Evidence of evolutionary selection for cotranslational folding

Re-examining Correlations Between Synonymous Codon Usage and Protein Bond Angles in Escherichia coli

Rosenberg AA, Marx A, Bronstein AM (Codon-specific Ramachandran plots show amino acid backbone conformation depends on identity of the translated codon. Nat Commun. 2022:13:2815) recently found a surprising correlation between synonymous codon usage and the dihedral bond angles of the resulting amino acid. However, their analysis did not account for the strongest known correlate of codon usage: gene expression. We re-examined the relationship between bond angles and codon usage by applying the approach of Rosenberg et al. to simulated protein-coding sequences that (i) have random codon usage, (ii) codon usage determined by mutation biases, and (iii) maintain the general relationship between codon usage and gene expression via the assumption of selection-mutation-drift equilibrium. We observed correlations between dihedral bond angle and codon usage when codon usage is entirely random, indicating possible conflation of noise with differences in bond angle distributions between synonymous codons. More relevant to the general analysis of codon usage patterns, we found surprisingly good agreement between the analysis of the real sequences and the analysis of sequences simulated assuming selection-mutation-drift equilibrium, with 91% of significant synonymous codon pairs detected in the former were also detected in the latter. We believe the correlation between codon usage and dihedral bond angles resulted from the variation in codon usage across genes due to the interplay between mutation bias, natural selection for translation efficiency, and gene expression, further underscoring these factors must be controlled for when looking for novel patterns related to codon usage.

Back in time to the Gly-rich prototype of the phosphate binding elementary function

Binding of nucleotides and their derivatives is one of the most ancient elementary functions dating back to the Origin of Life. We review here the works considering one of the key elements in binding of (di)nucleotide-containing ligands - phosphate binding. We start from a brief discussion of major participants, conditions, and events in prebiotic evolution that resulted in the Origin of Life. Tracing back to the basic functions, including metal and phosphate binding, and, potentially, formation of primitive protein-protein interactions, we focus here on the phosphate binding. Critically assessing works on the structural, functional, and evolutionary aspects of phosphate binding, we perform a simple computational experiment reconstructing its most ancient and generic sequence prototype. The profiles of the phosphate binding signatures have been derived in form of position-specific scoring matrices (PSSMs), their peculiarities depending on the type of the ligands have been analyzed, and evolutionary connections between them have been delineated. Then, the apparent prototype that gave rise to all relevant phosphate-binding signatures had also been reconstructed. We show that two major signatures of the phosphate binding that discriminate between the binding of dinucleotide- and nucleotide-containing ligands are GxGxxG and GxxGxG, respectively. It appears that the signature archetypal for dinucleotide-containing ligands is more generic, and it can frequently bind phosphate groups in nucleotide-containing ligands as well. The reconstructed prototype's key signature GxGGxG underlies the role of glycine residues in providing flexibility and interactions necessary for binding the phosphate groups. The prototype also contains other ancient amino acids, valine, and alanine, showing versatility towards evolutionary design and functional diversification.

Mechanisms and pathology of protein misfolding and aggregation

Despite advances in machine learning-based protein structure prediction, we are still far from fully understanding how proteins fold into their native conformation. The conventional notion that polypeptides fold spontaneously to their biologically active states has gradually been replaced by our understanding that cellular protein folding often requires context-dependent guidance from molecular chaperones in order to avoid misfolding. Misfolded proteins can aggregate into larger structures, such as amyloid fibrils, which perpetuate the misfolding process, creating a self-reinforcing cascade. A surge in amyloid fibril structures has deepened our comprehension of how a single polypeptide sequence can exhibit multiple amyloid conformations, known as polymorphism. The assembly of these polymorphs is not a random process but is influenced by the specific conditions and tissues in which they originate. This observation suggests that, similar to the folding of native proteins, the kinetics of pathological amyloid assembly are modulated by interactions specific to cells and tissues. Here, we review the current understanding of how intrinsic protein conformational propensities are modulated by physiological and pathological interactions in the cell to shape protein misfolding and aggregation pathology.

Co-translational formation of disulfides guides folding of the SARS-CoV-2 receptor binding domain

Many secreted proteins, including viral proteins, contain multiple disulfide bonds. How disulfide formation is coupled to protein folding in the cell remains poorly understood at the molecular level. Here, we combine experiment and simulation to address this question as it pertains to the SARS-CoV-2 receptor binding domain (RBD). We show that the RBD can only refold reversibly if its native disulfides are present before folding. But in their absence, the RBD spontaneously misfolds into a nonnative, molten-globule-like state that is structurally incompatible with complete disulfide formation and that is highly prone to aggregation. Thus, the RBD native structure represents a metastable state on the protein's energy landscape with reduced disulfides, indicating that nonequilibrium mechanisms are needed to ensure native disulfides form before folding. Our atomistic simulations suggest that this may be achieved via co-translational folding during RBD secretion into the endoplasmic reticulum. Namely, at intermediate translation lengths, native disulfide pairs are predicted to come together with high probability, and thus, under suitable kinetic conditions, this process may lock the protein into its native state and circumvent highly aggregation-prone nonnative intermediates. This detailed molecular picture of the RBD folding landscape may shed light on SARS-CoV-2 pathology and molecular constraints governing SARS-CoV-2 evolution.

Evolutionary adaptation of the protein folding pathway for secretability

Secretory preproteins of the Sec pathway are targeted post-translationally and cross cellular membranes through translocases. During cytoplasmic transit, mature domains remain non-folded for translocase recognition/translocation. After translocation and signal peptide cleavage, mature domains fold to native states in the bacterial periplasm or traffic further. We sought the structural basis for delayed mature domain folding and how signal peptides regulate it. We compared how evolution diversified a periplasmic peptidyl-prolyl isomerase PpiA mature domain from its structural cytoplasmic PpiB twin. Global and local hydrogen-deuterium exchange mass spectrometry showed that PpiA is a slower folder. We defined at near-residue resolution hierarchical folding initiated by similar foldons in the twins, at different order and rates. PpiA folding is delayed by less hydrophobic native contacts, frustrated residues and a β-turn in the earliest foldon and by signal peptide-mediated disruption of foldon hierarchy. When selected PpiA residues and/or its signal peptide were grafted onto PpiB, they converted it into a slow folder with enhanced in vivo secretion. These structural adaptations in a secretory protein facilitate trafficking.

