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

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.

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.

A novel de novo synonymous variant in GREB1L impacts the mRNA splicing associated with aplasia of the urogenital system

GREB1-like retinoic acid receptor coactivator (GREB1L) gene is associated with autosomal dominant renal hypodysplasia/aplasia 3 (RHDA3) and deafness, autosomal dominant 80 (DFNA80). Among the GREB1L variants reported, most of them are missense or frameshift, while no pathogenic synonymous variants have been recorded. Classical theory paid little attention to synonymous variants and classified it as nonpathogenic; however, recent studies suggest that the variants might be equally important. Here, we report a 7-year-old girl with new symptoms of clitoromegaly, uterovaginal, and ovarian agenesis as well as right kidney missing. A novel de novo GREB1L synonymous variant (NM_001142966: c.4731C>T, p.G1577=) was identified via whole exome sequencing. The variant was predicted to be disease-causing through in silico analysis and was classified as likely pathogenic. Minigene splicing assays confirmed a 6 bp deletion in mutant cDNA comparing with the wild type, leading to two amino acids lost in GREB1L protein. Secondary and tertiary structure modeling showed alterations in protein structure. Our finding reveals a novel GREB1L variant with a new phenotype of urogenital system and is the first to report a pathogenic synonymous variant in GREB1L which affects mRNA splicing, suggesting synonymous variants cannot be ignored in prenatal diagnosis and genetic counseling.

Interconnected Codons: Unravelling the Epigenetic Significance of Flanking Sequences in CpG Dyads

Hypothesizing that CpG codon dyads, formed by consecutive codons containing a cytosine-guanine pair (NNC-GNN), may play a crucial role in gene function, we conducted an extensive analysis to investigate their distribution and conservation within mammalian genes. Our findings reveal that genes characterized by a high density of CpG codon dyads are notably associated with homeobox domains and RNA polymerase II transcription factors. Conversely, genes exhibiting low CpG codon dyad density have links to DNA damage repair and mitosis. Importantly, our study identifies a re-markable increase in expressed genes that harbor CpG during embryonic development, suggesting their potential involvement in gene regulation at these developmental stages. These results under-score the functional significance of CpG codon dyads in DNA methylation and gene expression, fur-ther demonstrating the coevolution of consecutive codons and their contribution to codon usage bias.

Ser/Leu-swapped cell-free translation system constructed with natural/in vitro transcribed-hybrid tRNA set

The Ser/Leu-swapped genetic code can act as a genetic firewall, mitigating biohazard risks arising from horizontal gene transfer in genetically modified organisms. Our prior work demonstrated the orthogonality of this swapped code to the standard genetic code using a cell-free translation system comprised of 21 in vitro transcribed tRNAs. In this study, to advance this system for protein engineering, we introduce a natural/in vitro transcribed-hybrid tRNA set. This set combines natural tRNAs from Escherichia coli (excluding Ser, Leu, and Tyr) and in vitro transcribed tRNAs, encompassing anticodon-swapped tRNASerGAG and tRNALeuGGA. This approach reduces the number of in vitro transcribed tRNAs required from 21 to only 4. In this optimized system, the production of a model protein, superfolder green fluorescent protein, increases to 3.5-fold. With this hybrid tRNA set, the Ser/Leu-swapped cell-free translation system will stand as a potent tool for protein production with reduced biohazard concerns in future biological endeavors.

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.

Genes for highly abundant proteins in Escherichia coli avoid 5' codons that promote ribosomal initiation

In many species highly expressed genes (HEGs) over-employ the synonymous codons that match the more abundant iso-acceptor tRNAs. Bacterial transgene codon randomization experiments report, however, that enrichment with such "translationally optimal" codons has little to no effect on the resultant protein level. By contrast, consistent with the view that ribosomal initiation is rate limiting, synonymous codon usage following the 5' ATG greatly influences protein levels, at least in part by modifying RNA stability. For the design of bacterial transgenes, for simple codon based in silico inference of protein levels and for understanding selection on synonymous mutations, it would be valuable to computationally determine initiation optimality (IO) scores for codons for any given species. One attractive approach is to characterize the 5' codon enrichment of HEGs compared with the most lowly expressed genes, just as translational optimality scores of codons have been similarly defined employing the full gene body. Here we determine the viability of this approach employing a unique opportunity: for Escherichia coli there is both the most extensive protein abundance data for native genes and a unique large-scale transgene codon randomization experiment enabling objective definition of the 5' codons that cause, rather than just correlate with, high protein abundance (that we equate with initiation optimality, broadly defined). Surprisingly, the 5' ends of native genes that specify highly abundant proteins avoid such initiation optimal codons. We find that this is probably owing to conflicting selection pressures particular to native HEGs, including selection favouring low initiation rates, this potentially enabling high efficiency of ribosomal usage and low noise. While the classical HEG enrichment approach does not work, rendering simple prediction of native protein abundance from 5' codon content futile, we report evidence that initiation optimality scores derived from the transgene experiment may hold relevance for in silico transgene design for a broad spectrum of bacteria.

