Systematic Detection of Amino Acid Substitutions in Proteomes Reveals Mechanistic Basis of Ribosome Errors and Selection for Translation Fidelity

Comparison of Shared Class I HLA-Bound Noncanonical Neoepitopes between Normal and Neoplastic Tissues of Pancreatic Adenocarcinoma

PURPOSE

Developing T-cell or vaccine therapies for pancreatic ductal adenocarcinoma (PDAC) has been challenging because of a lack of knowledge regarding immunodominant, cancer-specific antigens as PDAC are characterized by a scarcity of genomic mutation-associated neoepitopes, and effective approaches to discover them are limited.

EXPERIMENTAL DESIGN

An advanced mass spectrometry approach was employed to compare the immunopeptidome of PDAC tissues and matched normal tissues from the same patients.

RESULTS

This study identified HLA class I-binding variant peptides derived from canonical proteins, which had single amino-acid substitutions not attributed to genetic mutations or RNA editing. These amino-acid substitutions appeared to result from translational errors. The variant peptides were predominantly found in tumor tissues, with certain peptides common among multiple patients. Importantly, several of these variant peptides were more immunogenic than their wild-type counterparts.

CONCLUSIONS

The shared noncanonical neoepitopes identified in this study offer promising candidates for vaccine and T-cell therapy development, potentially providing new avenues for immunotherapy in PDAC. See related commentary by Yuan et al., p. 1821.

Constraints on the optimization of gene product diversity

RNA and proteins can have diverse isoforms due to post-transcriptional and post-translational modifications. A fundamental question is whether these isoforms are mostly beneficial or the result of noisy molecular processes. To assess the plausibility of these explanations, we developed mathematical models depicting different regulatory architectures and investigated isoform evolution under multiple population genetic regimes. We found that factors beyond selection, such as effective population size and the number of cis-acting loci, significantly influence evolutionary outcomes. We found that sub-optimal phenotypes are more likely to evolve when populations are small and/or when the number of cis-loci is large. We also discovered that opposing selection on cis- and trans-acting loci can constrain adaptation, leading to a non-monotonic relationship between effective population size and optimization. More generally, our models provide a quantitative framework for developing statistical tests to analyze empirical data; as a demonstration of this, we analyzed A-to-I RNA editing levels in coleoids and found these to be largely consistent with non-adaptive explanations.

Translational error in mice increases with ageing in an organ-dependent manner

The accuracy of protein synthesis and its relation to ageing has been of long-standing interest. To study whether spontaneous changes in the rate of ribosomal error occur as a function of age, we first determined that stop-codon readthrough is a more sensitive read-out of mistranslation due to codon-anticodon mispairing than missense amino acid incorporation. Subsequently, we developed knock-in mice for in-vivo detection of stop-codon readthrough using a gain-of-function Kat2-TGA-Fluc readthrough reporter which combines fluorescent and sensitive bioluminescent imaging techniques. We followed expression of reporter proteins in-vivo over time, and assessed Kat2 and Fluc expression in tissue extracts and by whole organ ex-vivo imaging. Collectively, our results provide evidence for an organ-dependent, age-related increase in translational error: stop-codon readthrough increases with age in muscle (+ 75%, p < 0.001) and brain (+ 50%, p < 0.01), but not in liver (p > 0.5). Together with recent data demonstrating premature ageing in mice with an error-prone ram mutation, our findings highlight age-related decline of translation fidelity as a possible contributor to ageing.

Isoleucine-to-valine substitutions support cellular physiology during isoleucine deprivation

Aminoacyl-tRNA synthetases (ARSs) couple tRNAs with their corresponding amino acids. While ARSs can bind structurally similar amino acids, extreme specificity is ensured by subsequent editing activity. Yet, we found that upon isoleucine (I) restriction, healthy fibroblasts consistently incorporated valine (V) into proteins at isoleucine codons, resulting from misacylation of tRNAIle with valine by wildtype IARS1. Using a dual-fluorescent reporter of translation, we found that valine supplementation could fully compensate for isoleucine depletion and restore translation to normal levels in healthy, but not IARS1 deficient cells. Similarly, the antiproliferative effects of isoleucine deprivation could be fully restored by valine supplementation in healthy, but not IARS1 deficient cells. This indicates I > V substitutions help prevent translational termination and maintain cellular function in human primary cells during isoleucine deprivation. We suggest that this is an example of a more general mechanism in mammalian cells to preserve translational speed at the cost of translational fidelity in response to (local) amino acid deficiencies.

Further Evidence for Strong Nonneutrality of Yeast Synonymous Mutations

Although synonymous mutations are commonly assumed neutral or nearly so, recent years have seen reports of fitness effects of synonymous mutations detected under laboratory conditions. In a previous study, we used genome editing to construct thousands of yeast mutants each carrying a synonymous or nonsynonymous mutation in one of 21 genes, and discovered that most synonymous and most nonsynonymous mutations are deleterious. A concern was raised that this observation could be caused by the fitness effects of potential CRISPR/Cas9 off-target edits and/or secondary mutations, and an experiment that would be refractory to such effects was proposed. Using genome sequencing, we here show that no CRISPR/Cas9 off-target editing occurred, although some mutants did carry secondary mutations. Analysis of mutants with negligible effects from secondary mutations and new data collected from the proposed experiment confirms the original conclusion. These findings, along with other reports of fitness effects of synonymous mutations from both case and systematic studies, necessitate a paradigm shift from assuming (near) neutrality of synonymous mutations.

A machine learning approach uncovers principles and determinants of eukaryotic ribosome pausing

Nonuniform local translation speed dictates diverse protein biogenesis outcomes. To unify known and uncover unknown principles governing eukaryotic elongation rate, we developed a machine learning pipeline to analyze RiboSeq datasets. We find that the chemical nature of the incoming amino acid determines how codon optimality influences elongation rate, with hydrophobic residues more dependent on transfer RNA (tRNA) levels than charged residues. Unexpectedly, we find that wobble interactions exert a widespread effect on elongation pausing, with wobble-mediated decoding being slower than Watson-Crick decoding, irrespective of tRNA levels. Applying our ribosome pausing principles to ribosome collisions reveals that disomes arise upon apposition of fast-decoding and slow-decoding signatures. We conclude that codon choice and tRNA pools are evolutionarily constrained to harmonize elongation rate with cotranslational folding while minimizing wobble pairing and deleterious stalling.

