to systemic aging outcomes and opens the door to dietary or pharmacological interventions that target aging at the level of chromatin organization and genome defense. Fucoidan’s strong safety profile and traditional dietary use suggest rapid translational potential in human aging research.

Review coordinated by Life Science Editors Foundation Reviewed by: Dr. Angela Andersen, Life Science Editors Foundation & Life Science Editors Potential Conflicts of Interest: None

PUNCHLINE Prostate cancer–associated fibroblasts (CAFs) exhibit conserved and quantifiable differences in morphology and biomechanics compared to matched non-malignant fibroblasts (NPFs). These morphomechanical features—particularly increased stiffness, volume, and nuclear elongation—are correlated with transcriptional programs and clinical outcomes, positioning fibroblast biophysics as a potential biomarker and therapeutic target in prostate cancer.

BACKGROUND Tumor progression is tightly intertwined with the tumor microenvironment (TME), where CAFs play a key role by remodeling the extracellular matrix and altering tissue mechanics. While bulk tissue stiffness has been studied extensively in cancer, the mechanical properties of individual CAFs—and their consistency across patients and link to clinical outcomes—are not well defined. The study leverages a rare resource: 35 pairs of matched CAF and NPF primary cultures from radical prostatectomy specimens, enabling a systematic comparison of morphomechanical traits and their clinical relevance.

QUESTIONS ADDRESSED Do prostate CAFs exhibit consistent morphomechanical changes compared to matched NPFs?

Are these features linked to patient outcomes or tumor grade?

Can CAF biomechanics be modulated by signaling pathways or therapeutic agents?

Do these traits reflect distinct transcriptional signatures, particularly the myofibroblast-like (myCAF) phenotype?

SUMMARY Using real-time deformability cytometry (RT-DC), atomic force microscopy (AFM), and high-content imaging, the authors show that CAFs are consistently stiffer, larger, and more elongated than NPFs across patients. A principal component–derived morphomechanical score integrates five features (volume, Young’s modulus, nuclear area, nuclear circularity, and F-actin alignment) and stratifies patients by clinical outcome. Transcriptomic correlates reveal a link to microtubule dynamics and myCAF signatures. Notably, CAF stiffness can be altered by TGF-β signaling and anti-cancer agents, suggesting potential avenues for stromal reprogramming.

KEY RESULTS CAFs Exhibit Conserved Biophysical Phenotypes

Across 35 matched pairs, CAFs are consistently stiffer (RT-DC, AFM) and larger in both nuclear and cytoplasmic dimensions.

F-actin fibers in CAFs are more aligned, and nuclei more elongated, than in NPFs.

These features were independent of tumor grade but associated with clinical relapse.

A Composite Morphomechanical Score Correlates with Outcome

PCA of the five morphomechanical traits yields a score that stratifies patients.

Higher scores are associated with biochemical and clinical relapse.

Transcriptional Correlates of Biomechanical States

49 genes correlate with the morphomechanical score; top hits include NAV3, MYOCD, and ARHGAP28, implicating cytoskeletal remodeling.

Enrichment for microtubule and myCAF signatures supports a contractile phenotype underlying mechanical changes.

Biophysical Traits Are Pharmacologically Modifiable

TGF-β1 increases nuclear size and stiffness in CAFs, while TGF-β inhibition reduces stiffness.

Docetaxel and axitinib also modulate fibroblast biophysics, suggesting that approved cancer therapies may influence the stromal compartment.

STRENGTHS Large, well-annotated cohort with matched CAF/NPF pairs.

Rigorous integration of imaging, biophysical assays, and transcriptomics.

Clear demonstration of phenotypic consistency and clinical relevance.

Insight into mechanobiological regulation and therapeutic modulation of CAFs.

FUTURE WORK Can morphomechanical profiling be applied to in situ biopsies or circulating fibroblasts?

Is the morphomechanical phenotype of CAFs reversible, and does this influence tumor behavior?

How do CAF mechanics interface with epithelial cell signaling and immune exclusion?

Could targeted reprogramming of CAFs (e.g., via TGF-β blockade) improve therapeutic response?

FINAL TAKEAWAY This study establishes that prostate CAFs are not only functionally distinct but also physically distinct in measurable and clinically relevant ways. The morphomechanical phenotype of CAFs emerges as a novel dimension of tumor biology—potentially serving as both a biomarker and a therapeutic target. By placing CAF biomechanics in the context of differentiation state, gene expression, and treatment response, the work opens new avenues for integrating stromal biology into precision oncology.

Review coordinated by Life Science Editors Foundation Reviewed by: Dr. Angela Andersen, Life Science Editors Foundation & Life Science Editors. Potential Conflicts of Interest: None.

PUNCHLINE: Chromatin organization, orchestrated by the epigenetic reader MeCP2, governs nuclear stiffness in a concentration- and differentiation-dependent manner—providing a mechanistic link between heterochromatin compaction, mechanotransduction, and the severity of Rett syndrome phenotypes.

BACKGROUND: Nuclear mechanics are critical for how cells sense and respond to physical forces, yet most attention has focused on the cytoskeleton and lamin network. Chromatin, particularly heterochromatin, has been considered a secondary contributor, despite its dominant nuclear occupancy. MeCP2, a methyl-CpG-binding protein abundantly expressed in neurons and mutated in Rett syndrome, is known to cluster heterochromatin and modulate chromatin structure. Rett syndrome mutations impact MeCP2's binding and chromatin compaction abilities, but changes in gene expression do not strongly correlate with disease severity. This study proposes an alternative hypothesis: MeCP2 mutations impair the physical properties of the nucleus via disorganized chromatin architecture, offering a new framework to understand the mechanobiology of neuronal development and disease.

QUESTIONS ADDRESSED:

How does MeCP2 concentration influence nuclear stiffness, and is this linked to chromatin compaction?

Do Rett syndrome mutations disrupt MeCP2’s role in nuclear mechanics?

Is chromatin-mediated nuclear stiffness regulated independently of canonical mechanotransduction gene expression?

SUMMARY: Using atomic force microscopy (AFM) to directly measure nuclear stiffness in purified nuclei, the authors show that MeCP2 levels strongly correlate with increased nuclear stiffness. MeCP2 overexpression in myoblasts leads to heterochromatin clustering and ~15–20x increases in nuclear stiffness. During neural differentiation, wild-type cells exhibit dramatic stiffening of nuclei, which is largely abolished in MeCP2 knockout cells. Rett syndrome mutations, including R106W and T158M, differentially impair this function—with T158M inducing nuclear softening even below baseline. Importantly, these mechanical changes occur without global alterations in expression of mechanosensitive genes, implicating chromatin structure itself as a mechanical determinant.

KEY RESULTS

Chromatin Stiffness Is Cytoskeleton-Independent Nuclei purified from cells retain stiffness comparable to the nuclear region of intact cells, showing that chromatin contributes autonomously to nuclear mechanics. In the absence of cytoskeletal components, MeCP2-dependent changes remain robust.

