Differential translation efficiency of orthologous genes is involved in phenotypic divergence of yeast species

SARS-CoV-2 Displays a Suboptimal Codon Usage Bias for Efficient Translation in Human Cells Diverted by Hijacking the tRNA Epitranscriptome

Codon bias analysis of SARS-CoV-2 reveals suboptimal adaptation for translation in human cells it infects. The detailed examination of the codons preferentially used by SARS-CoV-2 shows a strong preference for LysAAA, GlnCAA, GluGAA, and ArgAGA, which are infrequently used in human genes. In the absence of an adapted tRNA pool, efficient decoding of these codons requires a 5-methoxycarbonylmethyl-2-thiouridine (mcm5s2) modification at the U34 wobble position of the corresponding tRNAs (tLysUUU; tGlnUUG; tGluUUC; tArgUCU). The optimal translation of SARS-CoV-2 open reading frames (ORFs) may therefore require several adjustments to the host's translation machinery, enabling the highly biased viral genome to achieve a more favorable "Ready-to-Translate" state in human cells. Experimental approaches based on LC-MS/MS quantification of tRNA modifications and on alteration of enzymatic tRNA modification pathways provide strong evidence to support the hypothesis that SARS-CoV-2 induces U34 tRNA modifications and relies on these modifications for its lifecycle. The conclusions emphasize the need for future studies on the evolution of SARS-CoV-2 codon bias and its ability to alter the host tRNA pool through the manipulation of RNA modifications.

Comparative genomics analysis and transposon mutagenesis provides new insights into high menaquinone-7 biosynthetic potential of Bacillus subtilis natto

This research combined Whole-Genome sequencing, intraspecific comparative genomics and transposon mutagenesis to investigate the menaquinone-7 (MK-7) synthesis potential in Bacillus subtilis natto. First, Whole-Genome sequencing showed that Bacillus subtilis natto BN-P15-11-1 contains one single circular chromosome in size of 3,982,436 bp with a GC content of 43.85 %, harboring 4,053 predicted coding genes. Next, the comparative genomics analysis among strain BN-P15-11-1 with model Bacillus subtilis 168 and four typical Bacillus subtilis natto strains proves that the closer evolutionary relationship Bacillus subtilis natto BN-P15-11-1 and Bacillus subtilis 168 both exhibit strong biosynthetic potential. To further dig for MK-7 biosynthesis latent capacity of BN-P15-11-1, we constructed a mutant library using transposons and a high throughput screening method using microplates. We obtained a YqgQ deficient high MK-7 yield strain F4 with a yield 3.02 times that of the parent strain. Experiments also showed that the high yield mutants had defects in different transcription and translation regulatory factor genes, indicating that regulatory factor defects may affect the biosynthesis and accumulation of MK-7 by altering the overall metabolic level. The findings of this study will provide more novel insights on the precise identification and rational utilization of the Bacillus subtilis subspecies for biosynthesis latent capacity.

Elongation factor 1A1 regulates metabolic substrate preference in mammalian cells

Eukaryotic elongation factor 1A1 (EEF1A1) is canonically involved in protein synthesis but also has noncanonical functions in diverse cellular processes. Previously, we identified EEF1A1 as a mediator of lipotoxicity and demonstrated that chemical inhibition of EEF1A1 activity reduced mouse liver lipid accumulation. These findings suggested a link between EEF1A1 and metabolism. Therefore, we investigated its role in regulating metabolic substrate preference. EEF1A1-deficient Chinese hamster ovary (2E2) cells displayed reduced media lactate accumulation. These effects were also observed with EEF1A1 knockdown in human hepatocyte-like HepG2 cells and in WT Chinese hamster ovary and HepG2 cells treated with selective EEF1A inhibitors, didemnin B, or plitidepsin. Extracellular flux analyses revealed decreased glycolytic ATP production and increased mitochondrial-to-glycolytic ATP production ratio in 2E2 cells, suggesting a more oxidative metabolic phenotype. Correspondingly, fatty acid oxidation was increased in 2E2 cells. Both 2E2 cells and HepG2 cells treated with didemnin B exhibited increased neutral lipid content, which may be required to support elevated oxidative metabolism. RNA-seq revealed a >90-fold downregulation of a rate-limiting glycolytic enzyme, hexokinase 2, which we confirmed through immunoblotting and enzyme activity assays. Pathway enrichment analysis identified downregulations in TNFA signaling via NFKB and MYC targets. Correspondingly, nuclear abundances of RELB and MYC were reduced in 2E2 cells. Thus, EEF1A1 deficiency may perturb glycolysis by limiting NFKB- and MYC-mediated gene expression, leading to decreased hexokinase expression and activity. This is the first evidence of a role for a translation elongation factor, EEF1A1, in regulating metabolic substrate utilization in mammalian cells.

The Role of tRNA-Centered Translational Regulatory Mechanisms in Cancer

Cancer is a leading cause of morbidity and mortality worldwide. While numerous factors have been identified as contributing to the development of malignancy, our understanding of the mechanisms involved remains limited. Early cancer detection and the development of effective treatments are therefore critical areas of research. One class of molecules that play a crucial role in the transmission of genetic information are transfer RNAs (tRNAs), which are the most abundant RNA molecules in the human transcriptome. Dysregulated synthesis of tRNAs directly results in translation disorders and diseases, including cancer. Moreover, various types of tRNA modifications and the enzymes responsible for these modifications have been implicated in tumor biology. Furthermore, alterations in tRNA modification can impact tRNA stability, and impaired stability can prompt the cleavage of tRNAs into smaller fragments known as tRNA fragments (tRFs). Initially believed to be random byproducts lacking any physiological function, tRFs have now been redefined as non-coding RNA molecules with distinct roles in regulating RNA stability, translation, target gene expression, and other biological processes. In this review, we present recent findings on translational regulatory models centered around tRNAs in tumors, providing a deeper understanding of tumorigenesis and suggesting new directions for cancer treatment.

