Advances in methods for tRNA sequencing and quantification.

In the past decade tRNA sequencing (tRNA-seq) has attracted considerable attention as an important tool for the development of novel approaches to quantify highly modified tRNA species and to propel tRNA research aimed at understanding the cellular physiology and disease and development of tRNA-based therapeutics. Many methods are available to quantify tRNA abundance while accounting for modifications and tRNA charging/acylation. Advances in both library preparation methods and bioinformatic workflows have enabled developments in next-generation sequencing (NGS) workflows. Other approaches forgo NGS applications in favor of hybridization-based approaches. In this review we provide a brief comparative overview of various tRNA quantification approaches, focusing on the advantages and disadvantages of these methods, which together facilitate reliable tRNA quantification.

New approaches to predict the effect of co-occurring variants on protein characteristics.

Predicting the effect of a mutated gene before the onset of symptoms of genetic diseases would greatly facilitate diagnosis and potentiate early intervention. There have been myriad attempts to predict the effects of single-nucleotide variants. However, the applicability of these efforts does not scale to co-occurring variants. Furthermore, an increasing number of protein therapeutics contain co-occurring nucleotide variations, adding uncertainty during development to the safety and efficiency of these drugs. Co-occurring nucleotide variants may often have synergistic, additive, or antagonistic effects on protein attributes, further complicating the task of outcome prediction. We tested four models based on the cooperative and antagonistic effects of co-occurring variants to predict pathogenicity and effectiveness of protein therapeutics. A total of 30 attributes, including amino acid and nucleotide features, as well as existing single-variant effect prediction tools, were considered on the basis of previous studies on single-nucleotide variants. Importantly, the effects of synonymous variants, often seen in protein therapeutics, were also included in our models. We used 12 datasets of people with monogenic diseases and controls with co-occurring genetic variants to evaluate the accuracy of our models, accomplishing a degree of accuracy comparable to that of prediction tools for single-nucleotide variants. More importantly, our framework is generalizable to new, well-curated datasets of monogenic diseases and new variant scoring tools. This approach successfully assists in addressing the challenging task of predicting the effect of co-occurring variants on pathogenicity and protein effectiveness and is applicable for a wide range of protein therapeutics and genetic diseases.

A synonymous variant is unmasked in thalassaemia.

The genetic underpinnings of beta-thalassaemia encompass a myriad of molecular mechanisms. The ability of synonymous mutations, an often-overlooked category of variants, to influence ß-globin expression and phenotypic disease is highlighted by this report by Gorivale et al. Commentary on: Gorivale et al. When a synonymous mutation breaks the silence in a thalassaemia patient. Br J Haematol 2024;204:677-682.

Analysis of 3.5 million SARS-CoV-2 sequences reveals unique mutational trends with consistent nucleotide and codon frequencies.

BACKGROUND: Since the onset of the SARS-CoV-2 pandemic, bioinformatic analyses have been performed to understand the nucleotide and synonymous codon usage features and mutational patterns of the virus. However, comparatively few have attempted to perform such analyses on a considerably large cohort of viral genomes while organizing the plethora of available sequence data for a month-by-month analysis to observe changes over time. Here, we aimed to perform sequence composition and mutation analysis of SARS-CoV-2, separating sequences by gene, clade, and timepoints, and contrast the mutational profile of SARS-CoV-2 to other comparable RNA viruses. METHODS: Using a cleaned, filtered, and pre-aligned dataset of over 3.5 million sequences downloaded from the GISAID database, we computed nucleotide and codon usage statistics, including calculation of relative synonymous codon usage values. We then calculated codon adaptation index (CAI) changes and a nonsynonymous/synonymous mutation ratio (dN/dS) over time for our dataset. Finally, we compiled information on the types of mutations occurring for SARS-CoV-2 and other comparable RNA viruses, and generated heatmaps showing codon and nucleotide composition at high entropy positions along the Spike sequence. RESULTS: We show that nucleotide and codon usage metrics remain relatively consistent over the 32-month span, though there are significant differences between clades within each gene at various timepoints. CAI and dN/dS values vary substantially between different timepoints and different genes, with Spike gene on average showing both the highest CAI and dN/dS values. Mutational analysis showed that SARS-CoV-2 Spike has a higher proportion of nonsynonymous mutations than analogous genes in other RNA viruses, with nonsynonymous mutations outnumbering synonymous ones by up to 20:1. However, at several specific positions, synonymous mutations were overwhelmingly predominant. CONCLUSIONS: Our multifaceted analysis covering both the composition and mutation signature of SARS-CoV-2 gives valuable insight into the nucleotide frequency and codon usage heterogeneity of SARS-CoV-2 over time, and its unique mutational profile compared to other RNA viruses.