Cotranslational formation of disulfides guides folding of the SARS COV-2 receptor binding domain

Many secreted proteins contain multiple disulfide bonds. How disulfide formation is coupled to protein folding in the cell remains poorly understood at the molecular level. Here, we combine experiment and simulation to address this question as it pertains to the SARS-CoV-2 receptor binding domain (RBD). We show that, whereas RBD can refold reversibly when its disulfides are intact, their disruption causes misfolding into a nonnative molten-globule state that is highly prone to aggregation and disulfide scrambling. Thus, non-equilibrium mechanisms are needed to ensure disulfides form prior to folding in vivo. Our simulations suggest that co-translational folding may accomplish this, as native disulfide pairs are predicted to form with high probability at intermediate lengths, ultimately committing the RBD to its metastable native state and circumventing nonnative intermediates. This detailed molecular picture of the RBD folding landscape may shed light on SARS-CoV-2 pathology and molecular constraints governing SARS-CoV-2 evolution.

Mechanisms governing codon usage bias and the implications for protein expression in the chloroplast of Chlamydomonas reinhardtii

Chloroplasts possess a considerably reduced genome that is decoded via an almost minimal set of tRNAs. These features make an excellent platform for gaining insights into fundamental mechanisms that govern protein expression. Here, we present a comprehensive and revised perspective of the mechanisms that drive codon selection in the chloroplast of Chlamydomonas reinhardtii and the functional consequences for protein expression. In order to extract this information, we applied several codon usage descriptors to genes with different expression levels. We show that highly expressed genes strongly favor translationally optimal codons, while genes with lower functional importance are rather affected by directional mutational bias. We demonstrate that codon optimality can be deduced from codon-anticodon pairing affinity and, for a small number of amino acids (leucine, arginine, serine, and isoleucine), tRNA concentrations. Finally, we review, analyze, and expand on the impact of codon usage on protein yield, secondary structures of mRNA, translation initiation and termination, and amino acid composition of proteins, as well as cotranslational protein folding. The comprehensive analysis of codon choice provides crucial insights into heterologous gene expression in the chloroplast of C. reinhardtii, which may also be applicable to other chloroplast-containing organisms and bacteria.

A Short Tale of the Origin of Proteins and Ribosome Evolution

Proteins are the workhorses of the cell and have been key players throughout the evolution of all organisms, from the origin of life to the present era. How might life have originated from the prebiotic chemistry of early Earth? This is one of the most intriguing unsolved questions in biology. Currently, however, it is generally accepted that amino acids, the building blocks of proteins, were abiotically available on primitive Earth, which would have made the formation of early peptides in a similar fashion possible. Peptides are likely to have coevolved with ancestral forms of RNA. The ribosome is the most evident product of this coevolution process, a sophisticated nanomachine that performs the synthesis of proteins codified in genomes. In this general review, we explore the evolution of proteins from their peptide origins to their folding and regulation based on the example of superoxide dismutase (SOD1), a key enzyme in oxygen metabolism on modern Earth.

Protocol to identify host-viral protein interactions between coagulation-related proteins and their genetic variants with SARS-CoV-2 proteins

Here, we describe a bioinformatics pipeline that evaluates the interactions between coagulation-related proteins and genetic variants with SARS-CoV-2 proteins. This pipeline searches for host proteins that may bind to viral protein and identifies and scores the protein genetic variants to predict the disease pathogenesis in specific subpopulations. Additionally, it is able to find structurally similar motifs and identify potential binding sites within the host-viral protein complexes to unveil viral impact on regulated biological processes and/or host-protein impact on viral invasion or reproduction. For complete details on the use and execution of this protocol, please refer to Holcomb et al. (2021).

Large protein complex interfaces have evolved to promote cotranslational assembly

Assembly pathways of protein complexes should be precise and efficient to minimise misfolding and unwanted interactions with other proteins in the cell. One way to achieve this efficiency is by seeding assembly pathways during translation via the cotranslational assembly of subunits. While recent evidence suggests that such cotranslational assembly is widespread, little is known about the properties of protein complexes associated with the phenomenon. Here, using a combination of proteome-specific protein complex structures and publicly available ribosome profiling data, we show that cotranslational assembly is particularly common between subunits that form large intermolecular interfaces. To test whether large interfaces have evolved to promote cotranslational assembly, as opposed to cotranslational assembly being a non-adaptive consequence of large interfaces, we compared the sizes of first and last translated interfaces of heteromeric subunits in bacterial, yeast, and human complexes. When considering all together, we observe the N-terminal interface to be larger than the C-terminal interface 54% of the time, increasing to 64% when we exclude subunits with only small interfaces, which are unlikely to cotranslationally assemble. This strongly suggests that large interfaces have evolved as a means to maximise the chance of successful cotranslational subunit binding.

mRNA and tRNA modification states influence ribosome speed and frame maintenance during poly(lysine) peptide synthesis

Ribosome speed is dictated by multiple factors including substrate availability, cellular conditions, and product (peptide) formation. Translation slows during the synthesis of cationic peptide sequences, potentially influencing the expression of thousands of proteins. Available evidence suggests that ionic interactions between positively charged nascent peptides and the negatively charged ribosome exit tunnel impede translation. However, this hypothesis was difficult to test directly because of inability to decouple the contributions of amino acid charge from mRNA sequence and tRNA identity/abundance in cells. Furthermore, it is unclear if other components of the translation system central to ribosome function (e.g., RNA modification) influence the speed and accuracy of positively charged peptide synthesis. In this study, we used a fully reconstituted Escherichia coli translation system to evaluate the effects of peptide charge, mRNA sequence, and RNA modification status on the translation of lysine-rich peptides. Comparison of translation reactions on poly(lysine)-encoding mRNAs conducted with either Lys-tRNA^Lys or Val-tRNA^Lys reveals that that amino acid charge, while important, only partially accounts for slowed translation on these transcripts. We further find that in addition to peptide charge, mRNA sequence and both tRNA and mRNA modification status influence the rates of amino acid addition and the ribosome’s ability to maintain frame (instead of entering the −2, −1, and +1 frames) during poly(lysine) peptide synthesis. Our observations lead us to expand the model for explaining how the ribosome slows during poly(lysine) peptide synthesis and suggest that posttranscriptional RNA modifications can provide cells a mechanism to precisely control ribosome movements along an mRNA.

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).

Folding and Evolution of a Repeat Protein on the Ribosome

Life on earth is the result of the work of proteins, the cellular nanomachines that fold into elaborated 3D structures to perform their functions. The ribosome synthesizes all the proteins of the biosphere, and many of them begin to fold during translation in a process known as cotranslational folding. In this work we discuss current advances of this field and provide computational and experimental data that highlight the role of ribosome in the evolution of protein structures. First, we used the sequence of the Ankyrin domain from the Drosophila Notch receptor to launch a deep sequence-based search. With this strategy, we found a conserved 33-residue motif shared by different protein folds. Then, to see how the vectorial addition of the motif would generate a full structure we measured the folding on the ribosome of the Ankyrin repeat protein. Not only the on-ribosome folding data is in full agreement with classical in vitro biophysical measurements but also it provides experimental evidence on how folded proteins could have evolved by duplication and fusion of smaller fragments in the RNA world. Overall, we discuss how the ribosomal exit tunnel could be conceptualized as an active site that is under evolutionary pressure to influence protein folding.

