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Reviewer #1 (Evidence, reproducibility and clarity):
This manuscript described the translational responses to single and combined BCAA shortages in mouse cell lines. Using Ribo-seq and RNA-seq analysis, the authors found selective ribosome pausing at codons that encode the depleted amino acids, where the pausing at valine codons was prominent at both a single and triple starvations whereas isoleucine codons showed pausing only under a single depletion. They analyzed the mechanisms of the unexpected selective pausing and proposed that the positional codon usage bias could shape the ribosome stalling and tRNA charging patterns across different amino acids. They also examined the stress responses and the changes in the protein expression levels under BCAA starvation.
The manuscript was well-written, and the findings are interesting, especially their model that positional codon usage bias could be a regulator of ribosome pausing and tRNA charging levels. Although different translational responses to distinct amino acid starvation have been widely documented, the positional codon usage bias is an interesting aspect. The manuscript's central message could have been made clearer. The authors may consider emphasizing this point more explicitly in the abstract. The rich multi-omics dataset in this work provides valuable resources for the translation field.
We thank the reviewer for the thoughtful and positive evaluation of our work.
Major comments
- The abstract may need to be revised since it is hard to immediately catch the authors' main point. If the authors regard this work as a resource paper, the current version is fine. But it could be better to point out the positional codon usages the authors found, which is a strong point of the current manuscript.
Response: We thank the reviewer for highlighting the importance of positional codon usage, which indeed represents a key finding of our study. We revised the abstract, and we now emphasize this aspect more clearly. However, in response to review #2, we have framed the observed positional effects and the idea of an elongation bottleneck as one possible contributing mechanism among others and relate it specifically to the attenuation of isoleucine-specific stalling under triple starvation.
- Page 18 "Beyond these tRNA dynamics, our data also highlight the importance of the codon positional context within mRNAs, indicating that where a codon is located within the CDS can influence both the extent of ribosomal stalling and overall translation efficiency during nutrient stress." This idea is interesting. To what extent the authors think this could be generalized? The authors may discuss whether they think their proposed model is specific to the different ribosome stalling patterns between valine and isoleucine codons or generalized to other codon combinations. For example, the positional codon usage bias will be different among different organisms, and are there any previous reports on ribosome behaviors that align with their model?
Response: We thank the reviewer for raising these important points. While our study primarily focuses on the differential stalling patterns of valine and isoleucine codons, we believe the underlying principle, that the position of codons within the CDS can modulate the extent of ribosome stalling, may under very specific circumstances extend beyond this amino acid pair. We expect this positional effect to be potentially relevant for combinations in which one amino acid has considerable enrichment near the 5′ end of coding sequences, coupled with starvation-sensitive tRNA isoacceptors, while the other does not. In our case, valine meets these criteria (see Fig. S11A and Fig. 6). In contrast, isoleucine and leucine codons, although also relatively frequent, show more variable positional distributions and are both decoded by isoacceptors that appear more resistant to starvation, as illustrated in Fig. 6 and reported for mammals and bacteria in Saikia et al. 2016; Darnell, Subramaniam, and O’Shea 2018; Elf et al. 2003; Dittmar et al. 2005. To explore the generalizability of this model, we have now included a transcriptome-wide analysis of codon position biases in mouse for all codons in the revised manuscript (Supplementary Figures 10 and 11). This analysis may serve as a basis to identify additional candidate codons for future studies. Furthermore, we now mention in the Discussion that amino acids with similar properties to valine regarding their positional distribution and tRNA isoacceptors, such as phenylalanine, and glutamine, whose tRNA isoacceptors are predicted to be fully deacylated under their respective starvation in bacteria (Elf et al. 2003), could be promising candidates for testing this model, in combination with amino acids, whose tRNAs are expected to remain partially charged under starvation or to be depleted at the start of the CDS such as i.e. His (Supplementary Fig.11C).
Even if the authors think this model can be applied to BCAA starvation, would it be possible to explain the different isoleucine codon responses between single and double starvation? The authors may discuss why the ribosome stalling at isoleucine AUU and AUC codons was slightly attenuated under double starvation. And how about the different leucine codon responses among single, double, and triple starvations, although the pausing is not as strong as isoleucine and valine codons?
Response: Regarding the attenuated isoleucine stalling under double starvation, we believe this is primarily due to stronger inhibition of the mTORC1 pathway when leucine is co-depleted (i.e., in the double starvation condition; Fig. 2D–F). This results in a more substantial suppression of global translation, reducing overall tRNA demand and thereby mitigating stalling (Darnell, 2018). A similar effect may explain the only mild leucine codon stalling observed under single leucine starvation, which also triggers strong mTORC1 inhibition and reduced initiation. In contrast, triple starvation does not suppress mTORC1 to the same extent, and thus reduced initiation alone cannot explain the absence of leucine codon stalling. Instead, we propose that additional features, such as the relative sensitivity of tRNA isoacceptors to starvation and their aminoacylation dynamics, must be considered. Valine tRNAs, for example, are known to be highly sensitive and become strongly deacylated under starvation in bacteria (Elf et al. 2003), a pattern that we also find in our own data (Fig. 6). Leucine tRNAs, by contrast, appear more resistant, possibly due to better amino acid recycling or isoacceptor-specific differences in charging kinetics, though further validation would be needed. However, combined with the strong stalling at 5′-enriched valine codons, this could reduce downstream ribosome traffic and limit exposure of leucine codons, thus preventing stalling. However, our new analysis of the positional relationship between valine and leucine codons within individual transcripts (now shown in Supplementary Figure 11B) did not reveal as strong a pattern as we observed for valine and isoleucine codons. We now discuss these points and their implications in the revised Discussion.
Experimental validation using artificial reporters carrying biased sequences may also be considered.
Response: We appreciate the reviewer’s suggestion. In fact, we explored this experimentally using a dual-fluorescent reporter system (GFP–RFP) (Juszkiewicz and Hegde 2017) containing consecutive Val or Ile codons. However, the constructs yielded variable and non-reproducible results under starvation conditions. In addition, testing the role of codon position would require placing the same codons at multiple defined positions within a single transcript and performing ribosome profiling directly on the reporter. This type of targeted experimental validation is technically challenging and falls beyond the scope of the current study. We now mention this explicitly in the revised Discussion as an interesting direction for future work.
- Page 13 "Moreover, we noticed that DT changes extend beyond the ribosomal A-site, including the P-site, E-site, and even further positions (Supplementary Fig. 2A), consistent with other studies on single amino acid starvation 39 (Supplementary Fig. 2B-C)." Could the widespread DT changes be due to Ribo-DT pipeline they used or difficulties in offset determination? Indeed the authors showed that this feature was found in other datasets, but it seems that the datasets were processed and analyzed in the same way as their data. The original Ribo-DT paper (Gobet and Naef, 2022, Methods) also showed some widespread DT changes even from RNA-seq. Another analysis method like the codon subsequence abundant shift as a part of diricore analysis (Loayza-Puch et al., 2016, Nature) did not show that broad changed regions. The authors are encouraged to re-analyze the data sets using different methods.