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.

Translational and transcriptional responses in human primary hepatocytes under hypoxia.

The liver is the primary source of a large number of plasma proteins and plays a critical role in multiple biological processes. Inadequate oxygen supply characterizing various clinical settings such as liver transplantation exposes the liver to hypoxic conditions. Studies assessing hypoxia-induced global translational changes in liver are lacking. Here, we employed a recently developed ribosome-profiling technique to assess global translational responses of human primary hepatocytes exposed to acute hypoxic stress (1% O2) for the short term. In parallel, transcriptome profiling was performed to assess mRNA expression changes. We found that translational responses appeared earlier and were predominant over transcriptional responses. A significant decrease in translational efficiency of several ribosome genes indicated translational inhibition of new ribosome protein synthesis in hypoxia. Pathway enrichment analysis highlighted altered translational regulation of MAPK signaling, drug metabolism, oxidative phosphorylation, and nonalcoholic fatty liver disease pathways. Gene Ontology enrichment analysis revealed terms related to translation, metabolism, angiogenesis, apoptosis, and response to stress. Transcriptional induction of genes encoding heat shock proteins was observed within 30 min of hypoxia. Induction of genes encoding stress response mediators, metabolism regulators, and proangiogenic proteins was observed at 240 min. Despite the liver being the primary source of coagulation proteins and the implicated role of hypoxia in thrombosis, limited differences were observed in genes encoding coagulation-associated proteins. Overall, our study demonstrates the predominance of translational regulation over transcription and highlights differentially regulated pathways or biological processes in short-term hypoxic stress responses of human primary hepatocytes. NEW & NOTEWORTHY The novelty of this study lies in applying parallel ribosome- and transcriptome-profiling analyses to human primary hepatocytes in hypoxia. To our knowledge, this is the first study to assess global translational responses using ribosome profiling in hypoxic hepatocytes. Our results demonstrate the predominance of translational responses over transcriptional responses in early hepatic hypoxic stress responses. Furthermore, our study reveals multiple pathways and specific genes showing altered regulation in hypoxic hepatocytes.

A mechanistic investigation of thrombotic microangiopathy associated with IV abuse of Opana ER.

Since 2012, a number of case reports have described the occurrence of thrombotic microangiopathy (TMA) following IV abuse of extended-release oxymorphone hydrochloride (Opana ER), an oral opioid for long-term treatment of chronic pain. Here, we present unique clinical features of 3 patients and investigate IV exposure to the tablet's inert ingredients as a possible causal mechanism. Guinea pigs were used as an animal model to understand the hematopathologic and nephrotoxic potential of the inert ingredient mixture (termed here as PEO+) which primarily contains high-molecular-weight polyethylene oxide (HMW PEO). Microangiopathic hemolytic anemia, thrombocytopenia, and acute kidney injury were found in a group of 3 patients following recent injection of adulterated extended-release oxymorphone tablets. Varying degrees of cardiac involvement and retinal ischemia occurred, with TMA evident on kidney biopsy. A TMA-like state also developed in guinea pigs IV administered PEO+. Acute tubular and glomerular renal injury was accompanied by nonheme iron deposition and hypoxia-inducible factor-1α upregulation in the renal cortex. Similar outcomes were observed following dosing with HMW PEO alone. IV exposure to the inert ingredients in reformulated extended-release oxymorphone can elicit TMA. Although prescription opioid abuse shows geographic variation, all physicians should be highly inquisitive of IV drug abuse when presented with cases of TMA.

A Single Synonymous Variant (c.354G>A [p.P118P]) in ADAMTS13 Confers Enhanced Specific Activity.