Analysis of codon usage patterns in open reading frame 4 of hepatitis E viruses

Background

Hepatitis E virus (HEV) is a member of the family Hepeviridae and causes acute HEV infections resulting in thousands of deaths worldwide. The zoonotic nature of HEV in addition to its tendency from human to human transmission has led scientists across the globe to work on its different aspects. HEV also accounts for about 30% mortality rates in case of pregnant women. The genome of HEV is organized into three open reading frames (ORFs): ORF1 ORF2 and ORF3. A reading frame encoded protein ORF4 has recently been discovered which is exclusive to GT 1 isolates of HEV. The ORF4 is suggested to play crucial role in pregnancy-associated pathology and enhanced replication. Though studies have documented the ORF4’s importance, the genetic features of ORF4 protein genes in terms of compositional patterns have not been elucidated. As codon usage performs critical role in establishment of the host–pathogen relationship, therefore, the present study reports the codon usage analysis (based on nucleotide sequences of HEV ORF4 available in the public database) in three hosts along with the factors influencing the codon usage patterns of the protein genes of ORF4 of HEV.

Results

The nucleotide composition analysis indicated that ORF4 protein genes showed overrepresentation of C nucleotide and while A nucleotide was the least-represented, with random distribution of G and T(U) nucleotides. The relative synonymous codon usage (RSCU) analysis revealed biasness toward C/G-ended codons (over U/A) in all three natural HEV-hosts (human, rat and ferret). It was observed that all the ORF4 genes were richly endowed with GC content. Further, our results showed the occurrence of both coincidence and antagonistic codon usage patterns among HEV-hosts. The findings further emphasized that both mutational and selection forces influenced the codon usage patterns of ORF4 protein genes.

Conclusions

To the best of our knowledge, this is first bioinformatics study evaluating codon usage patterns in HEV ORF4 protein genes. The findings from this study are expected to increase our understanding toward significant factors involved in evolutionary changes of ORF4.

Supplementary Information

The online version contains supplementary material available at 10.1186/s43088-022-00244-w.

Thermodynamics of co-translational folding and ribosome-nascent chain interactions

Proteins can begin the conformational search for their native structure in parallel with biosynthesis on the ribosome, in a process termed co-translational folding. In contrast to the reversible folding of isolated domains, as a nascent chain emerges from the ribosome exit tunnel during translation the free energy landscape it explores also evolves as a function of chain length. While this presents a substantially more complex measurement problem, this review will outline the progress that has been made recently in understanding, quantitatively, the process by which a nascent chain attains its full native stability, as well as the mechanisms through which interactions with the nearby ribosome surface can perturb or modulate this process.

CHARMING: Harmonizing synonymous codon usage to replicate a desired codon usage pattern

There is a growing appreciation that synonymous codon usage, although historically regarded as phenotypically silent, can instead alter a wide range of mechanisms related to functional protein production, a term we use here to describe the net effect of transcription (mRNA synthesis), mRNA half-life, translation (protein synthesis) and the probability of a protein folding correctly to its active, functional structure. In particular, recent discoveries have highlighted the important role that sub-optimal codons can play in modifying co-translational protein folding. These results have drawn increased attention to the patterns of synonymous codon usage within coding sequences, particularly in light of the discovery that these patterns can be conserved across evolution for homologous proteins. Because synonymous codon usage differs between organisms, for heterologous gene expression it can be desirable to make synonymous codon substitutions to match the codon usage pattern from the original organism in the heterologous expression host. Here we present CHARMING (for Codon HARMonizING), a robust and versatile algorithm to design mRNA sequences for heterologous gene expression and other related codon harmonization tasks. CHARMING can be run as a downloadable Python script or via a web portal at http://www.codons.org.

Slowest-first protein translation scheme: Structural asymmetry and co-translational folding

Proteins are translated from the N to the C terminus, raising the basic question of how this innate directionality affects their evolution. To explore this question, we analyze 16,200 structures from the Protein Data Bank (PDB). We find remarkable enrichment of α helices at the C terminus and β strands at the N terminus. Furthermore, this α-β asymmetry correlates with sequence length and contact order, both determinants of folding rate, hinting at possible links to co-translational folding (CTF). Hence, we propose the "slowest-first" scheme, whereby protein sequences evolved structural asymmetry to accelerate CTF: the slowest of the cooperatively folding segments are positioned near the N terminus so they have more time to fold during translation. A phenomenological model predicts that CTF can be accelerated by asymmetry in folding rate, up to double the rate, when folding time is commensurate with translation time; analysis of the PDB predicts that structural asymmetry is indeed maximal in this regime. This correspondence is greater in prokaryotes, which generally require faster protein production. Altogether, this indicates that accelerating CTF is a substantial evolutionary force whose interplay with stability and functionality is encoded in secondary structure asymmetry.

Combinations of slow-translating codon clusters can increase mRNA half-life in Saccharomyces cerevisiae

The presence of a single cluster of nonoptimal codons was found to decrease a transcript's half-life through the interaction of the ribosome-associated quality control machinery with stalled ribosomes in Saccharomyces cerevisiae The impact of multiple nonoptimal codon clusters on a transcript's half-life, however, is unknown. Using a kinetic model, we predict that inserting a second nonoptimal cluster near the 5' end can lead to synergistic effects that increase a messenger RNA's (mRNA's) half-life in S. cerevisiae Specifically, the 5' end cluster suppresses the formation of ribosome queues, reducing the interaction of ribosome-associated quality control factors with stalled ribosomes. We experimentally validate this prediction by introducing two nonoptimal clusters into three different genes and find that their mRNA half-life increases up to fourfold. The model also predicts that in the presence of two clusters, the cluster closest to the 5' end is the primary determinant of mRNA half-life. These results suggest the "translational ramp," in which nonoptimal codons are located near the start codon and increase translational efficiency, may have the additional biological benefit of allowing downstream slow-codon clusters to be present without decreasing mRNA half-life. These results indicate that codon usage bias plays a more nuanced role in controlling cellular protein levels than previously thought.

