- Sep 2019
[Note: this preprint has been peer reviewed by eLife. The decision letter after peer review, based on three reviews, follows. The decision was sent on 21 May 2019.]
Masachis, Darfeuille et al. analyse a type I toxin - antitoxin (TA) module of the major human gastric pathogen Helicobacter pylori (Hp). Expression of toxins encoded by Type I modules is controlled by small, labile, cis-encoded antisense RNAs and often also by complicated mRNA metabolism that envolves conserved mRNA folding pathways and/or mRNA processing. Using a combination of elegant and robust in vitro and in vivo methods, the authors first show that that the aapA3/IsoA3 TA system of Hp is regulated in a way very similar to that of the homologous aapA1/IsoA1 system from the same organism (Figs 1 and 2). This initial part of the manuscript sets the stage for the next step, where the authors employ a powerful genetic screen combined with deep sequencing to identify single nucleotide changes that abolish production of the AapA3 toxin (Fig. 3). This principle, which was invented by the authors, is technically robust, intellectually attractive and very powerful, and may yield novel insights that at present cannot be reached by other approaches. In particular, the authors discover that single point mutations outside the toxin gene reading frame suppress toxin gene translation. Focusing on the translation initiation region, they discover two mRNA hairpin structures that, when stabilized by single base changes, reduce translation by preventing ribosome binding (Figs 4-6). They propose that these structures are metastable and form during transcription to keep the toxin translation-rate low, as explained in the model figure (Fig. 7).
All of the reviewers thought the quality of the experimental work in the manuscript is outstanding and the conclusions are justified. However, all thought it would be nice to have additional evidence of the proposed metastable structures in the nascent toxin mRNA. While the reviewers understood this might be technically difficult, they agreed that it is worth a try and had the following suggestions.
1) Phylogeny (i.e. nucleotide co-variation in sequence alignments) was previously used to deduce the existence of stem-loop structures not only in ribosomal RNAs but also in mRNAs (e.g., hok mRNAs). Did the Authors consider using this approach to support the existence of the proposed metastable structures in the nascent toxin transcript? This possibility depends on the actual homologous sequences available and is not possible in all cases. If phylogeny indeed supports the existence of the metastable structures, the Authors could look for coupled nucleotide covariations that would support a conserved mRNA folding pathway (that is, one mRNA sequence elements pairs with two or more other elements during the fife-time of the mRNA) . The Authors state in the Discussion that "these local hairpins were previously predicted to form during the co-transcriptional folding pathway of several AapA mRNAs (Arnion et al., 2017)." However, they authors did not explain how these hairpins were predicted. It is worth explaining this central point.
2) Although transient structures are by definition hard to detect, the authors could try in vivo structure probing (DMS) of truncated mRNAs 1-64 and 1-90 to demonstrate the existence of the first and the second metastable structures, respectively.
3) It is preferable to carry out 2D structure predictions on the naturally occurring transcript, not a sub-sequence. 2D structure prediction generated by algorithms such as RNAfold (or Mfold) that are guided by delta-G stability optimisation are sensitive to the sequence context, so the correct sequence needs to be used to be able to draw conclusions. Additionally, the findings presented in Figure 3D could be analyzed a bit further to produce significant, independent evidence for some structure features. Specifically,
Figure 2 caption:
- lines 184 - 186: "2D structure predictions were generated with the RNAfold Web Server (Gruber, Lorenz, Bernhart, Neuböck, & Hofacker, 2008) and VARNA (Darty, Denise, & Ponty, 2009) was used to draw the diagrams."
- Please state clearly whether any of the results of the experimental 2D structure probing were used as input to RNAfold (i.e. as additional constraints to the prediction algorithm).
- Please add coloring to the peaks depending on which codon position they overlap (1, 2 or 3) and carefully discuss the corresponding results, also in the context of the 2D structure elements.
- Given that you have a decent number of pair-mutations, analyze them to see whether any correspond to RNA structure base-pairs (and whether any of the pair mutations rescue the base-pair and thus affect the system differently). This would serve as additional, independent evidence of 2D structure probing and predictions.
[Note: this preprint has been peer reviewed by eLife. The decision letter after peer review, based on three reviews, follows. The decision was sent on 17 June 2019.]