MeCP2 Induces Heterochromatin Compaction and Increases Nuclear Stiffness MeCP2 clustering activity scales with concentration: untransfected myoblasts show 1.4 kPa stiffness, while MeCP2-overexpressing nuclei reach 23.5 kPa. Heterochromatin becomes fewer in number but larger in volume, indicating fusion and compaction.

MeCP2 Is Required for Nuclear Stiffening During Neural Differentiation Differentiation of ESCs into neurons leads to a ~10x increase in nuclear stiffness in wild-type cells, but not in MeCP2 knockouts. NSCs and neurons from KO mice show both impaired heterochromatin clustering and lower stiffness, especially at timepoints when MeCP2 expression peaks in wild-type neurons.

Rett Syndrome Mutations Impair MeCP2-Dependent Stiffening Of 9 Rett-linked mutations tested, several (e.g., R106W, T158M) failed to increase nuclear stiffness, clustering with untransfected controls. Other variants (e.g., A140V) retained or exaggerated MeCP2-like effects, correlating with milder phenotypes.

Mechanostiffness Is Not Driven by Mechanotransduction Gene Expression RNA-seq and qPCR reveal only minor changes in mechanotransduction-related genes (e.g., Tgfbr1, Notch2), and ChIP-seq does not show MeCP2 binding at these loci—supporting a model where stiffness arises from structural chromatin effects, not transcriptional changes.

STRENGTHS:

Direct mechanical measurements using AFM in purified nuclei across multiple cell states.

Dissects MeCP2 function independently of its transcriptional effects.

Uses Rett syndrome mutants to connect biophysics to disease severity.

Establishes chromatin structure as an autonomous determinant of nuclear stiffness.

Integrates epigenetics, mechanics, and disease in a novel conceptual framework.

FUTURE WORK:

Can modulating MeCP2 levels or chromatin compaction rescue mechanical defects in Rett models?

Do neurons use MeCP2-mediated stiffness to regulate mechanosensitive gene expression or signaling?

Are similar chromatin-stiffness mechanisms active in other cell types or diseases?

Could small molecules targeting chromatin modifiers restore nuclear mechanics in disease?

FINAL TAKEAWAY: This study redefines the role of chromatin—particularly MeCP2-organized heterochromatin—as a critical regulator of nuclear stiffness during neuronal differentiation. By decoupling mechanical properties from transcriptional changes, it provides a mechanistic explanation for how MeCP2 mutations contribute to the pathophysiology of Rett syndrome. These findings suggest that chromatin organization is not merely a regulator of gene expression but also a physical architect of the cell’s mechanical identity.

Review coordinated by Life Science Editors Foundation Reviewed by: Dr. Angela Andersen, Life Science Editors Foundation & Life Science Editors. Potential Conflicts of Interest: None.

PUNCHLINE: Neural differentiation during early human brain development is accompanied by precise and dynamic expression of tRNA-derived fragments (tDRs), revealing a new regulatory layer shaped by tRNA cleavage, modification, and sequence features.

BACKGROUND: tRNA-derived fragments (tDRs), once considered byproducts of degradation, are now recognized as functional regulators implicated in diverse biological contexts—from metabolic diseases to cancer and neurovascular pathology. For instance, tDR tRF-3001a promotes neurovascular dysfunction in diabetic retinopathy via miRNA-like regulation, CAT1 tDR stabilizes NOTCH2 to drive tumorigenesis, and tRF-Val-CAC-024 tDR enhances glycolysis and metastasis in lung adenocarcinoma. These studies show tDRs can modulate gene expression, protein interactions, and cellular phenotypes. Despite increasing recognition of tDRs in pathology, their roles in normal human development—particularly neurodevelopment—remain poorly understood. This study addresses this gap by profiling tDR expression in human cerebral cortex organoids to explore how tRNA processing and modifications contribute to the emergence of neural cell identity.

QUESTIONS ADDRESSED: Do tRNA-derived fragments exhibit neural-specific expression patterns during early human brain development?

What tRNA features (isotypes, sequences, modifications) are associated with tDR enrichment in neural versus stem-like states?

SUMMARY: By applying ARM-seq (AlkB-facilitated RNA methylation sequencing) to cerebral organoids at progressive stages of cortical development, the authors mapped a dynamic landscape of tDRs. They identified 3′ tDRs from specific tRNA isotypes (e.g., Ala, Gly, Arg, SeC) that are selectively enriched in neurons, while 5′ tDRs dominate in earlier stem-like states. These neural-specific tDRs display conserved sequence motifs, modified nucleotides (e.g., m²²G26, m¹I37), and structured read coverage profiles, suggesting regulated processing rather than stochastic degradation. Clustering analyses revealed distinct tDR expression programs correlated with neural identity and modification signatures. These findings suggest that tRNA processing contributes to the RNA-based regulatory repertoire of human neurodevelopment.

KEY RESULTS

Cerebral Organoids Model Human Neurodevelopment The authors validated their organoid model using immunostaining and small RNA profiles, confirming progression from stem cells to radial glia and cortical neurons over a 70-day differentiation period. Neural markers and expected small RNAs (e.g., miR-9, SNORD115) were enriched at late time points.

tDR Profiles Are Dynamic and Isoform-Specific ARM-seq uncovered widespread and dynamic changes in tDRs across development. Notably, 3′ tDRs from Ala, Gly, and SeC tRNAs increase during neurogenesis, while 5′ tDRs from His, Thr, and Glu decrease. These changes were isodecoder-specific and often involved switch-like transitions in dominant fragment types.

Neural-Specific tDRs Have Unique Structural Features tDRs enriched in neural samples shared conserved cleavage patterns and modifications. Neural-specific fragments clustered together in UMAP space and showed enrichment for motifs associated with known RNA -modifying enzymes (e.g., TRMT1, PUS3). Sequence conservation at key cleavage sites (e.g., position 40) suggested modified processing routes.

tDR Clusters Reflect Functional States tDRs grouped into neural-favored, stem-favored, and neutral clusters based on read coverage, modification profiles, and sequence context. These clusters were dominated by specific tRNA isotypes, reinforcing a link between tDR origin and cell state.

STRENGTHS: First map of neural-specific tDRs in human brain development using an organoid model and optimized small RNA sequencing.

Combines tRNA modifications and sequence features to explain stage-specific tDR generation.

Leverages ARM-seq with AlkB treatment to overcome known biases in modified tRNA sequencing.

Provides mechanistic hypotheses about how sequence motifs and modifications guide selective tDR biogenesis.

Connects developmental RNA processing to emerging roles of tDRs in disease and physiology, as shown in tRF-3001a, CAT1, and tRF-Val-CAC-024 studies.

FUTURE WORK: What are the specific targets and functions of neural-enriched tDRs?

Do RNA modification enzymes like TRMT1 or PUS3 regulate tDR production during neurodevelopment?

Could dysregulated tDR profiles contribute to neurodevelopmental disorders similar to their roles in diabetic or cancer pathology?

FINAL TAKEAWAY: This study adds a developmental perspective to the expanding field of tRNA fragmentation biology. It identifies a network of neural-specific tDRs that may play regulatory roles during human brain development. It builds on the concept of tDRs as programmed, functional molecules, highlighting a previously unrecognized layer of RNA-based regulation in neural differentiation—laying the foundation for future studies into how tRNA processing contributes to human brain function and disease.