Decoding the effects of synonymous variants

Synonymous single nucleotide variants (sSNVs) are common in the human genome but are often overlooked. However, sSNVs can have significant biological impact and may lead to disease. Existing computational methods for evaluating the effect of sSNVs suffer from the lack of gold-standard training/evaluation data and exhibit over-reliance on sequence conservation signals. We developed synVep (synonymous Variant effect predictor), a machine learning-based method that overcomes both of these limitations. Our training data was a combination of variants reported by gnomAD (observed) and those unreported, but possible in the human genome (generated). We used positive-unlabeled learning to purify the generated variant set of any likely unobservable variants. We then trained two sequential extreme gradient boosting models to identify subsets of the remaining variants putatively enriched and depleted in effect. Our method attained 90% precision/recall on a previously unseen set of variants. Furthermore, although synVep does not explicitly use conservation, its scores correlated with evolutionary distances between orthologs in cross-species variation analysis. synVep was also able to differentiate pathogenic vs. benign variants, as well as splice-site disrupting variants (SDV) vs. non-SDVs. Thus, synVep provides an important improvement in annotation of sSNVs, allowing users to focus on variants that most likely harbor effects.

Identification of conserved slow codons that are important for protein expression and function

ABSTRASTDue to the redundancy of the genetic code most amino acids are encoded by several 'synonymous' codons. These codons are used unevenly, and each organism demonstrates its own unique codon usage bias, where the 'preferred' codons are associated with tRNAs that are found in high concentrations. Therefore, for decades, the prevailing view had been that preferred and non-preferred codons are linked to high or slow translation rates, respectively.However, this simplified view is contrasted by the frequent failures of codon-optimization efforts and by evidence of non-preferred (i.e. 'slow') codons having specific roles important for efficient production of functional proteins. One such specific role of slower codons is the regulation of co-translational protein folding, a complex biophysical process that is very challenging to model or to measure.Here, we combined a genome-wide approach with experiments to investigate the role of slow codons in protein production and co-translational folding. We analysed homologous gene groups from divergent bacteria and identified positions of inter-species conservation of bias towards slow codons. We then generated mutants where the conserved slow codons are substituted with 'fast' ones, and experimentally studied the effects of these codon substitutions. Using cellular and biochemical approaches we find that at certain locations, slow-to-fast codon substitutions reduce protein expression, increase protein aggregation, and impair protein function.This report provides an approach for identifying functionally relevant regions with slower codons and demonstrates that such codons are important for protein expression and function.

An intrinsically disordered nascent protein interacts with specific regions of the ribosomal surface near the exit tunnel

The influence of the ribosome on nascent chains is poorly understood, especially in the case of proteins devoid of signal or arrest sequences. Here, we provide explicit evidence for the interaction of specific ribosomal proteins with ribosome-bound nascent chains (RNCs). We target RNCs pertaining to the intrinsically disordered protein PIR and a number of mutants bearing a variable net charge. All the constructs analyzed in this work lack N-terminal signal sequences. By a combination chemical crosslinking and Western-blotting, we find that all RNCs interact with ribosomal protein L23 and that longer nascent chains also weakly interact with L29. The interacting proteins are spatially clustered on a specific region of the large ribosomal subunit, close to the exit tunnel. Based on chain-length-dependence and mutational studies, we find that the interactions with L23 persist despite drastic variations in RNC sequence. Importantly, we also find that the interactions are highly Mg+2-concentration-dependent. This work is significant because it unravels a novel role of the ribosome, which is shown to engage with the nascent protein chain even in the absence of signal or arrest sequences.

Protein structure and aggregation: a marriage of necessity ruled by aggregation gatekeepers

Protein aggregation propensity is a pervasive and seemingly inescapable property of proteomes. Strikingly, a significant fraction of the proteome is supersaturated, meaning that, for these proteins, their native conformation is less stable than the aggregated state. Maintaining the integrity of a proteome under such conditions is precarious and requires energy-consuming proteostatic regulation. Why then is aggregation propensity maintained at such high levels over long evolutionary timescales? Here, we argue that the conformational stability of the native and aggregated states are correlated thermodynamically and that codon usage strengthens this correlation. As a result, the folding of stable proteins requires kinetic control to avoid aggregation, provided by aggregation gatekeepers. These unique residues are evolutionarily selected to kinetically favor native folding, either on their own or by coopting chaperones.

How Does the Ribosome Fold the Proteome?

Folding of polypeptides begins during their synthesis on ribosomes. This process has evolved as a means for the cell to maintain proteostasis, by mitigating the risk of protein misfolding and aggregation. The capacity to now depict this cellular feat at increasingly higher resolution is providing insight into the mechanistic determinants that promote successful folding. Emerging from these studies is the intimate interplay between protein translation and folding, and within this the ribosome particle is the key player. Its unique structural properties provide a specialized scaffold against which nascent polypeptides can begin to form structure in a highly coordinated, co-translational manner. Here, we examine how, as a macromolecular machine, the ribosome modulates the intrinsic dynamic properties of emerging nascent polypeptide chains and guides them toward their biologically active structures.

Mechanisms of Cotranslational Protein Maturation in Bacteria

Growing cells invest a significant part of their biosynthetic capacity into the production of proteins. To become functional, newly-synthesized proteins must be N-terminally processed, folded and often translocated to other cellular compartments. A general strategy is to integrate these protein maturation processes with translation, by cotranslationally engaging processing enzymes, chaperones and targeting factors with the nascent polypeptide. Precise coordination of all factors involved is critical for the efficiency and accuracy of protein synthesis and cellular homeostasis. This review provides an overview of the current knowledge on cotranslational protein maturation, with a focus on the production of cytosolic proteins in bacteria. We describe the role of the ribosome and the chaperone network in protein folding and how the dynamic interplay of all cotranslationally acting factors guides the sequence of cotranslational events. Finally, we discuss recent data demonstrating the coupling of protein synthesis with the assembly of protein complexes and end with a brief discussion of outstanding questions and emerging concepts in the field of cotranslational protein maturation.

Avoidance of protein unfolding constrains protein stability in long-term evolution

Every amino acid residue can influence a protein's overall stability, making stability highly susceptible to change throughout evolution. We consider the distribution of protein stabilities evolutionarily permittable under two previously reported protein fitness functions: flux dynamics and misfolding avoidance. We develop an evolutionary dynamics theory and find that it agrees better with an extensive protein stability data set for dihydrofolate reductase orthologs under the misfolding avoidance fitness function rather than the flux dynamics fitness function. Further investigation with ribonuclease H data demonstrates that not any misfolded state is avoided; rather, it is only the unfolded state. At the end, we discuss how our work pertains to the universal protein abundance-evolutionary rate correlation seen across organisms' proteomes. We derive a closed-form expression relating protein abundance to evolutionary rate that captures Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens experimental trends without fitted parameters.