Bioinformatic Analysis Reveals the Role of Translation Elongation Efficiency Optimisation in the Evolution of Ralstonia Genus

Translation efficiency modulates gene expression in prokaryotes. The comparative analysis of translation elongation efficiency characteristics of Ralstonia genus bacteria genomes revealed that these characteristics diverge in accordance with the phylogeny of Ralstonia. The first branch of this genus is a group of bacteria commonly found in moist environments such as soil and water that includes the species R. mannitolilytica, R. insidiosa, and R. pickettii, which are also described as nosocomial infection pathogens. In contrast, the second branch is plant pathogenic bacteria consisting of R. solanacearum, R. pseudosolanacearum, and R. syzygii. We found that the soil Ralstonia have a significantly lower number and energy of potential secondary structures in mRNA and an increased role of codon usage bias in the optimization of highly expressed genes' translation elongation efficiency, not only compared to phytopathogenic Ralstonia but also to Cupriavidus necator, which is closely related to the Ralstonia genus. The observed alterations in translation elongation efficiency of orthologous genes are also reflected in the difference of potentially highly expressed gene' sets' content among Ralstonia branches with different lifestyles. Analysis of translation elongation efficiency characteristics can be considered a promising approach for studying complex mechanisms that determine the evolution and adaptation of bacteria in various environments.

gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm

The tRNA adaptation index (tAI) is a translation efficiency metric that considers weighted values (S _ij values) for codon-tRNA wobble interaction efficiencies. The initial implementation of the tAI had significant flaws. For instance, generated S _ij weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. Consequently, a species-specific approach (stAI) was developed to overcome those limitations. However, the stAI method employed a hill climbing algorithm to optimize the S _ij weights, which is not ideal for obtaining the best set of S _ij weights because it could struggle to find the global maximum given a complex search space, even after using different starting positions. In addition, it did not perform well in computing the tAI of fungal genomes in comparison with the original implementation. We developed a novel approach named genetic tAI (gtAI) implemented as a Python package (https://github.com/AliYoussef96/gtAI), which employs a genetic algorithm to obtain the best set of S _ij weights and follows a new codon usage-based workflow that better computes the tAI of genomes from the three domains of life. The gtAI has significantly improved the correlation with the codon adaptation index (CAI) and the prediction of protein abundance (empirical data) compared to the stAI.

Multiple intermolecular interactions facilitate rapid evolution of essential genes

Essential genes are commonly assumed to function in basic cellular processes and to change slowly. However, it remains unclear whether all essential genes are similarly conserved or if their evolutionary rates can be accelerated by specific factors. To address these questions, we replaced 86 essential genes of Saccharomyces cerevisiae with orthologues from four other species that diverged from S. cerevisiae about 50, 100, 270 and 420 Myr ago. We identify a group of fast-evolving genes that often encode subunits of large protein complexes, including anaphase-promoting complex/cyclosome (APC/C). Incompatibility of fast-evolving genes is rescued by simultaneously replacing interacting components, suggesting it is caused by protein co-evolution. Detailed investigation of APC/C further revealed that co-evolution involves not only primary interacting proteins but also secondary ones, suggesting the evolutionary impact of epistasis. Multiple intermolecular interactions in protein complexes may provide a microenvironment facilitating rapid evolution of their subunits.

A dynamical stochastic model of yeast translation across the cell cycle

Translation is a central step in gene expression, however its quantitative and time-resolved regulation is poorly understood. We developed a discrete, stochastic model for protein translation in S. cerevisiae in a whole-transcriptome, single-cell context. A "base case" scenario representing an average cell highlights translation initiation rates as the main co-translational regulatory parameters. Codon usage bias emerges as a secondary regulatory mechanism through ribosome stalling. Demand for anticodons with low abundancy is shown to cause above-average ribosome dwelling times. Codon usage bias correlates strongly both with protein synthesis rates and elongation rates. Applying the model to a time-resolved transcriptome estimated by combining data from FISH and RNA-Seq experiments, it could be shown that increased total transcript abundance during the cell cycle decreases translation efficiency at single transcript level. Translation efficiency grouped by gene function shows highest values for ribosomal and glycolytic genes. Ribosomal proteins peak in S phase while glycolytic proteins rank highest in later cell cycle phases.

tRNA copy number and codon usage in the sea cucumber genome provide insights into adaptive translation for saponin biosynthesis

Genomic tRNA copy numbers determine cytoplasmic tRNA abundances, which in turn influence translation efficiency, but the underlying mechanism is not well understood. Using the sea cucumber Apostichopus japonicus as a model, we combined genomic sequence, transcriptome expression and ecological food resource data to study its codon usage adaptation. The results showed that, unlike intragenic non-coding RNAs, transfer RNAs (tRNAs) tended to be transcribed independently. This may be attributed to their specific Pol III promoters that lack transcriptional regulation, which may underlie the correlation between genomic copy number and cytoplasmic abundance of tRNAs. Moreover, codon usage optimization was mostly restrained by a gene's amino acid sequence, which might be a compromise between functionality and translation efficiency for stress responses were highly optimized for most echinoderms, while enzymes for saponin biosynthesis (LAS, CYPs and UGTs) were especially optimized in sea cucumbers, which might promote saponin synthesis as a defence strategy. The genomic tRNA content of A. japonicus was positively correlated with amino acid content in its natural food particles, which should promote its efficiency in protein synthesis. We propose that coevolution between genomic tRNA content and codon usage of sea cucumbers facilitates their saponin synthesis and survival using food resources with low nutrient content.

The impact of codon choice on translation process in Saccharomyces cerevisiae: folding class, protein function and secondary structure

The genetic code consists in a set of rules used by living organisms to translate genomic information, contained in genes, into proteins; every amino acid is coded by a set of nucleotide triplets or codons. We refer to codon choice as the choice of a given codon, among the synonymous available ones, to code a given amino acid occurrence. The aim of this work is to shed light on the pivotal role that codon choice plays in regulating the timing of translation process, through patterns of low and high translation efficiency codons. A translation efficiency value, namely codon score, was associated to each codon through a formula based on the number of tRNAs gene copies able to translate the given codon. By using codon scores, those k-mers of the proteome of Saccharomyces cerevisiae, showing low and high average scores associated to the correspondent codons, were computed. The analysis of distribution of both low and high average score k-mers clearly showed that, in particular for higher k-mer size, they occur much more than expected, strongly suggesting a functional role. Moreover performed analysis highlighted that significant k-mers preferentially occur in some protein folding classes, such as those containing alpha helices, and in some functional classes mainly involved in transcription process while codon choice seems to have a very low impact in proteins associated to energy production and metabolism. The relationship between secondary structures and significant k-mers was investigated, revealing that low score k-mers tend to preferentially occur in coil or close to coil regions and almost never in beta sheets, while high score k-mers preferentially occur in alpha helices, avoiding beta sheets, and close to coil regions for high k-mer sizes. Finally the analysis of distribution of significant codon patterns along the proteins highlighted a relevant enrichment of low average score k-mers at the 5' end of protein-coding sequences in the region from 5th to 25th amino acid.

Multifaceted control of mRNA translation machinery in cancer

The mRNA translation machinery is tightly regulated through several, at times overlapping, mechanisms that modulate its efficiency and accuracy. Due to their fast rate of growth and metabolism, cancer cells require an excessive amount of mRNA translation and protein synthesis. However, unfavorable conditions, such as hypoxia, amino acid starvation, and oxidative stress, which are abundant in cancer, as well as many anti-cancer treatments inhibit mRNA translation. Cancer cells adapt to the various internal and environmental stresses by employing specialised transcript-specific translation to survive and gain a proliferative advantage. We will highlight the major signaling pathways and mechanisms of translation that regulate the global or mRNA-specific translation in response to the intra- or extra-cellular signals and stresses that are key components in the process of tumourigenesis.

