eIF5A controls mitoprotein import by relieving ribosome stalling at the TIM50 translocase mRNA

  1. Marina Barba-Aliaga
  2. Vanessa Bernal
  3. Cynthia Rong
  4. Brian M. Zid
  5. Paula Alepuz

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Abstract

The efficient import of nuclear-encoded proteins into mitochondria is crucial for proper mitochondrial function. The conserved translation factor eIF5A is primarily known as an elongation factor which binds ribosomes to alleviate ribosome stalling at sequences encoding polyprolines or combinations of proline with glycine and charged amino acids. eIF5A is known to impact the mitochondrial function across a variety of species although the precise molecular mechanism underlying this impact remains unclear. We found that depletion of eIF5A in yeast drives reduced translation and levels of TCA cycle and oxidative phosphorylation proteins. We further found that loss of eIF5A leads to the accumulation of mitoprotein precursors in the cytosol as well as to the induction of a mitochondrial import stress response. Here we identify an essential polyproline-containing protein as a direct eIF5A target for translation: the mitochondrial inner membrane protein Tim50, which is the receptor sub-unit of the TIM23 translocase complex. We show how eIF5A directly controls mitochondrial protein import through the alleviation of ribosome stalling along TIM50 mRNA at the mitochondrial surface. Removal of the polyprolines from Tim50 rescues the mitochondrial import stress response, as well as the translation of oxidative phosphorylation reporter genes in an eIF5A loss of function. Overall, our findings elucidate how eIF5A impacts the mitochondrial function by reducing ribosome stalling and facilitating protein translation, thereby positively impacting the mitochondrial import process.

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    Reviewer #1

    Evidence, reproducibility and clarity

    The manuscript by Barba-Aliaga and colleagues describe a potential function of eIF5A for the control of TIM50 translation. The authors showed that in temperature-sensitive mutants of eIF5A several mitochondrial proteins are decreased including OXPHOS subunits, proteins of the TCA cycle and some components of protein translocases. Some precursor proteins appear to localize into the cytosol. As consequent of mitochondrial dysfunction, the expression of some stress components is induced. The idea is that eIF5A ribosome-stalling of the proline-rich Tim50 of the TIM23 complex and thereby controls mitochondrial protein set-up.

    The findings are potentially interesting. However, some control experiments are required to substantiate the findings.

    To support their conclusion the authors should show whether Tim50 levels are affected in the eIF5A-ts mutants used. Tim50 protein half-life is approximately 9.6 h (Christiano et al, 2014), which makes difficult to measure large differences in new protein synthesis upon eIF5A depletion. However, we used different approaches to show that reduction in eIF5A provokes a reduction in Tim50 protein levels and synthesis. 1) The steady-state levels of Tim50 protein (genomic HA-tagged version) are shown by western blotting analysis in Fig. S4B and confirm a significant drop of approximately 20% in the tif51A-1 mutant at restrictive temperature. 2) The use of a construct in which Tim50 is fused to a nanoluciferase reporter under the control of a tetO7 inducible promoter shows a significant 3-fold reduction in Tim50 protein synthesis in the tif51A-1 mutant compared to wild-type (Fig. 4C). In addition, the protein synthesis time is calculated and indicates that it takes the double time for the tif51A-1 strain to synthesize Tim50 protein than the wild-type (Fig. 4E). 3) The expression of a FLAG-TIM50-GFP version under a GAL inducible system also shows a significant reduction in Tim50 protein synthesis in the two eIF5A temperature-sensitive strains (Fig. S4C). 4) The proteomic analysis performed at 41ºC showed a 20% reduction in Tim50 protein levels in the two eIF5A temperature-sensitive strains, although not being statistically significant (Table S1). Furthermore, TIM50 mRNA levels were determined by RT-qPCR across all the experiments mentioned to confirm that the low levels of Tim50 protein were not due to decreased transcription or increased mRNA degradation. 5) An additional experiment of polysome profiling has been included in Fig. R1 (Figure for Reviewers) showing a higher TIM50 mRNA abundance at low polysomal fractions and a lower mRNA abundance at heavy polysomal fractions upon eIF5A depletion. This indicates that the *TIM50 *mRNA abundance is significantly shifted to earlier fractions and translation of Tim50 is reduced in the tif51A-1 mutant at restrictive temperature but not at permissive temperature. Altoghether, all these experiments confirm a significant reduction of Tim50 protein levels upon eIF5A depletion and conclusions are supported on these results.

    How are the levels of TOM and TIM23 subunits?

    Response: Our proteomic analysis shows that the protein levels of Tom70 and Tom20 receptor subunits of the TOM complex are significantly decreased in the two eIF5A temperature-sensitive strains (Table S1). These results are in agreement with the polysome profiling results, where it is seen a significant reduction of TOM70 and TOM20 mRNAs in the heavy polysomal fractions while a significant increase of these mRNAs is observed in the light fractions of eIF5A-depleted cells (Fig. 2C and Fig. S2D). Apart from Tim50, no other proteins of the Tim23 translocase complex were detected in the proteomic analysis.

    Furthermore, how are the levels of the Tim50 variant that lack the proline residues? Is the stability or function of Tim50 affected by these mutations?

    Although we did not specifically analysed the Tim50ΔPro protein levels, a quantification of the Tim50ΔPro fluorescent signal has been performed to address this matter and is shown in Fig. R2 and mentioned in the corresponding Results section. Results indicate that the Tim50 variant lacking the proline residues has similar protein levels to the wild-type version and therefore, it is tempting to say that its stability should also be similar. However, if Reviewers consider this to be essential for publishing, additional experiments using cycloheximide could be conducted in order to better assess the stability and half-life of this Tim50 version.

    Additionally, functional levels of Tim50ΔPro protein is shown by the fact that wild-type cells carrying this Tim50 protein version as the only copy of Tim50 grew well in glycerol media, where Tim50 is essential for the mitochondrial function (Fig. 5A). However, we suspect that Tim50ΔPro is a bit less efficient protein since a double mutant tif51A-1 Tim50ΔPro shows even reduced growth than the single tif51A-1 mutant (Fig. 5A). This information also responds to the comments made by Reviewer #2.

    How specific is the effect of eIF5A on Tim50? Is there any other mitochondrial substrate of eIF5A? It is not so clear to the reviewer why the authors focused on Tim50.

    Response: eIF5A has been shown to be necessary for the translation of mRNA codons encoding for consecutive prolines and, consequently, lack of eIF5A causes ribosome stalling in these polyproline motifs (Gutierrez et al., 2013; Pelechano and Alepuz, 2017; Schuller et al., 2017). In our manuscript we showed: 1) using an artificial tetO7-TIM50-nanoLuc genomic construct we demonstrate that the synthesis of Tim50 protein (measured as appearance of luciferase activity upon induction of tetO promoter) is significantly reduced by 3-fold under eIF5A depletion only when Tim50 contains the stretch of 7 consecutive prolines (Fig. 4A-D); 2) genomic Tim50-HA and plasmid FLAG-TIM50-GFP protein levels are significantly reduced upon eIF5A depletion (Fig. S4B); 3) calculation of the time for translation elongation of Tim50 mRNA shows that this time is double in cells with eIF5A depletion than in cells containing normal eIF5A levels (Fig. 4E); and 4) analysis of published ribosome profiling data shows a precipitous drop-off in ribosome density exactly where the stretch of polyprolines is located in Tim50 (540-561bp) upon eIF5A depletion but not in the control strain (Fig. 4F). This result is indicative of ribosome stalling at Tim50 polyproline motif upon eIF5A depletion. Altogether, our results strongly support a direct and specific role of eIF5A in Tim50 protein synthesis. However, as we discuss in relation to Fig. 5 and in the Discussion section, Tim50 does not seem to be the only mitochondrial substrate of eIF5A, since recovery of Tim50 protein synthesis does not rescue the growth of eIF5A mutants under respiratory conditions. In this line, we have added further data pointing to ribosome stalling for other co-translationally inserted mitoproteins which are potential substrates of eIF5A (Table S6). Accordingly, this has also been included in the Discussion section. This information also responds to the comments made by Reviewer #4.