Alternate RNA decoding results in stable and abundant proteins in mammals

Amino acid substitutions may substantially alter protein stability and function, but the contribution of substitutions arising from alternate translation (deviations from the genetic code) is unknown. To explore it, we analyzed deep proteomic and transcriptomic data from over 1,000 human samples, including 6 cancer types and 26 healthy human tissues. This global analysis identified 60,024 high confidence substitutions corresponding to 8,801 unique sites in proteins derived from 1,990 genes. Some substitutions are shared across samples, while others exhibit strong tissue-type and cancer specificity. Surprisingly, products of alternate translation are more abundant than their canonical counterparts for hundreds of proteins, suggesting sense codon recoding. Recoded proteins include transcription factors, proteases, signaling proteins, and proteins associated with neurodegeneration. Mechanisms contributing to substitution abundance include protein stability, codon frequency, codon-anticodon mismatches, and RNA modifications. We characterize sequence motifs around alternatively translated amino acids and how substitution ratios vary across protein domains, tissue types and cancers. The substitution ratios are positively associated with intrinsically disordered regions and genetic polymorphisms in gnomAD, though the polymorphisms cannot account for the substitutions. Both the sequence and the tissue-specificity of alternatively translated proteins are conserved between human and mouse. These results demonstrate the contribution of alternate translation to diversifying mammalian proteomes, and its association with protein stability, tissue-specific proteomes, and diseases.

Genome-wide impact of codon usage bias on translation optimization in Drosophila melanogaster

Accuracy and efficiency are fundamental to mRNA translation. Codon usage bias is widespread across species. Despite the long-standing association between optimized codon usage and improved translation, our understanding of its evolutionary basis and functional effects remains limited. Drosophila is widely used to study codon usage bias, but genome-scale experimental data are scarce. Using high-resolution mass spectrometry data from Drosophila melanogaster, we show that optimal codons have lower translation errors than nonoptimal codons after accounting for these biases. Genomic-scale analysis of ribosome profiling data shows that optimal codons are translated more rapidly than nonoptimal codons. Although we find no long-term selection favoring synonymous mutations in D. melanogaster after diverging from D. simulans, we identify signatures of positive selection driving codon optimization in the D. melanogaster population. These findings expand our understanding of the functional consequences of codon optimization and serve as a foundation for future investigations.

Impact of tRNA-induced proline-to-serine mistranslation on the transcriptome of Drosophila melanogaster

Mistranslation is the misincorporation of an amino acid into a polypeptide. Mistranslation has diverse effects on multicellular eukaryotes and is implicated in several human diseases. In Drosophila melanogaster, a serine transfer RNA (tRNA) that misincorporates serine at proline codons (P→S) affects male and female flies differently. The mechanisms behind this discrepancy are currently unknown. Here, we compare the transcriptional response of male and female flies to P→S mistranslation to identify genes and cellular processes that underlie sex-specific differences. Both males and females downregulate genes associated with various metabolic processes in response to P→S mistranslation. Males downregulate genes associated with extracellular matrix organization and response to negative stimuli such as wounding, whereas females downregulate aerobic respiration and ATP synthesis genes. Both sexes upregulate genes associated with gametogenesis, but females also upregulate cell cycle and DNA repair genes. These observed differences in the transcriptional response of male and female flies to P→S mistranslation have important implications for the sex-specific impact of mistranslation on disease and tRNA therapeutics.

Synonymous rpsH variants: the common denominator in Escherichia coli adapting to ionizing radiation

Ionizing radiation (IR) in high doses is generally lethal to most organisms. Investigating mechanisms of radiation resistance is crucial for gaining insights into the underlying cellular responses and understanding the damaging effects of IR. In this study, we conducted a comprehensive analysis of sequencing data from an evolutionary experiment aimed at understanding the genetic adaptations to ionizing radiation in Escherichia coli. By including previously neglected synonymous mutations, we identified the rpsH c.294T > G variant, which emerged in all 17 examined isolates across four subpopulations. The identified variant is a synonymous mutation affecting the 30S ribosomal protein S8, and consistently exhibited high detection and low allele frequencies in all subpopulations. This variant, along with two additional rpsH variants, potentially influences translational control of the ribosomal spc operon. The early emergence and stability of these variants suggest their role in adapting to environmental stress, possibly contributing to radiation resistance. Our findings shed light on the dynamics of ribosomal variants during the evolutionary process and their potential role in stress adaptation, providing valuable implications for understanding clinical radiation sensitivity and improving radiotherapy.

The central role of transfer RNAs in mistranslation

Transfer RNAs (tRNA) are essential small non-coding RNAs that enable the translation of genomic information into proteins in all life forms. The principal function of tRNAs is to bring amino acid building blocks to the ribosomes for protein synthesis. In the ribosome, tRNAs interact with messenger RNA (mRNA) to mediate the incorporation of amino acids into a growing polypeptide chain following the rules of the genetic code. Accurate interpretation of the genetic code requires tRNAs to carry amino acids matching their anticodon identity and decode the correct codon on mRNAs. Errors in these steps cause the translation of codons with the wrong amino acids (mistranslation), compromising the accurate flow of information from DNA to proteins. Accumulation of mutant proteins due to mistranslation jeopardizes proteostasis and cellular viability. However, the concept of mistranslation is evolving, with increasing evidence indicating that mistranslation can be used as a mechanism for survival and acclimatization to environmental conditions. In this review, we discuss the central role of tRNAs in modulating translational fidelity through their dynamic and complex interplay with translation factors. We summarize recent discoveries of mistranslating tRNAs and describe the underlying molecular mechanisms and the specific conditions and environments that enable and promote mistranslation.

A Proteogenomic Pipeline for the Analysis of Protein Biosynthesis Errors in the Human Pathogen Candida albicans

Candida albicans is a diploid pathogen known for its ability to live as a commensal fungus in healthy individuals but causing both superficial infections and disseminated candidiasis in immunocompromised patients where it is associated with high morbidity and mortality. Its success in colonizing the human host is attributed to a wide range of virulence traits that modulate interactions between the host and the pathogen, such as optimal growth rate at 37 °C, the ability to switch between yeast and hyphal forms, and a remarkable genomic and phenotypic plasticity. A fascinating aspect of its biology is a prominent heterogeneous proteome that arises from frequent genomic rearrangements, high allelic variation, and high levels of amino acid misincorporations in proteins. This leads to increased morphological and physiological phenotypic diversity of high adaptive potential, but the scope of such protein mistranslation is poorly understood due to technical difficulties in detecting and quantifying amino acid misincorporation events in complex protein samples. We have developed and optimized mass spectrometry and bioinformatics pipelines capable of identifying rare amino acid misincorporation events at the proteome level. We have also analyzed the proteomic profile of an engineered C. albicans strain that exhibits high level of leucine misincorporation at protein CUG sites and employed an in vivo quantitative gain-of-function fluorescence reporter system to validate our LC-MS/MS data. C. albicans misincorporates amino acids above the background level at protein sites of diverse codons, particularly at CUG, confirming our previous data on the quantification of leucine incorporation at single CUG sites of recombinant reporter proteins, but increasing misincorporation of Leucine at these sites does not alter the translational fidelity of the other codons. These findings indicate that the C. albicans statistical proteome exceeds prior estimates, suggesting that its highly plastic phenome may also be modulated by environmental factors due to translational ambiguity.