Review coordinated by Life Science Editors Foundation Reviewed by: Dr. Angela Andersen, Life Science Editors Foundation & Life Science Editors. Potential Conflicts of Interest: None.

PUNCHLINE: A stress-responsive p38 signaling pathway in choanoflagellates reveals deep evolutionary conservation of cellular stress adaptation mechanisms—functionally linking unicellular and multicellular stress responses.

BACKGROUND: Cells across all domains of life must sense and respond to environmental stress, and kinase signaling pathways play a critical role in mediating these responses. In animals, p38 mitogen-activated protein kinase (MAPK) is a well-known regulator of stress responses, cell proliferation, and differentiation. However, its evolutionary origins remain unclear. Choanoflagellates—the closest living relatives of animals—provide a unique window into the early evolution of signaling pathways before multicellularity. While previous studies have identified kinase homologs in choanoflagellates, their functional roles have been difficult to study due to limited genetic tools. This study uses high-throughput small-molecule screening and CRISPR-based gene editing in Salpingoeca rosetta to systematically dissect p38 kinase signaling in response to environmental stress.

Questions Addressed: How do kinases regulate stress responses in choanoflagellates? Can human kinase inhibitors be repurposed to probe kinase function in choanoflagellates? SUMMARY: This study functionally characterizes a stress-responsive p38 kinase pathway in choanoflagellates, demonstrating that kinase signaling in unicellular organisms plays a key role in environmental stress adaptation. Using a high-throughput screen of 1,255 human kinase inhibitors, the authors identified 95 compounds that disrupt S. rosetta proliferation. By focusing on sorafenib, a known human kinase inhibitor, they discovered that p38 kinase in S. rosetta is activated by heat shock and other stressors, revealing an ancient and conserved function for this pathway.

Key Results 1. Kinase Inhibitor Screening Identifies Regulators of S. rosetta Proliferation A comprehensive kinase inhibitor screen was conducted using 1,255 human kinase inhibitors. 95 inhibitors significantly affected S. rosetta cell growth, suggesting deep conservation of kinase function between choanoflagellates and animals. The library covered all major kinase families, and flow cytometry and imaging validated inhibitor effects.

1. Sorafenib Inhibits p38 Kinase and Blocks Stress-Induced Phosphorylation S. rosetta p38 kinase was identified as a sorafenib target, supporting its role in stress signaling. Heat shock increases p38 phosphorylation, but this activation is blocked by sorafenib, confirming a conserved stress-responsive pathway. p38 kinases in S. rosetta share critical catalytic residues with human p38, further supporting functional conservation.

2. p38 Activation is Stress-Specific and Not Required for Proliferation While p38 is activated by heat shock and oxidative stress, its inhibition does not prevent S. rosetta proliferation. CRISPR knockout of p38 (Sr-p38¹⁻¹⁵) confirmed that p38 activation is required for stress response but not cell division.

3. p38 Kinase Function Precedes Multicellularity The study reveals that p38’s role in stress adaptation predates animals, suggesting that stress responses were critical for early eukaryotic evolution. p38 homologs are present across choanoflagellates, reinforcing its ancient function.

STRENGTHS: Bridges a Functional Gap in Evolutionary Biology. This study moves beyond comparative genomics by functionally testing kinase signaling in a unicellular organism, shedding light on the ancestral origins of stress pathways.

High-Throughput Chemical Genetics as a Tool for Evolutionary Biology. Using human kinase inhibitors to probe choanoflagellate signaling is an innovative approach that extends the power of small-molecule screening beyond traditional model organisms.

p38 MAPK as a Conserved Stress Sensor. The discovery that choanoflagellates use p38 signaling to respond to stress suggests that stress adaptation mechanisms evolved before multicellularity—a key insight into early eukaryotic evolution.

Biomedical and Biotechnological Implications. Understanding how stress signaling evolved could have implications for drug targeting in diseases like cancer and neurodegeneration, where kinase dysregulation plays a role.

FUTURE WORK: • Does This Apply to Other Kinases? • How Does p38 Interact with Other Stress Pathways? • Do other unicellular relatives of animals use p38 for stress signaling? • How does p38 respond to other environmental stressors (e.g., salinity, bacterial signals)?

FINAL TAKEAWAY: This study functionally validates a stress-responsive p38 signaling pathway in choanoflagellates, providing compelling evidence that key elements of stress adaptation predate multicellularity. Beyond evolutionary implications, this work pioneers the use of kinase inhibitors to probe non-model organisms, opening up new avenues for studying the origins of complex cellular regulation.

Review coordinated by Life Science Editors Foundation Reviewed by: Dr. Angela Andersen, Life Science Editors Foundation & Life Science Editors. Potential Conflicts of Interest: None.

PUNCHLINE: tRNA Synthetase Inhibition Paradoxically Blocks Stress Granule Formation by Causing Unresolved Ribosome Stalling Despite Activation of the Integrated Stress Response.

BACKGROUND: Stress granules (SGs) and P-bodies (PBs) are dynamic ribonucleoprotein (RNP) condensates that form in response to cellular stress and contribute to post-transcriptional gene regulation. SGs are implicated in various physiological and pathological contexts, including neurodegenerative diseases, viral infections, and cancer. Mutations in proteins involved in SG dynamics have been implicated in Charcot-Marie-Tooth disease (CMT2), amyotrophic lateral sclerosis (ALS), and frontotemporal dementia (FTD). The assembly of SGs and PBs is thought to depend on sequestering translationally repressed mRNAs following translational initiation inhibition. The integrated stress response (ISR) mediates translational control under stress via phosphorylation of eIF2α, leading to global translation suppression and the formation of SGs. Ribosome stalling and stress-induced ISR activation should facilitate SG formation, but SGs require ribosome-free mRNAs, and trapped ribosomes block SG assembly. Hypothesis: Persistent stalled ribosomes due to tRNA synthetase inhibition prevent SG and PB assembly. • How does tRNA synthetase inhibition affect the formation of stress-induced RNP granules, including SGs and PBs? • Does the uncoupling of ISR activation from RNP granule assembly indicate a fundamental regulatory mechanism of stress responses?

SUMMARY: This study demonstrates that tRNA synthetase activity is crucial for stress granule (SG) and P-body (PB) formation, challenging the idea that integrated stress response (ISR) activation alone is sufficient. The authors show that tRNA synthetase inhibition prevents SG/PB assembly by inducing persistent ribosome stalling, which traps mRNAs and disrupts RNP granule formation. By uncoupling ISR activation from stress granule assembly, these findings refine our understanding of how translation and RNP granule dynamics respond to stress, with significant implications for neurodegenerative diseases and therapeutic strategies.

