The layered costs and benefits of translational redundancy

Article activity feed

1. 

   Version published to 10.7554/elife.81005 on eLife

   Mar 2, 2023
2. 

   eLife

   Nov 9, 2022

   Author Response

   Reviewer #1 (Public Review):

   The layered costs and benefits of translational redundancy by Raval et al. aim to investigate the impact of gene copy number redundancy on E. coli fitness, using growth rate in different media as the primary fitness readout. Genes for most tRNAs and the three ribosomal RNAs are present in multiple copies on the E. coli chromosome. The authors ask how alterations in the gene copy number affect the growth rate of E. coli in growth media that support different rates of growth for the wild type.

   While it was shown before that mutants with reduced numbers of ribosomal RNA operons grow at reduced rates in rich medium (LB), this study extends these findings and reaches some important conclusions:

   1. In a poor medium (supporting slow growth rates), the mutants with fewer rRNA operons actually …

   Author Response

   Reviewer #1 (Public Review):

   The layered costs and benefits of translational redundancy by Raval et al. aim to investigate the impact of gene copy number redundancy on E. coli fitness, using growth rate in different media as the primary fitness readout. Genes for most tRNAs and the three ribosomal RNAs are present in multiple copies on the E. coli chromosome. The authors ask how alterations in the gene copy number affect the growth rate of E. coli in growth media that support different rates of growth for the wild type.

   While it was shown before that mutants with reduced numbers of ribosomal RNA operons grow at reduced rates in rich medium (LB), this study extends these findings and reaches some important conclusions:

   1. In a poor medium (supporting slow growth rates), the mutants with fewer rRNA operons actually grow faster than the wild type, showing that redundancy comes at a cost.

   1. The same is true for mutants with reduced gene copy number of certain tRNAs and correlates with slower rates of protein synthesis in these mutants.

   1. That rRNA operon gene copy number is more decisive for growth rate than any tRNA gene copy number (>1).

   In addition, measurements of strains with deletions of genes encoding tRNA-modification enzymes that affect tRNA specificity are included. While interesting, no unifying conclusion could be reached on the impact of these mutations on growth rate.

   Thank you for this clear summary of our work.

   The well-known "growth law" relationships between growth rate and macromolecular composition (RNA/protein ratio, for example) specifically concern steady-state growth rates. It is concerning that all growth rates in this work were measured on cultures that were only back-diluted 1:100 from overnight LB precultures. That only allows 6-7 doubling times before the preculture OD is reached again. The exponential part of growth would end before that, allowing perhaps only 3-4 generations of growth in the new medium before the growth rate was measured. Thus, the cultures were not in balanced growth ("steady state") when the measurements were made, rather they were presumably in various states of adapting to altered nutrient availability.

   A detailed connection with exact growth rate laws indeed requires growth rate measurement in steady-state. Hence, we refrained from making such a connection in this manuscript, though it would be an interesting future avenue to explore. Our main goal here was to ask how E. coli growth rate is affected by external nutrient availability and internal translation components. For this, the key comparisons involve the WT vs. gene deletion mutations, and rich vs. poor growth media. For any given comparison, strains were tested under identical conditions and experimental protocols, and hence we can address our main questions without the need to obtain steady-state growth. As an aside, we note that the nutrient fluctuations inherent in such experiments may also be more relevant than steady-state growth for natural bacterial populations.

   As noted by the reviewer, we measured fitness only in a relatively narrow growth regime of several doublings; but we do capture exponential growth by focusing on the early data points (representing the exponential phase) for our growth rate calculations. We have now explicitly mentioned this in the methods section “Measuring growth parameters”.

   A second concern is the use of the term "tRNA expression levels" in the text in Figure 4. I believe the YAMAT-seq method reports on the fractional contribution of a given tRNA to the total tRNA pool. Thus, since the total tRNA pool is larger in fast-growing cells than in slow-growing cells, a given tRNA may be present at a higher absolute concentration in the fast than in the slow-growing cells but will be reported as "higher in poor" in figure 4, if the given tRNA constitutes a smaller fraction of the total tRNA pool in rich than in poor medium. For this reason, the conclusions regarding the effect of growth medium quality on tRNA levels are not justified.

   Thank you for this important point. We agree that our phrasing was incorrect, and we have modified the relevant text and figures accordingly. The fractional contribution of a given tRNA isotype to the total tRNA pool is still useful to compare, and is justified as now rephrased.