Codon usage bias and environmental adaptation in microbial organisms

In each genome, synonymous codons are used with different frequencies; this general phenomenon is known as codon usage bias. It has been previously recognised that codon usage bias could affect the cellular fitness and might be associated with the ecology of microbial organisms. In this exploratory study, we investigated the relationship between codon usage bias, lifestyles (thermophiles vs. mesophiles; pathogenic vs. non-pathogenic; halophilic vs. non-halophilic; aerobic vs. anaerobic and facultative) and habitats (aquatic, terrestrial, host-associated, specialised, multiple) of 615 microbial organisms (544 bacteria and 71 archaea). Principal component analysis revealed that species with given phenotypic traits and living in similar environmental conditions have similar codon preferences, as represented by the relative synonymous codon usage (RSCU) index, and similar spectra of tRNA availability, as gauged by the tRNA gene copy number (tGCN). Moreover, by measuring the average tRNA adaptation index (tAI) for each genome, an index that can be associated with translational efficiency, we observed that organisms able to live in multiple habitats, including facultative organisms, mesophiles and pathogenic bacteria, are characterised by a reduced translational efficiency, consistently with their need to adapt to different environments. Our results show that synonymous codon choices might be under strong translational selection, which modulates the choice of the codons to differently match tRNA availability, depending on the organism's lifestyle needs. To our knowledge, this is the first large-scale study that examines the role of codon bias and translational efficiency in the adaptation of microbial organisms to the environment in which they live.

Core Fermentation (CoFe) granules focus coordinated glycolytic mRNA localization and translation to fuel glucose fermentation

Glycolysis is a fundamental metabolic pathway for glucose catabolism across biology, and glycolytic enzymes are among the most abundant proteins in cells. Their expression at such levels provides a particular challenge. Here we demonstrate that the glycolytic mRNAs are localized to granules in yeast and human cells. Detailed live cell and smFISH studies in yeast show that the mRNAs are actively translated in granules, and this translation appears critical for the localization. Furthermore, this arrangement is likely to facilitate the higher level organization and control of the glycolytic pathway. Indeed, the degree of fermentation required by cells is intrinsically connected to the extent of mRNA localization to granules. On this basis, we term these granules, core fermentation (CoFe) granules; they appear to represent translation factories, allowing high-level coordinated enzyme synthesis for a critical metabolic pathway.

Yeast-Based Biosynthesis of Natural Products From Xylose

Xylose is the second most abundant sugar in lignocellulosic hydrolysates. Transformation of xylose into valuable chemicals, such as plant natural products, is a feasible and sustainable route to industrializing biorefinery of biomass materials. Yeast strains, including Saccharomyces cerevisiae, Scheffersomyces stipitis, and Yarrowia lipolytica, display some paramount advantages in expressing heterologous enzymes and pathways from various sources and have been engineered extensively to produce natural products. In this review, we summarize the advances in the development of metabolically engineered yeasts to produce natural products from xylose, including aromatics, terpenoids, and flavonoids. The state-of-the-art metabolic engineering strategies and representative examples are reviewed. Future challenges and perspectives are also discussed on yeast engineering for commercial production of natural products using xylose as feedstocks.

Nucleotide composition affects codon usage toward the 3'-end

The 3’-end of the coding sequence in several species is known to show specific codon usage bias. Several factors have been suggested to underlie this phenomenon, including selection against translation efficiency, selection for translation accuracy, and selection against RNA folding. All are supported by some evidence, but there is no general agreement as to which factors are the main determinants. Nor is it known how universal this phenomenon is, and whether the same factors explain it in different species. To answer these questions, we developed a measure that quantifies the codon usage bias at the gene end, and used it to compute this bias for 91 species that span the three domains of life. In addition, we characterized the codons in each species by features that allow discrimination between the different factors. Combining all these data, we were able to show that there is a universal trend to favor AT-rich codons toward the gene end. Moreover, we suggest that this trend is explained by avoidance from forming RNA secondary structures around the stop codon, which may interfere with normal translation termination.

The stop-and-go traffic regulating protein biogenesis: How translation kinetics controls proteostasis

Generating a functional proteome requires the ribosome to carefully regulate disparate co-translational processes that determine the fate of nascent polypeptides. With protein synthesis being energetically expensive, the ribosome must balance the costs of efficiently making a protein with those of properly folding it. Emerging as a primary means of regulating this trade-off is the nonuniform rate of translation elongation that defines translation kinetics. The varying speeds with which the ribosome progresses along a transcript have been implicated in several aspects of protein biogenesis, including co-translational protein folding and translational fidelity, as well as gene expression by mediating mRNA decay and protein quality control pathways. The optimal translation kinetics required to efficiently execute these processes can be distinct. Thus, the ribosome is tasked with tightly regulating translation kinetics to balance these processes while maintaining adaptability for changing cellular conditions. In this review, we first discuss the regulatory role of translation elongation in protein biogenesis and what factors influence elongation kinetics. We then describe how changes in translation kinetics signal downstream pathways that dictate the fate of nascent polypeptides. By regulating these pathways, the kinetics of translation elongation has emerged as a critical tool for driving gene expression and maintaining proteostasis through varied mechanisms, including nascent chain folding and binding different ribosome-associated machinery. Indeed, a growing number of examples demonstrate the important role of local changes in elongation kinetics in modulating the pathophysiology of human disease.

Repertoires of tRNAs: The Couplers of Genomics and Proteomics

The pool of transfer RNA (tRNA) molecules in cells allows the ribosome to decode genetic information. This repertoire of molecular decoders is positioned in the crossroad of the genome, the transcriptome, and the proteome. Omics and systems biology now allow scientists to explore the entire repertoire of tRNAs of many organisms, revealing basic exciting biology. The tRNA gene set of hundreds of species is now characterized, in addition to the tRNA genes of organelles and viruses. Genes encoding tRNAs for certain anticodon types appear in dozens of copies in a genome, while others are universally absent from any genome. Transcriptome measurement of tRNAs is challenging, but in recent years new technologies have allowed researchers to determine the dynamic expression patterns of tRNAs. These advances reveal that availability of ready-to-translate tRNA molecules is highly controlled by several transcriptional and posttranscriptional regulatory processes. This regulation shapes the proteome according to the cellular state. The tRNA pool profoundly impacts many aspects of cellular and organismal life, including protein expression level, translation accuracy, adequacy of folding, and even mRNA stability. As a result, the shape of the tRNA pool affects organismal health and may participate in causing conditions such as cancer and neurological conditions.