Synonymous variants within coding regions may influence protein expression and function. We have previously reported increased protein expression levels ex vivo (~120% in comparison to wild-type) from a synonymous polymorphism variant, c.354G>A [p.P118P], of the ADAMTS13 gene, encoding a plasma protease responsible for von Willebrand Factor (VWF) degradation. In the current study, we investigated the potential mechanism(s) behind the increased protein expression levels from this variant and its effect on ADAMTS13 physico-chemical properties. Cell-free assays showed enhanced translation of the c.354G>A variant and the analysis of codon usage characteristics suggested that introduction of the frequently used codon/codon pair(s) may have been potentially responsible for this effect. Limited proteolysis, however, showed no substantial influence of altered translation on protein conformation. Analysis of post-translational modifications also showed no notable differences but identified three previously unreported glycosylation markers. Despite these similarities, p.P118P variant unexpectedly showed higher specific activity. Structural analysis using modeled interactions indicated that subtle conformational changes arising from altered translation kinetics could affect interactions between an exosite of ADAMTS13 and VWF resulting in altered specific activity. This report highlights how a single synonymous nucleotide variation can impact cellular expression and specific activity in the absence of measurable impact on protein structure.

Single synonymous mutation in factor IX alters protein properties and underlies haemophilia B.

BACKGROUND: Haemophilia B is caused by genetic aberrations in the F9 gene. The majority of these are non-synonymous mutations that alter the primary structure of blood coagulation factor IX (FIX). However, a synonymous mutation c.459G>A (Val107Val) was clinically reported to result in mild haemophilia B (FIX coagulant activity 15%-20% of normal). The F9 mRNA of these patients showed no skipping or retention of introns and/or change in mRNA levels, suggesting that mRNA integrity does not contribute to the origin of the disease in affected individuals. The aim of this study is to elucidate the molecular mechanisms that can explain disease manifestations in patients with this synonymous mutation. METHODS: We analyse the molecular mechanisms underlying the FIX deficiency through in silico analysis and reproducing the c.459G>A (Val107Val) mutation in stable cell lines. Conformation and non-conformation sensitive antibodies, limited trypsin digestion, activity assays for FIX, interaction with other proteins and post-translation modifications were used to evaluate the biophysical and biochemical consequences of the synonymous mutation. RESULTS: The Val107Val synonymous mutation in F9 was found to significantly diminish FIX expression. Our results suggest that this mutation slows FIX translation and affects its conformation resulting in decreased extracellular protein level. The altered conformation did not change the specific activity of the mutated protein. CONCLUSIONS: The pathogenic basis for one synonymous mutation (Val107Val) in the F9 gene associated with haemophilia B was determined. A mechanistic understanding of this synonymous variant yields potential for guiding and developing future therapeutic treatments.

A new and updated resource for codon usage tables.

BACKGROUND: Due to the degeneracy of the genetic code, most amino acids can be encoded by multiple synonymous codons. Synonymous codons naturally occur with different frequencies in different organisms. The choice of codons may affect protein expression, structure, and function. Recombinant gene technologies commonly take advantage of the former effect by implementing a technique termed codon optimization, in which codons are replaced with synonymous ones in order to increase protein expression. This technique relies on the accurate knowledge of codon usage frequencies. Accurately quantifying codon usage bias for different organisms is useful not only for codon optimization, but also for evolutionary and translation studies: phylogenetic relations of organisms, and host-pathogen co-evolution relationships, may be explored through their codon usage similarities. Furthermore, codon usage has been shown to affect protein structure and function through interfering with translation kinetics, and cotranslational protein folding. RESULTS: Despite the obvious need for accurate codon usage tables, currently available resources are either limited in scope, encompassing only organisms from specific domains of life, or greatly outdated. Taking advantage of the exponential growth of GenBank and the creation of NCBI's RefSeq database, we have developed a new database, the High-performance Integrated Virtual Environment-Codon Usage Tables (HIVE-CUTs), to present and analyse codon usage tables for every organism with publicly available sequencing data. Compared to existing databases, this new database is more comprehensive, addresses concerns that limited the accuracy of earlier databases, and provides several new functionalities, such as the ability to view and compare codon usage between individual organisms and across taxonomical clades, through graphical representation or through commonly used indices. In addition, it is being routinely updated to keep up with the continuous flow of new data in GenBank and RefSeq. CONCLUSION: Given the impact of codon usage bias on recombinant gene technologies, this database will facilitate effective development and review of recombinant drug products and will be instrumental in a wide area of biological research. The database is available at hive.biochemistry.gwu.edu/review/codon .

