Codon bias and the folding dynamics of the cystic fibrosis transmembrane conductance regulator

Synonymous or silent mutations are often overlooked in genetic analyses for disease-causing mutations unless they are directly associated with potential splicing defects. More recent studies, however, indicate that some synonymous single polynucleotide polymorphisms (sSNPs) are associated with changes in protein expression, and in some cases, protein folding and function. The impact of codon usage and mRNA structural changes on protein translation rates and how they can affect protein structure and function is just beginning to be appreciated. Examples are given here that demonstrate how synonymous mutations alter the translational kinetics and protein folding and/or function. The mechanism for how this occurs is based on a model in which codon usage modulates the translational rate by introducing pauses caused by nonoptimal or rare codons or by introducing changes in the mRNA structure, and this in turn influences co-translational folding. Two examples of this include the multidrug resistance protein (p-glycoprotein) and the cystic fibrosis transmembrane conductance regulator gene (CFTR). CFTR is also used here as a model to illustrate how synonymous mutations can be examined using in silico predictive methods to identify which sSNPs have the potential to change protein structure. The methodology described here can be used to help identify “non-silent” synonymous mutations in other genes.     

Decoding mechanisms by which silent codon changes influence protein biogenesis and function

ScopeSynonymous codon usage has been a focus of investigation since the discovery of the genetic code and its redundancy. The occurrences of synonymous codons vary between species and within genes of the same genome, known as codon usage bias. Today, bioinformatics and experimental data allow us to compose a global view of the mechanisms by which the redundancy of the genetic code contributes to the complexity of biological systems from affecting survival in prokaryotes, to fine tuning the structure and function of proteins in higher eukaryotes. Studies analyzing the consequences of synonymous codon changes in different organisms have revealed that they impact nucleic acid stability, protein levels, structure and function without altering amino acid sequence. As such, synonymous mutations inevitably contribute to the pathogenesis of complex human diseases. Yet, fundamental questions remain unresolved regarding the impact of silent mutations in human disorders. In the present review we describe developments in this area concentrating on mechanisms by which synonymous mutations may affect protein function and human health.PurposeThis synopsis illustrates the significance of synonymous mutations in disease pathogenesis. We review the different steps of gene expression affected by silent mutations, and assess the benefits and possible harmful effects of codon optimization applied in the development of therapeutic biologics.Physiological and medical relevanceUnderstanding mechanisms by which synonymous mutations contribute to complex diseases such as cancer, neurodegeneration and genetic disorders, including the limitations of codon-optimized biologics, provides insight concerning interpretation of silent variants and future molecular therapies.     

Predicting the functional impact of protein mutations: application to cancer genomics

As large-scale re-sequencing of genomes reveals many protein mutations, especially in human cancer tissues, prediction of their likely functional impact becomes important practical goal. Here, we introduce a new functional impact score (FIS) for amino acid residue changes using evolutionary conservation patterns. The information in these patterns is derived from aligned families and sub-families of sequence homologs within and between species using combinatorial entropy formalism. The score performs well on a large set of human protein mutations in separating disease-associated variants (∼19 200), assumed to be strongly functional, from common polymorphisms (∼35 600), assumed to be weakly functional (area under the receiver operating characteristic curve of ∼0.86). In cancer, using recurrence, multiplicity and annotation for ∼10 000 mutations in the COSMIC database, the method does well in assigning higher scores to more likely functional mutations (‘drivers’). To guide experimental prioritization, we report a list of about 1000 top human cancer genes frequently mutated in one or more cancer types ranked by likely functional impact; and, an additional 1000 candidate cancer genes with rare but likely functional mutations. In addition, we estimate that at least 5% of cancer-relevant mutations involve switch of function, rather than simply loss or gain of function.     

Birth, life and death of nascent polypeptide chains

The journey of nascent polypeptides from synthesis at the peptidyl transferase center of the ribosome ("birth") to full function ("maturity") involves multiple interactions, constraints, modifications and folding events. Each step of this journey impacts the ultimate expression level and functional capacity of the translated protein. It has become clear that the kinetics of protein translation is predominantly modulated by synonymous codon usage along the mRNA, and that this provides an active mechanism for coordinating the synthesis, maturation and folding of nascent polypeptides. Multiple quality control systems ensure that proteins achieve their native, functional form. Unproductive co-translational folding intermediates that arise during protein synthesis may undergo enhanced interaction with components of these systems, such as chaperones, and/or be subjects of co-translational degradation ("death"). This review provides an overview of our current understanding of the complex co-translational events that accompany the synthesis, maturation, folding and degradation of nascent polypeptide chains.     