Metabolic engineering in the host Yarrowia lipolytica

The nonconventional, oleaginous yeast, Yarrowia lipolytica is rapidly emerging as a valuable host for the production of a variety of both lipid and nonlipid chemical products. While the unique genetics of this organism pose some challenges, many new metabolic engineering tools have emerged to facilitate improved genetic manipulation in this host. This review establishes a case for Y. lipolytica as a premier metabolic engineering host based on innate metabolic capacity, emerging synthetic tools, and engineering examples. The metabolism underlying the lipid accumulation phenotype of this yeast as well as high flux through acyl-CoA precursors and the TCA cycle provide a favorable metabolic environment for expression of relevant heterologous pathways. These properties allow Y. lipolytica to be successfully engineered for the production of both native and nonnative lipid, organic acid, sugar and acetyl-CoA derived products. Finally, this host has unique metabolic pathways enabling growth on a wide range of carbon sources, including waste products. The expansion of carbon sources, together with the improvement of tools as highlighted here, have allowed this nonconventional organism to act as a cellular factory for valuable chemicals and fuels.

The evolutionary signal in metagenome phyletic profiles predicts many gene functions

BACKGROUND

The function of many genes is still not known even in model organisms. An increasing availability of microbiome DNA sequencing data provides an opportunity to infer gene function in a systematic manner.

RESULTS

We evaluated if the evolutionary signal contained in metagenome phyletic profiles (MPP) is predictive of a broad array of gene functions. The MPPs are an encoding of environmental DNA sequencing data that consists of relative abundances of gene families across metagenomes. We find that such MPPs can accurately predict 826 Gene Ontology functional categories, while drawing on human gut microbiomes, ocean metagenomes, and DNA sequences from various other engineered and natural environments. Overall, in this task, the MPPs are highly accurate, and moreover they provide coverage for a set of Gene Ontology terms largely complementary to standard phylogenetic profiles, derived from fully sequenced genomes. We also find that metagenomes approximated from taxon relative abundance obtained via 16S rRNA gene sequencing may provide surprisingly useful predictive models. Crucially, the MPPs derived from different types of environments can infer distinct, non-overlapping sets of gene functions and therefore complement each other. Consistently, simulations on > 5000 metagenomes indicate that the amount of data is not in itself critical for maximizing predictive accuracy, while the diversity of sampled environments appears to be the critical factor for obtaining robust models.

CONCLUSIONS

In past work, metagenomics has provided invaluable insight into ecology of various habitats, into diversity of microbial life and also into human health and disease mechanisms. We propose that environmental DNA sequencing additionally constitutes a useful tool to predict biological roles of genes, yielding inferences out of reach for existing comparative genomics approaches.

Codon usage of highly expressed genes affects proteome-wide translation efficiency

Although the genetic code is redundant, synonymous codons for the same amino acid are not used with equal frequencies in genomes, a phenomenon termed "codon usage bias." Previous studies have demonstrated that synonymous changes in a coding sequence can exert significant cis effects on the gene's expression level. However, whether the codon composition of a gene can also affect the translation efficiency of other genes has not been thoroughly explored. To study how codon usage bias influences the cellular economy of translation, we massively converted abundant codons to their rare synonymous counterpart in several highly expressed genes in Escherichia coli This perturbation reduces both the cellular fitness and the translation efficiency of genes that have high initiation rates and are naturally enriched with the manipulated codon, in agreement with theoretical predictions. Interestingly, we could alleviate the observed phenotypes by increasing the supply of the tRNA for the highly demanded codon, thus demonstrating that the codon usage of highly expressed genes was selected in evolution to maintain the efficiency of global protein translation.

Codon harmonization - going beyond the speed limit for protein expression

Codon usage distribution has been soundly used by nature to fine tune protein biogenesis. Alteration of the mRNA structure or sequential scheduling of codons can profoundly affect translation, thus altering protein yield, functionality, solubility, and proper folding. Building on these observations, here, we present an evaluation of different recently designed algorithms of sequence adaptation based on Codon Adaptation Index (CAI) profiling. The first algorithm globally harmonizes synonymous codons in the original sequence in full respect to the heterologous expression host codon usage. The second recodes the sequence in accordance with the native sequence CAI profile. Our data, generated on three model proteins, highlights the importance to consider gene recoding as a parameter itself for recombinant protein expression improvement.

Molecular changes in vitellogenin gene of Spodoptera exigua after long-time exposure to cadmium - Toxic side effect or microevolution?

The reproduction of pest insects is a continuously ongoing issue, especially in the environmental pollution context. Natural or artificial stressing factors enforce a kind of trade-off, most often between growth/survival and reproduction, which improves fitness of the organism. Harmful factors, such as cadmium, can affect the vitellogenesis leading to reduction of yolk synthesis and egg production. The aim of this study was to assess whether 130-generational selection to cadmium in food might have induced change in vitellogenesis of Spodoptera exigua. We analyzed the level of Vg gene expression in S. exigua from the control and the cadmium strain at regular time intervals within 48h after eclosion. The full sequence of Vg gene was also compared between strains. The vitellogenin gene expression in both strains was time-dependent. This dependence was more visible in the control strain. In the cadmium strain the vitellogenin expression was significantly lower, comparing with the control strain in the first day after eclosion but increased significantly in the second day. The sequenced CDS (5286bp long) of the control and the cadmium strains were translated into protein sequences containing both 1761 aa. The protein sequences comparison revealed that there is one amino acid change at aa position 1282. Multiple alignments of six orthologous proteins from different species showed that amino acid change is located in the conserved position. Long-lasting exposure to cadmium resulted in permanent mutation in vitellogenin gene. We do not know yet if the mutation can improve fitness of the cadmium-selected insects. However, we can suppose that the mutation is neutral or even beneficial. The mutation and most probably additional effects of cadmium exposure have an influence on the vitellogenin expression. Some modification in the expression of the vitellogenin receptor are also likely to be important.

stAIcalc: tRNA adaptation index calculator based on species-specific weights

Summary

The tRNA Adaptation Index (tAI) is a tRNA-centric measure of translation efficiency which includes weights that take into account the efficiencies of the different wobble interactions. To enable the calculation of the index based on a species-specific inference of these weights, we created the stAI calc . The calculator includes optimized tAI weights for 100 species from the three domains of life along with a standalone software package that optimizes the weights for new organisms. The tAI with the optimized weights should enable performing large scale studies in disciplines such as molecular evolution, genomics, systems biology and synthetic biology.

Availability and Implementation

The calculator is publicly available at http://www.cs.tau.ac.il/∼tamirtul/stAIcalc/stAIcalc.html.

Contact

tamirtul@post.tau.ac.il.