    Our focus on Tim50 in this manuscript resides in that we found a global downregulation of mitochondrial protein synthesis (Fig.1 and 2) in parallel to the accumulation of mitochondrial precursor proteins in the cytoplasm and induction of the mitoCPR response (Fig.3). All these data were pointing to a mitochondrial protein import defect. Since Tim50 is an essential component of the Tim23 translocase complex, its protein levels are reduced in eIF5A mutants and Tim50 contains a polyproline motif, all these data were pointing towards a Tim50-dependent effect in mitochondrial protein import upon eIF5A depletion, which we addressed in the manuscript.

    Figure 1A: Which tif51A strain was used?

    Response: The proteomic analysis was performed with tif51A-1 and tif51A-3 temperature-sensitive strains (see Table S1) and Fig.1A shows the average of the values obtained for the two mutants (proteins detected as down-regulated in these two samples and from 3 different biological replicates). This is now clarified in the Figure 1A legend. A similar approach was also followed in Pelechano and Alepuz, 2017. Additionally, the ratios between the protein level in the temperature-sensitive mutant respect wild-type for each protein and for each eIF5A mutant are also shown in Table S1. This information also responds to the comments made by Reviewer #2.

    Figure 1C: The authors should show the steady state levels of some OXPHOS/TCA components to confirm the findings of Figure 1A.

    Response: Proteomic findings have been confirmed for several proteins. The steady state levels of Por1 and Hsp60 proteins were investigated by western blotting (Figs. 1C,D) and results show a significant down-regulation on the two eIF5A temperature-sensitive strains at 41ºC, which confirms the findings of Fig. 1A. Additionally, we have included the same experiment performed at 37ºC (Fig. S1E), which also confirms the same conclusion.

    Furthermore, the steady-state levels of Tim50 protein were also investigated by western blotting (Fig. S4B), and results also showed a significant down-regulation in the tif51A-1 mutant at restrictive temperature (37ºC), compared to wild-type. This result also confirms the findings of Fig. 1A.

    However, if Reviewers consider that additional confirmation for OXPHOS/TCA proteins to be essential for publishing, additional experiments could be conducted to assess the protein levels of other OXPHOS/TCA proteins.

    The manuscript contains several quantifications. However, central information like number of repeats or whether a standard deviation or S.E.M. is depicted are missing.

    Response: Clear information on the number of repeats, type of graphical representation and statistical analysis is now included for all figures in the corresponding figure legends and also detailed in the Materials and Methods section. This information also responds to the comments made by Reviewer #2.

    Figure 3: The authors propose that precursor form aggregates outside mitochondria. To assess the data, a quantification should address in how many cells are protein aggregates.

    Response: The quantification of cytoplasmic Yta12 aggregates is now included in Fig.3E, which shows significant differences between the tif51A-1 mutant and the wild-type strain. In addition, quantification of cytosolic Tim50 aggregates was already included in Fig. 4H, which also shows significant differences between the tif51A-1 mutant and the wild-type strain. These two figures include the individual values from three biological replicates (at least 150 cells were analyzed), mean, standard deviation and statistical analysis.

    Do the observed aggregated proteins interact with Hsp104? recycled?

    Response: Yes, the cytoplasmic mitochondrial precursor aggregated proteins co-localize with Hsp104 as shown in Fig. 3I for Cyc1 and in Fig. 4J for Tim50. The quantification of Cyc1 and Tim50 co-localization with Hsp104 is shown in Fig S5D.

    Significance

    See above

    Reviewer #2

    Evidence, reproducibility and clarity

    The authors report here novel findings concerning the role of eIF5A in mediating protein import to mitochondria in the model eukaryote Saccharomyces cerevisiae. It was previously known from structural and other studies that the translation factor eIF5A binds to the E-site of stalled ribosomes to help promote peptide bond formation. It was inferred by ribosome footprinting and reporter studies assessing the impact of eIF5A depletion that eIF5A is particularly needed to translate several specific amino acid motifs including polyproline stretches. However additional target sequences are known.

    Here a proteomics approach reveals clear evidence that mitochondrially targeted proteins are impacted by temperature sensitive mutations in eIF5A that deplete the factor, including those without polyprolines. The authors then use a range of molecular and cell biology to focus on the role of mitochondrial signal sequences/mitochondrial protein import and the mitochondrial stress response, before highlighting a role for poly-prolines in Tim50, a major mitochondrial protein import factor. Consistent with the ribosome footprinting done previously it is shown that a stretch of 7 prolines limit its translation when eIF5A is depleted and studies shown here are consistent with the idea that this has wider consequences for mitochondrial protein import and hence translation/stability of other proteins. However improved Tim50 translation alone, by eliminating the poly-proline motif, is not sufficient to overcome all consequences of eIF5A depletion for mitochondrial protein import and for viability, suggesting a wider role.

    In general the text flows nicely, this could be a study that explains why a large number of mitochondrially targeted proteins are impacted by depletion of eIF5A in yeast. As the poly Pro sequence in Tim50 is not conserved in higher eukaryotes it is unclear how this observation will scale to other systems, but it provides an example of how studies in a relatively simple system can trace wide-spread impact of the loss of one component of a central pathway-here protein synthesis to altered translation of a key component of another process-mitochondrial protein import. Given that eIF5A and its hypusine modifying enzymes are mutated in rare human disorders, it is likely there will be interest in this study.

    However, while the conclusions may be justified, there are significant deficiencies in how the experiments have been analysed and presented in this version of the manuscript that impact every figure shown, coupled with deficiencies in the methods section that all need to be addressed. Thus, we have here the basis of what should be a very interesting paper here, but there is a lot of work to do to remedy perceived weaknesses. It may be that the overall conclusions are entirely sound and appropriate, but I suspect that performing the statistics in less biased ways may change some of the significant differences claimed. Some explanations concerning how data analyses were conducted and the reasons for specific analysis decisions being made would also improve the narrative. These points are expanded on below.

    All the edits suggested here are aimed at improving the rigor of reporting in this study. Depending on how they are answered some may become major issues, or they could all be minor.

    1 Figure 1 shows proteomic data for response to heat shock at 41{degree sign}C. In the text it is made clear that two different temperature sensitive missense alleles the 51A-1 and 51A-3 were analysed, but the single volcano plot in Figure 1A does not say whether it is reporting one of these experiments compared to WT (which one) or some other analysis (ie have data from the 2 mutants been amalgamated somehow?). I would assume only one, but which one, and why only one plot? How different is the other experiment? Why does the Figure title say the experiment is an eIF5A deletion when it is not this?

    Response: The data shown in Figure 1A corresponds to the average values obtained in the proteomic analysis for the two temperature-sensitive mutants tif51A-1 and tif51A-3 (with data for each mutant obtained from 3 different biological replicates). Highly reproducible proteomic results and similar between the two mutants were obtained (see in Fig. S1A the MDS-plot showing all replicates for each strain and condition studied in the proteomic analysis). In addition, the proteomic data showing the protein 41°C/25°C ratio for each eIF5A temperature-sensitive mutant with respect to wild-type is shown in the Table S1. This is now clarified in the Figure 1A legend. A similar approach using the mean values of the two mutants was followed in the analysis of ribosome footprintings made in Pelechano and Alepuz, 2017. Additionally, the ratios between the protein level in the temperature-sensitive mutant respect wild-type for each protein and for each eIF5A mutant are also shown in Table S1. This information also responds to the comments made by Reviewer #1.

    Reviewer #2 is right with his/her comment and there was a mistake in the Fig.1 title. Now it is corrected and written “depletion” instead of the wrong “deletion”.

    2 Why were the experiments shown in Figure 1 done at 41{degree sign}C when all other experiments are done at 37{degree sign}C? This experimental difference is ignored in the text and no comparison of the impact of 37 vs 41 is made anywhere in the manuscript. For example it would be straightforward to perform a comparison of eIF5A depletion (by western blot), polyribosome profiles, strain growth/inhibition at both temperatures.

    Response: Our aim carrying out a proteomic experiment after 4 hours of incubation of the temperature-sensitive strains at 41°C was to get a more profound depletion of the eIF5A protein, which is very abundant and stable at normal conditions, in order to get clear proteomic results. The proteomic results were pointing to a reduction in the levels of many mitochondrial proteins, corroborating previous results obtained in murine embryonic fibroblasts upon depletion of active eIF5A conditions (https://doi.org/10.1016/j.cmet.2019.05.003). From this starting point we tried to find out the molecular mechanism involved and all the rest of experiments are done with temperature sensitive eIF5A mutants under restrictive temperature of 37°C that is the most common conditions used in yeast by us and others, and in which wild-type yeast cells still grow vigorously.