同义密码子使用模式对蛋白产物表达及构象形成的影响*

鉴于遗传密码子的简并性能够将基因遗传信息的容量提升,同义密码子使用偏嗜性得以在生物体的基因组中广泛存在。虽然同义密码子之间碱基的变化并不能导致氨基酸种类的改变,在研究mRNA半衰期、编码多肽翻译效率及肽链空间构象正确折叠的准确性和翻译等这一系列过程中发现,同义密码子使用的偏嗜性在某种程度上通过精微调控翻译机制体现其遗传学功能。同义密码子指导tRNA在翻译过程中识别核糖体的速率变化是由氨基酸的特定顺序决定,并且在新生多肽链合成时,蛋白质共翻译转运机制同时调节其空间构象的正确折叠从而保证蛋白的正常生物学功能。某些同义密码子使用偏嗜性与特定蛋白结构的形成具有显著相关性,密码子使用偏嗜性一旦改变将可能导致新生多肽空间构象出现错误折叠。结合近些年来国内外在此领域的研究成果,阐述同义密码子使用偏嗜性如何发挥精微调控翻译的生物学功能与作用。     

Silent mutations affect in vivo protein folding in Escherichia coli

As an approach to investigate the molecular mechanism of in vivo protein folding and the role of translation kinetics on specific folding pathways, we made codon substitutions in the EgFABP1 (Echinococcus granulosus fatty acid binding protein1) gene that replaced five minor codons with their synonymous major ones. The altered region corresponds to a turn between two short alpha helices. One of the silent mutations of EgFABP1 markedly decreased the solubility of the protein when expressed in Escherichia coli. Expression of this protein also caused strong activation of a reporter gene designed to detect misfolded proteins, suggesting that the turn region seems to have special translation kinetic requirements that ensure proper folding of the protein. Our results highlight the importance of codon usage in the in vivo protein folding.     

Mechanism of induced folding: Both folding before binding and binding before folding can be realized in staphylococcal nuclease mutants

A considerable number of functional proteins are unstructured under physiological condition. These "intrinsically disordered" proteins exhibit induced folding when they bind their targets. The induced folding comprises two elementary processes: folding and binding. Two mechanisms are possible for the induced folding: either folding before binding or binding before folding. We found that these two mechanisms can be distinguished by the target-concentration dependence of folding kinetics. We also created two types of mutants of staphylococcal nuclease showing the different inhibitor-concentration dependence of induced folding kinetics. One mutant obeys the scheme of binding before folding, while the other the folding before binding. This is the first experimental evidence demonstrating that both mechanisms are realized for a single protein. Binding before folding is possible, when the protein lacks essential nonlocal interaction to stabilize the native conformation. The results cast light on the protein folding mechanism involved in the intrinsically disordered proteins.     

Facile Method for High-throughput Identification of Stabilizing Mutations

Characterizing the effects of mutations on stability is critical for understanding the function and evolution of proteins and improving their biophysical properties. High throughput folding and abundance assays have been successfully used to characterize missense mutations associated with reduced stability. However, screening for increased thermodynamic stability is more challenging since such mutations are rarer and their impact on assay readout is more subtle. Here, a multiplex assay for high throughput screening of protein folding was developed by combining deep mutational scanning, fluorescence-activated cell sorting, and deep sequencing. By analyzing a library of 2000 variants of Adenylate kinase we demonstrate that the readout of the method correlates with stability and that mutants with up to 13 °C increase in thermal melting temperature could be identified with low false positive rate. The discovery of many stabilizing mutations also enabled the analysis of general substitution patterns associated with increased stability in Adenylate kinase. This high throughput method to identify stabilizing mutations can be combined with functional screens to identify mutations that improve both stability and activity.     