Novel mRNA-specific effects of ribosome drop-off on translation rate and polysome profile

The well established phenomenon of ribosome drop-off plays crucial roles in translational accuracy and nutrient starvation responses during protein translation. When cells are under stress conditions, such as amino acid starvation or aminoacyl-tRNA depletion due to a high level of recombinant protein expression, ribosome drop-off can substantially affect the efficiency of protein expression. Here we introduce a mathematical model that describes the effects of ribosome drop-off on the ribosome density along the mRNA and on the concomitant protein synthesis rate. Our results show that ribosome premature termination may lead to non-intuitive ribosome density profiles, such as a ribosome density which increases from the 5' to the 3' end. Importantly, the model predicts that the effects of ribosome drop-off on the translation rate are mRNA-specific, and we quantify their resilience to drop-off, showing that the mRNAs which present ribosome queues are much less affected by ribosome drop-off than those which do not. Moreover, among those mRNAs that do not present ribosome queues, resilience to drop-off correlates positively with the elongation rate, so that sequences using fast codons are expected to be less affected by ribosome drop-off. This result is consistent with a genome-wide analysis of S. cerevisiae, which reveals that under favourable growth conditions mRNAs coding for proteins involved in the translation machinery, known to be highly codon biased and using preferentially fast codons, are highly resilient to ribosome drop-off. Moreover, in physiological conditions, the translation rate of mRNAs coding for regulatory, stress-related proteins, is less resilient to ribosome drop-off. This model therefore allows analysis of variations in the translational efficiency of individual mRNAs by accounting for the full range of known ribosome behaviours, as well as explaining mRNA-specific variations in ribosome density emerging from ribosome profiling studies.

Synonymous Codons: Choose Wisely for Expression

The genetic code, which defines the amino acid sequence of a protein, also contains information that influences the rate and efficiency of translation. Neither the mechanisms nor functions of codon-mediated regulation were well understood. The prevailing model was that the slow translation of codons decoded by rare tRNAs reduces efficiency. Recent genome-wide analyses have clarified several issues. Specific codons and codon combinations modulate ribosome speed and facilitate protein folding. However, tRNA availability is not the sole determinant of rate; rather, interactions between adjacent codons and wobble base pairing are key. One mechanism linking translation efficiency and codon use is that slower decoding is coupled to reduced mRNA stability. Changes in tRNA supply mediate biological regulationfor instance,, changes in tRNA amounts facilitate cancer metastasis.

The landscape of microbial phenotypic traits and associated genes

Bacteria and Archaea display a variety of phenotypic traits and can adapt to diverse ecological niches. However, systematic annotation of prokaryotic phenotypes is lacking. We have therefore developed ProTraits, a resource containing ∼545 000 novel phenotype inferences, spanning 424 traits assigned to 3046 bacterial and archaeal species. These annotations were assigned by a computational pipeline that associates microbes with phenotypes by text-mining the scientific literature and the broader World Wide Web, while also being able to define novel concepts from unstructured text. Moreover, the ProTraits pipeline assigns phenotypes by drawing extensively on comparative genomics, capturing patterns in gene repertoires, codon usage biases, proteome composition and co-occurrence in metagenomes. Notably, we find that gene synteny is highly predictive of many phenotypes, and highlight examples of gene neighborhoods associated with spore-forming ability. A global analysis of trait interrelatedness outlined clusters in the microbial phenotype network, suggesting common genetic underpinnings. Our extended set of phenotype annotations allows detection of 57 088 high confidence gene-trait links, which recover many known associations involving sporulation, flagella, catalase activity, aerobicity, photosynthesis and other traits. Over 99% of the commonly occurring gene families are involved in genetic interactions conditional on at least one phenotype, suggesting that epistasis has a major role in shaping microbial gene content.

The DEAD-Box Protein Dhh1p Couples mRNA Decay and Translation by Monitoring Codon Optimality

A major determinant of mRNA half-life is the codon-dependent rate of translational elongation. How the processes of translational elongation and mRNA decay communicate is unclear. Here, we establish that the DEAD-box protein Dhh1p is a sensor of codon optimality that targets an mRNA for decay. First, we find mRNAs whose translation elongation rate is slowed by inclusion of non-optimal codons are specifically degraded in a Dhh1p-dependent manner. Biochemical experiments show Dhh1p is preferentially associated with mRNAs with suboptimal codon choice. We find these effects on mRNA decay are sensitive to the number of slow-moving ribosomes on an mRNA. Moreover, we find Dhh1p overexpression leads to the accumulation of ribosomes specifically on mRNAs (and even codons) of low codon optimality. Lastly, Dhh1p physically interacts with ribosomes in vivo. Together, these data argue that Dhh1p is a sensor for ribosome speed, targeting an mRNA for repression and subsequent decay.

Quantitation of Protein Translation Rate In Vivo with Bioorthogonal Click-Chemistry

The development of novel bioorthogonal reactives that can be used to tag biomolecules in vivo has revolutionized the studies of cellular and molecular biology. Among those novel reactive substances, amino acid analogs can be used to label nascent proteins, thus opening new avenues for measuring protein translation rates in vivo with a limited manipulation of the sample. Here, we describe the use of Click-chemistry to tag and separate newly synthesized proteins in mammalian cells that can be used, coupled with western analysis, to estimate the translation rate of any protein of interest.

Extensive complementarity between gene function prediction methods

MOTIVATION

The number of sequenced genomes rises steadily but we still lack the knowledge about the biological roles of many genes. Automated function prediction (AFP) is thus a necessity. We hypothesized that AFP approaches that draw on distinct genome features may be useful for predicting different types of gene functions, motivating a systematic analysis of the benefits gained by obtaining and integrating such predictions.

RESULTS

Our pipeline amalgamates 5 133 543 genes from 2071 genomes in a single massive analysis that evaluates five established genomic AFP methodologies. While 1227 Gene Ontology (GO) terms yielded reliable predictions, the majority of these functions were accessible to only one or two of the methods. Moreover, different methods tend to assign a GO term to non-overlapping sets of genes. Thus, inferences made by diverse genomic AFP methods display a striking complementary, both gene-wise and function-wise. Because of this, a viable integration strategy is to rely on a single most-confident prediction per gene/function, rather than enforcing agreement across multiple AFP methods. Using an information-theoretic approach, we estimate that current databases contain 29.2 bits/gene of known Escherichia coli gene functions. This can be increased by up to 5.5 bits/gene using individual AFP methods or by 11 additional bits/gene upon integration, thereby providing a highly-ranking predictor on the Critical Assessment of Function Annotation 2 community benchmark. Availability of more sequenced genomes boosts the predictive accuracy of AFP approaches and also the benefit from integrating them.

AVAILABILITY AND IMPLEMENTATION

The individual and integrated GO predictions for the complete set of genes are available from http://gorbi.irb.hr/ CONTACT: fran.supek@irb.hrSupplementary information: Supplementary materials are available at Bioinformatics online.