   Reviewer #2 (Public Review):

   Raval et al. by creating a series of deletion mutants of tRNAs, rRNAs, and tRNA modifying enzymes, have shown the importance of gene copy number redundancy in rich media. Moreover, they successfully showed that having too many tRNAs in poor media can be harmful (for a subset of the examined tRNAs). Below, please find my comments regarding some of the methodologies, conclusions, and controls needed to stratify this manuscript's findings.

   Figure 2 presents Rrel as a relative measurement (GRmut/GRwt). Therefore, I'm confused as to how Rrel can be negative, as shown in supplemental file 3 (statistics).

   We apologize for the confusion. Supplemental file 3 shows details of the statistical analysis (not raw data), and we included the effect size here (mean difference between the WT and the mutant relative growth rate) along with statistical significance. Thus, if the rel R of a given mutant is 1.1, the mean difference would be (1–1.1) = –0.1, meaning that it is performing 10% better than the WT.

   The “raw” relative growth rates are provided in source data files (labeled figure-wise), and there are no negative values there, as expected.

   We have now explicitly (and separately) referenced the source and statistics data files in the data analysis section in the methods, and in each figure legend. We hope this avoids confusion and makes it easier for readers to find the correct file.

   Does Figure 3 show the mean of 4 biological replicates or technical replicates? It should be stated clearly in the legend of figure 3.

   All replicates are biological replicates until unless stated otherwise. This is now stated in the methods (lines 185-187), and in the figure legends.

   Do all strains (datapoint on figure 3 left panel) significantly perform better than the WT in nutrient downshift? Looking at supplemental file 3 I see this is not the case. Please mark the statistically significant points. I suggest giving each set a different symbol/shape and coloring the significant ones in red.

   We had considered indicating statistical significance in the plot, but decided not to do so because it was difficult to show the many potentially useful layers of information without cluttering the plot. One other practical difficulty was that each point in the figure represents two values: one from the upshift (Y axis) and one from the downshift (X axis). For some mutants the fitness difference was significant in only one direction, so it was not straightforward to indicate significance. Further, our main goal here was to show where strains from different deletion Sets (Figure 1) fall in this plot (i.e. which quadrant they occupy), and so we wanted to ensure that points were easily distinguished by Set. In the text we do not include statistically non-significant points in the summary of observed patterns, and refer readers to information on statistical significance provided in the supplemental file.

   Another issue is that in the statistics of figure 2 (in supplemental file 3), positive values reflect cases where the mutant performs poorly compared to the WT, while in figure 3 the negative values indicate this. Such discrepancy is not very clear. And again, how can Rrel be negative?

   As noted in response to an earlier comment, Rrel values (given in source data files) are not negative, but effect sizes (given in supplemental file with statistics) may be negative or positive since they show differences in the relative growth rate of WT and mutant. We agree that the discrepancy between the calculation of mean difference for Figs 2 and 3 was confusing. We have now fixed this: in both cases, negative mean difference values now indicate that the mutant performs better.

   Both axes say glycerol. What about galactose?

   The typo has been corrected.

   Lines 414-419: The authors state that "all but one had a growth rate that was comparable to WT (16 strains) or higher than WT (10 strains) after transitioning from rich to poor media (i.e. during a nutrient downshift, note data distribution along the x-axis in Fig 3; Supplementary file 3). In contrast, after a nutrient upshift, 11 strains showed significantly slower growth in one or both pairs of media, and only 2 showed significantly faster growth than WT (note data distribution along the y-axis in Fig 3; Supplementary file 3)".

   Looking at the Rrel values when transitioning from TB to Glycerol and vice versa suggests no direction in the effect of reducing redundancy. During downshift, four strains perform better, and three strains perform worse than the WT. During upshift, four stains perform better, and six strains perform worse. Only during downshift and upshift from TB to Gal and vice versa give a strong signal.

   The authors should write it clearly in the text because the effect is specific to that transition/conditions and not of general meaning is written in the text (e.g., transition from every rich to every poor media and vice versa). I am convinced that the authors see an actual effect when downshifting or upshifting from TB to galactose and vice versa. In that case, the conclusion is that redundancy is good or bad depending on the conditions one used and not as a general theme.

   Also, this is true just for some tRNAs, so I don't think the conclusion is general regarding the question of redundancy.