    In our previous manuscript version, the depletion of eIF5A after growing the cells at 41ºC for 4 h was shown in Fig. 1C. These data has been expanded and we have now included in Fig. S1E a western blotting analysis that shows the depletion of eIF5A after incubating the cells at 37ºC and 41 ºC for 4 h (Fig. S1E). The steady state level of the mitochondrial Por1 protein was investigated by western blotting (Figs. 1C,D) and results show a significant down-regulation in the two eIF5A temperature-sensitive strains at 41ºC. We have now included the same experiment performed at 37ºC (Fig. S1E), which also confirms the same conclusion. In addition, following Reviewer #2 suggestions, growth of the wild-type and tif51A-1 strains was tested by serial drop assays conducted at 25ºC, 37ºC and 41ºC and results confirm that both 37ºC and 41ºC temperatures impair the growth of the tif51A-1 strain but not the wild-type (Fig.S1B). The new information included in Figure S1 is now explained in the Results section. This information also responds to the comments made by Reviewer #4.

    3 Western blot quantification. In Figure 1D and E the authors present western blot quantification. However they have chosen to normalise every panel to the signal in lane 1. This means that there is no variation at all in that sample as every replicate is =1. This completely skews the statistical assumptions made (because there will be variation in that sample) and effectively invalidates all the statistics shown. An appropriate approach to use is to normalise the signal in each lane to the mean signal across all lanes in a single blot. That way if all are identical they remain at 1, but importantly variation across all samples is captured. This should be done to the loading controls as well before working out ratios or performing any statistical analyses.

    Response: Following Reviewer #2 suggestions we have changed the normalization methodology for the Western blots and we have now normalized the signal in each lane to the mean signal across all lanes in each single blot, and do so also for the loading controls. We have conducted this analysis in every western blotting experiment shown in the manuscript (Figs. 1D, S4B and S4C) and statistical analyses have been performed again to capture variation across all samples. In addition, this is also included in the Materials and Methods section (“Western blotting” subsection). Results obtain are similar to previous ones but we agree that this new approach improves the data presentation.

    For this type of experiment it is more appropriate to use Anova than a T-test. This advice applies to every western data analysis figure in the whole manuscript and so all associated statistics need to be done again from the original quantification values. If T-test is justified then a correction for multiple hypothesis testing should be applied.

    Response: After reviewing a large number of publications analysing similar data, and also following the recommendations of our statistical department, we have retained the statistics used in our previous version (with the new data normalisation as explained above, following the recommendations of Reviewer #2). This is because for each western blot figure shown, we have performed experiments with two different biological samples, wild-type cells and eIF5A mutant cells, and compared results for a single variable (Por1 protein level; eIF5A protein level or Hsp60 protein level) using three or more biological replicates. In this context, we compare the mean of the protein levels obtained from the biological replicate for two groups: wild-type and eIF5A mutant. Therefore, we believe that the statistical T-test is more appropriate. However, we could repeat the statistic if it is finally considered more appropriate.

    In all bar chart figures in addition to showing the mean and SD, each replicate value should be shown (eg as done in Fig 2C). Graphpad allows individual points to be plotted easily.

    Response: All Figures along the manuscript now include individual values from each replicate, in addition to showing the mean, SD and statistical analysis. All figure legends have been corrected accordingly.

    5 Figure 2. Polysome profiles. The impact of translation elongation stalls on global polysome profiles is complex, but a global run off is highly unlikely. Stalls later in the coding region would be anticipated to cause an increase in ribosome density as more ribosomes accumulate (like cars queueing held at a red light). However where a stall is early in a longer ORF, for example at a signal sequence, then there is less opportunity for ribosomes to join and so for those mRNAs moving to lighter points in the gradient may be observed. This may also cause knock on effects on AUG clearance and initiation which the authors appear to see as there may be an increased 60S peak in the traces shown. Are there differences in overall -low vs high polysomes, the traces shown suggest there may be? Discussion of these points is merited in the results section given the subsequent qPCR experiment.

    Response: The comments made by the Reviewer #2 are very interesting and we have made changes accordingly. First, we now show in Fig. 2A,B and Fig.S2B,C the quantification of polysomal and monosomal fractions in wild-type and* tif51A-1* mutants at permissive and restrictive temperatures. It can be appreciated that there is no impact on global polysomal and monosomal fractions under eIF5A depletion. This result does not support a global stall at 3’ region of the ORF, because then an increase in polysomal fractions should be detected; nor a global stall at the 5’ region of the ORF, because then a decrease in polysomal fractions should be detected. However, with respect to individual mRNAs, our data show a significant reduction in the heavier polysomal fractions and a significant increase in lighter polysomal fractions for mRNAs encoding mitochondrial proteins, while no significant changes were observed for mRNAs encoding cytoplasmic proteins (Fig. 2C and Fig. S2D-I). These results could be interpreted as a result of ribosome stalls in the 5’ ORF regions, for example at the signal sequence, according to Reviewer #2 comments.

    We have now introduced this comment in the Results and Discussion sections.

    Figure 2 qPCR. Using qPCR to analyse RNA levels across polysome gradients is tricky for multiple reasons including that the total RNA level varies across fractions that can impact recovery efficiencies following precipitation of gradient fractions. Often investigators use a spike in control to act as a normalising factor. Here it is completely unclear what analysis was done because details are not stated anywhere. How were primers optimized, was amplification efficiency determined? Or are they assumed to be 100%, which they will not be? A detailed description or reference to a study where that is written is needed.

    Response: The RNA extraction and analyses by RT-qPCR of the mRNA levels in the polysomal gradients was done as in previous studies of our lab (Romero et al. Sci Rep. 2020;10(1):233. doi: 10.1038/s41598-019-57132-0; Ramos-Alonso et al. PLoS Genet. 2018;14(6):e1007476. doi: 10.1371/journal.pgen.1007476; van Wijlick et al. PLoS Genet. 2016;12(10):e1006395. doi: 10.1371/journal.pgen.1006395; Garre et al., 2012 Mol Biol Cell. ;23(1):137-50. doi: 10.1091/mbc.E11-05-0419.). Three independent replicates were analyzed and results were reproducible and statistically significant, as shown in Fig. S2. Total RNA was extracted from each fraction using the SpeedTools Total RNA Extraction kit (Biotools B&M Labs). In the first replicate a spike in RNA control (Phenylalanine) was added and tested that no significant differences in the results were obtained when using or not the spike in control (see below Figure R3 for referees). mRNA relative values are always obtained from qPCR using a calibrating efficiency standard curve for each pair of oligos, after the initial set up of the qPCR for this specific pair of oligos. Therefore, slight differences in amplification efficiencies for each oligo pair are taken into account. More details about qPCR are now included in the Materials and Methods section (“Polyribosome profile analysis” subsection) and one additional reference is also included for the processing of polysomal gradient fractions.

    It would be helpful to state how long CDS are for these mRNAs and where 2-3/2-8 cut off made is what for determining what is 'short' vs 'long' and the scientific basis for selecting 2-3 vs 2-8, why 8? Were M fractions also used in qPCR, they appear to be ignored in the analysis as currently presented?

    Response: The CDS lengths of the mRNAs analyzed by polysome profiling and other important features are now included in new Table S5. We decided to classify as short length mRNAs those with a length below 600 bp, while mRNAs with lengths above 600 bp were classified as long length mRNAs. This classification was made on the basis of specific mRNA profiles obtained by qPCR analysis. mRNAs with short lengths behaved similarly and we selected 2n-3n fractions since the main polysomal peak under normal conditions appeared among 4n-5n fractions. In this line, long length mRNAs also behaved similarly between them, and we selected 2n to 8n fractions since the main polysomal peak under normal conditions appeared right after the 8n fraction. This information is now included in the Results and Materials and Methods sections.