Selection for reduced translation costs at the intronic 5' end in fungi

It is generally believed that introns are not translated; therefore, the potential intronic features that may be related to the translation step (occurring after splicing) have yet to be thoroughly studied. Here, focusing on four fungi, we performed for the first time a comprehensive study aimed at characterizing how translation efficiency is encoded in introns and affects their evolution. By analysing their intronome we provide evidence of selection for STOP codons close to the intronic 5′ end, and show that the beginning of introns are selected for significantly high translation, presumably to reduce translation and metabolic costs in cases of non-spliced introns. Ribosomal profiling data analysis in Saccharomyces cerevisiae supports the conjecture that in this organism intron retention frequently occurs, introns are partially translated, and their translation efficiency affects organismal fitness. We show that the reported results are more significant in highly translated and highly spliced genes, but are not associated only with genes with a specific function. We also discuss the potential relation of the reported signals to efficient nonsense-mediated decay due to splicing errors. These new discoveries are supported by population-genetics considerations. In addition, they are contributory steps towards a broader understanding of intron evolution and the effect of silent mutations on gene expression and organismal fitness.

Codon-Driven Translational Efficiency Is Stable across Diverse Mammalian Cell States

Whether codon usage fine-tunes mRNA translation in mammals remains controversial, with recent papers suggesting that production of proteins in specific Gene Ontological (GO) pathways can be regulated by actively modifying the codon and anticodon pools in different cellular conditions. In this work, we compared the sequence content of genes in specific GO categories with the exonic genome background. Although a substantial fraction of variability in codon usage could be explained by random sampling, almost half of GO sets showed more variability in codon usage than expected by chance. Nevertheless, by quantifying translational efficiency in healthy and cancerous tissues in human and mouse, we demonstrated that a given tRNA pool can equally well translate many different sets of mRNAs, irrespective of their cell-type specificity. This disconnect between variations in codon usage and the stability of translational efficiency is best explained by differences in GC content between gene sets. GC variation across the mammalian genome is most likely a result of the interplay between genome repair and gene duplication mechanisms, rather than selective pressures caused by codon-driven translational rates. Consequently, codon usage differences in mammalian transcriptomes are most easily explained by well-understood mutational biases acting on the underlying genome.

Biological causal links on physiological and evolutionary time scales

Correlation does not imply causation. If two variables, say A and B, are correlated, it could be because A causes B, or that B causes A, or because a third factor affects them both. We suggest that in many cases in biology, the causal link might be bi-directional: A causes B through a fast-acting physiological process, while B causes A through a slowly accumulating evolutionary process. Furthermore, many trained biologists tend to consistently focus at first on the fast-acting direction, and overlook the slower process in the opposite direction. We analyse several examples from modern biology that demonstrate this bias (codon usage optimality and gene expression, gene duplication and genetic dispensability, stem cell division and cancer risk, and the microbiome and host metabolism) and also discuss an example from linguistics. These examples demonstrate mutual effects between the fast physiological processes and the slow evolutionary ones. We believe that building awareness of inference biases among biologists who tend to prefer one causal direction over another could improve scientific reasoning.

Translation attenuation via 3' terminal codon usage in bovine csn1s2 is responsible for the difference in αs2- and β-casein profile in milk

The rate of secretion of αs2-casein into bovine milk is approximately 25% of that of β-casein, yet mammary expression of their respective mRNA transcripts (csn1s2 and csn2) is not different. Our objective was to identify molecular mechanisms that explain the difference in translation efficiency between csn1s2 and csn2. Cell-free translational efficiency of csn2 was 5 times that of csn1s2. Transcripts of csn1s2 distributed into heavier polysomes than csn2 transcripts, indicating an attenuation of elongation and/or termination. Stimulatory and inhibitory effects of the 5' and 3' UTRs on translational efficiency were different with luciferase and casein sequences in the coding regions. Substituting the 5' and 3' UTRs from csn2 into csn1s2 did not improve csn1s2 translation, implicating the coding region itself in the translation difference. Deletion of a 28-codon fragment from the 3' terminus of the csn1s2 coding region, which displays codons with low correlations to cell fitness, increased translation to a par with csn2. We conclude that the usage of the last 28 codons of csn1s2 is the main regulatory element that attenuates its expression and is responsible for the differential translational expression of csn1s2 and csn2.

Modeling Gene Networks in Saccharomyces cerevisiae Based on Gene Expression Profiles

Detailed and innovative analysis of gene regulatory network structures may reveal novel insights to biological mechanisms. Here we study how gene regulatory network in Saccharomyces cerevisiae can differ under aerobic and anaerobic conditions. To achieve this, we discretized the gene expression profiles and calculated the self-entropy of down- and upregulation of gene expression as well as joint entropy. Based on these quantities the uncertainty coefficient was calculated for each gene triplet, following which, separate gene logic networks were constructed for the aerobic and anaerobic conditions. Four structural parameters such as average degree, average clustering coefficient, average shortest path, and average betweenness were used to compare the structure of the corresponding aerobic and anaerobic logic networks. Five genes were identified to be putative key components of the two energy metabolisms. Furthermore, community analysis using the Newman fast algorithm revealed two significant communities for the aerobic but only one for the anaerobic network. David Gene Functional Classification suggests that, under aerobic conditions, one such community reflects the cell cycle and cell replication, while the other one is linked to the mitochondrial respiratory chain function.

The Code of Silence: Widespread Associations Between Synonymous Codon Biases and Gene Function

Some mutations in gene coding regions exchange one synonymous codon for another, and thus do not alter the amino acid sequence of the encoded protein. Even though they are often called 'silent,' these mutations may exhibit a plethora of effects on the living cell. Therefore, they are often selected during evolution, causing synonymous codon usage biases in genomes. Comparative analyses of bacterial, archaeal, fungal, and human cancer genomes have found many links between a gene's biological role and the accrual of synonymous mutations during evolution. In particular, highly expressed genes in certain functional categories are enriched with optimal codons, which are decoded by the abundant tRNAs, thus enhancing the speed and accuracy of the translating ribosome. The set of genes exhibiting codon adaptation differs between genomes, and these differences show robust associations to organismal phenotypes. In addition to selection for translation efficiency, other distinct codon bias patterns have been found in: amino acid starvation genes, cyclically expressed genes, tissue-specific genes in animals and plants, oxidative stress response genes, cellular differentiation genes, and oncogenes. In addition, genomes of organisms harboring tRNA modifications exhibit particular codon preferences. The evolutionary trace of codon bias patterns across orthologous genes may be examined to learn about a gene's relevance to various phenotypes, or, more generally, its function in the cell.

A relay race on the evolutionary adaptation spectrum

Adaptation is the process in which organisms improve their fitness by changing their phenotype using genetic or non-genetic mechanisms. The adaptation toolbox consists of varied molecular and genetic means that we posit span an almost continuous "adaptation spectrum." Different adaptations are characterized by the time needed for organisms to attain them and by their duration. We suggest that organisms often adapt by progressing the adaptation spectrum, starting with rapidly attained physiological and epigenetic adaptations and culminating with slower long-lasting genetic ones. A tantalizing possibility is that earlier adaptations facilitate realization of later ones.