Natural Killer (NK) and the ILC1 subset of innate lymphoid cells share related functions in host defense but have been argued to arise from distinct pathways. Park et al present new evidence challenging this concept. They show that murine Toxoplasma gondii infection promotes the differentiation of NK cells into an ILC1-like cell population which is stable and long-lasting, even after the infection has been cleared. These T. gondii induced cells, unlike Eomes+CD49a- NK cells, are Eomes-CD49a+T-bet+ and therefore resemble ILC1 cells. The authors additionally show that their differentiation involves Eomes down regulation and is STAT-4 dependent, However, in common with NK cells and distinct from ILC1 the T. gondii induced "ILC-like" population circulates to blood and lungs. Finally, the authors employ single cell RNAseq to examine the heterogeneity of the major T. gondii induced innate lymphocyte populations and their NK vs ILC relatedness as assessed by gene expression. Together, their observations establish a previously unappreciated developmental link between NK and ILC1cells in the context of infection.
The 3 reviewers and editor agree that this is an important contribution that sheds new light on the developmental relationship of NK and ILC1 cells, a scientific issue that has received considerable attention in the innate immunity field. Although extensive, most of the criticisms raised can be addressed by revisions to the manuscript. One additional experiment is requested to provide a missing control.
All reviewers had a major concern about how this new population of T. gondii induced innate cells should be referred to in the manuscript. Based on the single cell RNAseq data, these cells (cluster 10) are still closer to NK cells than to ILC1s (Figure 5f and Suppl Fig 4e) despite their loss in Eomes expression and acquisition of CD49a expression. Thus, one could easily think of them as "Eomes negative NK" or "ex-NK" cells rather than ILC1s, and to simply refer to them as Eomes-CD49a+ ILC1 cells may be misleading . For this reason, the authors should modify the title of the paper and change their designation throughout the manuscript. We suggest "ILC1-like" as a good descriptor. In addition, although it is clear that the "Eomes negative NK" cells that are generated during T. gondii infection are transcriptionally and epigenetically distinct from the NK cells in the steady state and NK cells after infection (Figure 7 and suppl Figure 6), these "Eomes negative NK" cells referred to as "T. gondii-induced ILC1s" were not directly compared with classical ILC1s. Based on the single cell RNAseq data, these cells may not express many of the ILC1-related signature genes. Therefore, again, the authors need to be cautious in referring to them as ILC1 cells.
A second concern was that the NK 1.1 depletion shown in Supplemental figure 1 was performed with a PBS rather than isotope matched immunoglobulin control which is considered unacceptable. The authors should repeat at least once with proper control Ig to make sure this is not issue. It is not necessary to repeat entire survival curve just experiments shown in A and B and initial survival to make sure there is no death in controls vs. antibody treated.
[Note: this preprint has been peer reviewed by eLife. The decision letter after peer review, based on three reviews, follows. The decision was sent on 19 May 2019.]
This paper describes five cryo-EM structures of ribosomal complexes apparently representing different stages of RF2-catalyzed translation termination. The novel observations here are that the tip of domain 3 of RF2 undergoes a rearrangement from an a-helical conformation to a b-hairpin conformation during termination that likely facilitates exit of the newly synthesized protein from the ribosomal polypeptide exit tunnel and that the ribosome can undergo two thermally activated, spontaneous conformational changes, a relative rotation of the ribosomal subunits and a swiveling of the 'head' domain of the small subunit, during termination that likely facilitate dissociation of RF2 from the ribosome. These are interesting observations that significantly extend our understanding of how class I RFs and ribosome conformational changes drive important steps during termination and, as such, all three reviewers recommended publication provided the following comments are addressed adequately.
1) The maps provided through the eLife system seemed to be unsharpened, as they showed very little detail. However, even after sharpening them with a B-factor of -100A2, they still did not show the expected features for their respective resolutions. My suspicion is that FREALIGN has been used to overfit the data. This should be addressed in the revision. It should be indicated whether gold-standard separation of halves of the data sets were used in the final refinements, or whether those were limited to a specific spatial frequency (like was done in the classifications). If the latter, those frequencies should also be stated in the manuscript, and they should be significantly lower than the claimed resolutions.
In addition: a lot of basic cryo-EM information is missing: the authors should include: a) at least one micrograph image b) some representative 2D class averages c) local resolution maps of the five structures. Also, because the density of important parts of the maps seems to be a lot worse than the resolution claimed, it would be good to explicitly mention the local resolution of the important features discussed in the main text. d) for each structure, some zoomed-in figures with the density on top of the molecular model. These figures should be chosen as to validate the resolution claim. For example, in structures I, II and V, the RNA bases should be well separated (they do so at 3.6A), and in structures III and IV beta-strands should be well separated, and many (larger) side chains should be visible. In addition, some panels with density for the most important features of each structure should be shown. e) FSC curves between the refined PDB models and the cryo-EM maps are missing from the manuscript. These should be included. In addition, to evaluate potential overfitting of the models in the maps, for each structure, the authors should also include the FSC curves between a model that was refined in half-map1 versus half-map1, as well as the FSC curve between _thesame model versus half-map2.