Key Results * • tRNA Synthetase Inhibition Activates ISR but Prevents SG and PB Assembly * o While ISR activation via eIF2α phosphorylation typically leads to SG formation, the inhibition of tRNA synthetase paradoxically prevents it. * o tRNA synthetase inhibitors (e.g., halofuginone, borrelidin) strongly suppress translation but fail to promote SG/PB formation. * • Persistent Ribosome Stalls Trap mRNA in Polysomes * o Polysome profiling shows that mRNAs remain trapped in ribosomes instead of being released for SG/PB formation. * o Unlike typical translation inhibition (which allows ribosome runoff and mRNA sequestration into SGs), tRNA synthetase inhibition causes prolonged ribosome stalling. * • Ribosome Rescue Pathways Are Insufficient to Resolve Stalls * o The ribosome-associated quality control (RQC) pathway, mediated by ZNF598, does not effectively clear stalled ribosomes. * o These unresolved stalls prevent normal RNP granule assembly. * • Puromycin Restores SG/PB Assembly by Releasing Stalled Ribosomes * o Adding puromycin, which forces premature translation termination, rescues SG formation, confirming that unresolved ribosome stalls are the key factor blocking RNP granule assembly.

STRENGTHS * Refines the Link Between ISR and SGs. ISR activation alone is not sufficient for SG formation if ribosome stalling persists. This challenges the conventional view that ISR and SG assembly are always tightly linked. * Reveals a New Role for tRNA Synthetases in Stress Adaptation. Beyond their canonical role in aminoacylation, tRNA synthetases regulate cellular stress responses by influencing ribosome dynamics. * Potential Disease Connections. Mutations in tRNA synthetases are linked to Charcot-Marie-Tooth disease (CMT2) and neurodegeneration, conditions associated with defective SG dynamics. This study suggests that stalled ribosomes, rather than ISR dysfunction alone, might contribute to these diseases. * Therapeutic Considerations: tRNA synthetase inhibitors are explored for cancer, fibrosis, and autoimmune diseases, but their impact on stress granule formation could have unintended consequences. Targeting ribosome rescue pathways may mitigate these effects. * Use of Multiple Stressors and Experimental Approaches. The study employs various stress conditions (e.g., sodium arsenite, thapsigargin) to show that tRNA synthetase inhibition uniquely prevents SG/PB formation while still activating the ISR. The authors use puromycin to rescue stalled ribosomes, demonstrating that ribosome stalling, rather than translation repression per se, is the key inhibitory factor.

CONCEPTUAL LIMITATIONS * Generalizability to Other Translational Stress Conditions. While the study demonstrates that halofuginone and borrelidin, inhibitors of prolyl- and threonyl-tRNA synthetases, prevent SG/PB assembly, it remains unclear if this effect extends to all aminoacyl-tRNA synthetase inhibitors. Do other ribosome-stalling conditions, such as premature termination caused by nonsense mutations, similarly prevent RNP granule formation.? * Role of Ribosome-Associated Quality Control (RQC) Pathway. The study shows that the ZNF598-mediated RQC pathway is insufficient to resolve ribosome stalls caused by tRNA synthetase inhibition. Do other ribosome rescue mechanisms, such as Pelota/HBS1 or GTPBP1/2, play a role in resolving these stalled ribosomes?

TECHNICAL LIMITATIONS * Use of a Limited Number of Cell Lines. The experiments rely heavily on U-2 OS cells, which may not fully recapitulate the stress responses of other cell types, particularly neurons or immune cells, where stress granules have key functional roles. Future studies could extend these findings to primary neurons or disease models. * Lack of Direct Evidence for mRNA Sequestration Failure. While the study infers that mRNA is retained in polysomes due to ribosome stalling, it does not directly measure which mRNAs fail to enter SGs/PBs. RNA imaging or transcriptomic analysis of polysome-bound mRNAs would provide stronger support for the hypothesis that stalled ribosomes trap mRNAs and prevent RNP granule formation.

Review coordinated by Life Science Editors Foundation Reviewed by: Dr. Angela Andersen, Life Science Editors Foundation & Life Science Editors. Potential Conflicts of Interest: None.

Punchline:The liver and lung microenvironments influence various phenotypes of metastasized triple-negative breast cancer (TNBC) cells in different ways. Liver microenvironment accelerates disease progression and negatively impacts patient outcomes. Interesting paper and seems well done, identifies specific players in the different environment – consistent with the concept that the niche affects the phenotype of metastatic outgrowths.

Why is this an important problem? Metastasis is the primary cause of cancer-related deaths. Understanding how different organ environments influence the behavior of metastatic cancer cells is crucial for developing effective treatments for Stage IV disease. This research specifically focuses on TNBC, an aggressive breast cancer subtype, and its behavior in lung and liver metastatic sites.

What did we already know? * • Breast cancer frequently metastasizes to bone, liver, lungs, and brain. * • TNBC, a particularly aggressive subtype, primarily spreads to visceral organs, mainly the lungs and liver. * • The presence of bone metastases is associated with a less aggressive disease course compared to other sites. * • There are conflicting data on the aggressiveness of disease in the context of lung and liver metastases. * Results: * • Patients with liver metastases, as their first metastatic event, showed significantly shorter overall survival and time to the next metastatic event compared to those with lung metastases. Focused on a subset of patients with "mono-metastasis", meaning that a single metastasis was present in either the lung (12/318 patients with metastases) or liver (10/318 patients with metastases) at the initial diagnosis of metastasis. Kaplan-Meier plots of the progression and survival differences between patients with lung versus liver mono-metastases support the idea that liver metastases are associated with more aggressive disease progression compared to lung metastases in breast cancer patients. * * • Barcode labeling and metastasis clonality assessment in a mouse model of TNBC: mouse TNBC cells (MVT1) were tagged with unique genetic barcodes before being injected into the mammary fat pad of mice. The barcode composition of cells in the circulation (circulating tumor cells) and from each site (liver, lung) was analyzed. A greater number of unique barcodes were found in the lung metastases compared to the liver. Principal component analysis revealed that lung metastases were a distinct population compared to liver metastases and circulating tumor cells. * • After mammary fat pad injection & metastasis, mouse MVT1 or 4T1 cancer cells were isolated from either the lungs or liver, injected into the tail veins of healthy mice. Liver-resident TNBC cells have an enhanced ability to establish secondary metastases at lung and liver when compared to lung-resident cells. * * • MVT1 mouse TNBC cells expressed GFP and a soluble mCherry protein that is taken up by neighboring niche cells. Identified and analyzed both tumor and niche cell populations. * • Single-cell RNA sequencing of cancer cells: MTV1 metastatic TNBC cells have distinct molecular profiles depending on where they reside: energy generation pathways in liver-resident cells (might contribute to their increased metastatic activity) and stress and detoxification pathways in lung-resident cells (suggests a less favorable environment). * • Single-cell RNA sequencing of niche cells: Endothelial cells in the liver metastatic niche, unlike the primary tumor niche and lung niche. The unique abundance of endothelial cells in the liver niche suggests their potential involvement in shaping the metastatic behavior of liver-resident TNBC cells. Specific ligand-receptor pairs suggest a distinct communication network between cancer cells and their niche in the liver and lungs, whereby the liver niche is enriched in endothelial cells secreting Bmp2 and Bmp6 cytokines, while the lung niche is enriched in macrophages secreting Grn and Ssp1. * • Specific cytokine-receptor interactions between cancer cells and their niche were identified, with BMP2/6 secreted by liver endothelial cells and Granulin secreted by lung macrophages. * * • In vivo CRISPR-Cas9 screen used to investigate the roles of the identified cytokine-receptor pairs in metastasis formation. MTV1 TNBC cells were engineered with loss-of-function of the receptors for BMP2/6 (BMPR2, BMPR1A, and ACVR1) implicated in liver metastasis and Granulin (TNFRSF1A/B) implicated in lung metastasis. The engineered cells were injected into the tail vein and allowed to metastasize, isolated from lung and liver, and the abundance of different gene knockouts was analyzed. Additionally, they were reinjected into the tail vein to detect secondary metastasis. * * • Using this approach the organ of primary metastasis influenced the secondary metastasis (lung went to lung, liver to liver) - in contrast to when the experiment was done with WT cells injected into the mammary fat pad and isolated from liver and lung (when liver-derived TNBC showed higher secondary metastasis by tail vein to lung and liver, Fig 1I). This disconnect is a bit confusing. * * • There was no difference between the knockouts. This lack of organ specific knockouts between lung- and liver-resident cells could be due to the pleiotropic role of many of these receptors and the existence of interactions with additional cytokines. Notably, the expression of these receptors in cancer cells at the RNA level was similar in liver and lung metastases. * • Kaplan-Meier curve compares the survival of mice re-injected with either lung- or liver-resident cancer cells. Liver metastases were associated with decreased survival when compared to lung metastasis. Consistent with liver metastases associated with more aggressive disease progression compared to lung metastases. * • To investigate the effect of the niche on TNBC cells, TNBC cells were treated with either BMP2 or Granulin in vitro before being injected into the tail vein. This simulates the effects of the liver and lung microenvironment, respectively. BMP2 pre-treatment of TNBC cells enhanced metastasis formation in the lung, whereas Granulin treatment suppressed it. Supports the model that the liver niche boosts metastasis through BMP2, while the lung niche inhibits it through Granulin. This is a bit confusing with the apparent tropism of liver to liver in figure 5 but more consistent with figure 1.