Hyperactivation of mTOR/eIF4E Signaling Pathway Promotes the Production of Tryptophan-To-Phenylalanine Substitutants in EBV-Positive Gastric Cancer

Although messenger RNA translation is tightly regulated to preserve protein synthesis and cellular homeostasis, chronic exposure to interferon-γ (IFN-γ) in several cancers can lead to tryptophan (Trp) shortage via the indoleamine-2,3-dioxygenase (IDO)- kynurenine pathway and therefore promotes the production of aberrant peptides by ribosomal frameshifting and tryptophan-to-phenylalanine (W>F) codon reassignment events (substitutants) specifically at Trp codons. However, the effect of Trp depletion on the generation of aberrant peptides by ribosomal mistranslation in gastric cancer (GC) is still obscure. Here, it is shows that the abundant infiltrating lymphocytes in EBV-positive GC continuously secreted IFN-γ, upregulated IDO1 expression, leading to Trp shortage and the induction of W>F substitutants. Intriguingly, the production of W>F substitutants in EBV-positive GC is linked to antigen presentation and the activation of the mTOR/eIF4E signaling pathway. Inhibiting either the mTOR/eIF4E pathway or EIF4E expression counteracted the production and antigen presentation of W>F substitutants. Thus, the mTOR/eIF4E pathway exposed the vulnerability of gastric cancer by accelerating the production of aberrant peptides and boosting immune activation through W>F substitutant events. This work proposes that EBV-positive GC patients with mTOR/eIF4E hyperactivation may benefit from anti-tumor immunotherapy.

Ribosomal protein RPL39L is an efficiency factor in the cotranslational folding of a subset of proteins with alpha helical domains

Increasingly many studies reveal how ribosome composition can be tuned to optimally translate the transcriptome of individual cell types. In this study, we investigated the expression pattern, structure within the ribosome and effect on protein synthesis of the ribosomal protein paralog 39L (RPL39L). With a novel mass spectrometric approach we revealed the expression of RPL39L protein beyond mouse germ cells, in human pluripotent cells, cancer cell lines and tissue samples. We generated RPL39L knock-out mouse embryonic stem cell (mESC) lines and demonstrated that RPL39L impacts the dynamics of translation, to support the pluripotency and differentiation, spontaneous and along the germ cell lineage. Most differences in protein abundance between WT and RPL39L KO lines were explained by widespread autophagy. By CryoEM analysis of purified RPL39 and RPL39L-containing ribosomes we found that, unlike RPL39, RPL39L has two distinct conformations in the exposed segment of the nascent peptide exit tunnel, creating a distinct hydrophobic patch that has been predicted to support the efficient co-translational folding of alpha helices. Our study shows that ribosomal protein paralogs provide switchable modular components that can tune translation to the protein production needs of individual cell types.

Genetic and selective constraints on the optimization of gene product diversity

RNA and protein expressed from the same gene can have diverse isoforms due to various post-transcriptional and post-translational modifications. For the vast majority of alternative isoforms, It is unknown whether they are adaptive or simply biological noise. As we cannot experimentally probe the function of each isoform, we can ask whether the distribution of isoforms across genes and across species is consistent with expectations from different evolutionary processes. However, there is currently no theoretical framework that can generate such predictions. To address this, we developed a mathematical model where isoform abundances are determined collectively by cis-acting loci, trans-acting factors, gene expression levels, and isoform decay rates to predict isoform abundance distributions across species and genes in the face of mutation, genetic drift, and selection. We found that factors beyond selection, such as effective population size and the number of cis-acting loci, significantly influence evolutionary outcomes. Notably, suboptimal phenotypes are more likely to evolve when the population is small and/or when the number of cis-loci is large. We also explored scenarios where modification processes have both beneficial and detrimental effects, revealing a non-monotonic relationship between effective population size and optimization, demonstrating how opposing selection pressures on cis- and trans-acting loci can constrain the optimization of gene product diversity. As a demonstration of the power of our theory, we compared the expected distribution of A-to-I RNA editing levels in coleoids and found this to be largely consistent with non-adaptive explanations.

deTELpy: Python package for high-throughput detection of amino acid substitutions in mass spectrometry datasets

MOTIVATION

Errors in the processing of genetic information during protein synthesis can lead to phenotypic mutations, such as amino acid substitutions, e.g. by transcription or translation errors. While genetic mutations can be readily identified using DNA sequencing, and mutations due to transcription errors by RNA sequencing, translation errors can only be identified proteome-wide using mass spectrometry.

RESULTS

Here, we provide a Python package implementation of a high-throughput pipeline to detect amino acid substitutions in mass spectrometry datasets. Our tools enable users to process hundreds of mass spectrometry datasets in batch mode to detect amino acid substitutions and calculate codon-specific and site-specific translation error rates. deTELpy will facilitate the systematic understanding of amino acid misincorporation rates (translation error rates), and the inference of error models across organisms and under stress conditions, such as drug treatment or disease conditions.

AVAILABILITY AND IMPLEMENTATION

deTELpy is implemented in Python 3 and is freely available with detailed documentation and practical examples at https://git.mpi-cbg.de/tothpetroczylab/detelpy and https://pypi.org/project/deTELpy/ and can be easily installed via pip install deTELpy.

Mechanisms and Delivery of tRNA Therapeutics

Transfer ribonucleic acid (tRNA) therapeutics will provide personalized and mutation specific medicines to treat human genetic diseases for which no cures currently exist. The tRNAs are a family of adaptor molecules that interpret the nucleic acid sequences in our genes into the amino acid sequences of proteins that dictate cell function. Humans encode more than 600 tRNA genes. Interestingly, even healthy individuals contain some mutant tRNAs that make mistakes. Missense suppressor tRNAs insert the wrong amino acid in proteins, and nonsense suppressor tRNAs read through premature stop signals to generate full length proteins. Mutations that underlie many human diseases, including neurodegenerative diseases, cancers, and diverse rare genetic disorders, result from missense or nonsense mutations. Thus, specific tRNA variants can be strategically deployed as therapeutic agents to correct genetic defects. We review the mechanisms of tRNA therapeutic activity, the nature of the therapeutic window for nonsense and missense suppression as well as wild-type tRNA supplementation. We discuss the challenges and promises of delivering tRNAs as synthetic RNAs or as gene therapies. Together, tRNA medicines will provide novel treatments for common and rare genetic diseases in humans.