    Regarding the use of the Monosomal fractions, yes, they were used as it can be seen in Fig. S2 which includes the distribution in Monosomal (M), lighter (2n-3n/2n-8n) or heavier (n>3/n>8, P) polysomal fractions. In the polysomal profiles we can be see that depletion of eIF5A causes a reduction in the amount of mitochondrial mRNAs in the heavier fractions and a corresponding increase in the amount of mRNAs in the lighter polysomal fractions, while no significant changes are found in the monosomal fractions. Therefore, the statistically significant change in the heavier/lighter polysomal fraction ratio is indicative of the translation down-regulation and these ratios are shown in Fig. 2C. As the Reviewer #2 commented in point 5, the change in mRNA distribution to lighter polysomal fractions may be indicative or ribosome stalling at the 5’ ORF region, compatible with a stall at the mitochondrial target signal (MTS), and this discussion is now included in the Results and Discussion section.

    Which transcripts studied here encode proteins with signal sequences? As Signal sequence pauses early in translation should impact ribosome loading this is potentially important here as discussed above.

    Response: Yes, we agree with Reviewer #2 that this information may be relevant according to the hypothesis of ribosome stall at the MTS. Therefore, a score value of probability of harbouring an MTS presequence (Fukasawa et al., 2015) is now included in Table S5 for each of the mRNAS analyzed by polysome profiling. The discussion of this point has also been included in the Results and Discussion sections.

    While it has been shown that SRP recognition is able to slow and even arrest translation of ER signal recognition peptides, there is currently no known direct SRP like correlate for mitochondrial signal sequences. We are therefore unaware of literature showing that mitochondrial signal sequences pause translation in a manner similar to ER signal sequences. We have previously found that downstream translational slowing is important for mitochondrial mRNA targeting (Tsuboi et al 2020, Arceo et al 2022), but we believe that to be distinct to what the Reviewer #2 is addressing.

    Figures 3-5. Microscopy. The false green color images in Figure 3B do not show up well. They may be better shown in grayscale, with only the multiple overlays in color.

    Response: False color for fluorescent microscopy images are widely used because they help to visualize the results to the readers and also facilitate the interpretation of multiple overlays. The use of false color is also suggested by Reviewer #4.

    Figure 3C should show the data spread for all 150 cells and normalise differently as discussed above for westerns. I do not believe that all 150 WT cells have exactly the same GFP intensity, which is what the present plot claims.

    Response: As answered to point 3 made by this Reviewer, now all figures, including Fig. 3C, are made with Graphpad and scatter plot with all individual points plotted, additionally to showing the mean, SD and statistical analysis. Results correspond to three independent experiments and show a statistically significant difference in Pdr5-GFP intensity signal between wild-type and tif51A-1 mutant. Figure legend has been corrected accordingly.

    For panels 3D-F image quantification should be shown so that the variation across a population is clear. Eg in violin plots, or showing every point. It should be clear what proportion of cells have GFP aggregates and what the variation in number of granules is.

    Response: The quantification of cytoplasmic Yta12 aggregates is now included in Fig.3E, which shows significant differences between the tif51A-1 mutant and the wild-type strain. Results show the individual values from three independent experiments with a minimum of 150 cells counted. We used a bar graph in which the values (% of cells with 0, 1, 2 or 3 aggregates) for each independent experiment are shown together with the mean, SD and statistical analysis. Figure legend has been corrected accordingly. This information also responds to the comments made by Reviewer #1.

    Figure 4H has no error bars.

    Response: New Fig.4H now shows the individual values of each of the three independent replicates, mean and error bars (SD). Figure legend has been corrected accordingly.

    Figure 5C normalises 2 WTs to 1 as in Figure 3C. Both would be better as violin plots.

    Response: Results in Fig. 5C are now shown using Graphpad and scatter plot in which all individual values are plotted (not normalized wild-type to 1), and also mean, SD and statistical significance. Results correspond to three independent replicates with the fluorescence intensity measured in more than 150 cells.

    Figure 5D/E shows 37{degree sign}C data only. Do tif51A-1 cells have aggregates at 25{degree sign}C?There are no error bars in Figure 5E or any indication of how many cells/replicates were quantified.

    Response: Figures 5D and 5E only show data at 37ºC since there are no Tim50-GFP aggregates, nor aggregates of other mitochondrial proteins, in tif51A-1 mutants at 25ºC, as shown in Fig. S3C-F and Fig. S5C.

    New Fig. 5E shows individual values from each of the three independent experiments, mean, SD and statistical significance. Results correspond to the measurement of Tim50 protein aggregates in more than 150 cells. Figure legend has been corrected accordingly.

    There are no sizing bars on any of the micrographs.

    Response: Now, all sets of microscopy figures contain a size bar and this is indicated in the corresponding Figure legend.

    The methods states that all quantification was done using ImageJ, but there is no detail given about how this was done. There are lots of ways to use ImageJ.

    Response: A detailed description of the quantifications made using ImageJ is now included in the Materials and Methods section (“Fluorescent microscopy and analysis” subsection).

    Figure 4. Luciferase assay. It is clear that there are differences in Tim50 vs Tim50∆7pro signal over time from the primary plots. It is not clear why the quantification plots on the right are from 2 selected time points. It is more typical to calculate the rate of increase in RLU per min in the linear portion of the plot, for these examples it would be approximately 30-40 mins.

    Response: As luciferase mRNA level is also increasing with time, the total amount of luciferase protein will increase exponentially. At some point mRNA levels will reach a steady state and for a brief period there could be a linear portion of RLU increase, but that will be different for each condition and reporter as ribosome quality control can have a direct impact on mRNA half-life. We have instead chosen two time points to show that statistical differences in Tim50 protein expression upon eIF5A depletion are not dependent on the time point chosen. We have also included the full data plots for readers to view the raw data.

    Figure 4F. The text on p6 states Fig 4F is evidence of RQC induction. This is an overstatement. There are no data presented relating to RQC.

    Response: Ribosome-associated quality control (RQC) is a mechanism by which elongation-stalled ribosomes are sensed in the cell, and then removed from the stall site by ribosomal subunit dissociation. This is the definition of RQC. With high levels of RQC this will cause a drop in ribosome density downstream of the stall site because of ribosome removal. While we would agree that most studies do not show actual buildup of ribosomes at ribosome stalls, and removal after the stall, we do. Our ribosome profiling analysis shows in vivo distribution of ribosome density across the TIM50 mRNA in wild-type and upon eIF5A depletion. We show that in the eIF5A depletion the ribosome density is similar to wild-type for the first ~200 bp, then there is a buildup of ribosomes for ~300 bps up to the stretch of polyproline residues, indicative of slowed ribosome movement. This slowed ribosome movement is further supported by our translation duration measurements in Fig. 4E. Then the transcript is almost completely devoid of ribosomes after the stretch of proline residues, indicating the ribosomes are removed at the proline stretch. This combination of ribosome stalling (Fig. 4E,4F) and subsequent ribosome removal (Fig 4F) is the textbook definition of RQC, so we indicate this as evidence for RQC.

    Figure 5G. It is not clear to this reviewer why the CYC1 reporter is impacted by Tim50∆pro at 25{degree sign}C. Can the authors comment?

    Response: This is also not clear to us, however, no differences are seen with and without eIF5A depletion, supporting the interpretation that Cyc1 translation is not affected by eIF5A depletion when Tim50 protein levels are restored in the Tim50∆pro strain. However, in order to clarify this point, we propose, if it is considered necessary, to remake the Tim50∆pro CYC1 reporter strain.

    Does ∆pro impact Tim50 function or is there possibly some other off target impact of integrating the reporter in this strain?

    Response: As answered to Reviewer #1 in her/his point 1, the functionality of Tim50ΔPro is shown by the fact that wild-type cells carrying this Tim50 protein version as the only copy of Tim50 grew well in glycerol media, where Tim50 is essential for the mitochondrial function (Fig. 5A). However, we suspect that Tim50ΔPro is a bit less efficient protein since a double mutant tif51A-1 Tim50ΔPro shows even reduced growth than the single tif51A-1 mutant (Fig. 5A). We do not expect off target impact in this Tim50ΔPro strains, although we cannot exclude this 100%, as in any other yeast strain obtained by transformation.

    Significance

    Strengths and Limitations:

    Strengths are that the study uses a wide range of molecular approaches to address the questions and that the results present a clear story.

    Limitations are that the poly-proline residues identified in yeast Tim50 are not conserved through to humans, so the direct relevance to higher organisms is unclear. However there are many more poly-proline proteins in human genes than in yeast and there are rare genetic conditions affecting eIF5A and its hypusination

    Advance. provides a clear link between dysregulation of eIF5A, Tim50 expression and wider impact on mitochondria.