Molecular basis for variations in the sensitivity of pathogenic rhodopsin variants to 9-cis-retinal

Over 100 mutations in the rhodopsin gene have been linked to a spectrum of retinopathies that include retinitis pigmentosa and congenital stationary night blindness. Though most of these variants exhibit a loss of function, the molecular defects caused by these underlying mutations vary considerably. In this work, we utilize deep mutational scanning to quantitatively compare the plasma membrane expression of 123 known pathogenic rhodopsin variants in the presence and absence of the stabilizing cofactor 9-cis-retinal. We identify 69 retinopathy variants, including 20 previously uncharacterized variants, that exhibit diminished plasma membrane expression in HEK293T cells. Of these apparent class II variants, 67 exhibit a measurable increase in expression in the presence of 9-cis-retinal. However, the magnitude of the response to this molecule varies considerably across this spectrum of mutations. Evaluation of the observed shifts relative to thermodynamic estimates for the coupling between binding and folding suggests underlying differences in stability constrains the magnitude of their response to retinal. Nevertheless, estimates from computational modeling suggest that many of the least sensitive variants also directly compromise binding. Finally, we evaluate the functional properties of three previous uncharacterized, retinal-sensitive variants (ΔN73, S131P, and R135G) and show that two of these retain residual function in vitro. Together, our results provide a comprehensive experimental characterization of the proteostatic properties of retinopathy variants and their response to retinal.     

Structural and Functional Impact of Cancer-Related Missense Somatic Mutations

A number of large-scale cancer somatic genome sequencing projects are now identifying genetic alterations in cancers. Evaluation of the effects of these mutations is essential for understanding their contribution to tumorigenesis. We have used SNPs3D, a software suite originally developed for analyzing nonsynonymous germ-line variants, to identify single-base mutations with a high impact on protein structure and function. Two machine learning methods are used: one identifying mutations that destabilize protein three-dimensional structure and the other utilizing sequence conservation and detecting all types of effects on in vivo protein function. Incorporation of detailed structure information into the analysis allows detailed interpretation of the functional effects of mutations in specific cases.  Data from a set of breast and colorectal tumors were analyzed. In known cancer genes, mutations approaching 100% of mutations are found to impact protein function, supporting the view that these methods are appropriate for identifying driver mutations. Overall, 50-60% of all somatic missense mutations are predicted to have a high impact on structural stability or to more generally affect the function of the corresponding proteins. This value is similar to the fraction of all possible missense mutations that have a high impact and is much higher than the corresponding one for human population single-nucleotide polymorphisms, at about 30%. The majority of mutations in tumor suppressors destabilize protein structure, while mutations in oncogenes operate in more varied ways, including destabilization of less active conformational states. The set of high-impact mutations encompasses the possible drivers.     

e-MutPath: computational modeling reveals the functional landscape of genetic mutations rewiring interactome networks

Understanding the functional impact of cancer somatic mutations represents a critical knowledge gap for implementing precision oncology. It has been increasingly appreciated that the interaction profile mediated by a genomic mutation provides a fundamental link between genotype and phenotype. However, specific effects on biological signaling networks for the majority of mutations are largely unknown by experimental approaches. To resolve this challenge, we developed e-MutPath (edgetic Mutation-mediated Pathway perturbations), a network-based computational method to identify candidate ‘edgetic’ mutations that perturb functional pathways. e-MutPath identifies informative paths that could be used to distinguish disease risk factors from neutral elements and to stratify disease subtypes with clinical relevance. The predicted targets are enriched in cancer vulnerability genes, known drug targets but depleted for proteins associated with side effects, demonstrating the power of network-based strategies to investigate the functional impact and perturbation profiles of genomic mutations. Together, e-MutPath represents a robust computational tool to systematically assign functions to genetic mutations, especially in the context of their specific pathway perturbation effect.     

Minimalist protein model as a diagnostic tool for misfolding and aggregation

We propose a realistic coarse-grained protein model and a technique to "anchor" the model to available experimental data. We apply this procedure to characterize the effect of multiple mutations on the folding mechanism of protein S6. We show that the mutation of a few "gatekeeper" residues triggers significant changes on the folding landscape of S6. These results suggest that gatekeeper residues control the flexibility of critical regions of S6, that in turn regulates the delicate balance between folding and aggregation. Although obtained with a minimalist protein model, these results are fully consistent with experimental evidence and offer a clue to understand the interplay between folding and aggregation in protein S6.     