What's new? Sheds light on how the liver and lung microenvironments (endothelial vs macrophage, respectively) distinctly influence the behavior of TNBC cells and why liver metastasis is associated with poor survival. Offers potential therapeutic targets for liver vs lung metastases. The discovery of the contrasting roles of BMP2 and Granulin, and their cellular sources within the respective metastatic niches, is interesting.

Potential impact * • Treatment strategies for TNBC patients with liver or lung metastases could potentially be tailored based on the identified niche-specific vulnerabilities. * • Targeting BMP2 signaling in liver metastases could potentially reduce secondary spread. * • Stimulating Granulin activity could offer a new approach to inhibiting TNBC metastasis.

Limitations: * • The study primarily focused on TNBC, and further research is needed to determine if these findings apply to other cancer types metastasizing to the liver and lungs. * • I would have liked to see preclinical models with xenografts. Therapeutic potential not shown. * • The CRISPR-Cas9 screen did not identify organ-specific knockouts, likely due to the pleiotropic roles of the targeted receptors and the complex interplay of various cytokines within the niche.

Future work: * • Investigate the applicability of these findings to other cancer types with similar metastatic patterns. * • Further explore the complex interplay of cytokines and signaling pathways within the liver and lung metastatic niches. * • Develop therapeutic strategies to target BMP2 signaling in liver metastases and stimulate Granulin activity in lung metastases. * • Validate these findings in a larger cohort of patients to determine their clinical relevance.

Review coordinated by Life Science Editors Foundation

Reviewed by: Dr. Angela Andersen, Life Science Editors Foundation & Life Science Editors. *Assisted substantially by NotebookLM.

Potential Conflicts of Interest: Angela thinks Olivia Rissland is everything a scientist should be.

What is an N-degron? N-degrons are short amino acid sequences located at the N-terminus of a protein that signal for the protein's degradation. This process is an essential part of protein quality control and regulation within cells. N-degrons are recognized by specific E3 ubiquitin ligases, also known as N-recognins, which help target the protein for degradation by the ubiquitin-proteasome system.

How was this new Arg/N-degron pathway discovered? The authors were initially studying how N-terminal sequences affect gene expression using a reporter gene assay. They found that a specific tripeptide motif (KIH) inserted at the N-terminus of a reporter protein led to a dramatic decrease in protein expression. Further investigation revealed that this decrease was due to rapid protein degradation, indicating the presence of a novel N-degron.

What are the key features of this new N-degron pathway? This newly discovered N-degron pathway targets proteins with a lysine (K) or arginine (R) residue at the third position (position 3) from the N-terminus. Importantly, this pathway requires: * • Methionine Removal: The initiator methionine (M) at position 1 must be removed by the enzyme methionine aminopeptidase 2 (MetAP2) for the degron to be active. * • UBR4 Recognition: The E3 ligase UBR4, but not UBR1 or UBR2, recognizes this specific degron and initiates the degradation process.

Why is the identity of the second amino acid important? The second amino acid plays a crucial role in determining whether MetAP2 can cleave the initiator methionine. This study found that the degron is only active when the second amino acid is threonine (T) or valine (V). These amino acids allow MetAP2 to remove the methionine, exposing the lysine or arginine at position 3 for recognition by UBR4. In contrast, if the second amino acid is alanine (A) or serine (S), MetAP1 removes the methionine. The researchers hypothesize that these N-termini are then acetylated, preventing UBR4 recognition.

Is there evidence that this pathway affects endogenous proteins? Yes, analysis of previously published data and additional experiments by the researchers suggest that this MetAP2-UBR4 pathway is not limited to artificial reporter systems. They found that endogenous proteins with MTK or MVK N-termini were less stable than those with other amino acids at position.

Does UBR4 work alone in this pathway? UBR4 appears to function as part of a complex with the protein KCMF1 to degrade proteins containing this new degron. Experiments showed that disrupting the UBR4-KCMF1 complex stabilized the degradation of reporter proteins containing the KIH degron.

What is the broader significance of this discovery? The identification of this new Arg/N-degron pathway expands our understanding of the N-end rule, a fundamental mechanism for protein degradation in cells. It highlights the complexity of this system and reveals how the interplay between different enzymes like MetAP2 and E3 ligases like UBR4 can fine-tune protein stability. Additionally, it suggests that there may be other undiscovered N-degron pathways that remain to be characterized.

What questions still need to be answered about this new pathway? This study raises several new questions, including: * • Substrate Specificity: What are the precise rules governing UBR4 recognition of position 3 lysine and arginine degrons? Do other amino acids in the protein sequence affect degron recognition? * • Physiological Roles: What are the specific cellular processes and pathways regulated by this MetAP2-UBR4 N-degron pathway? * • Evolutionary Conservation: Is this pathway conserved in other organisms, or is it unique to mammals? * • Therapeutic Potential: Could this pathway be targeted for therapeutic purposes? For example, could stabilizing proteins involved in disease by manipulating this pathway be beneficial?

What was not known: * • Whether a lysine or arginine residue at position 3 of a protein could act as an N-degron. * • Whether MetAP2 could play a role in initiating N-degron-mediated degradation.