Examining the Effects of Temperature on the Evolution of Bacterial tRNA Pools

The genetic code consists of 61 codons coding for 20 amino acids. These codons are recognized by transfer RNAs (tRNAs) that bind to specific codons during protein synthesis. All organisms utilize less than all 61 possible anticodons due to base pair wobble: the ability to have a mismatch with a codon at its third nucleotide. Previous studies observed a correlation between the tRNA pool of bacteria and the temperature of their respective environments. However, it is unclear if these patterns represent biological adaptations to maintain the efficiency and accuracy of protein synthesis in different environments. A mechanistic mathematical model of mRNA translation is used to quantify the expected elongation rates and error rate for each codon based on an organism's tRNA pool. A comparative analysis across a range of bacteria that accounts for covariance due to shared ancestry is performed to quantify the impact of environmental temperature on the evolution of the tRNA pool. We find that thermophiles generally have more anticodons represented in their tRNA pool than mesophiles or psychrophiles. Based on our model, this increased diversity is expected to lead to increased missense errors. The implications of this for protein evolution in thermophiles are discussed.

Engineering tRNAs for the Ribosomal Translation of Non-proteinogenic Monomers

Ribosome-dependent protein biosynthesis is an essential cellular process mediated by transfer RNAs (tRNAs). Generally, ribosomally synthesized proteins are limited to the 22 proteinogenic amino acids (pAAs: 20 l-α-amino acids present in the standard genetic code, selenocysteine, and pyrrolysine). However, engineering tRNAs for the ribosomal incorporation of non-proteinogenic monomers (npMs) as building blocks has led to the creation of unique polypeptides with broad applications in cellular biology, material science, spectroscopy, and pharmaceuticals. Ribosomal polymerization of these engineered polypeptides presents a variety of challenges for biochemists, as translation efficiency and fidelity is often insufficient when employing npMs. In this Review, we will focus on the methodologies for engineering tRNAs to overcome these issues and explore recent advances both in vitro and in vivo. These efforts include increasing orthogonality, recruiting essential translation factors, and creation of expanded genetic codes. After our review on the biochemical optimizations of tRNAs, we provide examples of their use in genetic code manipulation, with a focus on the in vitro discovery of bioactive macrocyclic peptides containing npMs. Finally, an analysis of the current state of tRNA engineering is presented, along with existing challenges and future perspectives for the field.

Cysteine substitutants emerge in lung cancer proteomes during arginine restriction

In this issue of Molecular Cell, Yang et al.1 find that arginine-to-cysteine substitutants are enriched in a subset of lung cancer proteomes, potentiated by arginine deprivation, and promote resistance to chemotherapy.

Arginine deprivation enriches lung cancer proteomes with cysteine by inducing arginine-to-cysteine substitutants

Many types of human cancers suppress the expression of argininosuccinate synthase 1 (ASS1), a rate-limiting enzyme for arginine production. Although dependency on exogenous arginine can be harnessed by arginine-deprivation therapies, the impact of ASS1 suppression on the quality of the tumor proteome is unknown. We therefore interrogated proteomes of cancer patients for arginine codon reassignments (substitutants) and surprisingly identified a strong enrichment for cysteine (R>C) in lung tumors specifically. Most R>C events did not coincide with genetically encoded R>C mutations but were likely products of tRNA misalignments. The expression of R>C substitutants was highly associated with oncogenic kelch-like epichlorohydrin (ECH)-associated protein 1 (KEAP1)-pathway mutations and suppressed by intact-KEAP1 in KEAP1-mutated cancer cells. Finally, functional interrogation indicated a key role for R>C substitutants in cell survival to cisplatin, suggesting that regulatory codon reassignments endow cancer cells with more resilience to stress. Thus, we present a mechanism for enriching lung cancer proteomes with cysteines that may affect therapeutic decisions.

Impact of tRNA-induced proline-to-serine mistranslation on the transcriptome of Drosophila melanogaster

Mistranslation is the misincorporation of an amino acid into a polypeptide. Mistranslation has diverse effects on multicellular eukaryotes and is implicated in several human diseases. In Drosophila melanogaster, a serine transfer RNA (tRNA) that misincorporates serine at proline codons (P→S) affects male and female flies differently. The mechanisms behind this discrepancy are currently unknown. Here, we compare the transcriptional response of male and female flies to P→S mistranslation to identify genes and cellular processes that underlie sex-specific differences. Both males and females downregulate genes associated with various metabolic processes in response to P→S mistranslation. Males downregulate genes associated with extracellular matrix organization and response to negative stimuli such as wounding, whereas females downregulate aerobic respiration and ATP synthesis genes. Both sexes upregulate genes associated with gametogenesis, but females also upregulate cell cycle and DNA repair genes. These observed differences in the transcriptional response of male and female flies to P→S mistranslation have important implications for the sex-specific impact of mistranslation on disease and tRNA therapeutics.

Recent developments, opportunities, and challenges in the study of mRNA pseudouridylation

Pseudouridine is an abundant mRNA modification found in diverse organisms ranging from bacteria and viruses to multicellular plants and humans. New developments in pseudouridine profiling provide quantitative tools to map mRNA pseudouridylation sites. Sparse biochemical studies establish the potential for mRNA pseudouridylation to affect most stages of the mRNA life cycle from birth to death. This recent progress sets the stage for deeper investigations into the molecular and cellular functions of specific mRNA pseudouridines, including in disease.

Fit for Purpose Approach To Evaluate Detection of Amino Acid Substitutions in Shotgun Proteomics

Amino acid substitutions (AASs) alter proteins from their genome-expected sequences. Accumulation of substitutions in proteins underlies numerous diseases and antibiotic mechanisms. Accurate global detection of AASs and their frequencies is crucial for understanding these mechanisms. Shotgun proteomics provides an untargeted method for measuring AASs but introduces biases when extrapolating from the genome to identify AASs. To characterize these biases, we created a "ground-truth" approach using the similarities betweenEscherichia coli and Salmonella typhimurium to model the complexity of AAS detection. Shotgun proteomics on mixed lysates generated libraries representing ∼100,000 peptide-spectra and 4161 peptide sequences with a single AAS and defined stoichiometry. Identifying S. typhimurium peptide-spectra with only the E. coli genome resulted in 64.1% correctly identified library peptides. Specific AASs exhibit variable identification efficiencies. There was no inherent bias from the stoichiometry of the substitutions. Short peptides and AASs localized near peptide termini had poor identification efficiency. We identify a new class of "scissor substitutions" that gain or lose protease cleavage sites. Scissor substitutions also had poor identification efficiency. This ground-truth AAS library reveals various sources of bias, which will guide the application of shotgun proteomics to validate AAS hypotheses.