2) There appear to be many self-citations, and there are also a few places where relevant citations are missing or are mis-cited. There are too many to list individually, but, just a few examples: Page 4: the only citation for the phrase "recent biophysical and biochemical findings suggest a highly dynamic series of termination events" is a Rodnina paper. There are many, earlier papers from Ehrenberg, Gonzalez, Puglisi, Green, Joseph, etc. that should be cited here. Page 5: The only citation for the sentence "By contrast, biochemical experiments showed..." is a Green paper. There are earlier papers from Ehrenberg characterizing the effects of the GGQ-->GAQ mutations on the ability of RF3 to accelerate the dissociation of class I RFs from termination complexes that should be cited here. Page 5: There's a sentence that refers to X-ray, cryo-EM, and smFRET studies, but only provides citations to two smFRET studies (Casy et al, 2018 and Sternberg et al, 2009); Page 5: Moazed and Noller, 1989 identified and characterized the P/E hybrid state, but they didn't report that a deacylated P-site tRNA 'samples' the P/E hybrid state 'via a spontaneous intersubunit rotation'--that was later work from Noller and Ha; etc. There are several other instances of missing citations or mis-citations. We would ask that the authors review their citations with an eye for excessive self-citations and for missing citations or mis-citations. In this context, "Ensemble-EM" is also cited as a specific method in the introduction (Abeyrathne et al., 2016; Loveland et al., 2017). However, this method is more commonly known as (3D) classification of cryo-EM images, and there are many older, more appropriate citations.
3) The sample imaged is a model sample generated by in vitro assembly with purified components of a termination complex. In order to mimic a bona fide termination complex, a short messenger RNA with a strong Shine-Dalgarno sequence followed by a start codon and immediately after by a stop codon was used (mRNA sequence: 5'-GGC AAG GAG GUA AAA AUG UGA AAAAAA-3'). Similar constructs were used to crystallize termination complexes in the past and it has been proven by smFRET experiments that, at least regarding ribosomal inter-subunit dynamics, this model sample behaves similarly to a real termination complex with a peptide linked to the P site tRNA. However, the nature of this model sample should be apparent for the non-specialist reader, highlighting its similarities with a real termination complex but also its possible limitations, especially regarding the "artificial" nature of having a stop codon so close to the Shine-Dalgarno sequence, a situation that never happens in real mRNAs. The authors should explicitly acknowledge this and discuss its implications in the main text.
4) The authors set up a couple of somewhat 'strawman' arguments in claiming that: (i) there are discrepancies in the X-ray, cryo-EM, and smFRET literature with regard to whether ribosomes can undergo intersubunit rotation while bound to class I RFs or whether the non-rotated conformation of the ribosome is stabilized by bound class I RFs and (ii) class I RFs are able to terminate translation and dissociate from the ribosome without the aid of RF3. In the case of (i), it is obviously possible for class I RF-bound ribosomes to undergo intersubunit rotation while still favoring the non-rotated conformation of the ribosome. Moreover, there are enough differences between the cited studies, both in terms of the experimental conditions as well as the technical limitations associated with the various experimental techniques, that it is easy to rationalize differences with regard to whether the class I RF-bound ribosomes would be expected to undergo intersubunit rotation and/or whether the researchers would have been able to capture/observe intersubunit rotation. In the case of (ii), decades of biochemistry from Buckingham, Ehrenberg, Green, and others had already demonstrated that class I RFs are able to terminate translation and dissociate from the ribosome without the aid of RF3, and that the role of RF3 in termination is to accelerate the spontaneous dissociation of the class I RFs. If the authors want to highlight discrepancies in the literature, they should frame them in the context of differences between the studies, experimental design, limitations of the approaches/techniques in the cited papers that might account for such discrepancies. Re-writing this paragraph also in the light of addressing the missing citations and mis-citations pointed out under (2) will further help in toning these arguments down, which would strengthen the manuscript's scholarship.
