Codon Choice Research Articles

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

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

A Suite of Foundation Models Captures the Contextual Interplay Between Codons.

In the canonical genetic code, many amino acids are assigned more than one codon. Work by us and others has shown that the choice of these synonymous codon is not random, and carries regulatory and functional consequences. Existing protein foundation models ignore this context-dependent role of coding sequence in shaping the protein landscape of the cell. To address this gap, we introduce cdsFM, a suite of codon-resolution large language models, including both EnCodon and DeCodon models, with up to 1B parameters. Pre-trained on 60 million protein-coding sequences from more than 5,000 species, our models effectively learn the relationship between codons and amino acids, recapitualing the overall structure of the genetic code. In addition to outperforming state-of-the-art genomic foundation models in a variety of zero-shot and few-shot learning tasks, the larger pre-trained models were superior in predicting the choice of synonymous codons. To systematically assess the impact of synonymous codon choices on protein expression and our models' ability to capture these effects, we generated a large dataset measuring overall and surface expression levels of three proteins as a function of changes in their synonymous codons. We showed that our EnCodon models could be readily fine-tuned to predict the contextual consequences of synonymous codon choices. Armed with this knowledge, we applied EnCodon to existing clinical datasets of synonymous variants, and we identified a large number of synonymous codons that are likely pathogenic, several of which we experimentally confirmed in a cell-based model. Together, our findings establish the cdsFM suite as a powerful tool for decoding the complex functional grammar underlying the choice of synonymous codons.

Dengue virus preferentially uses human and mosquito non-optimal codons

Codon optimality refers to the effect that codon composition has on messenger RNA (mRNA) stability and translation level and implies that synonymous codons are not silent from a regulatory point of view. Here, we investigated the adaptation of virus genomes to the host optimality code using mosquito-borne dengue virus (DENV) as a model. We demonstrated that codon optimality exists in mosquito cells and showed that DENV preferentially uses nonoptimal (destabilizing) codons and avoids codons that are defined as optimal (stabilizing) in either human or mosquito cells. Human genes enriched in the codons preferentially and frequently used by DENV are upregulated during infection, and so is the tRNA decoding the nonoptimal and DENV preferentially used codon for arginine. We found that adaptation during single-host passaging in human or mosquito cells results in the selection of synonymous mutations towards DENV’s preferred nonoptimal codons that increase virus fitness. Finally, our analyses revealed that hundreds of viruses preferentially use nonoptimal codons, with those infecting a single host displaying an even stronger bias, suggesting that host–pathogen interaction shapes virus-synonymous codon choice.

Synthetic genomes unveil the effects of synonymous recoding.

Engineering the genetic code of an organism provides the basis for (i) making any organism safely resistant to natural viruses and (ii) preventing genetic information flow into and out of genetically modified organisms while (iii) allowing the biosynthesis of genetically encoded unnatural polymers1-4. Achieving these three goals requires the reassignment of multiple of the 64 codons nature uses to encode proteins. However, synonymous codon replacement-recoding-is frequently lethal, and how recoding impacts fitness remains poorly explored. Here, we explore these effects using whole-genome synthesis, multiplexed directed evolution, and genome-transcriptome-translatome-proteome co-profiling on multiple recoded genomes. Using this information, we assemble a synthetic Escherichia coli genome in seven sections using only 57 codons to encode proteins. By discovering the rules responsible for the lethality of synonymous recoding and developing a data-driven multi-omics-based genome construction workflow that troubleshoots synthetic genomes, we overcome the lethal effects of 62,007 synonymous codon swaps and 11,108 additional genomic edits. We show that synonymous recoding induces transcriptional noise including new antisense RNAs, leading to drastic transcriptome and proteome perturbation. As the elimination of select codons from an organism's genetic code results in the widespread appearance of cryptic promoters, we show that synonymous codon choice may naturally evolve to minimize transcriptional noise. Our work provides the first genome-scale description of how synonymous codon changes influence organismal fitness and paves the way for the construction of functional genomes that provide genetic firewalls from natural ecosystems and safely produce biopolymers, drugs, and enzymes with an expanded chemistry.