   The fitness impacts of altered redundancy are best explained by a combination of multiple factors (in addition to nutrient availability): the number of tRNA genes deleted, number of tRNA gene copies remaining as a backup, availability of wobble or ME as backup, and codon usage. Thus, any of these variables alone would provide only partial explanation for the observed fitness effects of all strains.

   In many tRNA deletion strains – especially single gene deletions – redundancy was not significantly lowered by the deletion, as we explain in the results section. These strains were therefore not expected to show major fitness impacts or follow strong nutrient dependent trends, and this is what we observe.

   The same is true for nutrient upshift-downshift experiments, where a vast majority of strains were not expected to show a specific pattern because they do not show significant fitness impacts in general, nor do they show a strong correlation in relative fitness impacts vs. growth rate (Figure 1d). In addition, in these experiments the difference between the two media also matters. For example, comparing the maximum WT growth rate, M9 Gal is poorer than M9 Glycerol. Therefore, shifts between TB-Gal are nutritionally more drastic than TB-Gly shifts, and one would expect a larger fitness impact in the former (for strains with significantly altered redundancy). Hence, despite differences across media pairs, our broader conclusions about the impact of redundancy are generalizable as long as redundancy and nutrients are both substantially altered, e.g. due to deletion of 3 tRNA genes, deletion of tRNA+ME, or deletion of multiple rRNA operons.

   Figures are indicated differently along the text. Sometimes they are written "figure X", sometimes FigX. Referring to the supplemental figures are also not consistent.

   We have now corrected this.

   Line 443-444: "In fact, 10 tRNAs were significantly upregulated in the poor medium relative to the rich medium".

   This result contradicts the author's hypothesis. If redundancy is bad in poor media because the cells have more tRNAs than they need, the tRNAs level will be downregulated, not upregulated. How do the authors explain this?

   This statement referred to the WT strain, and was meant to highlight that (as noted by the reviewer) some tRNAs appear to be upregulated in poor medium, which is counterintuitive. However, as noted by reviewer 1 (see their comment on the interpretation of YAMAT-seq data), we can only infer the relative contribution of each tRNA isotype to the total tRNA pool (rather than absolute up- or down- regulation). Thus, we have removed this specific sentence, and instead we focus on the mismatch between the media-dependent changes in the composition of the tRNA pool and the fitness effects of different tRNA isotypes (lines 475-482).

   Line 445-447: "In contrast (and as expected), all tested tRNA deletion strains had lower expression of focal tRNA isotypes in the rich medium (Fig 4B, left panel), showing that the backup gene copies are not upregulated sufficiently to compensate for the loss of deleted tRNAs". It is great that the authors validated the expression in their strains. However, for accuracy, please indicate that it was done in four strains to avoid the impression that they did it in all the strains.

   We have now reworded this sentence to remind readers that we measured 4 tRNA deletion strains in this experiment.

   Finally, across the manuscript, the authors reveal that deleting some tRNAs or modifying enzymes can be deleterious in rich media or advantageous in poor media. However, I think this result and the conclusions derived from it could be more convincing if the authors would show in a subset of their strains that expressing the deleted tRNAs or modifying enzymes from a plasmid can rescue the phenotype.

   Thank you for this suggestion. For a small subset of strains, we now include data showing that complementation from a plasmid indeed rescues the deletion phenotype (Fig 2 – Fig supplement 7).

   Reviewer #3 (Public Review):

   In this manuscript, Raval et al. investigated the cost and benefit of maintaining seemingly redundant components of the translation machinery in the E. coli genome. They used systematic deletion of different components of the translation machinery including tRNA genes, tRNA modification enzymes, and ribosomal RNA genes to create a collection of mutant strains with reduced redundancy. Then they measured the effect of the reduced redundancy on cellular fitness by measuring the growth rate of each mutant strain in different growth conditions.

   This manuscript beautifully shows how maintaining multiple copies of translation machinery genes such as tRNA or ribosomal RNA is beneficial in a nutrient-rich environment, while it is costly in nutrient-poor environments. Similarly, they show how maintaining parallel pathways such as non-target tRNA which directly decodes a codon versus target tRNA plus tRNA modifying enzymes which enable wobble interactions between a tRNA and a codon have a similar effect in terms of cost and benefit.