Evolutionary Pressures on the Yeast Transcriptome

Codon usage bias (CUB) is the well known phenomenon that the frequency of synonymous codons is unequal. This is presumably the result of adaptive pressures favouring some codons over others. The underlying reason for this pressure is unknown, although a large number of possible driver mechanisms have been proposed; one of them is the decoding time. The standard model to calculate decoding time is the Gromadski-Rodnina model. Yet, recently, there have been a number of studies arguing to the effect that this conventional speed-model is not relevant to understand the dynamics of translation. However, results remain inconclusive so far. This contribution takes a novel approach to address this issue based on comparing mRNA with random synonymous variants to estimate the evolutionary pressures that have acted on the transcriptome. It emerges that over 70 percent of ORFs have been subject to a strong selection pressure for translation speed and that there is also a strong selection pressure for the avoidance of traffic jams. Finally, it is also shown that both homogeneous and very heterogeneous transcripts are over-represented. These results corroborate the validity of the Gromadski-Rodnina model.

Rationally designed, heterologous S. cerevisiae transcripts expose novel expression determinants

Deducing generic causal relations between RNA transcript features and protein expression profiles from endogenous gene expression data remains a major unsolved problem in biology. The analysis of gene expression from heterologous genes contributes significantly to solving this problem, but has been heavily biased toward the study of the effect of 5' transcript regions and to prokaryotes. Here, we employ a synthetic biology driven approach that systematically differentiates the effect of different regions of the transcript on gene expression up to 240 nucleotides into the ORF. This enabled us to discover new causal effects between features in previously unexplored regions of transcripts, and gene expression in natural regimes. We rationally designed, constructed, and analyzed 383 gene variants of the viral HRSVgp04 gene ORF, with multiple synonymous mutations at key positions along the transcript in the eukaryote S. cerevisiae. Our results show that a few silent mutations at the 5'UTR can have a dramatic effect of up to 15 fold change on protein levels, and that even synonymous mutations in positions more than 120 nucleotides downstream from the ORF 5'end can modulate protein levels up to 160%-300%. We demonstrate that the correlation between protein levels and folding energy increases with the significance of the level of selection of the latter in endogenous genes, reinforcing the notion that selection for folding strength in different parts of the ORF is related to translation regulation. Our measured protein abundance correlates notably(correlation up to r = 0.62 (p=0.0013)) with mean relative codon decoding times, based on ribosomal densities (Ribo-Seq) in endogenous genes, supporting the conjecture that translation elongation and adaptation to the tRNA pool can modify protein levels in a causal/direct manner. This report provides an improved understanding of transcript evolution, design principles of gene expression regulation, and suggests simple rules for engineering synthetic gene expression in eukaryotes.

Causal signals between codon bias, mRNA structure, and the efficiency of translation and elongation

Ribosome profiling data report on the distribution of translating ribosomes, at steady-state, with codon-level resolution. We present a robust method to extract codon translation rates and protein synthesis rates from these data, and identify causal features associated with elongation and translation efficiency in physiological conditions in yeast. We show that neither elongation rate nor translational efficiency is improved by experimental manipulation of the abundance or body sequence of the rare AGG tRNA. Deletion of three of the four copies of the heavily used ACA tRNA shows a modest efficiency decrease that could be explained by other rate-reducing signals at gene start. This suggests that correlation between codon bias and efficiency arises as selection for codons to utilize translation machinery efficiently in highly translated genes. We also show a correlation between efficiency and RNA structure calculated both computationally and from recent structure probing data, as well as the Kozak initiation motif, which may comprise a mechanism to regulate initiation.

Complete DNA sequence of Kuraishia capsulata illustrates novel genomic features among budding yeasts (Saccharomycotina)

The numerous yeast genome sequences presently available provide a rich source of information for functional as well as evolutionary genomics but unequally cover the large phylogenetic diversity of extant yeasts. We present here the complete sequence of the nuclear genome of the haploid-type strain of Kuraishia capsulata (CBS1993^T), a nitrate-assimilating Saccharomycetales of uncertain taxonomy, isolated from tunnels of insect larvae underneath coniferous barks and characterized by its copious production of extracellular polysaccharides. The sequence is composed of seven scaffolds, one per chromosome, totaling 11.4 Mb and containing 6,029 protein-coding genes, ∼13.5% of which being interrupted by introns. This GC-rich yeast genome (45.7%) appears phylogenetically related with the few other nitrate-assimilating yeasts sequenced so far, Ogataea polymorpha, O. parapolymorpha, and Dekkera bruxellensis, with which it shares a very reduced number of tRNA genes, a novel tRNA sparing strategy, and a common nitrate assimilation cluster, three specific features to this group of yeasts. Centromeres were recognized in GC-poor troughs of each scaffold. The strain bears MAT alpha genes at a single MAT locus and presents a significant degree of conservation with Saccharomyces cerevisiae genes, suggesting that it can perform sexual cycles in nature, although genes involved in meiosis were not all recognized. The complete absence of conservation of synteny between K. capsulata and any other yeast genome described so far, including the three other nitrate-assimilating species, validates the interest of this species for long-range evolutionary genomic studies among Saccharomycotina yeasts.

Modelling the efficiency of codon-tRNA interactions based on codon usage bias

The tRNA adaptation index (tAI) is a widely used measure of the efficiency by which a coding sequence is recognized by the intra-cellular tRNA pool. This index includes among others weights that represent wobble interactions between codons and tRNA molecules. Currently, these weights are based only on the gene expression in Saccharomyces cerevisiae. However, the efficiencies of the different codon–tRNA interactions are expected to vary among different organisms. In this study, we suggest a new approach for adjusting the tAI weights to any target model organism without the need for gene expression measurements. Our method is based on optimizing the correlation between the tAI and a measure of codon usage bias. Here, we show that in non-fungal the new tAI weights predict protein abundance significantly better than the traditional tAI weights. The unique tRNA–codon adaptation weights computed for 100 different organisms exhibit a significant correlation with evolutionary distance. The reported results demonstrate the usefulness of the new measure in future genomic studies.