Resilience and proteome response of Escherichia coli to high levels of isoleucine mistranslation

Accurate pairing of amino acids and tRNAs is a prerequisite for faithful translation of genetic information during protein biosynthesis. Here we present the effects of proteome-wide mistranslation of isoleucine (Ile) by canonical valine (Val) or non-proteinogenic norvaline (Nva) in a genetically engineered Escherichia coli strain with an editing-defective isoleucyl-tRNA synthetase (IleRS). Editing-defective IleRS efficiently mischarges both Val and Nva to tRNAIle and impairs the translational accuracy of Ile decoding. When mistranslation was induced by the addition of Val or Nva to the growth medium, an Ile-to-Val or Ile-to-Nva substitution of up to 20 % was measured by high-resolution mass spectrometry. This mistranslation level impaired bacterial growth, promoted the SOS response and filamentation during stationary phase, caused global proteome dysregulation and upregulation of the cellular apparatus for maintaining proteostasis, including the major chaperones (GroES/EL, DnaK/DnaJ/GrpE and HtpG), the disaggregase ClpB and the proteases (Lon, HslV/HslU, ClpA, ClpS). The most important consequence of mistranslation appears to be non-specific protein aggregation, which is effectively counteracted by the disaggregase ClpB. Our data show that E. coli can sustain high isoleucine mistranslation levels and remain viable despite excessive protein aggregation and severely impaired translational fidelity. However, we show that inaccurate translation lowers bacterial resilience to heat stress and decreases bacterial survival at elevated temperatures.

Fitness Effects of Phenotypic Mutations at Proteome-Scale Reveal Optimality of Translation Machinery

Errors in protein translation can lead to non-genetic, phenotypic mutations, including amino acid misincorporations. While phenotypic mutations can increase protein diversity, the systematic characterization of their proteome-wide frequencies and their evolutionary impact has been lacking. Here, we developed a mechanistic model of translation errors to investigate how selection acts on protein populations produced by amino acid misincorporations. We fitted the model to empirical observations of misincorporations obtained from over a hundred mass spectrometry datasets of E. coli and S. cerevisiae. We found that on average 20% to 23% of proteins synthesized in the cell are expected to harbor at least one amino acid misincorporation, and that deleterious misincorporations are less likely to occur. Combining misincorporation probabilities and the estimated fitness effects of amino acid substitutions in a population genetics framework, we found 74% of mistranslation events in E. coli and 94% in S. cerevisiae to be neutral. We further show that the set of available synonymous tRNAs is subject to evolutionary pressure, as the presence of missing tRNAs would increase codon-anticodon cross-reactivity and misincorporation error rates. Overall, we find that the translation machinery is likely optimal in E. coli and S. cerevisiae and that both local solutions at the level of codons and a global solution such as the tRNA pool can mitigate the impact of translation errors. We provide a framework to study the evolutionary impact of codon-specific translation errors and a method for their proteome-wide detection across organisms and conditions.

Selective gene expression maintains human tRNA anticodon pools during differentiation

Transfer RNAs are essential for translating genetic information into proteins. The human genome contains hundreds of predicted tRNA genes, many in multiple copies. How their expression is regulated to control tRNA repertoires is unknown. Here we combined quantitative tRNA profiling and chromatin immunoprecipitation with sequencing to measure tRNA expression following the differentiation of human induced pluripotent stem cells into neuronal and cardiac cells. We find that tRNA transcript levels vary substantially, whereas tRNA anticodon pools, which govern decoding rates, are more stable among cell types. Mechanistically, RNA polymerase III transcribes a wide range of tRNA genes in human induced pluripotent stem cells but on differentiation becomes constrained to a subset we define as housekeeping tRNAs. This shift is mediated by decreased mTORC1 signalling, which activates the RNA polymerase III repressor MAF1. Our data explain how tRNA anticodon pools are buffered to maintain decoding speed across cell types and reveal that mTORC1 drives selective tRNA expression during differentiation.

Principles, challenges, and advances in ribosome profiling: from bulk to low-input and single-cell analysis

Ribosome profiling has revolutionized our understanding of gene expression regulation by providing a snapshot of global translation in vivo. This powerful technique enables the investigation of the dynamics of translation initiation, elongation, and termination, and has provided insights into the regulation of protein synthesis under various conditions. Despite its widespread adoption, challenges persist in obtaining high-quality ribosome profiling data. In this review, we discuss the fundamental principles of ribosome profiling and related methodologies, including selective ribosome profiling and translation complex profiling. We also delve into quality control to assess the reliability of ribosome profiling datasets, and the efforts to improve data quality by modifying the standard procedures. Additionally, we highlight recent advancements in ribosome profiling that enable the transition from bulk to low-input and single-cell applications. Single-cell ribosome profiling has emerged as a crucial tool for exploring translation heterogeneity within specific cell populations. However, the challenges of capturing mRNAs efficiently and the sparse nature of footprint reads in single-cell ribosome profiling present ongoing obstacles. The need to refine ribosome profiling techniques remains, especially when used at the single-cell level.

Exploring the "misfolding problem" by systematic discovery and analysis of functional-but-degraded proteins

In both health and disease, the ubiquitin-proteasome system (UPS) degrades point mutants that retain partial function but have decreased stability compared with their wild-type counterparts. This class of UPS substrate includes routine translational errors and numerous human disease alleles, such as the most common cause of cystic fibrosis, ΔF508-CFTR. Yet, there is no systematic way to discover novel examples of these "minimally misfolded" substrates. To address that shortcoming, we designed a genetic screen to isolate functional-but-degraded point mutants, and we used the screen to study soluble, monomeric proteins with known structures. These simple parent proteins yielded diverse substrates, allowing us to investigate the structural features, cytotoxicity, and small-molecule regulation of minimal misfolding. Our screen can support numerous lines of inquiry, and it provides broad access to a class of poorly understood but biomedically critical quality-control substrates.

Milligrams to kilograms: making microbes work at scale

If biomanufacturing can become a sustainable route for producing chemicals, it will provide a critical step in reducing greenhouse gas emissions to fight climate change. However, efforts to industrialize microbial synthesis of chemicals have met with varied success, due, in part, to challenges in translating laboratory successes to industrial scale. With a particular focus on Escherichia coli, this review examines the lessons learned when studying microbial physiology and metabolism under conditions that simulate large-scale bioreactors and methods to minimize cellular waste through reduction of maintenance energy, optimizing the stress response and minimizing culture heterogeneity. With general strategies to overcome these challenges, biomanufacturing process scale-up could be de-risked and the time and cost of bringing promising syntheses to market could be reduced.