   Further, the authors show the mechanisms that contribute to the increased or reduced fitness following a reduction in gene copy number by measuring tRNA abundance and translation capacity. This enables them to show how on one hand reduced copy numbers of tRNA genes result in lower tRNA abundance in rich growth media, however in nutrient-limiting media higher copy number leads to increased expression cost which does not lead to an increased translation rate.

   Overall, this work beautifully demonstrates the cost and benefits of the seemingly redundant translation machinery components in E. coli.

   Thank you for the clear summary and encouraging comments.

   However, in my opinion, this work’s conclusion should be that the seeming redundancy of the translation machinery is not redundant after all. As mentioned by the authors, it is known that tRNA gene copy number is associated with tRNA abundance (Dong et al. 1996, doi: 10.1006/jmbi.1996.0428), this effect is also nicely demonstrated by the authors in the section titled “Gene regulation cannot compensate for loss of tRNA gene copies”. Moreover, this work demonstrates how the loss of the seeming redundancy is deleterious in a nutrient-rich environment. Therefore, I believe the experiments presented in this work together with previous works should lead to the conclusion that the multiple gene copies and parallel tRNA decoding pathways are not redundant but rather essential for fast growth in rich environments.

   The point is well taken. However, as described in the introduction, here we focus on functional redundancy at the cellular level, where there are multiple ways of achieving the same translation rate. Hence we say that translation components are redundant at this level of analysis. One of the key conclusions from our work is that such redundancy is context-dependent, i.e. it is essential when rapid growth is possible, but is costly and dispensable otherwise. Therefore, we show that the definition of redundancy itself changes with environmental conditions.

   The following analogy may help convey this. There may be many ways to reach a flight on an airport: multiple entrances, multiple check-in and security check counters, multiple boarding gates, etc. On a deserted airport these may seem redundant and even costly to maintain. On the other hand, they have a utility when traffic is high. Hence even though from a purely architectural perspective the multiple routes are redundant, from a utilitarian perspective it depends on the flux of passengers.

   Read the original source
3. 

   eLife

   Nov 9, 2022

   eLife assessment

   The authors investigate the cost and benefits of maintaining seemingly redundant multiple copies of the translation machinery components. The authors demonstrate that while redundant multiple copies are beneficial in a nutrient-rich environment, maintaining these extra copies is costly and deleterious in a nutrient-poor environment. This explains why copy numbers of translation machinery genes are under selection according to the environmental niche an organism occupies. The work is very important and the findings exciting and supported by compelling evidence. In particular, the fitness gain upon deletion of translation genes in poor conditions is an insightful observation.

   Read the original source
4. 

   eLife

   Nov 9, 2022

   Reviewer #1 (Public Review):

   The layered costs and benefits of translational redundancy by Raval et al. aim to investigate the impact of gene copy number redundancy on E. coli fitness, using growth rate in different media as the primary fitness readout. Genes for most tRNAs and the three ribosomal RNAs are present in multiple copies on the E. coli chromosome. The authors ask how alterations in the gene copy number affect the growth rate of E. coli in growth media that support different rates of growth for the wild type.

   While it was shown before that mutants with reduced numbers of ribosomal RNA operons grow at reduced rates in rich medium (LB), this study extends these findings and reaches some important conclusions:

   1. In a poor medium (supporting slow growth rates), the mutants with fewer rRNA operons actually grow faster than the wild …

   Reviewer #1 (Public Review):

   The layered costs and benefits of translational redundancy by Raval et al. aim to investigate the impact of gene copy number redundancy on E. coli fitness, using growth rate in different media as the primary fitness readout. Genes for most tRNAs and the three ribosomal RNAs are present in multiple copies on the E. coli chromosome. The authors ask how alterations in the gene copy number affect the growth rate of E. coli in growth media that support different rates of growth for the wild type.

   While it was shown before that mutants with reduced numbers of ribosomal RNA operons grow at reduced rates in rich medium (LB), this study extends these findings and reaches some important conclusions:

   1. In a poor medium (supporting slow growth rates), the mutants with fewer rRNA operons actually grow faster than the wild type, showing that redundancy comes at a cost.

   2. The same is true for mutants with reduced gene copy number of certain tRNAs and correlates with slower rates of protein synthesis in these mutants.

   3. That rRNA operon gene copy number is more decisive for growth rate than any tRNA gene copy number (>1).

   In addition, measurements of strains with deletions of genes encoding tRNA-modification enzymes that affect tRNA specificity are included. While interesting, no unifying conclusion could be reached on the impact of these mutations on growth rate.