Gene variants of coagulation related proteins that interact with SARS-CoV-2

Thrombosis is a recognized complication of Coronavirus disease of 2019 (COVID-19) and is often associated with poor prognosis. There is a well-recognized link between coagulation and inflammation, however, the extent of thrombotic events associated with COVID-19 warrants further investigation. Poly(A) Binding Protein Cytoplasmic 4 (PABPC4), Serine/Cysteine Proteinase Inhibitor Clade G Member 1 (SERPING1) and Vitamin K epOxide Reductase Complex subunit 1 (VKORC1), which are all proteins linked to coagulation, have been shown to interact with SARS proteins. We computationally examined the interaction of these with SARS-CoV-2 proteins and, in the case of VKORC1, we describe its binding to ORF7a in detail. We examined the occurrence of variants of each of these proteins across populations and interrogated their potential contribution to COVID-19 severity. Potential mechanisms, by which some of these variants may contribute to disease, are proposed. Some of these variants are prevalent in minority groups that are disproportionally affected by severe COVID-19. Therefore, we are proposing that further investigation around these variants may lead to better understanding of disease pathogenesis in minority groups and more informed therapeutic approaches.

Assessing optimal: inequalities in codon optimization algorithms

BACKGROUND

Custom genes have become a common resource in recombinant biology over the last 20 years due to the plummeting cost of DNA synthesis. These genes are often "optimized" to non-native sequences for overexpression in a non-native host by substituting synonymous codons within the coding DNA sequence (CDS). A handful of studies have compared native and optimized CDSs, reporting different levels of soluble product due to the accumulation of misfolded aggregates, variable activity of enzymes, and (at least one report of) a change in substrate specificity. No study, to the best of our knowledge, has performed a practical comparison of CDSs generated from different codon optimization algorithms or reported the corresponding protein yields.

RESULTS

In our efforts to understand what factors constitute an optimized CDS, we identified that there is little consensus among codon-optimization algorithms, a roughly equivalent chance that an algorithm-optimized CDS will increase or diminish recombinant yields as compared to the native DNA, a near ubiquitous use of a codon database that was last updated in 2007, and a high variability of output CDSs by some algorithms. We present a case study, using KRas4B, to demonstrate that a median codon frequency may be a better predictor of soluble yields than the more commonly utilized CAI metric.

CONCLUSIONS

We present a method for visualizing, analyzing, and comparing algorithm-optimized DNA sequences for recombinant protein expression. We encourage researchers to consider if DNA optimization is right for their experiments, and work towards improving the reproducibility of published recombinant work by publishing non-native CDSs.

Modification of Transfer RNA Levels Affects Cyclin Aggregation and the Correct Duplication of Yeast Cells

Codon usage bias (the preferential use of certain synonymous codons (optimal) over others is found at the organism level (intergenomic) within specific genomes (intragenomic) and even in certain genes. Whether it is the result of genetic drift due to GC/AT content and/or natural selection is a topic of intense debate. Preferential codons are mostly found in genes encoding highly-expressed proteins, while lowly-expressed proteins usually contain a high proportion of rare (lowly-represented) codons. While optimal codons are decoded by highly expressed tRNAs, rare codons are usually decoded by lowly-represented tRNAs. Whether rare codons play a role in controlling the expression of lowly- or temporarily-expressed proteins is an open question. In this work we approached this question using two strategies, either by replacing rare glycine codons with optimal counterparts in the gene that encodes the cell cycle protein Cdc13, or by overexpression the tRNA ^Gly that decodes rare codons from the fission yeast, Schizosaccharomyces pombe. While the replacement of synonymous codons severely affected cell growth, increasing tRNA levels affected the aggregation status of Cdc13 and cell division. These lead us to think that rare codons in lowly-expressed cyclin proteins are crucial for cell division, and that the overexpression of tRNA that decodes rare codons affects the expression of proteins containing these rare codons. These codons may be the result of the natural selection of codons in genes that encode lowly-expressed proteins.

Ribosome occupancy profiles are conserved between structurally and evolutionarily related yeast domains

Motivation

Protein synthesis is a non-equilibrium process, meaning that the speed of translation can influence the ability of proteins to fold and function. Assuming that structurally similar proteins fold by similar pathways, the profile of translation speed along an mRNA should be evolutionarily conserved between related proteins to direct correct folding and downstream function. The only evidence to date for such conservation of translation speed between homologous proteins has used codon rarity as a proxy for translation speed. There are, however, many other factors including mRNA structure and the chemistry of the amino acids in the A- and P-sites of the ribosome that influence the speed of amino acid addition.

Results

Ribosome profiling experiments provide a signal directly proportional to the underlying translation times at the level of individual codons. We compared ribosome occupancy profiles (extracted from five different large-scale yeast ribosome profiling studies) between related protein domains to more directly test if their translation schedule was conserved. Our analysis reveals that the ribosome occupancy profiles of paralogous domains tend to be significantly more similar to one another than to profiles of non-paralogous domains. This trend does not depend on domain length, structural classes, amino acid composition or sequence similarity. Our results indicate that entire ribosome occupancy profiles and not just rare codon locations are conserved between even distantly related domains in yeast, providing support for the hypothesis that translation schedule is conserved between structurally related domains to retain folding pathways and facilitate efficient folding.

Availability and implementation

Python3 code is available on GitHub at https://github.com/DanNissley/Compare-ribosome-occupancy.

Supplementary information

Supplementary data are available at Bioinformatics online.

Synonymous but Not Silent: The Codon Usage Code for Gene Expression and Protein Folding

Codon usage bias, the preference for certain synonymous codons, is found in all genomes. Although synonymous mutations were previously thought to be silent, a large body of evidence has demonstrated that codon usage can play major roles in determining gene expression levels and protein structures. Codon usage influences translation elongation speed and regulates translation efficiency and accuracy. Adaptation of codon usage to tRNA expression determines the proteome landscape. In addition, codon usage biases result in nonuniform ribosome decoding rates on mRNAs, which in turn influence the cotranslational protein folding process that is critical for protein function in diverse biological processes. Conserved genome-wide correlations have also been found between codon usage and protein structures. Furthermore, codon usage is a major determinant of mRNA levels through translation-dependent effects on mRNA decay and translation-independent effects on transcriptional and posttranscriptional processes. Here, we discuss the multifaceted roles and mechanisms of codon usage in different gene regulatory processes.

Translational Control by Ribosome Pausing in Bacteria: How a Non-uniform Pace of Translation Affects Protein Production and Folding

Protein homeostasis of bacterial cells is maintained by coordinated processes of protein production, folding, and degradation. Translational efficiency of a given mRNA depends on how often the ribosomes initiate synthesis of a new polypeptide and how quickly they read the coding sequence to produce a full-length protein. The pace of ribosomes along the mRNA is not uniform: periods of rapid synthesis are separated by pauses. Here, we summarize recent evidence on how ribosome pausing affects translational efficiency and protein folding. We discuss the factors that slow down translation elongation and affect the quality of the newly synthesized protein. Ribosome pausing emerges as important factor contributing to the regulatory programs that ensure the quality of the proteome and integrate the cellular and environmental cues into regulatory circuits of the cell.