Response: We agree with the reviewer that the fact that DT changes beyond the ribosomal A-site is puzzling, but this has already been seen in other papers using other approaches (Darnell, Subramaniam, and O’Shea 2018). To validate that this shift is not due to our A-site assignment, enrichment analysis, or DT method, we applied the Diricore pipeline to our Ribo-Seq data. The output of the pipeline provides either 5’-end ribosome density or “subsequence” analysis using an A-site offset for each read size based on the metagene profile at the start codon. Both analyses show the same enriched codons across the different conditions as in our analyses, and the broad shift is similar, with the maximum signal at E, -1 position (Fig. R1).
- Page 13 "Intriguingly, only two of the three isoleucine codons (AUU and AUC) showed increased DTs upon Ile starvation (p < 0.01), while just one leucine codon (CUU) exhibited a modest but significant DT increase (p < 0.01) under Leu starvation (Figure 1A-B, Supplementary Figure 2A)." How can the authors explain the different strengths of ribosome pausing at Ile codons under Ile and double starvation? The AUA codon did not show any pausing under either of the starvation conditions. Throughout the manuscript, the authors mainly describe the difference between amino acids but it is desirable to discuss the codon-level difference as well.
Response: Thank you for raising this point. The observed differences in stalling between the isoleucine codons can likely be explained by differences in tRNA isoacceptor charging and positional bias within transcripts. The AUA codon is decoded by a distinct tRNAIle isoacceptor (tRNAIleUAU), which, according to our tRNA charging data (Fig. 6), remains largely charged during Ile starvation. This observation aligns with previous reports suggesting that this isoacceptor is more resistant to starvation-induced deacylation in mammalian cells and bacteria (Saikia et al. 2016; Elf et al. 2003). In contrast, the AUU and AUC codons are primarily decoded by the tRNAIleAAU isoacceptor, which we find to be strongly deacylated under Ile starvation, likely contributing to the observed codon-specific ribosome pausing. Additionally, we found that the AUA codons are relatively rare in general and particularly underrepresented near the 5′ ends of coding sequences. Our new spatial analysis (now included in Supplementary Figure 11B) confirms that AUA codons tend to occur downstream of AUU and AUC codons within transcripts. This potentially further reduces stalling on these codons and further diminishes their apparent DT increase under starvation. In order to better explain these important points, we have now expanded the codon-level discussion of these differences in the revised manuscript.
- Page 13 "We examined the effects of single amino acid starvations (-Leu, -Ile and -Val), as well as combinations, including a double starvation of leucine and isoleucine (hereafter referred to as "double") and a starvation of leucine, isoleucine, and valine ("triple"), allowing us to identify potential non-additive effects." The different double starvations, isoleucine and valine, and leucine and valine, will further support their hypothesis on the effects of the positional codon usage bias on ribosome pausing and tRNA charging patterns. Although this could be beyond the scope of the current manuscript, the authors are encouraged to provide a rationale for the chosen combination.
Response: Our experimental design evolved stepwise: we initially focused on leucine and isoleucine depletion as we found that despite their structure similarity these had respectively short and long dwell times in our previous work in the mouse liver (Gobet et al. 2020). Valine was included at a later stage to cover all the BCAAs. At the time, we did not anticipate valine to yield particularly striking effects in cells, and therefore we did not include systematic pairwise depletions involving valine. However, the strong and unexpected stalling observed at valine codons, especially under triple starvation, became a central aspect of the study. Thus, we agree that additional combinations, such as Leu/Val or Val/Ile, could be informative and now mention this in the Discussion as a potential direction for future studies.
Minor comments
Page 16 "these results imply that BCAA deprivation lowers protein output through multiple pathways: a combination of reduced initiation, direct elongation blocks (stalling), and possibly an increased proteolysis" This conclusion is totally right but may be too general. Could the authors summarize BCAA-specific features of the events including reduced initiation, stalling, and proteolysis that all contribute to protein outputs? This is not well discussed in the latter sections including Discussion.
Response: We thank the reviewer for this helpful suggestion. We agree that the original statement was too general and have revised the relevant section to more clearly delineate the distinct responses observed under each BCAA starvation condition. Specifically, we now summarize that valine starvation is characterized by strong, positionally biased ribosome stalling; leucine starvation primarily impacts translation initiation, likely via mTORC1 repression; and isoleucine starvation shows a mixed phenotype, with features of both impaired initiation and codon-specific elongation delays. We also clarify that while protein stability or degradation may contribute to the observed changes in protein output, our current data do not allow for quantitative assessment of proteolytic effects (e.g., changes in protein half-life). Therefore, we refrain from making direct quantitative conclusions about the differential modulations of proteolysis and instead focus our discussion on the translational mechanisms supported by our data.
Reviewer #1 (Significance):
The manuscript was well-written, and the findings are interesting, especially their model that positional codon usage bias could be a regulator of ribosome pausing and tRNA charging levels. Although different translational responses to distinct amino acid starvation have been widely documented, the positional codon usage bias is an interesting aspect. The manuscript's central message could have been made clearer. The authors may consider emphasizing this point more explicitly in the abstract. The rich multi-omics dataset in this work provides valuable resources for the translation field.
We thank the reviewer for the encouraging comments and share the view that positional codon-usage bias is an important result; accordingly, we now underscore this point explicitly in the revised Abstract. We also emphasise that our other observations are, to our knowledge, novel: only a handful of multi-omics studies have combined ribosome-pausing profiles with direct tRNA-aminoacylation measurements, and none has systematically examined multiple amino-acid-deprivation conditions as presented here.