A new mRNA structure prediction based approach to identifying improved signal peptides for bone morphogenetic protein 2

BackgroundSignal peptide (SP) engineering has proven able to improve production of many proteins yet is a laborious process that still relies on trial and error. mRNA structure around the translational start site is important in translation initiation and has rarely been considered in this context, with recent improvements in in silico mRNA structure potentially rendering it a useful predictive tool for SP selection. Here we attempt to create a method to systematically screen candidate signal peptide sequences in silico based on both their nucleotide and amino acid sequences. Several recently released computational tools were used to predict signal peptide activity (SignalP), localization target (DeepLoc) and predicted mRNA structure (MXFold2). The method was tested with Bone Morphogenetic Protein 2 (BMP2), an osteogenic growth factor used clinically for bone regeneration. It was hoped more effective BMP2 SPs could improve BMP2-based gene therapies and reduce the cost of recombinant BMP2 production.ResultsAmino acid sequence analysis indicated 2,611 SPs from the TGF-β superfamily were predicted to function when attached to BMP2. mRNA structure prediction indicated structures at the translational start site were likely highly variable. The five sequences with the most accessible translational start sites, a codon optimized BMP2 SP variant and the well-established hIL2 SP sequence were taken forward to in vitro testing. The top five candidates showed non-significant improvements in BMP2 secretion in HEK293T cells. All showed reductions in secretion versus the native sequence in C2C12 cells, with several showing large and significant decreases. None of the tested sequences were able to increase alkaline phosphatase activity above background in C2C12s. The codon optimized control sequence and hIL2 SP showed reasonable activity in HEK293T but very poor activity in C2C12.ConclusionsThese results support the use of peptide sequence based in silico tools for basic predictions around signal peptide activity in a synthetic biology context. However, mRNA structure prediction requires improvement before it can produce reliable predictions for this application. The poor activity of the codon optimized BMP2 SP variant in C2C12 emphasizes the importance of codon choice, mRNA structure, and cellular context for SP activity.

Specific codons control cellular resources and fitness.

As cellular engineering progresses from simply overexpressing proteins to imparting complex phenotypes through multigene expression, judicious appropriation of cellular resources is essential. Since codon use is degenerate and biased, codons may control cellular resources at a translational level. We investigate how partitioning transfer RNA (tRNA) resources by incorporating dissimilar codon usage can drastically alter interdependence of expression level and burden on the host. By isolating the effect of individual codons' use during translation elongation while eliminating confounding factors, we show that codon choice can trans-regulate fitness of the host and expression of other heterologous or native genes. We correlate specific codon usage patterns with host fitness and derive a coding scheme for multigene expression called the Codon Health Index (CHI, χ). This empirically derived coding scheme (χ) enables the design of multigene expression systems that avoid catastrophic cellular burden and is robust across several proteins and conditions.

The role of transcript regions and amino acid choice in nucleosome positioning.

Eukaryotic DNA is organized and compacted in a string of nucleosomes, DNA-wrapped protein cylinders. The positions of nucleosomes along DNA are not random but show well-known base pair sequence preferences that result from the sequence-dependent elastic and geometric properties of the DNA double helix. Here, we focus on DNA around transcription start sites, which are known to typically attract nucleosomes in multicellular life forms through their high GC content. We aim to understand how these GC signals, as observed in genome-wide averages, are produced and encoded through different genomic regions (mainly 5' UTRs, coding exons, and introns). Our study uses a bioinformatics approach to decompose the genome-wide GC signal into between-region and within-region signals. We find large differences in GC signal contributions between vertebrates and plants and, remarkably, even between closely related species. Introns contribute most to the GC signal in vertebrates, while in plants the exons dominate. Further, we find signal strengths stronger on DNA than on mRNA, suggesting a biological function of GC signals along the DNA itself, as is the case for nucleosome positioning. Finally, we make the surprising discovery that both the choice of synonymous codons and amino acids contribute to the nucleosome positioning signal.