Genome-wide screening reveals metabolic regulation of stop-codon readthrough by cyclic AMP

Translational fidelity is critical for microbial fitness, survival and stress responses. Much remains unknown about the genetic and environmental control of translational fidelity and its single-cell heterogeneity. In this study, we used a high-throughput fluorescence-based assay to screen a knock-out library of Escherichia coli and identified over 20 genes critical for stop-codon readthrough. Most of these identified genes were not previously known to affect translational fidelity. Intriguingly, we show that several genes controlling metabolism, including cyaA and crp, enhance stop-codon readthrough. CyaA catalyzes the synthesis of cyclic adenosine monophosphate (cAMP). Combining RNA sequencing, metabolomics and biochemical analyses, we show that deleting cyaA impairs amino acid catabolism and production of ATP, thus repressing the transcription of rRNAs and tRNAs to decrease readthrough. Single-cell analyses further show that cAMP is a major driver of heterogeneity in stop-codon readthrough and rRNA expression. Our results highlight that carbon metabolism is tightly coupled with stop-codon readthrough.

Determining the effects of temperature on the evolution of bacterial tRNA pools

The genetic code consists of 61 codon coding for 20 amino acids. These codons are recognized by transfer RNAs (tRNA) that bind to specific codons during protein synthesis. Most organisms utilize less than all 61 possible anticodons due to base pair wobble: the ability to have a mismatch with a codon at its third nucleotide. Previous studies observed a correlation between the tRNA pool of bacteria and the temperature of their respective environments. However, it is unclear if these patterns represent biological adaptations to maintain the efficiency and accuracy of protein synthesis in different environments. A mechanistic mathematical model of mRNA translation is used to quantify the expected elongation rates and error rate for each codon based on an organism's tRNA pool. A comparative analysis across a range of bacteria that accounts for covariance due to shared ancestry is performed to quantify the impact of environmental temperature on the evolution of the tRNA pool. We find that thermophiles generally have more anticodons represented in their tRNA pool than mesophiles or psychrophiles. Based on our model, this increased diversity is expected to lead to increased missense errors. The implications of this for protein evolution in thermophiles are discussed.

Identification of a non-canonical ciliate nuclear genetic code where UAA and UAG code for different amino acids

The genetic code is one of the most highly conserved features across life. Only a few lineages have deviated from the "universal" genetic code. Amongst the few variants of the genetic code reported to date, the codons UAA and UAG virtually always have the same translation, suggesting that their evolution is coupled. Here, we report the genome and transcriptome sequencing of a novel uncultured ciliate, belonging to the Oligohymenophorea class, where the translation of the UAA and UAG stop codons have changed to specify different amino acids. Genomic and transcriptomic analyses revealed that UAA has been reassigned to encode lysine, while UAG has been reassigned to encode glutamic acid. We identified multiple suppressor tRNA genes with anticodons complementary to the reassigned codons. We show that the retained UGA stop codon is enriched in the 3'UTR immediately downstream of the coding region of genes, suggesting that there is functional drive to maintain tandem stop codons. Using a phylogenomics approach, we reconstructed the ciliate phylogeny and mapped genetic code changes, highlighting the remarkable number of independent genetic code changes within the Ciliophora group of protists. According to our knowledge, this is the first report of a genetic code variant where UAA and UAG encode different amino acids.

Phenotype switching of the mutation rate facilitates adaptive evolution

The mutation rate plays an important role in adaptive evolution. It can be modified by mutator and anti-mutator alleles. Recent empirical evidence hints that the mutation rate may vary among genetically identical individuals: evidence from bacteria suggests that the mutation rate can be affected by expression noise of a DNA repair protein and potentially also by translation errors in various proteins. Importantly, this non-genetic variation may be heritable via a transgenerational epigenetic mode of inheritance, giving rise to a mutator phenotype that is independent from mutator alleles. Here, we investigate mathematically how the rate of adaptive evolution is affected by the rate of mutation rate phenotype switching. We model an asexual population with two mutation rate phenotypes, non-mutator and mutator. An offspring may switch from its parental phenotype to the other phenotype. We find that switching rates that correspond to so-far empirically described non-genetic systems of inheritance of the mutation rate lead to higher rates of adaptation on both artificial and natural fitness landscapes. These switching rates can maintain within the same individuals both a mutator phenotype and intermediary mutations, a combination that facilitates adaptation. Moreover, non-genetic inheritance increases the proportion of mutators in the population, which in turn increases the probability of hitchhiking of the mutator phenotype with adaptive mutations. This in turns facilitates the acquisition of additional adaptive mutations. Our results rationalize recently observed noise in the expression of proteins that affect the mutation rate and suggest that non-genetic inheritance of this phenotype may facilitate evolutionary adaptive processes.

Decoding and Recoding of mRNA Sequences by the Ribosome

Faithful translation of messenger RNA (mRNA) into protein is essential to maintain protein homeostasis in the cell. Spontaneous translation errors are very rare due to stringent selection of cognate aminoacyl transfer RNAs (tRNAs) and the tight control of the mRNA reading frame by the ribosome. Recoding events, such as stop codon readthrough, frameshifting, and translational bypassing, reprogram the ribosome to make intentional mistakes and produce alternative proteins from the same mRNA. The hallmark of recoding is the change of ribosome dynamics. The signals for recoding are built into the mRNA, but their reading depends on the genetic makeup of the cell, resulting in cell-specific changes in expression programs. In this review, I discuss the mechanisms of canonical decoding and tRNA-mRNA translocation; describe alternative pathways leading to recoding; and identify the links among mRNA signals, ribosome dynamics, and recoding.

Molecular mechanisms of eukaryotic translation fidelity and their associations with diseases

Converting genetic information into functional proteins is a complex, multi-step process, with each step being tightly regulated to ensure the accuracy of translation, which is critical to cellular health. In recent years, advances in modern biotechnology, especially the development of cryo-electron microscopy and single-molecule techniques, have enabled a clearer understanding of the mechanisms of protein translation fidelity. Although there are many studies on the regulation of protein translation in prokaryotes, and the basic elements of translation are highly conserved in prokaryotes and eukaryotes, there are still great differences in the specific regulatory mechanisms. This review describes how eukaryotic ribosomes and translation factors regulate protein translation and ensure translation accuracy. However, a certain frequency of translation errors does occur in translation, so we describe diseases that arise when the rate of translation errors reaches or exceeds a threshold of cellular tolerance.

Proteome diversification by mRNA translation in cancer

mRNA translation is a highly conserved and tightly controlled mechanism for protein synthesis and is well known to be altered by oncogenes to promote cancer development. This distorted mRNA translation is accompanied by the vulnerability of cancer to inhibitors of key mRNA translation components. Novel studies also suggest that these alternations could be utilized for immunotherapy. Ribosome heterogeneity and alternative responses to nutrient shortages, which aid cancer growth and spread, are proposed to elicit aberrant protein production but may also result in previously unidentified therapeutic targets, such as the presentation of cancer-specific peptides at the surface of cancer cells (neoepitopes). This review will assess the driving forces in tRNA and ribosome function that underlie proteome diversification due to alterations in mRNA translation in cancer cells.