Reviewer #2 (Evidence, reproducibility and clarity):
This study examines the consequences of starvation for the BRCAAs, either singly, for Leu & Ile, or for all three simultaneously in HeLa cells on overall translation rates, decoding rates at each codon, and on ribosome density, protein expression, and distribution of ribosome stalling events across the CDS for each expressed gene. The single amino acid starvation regimes specifically reduce the cognate intracellular amino acid pool and lead to deacylation of at least a subset of the cognate tRNAs in a manner dependent on continuing protein synthesis. They also induce the ISR equally and decrease bulk protein synthesis equally in a manner that appears to occur largely at the initiation level for -Leu and -Val, judging by the decreased polysome:monsome ratio, but at both the initiation and elongation levels for -Ile-a distinction that remains unexplained. Only -Leu appears to down-regulate mTORC1 and TOP mRNA translation.There is a significant down-regulation of protein levels for 50-200 genes, which tend to be unstable in nutrient-replete cells, only a fraction of which are associated with reduced ribosome occupancies (RPFs measured by Ribo-Seq) on the corresponding mRNAs in the manner expected for reduced initiation, suggesting that delayed elongation is responsible for reduced protein levels for the remaining fraction of genes. All three single starvations lead to increased decoding times for a subset of the cognate "hungry" codons: CUU for -Leu, AUU and AUC for -Ile, and all of the Val codons, in a manner that is said to correspond largely to the particular tRNA isoacceptors that become deacylated, although this correspondence was not explained explicitly and might not be as simple as claimed. All three single starvations also evoke skewing of RPFs towards the 5' ends of many CDSs in a manner correlated with an enrichment within the early regions of the CDSs for one or more of the cognate codons that showed increased decoding times for -Ile (AUC codon) and -Val (GUU, GUC, and GUG), but not for -Leu-of which the latter was not accounted for. These last findings suggest that, at least for -Val and -Ile, delays in decoding N-terminal cognate codons cause elongating ribosomes to build-up early in the CDS. They go on to employ a peak calling algorithm to identify stalling sites in an unbiased way within the CDS, which are greatest in number for -Val, and find that Val codons are enriched in the A-sites (slightly) and adjacent 5' nucleotides (to a greater extent) for -Val starvation; and similarly for Ile codons in -Ile conditions, but not for -Leu starvation-again for unknown reasons. It's unclear why their called stalling sites have various other non-hungry codons present in the A sites with the cognate hungry codons being enriched further upstream, given that stalling should occur with the "hungry" cognate codon in the A site. The proteins showing down-regulation are enriched for stalling sites only in the case of the -Val starvation in the manner expected if stalling is contributing to reduced translation of the corresponding mRNA. It's unclear why this enrichment apparently does not extend to -Ile starvation which shows comparable skewing of RPFs towards the 5'ends, and this fact diminishes the claim that pausing generally contributes to reduced translation for genes with abundant hungry codons. All of the same analyses were carried out for the Double -Ile/-Leu and Triple starvations and yield unexpected results, particularly for the triple starvation wherein decoding times are increased only at Val codons, skewing of RPFs towards the 5' ends of CDSs is correlated only with an enrichment for Val codons within the early regions of the CDSs, and stall sites are enriched only for Val codons at nearly upstream sites, all consistent with the finding that only Val tRNAs become deacylated in the Triple regime. To explain why only Val tRNA charging is reduced despite the observed effective starvation for all three amino acids, they note first that stalling at Val codons is skewed towards the 5'ends of CDS for both -Val and triple starvations more so than observed for Ile or -Leu starvation, which they attribute to a greater frequency of Val codons vs Ile codons in the 5' ends of CDSs. As such, charged Val tRNAs are said to be consumed in translating the 5'ends of CDSs and the resulting stalling prevents ribosomes from reaching downstream Ile and Leu codons at the same frequencies and thus prevents deacylation of the cognate Ile and Leu tRNAs. It's unclear whether this explanation is adequate to explain the complete lack of Ile or Leu tRNA deacylation observed even when amino acid recycling by the proteasome is inhibited-a treatment shown to exacerbate deacylation of cognate tRNAs in the single amino acid starvations and of Val tRNA in the triple starvation. As such, the statement in the Abstract "Notably, we could show that isoleucine starvation-specific stalling largely diminished under triple starvation, likely due to early elongation bottlenecks at valine codons" might be too strong and the word "possibly" would be preferred over "likely". It's also unclear why the proteins that are down-regulated in the triple starvation are not significantly enriched for stalling sites (Fig. 5B) given that the degree of skewing is comparable or greater than for -Val. This last point seems to undermine their conclusion in the Abstract that "that many proteins downregulated under BCAA deprivation harbor stalling sites, suggesting that compromised elongation contributes to decreased protein output." In the case of the double -Ile/-Leu starvation, a related phenomenon occurs wherein decoding rates are decreased for only the AUU Ile codon and only the AAU Ile tRNA becomes deacylated; although in this case increased RPFs in the 5' ends are not correlated with enrichment for Ile or Leu codons and, although not presented, apparently stall sites are not associated with the Ile codon in the double starvation. In addition, stalling sites are not enriched in the proteins down-regulated by the double starvation. Moreover, because Ile codons are not enriched in the 5'ends of CDS, it doesn't seem possible to explain the selective deacylation of the single Ile tRNA observed in the double starvation by the same "bottleneck" mechanism proposed to explain selective deacylation of only Val tRNAs during the triple starvation. This is another reason for questioning their "bottleneck" mechanism.
We thank the reviewer for their deep assessment, exhaustive reading, and constructive feedback, which have greatly contributed to improving the clarity and contextualization of our manuscript. We would first like to clarify that all experiments in this study were conducted in NIH3T3 mouse fibroblasts, not HeLa cells; we assume this was a misunderstanding and have verified that the correct cell line is consistently indicated throughout the manuscript. We also clarify that our data show that -Leu, double starvation, and to a lesser extent -Ile, downregulate mTORC1 signaling and TOP mRNA translation, whereas valine -Val and triple starvation had minimal effects on these pathways. We agree that some of our conclusions and observed phenomena were not explained in sufficient detail in the original version. To address this, we have significantly reworked the discussion, added complementary figures and clarified key points throughout the text, to better convey the underlying rationale and biological interpretation of our findings. We address each of the reviewer’s points in detail in the point-by-point responses below.
Specific comments (some of which were mentioned above):
-The authors have treated cells with CHX in the Ribo-Seq experiments, which has been shown to cause artifacts in determining the locations of ribosome stalling in vivo owing to continued elongation in the presence of CHX (https://doi.org/10.1371/journal.pgen.1005732 ). The authors should comment on whether this artifact could be influencing some of their findings, particular the results in Fig. 5C where the hungry codons are often present upstream of the A sites of called stalling sites in the manner expected if elongation continued slowly following stalling in the presence of CHX.
Response: We thank the reviewer for raising this important concern. We would like to clarify that our ribosome profiling protocol did not include CHX pretreatment of live cells. CHX was added only during the brief PBS washes immediately before lysis and in the lysis buffer itself. This approach aligns with best practices aimed at minimizing post-lysis ribosome run-off, and is intended to prevent the downstream ribosome displacement artifacts described by Hussmann et al. 2015, which result from pre-incubation of live cells with CHX for several minutes before harvesting. Furthermore, recent studies have demonstrated that CHX-induced biases are species-specific. For instance, Sharma et al. 2021 found that human (and mice) ribosomes are not susceptible to conformational restrictions by CHX, nor does CHX distort gene-level measurements of ribosome occupancy. This suggests that the use of CHX in the lysis buffer, as performed in our protocol, is unlikely to introduce significant artifacts in our ribosome profiling data. To further support this, we reanalyzed data from Darnell, Subramaniam, and O’Shea 2018, where the ribosome profiling samples were prepared without any CHX pretreatment or CHX in the wash buffer, and still observed similar upstream enrichments in their stalling profiles (see Supplementary Figure 2B-C in our manuscript). Additionally, in our previous work (Gobet et al. 2020), we compared ribosome dwell times with and without CHX in the lysis buffer and found no significant differences, reinforcing the notion that CHX use during lysis does not substantially affect the measurement of ribosome stalling. Given these considerations, we believe that CHX-related artifacts, such as downstream ribosome movement, are unlikely to explain the enrichment of hungry codons upstream of identified stalling sites in our data. We have now adjusted the Methods section to clarify this point.
-p. 12: "These starvation-specific DT and ribosome density modulations were also evident at the individual transcript level, as exemplified by Col1a1, Col1a2, Aars, and Mki67 which showed persistent Val-codon-specific ribosome density increases but lost Ile-codon-specific increases under triple starvation (Supplementary Figure 3A-D). " This conclusion is hard to visualize for any but Val codons. It would help to annotate the relevant peaks of interest for -Ile starvation with arrows.
Response: We agree and thank the reviewer for this observation. We have now annotated exemplary peaks in Supplementary Figure 3A–D to highlight ribosome pileups over Ile codons. However, we agree that it is still hard to visualize in the given Figure. Therefore, we added scatter plots for each of the transcripts that show the RPM of each position in the Ctrl vs starvation to allow for a better illustration of the milder effects upon Ile starvation (Supplementary Figure 4).