What this preprint reveals: * • A new family of N-degrons: The study identified a new class of N-degrons characterized by a lysine or arginine residue at position 3, following a methionine at position 1 and a MetAP2-cleavable residue (threonine or valine) at position * • MetAP2-dependent initiation of the Arg/N-degron pathway: The study found that MetAP2-mediated removal of the initiator methionine is essential for the recognition and degradation of these position 3 lysine/arginine degrons. This is the first demonstration of MetAP2's involvement in this pathway * • UBR4 as the primary E3 ligase: UBR4, rather than UBR1 or UBR2, was identified as the primary E3 ligase responsible for recognizing and targeting proteins with the newly identified position 3 degrons for degradation. * • Role of downstream residues: The study showed that amino acid residues downstream of the position 3 lysine/arginine can influence both methionine cleavage by MetAP2 and recognition by UBR4, highlighting the complexity of the N-degron pathway. * • Endogenous protein regulation: The study provided evidence suggesting that this MetAP2-dependent, UBR4-mediated Arg/N-degron pathway regulates the stability of endogenous proteins, highlighting its broader biological significance.

Ang's take- somewhat specialized and 'ectopic' but important, thorough, and unambiguous. Satisfying. Very likely to be physiologically relevant even though most of the assays were done with reporters. Regardless, showing that this rule 'is' true is useful for technological applications.

Review coordinated by Life Science Editors Foundation

Reviewed by: Dr. Angela Andersen, Life Science Editors Foundation & Life Science Editors. *Assisted by NotebookLM.

Potential Conflicts of Interest: None

Under review at Nature Portfolio

Punchline: Neurons under stress can locally synthesize Heat Shock Proteins (HSPs) in dendrites by increasing the transport of their mRNAs from the soma.

Why is this interesting? This is a previously unknown mechanism for locally synthesizing HSPs in neuronal dendrites in response to stress. It could shed light on therapeutic strategies for neurodegenerative diseases, which are characterized by a loss of proteostasis.

Background:

• • Maintaining proteostasis is difficult for neurons because of their complex polarized morphology and the need for constant remodeling of the synaptic proteome.
• • Local Translation in Neurons: The concept of local translation, particularly within neuronal dendrites, was already well-established. mRNA localization and local translation are fundamental processes in neurons, allowing for spatial and temporal control of protein synthesis. This is particularly crucial in dendrites, which are distant from the soma and require localized protein synthesis for synaptic plasticity and other functions.
• • HSPs and Proteostasis: The importance of heat shock proteins (HSPs) in maintaining cellular proteostasis was also well-understood. HSPs act as chaperones, assisting in the proper folding of proteins and preventing the formation of harmful aggregates.
• • RNA-Binding Proteins and mRNA Localization: RNA-binding proteins (RBPs) play a critical role in regulating mRNA localization and translation. These proteins often recognize mRNAs and direct their transport to specific subcellular locations.

Results: * • When hippocampal and spinal cord motor neurons are stressed, they increase the transport of HSP mRNAs to the dendrites. * • Used a variety of techniques to stress the neurons, including inhibiting the proteasome, hypoxia, and exposure to amyloid-beta peptides. * • All of these stresses led to an increase in the levels of HSP mRNAs in the dendrites. * • The increase in HSP mRNA levels in the dendrites was accompanied by an increase in the levels of HSP proteins in the dendrites. * • This suggests that the HSP mRNAs are being translated into proteins in the dendrites. * • Transport of HSP mRNAs to the dendrites was dependent on the microtubule motor protein dynein. * • Two RNA-binding proteins, FUS and HNRNPA2B1, regulate the transport of HSP mRNAs to dendrites. * • Depletion of FUS or expression of the ALS-associated HNRNPA2B1 D290V mutation impaired the dendritic localization of HSP mRNAs in mouse and human motor neurons.

Discussion: * • Stress-Responsive HSP mRNA Transport and Translation in Dendrites: While previous studies had identified local translation of some proteins in dendrites and recognized the role of HSPs in neurons, this paper specifically focuses on the regulated transport and localized translation of HSP mRNAs in dendrites as a key mechanism for responding to proteotoxic stress. This adds a new layer of understanding to neuronal stress responses. * • Identification of FUS and HNRNPA2B1 as Key Regulators: The study goes a step further by identifying and characterizing the specific roles of RNA-binding proteins FUS and HNRNPA2B1 in regulating HSP mRNA transport. This mechanistic insight into how HSP mRNA localization is controlled enhances our understanding of how neurons fine-tune proteostasis in a spatially defined manner. * • Linking HSP mRNA Localization to ALS: The study makes a significant connection between the dysregulation of HSP mRNA localization and amyotrophic lateral sclerosis (ALS). By demonstrating that an ALS-associated mutation in HNRNPA2B1 (D290V) impairs HSPA8 mRNA localization and increases neuronal vulnerability, the study provides a potential molecular mechanism for this devastating neurodegenerative disease. This link between impaired local translation, proteostasis, and ALS opens up new avenues for research and potential therapeutic interventions.

Limitations: • Experiments conducted in cultured neurons.

Future work: * • Investigate the role of this mechanism in vivo. * • Determine whether this mechanism is impaired in other neurodegenerative diseases. * • Inform therapeutic strategies that can target this mechanism to treat or prevent neurodegenerative diseases.

Selected Reading 1. Bourke, Ashley M. et al. De-centralizing the Central Dogma: mRNA translation in space and time Molecular Cell, Volume 83, Issue 3, 452 – 468 (2023) 2. Davidson, Alexander et al. Localized Translation of gurken/TGF-α mRNA during Axis Specification Is Controlled by Access to Orb/CPEB on Processing Bodies Cell Reports, Volume 14, Issue 10, 2451 – 2462 (2016) 3. Gehrke, Stephan et al. PINK1 and Parkin Control Localized Translation of Respiratory Chain Component mRNAs on Mitochondria Outer Membrane Cell Metabolism, Volume 21, Issue 1, 95 – 108 (2015) 4. Hacisuleyman, E., Hale, C.R., Noble, N. et al. Neuronal activity rapidly reprograms dendritic translation via eIF4G2:uORF binding. Nat Neurosci 27, 822–835 (2024). 5. Höpfler, Markus et al. Control of mRNA fate by its encoded nascent polypeptide Molecular Cell, Volume 83, Issue 16, 2840 – 2855 (2023) 6. Park, Sungjin et al. The mammalian midbody and midbody remnant are assembly sites for RNA and localized translation Developmental Cell, Volume 58, Issue 19, 1917 - 1932.e6 (2023) 7. Lautier, Ophélie et al. Co-translational assembly and localized translation of nucleoporins in nuclear pore complex biogenesis Molecular Cell, Volume 81, Issue 11, 2417 - 2427.e5 (2021) 8. Ramat, A., Haidar, A., Garret, C. et al. Spatial organization of translation and translational repression in two phases of germ granules. Nat Commun 15, 8020 (2024).