What Has Genomics Taught An Evolutionary Biologist?

Genomics, an interdisciplinary field of biology on the structure, function, and evolution of genomes, has revolutionized many subdisciplines of life sciences, including my field of evolutionary biology, by supplying huge data, bringing high-throughput technologies, and offering a new approach to biology. In this review, I describe what I have learned from genomics and highlight the fundamental knowledge and mechanistic insights gained. I focus on three broad topics that are central to evolutionary biology and beyond-variation, interaction, and selection-and use primarily my own research and study subjects as examples. In the next decade or two, I expect that the most important contributions of genomics to evolutionary biology will be to provide genome sequences of nearly all known species on Earth, facilitate high-throughput phenotyping of natural variants and systematically constructed mutants for mapping genotype-phenotype-fitness landscapes, and assist the determination of causality in evolutionary processes using experimental evolution.

Anticodon sequence determines the impact of mistranslating tRNAAla variants

Transfer RNAs (tRNAs) maintain translation fidelity through accurate charging by their cognate aminoacyl-tRNA synthetase and codon:anticodon base pairing with the mRNA at the ribosome. Mistranslation occurs when an amino acid not specified by the genetic message is incorporated into proteins and has applications in biotechnology, therapeutics and is relevant to disease. Since the alanyl-tRNA synthetase uniquely recognizes a G3:U70 base pair in tRNAAla and the anticodon plays no role in charging, tRNAAla variants with anticodon mutations have the potential to mis-incorporate alanine. Here, we characterize the impact of the 60 non-alanine tRNAAla anticodon variants on the growth of Saccharomyces cerevisiae. Overall, 36 tRNAAla anticodon variants decreased growth in single- or multi-copy. Mass spectrometry analysis of the cellular proteome revealed that 52 of 57 anticodon variants, not decoding alanine or stop codons, induced mistranslation when on single-copy plasmids. Variants with G/C-rich anticodons resulted in larger growth deficits than A/U-rich variants. In most instances, synonymous anticodon variants impact growth differently, with anticodons containing U at base 34 being the least impactful. For anticodons generating the same amino acid substitution, reduced growth generally correlated with the abundance of detected mistranslation events. Differences in decoding specificity, even between synonymous anticodons, resulted in each tRNAAla variant mistranslating unique sets of peptides and proteins. We suggest that these differences in decoding specificity are also important in determining the impact of tRNAAla anticodon variants.

Variance in translational fidelity of different bacterial species is affected by pseudouridines in the tRNA anticodon stem-loop

Delicate variances in the translational machinery affect how efficiently different organisms approach protein synthesis. Determining the scale of this effect, however, requires knowledge on the differences of mistranslation levels. Here, we used a dual-luciferase reporter assay cloned into a broad host range plasmid to reveal the translational fidelity profiles of Pseudomonas putida, Pseudomonas aeruginosa and Escherichia coli. We observed that these profiles are surprisingly different, whereas species more prone to translational frameshifting are not necessarily more prone to stop codon readthrough. As tRNA modifications are among the factors that have been implicated to affect translation accuracy, we also show that translational fidelity is context-specifically influenced by pseudouridines in the anticodon stem-loop of tRNA, but the effect is not uniform between species.

Correlation between protein abundance and sequence conservation: what do recent experiments say?

Cells evolve in a space of parameter values set by physical and chemical forces. These constraints create associations among cellular properties. A particularly strong association is the negative correlation between the rate of evolution of proteins and their abundance in the cell. Highly expressed proteins evolve slower than lowly expressed ones. Multiple hypotheses have been put forward to explain this relationship, including, for instance, the requirement for higher mRNA stability, misfolding avoidance, and misinteraction avoidance for highly expressed proteins. Here, we review some of these hypotheses, their predictions, and how they are supported to finally discuss recent experiments that have been performed to test these predictions.

A male germ-cell-specific ribosome controls male fertility

Ribosomes are highly sophisticated translation machines that have been demonstrated to be heterogeneous in the regulation of protein synthesis^1,2. Male germ cell development involves complex translational regulation during sperm formation³. However, it remains unclear whether translation during sperm formation is performed by a specific ribosome. Here we report a ribosome with a specialized nascent polypeptide exit tunnel, Ribosome^ST, that is assembled with the male germ-cell-specific protein RPL39L, the paralogue of core ribosome (Ribosome^Core) protein RPL39. Deletion of Ribosome^ST in mice causes defective sperm formation, resulting in substantially reduced fertility. Our comparison of single-particle cryo-electron microscopy structures of ribosomes from mouse kidneys and testes indicates that Ribosome^ST features a ribosomal polypeptide exit tunnel of distinct size and charge states compared with Ribosome^Core. Ribosome^ST predominantly cotranslationally regulates the folding of a subset of male germ-cell-specific proteins that are essential for the formation of sperm. Moreover, we found that specialized functions of Ribosome^ST were not replaceable by Ribosome^Core. Taken together, identification of this sperm-specific ribosome should greatly expand our understanding of ribosome function and tissue-specific regulation of protein expression pattern in mammals.

Gene product diversity: adaptive or not?

One gene does not equal one RNA or protein. The genomic revolution has revealed numerous different RNA and protein molecules that can be produced from one gene, such as circular RNAs generated by back-splicing, proteins with residues mismatching the genomic encoding because of RNA editing, and proteins extended in the C terminus via stop codon readthrough in translation. Are these diverse products results of exquisite gene regulations or imprecise biological processes? While there are cases where the gene product diversity appears beneficial, genome-scale patterns suggest that much of this diversity arises from nonadaptive, molecular errors. This finding has important implications for studying the functions of diverse gene products and for understanding the fundamental properties and evolution of cellular life.

Phenotypic mutations contribute to protein diversity and shape protein evolution

Errors in DNA replication generate genetic mutations, while errors in transcription and translation lead to phenotypic mutations. Phenotypic mutations are orders of magnitude more frequent than genetic ones, yet they are less understood. Here, we review the types of phenotypic mutations, their quantifications, and their role in protein evolution and disease. The diversity generated by phenotypic mutation can facilitate adaptive evolution. Indeed, phenotypic mutations, such as ribosomal frameshift and stop codon readthrough, sometimes serve to regulate protein expression and function. Phenotypic mutations have often been linked to fitness decrease and diseases. Thus, understanding the protein heterogeneity and phenotypic diversity caused by phenotypic mutations will advance our understanding of protein evolution and have implications on human health and diseases.