Codon usage behavior distinguishes pathogenic Clostridium species from the non-pathogenic species

Genus Clostridium is of the largest genus in class Clostridia. It is comprised of spore-forming, anaerobic, gram-positive organisms. The members of this genus include human pathogens to free-living nitrogen fixing bacteria. In the present study, we have performed a comparison of the choice of preferred codons, codon usage patterns, dinucleotide and amino acid usage pattern of 76 species of Genus Clostridium. We found the pathogenic clostridium species to have smaller AT-rich genomes as compared to opportunistic and non-pathogenic clostridium species. The choice of preferred and optimal codons was also influenced by genomic GC/AT content of the respective clostridium species. The pathogenic clostridium species displayed a strict bias in the codon usage, employing 35 of the 61 codons encoding for 20 amino acids. Comparison of amino acid usage revealed an increased usage of amino acids with lower biosynthetic cost by pathogenic clostridium species as compared to opportunistic and non-pathogenic clostridium species. Smaller genome, strict codon usage bias and amino acid usage lead to lower protein energetic cost for the clostridial pathogens. Overall, we found the pathogenic members of genus Clostridium to prefer small, AT-rich codons to reduce biosynthetic costs and match the cellular environment of its AT-rich human host.

Determinants of associations between codon and amino acid usage patterns of microbial communities and the environment inferred based on a cross-biome metagenomic analysis

Codon and amino acid usage were associated with almost every aspect of microbial life. However, how the environment may impact the codon and amino acid choice of microbial communities at the habitat level is not clearly understood. Therefore, in this study, we analyzed codon and amino acid usage patterns of a large number of environmental samples collected from diverse ecological niches. Our results suggested that samples derived from similar environmental niches, in general, show overall similar codon and amino acid distribution as compared to samples from other habitats. To substantiate the relative impact of the environment, we considered several factors, such as their similarity in GC content, or in functional or taxonomic abundance. Our analysis demonstrated that none of these factors can fully explain the trends that we observed at the codon or amino acid level implying a direct environmental influence on them. Further, our analysis demonstrated different levels of selection on codon bias in different microbial communities with the highest bias in host-associated environments such as the digestive system or oral samples and the lowest level of selection in soil and water samples. Considering a large number of metagenomic samples here we showed that microorganisms collected from similar environmental backgrounds exhibit similar patterns of codon and amino acid usage irrespective of the location or time from where the samples were collected. Thus our study suggested a direct impact of the environment on codon and amino usage of microorganisms that cannot be explained considering the influence of other factors.

Oxidative stress strongly restricts the effect of codon choice on the efficiency of protein synthesis in Escherichia coli.

The response of enterobacteria to oxidative stress is usually considered to be regulated by transcription factors such as OxyR and SoxR. Nevertheless, several reports have shown that under oxidative stress the levels, modification and aminoacylation of tRNAs may be altered suggesting a role of codon bias in regulation of gene expression under this condition. In order to characterize the effects of oxidative stress on translation elongation we constructed a library of 61 plasmids, each coding for the green fluorescent protein (GFP) translationally fused to a different set of four identical codons. Using these reporters, we observed that GFP production levels vary widely (~15 fold) when Escherichia coli K-12 is cultured in minimal media as a consequence of codon choice variations. When bacteria are cultured under oxidative stress caused by paraquat the levels of GFP produced by most clones is reduced and, in contrast to control conditions, the range of GFP levels is restricted to a ~2 fold range. Restricting elongation of particular sequences does not increase the range of GFP production under oxidative stress, but altering translation initiation rates leads to an increase in this range. Altogether, our results suggest that under normal conditions the speed of translation elongation is in the range of the speed of initiation and, consequently, codon choice impacts the speed of protein synthesis. In contrast, under oxidative stress translation initiation becomes much slower than elongation, limiting the speed of translation such that codon choice has at most only subtle effects on the overall output of translation.

An investigation of codon usage pattern analysis in pancreatitis associated genes