Expression of transgenes enriched in rare codons is enhanced by the MAPK pathway

The ability to translate three nucleotide sequences, or codons, into amino acids to form proteins is conserved across all organisms. All but two amino acids have multiple codons, and the frequency that such synonymous codons occur in genomes ranges from rare to common. Transcripts enriched in rare codons are typically associated with poor translation, but in certain settings can be robustly expressed, suggestive of codon-dependent regulation. Given this, we screened a gain-of-function library for human genes that increase the expression of a GFP^rare reporter encoded by rare codons. This screen identified multiple components of the mitogen activated protein kinase (MAPK) pathway enhancing GFP^rare expression. This effect was reversed with inhibitors of this pathway and confirmed to be both codon-dependent and occur with ectopic transcripts naturally coded with rare codons. Finally, this effect was associated, at least in part, with enhanced translation. We thus identify a potential regulatory module that takes advantage of the redundancy in the genetic code to modulate protein expression.

Network analysis of synonymous codon usage

MOTIVATION

Most amino acids are encoded by multiple synonymous codons, some of which are used more rarely than others. Analyses of positions of such rare codons in protein sequences revealed that rare codons can impact co-translational protein folding and that positions of some rare codons are evolutionarily conserved. Analyses of their positions in protein 3-dimensional structures, which are richer in biochemical information than sequences alone, might further explain the role of rare codons in protein folding.

RESULTS

We model protein structures as networks and use network centrality to measure the structural position of an amino acid. We first validate that amino acids buried within the structural core are network-central, and those on the surface are not. Then, we study potential differences between network centralities and thus structural positions of amino acids encoded by conserved rare, non-conserved rare and commonly used codons. We find that in 84% of proteins, the three codon categories occupy significantly different structural positions. We examine protein groups showing different codon centrality trends, i.e. different relationships between structural positions of the three codon categories. We see several cases of all proteins from our data with some structural or functional property being in the same group. Also, we see a case of all proteins in some group having the same property. Our work shows that codon usage is linked to the final protein structure and thus possibly to co-translational protein folding.

AVAILABILITY AND IMPLEMENTATION

https://nd.edu/∼cone/CodonUsage/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Validation of DBFOLD: An efficient algorithm for computing folding pathways of complex proteins

Atomistic simulations can provide valuable, experimentally-verifiable insights into protein folding mechanisms, but existing ab initio simulation methods are restricted to only the smallest proteins due to severe computational speed limits. The folding of larger proteins has been studied using native-centric potential functions, but such models omit the potentially crucial role of non-native interactions. Here, we present an algorithm, entitled DBFOLD, which can predict folding pathways for a wide range of proteins while accounting for the effects of non-native contacts. In addition, DBFOLD can predict the relative rates of different transitions within a protein’s folding pathway. To accomplish this, rather than directly simulating folding, our method combines equilibrium Monte-Carlo simulations, which deploy enhanced sampling, with unfolding simulations at high temperatures. We show that under certain conditions, trajectories from these two types of simulations can be jointly analyzed to compute unknown folding rates from detailed balance. This requires inferring free energies from the equilibrium simulations, and extrapolating transition rates from the unfolding simulations to lower, physiologically-reasonable temperatures at which the native state is marginally stable. As a proof of principle, we show that our method can accurately predict folding pathways and Monte-Carlo rates for the well-characterized Streptococcal protein G. We then show that our method significantly reduces the amount of computation time required to compute the folding pathways of large, misfolding-prone proteins that lie beyond the reach of existing direct simulation. Our algorithm, which is available online, can generate detailed atomistic models of protein folding mechanisms while shedding light on the role of non-native intermediates which may crucially affect organismal fitness and are frequently implicated in disease.

Many proteins must adopt a specific structure in order to function. Computational simulations have been used to shed light on the mechanisms of protein folding, but unfortunately, realistic simulations can typically only be run for small proteins, due to severe limits in computational speed. Here, we present a method to solve this problem, whereby instead of directly simulating folding from an unfolded state, we run simulations that allow for computation of equilibrium folding free energies, alongside high temperature simulations to compute unfolding rates. From these quantities, folding rates can be computed using detailed balance. Importantly, our method can account for the effects of nonnative contacts which transiently form during folding and must be broken prior to adoption of the native state. Such contacts, which are often excluded from simple models of folding, may crucially affect real protein folding pathways and are often observed in folding intermediates implicated in disease.

Potential impact on coagulopathy of gene variants of coagulation related proteins that interact with SARS-CoV-2

Thrombosis has been one of the complications of the Coronavirus disease of 2019 (COVID-19), often associated with poor prognosis. There is a well-recognized link between coagulation and inflammation, however, the extent of thrombotic events associated with COVID-19 warrants further investigation. Poly(A) Binding Protein Cytoplasmic 4 (PABPC4), Serine/Cysteine Proteinase Inhibitor Clade G Member 1 (SERPING1) and Vitamin K epOxide Reductase Complex subunit 1 (VKORC1), which are all proteins linked to coagulation, have been shown to interact with SARS proteins. We computationally examined the interaction of these with SARS-CoV-2 proteins and, in the case of VKORC1, we describe its binding to ORF7a in detail. We examined the occurrence of variants of each of these proteins across populations and interrogated their potential contribution to COVID-19 severity. Potential mechanisms by which some of these variants may contribute to disease are proposed. Some of these variants are prevalent in minority groups that are disproportionally affected by severe COVID-19. Therefore, we are proposing that further investigation around these variants may lead to better understanding of disease pathogenesis in minority groups and more informed therapeutic approaches.

Author summary

Increased blood clotting, especially in the lungs, is a common complication of COVID-19. Infectious diseases cause inflammation which in turn can contribute to increased blood clotting. However, the extent of clot formation that is seen in the lungs of COVID-19 patients suggests that there may be a more direct link. We identified three human proteins that are involved indirectly in the blood clotting cascade and have been shown to interact with proteins of SARS virus, which is closely related to the novel coronavirus. We examined computationally the interaction of these human proteins with the viral proteins. We looked for genetic variants of these proteins and examined how these variants are distributed across populations. We investigated whether variants of these genes could impact severity of COVID-19. Further investigation around these variants may provide clues for the pathogenesis of COVID-19 particularly in minority groups.