    Audience. Scientists interested in protein synthesis, mitochondrial biology and clinicians investigating rare human disorders of eIF5A and hypusination.

    Reviewer #3 (Evidence, reproducibility and clarity (Required)):

    eIF5A is required to mediate efficient translation elongation of some amino-acid sequences like polyproline motifs, and eIF5A depletion was reported to impair mitochondrial respiration functions, decreasing mitochondrial protein levels. In this study, Barba-Aliaga et al. showed that eIF5A is important for the translation of the Pro-repeat containing protein, Tim50, an essential subunit of the TIM23 complex, the presequence translocase in the mitochondrial inner membrane. eIF5A ts mutants caused ribosome stalling of Tim50 mRNA on the mitochondrial surface at non-permissive temperature, and the removal of the Pro-repeat from Tim50 (Tim50-delta7Pro mutant) made its translation independent of eIF5A. However, the replacement of endogenous Tim50 with Tim50-delta7Pro did not recover the cell growth defects of eIF5A ts mutant on respiration medium at semi-permissive temperature, suggesting that Tim50 is not the only reason for the global mitochondrial defects caused by defective eIF5A.

    (1) I am wondering why the authors mainly used the eIF5A ts mutant strains instead of the eIF5A degron strain since, for example, the decrease in the level of Tim50 was only marginal (Fig. EV4A).

    Response: eIF5A is a very abundant protein and with high stability (SGD data: 273594 molecules/cell in YPD and 9.1 h protein half-life). We have used temperature-sensitive strains, tif51A-1, instead of eIF5A-degron because eIF5A is depleted much quicker in the first than the second system. As it can be seen in Schuller et al., Mol Cell. 2017;66(2):194-205.e5. doi: 10.1016/j.molcel.2017.03.003, with the eIF5A-degron system the addition of auxin was made in parallel to a transcriptional shut off using GAL promoter to express eIF5A-degron, changing the media from galactose to glucose and incubating the cells for 10 hours. With our approach using temperature-sensitive proteins, almost full depletion (without affecting viability, see Li et al., Genetics 2014; 197(4):1191-200 doi: 10.1534/genetics.114.166926) can be done after 4-6 h incubation at 37ºC or 4 h incubation at 41ºC (Fig. 1C and Fig. S1E, almost no signal is detected by western blotting). Therefore, we chose to use eIF5A depletion with temperature-sensitive yeast strains to achieve stronger protein depletion with shorter times and avoid secondary effects. In addition, the two eIF5A temperature-sensitive strains used in this study have been widely used by us and others (Pelechano and Alepuz, 2017; Zanelli and Valentini, 2005; Zanelli et al., 2006; Dias et al., 2008; Muñoz-Soriano et al., 2017; Rossi et al., 2014; Li et al., 2014; Xiao et al., 2024).

    (2) To show that the compromised translation of Tim50 in the absence of functional eIF5A causes defects in the mitochondrial protein import by clogging the import channels, the authors should directly observe the accumulation of the precursor forms of several matrix-targeting proteins by immunoblotting. In this sense, the results in Fig. 1C for Hsp60 do not fit the interpretation of import channel clogging.

    Response: We did not see precursor mitochondrial proteins by Western blot upon eIF5A depletion possibly because: 1) the mature protein form is more abundant and stable; 2) the precursor mito-protein appears in cytoplasmic aggregates and this may not be easily extracted during preparation of proteins for Western blot analysis. In the work by Weidberg and Amon, 2018, who described the mitoCPR response; Krämer et al., 2023, who described mitostores; and others (Wrobel et al., 2015; Boos et al., 2019) the authors use extreme over-expression of mitoproteins or mutations in essential proteins for mitochondrial biogenesis to induce clogging of translocases and accumulation of precursors in the cytosol. However, we are using and detecting proteins at their physiological levels, expressed under their native promoters, what may explain why we do not detect precursor mito-proteins. We are using what we believe to be a much more physiologically relevant system, where we use endogenous expression of mitochondrially imported proteins. Yet we see similar transcriptional induction of mitoCPR targets (CIS1, PDR5, PDR15) and mislocalization of mitochondrial proteins to Hsp104 marked aggregates (MitoStores).

    (3) The authors speculated in the Discussion section that import defects caused by compromised translation of Tim50 could cause down-regulation of translation through prolonged mitochondrial stress. However, this lacks experimental evidence.

    Response: We do see that depletion of eIF5A causes import defects through Tim50 and correlates with the down-regulation of translation of mRNAs encoding mitoproteins as shown in Fig. 2C and Fig. S2. In these figures it can be seen that mito-mRNAs move from heavier to lighter polysomal fractions upon eIF5A depletion, indicating that less ribosomes are bound to these mRNAs. Importantly, synthesis of Cyc1 and Cox5A mitochondrial proteins is recovered when TIM50 gene is replaced by an eIF5A-translation independent TIM50ΔPro gene, arguing in favor of a translation defect caused by eIF5A depletion through the collapse of import systems produced by the ribosome stalling in TIM50 mRNA.

    As discussed by Reviewer #2 and in our answers to his/her points 5 and 6, the reduction in the number of ribosomes bound to mito-mRNAs upon eIF5A depletion may be a consequence of the stall of ribosomes after the mRNA 5’ coding region encoding the MTS. This discussion has now been introduced in the Discussion section. This information also responds to the comments made by Reviewer #2.

    (4) The authors stated that human Tim50 does not have Pro-repeat motif, but how about other organisms (like other fungi species)? Is the present observation specific only to S. cerevisiae?

    Response: We have now included a sequence alignment of the Tim50 protein sequences of different yeast species (Saccharomyces cerevisiae, Candida albicans, Candida glabrata, Candida lipolytica, Schizzosaccharomyces pombe, Schizzosaccharomyces jamonicus), mouse and human (Fig. S4A). The resulting alignment shows that S. cerevisiae is the only organism presenting the seven consecutive proline residues. Still, C. albicans and C. glabrata conserve five consecutive prolines while C. lipolytica conserves five non-consecutive prolines. Furthermore, S. pombe and S. jamonicus, and mouse and human, conserve three and four non-consecutive prolines respectively. This means that the observations presented in this manuscript could be extended to other fungi species as well since most of the proline residues are conserved and are predicted to behave as eIF5A-dependent motifs for translation. Moreover, the described eIF5A-dependent tripeptide motif PDP is found in humans, mice and S. pombe at the Tim50 region where we found the PPP motif inducing ribosome stalling in S. cerevisiae (Fig S4A). This may confer eIF5A-dependent ribosome stall since as we showed in our previous ribosome footprinting (Pelechano et al., 2017), this PDP motif causes a similar high ribosome stall as the PPP motif. This discussion has now been introduced in the Results and Discussion sections.

    (5) Two references in the text are marked with "?", which should be corrected.

    Response: We thank you the Reviewer #3 for noticing this, references have been corrected in the text.

    __Reviewer #3 (Significance (Required)): __

    The essence of this work, the role of eIF5A in the efficient translation of Pro-repeat containing Tim50 (Figs. 4 and 5), is important and worth publication. However, the results of the effects of defective eIF5A on the levels and localization of mitochondrial proteins (Figs.1-3) can be even deleted to make clear the point of this work.

    Reviewer #4 (Evidence, reproducibility and clarity (Required)):

    The manuscript submitted by Barba-Aliaga et al. aims to understand on the molecular level how eIF5A influences mitochondrial function. elF5A promotes translation elongation at stretches prone to translational stalling like e.g. polyproline sequence. The finding that eIF5a influences mitochondrial function has been previously reported by the same group and by others. In this context, it was suggested that eIF5a promotes translation of N-terminal mitochondrial targeting signals. Here, the authors propose an alternative mechanism and suggest that "eIF5a directly controls mitochondrial protein import through alleviation of ribosome stalling along TIM50 mRNA." Using luciferase reporter assay, the authors indeed convincingly show that the speed of Tim50 translation is dependent on the presence of functional TIF51A, the major eIF5a in yeast, and that this dependence comes from the presence of the polyproline stretch in Tim50. The rest of the manuscript is unfortunately less clear and it is very hard, if not impossible, to sort out direct from secondary effects and compensations. The authors use proteomics, biochemical methods, RNAseq and fluorescence microscopy to analyze the temperature sensitive tif51A mutant but the conditions used in the manuscript are non-consistent between various experiments presented, in respect to the medium, temperature, preculture condition and the length of treatment used.