BackgroundPancreatitis is an inflammatory disorder resulting from the autoactivation of trypsinogen in the pancreas. The genetic basis of the disease is an old phenomenon, and evidence is accumulating for the involvement of synonymous/non-synonymous codon variants in disease initiation and progression.ResultsThe present study envisaged a panel of 26 genes involved in pancreatitis for their codon choices, compositional analysis, relative dinucleotide frequency, nucleotide disproportion, protein physical properties, gene expression, codon bias, and interrelated of all these factors. In this set of genes, gene length was positively correlated with nucleotide skews and codon usage bias. Codon usage of any gene is dependent upon its AT and GC component; however, AGG, CGT, and CGA encoding for Arg, TCG for Ser, GTC for Val, and CCA for Pro were independent of nucleotide compositions. In addition, Codon GTC showed a correlation with protein properties, isoelectric point, instability index, and frequency of basic amino acids. We also investigated the effect of various evolutionary forces in shaping the codon usage choices of genes.ConclusionsThis study will enable us to gain insight into the molecular signatures associated with the disease that might help identify more potential genes contributing to enhanced risk for pancreatitis. All the genes associated with pancreatitis are generally associated with physiological function, and mutations causing loss of function, over or under expression leads to an ailment. Therefore, the present study attempts to envisage the molecular signature in a group of genes that lead to pancreatitis in case of malfunction.

Synthetic refactor of essential genes decodes functionally constrained sequences in yeast genome

SummaryThe relationship between gene sequence and function matters for fundamental and practical reasons. Here, yeast essential genes were systematically refactored to identify invariable sequences in the coding and regulatory regions. The coding sequences were synonymously recoded with all optimal codons to explore the importance of codon choice. The promoters and terminators were swapped with well-characterized CYC1 promoter and terminator to examine whether a specialized expression is required for the function of a specific gene. Among the 10 essential genes from Chr.XIIL, this scheme successfully generated 7 refactored genes that can effectively support wild-type-like fitness under various conditions, thereby revealing amazing sequence plasticity of yeast genes. Moreover, different invariable elements were identified from the remaining 3 genes, exampling the logics for genetic information encoding and regulation. Further refactoring of all essential genes using this strategy will generate comprehensive understanding of gene sequence choice, thereby guiding its design in various applications.

Codon Usage Bias Correlates With Gene Length in Neurodegeneration Associated Genes.

Codon usage analysis is a crucial part of molecular characterization and is used to determine the factors affecting the evolution of a gene. The length of a gene is an important parameter that affects the characteristics of the gene, such as codon usage, compositional parameters, and sometimes, its functions. In the present study, we investigated the association of various parameters related to codon usage with the length of genes. Gene expression is affected by nucleotide disproportion. In sixty genes related to neurodegenerative disorders, the G nucleotide was the most abundant and the T nucleotide was the least. The nucleotide T exhibited a significant association with the length of the gene at both the overall compositional level and the first and second codon positions. Codon usage bias (CUB) of these genes was affected by pyrimidine and keto skews. Gene length was found to be significantly correlated with codon bias in neurodegeneration associated genes. In gene segments with lengths below 1,200 bp and above 2,400 bp, CUB was positively associated with length. Relative synonymous CUB, which is another measure of CUB, showed that codons TTA, GTT, GTC, TCA, GGT, and GGA exhibited a positive association with length, whereas codons GTA, AGC, CGT, CGA, and GGG showed a negative association. GC-ending codons were preferred over AT-ending codons. Overall analysis indicated that the association between CUB and length varies depending on the segment size; however, CUB of 1,200–2,000 bp gene segments appeared not affected by gene length. In synopsis, analysis suggests that length of the genes correlates with various imperative molecular signatures including A/T nucleotide disproportion and codon choices. In the present study we additionally evaluated various molecular features and their correlation with different indices of codon usage, like the Codon Adaptation Index (CAI) and Relative Dynonymous Codon Usage (RSCU) of codons. We also considered the impact of gene fragment size on different molecular features in genes related to neurodegeneration. This analysis will aid our understanding of and in potentially modulating gene expression in cases of defective gene functioning in clinical settings.