5) Class I RFs are post-translationally methylated at the Q residue of the GGQ motif of domain 3 and Buckingham, Ehrenberg, and others have shown that this methylation accelerates and/or facilitates class I-catalyzed termination both in vitro and in vivo. Nonetheless, Svidritskiy et al do not report whether and to what extent their RF2 is methylated. Was RF2 overexpressed in a manner that ensured homogeneous methylation or lack of methylation? If they are overexpressing prfB and not overexpressing prmC, it is likely that they have a mix of methylated and unmethylated RF2. Assuming they are using the wt E. coli prfB gene, then the residue at position 246 is a T, rather than an A or S, and Buckingham has shown that, in the wt T246 background, a lack of methylation at Q252 is either seriously detrimental in richer media or lethal in more minimal media. It was felt that a discussion of this issue was not needed in the main text, but that it would be helpful if the authors would include the important/relevant experimental details in the Methods section, for example, did they use the T246 wt E. coli variant of RF2; and did they overexpress prmC along with prfB?
6) Structure I is denoted and treated as a pre-termination complex, but that does not seem at all possible given that the sample was prepared by incubating a pre-termination complex for 30 min in the presence of excess RF2, conditions that Figure 1-Figure Supplement 3 suggest results in robust termination. Structure I is more likely the non-rotated conformation of a post-termination complex that is in equilibrium with its rotated counterpart, Structure V. Based on my reading of the manuscript, it is likely that the authors understand this point, but are nonetheless using this structure as a mimic/analog of a pre-termination complex. If so, I think this is fine, but the authors should explicitly state that this is what they are doing. Related to this, the authors should clarify the description of their activity assay, show the raw data, and/or report 'Released [S35]-fMet (%)' instead of 'Released [S35]-fMet, CPM' on the y-axis of Figure 1-Figure Supplement 3; as the activity assay is currently described, reported, and plotted, it is impossible to determine whether RF2 is 1% or 99% active in termination.
7) The final sentence of the manuscript reads: "Translation termination and recycling of the release factors and the ribosome therefore rely on the spontaneous ribosome dynamics, triggered by local rearrangements of the universally conserved elements of the peptidyl-transferase and decoding centers". There are a couple of problems with this sentence as written. First, smFRET experiments by Gonzalez, Puglisi, and Rodnina have previously shown that "Translation termination and recycling of the release factors and the ribosome therefore rely on the spontaneous ribosome dynamics" and the relevant articles should therefore be cited here. Moreover, given the data are static structures solved using a sample that is at equilibrium, it is not clear how the authors determined that these spontaneous ribosome dynamics were "triggered by local rearrangements of the universally conserved elements of the peptidyl-transferase and decoding centers". Isn't it equally possible, given the data presented, that the local rearrangements were triggered by the ribosome dynamics?
[Note: this preprint has been peer reviewed by eLife. The decision letter after peer review, based on three reviews, follows. The decision was sent on 24 May 2019.]
The manuscript from Munkley, Elliott and colleagues shows that the epithelial splicing regulator ESRP2 is transcriptionally upregulated by the androgen receptor (AR), an observation based on a previous study of gene expression changes in response to androgen in the androgen receptor positive LNCaP prostate cancer cell line by some of these investigators. ESRP2 upregulation leads to a series of changes in alternative splicing, including switches with potential effects in disease relapse and metastasis which correlate with disease outcomes. Prostate cancer is driven by androgens via AR, and therapy involves androgen deprivation (ADT) to slow progression. However, it has also been reported that ADT promotes epithelial mesenchymal transition (EMT) (e.g. Sun et al, 2012), which might be related to the common progression to castration resistant prostate cancer following ADT. Munkley et al show that levels of ESRP2 are reduced after androgen deprivation in 7 prostate cancer patients. A number of other analyses using additional cell lines, a xenograft model, and data from other published prostate cancer samples leads to a general proposal that a decrease in ESRP2 expression (but not ESRP1) and some splicing changes associated with its depletion following androgen deprivation may be associated with prostate cancer progression and worse outcomes. One highlighted example is exon 30 in FLNB, skipping of which is associated with metastatic progression in breast cancer.
A number of papers describing roles for ESRP1/2 in various cancers including breast, colorectal, lung, and ovarian carcinomas have yielded conflicting conclusions on the role of ESRPs or epithelial-specific isoforms it regulates, such as CD44, in cancer progression and/or patient outcomes. In some cases ESRPs are proposed to be tumor suppressors, whereas in other cases they are proposed to promote more aggressive cancers (see, for example, Zhang et al., Genes and Dev 33: 166-179 and references therein). As cited by the authors, a recent manuscript reports that duplication and increased expression of ESRP1 (which would largely promote the same splicing events as ESRP2) is associated with more aggressive human prostate cancers. Thus, a central question is whether the current manuscript can provide further clarity regarding the general role of ESRPs (including ESRP2) in cancer, including prostate cancer.