Entrainment to periodic initiation and transition rates in a computational model for gene translation

Periodic oscillations play an important role in many biomedical systems. Proper functioning of biological systems that respond to periodic signals requires the ability to synchronize with the periodic excitation. For example, the sleep/wake cycle is a manifestation of an internal timing system that synchronizes to the solar day. In the terminology of systems theory, the biological system must entrain or phase-lock to the periodic excitation. Entrainment is also important in synthetic biology. For example, connecting several artificial biological systems that entrain to a common clock may lead to a well-functioning modular system. The cell-cycle is a periodic program that regulates DNA synthesis and cell division. Recent biological studies suggest that cell-cycle related genes entrain to this periodic program at the gene translation level, leading to periodically-varying protein levels of these genes. The ribosome flow model (RFM) is a deterministic model obtained via a mean-field approximation of a stochastic model from statistical physics that has been used to model numerous processes including ribosome flow along the mRNA. Here we analyze the RFM under the assumption that the initiation and/or transition rates vary periodically with a common period . We show that the ribosome distribution profile in the RFM entrains to this periodic excitation. In particular, the protein synthesis pattern converges to a unique periodic solution with period . To the best of our knowledge, this is the first proof of entrainment in a mathematical model for translation that encapsulates aspects such as initiation and termination rates, ribosomal movement and interactions, and non-homogeneous elongation speeds along the mRNA. Our results support the conjecture that periodic oscillations in tRNA levels and other factors related to the translation process can induce periodic oscillations in protein levels, and may suggest a new approach for re-engineering genetic systems to obtain a desired, periodic, protein synthesis rate.

Most associations between transcript features and gene expression are monotonic

Dozens of previous studies in the field have dealt with the relations between transcript features and their expression. Indeed, understanding the way gene expression is encoded in transcripts should not only contribute to disciplines, such as functional genomics and molecular evolution, but also to biotechnology and human health. Previous studies in the field mainly aimed at predicting protein levels of genes based on their transcript features. Most of the models employed in this context assume that the effect of each transcript feature on gene expression is monotonic. In the current study we aim to understand, for the first time, if indeed the relations between transcript features (i.e., the UTRs and ORF) and measurements related to the different stages of gene expression is monotonic. To this end, we analyze 5432 transcript features and perform gene expression measurements (mRNA levels, ribosomal densities, protein levels, etc.) of 4367 S. cerevisiae genes. We use the Maximal Information Coefficient (MIC) in order to identify potential relations that are not necessarily linear or monotonic. Our analyses demonstrate that the relation between most transcript features and the examined gene expression measurements is monotonic (only up to 1-5% of the variables, with significance levels of 0.001, are non-monotonic); in addition, in the cases of deviation from monotonicity the relation/deviation is very weak. These results should help in guiding the development of computational gene expression modeling and engineering, and improve the understanding of this process. Furthermore, the relatively simple relations between a transcript's nucleotide composition and its expression should contribute towards better understanding of transcript evolution at the molecular level.

Inferring gene function from evolutionary change in signatures of translation efficiency

Background

The genetic code is redundant, meaning that most amino acids can be encoded by more than one codon. Highly expressed genes tend to use optimal codons to increase the accuracy and speed of translation. Thus, codon usage biases provide a signature of the relative expression levels of genes, which can, uniquely, be quantified across the domains of life.

Results

Here we describe a general statistical framework to exploit this phenomenon and to systematically associate genes with environments and phenotypic traits through changes in codon adaptation. By inferring evolutionary signatures of translation efficiency in 911 bacterial and archaeal genomes while controlling for confounding effects of phylogeny and inter-correlated phenotypes, we linked 187 gene families to 24 diverse phenotypic traits. A series of experiments in Escherichia coli revealed that 13 of 15, 19 of 23, and 3 of 6 gene families with changes in codon adaptation in aerotolerant, thermophilic, or halophilic microbes. Respectively, confer specific resistance to, respectively, hydrogen peroxide, heat, and high salinity. Further, we demonstrate experimentally that changes in codon optimality alone are sufficient to enhance stress resistance. Finally, we present evidence that multiple genes with altered codon optimality in aerobes confer oxidative stress resistance by controlling the levels of iron and NAD(P)H.

Conclusions

Taken together, these results provide experimental evidence for a widespread connection between changes in translation efficiency and phenotypic adaptation. As the number of sequenced genomes increases, this novel genomic context method for linking genes to phenotypes based on sequence alone will become increasingly useful.

Ribosome profiling reveals post-transcriptional buffering of divergent gene expression in yeast

Understanding the patterns and causes of phenotypic divergence is a central goal in evolutionary biology. Much work has shown that mRNA abundance is highly variable between closely related species. However, the extent and mechanisms of post-transcriptional gene regulatory evolution are largely unknown. Here we used ribosome profiling to compare transcript abundance and translation efficiency in two closely related yeast species (S. cerevisiae and S. paradoxus). By comparing translation regulatory divergence to interspecies differences in mRNA sequence features, we show that differences in transcript leaders and codon bias substantially contribute to divergent translation. Globally, we find that translation regulatory divergence often buffers species differences in mRNA abundance, such that ribosome occupancy is more conserved than transcript abundance. We used allele-specific ribosome profiling in interspecies hybrids to compare the relative contributions of cis- and trans-regulatory divergence to species differences in mRNA abundance and translation efficiency. The mode of gene regulatory divergence differs for these processes, as trans-regulatory changes play a greater role in divergent mRNA abundance than in divergent translation efficiency. Strikingly, most genes with aberrant transcript abundance in F1 hybrids (either over- or underexpressed compared to both parent species) did not exhibit aberrant ribosome occupancy. Our results show that interspecies differences in translation contribute substantially to the evolution of gene expression. Compensatory differences in transcript abundance and translation efficiency may increase the robustness of gene regulation.

Relative specificity: all substrates are not created equal

A biological molecule, e.g., an enzyme, tends to interact with its many cognate substrates, targets, or partners differentially. Such a property is termed relative specificity and has been proposed to regulate important physiological functions, even though it has not been examined explicitly in most complex biochemical systems. This essay reviews several recent large-scale studies that investigate protein folding, signal transduction, RNA binding, translation and transcription in the context of relative specificity. These results and others support a pervasive role of relative specificity in diverse biological processes. It is becoming clear that relative specificity contributes fundamentally to the diversity and complexity of biological systems, which has significant implications in disease processes as well.

A comprehensive tRNA deletion library unravels the genetic architecture of the tRNA pool

Deciphering the architecture of the tRNA pool is a prime challenge in translation research, as tRNAs govern the efficiency and accuracy of the process. Towards this challenge, we created a systematic tRNA deletion library in Saccharomyces cerevisiae, aimed at dissecting the specific contribution of each tRNA gene to the tRNA pool and to the cell's fitness. By harnessing this resource, we observed that the majority of tRNA deletions show no appreciable phenotype in rich medium, yet under more challenging conditions, additional phenotypes were observed. Robustness to tRNA gene deletion was often facilitated through extensive backup compensation within and between tRNA families. Interestingly, we found that within tRNA families, genes carrying identical anti-codons can contribute differently to the cellular fitness, suggesting the importance of the genomic surrounding to tRNA expression. Characterization of the transcriptome response to deletions of tRNA genes exposed two disparate patterns: in single-copy families, deletions elicited a stress response; in deletions of genes from multi-copy families, expression of the translation machinery increased. Our results uncover the complex architecture of the tRNA pool and pave the way towards complete understanding of their role in cell physiology.