Codon Usage Analysis of Pro-Apoptotic Bim Gene Isoforms

Background: Bim is a Bcl-2 homology 3 (BH3)-only proteins, a group of pro-apoptotic proteins involved in physiological and pathological conditions. Both the overexpression and under-expression of Bim protein are associated with the diseased condition, and various isoforms of Bim protein are present with differential apoptotic potential. Objective: The present study attempted to envisage the association of various molecular signatures with the codon choices of Bim isoforms. Methods: Molecular signatures like composition, codon usage, nucleotide skews, the free energy of mRNA transcript, physical properties of proteins, codon adaptation index, relative synonymous codon usage, and dinucleotide odds ratio were determined and analyzed for their associations with codon choices of Bim gene. Results: Skew analysis of the Bim gene indicated the preference of C nucleotide over G, A, and T and preference of G over T and A nucleotides was observed. An increase in C content at the first and third codon position increased gene expression while it decreased at the second codon position. Compositional constraints on nucleotide C at all three codon positions affected gene expression. The analysis revealed an exceptionally high usage of CpC dinucleotide in all the envisaged 31 isoforms of Bim. We correlated it with the requirement of rapid demethylation machinery to fine-tune the Bimgene expression. Also, mutational pressure played a dominant role in shaping codon usage bias in Bim isoforms. Conclusion: An exceptionally high usage of CpC dinucleotide in all the envisaged 31 isoforms of Bim indicates a high order selectional force to fine tune Bim gene expression.

Dynamic queuosine changes in tRNA couple nutrient levels to codon choice in Trypanosoma brucei.

Every type of nucleic acid in cells undergoes programmed chemical post-transcriptional modification. Generally, modification enzymes use substrates derived from intracellular metabolism, one exception is queuine (q)/queuosine (Q), which eukaryotes obtain from their environment; made by bacteria and ultimately taken into eukaryotic cells via currently unknown transport systems. Here, we use a combination of molecular, cell biology and biophysical approaches to show that in Trypanosoma brucei tRNA Q levels change dynamically in response to concentration variations of a sub-set of amino acids in the growth media. Most significant were variations in tyrosine, which at low levels lead to increased Q content for all the natural tRNAs substrates of tRNA-guanine transglycosylase (TGT). Such increase results from longer nuclear dwell time aided by retrograde transport following cytoplasmic splicing. In turn high tyrosine levels lead to rapid decrease in Q content. Importantly, the dynamic changes in Q content of tRNAs have negligible effects on global translation or growth rate but, at least, in the case of tRNATyr it affected codon choice. These observations have implications for the occurrence of other tunable modifications important for ‘normal’ growth, while connecting the intracellular localization of modification enzymes, metabolites and tRNAs to codon selection and implicitly translational output.

Plasmid Curing and Exchange Using a Novel Counter-Selectable Marker Based on Unnatural Amino Acid Incorporation at a Sense Codon.

A protocol was designed for plasmid curing using a novel counter-selectable marker, named pylSZK-pylT, in Escherichia coli. The pylSZK-pylT marker consists of the archaeal pyrrolysyl-tRNA synthetase (PylRS) and its cognate tRNA (tRNApyl) with modification, and incorporates an unnatural amino acid (Uaa), Nε-benzyloxycarbonyl-l-lysine (ZK), at a sense codon in ribosomally synthesized proteins, resulting in bacterial growth inhibition or killing. Plasmid curing is performed by exerting toxicity on pylSZK-pylT located on the target plasmid, and selecting only proliferative bacteria. All tested bacteria obtained using this protocol had lost the target plasmid (64/64), suggesting that plasmid curing was successful. Next, we attempted to exchange plasmids with the identical replication origin and an antibiotic resistance gene without plasmid curing using a modified protocol, assuming substitution of plasmids complementing genomic essential genes. All randomly selected bacteria after screening had only the substitute plasmid and no target plasmid (25/25), suggesting that plasmid exchange was also accomplished. Counter-selectable markers based on PylRS-tRNApyl, such as pylSZK-pylT, may be scalable in application due to their independence from the host genotype, applicability to a wide range of species, and high tunability due to the freedom of choice of target codons and Uaa’s to be incorporated.

A nascent polypeptide sequence modulates DnaA translation elongation in response to nutrient availability.

The ability to regulate DNA replication initiation in response to changing nutrient conditions is an important feature of most cell types. In bacteria, DNA replication is triggered by the initiator protein DnaA, which has long been suggested to respond to nutritional changes; nevertheless, the underlying mechanisms remain poorly understood. Here, we report a novel mechanism that adjusts DnaA synthesis in response to nutrient availability in Caulobacter crescentus. By performing a detailed biochemical and genetic analysis of the dnaA mRNA, we identified a sequence downstream of the dnaA start codon that inhibits DnaA translation elongation upon carbon exhaustion. Our data show that the corresponding peptide sequence, but not the mRNA secondary structure or the codon choice, is critical for this response, suggesting that specific amino acids in the growing DnaA nascent chain tune translational efficiency. Our study provides new insights into DnaA regulation and highlights the importance of translation elongation as a regulatory target. We propose that translation regulation by nascent chain sequences, like the one described, might constitute a general strategy for modulating the synthesis rate of specific proteins under changing conditions.