Munkley et al raise the clinically-relevant point that current treatments for prostate cancer might have undesirable side-effects by inhibiting ESRP2 mediated splicing events. Overall, the manuscript is clearly presented. The data documenting the ESRP and AR regulated splicing program, and the restriction of tumor growth by ESRPs (Figs 1-4, 6) are very clear with very nice correlations between responses to ESRP overexpression, knockdown and androgen stimulation.
1) A key concern relates to the relative levels and effects of ESRP1 and ESPR2 under conditions of androgen induction or ADT in prostate cells. The authors do a good job documenting that ESRP2 is under transcriptional control of the androgen receptor, while ESRP1 is not, and that there is a 2-fold reduction in ESPR2 expression post-ADT in cancer samples. On the other hand, a) both ESRP 1 and 2 seem down-regulated at the protein level in androgen receptor-negative prostate cancer cells lines (probably by different mechanisms), b) both ESRP1 and 2 mRNAs are up-regulated in tumor samples compared to controls, c) both ESRP1 and ESRP2 are up- regulated in a cohort of metastatic patient samples, d) the correlation between ESRP levels and recurrence free survival is a more significant for ESRP 1 than 2, and e) a number of functional assays from this manuscript and other publications argue that both ESRP1 and ESPR2 can contribute to regulate overlapping targets relevant for epithelial-specific splicing. Therefore one key question that remains is to what extent the androgen-mediated transcriptional regulation of ESRP2 does contribute to splicing regulation in the context of the relative levels / activities of ESRP1: while a number of the results presented show that androgen treatment can promote splicing towards a stronger "epithelial" pattern, the authors should make additional efforts to demonstrate that ablation of ESRP2 alone (in the presence of ESRP1) leads to substantial changes in splicing that would be expected to explain the association of a loss of ESRP2 with worse outcomes, which is an essential point for the validity of their model. For example, an analysis similar to that of Figure 1A for ESRP1 should be included, as well as other experiments aimed to determine whether the activity of ESRP1 can buffer the effects of ATD on ESRP2.
2) There is also a need for clarity in terms of the coherence of the predicted biological effects of the alternative splice site switches and at least one proof-of-principle demonstration that they are relevant for any property of prostate cells relevant to cancer, as it is difficult to draw firm conclusions from the data presented as to whether the regulation of ESRP2 by androgens is definitively associated with prostate cancer progression or outcomes in a positive or negative manner.
a) Figure 5A shows exons that are more included or skipped in prostate cancer vs normal using TCGA data. But only 6 of the 44 ESRP-AR regulated events are highlighted on the plot, two of which do not change significantly, including FLNB which is highlighted in the abstract and is the only event used to test the response to the AR antagonist Casodex. All of the events from Fig 3 should be highlighted in Figure 5A, with ESRP activated and repressed exons clearly distinguished by colour or symbol. The authors should explain -when known- the nature of the differential activities of the isoforms and whether the isoform switch observed in the presence of androgens / mediated by ESRPs is predicted to contribute, repress or be neutral to tumor cell growth, apoptosis, motility, metastasis, etc. and therefore whether a functionally coherent program of alternative splicing is coordinated by ERSPs or whether various contrasting contributions are predicted whose relative significance will depend on context, etc. If not, is it possible to stratify the data e.g. by tumor grade, or by ESRP expression level? Would this for instance, reveal different classes where events such as FLNB do show a difference between cancer and normal in some classes?
b) In Figure 6, why is FLNB e30 the only splicing event monitored for response to Casodex - especially since this is one of the events that is not altered between prostate cancer and normal tissue-? This Figure should be more systematic with more splicing events.
c) Increased inclusion of exon 30 in FLNB (which occurs for example upon androgen stimulation) is consistent with inhibition of EMT (something that could be stated more clearly in the text). But there is no mechanistic model presented as to how a change in FLNB splicing (or other targets) impacts prostate CA. What about the other alternative splicing events highlighted in Figures 4 / 5? Even if FLNB splicing switches have been shown to influence expression of EMT markers in breast cancer cells (Li et al 2018), it will be essential to show that the degree of switch observed in prostate cancer cells (for FLNB or any other gene) has a relevant biological readout.