In Vitro Roles of Burkholderia Intracellular Motility A (BimA) in Infection of Human Neuroblastoma Cell Line

The bacterial pathogen Burkholderia pseudomallei causes human melioidosis, which can infect the brain, leading to encephalitis and brain abscesses. Infection of the nervous system is a rare condition but is associated with an increased risk of mortality. Burkholderia intracellular motility A (BimA) was reported to play an important role in the invasion and infection of the central nervous system in a mouse model. Thus, to gain insight of the cellular mechanisms underlying the pathogenesis of neurological melioidosis, we explored the human neuronal proteomics to identify the host factors that are up- and downregulated during Burkholderia infection. When infected the SH-SY5Y cells with B. pseudomallei K96243 wild-type (WT), 194 host proteins showed a fold change of >2 compared with uninfected cells. Moreover, 123 proteins showed a fold change of >2 when infected with a knockout bimA mutant (ΔbimA) mutant compared with WT. The differentially expressed proteins were mainly associated with metabolic pathways and pathways linked to human diseases. Importantly, we observed the downregulation of proteins in the apoptosis and cytotoxicity pathway, and in vitro investigation with the ΔbimA mutant revealed the association of BimA with the induction of these pathways. Additionally, we disclosed that BimA was not required for invasion into the neuron cell line but was necessary for effective intracellular replication and multinucleated giant cell (MNGC) formation. These findings show the extraordinary capacity of B. pseudomallei in subverting and interfering with host cellular systems to establish infection and extend our understanding of B. pseudomallei BimA involvement in the pathogenesis of neurological melioidosis. IMPORTANCE Neurological melioidosis, caused by Burkholderia pseudomallei, can result in severe neurological damage and enhance the mortality rate of melioidosis patients. We investigate the involvement of the virulent factor BimA, which mediates actin-based motility, in the intracellular infection of neuroblastoma SH-SY5Y cells. Using proteomics-based analysis, we provide a list of host factors exploited by B. pseudomallei. The expression level of selected downregulated proteins in neuron cells infected with the ΔbimA mutant was determined by quantitative reverse transcription-PCR and was consistent with our proteomic data. The role of BimA in the apoptosis and cytotoxicity of SH-SY5Y cells infected by B. pseudomallei was uncovered in this study. Additionally, our research demonstrates that BimA is required for successful intracellular survival and cell fusion upon infection of neuron cells. Our findings have significant implications for understanding the pathogenesis of B. pseudomallei infections and developing novel therapeutic strategies to combat this deadly disease.

Developmental Selection and the Perception of Mutation Bias

The notion that mutations are random relative to their fitness effects is central to the Neo-Darwinian view of evolution. However, a recent interpretation of the patterns of mutation accumulation in the genome of Arabidopsis thaliana has challenged this notion, arguing for the presence of a targeted DNA repair mechanism that causes a nonrandom association of mutation rates and fitness effects. Specifically, this mechanism was suggested to cause a reduction in the rates of mutations on essential genes, thus lowering the rates of deleterious mutations. Central to this argument were attempts to rule out selection at the population level. Here, we offer an alternative and parsimonious interpretation of the patterns of mutation accumulation previously attributed to mutation bias, showing how they can instead or additionally be caused by developmental selection, that is selection occurring at the cellular level during the development of a multicellular organism. Thus, the depletion of deleterious mutations in A. thaliana may indeed be the result of a selective process, rather than a bias in mutation. More broadly, our work highlights the importance of considering development in the interpretation of population-genetic analyses of multicellular organisms, and it emphasizes that efforts to identify mechanisms involved in mutational biases should explicitly account for developmental selection.

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.

A comprehensive analysis of Usutu virus (USUV) genomes revealed lineage-specific codon usage patterns and host adaptations

The Usutu virus (USUV) is an emerging arbovirus virus maintained in the environment of Afro-Eurasia via a bird-mosquito-bird enzootic cycle and sporadically infected other vertebrates. Despite primarily asymptomatic or mild symptoms, humans infected by USUV can develop severe neurological diseases such as meningoencephalitis. However, no detailed study has yet been conducted to investigate its evolution from the perspective of codon usage patterns. Codon usage choice of viruses reflects the genetic variations that enable them to reconcile their viability and fitness toward the external environment and new hosts. This study performed a comprehensive evolution and codon usage analysis of USUVs. Our reconstructed phylogenetic tree confirmed that the circulation viruses belong to eight distinct lineages, reaffirmed by principal component analysis based on codon usage patterns. We also found a relatively small codon usage bias and that natural selection, mutation pressure, dinucleotide abundance, and evolutionary processes collectively shaped the codon usage of the USUV, with natural selection predominating over the others. Additionally, a complex interaction of codon usage between the USUV and its host was observed. This process could have enabled USUV to adapt to various hosts and vectors, including humans. Therefore, the USUV may possess a potential risk of cross-species transmission and subsequent outbreaks. In this respect, further epidemiologic surveys, diversity monitoring, and pathogenetic research are warranted.

Proteome-Wide Structural Computations Provide Insights into Empirical Amino Acid Substitution Matrices

The relative contribution of mutation and selection to the amino acid substitution rates observed in empirical matrices is unclear. Herein, we present a neutral continuous fitness-stability model, inspired by the Arrhenius law (qij=aije-ΔΔGij). The model postulates that the rate of amino acid substitution (i→j) is determined by the product of a pre-exponential factor, which is influenced by the genetic code structure, and an exponential term reflecting the relative fitness of the amino acid substitutions. To assess the validity of our model, we computed changes in stability of 14,094 proteins, for which 137,073,638 in silico mutants were analyzed. These site-specific data were summarized into a 20 square matrix, whose entries, ΔΔGij, were obtained after averaging through all the sites in all the proteins. We found a significant positive correlation between these energy values and the disease-causing potential of each substitution, suggesting that the exponential term accurately summarizes the fitness effect. A remarkable observation was that amino acids that were highly destabilizing when acting as the source, tended to have little effect when acting as the destination, and vice versa (source → destination). The Arrhenius model accurately reproduced the pattern of substitution rates collected in the empirical matrices, suggesting a relevant role for the genetic code structure and a tuning role for purifying selection exerted via protein stability.