-To better make the point that codon-specific stalling under BCAA starvation appears to be not driven by codon usage, rather than the analysis in Fig. 1H, wouldn't it be better to examine the correlation between increases in DT under the single amino acid starvation conditions and the codon frequencies across all codons?
Response: We appreciate the suggestion. We have now added an additional analysis correlating the change in DT with codon usage frequency for each starvation condition. This is included in Supplementary Figure 5A-D and supports our interpretation that codon frequency alone does not explain the observed stalling behavior.
-p. 13, entire paragraph beginning with "Our RNA-seq and Ribo-seq revealed a general activation of stress response pathways across all starvations..." It is difficult to glean any important conclusions from this lengthy analysis, and the results do not appear to be connected to the overall topic of the study. If there are important conclusions here that relate to the major findings then these connections should be made or noted later in the Discussion. If not, perhaps the analysis should be largely relegated to the Supplemental material.
Response: We thank the reviewer for this comment. The paragraph in question is intended to provide a global overview of transcriptional and translational responses across the starvation conditions. It serves both as a quality control (e.g., PCA clustering and global shifts in RPF/RNA-seq profiles), and to confirm that expected starvation-induced responses are among the strongest detectable signals separating the starved samples from the control. Indeed, these observations establish that the perturbations are effective and that hallmark nutrient stress responses are globally engaged across conditions. Importantly, very few studies to date have examined transcriptional and translational responses under single or combined branched-chain amino acid (BCAA) starvation conditions. It therefore remains unclear to what extent BCAA depletion broadly remodels gene expression and translation. Our analysis contributes to addressing this gap, revealing that while certain stress pathways are commonly induced, others show condition-specific patterns such as we observed for -Ile starvation. To maintain focus, we have kept the detailed pathway analyses and transcript-level enrichments in the Supplement and rewritten the corresponding text in a more compact manner, reducing it by more than one third.
-p. 15: "Together, these findings highlight that BCAA starvation triggers a combination of effects on initiation and elongation, with varying dynamics by amino acid starvation." I take issue with this statement as it appears that translation is reduced primarily at the initiation step for all conditions except -Ile. As noted above, these data are never menitioned in the DISCUSSION as to why only -Ile would show a marked elongation component to the inhibition whereas -Val gives the greatest amount of ribosome stalling.
Response: We acknowledge the reviewer’s point. While the polysome profiles (Figure 3F-H) directly indicate that most conditions repress initiation, codon- and condition-specific elongation defects can still contribute to reduced protein output, even if they are not always detectable as global polysome shifts. Polysome profiles reflect the combined outcome of reduced initiation (which decreases polysome numbers) and ribosome stalling (which can, but does not always have to, increase ribosome density on individual transcripts, potentially counteracting the effects of reduced initiation). For valine starvation strong stalling occurs very early in the CDS (Figure 5F). This bottleneck restricts overall ribosome movement to downstream regions. Thus, while elongation is profoundly impaired, the total number of ribosomes per transcript (which polysome signals largely reflect) may appear low due to reduced overall ribosome traffic. In contrast, isoleucine codon stalling tends to occur also further downstream on the transcript (Figure 5F), allowing ribosomes to accumulate in larger numbers on the mRNA, leading to a clearer "elongation signature" in polysome profiles (Figure 3F, H). Additionally, we observed slightly higher inter-replicate variance for isoleucine starvation (Supplementary Figure 6B), which may have reduced the number of statistically significant stalling sites extracted compared to valine. We have revised the main text and discussion to clarify these points.
-I cannot decipher Fig. 4D and more detail is required to indicate the identity of each column of data.
Response: We thank the reviewer for pointing this out. Figure 4D (now Figure 4E) presents an UpSet plot, which is a scalable alternative to Venn diagrams commonly used to visualize intersections across multiple sets. Briefly, each bar in the upper plot represents the number of transcripts with increased 5′ ribosome coverage (Δpi < -0.15; p < 0.05) shared across the conditions indicated in the dot matrix below. Each column in the dot matrix highlights the specific combination of conditions contributing to a given intersection (e.g., dots under “Val” and “Triple” show the overlap between these two). To improve clarity, we have expanded the figure legend accordingly and now refer to the UpSetR methodology in the main text.
-In Fig. 4E, one cannot determine what the P values actually are, which should be provided in the legend to confirm statistical significance.
Response: Thank you for pointing that out. The legend in Figure 4E (now Figure 4F) for the p-values was accidentally removed during figure editing. We have added the legend back, so that the statistical significance is clear.
-It's difficult to understand how the -Leu condition and the Double starvation can produce polarized RPFs (Fig. 4A) without evidence of stalling at the cognate hungry codons (Fig. 4E), despite showing later in Fig. 5A that the numbers of stall sites are comparable in those cases to that found for -Ile.
Response: We appreciate this comment, which points to an important property of RPF profiles under nutrient stress. As shown in Figure 4A, all starvation conditions induce a degree of 5′ ribosome footprint polarization, a pattern that can be observed under various stress conditions and perturbations (Allen et al. 2021; Hwang and Buskirk 2017; Li et al. 2023). This general 5′ bias likely reflects a combination of slowed elongation and altered ribosome dynamics and is not necessarily linked to codon-specific stalling. However, Val and Triple starvation show a much stronger and more asymmetric polarization, characterized by pronounced 5′ accumulation and 3′ depletion of ribosome density. To better illustrate this, we have updated the visualization of polarity scores and added a new bar chart summarizing the number of transcripts showing strong 5′ polarization under each condition. This quantification highlights that the effect is markedly more prevalent under Val and Triple conditions than under Leu or Double starvation. In addition, Figure 4F demonstrates that this polarity is codon-specific under Val and Triple starvation. We clarify that this analysis tests for enrichment of specific codons near the start codon among the polarized transcripts and does not directly assess stalling. The observed enrichment of Val codons in the 5′ regions of polarized transcripts supports the interpretation that early elongation delays contribute to the RPF shift. In contrast, no such enrichment is observed for Leu starvation, reinforcing that Leu-induced polarity is not driven by stalling at Leu codons. While Figure 5 shows a similar number of peak-called stalling sites in -Leu, -Ile, and Double starvation, we note that Ribo-seq signal variability under Ile starvation was higher, which may have limited statistical power for detecting stalling sites, even though clear dwell time increases were observed at specific codons. Additionally, we have improved the metagene plots depicting total ribosome footprint density in Figure 4A. The previous version incorrectly showed sharp drops at CDS boundaries due to binning artifacts. The updated version more accurately reflects the density distribution and further highlights the stronger polarization in Val and Triple conditions. Together, these clarifications and improvements within the main text now more clearly distinguish between general polarity effects and codon-specific stalling.
-Fig. 5B: the P values should be given for all five columns, and it should be explained here or in the Discussion why the authors conclude that stalling is an important determinant for reduced translation when a significant correlation seems to exist only for the -Val condition and not even for the Triple condition.