    Response: We do not agree with this Reviewer #4 appreciation. We used different molecular approaches to investigate different questions. Indeed, this is one of the Strengths that is highlighted by Reviewer 2 as it reads above: “Strengths are that the study uses a wide range of molecular approaches to address the questions and that the results present a clear story.” All the experiments presented in the manuscript, apart from proteomics analysis (Fig. 1), have been performed in the same conditions respect to the medium (SGal), temperature (25ºC/37ºC), preculture condition (SGal, 25ºC) and length of treatment used (4 h of depletion at 37ºC). This is already clearly specified in every Figure legend along the whole manuscript and also in the Materials and Methods section. In addition, individual values from each replicate, mean, standard deviation and statistical tests are shown for every Figure in the manuscript. Therefore, we do believe that conditions are consistent between experiments and conclusions are made based on different experiments and different scientific approaches.

    We agree with Reviewer #4 in that depletion of eIF5A protein in the temperature sensitive* tif51A-1* mutant was done in the proteomic at 41°C for 4 h, whereas in the rest of experiments depletion is made at 37°C for 4 h. As answered to Reviewer #2 (see answer to point 2), stronger depletion conditions were used to get clear proteomic results, and in order to compare both temperatures we have added now some controls showing eIF5A depletion and growth of* tif51A-1* mutant at 41°C and 37°C; importantly, we also show the reduction in mito-protein levels upon eIF5A depletion at 37°C (Fig. S1B and E).

    In some cases, the genetic background of the yeast strains and plasmids used are also unclear (e.g. pYES2-pGAL-FLAG-TIM50-GFP-URA3 - based on the provided description, TIM50 was inserted between FLAG and GFP tags; if so, mitochondrial targeting signal of Tim50 would be masked making its import into mitochondria impossible).

    Response: We do not agree with this appreciation. The genetic background of the yeast strains is always the same along the whole manuscript (BY4741 background) and is clearly specified in Table S2. In this line, all the information regarding the plasmids used can be found at Table S3 and plasmids construction is extensively detailed in the Materials and Methods section (“Yeast strains, plasmids, and growth conditions” subsection).

    Regarding the pYES2-pGAL-FLAG-TIM50-GFP-URA3 plasmid and as already mentioned in the text, we only used this plasmid to analyze by western blotting the protein synthesis of Tim50 independently of its subcellular localization. Our results (Fig. S4C) confirm that the synthesis defect of this Tim50 version upon eIF5A depletion is only due to the presence of the polyproline region. Importantly, we did not make any conclusion regarding import defects or protein localization based on these results.

    I have no doubt that upon exposure of tif51A cells to 41{degree sign}C for 4h cells initiate a number of cellular responses including mitoCPR and formation of MitoStores, however, I don´t think that the authors convincingly show that these are initiated by reduced levels of Tim50 - on the contrary, the authors show that levels of Tim50 are actually not significantly changed. This can hardly be reconciled with the model proposed. In addition, should the effect of Tif51A on mitochondria primarily be due to its effect on Tim50, then Tim50deltaPro should rescue the phenotype of tif51a mutant but it didn´t; if anything, it made it worse (see Fig 5A - the double mutant grows worse than the single ones). Furthermore, expression of Cyc1 luciferase reporter is reduced in Tim50deltaPro strain even at permissive temperature, Figure 5G. Since cytochrome c is not a substrate of the presequence pathway this again points to the secondary effects that are being observed.

    Response: We believe that our main results, summarized next and all performed at 37°C, do show that translation defects in TIM50 mRNA are the cause of the mitoCPR induction and formation of MitoStores. First, Tim50 protein levels are significantly reduced upon eIF5A depletion, as shown in Fig. S4A and S4B. Although being statistically significant, we agree that the reduction in Tim50 protein level is quantitatively low. This can be explained by the high stability of Tim50 protein, with a half-life of approximately 9.6 h (Christiano et al, 2014), which makes it more difficult to measure large differences in new protein synthesis. This is why we additionally used an accurate and quantitative test for showing the eIF5A-dependency for TIM50 mRNA translation: the fusion of the TIM50 DNA sequence to a TetO7-inducible nLuc reporter, which allows to monitor the appearance of new Tim50 protein and to estimate the translation elongation rate (Fig.4C-E). The ribosome stalling at TIM50 mRNA provoked by eIF5A depletion, where this mRNA is located at the mitochondrial surface to promote the import of nascent Tim50 protein during translation (Fig. S5B), may cause by itself the clogging of the protein import system even though yields only a slight reduction in total Tim50 cellular protein. Second, as Reviewer #4 pointed with our model, Tim50deltaPro should rescue the phenotype of tif51A-1 mutant and it does it: no mitoCPR induction and no mito-protein cytoplasmic aggregation are observed (Fig. 5D-F). Moreover, no differences in Cyc1- and Cox5a-nanoLuc synthesis are observed in the tif51A-1 Tim50ΔPro strain between depletion and not depletion conditions (Fig. 5E). These results strongly suggest that the mitochondrial protein import defects (and consequently the mitoCPR induction and mito-protein cytoplasmic aggregation) caused by eIF5A depletion are a consequence of ribosome stalling during TIM50 mRNA translation. However, Reviewer #4 is right in that mitochondrial respiration and growth in glycerol are not restored in the tif51A-1 Tim50ΔPro strain, even though Tim50 protein levels have been restored under eIF5A depletion conditions. As we discuss in the manuscript, we expect that there are additional mitochondrial proteins as targets of eIF5A, such as Yta12 and/or others. We have added further data pointing to ribosome stalling and RQC for other cotranslationally inserted mitochondrial proteins (Table S6). Accordingly, this has also been included in the Discussion section. However, the identification and study of these other mitochondrial targets goes beyond the aim of our current study.

    Minor comments

    1. Page 1, mitochondrial proteins cross do not the intermembrane space through Tom40 but rather the outer membrane Response: We think the Reviewer #4 misunderstood the sentence because we are saying exactly what he/she states: mitoproteins cross the outer membrane to the intermembrane space through Tom40. Thus our sentence is:

    “Usually, mitoproteins contact the central receptor Tom20 and cross to the intermembrane space (IMS) through Tom40, the β-barrel pore-forming subunit.”

    Therefore, we kept the sentence.

    Page 4, ATP1 is present in the matrix and not the inner membrane

    Response: This has been corrected. We thank the Reviewer for pointing this.

    The citations are missing at several places - they are left as "?"

    Response: References have been corrected in the text.

    It would be nice if microscopy images were colored in magenta and cyan, rather than red and green, to make them accessible to a wider audience.

    Response: Green and red colors for fluorescent microscopy images are widely used in high-impact journals, especially when showing mitochondrial proteins and mitochondrial marker Su9-mCherry (Hughes et al., 2016, eLife, doi: 10.7554/eLife.13943; Kakimoto et al., 2018, Scientific Reports, doi: 10.1038/s41598-018-24466-0; Kreimendahl et al, 2020, BMC Biology, doi: 10.1186/s12915-020-00888-z). However, if the Reviewers think this is essential for publication, microscopy images can be colored in magenta and cyan instead.

    Formally speaking, Tim50 is not per se a translocase, it is either a component of the translocase or, more precisely, a receptor of the translocase. Similarly, Tom20 and Tom70 are not membrane transporters but rather receptors of the TOM complex.

    Response: We have changed the title and text to be more precise in the description of the components of the mitochondrial import systems as suggested by Reviewer #4.

    Reviewer #4 (Significance (Required)):

    This is a potentially interesting story, however, the conditions used for the analysis of the temperature sensitive mutants were either too harsh or these mutants are in general impossible to control, making the manuscript, in my opinion, unfortunately too premature for publication.