Effect of Protein Structure on Evolution of Cotranslational Folding

Cotranslational folding depends on the folding speed and stability of the nascent protein. It remains difficult, however, to predict which proteins cotranslationally fold. Here, we simulate evolution of model proteins to investigate how native structure influences evolution of cotranslational folding. We developed a model that connects protein folding during and after translation to cellular fitness. Model proteins evolved improved folding speed and stability, with proteins adopting one of two strategies for folding quickly. Low contact order proteins evolve to fold cotranslationally. Such proteins adopt native conformations early on during the translation process, with each subsequently translated residue establishing additional native contacts. On the other hand, high contact order proteins tend not to be stable in their native conformations until the full chain is nearly extruded. We also simulated evolution of slowly translating codons, finding that slower translation speeds at certain positions enhances cotranslational folding. Finally, we investigated real protein structures using a previously published data set that identified evolutionarily conserved rare codons in Escherichia coli genes and associated such codons with cotranslational folding intermediates. We found that protein substructures preceding conserved rare codons tend to have lower contact orders, in line with our finding that lower contact order proteins are more likely to fold cotranslationally. Our work shows how evolutionary selection pressure can cause proteins with local contact topologies to evolve cotranslational folding.

Observing the nonvectorial yet cotranslational folding of a multidomain protein, LDL receptor, in the ER of mammalian cells

Proteins have evolved by incorporating several structural units within a single polypeptide. As a result, multidomain proteins constitute a large fraction of all proteomes. Their domains often fold to their native structures individually and vectorially as each domain emerges from the ribosome or the protein translocation channel, leading to the decreased risk of interdomain misfolding. However, some multidomain proteins fold in the endoplasmic reticulum (ER) nonvectorially via intermediates with nonnative disulfide bonds, which were believed to be shuffled to native ones slowly after synthesis. Yet, the mechanism by which they fold nonvectorially remains unclear. Using two-dimensional (2D) gel electrophoresis and a conformation-specific antibody that recognizes a correctly folded domain, we show here that shuffling of nonnative disulfide bonds to native ones in the most N-terminal region of LDL receptor (LDLR) started at a specific timing during synthesis. Deletion analysis identified a region on LDLR that assisted with disulfide shuffling in the upstream domain, thereby promoting its cotranslational folding. Thus, a plasma membrane-bound multidomain protein has evolved a sequence that promotes the nonvectorial folding of its upstream domains. These findings demonstrate that nonvectorial folding of a multidomain protein in the ER of mammalian cells is more coordinated and elaborated than previously thought. Thus, our findings alter our current view of how a multidomain protein folds nonvectorially in the ER of living cells.

Analysis of computational codon usage models and their association with translationally slow codons

Improved computational modeling of protein translation rates, including better prediction of where translational slowdowns along an mRNA sequence may occur, is critical for understanding co-translational folding. Because codons within a synonymous codon group are translated at different rates, many computational translation models rely on analyzing synonymous codons. Some models rely on genome-wide codon usage bias (CUB), believing that globally rare and common codons are the most informative of slow and fast translation, respectively. Others use the CUB observed only in highly expressed genes, which should be under selective pressure to be translated efficiently (and whose CUB may therefore be more indicative of translation rates). No prior work has analyzed these models for their ability to predict translational slowdowns. Here, we evaluate five models for their association with slowly translated positions as denoted by two independent ribosome footprint (RFP) count experiments from S. cerevisiae, because RFP data is often considered as a “ground truth” for translation rates across mRNA sequences. We show that all five considered models strongly associate with the RFP data and therefore have potential for estimating translational slowdowns. However, we also show that there is a weak correlation between RFP counts for the same genes originating from independent experiments, even when their experimental conditions are similar. This raises concerns about the efficacy of using current RFP experimental data for estimating translation rates and highlights a potential advantage of using computational models to understand translation rates instead.

Synonymous codon substitutions perturb cotranslational protein folding in vivo and impair cell fitness

In the cell, proteins are synthesized from N to C terminus and begin to fold during translation. Cotranslational folding mechanisms are therefore linked to elongation rate, which varies as a function of synonymous codon usage. However, synonymous codon substitutions can affect many distinct cellular processes, which has complicated attempts to deconvolve the extent to which synonymous codon usage can promote or frustrate proper protein folding in vivo. Although previous studies have shown that some synonymous changes can lead to different final structures, other substitutions will likely be more subtle, perturbing predominantly the protein folding pathway without radically altering the final structure. Here we show that synonymous codon substitutions encoding a single essential enzyme lead to dramatically slower cell growth. These mutations do not prevent active enzyme formation; instead, they predominantly alter the protein folding mechanism, leading to enhanced degradation in vivo. These results support a model in which synonymous codon substitutions can impair cell fitness by significantly perturbing cotranslational protein folding mechanisms, despite the chaperoning provided by the cellular protein homeostasis network.

Cotranslational folding allows misfolding-prone proteins to circumvent deep kinetic traps

Many large proteins suffer from slow or inefficient folding in vitro. It has long been known that this problem can be alleviated in vivo if proteins start folding cotranslationally. However, the molecular mechanisms underlying this improvement have not been well established. To address this question, we use an all-atom simulation-based algorithm to compute the folding properties of various large protein domains as a function of nascent chain length. We find that for certain proteins, there exists a narrow window of lengths that confers both thermodynamic stability and fast folding kinetics. Beyond these lengths, folding is drastically slowed by nonnative interactions involving C-terminal residues. Thus, cotranslational folding is predicted to be beneficial because it allows proteins to take advantage of this optimal window of lengths and thus avoid kinetic traps. Interestingly, many of these proteins' sequences contain conserved rare codons that may slow down synthesis at this optimal window, suggesting that synthesis rates may be evolutionarily tuned to optimize folding. Using kinetic modeling, we show that under certain conditions, such a slowdown indeed improves cotranslational folding efficiency by giving these nascent chains more time to fold. In contrast, other proteins are predicted not to benefit from cotranslational folding due to a lack of significant nonnative interactions, and indeed these proteins' sequences lack conserved C-terminal rare codons. Together, these results shed light on the factors that promote proper protein folding in the cell and how biomolecular self-assembly may be optimized evolutionarily.

Successes and challenges in simulating the folding of large proteins

Computational simulations of protein folding can be used to interpret experimental folding results, to design new folding experiments, and to test the effects of mutations and small molecules on folding. However, whereas major experimental and computational progress has been made in understanding how small proteins fold, research on larger, multidomain proteins, which comprise the majority of proteins, is less advanced. Specifically, large proteins often fold via long-lived partially folded intermediates, whose structures, potentially toxic oligomerization, and interactions with cellular chaperones remain poorly understood. Molecular dynamics based folding simulations that rely on knowledge of the native structure can provide critical, detailed information on folding free energy landscapes, intermediates, and pathways. Further, increases in computational power and methodological advances have made folding simulations of large proteins practical and valuable. Here, using serpins that inhibit proteases as an example, we review native-centric methods for simulating the folding of large proteins. These synergistic approaches range from Gō and related structure-based models that can predict the effects of the native structure on folding to all-atom-based methods that include side-chain chemistry and can predict how disease-associated mutations may impact folding. The application of these computational approaches to serpins and other large proteins highlights the successes and limitations of current computational methods and underscores how computational results can be used to inform experiments. These powerful simulation approaches in combination with experiments can provide unique insights into how large proteins fold and misfold, expanding our ability to predict and manipulate protein folding.