   The well-known "growth law" relationships between growth rate and macromolecular composition (RNA/protein ratio, for example) specifically concern steady-state growth rates. It is concerning that all growth rates in this work were measured on cultures that were only back-diluted 1:100 from overnight LB precultures. That only allows 6-7 doubling times before the preculture OD is reached again. The exponential part of growth would end before that, allowing perhaps only 3-4 generations of growth in the new medium before the growth rate was measured. Thus, the cultures were not in balanced growth ("steady state") when the measurements were made, rather they were presumably in various states of adapting to altered nutrient availability.

   A second concern is the use of the term "tRNA expression levels" in the text in Figure 4. I believe the YAMAT-seq method reports on the fractional contribution of a given tRNA to the total tRNA pool. Thus, since the total tRNA pool is larger in fast-growing cells than in slow-growing cells, a given tRNA may be present at a higher absolute concentration in the fast than in the slow-growing cells but will be reported as "higher in poor" in figure 4, if the given tRNA constitutes a smaller fraction of the total tRNA pool in rich than in poor medium. For this reason, the conclusions regarding the effect of growth medium quality on tRNA levels are not justified.

   Read the original source
5. 

   eLife

   Nov 9, 2022

   Reviewer #2 (Public Review):

   Rava et al. by creating a series of deletion mutants of tRNAs, rRNAs, and tRNA modifying enzymes, have shown the importance of gene copy number redundancy in rich media. Moreover, they successfully showed that having too many tRNAs in poor media can be harmful (for a subset of the examined tRNAs). Below, please find my comments regarding some of the methodologies, conclusions, and controls needed to stratify this manuscript's findings.

   Figure 2 presents Rrel as a relative measurement (GRmut/GRwt). Therefore, I'm confused as to how Rrel can be negative, as shown in supplemental file 3 (statistics).
   Does Figure 3 show the mean of 4 biological replicates or technical replicates? It should be stated clearly in the legend of figure 3.

   Do all strains (datapoint on figure 3 left panel) significantly perform better …

   Reviewer #2 (Public Review):

   Rava et al. by creating a series of deletion mutants of tRNAs, rRNAs, and tRNA modifying enzymes, have shown the importance of gene copy number redundancy in rich media. Moreover, they successfully showed that having too many tRNAs in poor media can be harmful (for a subset of the examined tRNAs). Below, please find my comments regarding some of the methodologies, conclusions, and controls needed to stratify this manuscript's findings.

   Figure 2 presents Rrel as a relative measurement (GRmut/GRwt). Therefore, I'm confused as to how Rrel can be negative, as shown in supplemental file 3 (statistics).
   Does Figure 3 show the mean of 4 biological replicates or technical replicates? It should be stated clearly in the legend of figure 3.

   Do all strains (datapoint on figure 3 left panel) significantly perform better than the WT in nutrient downshift? Looking at supplemental file 3 I see this is not the case. Please mark the statistically significant points. I suggest giving each set a different symbol/shape and coloring the significant ones in red.

   Another issue is that in the statistics of figure 2 (in supplemental file 3), positive values reflect cases where the mutant performs poorly compared to the WT, while in figure 3 the negative values indicate this. Such discrepancy is not very clear. And again, how can Rrel be negative?

   Both axes say glycerol. What about galactose?

   Lines 414-419: The authors state that "all but one had a growth rate that was comparable to WT (16 strains) or higher than WT (10 strains) after transitioning from rich to poor media (i.e. during a nutrient downshift, note data distribution along the x-axis in Fig 3; Supplementary file 3). In contrast, after a nutrient upshift, 11 strains showed significantly slower growth in one or both pairs of media, and only 2 showed significantly faster growth than WT (note data distribution along the y-axis in Fig 3; Supplementary file 3)".

   Looking at the Rrel values when transitioning from TB to Glycerol and vice versa suggests no direction in the effect of reducing redundancy. During downshift, four strains perform better, and three strains perform worse than the WT. During upshift, four stains perform better, and six strains perform worse. Only during downshift and upshift from TB to Gal and vice versa give a strong signal.

   The authors should write it clearly in the text because the effect is specific to that transition/conditions and not of general meaning is written in the text (e.g., transition from every rich to every poor media and vice versa). I am convinced that the authors see an actual effect when downshifting or upshifting from TB to galactose and vice versa. In that case, the conclusion is that redundancy is good or bad depending on the conditions one used and not as a general theme.