Genes Common in Primary Immunodeficiencies and Cancer Display Overrepresentation of Codon CTG and Dominant Role of Selection Pressure in Shaping Codon Usage

Primary immunodeficiencies (PIDs) are disorders of the immune system that involve faulty cellular, humoral, or both cellular and humoral functions. PIDs are present at the crossroad between infections, immune dysregulation, and cancers. A panel encompassing 42 genes involved in both PIDs and cancer has been investigated for the genes’ compositional properties, codon usage patterns, various forces affecting codon choice, protein properties, and gene expression profiles. In the present study, the codon choice of genes was found to be dependent upon the richness of the nucleotide; the viz AT nucleotide rich genome preferred AT ending codons. The dinucleotide TpA adversely affected protein expression, while CpG did not. The CTG codon was the most overrepresented codon in 80.95% of genes. Analysis of various protein properties, including GRAVY, AROMA, isoelectric point, aliphatic index, hydrophobicity, instability index, and numbers of acidic, basic, and neutral amino acid residues revealed that the hydrophobicity index, instability index, and numbers of acidic and basic amino acid residues are the factors affecting gene expression. Based on neutrality analysis, parity analysis, ENc-GC3 analysis, and regression analysis of nucleotides present at the first and third positions of the codon, it was determined that selection pressure, mutation pressure, and compositional constraints all participated in shaping codon usage. The study will help determine the various evolutionary forces acting on genes common to both PIDs and cancer. Codon usage analysis might be helpful in the future to augment both diseases simultaneously. The research also indicates a peculiar pattern adapted by a set of genes involved in any disease.

Degradation of host translational machinery drives tRNA acquisition in viruses.

Viruses are traditionally thought to be under selective pressure to maintain compact genomes and thus depend on host cell translational machinery for reproduction. However, some viruses encode abundant tRNA and other translation-related genes, potentially optimizing for codon usage differences between phage and host. Here, we systematically interrogate selective advantages that carrying 18 tRNAs may convey to a T4-like Vibriophage. Host DNA and RNA degrade upon infection, including host tRNAs, which are replaced by those of the phage. These tRNAs are expressed at levels slightly better adapted to phage codon usage, especially that of late genes. The phage is unlikely to randomly acquire as diverse an array of tRNAs as observed (p= 0.0017). Together, our results support that the main driver behind phage tRNA acquisition is pressure to sustain translation as host machinery degrades, a process resulting in a dynamically adapted codon usage strategy during the course of infection.

A Code Within a Code: How Codons Fine-Tune Protein Folding in the Cell.

The genetic code sets the correspondence between the sequence of a given nucleotide triplet in an mRNA molecule, called a codon, and the amino acid that is added to the growing polypeptide chain during protein synthesis. With four bases (A, G, U, and C), there are 64 possible triplet codons: 61 sense codons (encoding amino acids) and 3 nonsense codons (so-called, stop codons that define termination of translation). In most organisms, there are 20 common/standard amino acids used in protein synthesis; thus, the genetic code is redundant with most amino acids (with the exception of Met and Trp) are being encoded by more than one (synonymous) codon. Synonymous codons were initially presumed to have entirely equivalent functions, however, the finding that synonymous codons are not present at equal frequencies in mRNA suggested that the specific codon choice might have functional implications beyond coding for amino acid. Observation of nonequivalent use of codons in mRNAs implied a possibility of the existence of auxiliary information in the genetic code. Indeed, it has been found that genetic code contains several layers of such additional information and that synonymous codons are strategically placed within mRNAs to ensure a particular translation kinetics facilitating and fine-tuning co-translational protein folding in the cell via step-wise/sequential structuring of distinct regions of the polypeptide chain emerging from the ribosome at different points in time. This review summarizes key findings in the field that have identified the role of synonymous codons and their usage in protein folding in the cell.