Response: We thank the reviewer for this important observation. In response, we have revised both the text and the figures to provide a clearer and biologically more meaningful representation of the relationship between ribosome stalling and reduced protein output. Specifically, we have replaced the previous Figure 5B with a new analysis that stratifies transcripts based on the number of identified stalling sites. This updated analysis, now shown in Figure 5B, reveals that under Val and Triple starvation conditions, proteins that are downregulated tend to originate from transcripts with multiple stalling sites. Importantly, the corresponding p-values for all five conditions are now explicitly shown in the figure (as red lines). As the reviewer correctly notes, only the Val condition shows a statistically significant enrichment when considering overall overlap. Triple starvation shows a similarly high proportion of overlap (72.3%) but does not reach statistical significance, likely due to the more complex background composition under combined starvation, which increases the expected overlap and reduces statistical power. By stratifying transcripts by the number of stalling sites, we uncover that transcripts with ≥2 stalling sites are enriched among downregulated proteins specifically under Val and Triple conditions, providing a more robust indication of the link between stalling and translation repression under Valine deprivations. We believe this refined approach, prompted by the reviewer’s comment, offers a clearer and biologically more relevant perspective on the role of ribosome stalling. The original analysis previously shown in Figure 5B is now provided as Supplemental Figure 10C for transparency and comparison. We have clarified this in the revised text and now interpret the relationship more cautiously.
-p. 17: "Of note, in cases where valine or isoleucine codons were present just upstream (rather than at) the stalling position, we noted a strong bias for GAG (E), GAA (E), GAU (D), GAC (D), AAG (K), CAG (Q), GUG (V) and GGA (G) (Val starvation) and AAC (N), GAC (D), CUG (L), GAG (E), GCC (A), CAG (Q), GAA (E) and AAG (K) (Ile starvation) at the stalling site (Supplementary Figure 7B)." The authors fail to explain why these codons would be present in the A sites at stalling sites rather than the hungry codons themselves, especially since it is the decoding times of the hungry codons that are increased according to Fig. 1A-E. As suggested above, is this a CHX artifact?
Response: We agree that the observation that the listed codons are enriched at identified stalling positions (now Supplementary Figure 10C), while the depleted amino acid codon is located upstream, is a finding that needs more detailed explanation. Importantly, this phenomenon is not attributable to CHX artifacts, as our Ribo-seq protocol employs CHX solely during brief washes and lysis to prevent post-lysis ribosome run-off, rather than live-cell pre-treatment. Instead, we propose two hypotheses to explain this pattern: Firstly, many of these enriched codons are already inherently slow-decoded with longer DTs even under control conditions (Supplementary Figure 5H, newly added). Together with the upstream hungry codons they might form a challenging consecutive decoding environment, which results in an attenuated ribosome slowdown downstream after the hungry codon. Second, ribosome queuing may further explain this pattern. When a ribosome encounters a critically hungry codon and stalls, subsequent ribosomes can form a queue. The codon within the A-site of the queued ribosome would be (more or less) independent of the identity of the hungry codon itself that caused the initial stall. Since the listed codons have a high frequency within the transcriptome (Supp. Fig 5B), they therefore have an increased likelihood of appearing at this “stalling site”. Importantly, both of these phenomena are not necessarily represented by a general increase of DT on all of the listed codons and would therefore only be captured by the direct extraction of stalling sites but might be averaged out in the global dwell time analysis. We mention this phenomenon now in the Discussion.
-Fig. 5D: P values for the significance, or lack thereof, of the different overlaps should be provided.
Response: Thanks for pointing out this omission. We have now computed hypergeometric p-values for comparisons shown in Figure 5D and Figure 5E, and report them directly in the main text. As described, the overlap in stalling sites between Val and triple starvation is highly significant (2522 positions, p < 2.2×10⁻¹⁶), while overlaps involving Ile-specific stalling positions are smaller but still statistically robust (e.g., 149 positions for Ile – Triple, p = 1.77×10⁻⁵²). Notably, we also calculated p-values at the transcript level and found that a large fraction of transcripts with Ile-specific stalling under single starvation also stall under triple starvation, though often at different positions (1806 transcripts, p = 1.78×10⁻⁵⁸). These values are now included in the revised results section to support the interpretation of these overlaps.
-p. 17: "Nonetheless, when we examined entire transcripts rather than single positions, many transcripts that exhibited isoleucine-related stalling under Ile starvation also stalled under triple starvation, but at different sites along the CDS (Figure 5E). This finding is particularly intriguing, as it suggests that while Ile-starvation-specific stalling sites may shift under triple starvation, the overall tendency of these transcripts to stall remains." The authors never come back to account for this unexpected result.
Response: Thank you for highlighting this point. We've incorporated this finding as part of the proposed "bottleneck" scenario. While the isoleucine-specific stalling sites identified under Ile starvation do shift or disappear under triple starvation, we've observed that the same transcripts still tend to exhibit stalling. However, this now primarily occurs at upstream valine codons. We interpret this as a consequence of early elongation stalling caused by strong pausing at Val codons. This restriction on ribosome progression effectively prevents ribosomes from reaching the original Ile stalling sites. Therefore, the stalling sites identified under triple starvation are largely explained by the Val codons, reflecting a redistribution of stalling rather than its loss. To further clarify this crucial point, we've now explicitly mentioned Figure 5D-E again in the subsequent paragraph, which introduces the bottleneck theory.
-It seems very difficult to reconcile the results in Fig. 5F with those in Fig. 4A, where similar polarities in RPFs are observed for -Ile and -Val in Fig, 4A but dramatically different distributions of stalling sites in Fig. 5F. More discussion of these discrepancies is required.
Response: Thank you for pointing this out. The apparent discrepancy between the RPF profiles shown in Figure 4A and the stalling site distributions in Figure 5F likely reflects the fact that RPF polarization includes both general (unspecific) and codon-specific components. Figure 4A displays total ribosome footprint density, capturing both broad stress-induced effects and codon-specific contributions, whereas Figure 5F focuses specifically on peak-called stalling sites, representing localized and statistically significant pauses. Importantly, we would like to emphasise that Fig 4 shows that -Val and -Ile starvation exhibit different responses and not the same patterns. To make these differences even clearer, we have now updated the visualizations in Figure 4, including improved polarity plots and a new bar chart summarizing the number of transcripts with strong 5′ polarization. These additions highlight that the RPF profiles under -Val starvation are more pronounced and asymmetric, particularly due to 3′ depletion, while the polarity under -Ile is milder and a distinct, much smaller subset of transcripts appears to show polarity score shifts. We believe the updated figures and accompanying explanations now make these distinctions clearer.
- p. 18: " These isoacceptor-specific patterns correlate largely with the particular subsets of leucine and isoleucine codons that stalled (Figure 1A)." This correlation needs to be addressed for each codon-anticodon pair for all of the codons showing stalling in Fig. 1A.