Review coordinated by Life Science Editors Foundation

Reviewed by: Dr. Angela Andersen, Life Science Editors Foundation

Potential Conflicts of Interest: None

Punch line: Activation of the yeast AMP-activated protein kinase (AMPK) negatively regulates MAGIC, inhibits the import of misfolded proteins into mitochondria & promotes mitochondrial biogenesis and fitness.

Why is this interesting? Maybe all those healthy things like caloric restriction, intermittent fasting, exercise etc that activate AMPK & extend lifespan do so by inhibiting MAGIC & preventing mitochondrial damage from misfolded proteins.

Background: Metabolic imbalance & loss of proteostasis are interconnected hallmarks of aging and age-related diseases. A mitochondria-mediated proteostasis mechanism called MAGIC (mitochondria as guardian in cytosol) concentrates cytosolic misfolded protein at the surface of mitochondria, where they are disaggregated by molecular chaperones, and then imported for degradation by mitochondrial proteases. Inhibition of this pathway prolongs protein aggregation in cytosol after proteotoxic stress, but excessive misfolded proteins in mitochondria can lead to mitochondrial damage.

Results: • Genetic screen for MAGIC regulators uncovered 145 genes. Loss of Snf1 (AMPK homolog) led to increased mitochondrial import even without proteotoxic stress. In contrast indirect, constitutive activation of Snf1 (e.g. low glucose) prevented the import of misfolded proteins in mitochondria.

• The data suggest that the reduced accumulation of misfolded proteins in mitochondria of Snf1-active cells is not due to enhanced intramitochondrial degradation nor to reduced levels of the misfolded protein, but rather due to blocked mitochondrial import.

• Deletion of HAP4 counteracted Snf1 activation and overexpression of Hap4 alone recapitulated Snf1 activation. The Hap2/3/4/5 complex activates the expression of nuclear encoded mitochondrial proteins. Their data suggest that high expression of mitochondrial preproteins due to an elevated Snf1-Hap4 axis compete with misfolded proteins for mitochondrial import.

• Proteotoxic stress led to a reduced growth rate & reduced mitochondrial fitness in high glucose medium but not under glucose limitation. The data suggest that low glucose, activation of Snf1 & prevention of misfolded protein import into mitochondria prevent the growth defect.

• Many neurodegenerative disease-associated aggregation-prone proteins (α-synuclein, FUSP525L, TDP-43, amyloid beta, C9ORF72-associated poly(GR) dipeptide) are detected in mitochondria of human patients or disease models and impair mitochondrial functions. Their data suggest that the import of α-synuclein & associated reduction in mitochondrial fitness can be counteracted by indirect AMPK/Snf1 activation (i.e. glucose limitation).

• Show data in yeast & human cells.

Discussion: This paper revealed an unexpected link between cellular metabolism and proteostasis through MAGIC/mitochondria.

• Snf1/AMPK is a key regulator of MAGIC & of misfolded protein import into mitochondria.

• Snf1/AMPK balances the mitochondrial metabolic and proteostatic functions in response to glucose availability and protects mitochondrial fitness under proteotoxic stress.

• The authors speculate that in high glucose, cells rely on glycolysis for ATP production and mitochondria ‘moonlighting’ in cellular proteostasis through MAGIC, but when glucose is limited and cells rely on oxidative phosphorylation for ATP generation, AMPK is activated and shuts down MAGIC, prioritizing the import of essential mitochondrial preproteins to ensure mitochondrial fitness and energy production.

• Acknowledge limitations: Snf1/Hap4 activation elevates the expression of hundreds of mitochondrial preproteins, not clear whether specific preproteins or cytosolic factors directly involved in inhibiting mitochondrial import, & that more details on mechanisms will be of interest.

• Caloric restriction & AMPK activation might contribute to lifespan extension by inhibiting MAGIC. In human, AMPK activity is elevated during health-benefitting activities such as exercise. Their data suggest that elevating AMPK activity may be beneficial in alleviating proteotoxicity associated with degenerative diseases - but hyperactivated AMPK has also been reported in several neurodegenerative diseases with proteostasis decline (Ang wonders- maybe AMPK is overwhelmed?).

THIS IS A GORGEOUS PAPER!

Future work - I can't wait to see the characterization of the ribosome biogenesis genes that they also pulled out as MAGIC regulators. Anticipating a translation, misfolded protein, mitochondria, aging axis :)

Review coordinated by Life Science Editors Foundation

Reviewed by: Dr. Angela Andersen, Life Science Editors Foundation

Potential Conflicts of Interest: None

Punch line: Rare risk variants associated with schizophrenia converge on the cAMP/PKA pathway.

Why is this interesting? The cAMP/PKA pathway could be a mechanism & therapeutic target for neuropsychiatric disorders arising from different mutations.

Background: * About 1-4% of people will develop psychosis or schizophrenia. * Schizophrenia is a highly heritable disease. * Genetic loci associated with schizophrenia can be common variants, which typically have small effects on risk, or rare variants, which can have large effects. * Rare, protein-truncating variants substantially increase the risk for mental illnesses like schizophrenia. * Disease-associated genes have diverse functions (e.g.): 1. RNA binding (RBM12) 2. transcriptional regulation (SP4, RB1CC1, SETD1A) 3. splicing (SRRM2) 4. signaling (AKAP11) 5. ion transport (CACNA1G, GRIN2A, GRIA3) 6. neuronal migration and growth (TRIO) 7. nuclear transport (XPO7) 8. ubiquitin ligation (CUL1, HERC1) ** What are the pathological mechanisms?* * A genetic screen identified the risk gene RBM12 as a novel repressor of GPCR/cAMP signaling (Semesta et al., PLOS Genetics, 2020). * Dysregulation of GPCR activity in the brain contributes to the pathophysiology of several neurological and neuropsychiatric disorders. * cAMP is a critical second messenger that mediates all important aspects of neuronal function, including development, excitability, and plasticity.

Results: * Use knockout HEK293 cells to verify that RBM12 is novel repressor of the GPCR/cAMP pathway that extends to multiple GPCRs coupled to the stimulatory G protein (e.g. dopamine 1 receptor, beta-2 adrenergic receptor). * Show RBM12 also represses this pathway in iPSC-derived neurons. RBM12 knockdown yielded hyperactive upregulation of NR4A1 and FOS mRNAs, two known CREB-dependent immediate early genes induced by neuronal activity. * RBM12 loss leads to increased PKA activity and supraphysiological CREB-dependent transcriptional responses. * RBM12 loss increased expression of the endogenous β2-AR transcriptional target mRNAs, PCK1 and FOS. * RBM12 loss increased CREB transcriptional reporter expression in response to a panel of endogenous or synthetic β2-AR agonists.<br /> * Transcriptional responses are orchestrated from endosomal β2-ARs in wild-type cells but from both plasma membrane and endosomal β2-ARs in RBM12 knockout cells. * Their results suggest that cAMP production and transcriptional signaling are independently subject to RBM12 regulation. * The neuropsychiatric disease-linked mutations fail to rescue GPCR-dependent hyperactivation in cells depleted of RBM12. * Defined β2-AR-dependent transcriptional targets in “wild-type” and RBM12 knockdown neurons by differential expression analysis between each respective basal and isoproterenol conditions. 669 unique β2-AR-dependent transcriptional targets across the two cell lines. * Discerned β2-AR-dependent targets that were exclusive to wild-type or RBM12 knockdown only (qualitatively distinct targets) versus targets that are in wt and RBM12 kd but upregulated to different extents (quantitatively distinct targets). * 21 wild-type- and 115 RBM12 knockdown-specific target genes. Factors involved in synaptic plasticity and schizophrenia such as JUN, ARC (encoding the activity-regulated cytoskeleton-associated protein), BDNF, and NRXN3 (encoding the cell adhesion molecule neurexin-3-alpha) were induced by GPCR signaling only in RBM12 knockdown neurons, while GRIA2 (encoding the AMPA receptor) and CBLN2 (encoding cerebellin 2 precursor) were upregulated upon GPCR signaling only in wt neurons. * the remaining 533 genes were induced in both wt & RBM12-depeleted, with a trend toward RBM12-dependent hyperactivation. * loss of RBM12 leads to aberrant expression of ADCY, PDE, and PRKACA, suggesting this mechanism underlies the hyperactive GPCR/cAMP/PKA signaling phenotypes.