   Also, this is true just for some tRNAs, so I don't think the conclusion is general regarding the question of redundancy.

   Figures are indicated differently along the text. Sometimes they are written "figure X", sometimes FigX. Referring to the supplemental figures are also not consistent.
   Line 443-444: "In fact, 10 tRNAs were significantly upregulated in the poor medium relative to the rich medium".

   This result contradicts the author's hypothesis. If redundancy is bad in poor media because the cells have more tRNAs than they need, the tRNAs level will be downregulated, not upregulated. How do the authors explain this?

   Line 445-447: "In contrast (and as expected), all tested tRNA deletion strains had lower expression of focal tRNA isotypes in the rich medium (Fig 4B, left panel), showing that the backup gene copies are not upregulated sufficiently to compensate for the loss of deleted tRNAs".

   It is great that the authors validated the expression in their strains. However, for accuracy, please indicate that it was done in four strains to avoid the impression that they did it in all the strains.

   Finally, across the manuscript, the authors reveal that deleting some tRNAs or modifying enzymes can be deleterious in rich media or advantageous in poor media. However, I think this result and the conclusions derived from it could be more convincing if the authors would show in a subset of their strains that expressing the deleted tRNAs or modifying enzymes from a plasmid can rescue the phenotype.

   Read the original source
6. 

   eLife

   Nov 9, 2022

   Reviewer #3 (Public Review):

   In this manuscript, Raval et al. investigated the cost and benefit of maintaining seemingly redundant components of the translation machinery in the E. coli genome. They used systematic deletion of different components of the translation machinery including tRNA genes, tRNA modification enzymes, and ribosomal RNA genes to create a collection of mutant strains with reduced redundancy. Then they measured the effect of the reduced redundancy on cellular fitness by measuring the growth rate of each mutant strain in different growth conditions.

   This manuscript beautifully shows how maintaining multiple copies of translation machinery genes such as tRNA or ribosomal RNA is beneficial in a nutrient-rich environment, while it is costly in nutrient-poor environments. Similarly, they show how maintaining parallel …

   Reviewer #3 (Public Review):

   In this manuscript, Raval et al. investigated the cost and benefit of maintaining seemingly redundant components of the translation machinery in the E. coli genome. They used systematic deletion of different components of the translation machinery including tRNA genes, tRNA modification enzymes, and ribosomal RNA genes to create a collection of mutant strains with reduced redundancy. Then they measured the effect of the reduced redundancy on cellular fitness by measuring the growth rate of each mutant strain in different growth conditions.

   This manuscript beautifully shows how maintaining multiple copies of translation machinery genes such as tRNA or ribosomal RNA is beneficial in a nutrient-rich environment, while it is costly in nutrient-poor environments. Similarly, they show how maintaining parallel pathways such as non-target tRNA which directly decodes a codon versus target tRNA plus tRNA modifying enzymes which enable wobble interactions between a tRNA and a codon have a similar effect in terms of cost and benefit.

   Further, the authors show the mechanisms that contribute to the increased or reduced fitness following a reduction in gene copy number by measuring tRNA abundance and translation capacity. This enables them to show how on one hand reduced copy numbers of tRNA genes result in lower tRNA abundance in rich growth media, however in nutrient-limiting media higher copy number leads to increased expression cost which does not lead to an increased translation rate.
   Overall, this work beautifully demonstrates the cost and benefits of the seemingly redundant translation machinery components in E. coli.

   However, in my opinion, this work's conclusion should be that the seeming redundancy of the translation machinery is not redundant after all. As mentioned by the authors, it is known that tRNA gene copy number is associated with tRNA abundance (Dong et al. 1996, doi: 10.1006/jmbi.1996.0428), this effect is also nicely demonstrated by the authors in the section titled "Gene regulation cannot compensate for loss of tRNA gene copies". Moreover, this work demonstrates how the loss of the seeming redundancy is deleterious in a nutrient-rich environment. Therefore, I believe the experiments presented in this work together with previous works should lead to the conclusion that the multiple gene copies and parallel tRNA decoding pathways are not redundant but rather essential for fast growth in rich environments.

   Read the original source
7. 

   Version published to 10.1101/2022.06.16.495782v1 on bioRxiv

   Jun 16, 2022