Response: We thank the reviewer for this important comment. In the revised manuscript, we have expanded the relevant sections to address codon–anticodon relationships more thoroughly. We now explicitly match codons that exhibited increased dwell times under starvation to the corresponding tRNA isoacceptors whose charging was affected, and we provide a clearer discussion of the caveats involved. As noted by the reviewer, this correlation is not straightforward, as it is complicated by wobble base pairing, anticodon modifications, and the fact that multiple codons can be decoded by more than one isoacceptor, and vice versa. Moreover, in our qPCR-based tRNA charging assay, certain isoacceptors cannot be distinguished due to highly similar sequences (e.g., LeuAAG and LeuUAG, and LeuCAA and LeuCAG), which limits resolution for exact pairing. In addition, we did not assess absolute tRNA abundance, which may further influence decoding capacity. Nevertheless, where resolution is possible, the patterns align well: All tRNAVal isoacceptors became uncharged under Val and triple starvation, matching the consistent dwell time increases across all Val codons. Only tRNAIleAAU (decoding AUU and AUC) was deacylated, matching to these codons showing increased dwell times, while AUA (decoded by still-charged tRNAIleUAU) did not. Only CUU (decoded by uncharged tRNALeuGAA) showed increased dwell time. A mild deacylation of the other Leu isoacceptors was observed, but isoacceptor-level resolution is limited by assay constraints. However, these rather minimal tRNA and DT changes were consistent with more dominant initiation repression rather than elongation stalls. To support this analysis, we included an illustrative figure (now in Supplementary Figure 12F) summarizing the codon–anticodon matches.
-p. 19: "For instance, in our double starvation condition, unchanged tRNA charging levels (Figure 6E) may result from a pronounced downregulation of global translation initiation, likely driven by the activation of stress responses (Figure 2), subsequently lowering the demand for charged tRNAs as it has been observed previously for Leu starvation 39.” This seems at odds with the comparable down-regulation of protein synthesis for the Double starvation and -Leu and -Ile single starvations shown in Fig. 3C. Also, in the current study, Leu starvation does lower charging of certain Leu tRNAs.
Response: We thank the reviewer for raising this important point. In the revised manuscript, we have clarified this section and now offer a more refined interpretation of the tRNA charging patterns observed under double starvation. While Figure 3C shows a comparable reduction in global protein synthesis across the -Leu, -Ile, and double starvation conditions, it needs to be considered that the OPP assay has limited sensitivity. It operates in a relatively low fluorescence intensity range and is subject to background signal, which may obscure subtle differences between conditions. Moreover, other factors such as changes in protein stability or turnover could also contribute to the observed differences. Therefore, inter-condition differences in translation repression should be interpreted with caution. However, based on our stress response analysis (Figure 2), mTORC1 inactivation appears strongest under double starvation, likely leading to more profound suppression of translation initiation. This would reduce the overall demand for charged tRNAs and could explain why no detectable tRNA deacylation was observed under double starvation, even though mild uncharging of Leu isoacceptors occurred under -Leu, which exhibited a milder stress response. This distinction is consistent with the observed mild dwell time increases for one Leu codon under -Leu, but not in the double condition. Similarly, the absence of Ile codon stalling and tRNA deacylation under double starvation may be attributed to stress-driven reductions in elongation demand, preventing the tRNA depletion and codon-specific delays observed under single Ile starvation. A more direct clarification is now included in the revised manuscript.
Reviewer #2 (Significance):
The results here are significant in showing that starvation for a single amino acid does not lead to deacylation of all isoacceptors for that amino acid and in revealing that starvation for one amino acid can prevent deacylation of tRNAs for other amino acids, as shown most dramatically for the selective deacylation of only Val tRNAs in the triple BRCAA starvation condition. For the various reasons indicated above, however, I'm not convinced that their "bottleneck" mechanism is adequate to explain this phenomenon, especially in the case of the selective deacylation of Ile vs Leu tRNA in the Double starvation regime. It's also significant that deacylation leads to ribosome build-up near the 5'ends of CDS, which seems to be associated with an enrichment for the hungry codons in the case of Val and Ile starvation, but inexplicably, not for Leu or the Double starvations. This last discrepancy makes it hard to understand how the -Leu and Double starvations produce RPF buildups near the 5 ends of CDSs. In addition, the claim in the Discussion that "our data also highlight the importance of the codon positional context within mRNAs, indicating that where a codon is located within the CDS can influence both the extent of ribosomal stalling and overall translation efficiency during nutrient stress" overstates the strength of evidence that the stalling events lead to substantial decreases in translational efficiencies for the affected mRNAs, as the stalling frequency and decreased protein output are significantly correlated only for the -Val starvation, and the data in Fig. 3 D-H suggest that the reductions in protein synthesis generally occur at the level of initiation, even for -Val starvation, with a contribution from slow elongation only for -Ile-which is in itself difficult to understand considering that stalling frequencies are highest in -Val. Thus, while many of the results are very intriguing and will be of considerable interest to the translation field, it is my opinion that a number of results have been overinterpreted and that important inconsistencies and complexities have been overlooked in concluding that a significant component of the translational inhibition arises from the increased decoding times at hungry codons during elongation and that the selective deacylation of Val tRNAs in the Triple starvation can be explained by the "bottleneck" mechanism. The complexities and limitations of the data and their intepretations should be discussed much more thoroughly in the Discussion, which currently is devoted mostly to other phenomena often of tangential importance to the current findings. A suitably revised manuscript would clearly state the limitations and caveats of the proposed mechanisms and consider other possible explanations as well.
Again, we thank the reviewer for the valuable insights and constructive critiques. We believe that the concerns regarding potential overinterpretation and inconsistencies have now been addressed through clearer explanations and more cautious interpretation throughout the revised manuscript. We also agree that the original Discussion included aspects that, while interesting, were of secondary importance. In light of the reviewer’s suggestions, we have restructured and rebalanced the Discussion to focus more directly on the key findings and their implications. Importantly, we wish to clarify that we do not propose the elongation bottleneck model as a general mechanism across all conditions. In particular, for double (Leu/Ile) starvation, we attribute the observed effects primarily to stress response–mediated translational repression, and not to codon-specific stalling or tRNA depletion. We believe that this distinction is now more clearly conveyed in the revised manuscript.
Reviewer #3 (Evidence, reproducibility and clarity):
Summary
Worpenberg and colleagues investigated the translational consequences of branched-chain amino acid (BCAA) starvation in mouse cells. Limitation of individual BCAAs has been reported to cause codon-specific and global translational repression. In this paper, the authors use RNA-seq, ribosome profiling (Ribo-seq), proteomics, and tRNA charging assays to characterize the impacts of individual and combined depletion of leucine, isoleucine, and valine on translation. They find that BCAA starvation increases codon-specific ribosome dwell times, activates global translational stress responses and reduces global protein synthesis. They infer that this effect is due to decreased translation initiation and codon-specific translational stalling. They find that the effects of simultaneous depletion are non-additive. In valine and triple (valine, leucine, and isoleucine) depletion, they show that affected transcripts have a high density of valine codons early in their coding sequences, creating an "elongation bottleneck" that obscures the impact of starvation of other amino acids. Finally, they identify isoacceptor-specific differences in tRNA charging that help explain the codon-specific effects that they observe.
We find the major findings convincing and clear. We find that some results are incompletely explained. We suggest an additional experiment and also have some minor comments that we hope will improve clarity and rigor.
We thank the reviewer for the thorough and constructive feedback. We appreciate the recognition of our main findings and the helpful suggestions for improving the manuscript. Below we address each point in detail.