Functional relevance of synonymous alleles reflected in allele rareness in the population

We provide theoretical evidence supporting the non-neutrality of synonymous alleles by investigating the rareness of synonymous alleles in the population. We find a significantly greater number of synonymous rare alleles than conventional neutral alleles derived from noncoding regions. A permutation experiment shows that the rareness of synonymous alleles is not a byproduct of random statistical noise. We then compare the frequencies of synonymous rare alleles and common alleles in various functional contexts in which synonymous alleles are known to be involved. Subsequently, we perform logistic regression analysis to elucidate the effect size of each independent factor contributing to the rareness of synonymous alleles. Additionally, we show that changes in optimality caused by synonymous mutations resulting in rare SNPs in the population tend to be biased toward optimality loss. We think that our study will contribute to the development of novel strategies for identifying functional synonymous mutations.     

Exploring synonymous codon usage preferences of disulfide-bonded and non-disulfide bonded cysteines in the E. coli genome

High-quality data about protein structures and their gene sequences are essential to the understanding of the relationship between protein folding and protein coding sequences. Firstly we constructed the EcoPDB database, which is a high-quality database of Escherichia coli genes and their corresponding PDB structures. Based on EcoPDB, we presented a novel approach based on information theory to investigate the correlation between cysteine synonymous codon usages and local amino acids flanking cysteines, the correlation between cysteine synonymous codon usages and synonymous codon usages of local amino acids flanking cysteines, as well as the correlation between cysteine synonymous codon usages and the disulfide bonding states of cysteines in the E. coli genome. The results indicate that the nearest neighboring residues and their synonymous codons of the C-terminus have the greatest influence on the usages of the synonymous codons of cysteines and the usage of the synonymous codons has a specific correlation with the disulfide bond formation of cysteines in proteins. The correlations may result from the regulation mechanism of protein structures at gene sequence level and reflect the biological function restriction that cysteines pair to form disulfide bonds. The results may also be helpful in identifying residues that are important for synonymous codon selection of cysteines to introduce disulfide bridges in protein engineering and molecular biology. The approach presented in this paper can also be utilized as a complementary computational method and be applicable to analyse the synonymous codon usages in other model organisms.     

Silent mutations in the gene encoding the p53 protein are preferentially located in conserved amino acid positions and splicing enhancers

The last release of p53 somatic mutation database contains more than 20,000 of mutation among which 951 are silent (synonymous). This striking amount of silent mutations is much more than what would be expected if synonymous mutations were effectively neutral. The prevalent explanation to reconcile this vast amount of silent mutations with the neutral expectation is that they are just the subproduct of the hypermutability process that affect cancer cells. Some evidences have been presented in this direction, and the explanation has been taken as granted. Assuming that silent mutations are effectively neutral has major implication in the investigation of mutational processes that affect the gene encoding the p53 protein, since on the basis of this assumption they are considered the Null hypothesis, for instance for measuring and comparing among tissues the endogenous mutability. From this it follows that determining whether silent mutations in the p53 gene, and in all disease genes in general, are or not basically mutational noise, is of paramount importance.

In this paper we readdress this topic by testing whether there is a relationship between the spatial distribution of silent mutations inside the p53 gene and functional significant features of the gene. For this purpose we divided the population of silent mutations in three groups: those that are found accompanied by other mutations (doublets and multiplest), those that were isolated as singlets, but the same mutation was also isolated as being part of a doublet (or multiplet) in another individual. And the last group is composed by those that were always found as singlets and never as being part of a doublet or a multiplet. This last group was expected to be enriched in functionally significant silent mutations. We found that all silent mutations, but particularly those of the last group, are preferentially located in conserved amino acid positions (i.e. functionally important amino acids) and also tend to be located inside suspected splicing enhancers. Noteworthy, this association remains even after eliminating the possible contribution of mutation hotspots. Besides, we present additional evidence in the direction that these putative splicing enhancers are real functional enhancers.