Geneticin reduces mRNA stability

Messenger RNA (mRNA) translation can lead to higher rates of mRNA decay, suggesting the ribosome plays a role in mRNA destruction. Furthermore, mRNA features, such as codon identities, which are directly probed by the ribosome, correlate with mRNA decay rates. Many amino acids are encoded by synonymous codons, some of which are decoded by more abundant tRNAs leading to more optimal translation and increased mRNA stability. Variable translation rates for synonymous codons can lead to ribosomal collisions as ribosomes transit regions with suboptimal codons, and ribosomal collisions can promote mRNA decay. In addition to different translation rates, the presence of certain codons can also lead to higher or lower rates of amino acid misincorporation which could potentially lead to protein misfolding if a substituted amino acid fails to make critical contacts in a structure. Here, we test whether Geneticin—G418, an aminoglycoside antibiotic known to promote amino acid misincorporation—affects mRNA stability. We observe that G418 decreases firefly luciferase mRNA stability in an in vitro translation system and also reduces mRNA stability in mouse embryonic stem cells (mESCs). G418-sensitive mRNAs are enriched for certain optimal codons that contain G or C in the wobble position, arguing that G418 blunts the stabilizing effects of codon optimality.

Preferred synonymous codons are translated more accurately: Proteomic evidence, among-species variation, and mechanistic basis

A commonly stated cause of unequal uses of synonymous codons is their differential translational accuracies. A key prediction of this long-standing translational accuracy hypothesis (TAH) of codon usage bias is higher translational accuracies of more frequently used synonymous codons, which, however, has had no direct evidence beyond case studies. Analyzing proteomic data from Escherichia coli, we present direct, global evidence for this prediction. The experimentally measured codon-specific translational accuracies validate a sequence-based proxy; this proxy provides support for the TAH from the vast majority of over 1000 taxa surveyed in all domains of life. We find that the relative translational accuracies of synonymous codons vary substantially among taxa and are strongly correlated with the amounts of cognate transfer RNAs (tRNAs) relative to those of near-cognate tRNAs. These and other observations suggest a model in which selections for translational efficiency and accuracy drive codon usage bias and its coevolution with the tRNA pool.

Mechanisms of protein evolution

How do proteins evolve? How do changes in sequence mediate changes in protein structure, and in turn in function? This question has multiple angles, ranging from biochemistry and biophysics to evolutionary biology. This review provides a brief integrated view of some key mechanistic aspects of protein evolution. First, we explain how protein evolution is primarily driven by randomly acquired genetic mutations and selection for function, and how these mutations can even give rise to completely new folds. Then, we also comment on how phenotypic protein variability, including promiscuity, transcriptional and translational errors, may also accelerate this process, possibly via "plasticity-first" mechanisms. Finally, we highlight open questions in the field of protein evolution, with respect to the emergence of more sophisticated protein systems such as protein complexes, pathways, and the emergence of pre-LUCA enzymes.

Quantifying shifts in natural selection on codon usage between protein regions: a population genetics approach

Background

Codon usage bias (CUB), the non-uniform usage of synonymous codons, occurs across all domains of life. Adaptive CUB is hypothesized to result from various selective pressures, including selection for efficient ribosome elongation, accurate translation, mRNA secondary structure, and/or protein folding. Given the critical link between protein folding and protein function, numerous studies have analyzed the relationship between codon usage and protein structure. The results from these studies have often been contradictory, likely reflecting the differing methods used for measuring codon usage and the failure to appropriately control for confounding factors, such as differences in amino acid usage between protein structures and changes in the frequency of different structures with gene expression.

Results

Here we take an explicit population genetics approach to quantify codon-specific shifts in natural selection related to protein structure in S. cerevisiae and E. coli. Unlike other metrics of codon usage, our approach explicitly separates the effects of natural selection, scaled by gene expression, and mutation bias while naturally accounting for a region’s amino acid usage. Bayesian model comparisons suggest selection on codon usage varies only slightly between helix, sheet, and coil secondary structures and, similarly, between structured and intrinsically-disordered regions. Similarly, in contrast to prevous findings, we find selection on codon usage only varies slightly at the termini of helices in E. coli. Using simulated data, we show this previous work indicating “non-optimal” codons are enriched at the beginning of helices in S. cerevisiae was due to failure to control for various confounding factors (e.g. amino acid biases, gene expression, etc.), and rather than selection to modulate cotranslational folding.

Conclusions

Our results reveal a weak relationship between codon usage and protein structure, indicating that differences in selection on codon usage between structures are slight. In addition to the magnitude of differences in selection between protein structures being slight, the observed shifts appear to be idiosyncratic and largely codon-specific rather than systematic reversals in the nature of selection. Overall, our work demonstrates the statistical power and benefits of studying selective shifts on codon usage or other genomic features from an explicitly evolutionary approach. Limitations of this approach and future potential research avenues are discussed.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12864-022-08635-0).

Tryptophan depletion results in tryptophan-to-phenylalanine substitutants

Activated T cells secrete interferon-γ, which triggers intracellular tryptophan shortage by upregulating the indoleamine 2,3-dioxygenase 1 (IDO1) enzyme^1-4. Here we show that despite tryptophan depletion, in-frame protein synthesis continues across tryptophan codons. We identified tryptophan-to-phenylalanine codon reassignment (W>F) as the major event facilitating this process, and pinpointed tryptophanyl-tRNA synthetase (WARS1) as its source. We call these W>F peptides 'substitutants' to distinguish them from genetically encoded mutants. Using large-scale proteomics analyses, we demonstrate W>F substitutants to be highly abundant in multiple cancer types. W>F substitutants were enriched in tumours relative to matching adjacent normal tissues, and were associated with increased IDO1 expression, oncogenic signalling and the tumour-immune microenvironment. Functionally, W>F substitutants can impair protein activity, but also expand the landscape of antigens presented at the cell surface to activate T cell responses. Thus, substitutants are generated by an alternative decoding mechanism with potential effects on gene function and tumour immunoreactivity.

Model of Genetic Code Structure Evolution under Various Types of Codon Reading

The standard genetic code (SGC) is a set of rules according to which 64 codons are assigned to 20 canonical amino acids and stop coding signal. As a consequence, the SGC is redundant because there is a greater number of codons than the number of encoded labels. This redundancy implies the existence of codons that encode the same genetic information. The size and organization of such synonymous codon blocks are important characteristics of the SGC structure whose evolution is still unclear. Therefore, we studied possible evolutionary mechanisms of the codon block structure. We conducted computer simulations assuming that coding systems at early stages of the SGC evolution were sets of ambiguous codon assignments with high entropy. We included three types of reading systems characterized by different inaccuracy and pattern of codon recognition. In contrast to the previous study, we allowed for evolution of the reading systems and their competition. The simulations performed under minimization of translational errors and reduction of coding ambiguity produced the coding system resistant to these errors. The reading system similar to that present in the SGC dominated the others very quickly. The survived system was also characterized by low entropy and possessed properties similar to that in the SGC. Our simulation show that the unambiguous SGC could emerged from a code with a lower level of ambiguity and the number of tRNAs increased during the evolution.