Major comments
Figure 3O: In this figure and the associated text, the authors try to determine whether differences in protein degradation can explain why some proteins have higher ribosome density but lower proteomic expression. However, since this analysis relies on published protein half-lives from non-starvation conditions and on the assumption that protein synthesis has entirely stopped, we are not convinced it is informative for this experimental context. It does not distinguish between a model in which protein synthesis has been reduced by stalling and a model in which both protein synthesis and degradation rate have increased, which are both consistent with their Ribo-seq and proteomic data. To address this issue, the authors should either perform protein half-life measurements under their starvation conditions, or more clearly explain these two models in the text and acknowledge that they cannot distinguish between them.
Response: We agree with the reviewer that our current analysis, which is based on protein half-lives obtained under non-starvation conditions, can not definitively separate the effects of reduced translation from those of increased protein degradation. We have revised the relevant section in the manuscript to more clearly state that this analysis is correlative in nature and serves only to explore one possible explanation for the observed disconnect between ribosome density and protein levels. We now also explicitly acknowledge that our dataset does not allow us to distinguish between a model in which protein output is reduced due to stalling and one in which both translation and degradation rates are altered. However, the observed log2FC in the proteomics data are often milder than expected based on complete-medium condition half-life alone, which would be difficult to reconcile with a dominant contribution from global protein destabilization. That said, we also acknowledge that protein degradation is highly context- and protein-specific, and that proteolytic regulation might still play a role. Performing a direct protein half-life measurement under our starvation conditions would indeed be required to rigorously test this, but such an experiment is outside the scope of this study. We now highlight this as a limitation and a valuable direction for future work, and we have softened any interpretations in the main text to reflect the uncertainty regarding the contribution of protein stability changes.
Minor comments
Figure 1G: Why does intracellular valine seem to be less depleted under starvation conditions than intracellular leucine or isoleucine? Are the limits of detections different for different amino acids? The authors should acknowledge this discrepancy and comment on whether it has any implications for interpretation of their results.
Response: We thank the reviewer for this important point. While valine appears slightly less depleted than leucine or isoleucine in Figure 1G, the fold changes and absolute reductions are strong for all three BCAAs, including valine. To further illustrate this, we have added a supplementary bar chart showing the measured intracellular concentrations in µmol/L, including mean and variance across five biological replicates (Supplementary Figure 5A). We believe that the variation may reflect technical factors, such as differences in detection sensitivity or ionization efficiency between amino acids in the targeted metabolomics assay and, therefore, that the observed difference does not have a meaningful impact on the interpretation of our results. We now directly acknowledge these differences in the main text.
Figure 1H: These data do not appear to meet the assumptions for linear regression. We suggest either reporting a Spearman R correlation (as the data appears linear in rank but not absolute value), or remove it entirely - we think the plot without statistics is sufficient.
Response: We thank the reviewer for the suggestion. In the revised manuscript, we removed the statistical annotation and retained only the trend line to illustrate the general pattern. We agree that this visualization alone is sufficient to support the qualitative point we aimed to convey.
Figure 2B: The in-text description of this figure states that "most" ISR genes show a "robust induction," but only three genes are shown in the figure, two of which are upregulated. The authors should instead specify that 2 out of the 3 genes profiled were robustly induced.
Response: We have rephrased the sentence to say “two of the three genes profiled…” for precision and consistency with the data shown.
Figure 2D: Please include the full, uncropped blots in the supplementary materials.
Response: We have now added the full, uncropped western blots to the supplementary material (Supplementary Figure 8).
Figure 2E: Swap the positions of the RPS6 and 4E-BP1 plots so they line up with their respective blots to make these figures easier to interpret. Authors should consider doing a one-way ANOVA and post-hoc analysis, if we correctly understand that they are making a conclusion about the difference between multiple groups in aggregate.
Response: We thank the reviewer for the suggestion. The alignment of the RPS6 and 4E-BP1 plots with their respective blots has been corrected. As this panel focuses on comparisons to the control condition only, we have retained the original presentation.
Figure 4B: Panel A in this figure is very convincing, and these plots don't add additional information. The authors could consider removing them. If this panel stays in, we suggest removing the "mid index" plot, since it is never referenced in the text and doesn't seem relevant to the message of the figure.
Response: We appreciate the feedback. While we considered removing panel B as suggested, we decided to retain it because it provides a useful summary of panel A. To improve clarity and visual interpretation, we replaced the original boxplot with a bar plot displaying mean values and SEM error bars. We believe the bar plot now nicely illustrates that Val and Triple starvation lead to stronger effects, especially in the reduction of the 3′ index. The “mid index” plot, which was not referenced in the text and did not contribute to the central message, has been removed as suggested.
Figure 4E: Why is there a reduction in frequency of a Leu and a Val codon under Ile starvation?
Response: Thank you for highlighting this observation. The reduction in the frequency of a specific Leu and Val codon under Ile starvation in Figure 4F (former Figure 4E) is indeed intriguing. This figure reflects codon usage in the first 20% of the CDSs among the subset of transcripts that exhibit a footprint polarization under each starvation condition. As such, the observed depletion likely arises from the specific transcript composition of the polarized subset under -Ile, which differs from that under -Val or other conditions. Importantly, this pattern is not consistently observed when analyzing the full transcripts (another Leu codon is affected), indicating that it is not a systematic depletion of these codons. One possibility is that an increased frequency of Ile codons (AUC) within the constrained region may lead to a relative underrepresentation of other codons, such as Leu and Val. Alternatively, this may reflect non-random codon co-occurrence patterns within specific transcripts. While our current data do not allow us to investigate this further, we acknowledge these as speculative explanations and now mention this point in the Discussion as a potential avenue for future study.
Figure 5G: There appears to be one Val codon early in the Hint1 transcript without much stalling under triple or valine starvation conditions. The authors should acknowledge this and comment on why this may be.
Response: We thank the reviewer for pointing this out. While the Hint1 transcript indeed contains a valine codon early in its CDS, no clear stalling peak was observed at that position under valine or triple starvation. Several factors may contribute to this: local sequence context can influence ribosome pausing, and not all cognate codons necessarily lead to detectable stalling even under amino acid starvation. Additionally, coverage at the 5′ end of Hint1 is relatively sparse in our dataset, and potential mappability limitations, such as regions with low complexity or repetitive elements, may further reduce resolution at specific sites. We now briefly mention this in the manuscript to clarify the possible causes.
Figure 5B: In the text referencing this figure, the authors state that "a high number of downregulated proteins with associated ribosome stalling sites did not show an overall decreased mean RPF count...as it would be expected from translation initiation defects, linking these stalling sites directly to proteomic changes." However, RPF is affected both by stalling (increases RPF) and initiation defects (decreases RPF). A gene with both stalling and decreased initiation may appear to have no RPF change. The data does suggest a contribution from stalling, but the authors should also acknowledge that reduced initiation may also be playing a role.
Response: We agree with the reviewer comment. Our cited statement should indeed be more nuanced. The reviewer correctly points out that RPFs are influenced by both increased ribosome density due to stalling and decreased ribosome density due to reduced initiation. Therefore, a gene experiencing both stalling and reduced initiation might appear to have no net change in RPF, or even a slight increase if stalling is dominant. Thus, while the presence of stalling sites strongly suggests a contribution from compromised elongation to reduced protein output, we cannot definitively rule out a concurrent role for reduced initiation, even in cases where RPF counts are not globally decreased. We revised this section in the manuscript to acknowledge this interplay.