Codon harmonization reduces amino acid misincorporation in bacterially expressed P. falciparum proteins and improves their immunogenicity

Codon usage frequency influences protein structure and function. The frequency with which codons are used potentially impacts primary, secondary and tertiary protein structure. Poor expression, loss of function, insolubility, or truncation can result from species-specific differences in codon usage. “Codon harmonization” more closely aligns native codon usage frequencies with those of the expression host particularly within putative inter-domain segments where slower rates of translation may play a role in protein folding. Heterologous expression of Plasmodium falciparum genes in Escherichia coli has been a challenge due to their AT-rich codon bias and the highly repetitive DNA sequences. Here, codon harmonization was applied to the malarial antigen, CelTOS (Cell-traversal protein for ookinetes and sporozoites). CelTOS is a highly conserved P. falciparum protein involved in cellular traversal through mosquito and vertebrate host cells. It reversibly refolds after thermal denaturation making it a desirable malarial vaccine candidate. Protein expressed in E. coli from a codon harmonized sequence of P. falciparum CelTOS (CH-PfCelTOS) was compared with protein expressed from the native codon sequence (N-PfCelTOS) to assess the impact of codon usage on protein expression levels, solubility, yield, stability, structural integrity, recognition with CelTOS-specific mAbs and immunogenicity in mice. While the translated proteins were expected to be identical, the translated products produced from the codon-harmonized sequence differed in helical content and showed a smaller distribution of polypeptides in mass spectra indicating lower heterogeneity of the codon harmonized version and fewer amino acid misincorporations. Substitutions of hydrophobic-to-hydrophobic amino acid were observed more commonly than any other. CH-PfCelTOS induced significantly higher antibody levels compared with N-PfCelTOS; however, no significant differences in either IFN-γ or IL-4 cellular responses were detected between the two antigens.

Protein Melting Temperature Cannot Fully Assess Whether Protein Folding Free Energy Underlies the Universal Abundance-Evolutionary Rate Correlation Seen in Proteins

The protein misfolding avoidance hypothesis explains the universal negative correlation between protein abundance and sequence evolutionary rate across the proteome by identifying protein folding free energy (ΔG) as the confounding variable. Abundant proteins resist toxic misfolding events by being more stable, and more stable proteins evolve slower because their mutations are more destabilizing. Direct supporting evidence consists only of computer simulations. A study taking advantage of a recent experimental breakthrough in measuring protein stability proteome-wide through melting temperature (Tm) (Leuenberger et al. 2017), found weak misfolding avoidance hypothesis support for the Escherichia coli proteome, and no support for the Saccharomyces cerevisiae, Homo sapiens, and Thermus thermophilus proteomes (Plata and Vitkup 2018). I find that the nontrivial relationship between Tm and ΔG and inaccuracy in Tm measurements by Leuenberger et al. 2017 can be responsible for not observing strong positive abundance-Tm and strong negative Tm-evolutionary rate correlations.

Conservation of location of several specific inhibitory codon pairs in the Saccharomyces sensu stricto yeasts reveals translational selection

Synonymous codons provide redundancy in the genetic code that influences translation rates in many organisms, in which overall codon use is driven by selection for optimal codons. It is unresolved if or to what extent translational selection drives use of suboptimal codons or codon pairs. In Saccharomyces cerevisiae, 17 specific inhibitory codon pairs, each comprised of adjacent suboptimal codons, inhibit translation efficiency in a manner distinct from their constituent codons, and many are translated slowly in native genes. We show here that selection operates within Saccharomyces sensu stricto yeasts to conserve nine of these codon pairs at defined positions in genes. Conservation of these inhibitory codon pairs is significantly greater than expected, relative to conservation of their constituent codons, with seven pairs more highly conserved than any other synonymous pair. Conservation is strongly correlated with slow translation of the pairs. Conservation of suboptimal codon pairs extends to two related Candida species, fungi that diverged from Saccharomyces ∼270 million years ago, with an enrichment for codons decoded by I•A and U•G wobble in both Candida and Saccharomyces. Thus, conservation of inhibitory codon pairs strongly implies selection for slow translation at particular gene locations, executed by suboptimal codon pairs.

Nature and Regulation of Protein Folding on the Ribosome

Co-translational protein folding is an essential process by which cells ensure the safe and efficient production and assembly of new proteins in their functional native states following biosynthesis on the ribosome. In this review, we describe recent progress in probing the changes during protein synthesis of the free energy landscapes that underlie co-translational folding and discuss the critical coupling between these landscapes and the rate of translation that ultimately determines the success or otherwise of the folding process. Recent developments have revealed a variety of mechanisms by which both folding and translation can be modulated or regulated, and we discuss how these effects are utilised by the cell to optimise the outcome of protein biosynthesis.

Mechanisms of Cotranslational Maturation of Newly Synthesized Proteins

The timely production of functional proteins is of critical importance for the biological activity of cells. To reach the functional state, newly synthesized polypeptides have to become enzymatically processed, folded, and assembled into oligomeric complexes and, for noncytosolic proteins, translocated across membranes. Key activities of these processes occur cotranslationally, assisted by a network of machineries that transiently engage nascent polypeptides at distinct phases of translation. The sequence of events is tuned by intrinsic features of the nascent polypeptides and timely association of factors with the translating ribosome. Considering the dynamics of translation, the heterogeneity of cellular proteins, and the diversity of interaction partners, it is a major cellular achievement that these processes are temporally and spatially so precisely coordinated, minimizing the generation of damaged proteins. This review summarizes the current progress we have made toward a comprehensive understanding of the cotranslational interactions of nascent chains, which pave the way to their functional state.

Within-Gene Shine-Dalgarno Sequences Are Not Selected for Function

The Shine-Dalgarno (SD) sequence motif facilitates translation initiation and is frequently found upstream of bacterial start codons. However, thousands of instances of this motif occur throughout the middle of protein coding genes in a typical bacterial genome. Here, we use comparative evolutionary analysis to test whether SD sequences located within genes are functionally constrained. We measure the conservation of SD sequences across Enterobacteriales, and find that they are significantly less conserved than expected. Further, the strongest SD sequences are the least conserved whereas we find evidence of conservation for the weakest possible SD sequences given amino acid constraints. Our findings indicate that most SD sequences within genes are likely to be deleterious and removed via selection. To illustrate the origin of these deleterious costs, we show that ATG start codons are significantly depleted downstream of SD sequences within genes, highlighting the constraint that these sequences impose on the surrounding nucleotides to minimize the potential for erroneous translation initiation.