    Response: We do not agree with the Reviewer #4 opinion, all experiments were done at 37ºC except the proteomic analysis that it is also confirmed further for Tim50 and Por1 proteins at 37ºC. We want to stress that we show all experiments with at least three biological replicates, individual values for each measurement are included now in the graphics as recommended by Reviewer #2, and the mean, SD and statistical tests are included. We make conclusions based in statistical significant differences along the manuscript. The temperature-sensitive yeast mutants used show reproducible analysis, they behave as expected in the controlled conditions used and they have been widely used in our lab and others (Pelechano and Alepuz, 2017; Zanelli and Valentini, 2005; Zanelli et al., 2006; Dias et al., 2008; Muñoz-Soriano et al., 2017; Rossi et al., 2014; Li et al., 2014; Xiao et al., 2024).

  2. Review Commons

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    Referee #4

    Evidence, reproducibility and clarity

    The manuscript submitted by Barba-Aliaga et al. aims to understand on the molecular level how eIF5A influences mitochondrial function. elF5A promotes translation elongation at stretches prone to translational stalling like e.g. polyproline sequence. The finding that eIF5a influences mitochondrial function has been previously reported by the same group and by others. In this context, it was suggested that eIF5a promotes translation of N-terminal mitochondrial targeting signals. Here, the authors propose an alternative mechanism and suggest that "eIF5a directly controls mitochondrial protein import through alleviation of ribosome stalling along TIM50 mRNA." Using luciferase reporter assay, the authors indeed convincingly show that the speed of Tim50 translation is dependent on the presence of functional TIF51A, the major eIF5a in yeast, and that this dependence comes from the presence of the polyproline stretch in Tim50. The rest of the manuscript is unfortunately less clear and it is very hard, if not impossible, to sort out direct from secondary effects and compensations. The authors use proteomics, biochemical methods, RNAseq and fluorescence microscopy to analyze the temperature sensitive tif51A mutant but the conditions used in the manuscript are non-consistent between various experiments presented, in respect to the medium, temperature, preculture condition and the length of treatment used. In some cases, the genetic background of the yeast strains and plasmids used are also unclear (e.g. pYES2-pGAL-FLAG-TIM50-GFP-URA3 - based on the provided description, TIM50 was inserted between FLAG and GFP tags; if so, mitochondrial targeting signal of Tim50 would be masked making its import into mitochondria impossible). I have no doubt that upon exposure of tif51A cells to 41{degree sign}C for 4h cells initiate a number of cellular responses including mitoCPR and formation of MitoStores, however, I don´t think that the authors convincingly show that these are initiated by reduced levels of Tim50 - on the contrary, the authors show that levels of Tim50 are actually not significantly changed. This can hardly be reconciled with the model proposed. In addition, should the effect of Tif51A on mitochondria primarily be due to its effect on Tim50, then Tim50deltaPro should rescue the phenotype of tif51a mutant but it didn´t; if anything, it made it worse (see Fig 5A - the double mutant grows worse than the single ones). Furthermore, expression of Cyc1 luciferase reporter is reduced in Tim50deltaPro strain even at permissive temperature, Figure 5G. Since cytochrome c is not a substrate of the presequence pathway this again points to the secondary effects that are being observed.

    Minor comments

    1. Page 1, mitochondrial proteins cross do not the intermembrane space through Tom40 but rather the outer membrane
    2. Page 4, ATP1 is present in the matrix and not the inner membrane
    3. The citations are missing at several places - they are left as "?"
    4. It would be nice if microscopy images were colored in magenta and cyan, rather than red and green, to make them accessible to a wider audience
    5. Formally speaking, Tim50 is not per se a translocase, it is either a component of the translocase or, more precisely, a receptor of the translocase. Similarly, Tom20 and Tom70 are not membrane transporters but rather receptors of the TOM complex.

    Significance

    This is a potentially interesting story, however, the conditions used for the analysis of the temperature sensitive mutants were either too harsh or these mutants are in general impossible to control, making the manuscript, in my opinion, unfortunately too premature for publication.

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    Referee #3

    Evidence, reproducibility and clarity

    eIF5A is required to mediate efficient translation elongation of some amino-acid sequences like polyproline motifs, and eIF5A depletion was reported to impair mitochondrial respiration functions, decreasing mitochondrial protein levels. In this study, Barba-Aliaga et al. showed that eIF5A is important for the translation of the Pro-repeat containing protein, Tim50, an essential subunit of the TIM23 complex, the presequence translocase in the mitochondrial inner membrane. eIF5A ts mutants caused ribosome stalling of Tim50 mRNA on the mitochondrial surface at non-permissive temperature, and the removal of the Pro-repeat from Tim50 (Tim50-delta7Pro mutant) made its translation independent of eIF5A. However, the replacement of endogenous Tim50 with Tim50-delta7Pro did not recover the cell growth defects of eIF5A ts mutant on respiration medium at semi-permissive temperature, suggesting that Tim50 is not the only reason for the global mitochondrial defects caused by defective eIF5A.

    1. I am wondering why the authors mainly used the eIF5A ts mutant strains instead of the eIF5A degron strain since, for example, the decrease in the level of Tim50 was only marginal (Fig. EV4A).
    2. To show that the compromised translation of Tim50 in the absence of functional eIF5A causes defects in the mitochondrial protein import by clogging the import channels, the authors should directly observe the accumulation of the precursor forms of several matrix-targeting proteins by immunoblotting. In this sense, the results in Fig. 1C for Hsp60 do not fit the interpretation of import channel clogging.
    3. The authors speculated in the Discussion section that import defects caused by compromised translation of Tim50 could cause down-regulation of translation through prolonged mitochondrial stress. However, this lacks experimental evidence.
    4. The authors stated that human Tim50 does not have Pro-repeat motif, but how about other organisms (like other fungi species)? Is the present observation specific only to S. cerevisiae?
    5. Two references in the text are marked with "?", which should be corrected.

    Significance

    The essence of this work, the role of eIF5A in the efficient translation of Pro-repeat containing Tim50 (Figs. 4 and 5), is important and worth publication. However, the results of the effects of defective eIF5A on the levels and localization of mitochondrial proteins (Figs.1-3) can be even deleted to make clear the point of this work.

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    Referee #2

    Evidence, reproducibility and clarity

    The authors report here novel findings concerning the role of eIF5A in mediating protein import to mitochondria in the model eukaryote Saccharomyces cerevisiae. It was previously known from structural and other studies that the translation factor eIF5A binds to the E-site of stalled ribosomes to help promote peptide bond formation. It was inferred by ribosome footprinting and reporter studies assessing the impact of eIF5A depletion that eIF5A is particularly needed to translate several specific amino acid motifs including polyproline stretches. However additional target sequences are known.

    Here a proteomics approach reveals clear evidence that mitochondrially targeted proteins are impacted by temperature sensitive mutations in eIF5A that deplete the factor, including those without polyprolines. The authors then use a range of molecular and cell biology to focus on the role of mitochondrial signal sequences/mitochondrial protein import and the mitochondrial stress response, before highlighting a role for poly-prolines in Tim50, a major mitochondrial protein import factor. Consistent with the ribosome footprinting done previously it is shown that a stretch of 7 prolines limit its translation when eIF5A is depleted and studies shown here are consistent with the idea that this has wider consequences for mitochondrial protein import and hence translation/stability of other proteins. However improved Tim50 translation alone, by eliminating the poly-proline motif, is not sufficient to overcome all consequences of eIF5A depletion for mitochondrial protein import and for viability, suggesting a wider role.

    In general the text flows nicely, this could be a study that explains why a large number of mitochondrially targeted proteins are impacted by depletion of eIF5A in yeast. As the poly Pro sequence in Tim50 is not conserved in higher eukaryotes it is unclear how this observation will scale to other systems, but it provides an example of how studies in a relatively simple system can trace wide-spread impact of the loss of one component of a central pathway-here protein synthesis to altered translation of a key component of another process-mitochondrial protein import. Given that eIF5A and its hypusine modifying enzymes are mutated in rare human disorders, it is likely there will be interest in this study.

    However, while the conclusions may be justified, there are significant deficiencies in how the experiments have been analysed and presented in this version of the manuscript that impact every figure shown, coupled with deficiencies in the methods section that all need to be addressed. Thus, we have here the basis of what should be a very interesting paper here, but there is a lot of work to do to remedy perceived weaknesses. It may be that the overall conclusions are entirely sound and appropriate, but I suspect that performing the statistics in less biased ways may change some of the significant differences claimed. Some explanations concerning how data analyses were conducted and the reasons for specific analysis decisions being made would also improve the narrative. These points are expanded on below.