Discussion: * Dysregulation of GPCR signaling could contribute to the neuronal pathologies stemming from loss of RBM12. * RBM12 function is required for normal cAMP production downstream of many Gαs-coupled receptors with established roles in the nervous system consistent with dysregulation of cAMP/PKA pathway. Specifically, the entire repertoire of targets, many of which orchestrate processes essential for neuronal differentiation, gene reprogramming, and memory and learning, shows a trend towards hyperactivation in RBM12 depleted neurons. * Over 100 genes are induced in response to receptor stimulation only in the knockdown (e.g. ARC and BDNF, with crucial roles in synaptic function, plasticity, and learning. * RBM12 could act through other mechanisms, given that RBM12 knockdown neurons also affects the expression of genes involved in neuron differentiation, synapse organization, and neurogenesis. * A study on post-mortem brains of patients with bipolar affective disorder demonstrated elevated levels of the PKAcat subunit Cα in temporal and frontal cortices compared to matched normal brains. * A different report on patient-derived platelet cells found that the catalytic subunit of cAMP-dependent protein kinase was significantly upregulated in untreated depressed and manic patients with bipolar disorder compared with untreated euthymic patients with bipolar disorder and healthy subjects. * Mutations in the schizophrenia risk gene histone methyltransferase SET domain-containing protein 1 A (SETD1A) also led to transcriptional and signaling signatures supporting hyperactivation of the cAMP pathway through upregulation of adenylyl cyclases and downregulation of PDEs. This in turn resulted in increased dendritic branching and length and altered network activity in human iPSC-derived glutamatergic neurons.

Beautiful follow up to their PLOS Genetics paper, and compelling pathological mechanism in combination with the recent SETD1A Cell Reports paper.

Future work: * Does loss of RBM12 increase dendritic branching and length and alter network activity in human iPSC-derived glutamatergic neurons (e.g. does it phenocopy loss of SETD1A). * Does pharmacologically targeting the cAMP pathway rescue the phenotypes caused by loss of RBM12? * If RBM12 is ubiquitously expressed, why is the disease neuronal? What is the relevant GPCR/neuronal mechanism? * How does RBM12 affect the abundance of the transcripts encoding the GPCR/cAMP effectors? * Do mutations in any of these other rare risk genes converge on GPCR? (transcriptional regulation (SP4, RB1CC1), splicing (SRRM2). signaling (AKAP11). ion transport (CACNA1G, GRIN2A, GRIA3), neuronal migration and growth (TRIO), nuclear transport (XPO7). ubiquitin ligation (CUL1, HERC1))

Review coordinated by Life Science Editors Foundation

Reviewed by: Dr. Angela Andersen

Potential Conflicts of Interest: None

Background: * mRNAs in polarized cells often have a distinct spatial localization patterns that enable localized protein production * In non-polarized cells, mRNAs encoding membrane and secretory proteins are predominantly translated on the endoplasmic reticulum (ER), some mRNAs are enriched on the mitochondrial surface, some mRNAs are bound to the RNA-binding protein (RBP) TIS11B at the surface of the rough ER in "TIS granules". * The translation of specific mRNAs in TIS granules allows assembly of protein complexes that cannot be established when the mRNAs are translated on the ER but outside of TIS granules (physiological relevance). * The canonical rough ER (CRER) is distinct from the TIS granule ER (TGER), and both are distinct from the cytosol.

Questions: * Do mRNAs that encode non-membrane proteins differentially localize to the ER or the cytosol? (in steady state) * Does the amount of protein synthesis differ depending on the subcytoplasmic location of an mRNA?

Summary: * A third of mRNAs that encode non-membrane proteins have a biased localization to TGER or CRER, indicating that the ER membrane is a general site of translation for both membrane and non-membrane proteins. * 52% of mRNAs that encode non-membrane proteins have a biased mRNA transcript localization pattern towards a single cytoplasmic compartment. the TGER, CRER or cytosol. * The localization at the TGER or CRER was largely controlled by a combinatorial code of AU-RBPs at the 3'UTR. TIS11B promotes mRNA localization to TGER and TIA1/L1 to CRER. * LARP4B bound to the 3'UTR promotes cytosolic localization. * The location of translation has an independent effect on protein levels independent of the RBPs/3'UTR: redirecting cytosolic mRNAs to the rough ER membrane increased their steady-state protein levels by two-fold, indicating that the ER environment promotes protein expression. * Compartment-enriched mRNAs differed in their mRNA production and degradation rates, as well as functional classes and levels of their encoded proteins. Therefore the cytoplasm is partitioned into different functional and regulatory compartments that are not enclosed by membranes. * low-abundance proteins are translated in the TGER region. mRNAs encoding zinc finger proteins and transcription factors were substantially enriched at the TGER. These gene classes are usually expressed at lower levels than others.. This localization may regulate protein complex assembly (membrane proteins that are translated in the TGER domain establish protein complexes that cannot be formed when the proteins are translated on the CRER). The TGER may ensure that low-abundance mRNAs are effectively translated into low-abundance proteins. * mRNAs that are the most stable and encode the most highly expressed proteins are enriched on the CRER and include helicases, cytoskeleton-bound proteins, and chromatin regulators, overturning the idea that most non-membrane protein-encoding mRNAs are translated in the cytosol. * mRNAs overrepresented in the cytosol had the highest production and degradation rates and were enriched in proteins involved in mRNA processing and translation factors, whose abundance levels require tight control.

Advance: Evidence for functional compartmentalization of non-membrane mRNA protein expression in the cytosol vs ER. In steady state, general localization of mRNAs to the ER promotes high protein levels.

Significance: Engineered 3'UTR sequences could potentially boost protein expression by localizing mRNAs to the ER in experimental settings, for vaccines etc.

Remaining questions/points: * How does the rough ER stimulate protein expression? * Does the mRNA localization affect complex formation and/or function of non-membrane proteins? * Does this occur in cells other than HEK293T? * Is this regulated?