Figure 5E: the black text on dark brown in the center of the Venn diagram is difficult to read. The diagram should either have a different color scheme, or the text in the center should be white instead of black for higher contrast.
Response: We have adjusted the text color for better contrast and improved readability.
Supplementary Figure 1C: The ribosome dwell time data in this study is described as "highly correlated" with another published dwell time dataset, but the P and E site data do not seem strongly correlated. The authors should remove the word "highly."
Response: We have removed the word “highly” to have a more cautious interpretation in the text.
Supplementary Figure 3E: Not all of the highlighted codons in this figure are ones with prolonged dwell times. To clarify the point that dwell time change is not related to codon frequency, this figure should only highlight codons that have a significantly prolonged dwell time in at least one starvation condition.
Response: We thank the reviewer for pointing this out. To improve clarity, we have revised the figure and now specifically highlight codons with significantly prolonged dwell times with stars.
Supplementary Figure 5C: The gene Chop is mentioned in the main text when referencing this figure, but is absent from the heatmap.
Response: We thank the reviewer for noting this. The gene Chop is annotated under its alternative name Ddit3 in the current version of the heatmap and is indeed present. To avoid confusion, we have now updated the label in the figure to display Chop (Ddit3) directly.
Supplementary Figure 7A: The authors could clarify this figure by adding additional language to either the figure panel or the figure legend specifying that the RPM metric being used comes from Ribo-seq.
Response: We have updated the legend to explicitly state that the RPM values shown are derived from Ribo-seq data.
Supplementary Figure 7D: The metric used to describe the spatial relationship between the first valine and isoleucine codons in transcripts in this figure seems to be describing something conceptually similar to the stalling sites in Figure 5G, but uses a different metric. These figures would be easier to interpret if these spatial relationships were presented in a consistent way throughout the manuscript.
Response: We thank the reviewer for this helpful observation. Supplementary Figure 7D (now Supplementary Figure 11B) originally used a gene-length-normalized metric to describe codon spacing, whereas Figure 5G depicted absolute nucleotide distances to stalling sites. To ensure consistency across the manuscript, we have now updated Supplementary Figure 11B to also use absolute distances. We believe this adjustment improves clarity and allows for a more direct comparison between spatial codon patterns and stalling events.
Discussion:
Reader understanding would be improved if the relevance of paragraphs were established in the first sentence. For instance, in the paragraphs about adaptive misacylation and posttranscriptional modifications, it is unclear until the end of the paragraph how these topics are relevant. Introducing the relevant aspects of the study (the fact that some starvation conditions have less severe effects and the observation about m6A-related mRNAs) at the beginning of these paragraphs would improve clarity.
Response: We thank the reviewer for this helpful comment. We agree that the flow and clarity of the Discussion can be improved by making the relevance of each paragraph clearer from the outset. In the revised manuscript, we have restructured these sections to better highlight the connection between each topic and our main findings. These changes also align with suggestions from Reviewer 2, and we believe they help to focus the Discussion more tightly around the core insights of our study.
The authors should provide more information and speculation about possible physiological relevance of their findings, particularly about the way that the effects of triple starvation are highly valine-dependent. Are there physiological conditions under which starvation of all three BCAAs is more likely than starvation of one or two of them? If so, are there any reasons why a valine-based bottleneck might be advantageous?
Response: We appreciate the reviewer's insightful question regarding the physiological relevance of our findings, particularly the valine-dependent bottleneck observed under triple BCAA starvation. This prompts a crucial discussion on the broader biological context of our work.
While complete starvation of all three BCAAs might be less frequent than individual deficiencies, such conditions are physiologically relevant in several contexts. In prolonged fasting, starvation, or severe cachectic states associated with chronic diseases (e.g., advanced cancer, critical illness), systemic amino acid pools, including BCAAs, can become significantly depleted due to increased catabolism and insufficient intake (Yu et al. 2021). Moreover, certain specialized diets or therapeutic strategies aim to modulate BCAA levels. For instance, in some Maple Syrup Urine Disease (MSUD) management protocols, BCAA intake is severely restricted to prevent the accumulation of toxic BCAA metabolites (Mann et al. 2021). Similarly, emerging cancer therapies sometimes explore nutrient deprivation strategies to selectively target tumor cells, which could involve broad BCAA reduction (e.g. Sheen et al. 2011; Xiao et al. 2016).
In these contexts, a valine-based bottleneck, as we describe, could indeed represent an adaptive strategy. If valine-tRNAs are particularly susceptible to deacylation and valine codons are strategically enriched at the 5' end of transcripts, stalling at these early positions could serve as a rapid "gatekeeper" for global translation. This early-stage inhibition would conserve cellular energy and available amino acids by quickly reducing the overall demand for charged tRNAs. Such a mechanism could potentially prioritize the translation of a subset of proteins that might have different codon usage biases or are translated via alternative, less valine-dependent mechanisms. This aligns with the concept of a multi-layered translational control where global initiation repression (as reflected in mTORC1 inhibition and polysome profiles) is complemented by specific elongation checkpoints, allowing for a more nuanced and adaptive response to severe nutrient stress.
Reviewer #3 (Significance):
Nature and significance of the advance
The main contribution of this work is to demonstrate that depletion of multiple amino acids simultaneously impacts translation elongation in ways that are not necessarily additive. These impacts can depend on the distribution of codons in a transcript. It adds to a growing body of work showing that essential amino acid starvation can cause codon-specific ribosome stalling. The authors suggest that the position-dependent stalling they observe could be a novel regulatory mechanism to alleviate the effects of multi-amino acid starvation. However, it is not fully clear from the paper what the significance of a valine-based regulatory adaptation to BCAA starvation is, or whether simultaneous starvation of all three BCAAs is of particular physiological relevance. The paper's primary contribution is mainly focused on the similarity between valine and triple BCAA starvation, and it provides limited insight into the effects of combined depletion of two BCAAs.
Context of existing literature
Although ribosome profiling does not distinguish between actively-elongating and stalled ribosomes, sites with higher read coverage, and thereby higher inferred dwell time, can be used to infer ribosome stalling (Ingolia 2011). Various downstream effects of essential amino acid depletion have been documented, such as leucine deficiency being sensed by mTORC1 via leucyl-tRNA synthetase (Dittmar 2005, Han 2012), and shared transcriptional responses among many amino acid depletion conditions (Tang 2015). These authors have previously measured the translational effects of nutrient stress using ribosome profiling (e.g., Gobet 2020), as have others (Darnell 2018, Kochavi et al. 2024). The present work represents the first study (to our knowledge) combining BCAA depletions, representing an incremental and useful contribution to our understanding of translational responses to stress conditions.
Audience
This work is of interest to investigators studying the response of human cells in stress conditions, such as in human disease, as well as investigators studying the basic biology of eukaryotic translational control.
Reviewer expertise: mRNA decay and translation regulation in bacteria.
We hope the authors have found our comments thoughtful and useful. We welcome further discussion or clarification via email: Juliana Stanley (julianst@mit.edu) and Hannah LeBlanc (leblanch@mit.edu).
We sincerely thank the reviewers for their thoughtful and constructive feedback, as well as for their careful and thorough reading of our manuscript. We also gratefully acknowledge the invitation for further discussion and would be happy to engage in future correspondence.
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