    All the edits suggested here are aimed at improving the rigor of reporting in this study. Depending on how they are answered some may become major issues, or they could all be minor.

    1 Figure 1 shows proteomic data for response to heat shock at 41{degree sign}C. In the text it is made clear that two different temperature sensitive missense alleles the 51A-1 and 51A-3 were analysed, but the single volcano plot in Figure 1A does not say whether it is reporting one of these experiments compared to WT (which one) or some other analysis (ie have data from the 2 mutants been amalgamated somehow?). I would assume only one, but which one, and why only one plot? How different is the other experiment? Why does the Figure title say the experiment is an eIF5A deletion when it is not this?

    2 Why were the experiments shown in Figure 1 done at 41{degree sign}C when all other experiments are done at 37{degree sign}C? This experimental difference is ignored in the text and no comparison of the impact of 37 vs 41 is made anywhere in the manuscript. For example it would be straightforward to perform a comparison of eIF5A depletion (by western blot), polyribosome profiles, strain growth/inhibition at both temperatures.

    3 Western blot quantification. In Figure 1D and E the authors present western blot quantification. However they have chosen to normalise every panel to the signal in lane 1. This means that there is no variation at all in that sample as every replicate is =1. This completely skews the statistical assumptions made (because there will be variation in that sample) and effectively invalidates all the statistics shown. An appropriate approach to use is to normalise the signal in each lane to the mean signal across all lanes in a single blot. That way if all are identical they remain at 1, but importantly variation across all samples is captured. This should be done to the loading controls as well before working out ratios or performing any statistical analyses. For this type of experiment it is more appropriate to use Anova than a T-test. This advice applies to every western data analysis figure in the whole manuscript and so all associated statistics need to be done again from the original quantification values. If T-test is justified then a correction for multiple hypothesis testing should be applied.

    1. In all bar chart figures in addition to showing the mean and SD, each replicate value should be shown (eg as done in Fig 2C). Graphpad allows individual points to be plotted easily.

    5 Figure 2. Polysome profiles. The impact of translation elongation stalls on global polysome profiles is complex, but a global run off is highly unlikely. Stalls later in the coding region would be anticipated to cause an increase in ribosome density as more ribosomes accumulate (like cars queueing held at a red light). However where a stall is early in a longer ORF, for example at a signal sequence, then there is less opportunity for ribosomes to join and so for those mRNAs moving to lighter points in the gradient may be observed. This may also cause knock on effects on AUG clearance and initiation which the authors appear to see as there may be an increased 60S peak in the traces shown. Are there differences in overall -low vs high polysomes, the traces shown suggest there may be? Discussion of these points is merited in the results section given the subsequent qPCR experiment.

    1. Figure 2 qPCR. Using qPCR to analyse RNA levels across polysome gradients is tricky for multiple reasons including that the total RNA level varies across fractions that can impact recovery efficiencies following precipitation of gradient fractions. Often investigators use a spike in control to act as a normalising factor. Here it is completely unclear what analysis was done because details are not stated anywhere. How were primers optimized, was amplification efficiency determined? Or are they assumed to be 100%, which they will not be? A detailed description or reference to a study where that is written is needed.

    It would be helpful to state how long CDS are for these mRNAs and where 2-3/2-8 cut off made is what for determining what is 'short' vs 'long' and the scientific basis for selecting 2-3 vs 2-8, why 8? Were M fractions also used in qPCR, they appear to be ignored in the analysis as currently presented?

    Which transcripts studied here encode proteins with signal sequences? As Signal sequence pauses early in translation should impact ribosome loading this is potentially important here as discussed above.

    1. Figures 3-5. Microscopy. The false green color images in Figure 3B do not show up well. They may be better shown in grayscale, with only the multiple overlays in color. Figure 3C should show the data spread for all 150 cells and normalise differently as discussed above for westerns. I do not believe that all 150 WT cells have exactly the same GFP intensity, which is what the present plot claims. For panels 3D-F image quantification should be shown so that the variation across a population is clear. Eg in violin plots, or showing every point. It should be clear what proportion of cells have GFP aggregates and what the variation in number of granules is. Figure 4H has no error bars. Figure 5C normalises 2 WTs to 1 as in Figure 3C. Both would be better as violin plots. Figure 5D/E shows 37{degree sign}C data only. Do tif51A-1 cells have aggregates at 25{degree sign}C? There are no error bars in Figure 5E or any indication of how many cells/replicates were quantified.

    There are no sizing bars on any of the micrographs The methods states that all quantification was done using ImageJ, but there is no detail given about how this was done. There are lots of ways to use ImageJ.

    1. Figure 4. Luciferase assay. It is clear that there are differences in Tim50 vs Tim50∆7pro signal over time from the primary plots. It is not clear why the quantification plots on the right are from 2 selected time points. It is more typical to calculate the rate of increase in RLU per min in the linear portion of the plot, for these examples it would be approximately 30-40 mins.

    2. Figure 4F. The text on p6 states Fig 4F is evidence of RQC induction. This is an overstatement. There are no data presented relating to RQC.

    3. Figure 5G. It is not clear to this reviewer why the CYC1 reporter is impacted by Tim50∆pro at 25{degree sign}C. Can the authors comment? Does ∆pro impact Tim50 function or is there possibly some other off target impact of integrating the reporter in this strain?

    Significance

    Strengths and Limitations:

    Strengths are that the study uses a wide range of molecular approaches to address the questions and that the results present a clear story.

    Limitations are that the poly-proline residues identified in yeast Tim50 are not conserved through to humans, so the direct relevance to higher organisms is unclear. However there are many more poly-proline proteins in human genes than in yeast and there are rare genetic conditions affecting eIF5A and its hypusination

    Advance. provides a clear link between dysregulation of eIF5A, Tim50 expression and wider impact on mitochondria.

    Audience.

    Scientists interested in protein synthesis, mitochondrial biology and clinicians investigating rare human disorders of eIF5A and hypusination.

  5. Review Commons

    Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

    Learn more at Review Commons

    Referee #1

    Evidence, reproducibility and clarity

    The manuscript by Barba-Aliaga and colleagues describe a potential function of eIF5A for the control of TIM50 translation. The authors showed that in temperature-sensitive mutants of eIF5A several mitochondrial proteins are decreased including OXPHOS subunits, proteins of the TCA cycle and some components of protein translocases. Some precursor proteins appear to localize into the cytosol. As consequent of mitochondrial dysfunction, the expression of some stress components is induced. The idea is that eIF5A ribosome-stalling of the proline-rich Tim50 of the TIM23 complex and thereby controls mitochondrial protein set-up.

    The findings are potentially interesting. However, some control experiments are required to substantiate the findings.

    1. To support their conclusion the authors should show whether Tim50 levels are affected in the eIF5A-ts mutants used. How are the levels of TOM and TIM23 subunits? Furthermore, how are the levels of the Tim50 variant that lack the proline residues? Is the stability or function of Tim50 affected by these mutations?
    2. How specific is the effect of eIF5A on Tim50? Is there any other mitochondrial substrate of eIF5A? It is not so clear to the reviewer why the authors focused on Tim50.
    3. Figure 1A: Which tif51A strain was used?
    4. Figure 1C: The authors should show the steady state levels of some OXPHOS/TCA components to confirm the findings of Figure 1A.
    5. The manuscript contains several quantifications. However, central information like number of repeats or whether a standard deviation or S.E.M. is depicted are missing.
    6. Figure 3: The authors propose that precursor form aggregates outside mitochondria. To assess the data, a quantification should address in how many cells are protein aggregates.
    7. Do the observed aggregated proteins interact with Hsp104?

    Significance

    The manuscript by Barba-Aliaga and colleagues describe a potential function of eIF5A for the control of TIM50 translation. The authors showed that in temperature-sensitive mutants of eIF5A several mitochondrial proteins are decreased including OXPHOS subunits, proteins of the TCA cycle and some components of protein translocases. Some precursor proteins appear to localize into the cytosol. As consequent of mitochondrial dysfunction, the expression of some stress components is induced. The idea is that eIF5A ribosome-stalling of the proline-rich Tim50 of the TIM23 complex and thereby controls mitochondrial protein set-up.

    The findings are potentially interesting. However, some control experiments are required to substantiate the findings.

  6. Version published to 10.1101/2023.12.19.572290v1 on bioRxiv