Exposing synonymous mutations.

Synonymous codon changes, which do not alter protein sequence, were previously thought to have no functional consequence. Although this concept has been overturned in recent years, there is no unique mechanism by which these changes exert biological effects. A large repertoire of both experimental and bioinformatic methods has been developed to understand the effects of synonymous variants. Results from this body of work have provided global insights into how biological systems exploit the degeneracy of the genetic code to control gene expression, protein folding efficiency, and the coordinated expression of functionally related gene families. Although it is now clear that synonymous variants are important in a variety of contexts, from human disease to the safety and efficacy of therapeutic proteins, there is no clear consensus on the approaches to identify and validate these changes. Here, we review the diverse methods to understand the effects of synonymous mutations.

Understanding the contribution of synonymous mutations to human disease.

Synonymous mutations - sometimes called 'silent' mutations - are now widely acknowledged to be able to cause changes in protein expression, conformation and function. The recent increase in knowledge about the association of genetic variants with disease, particularly through genome-wide association studies, has revealed a substantial contribution of synonymous SNPs to human disease risk and other complex traits. Here we review current understanding of the extent to which synonymous mutations influence disease, the various molecular mechanisms that underlie these effects and the implications for future research and biomedical applications.

Whole-genome sequencing identifies a recurrent functional synonymous mutation in melanoma.

Synonymous mutations, which do not alter the protein sequence, have been shown to affect protein function [Sauna ZE, Kimchi-Sarfaty C (2011) Nat Rev Genet 12(10):683-691]. However, synonymous mutations are rarely investigated in the cancer genomics field. We used whole-genome and -exome sequencing to identify somatic mutations in 29 melanoma samples. Validation of one synonymous somatic mutation in BCL2L12 in 285 samples identified 12 cases that harbored the recurrent F17F mutation. This mutation led to increased BCL2L12 mRNA and protein levels because of differential targeting of WT and mutant BCL2L12 by hsa-miR-671-5p. Protein made from mutant BCL2L12 transcript bound p53, inhibited UV-induced apoptosis more efficiently than WT BCL2L12, and reduced endogenous p53 target gene transcription. This report shows selection of a recurrent somatic synonymous mutation in cancer. Our data indicate that silent alterations have a role to play in human cancer, emphasizing the importance of their investigation in future cancer genome studies.

Sensitive measurement of single-nucleotide polymorphism-induced changes of RNA conformation: application to disease studies.

Single-nucleotide polymorphisms (SNPs) are often linked to critical phenotypes such as diseases or responses to vaccines, medications and environmental factors. However, the specific molecular mechanisms by which a causal SNP acts is usually not obvious. Changes in RNA secondary structure emerge as a possible explanation necessitating the development of methods to measure the impact of single-nucleotide variation on RNA structure. Despite the recognition of the importance of considering the changes in Boltzmann ensemble of RNA conformers in this context, a formal method to perform directly such comparison was lacking. Here, we solved this problem and designed an efficient method to compute the relative entropy between the Boltzmann ensembles of the native and a mutant structure. On the basis of this theoretical progress, we developed a software tool, remuRNA, and investigated examples of its application. Comparing the impact of common SNPs naturally occurring in populations with the impact of random point mutations, we found that structural changes introduced by common SNPs are smaller than those introduced by random point mutations. This suggests a natural selection against mutations that significantly change RNA structure and demonstrates, surprisingly, that randomly inserted point mutations provide inadequate estimation of random mutations effects. Subsequently, we applied remuRNA to determine which of the disease-associated non-coding SNPs are potentially related to RNA structural changes.

Cyclosporin A impairs the secretion and activity of ADAMTS13 (a disintegrin and metalloprotease with thrombospondin type 1 repeat).

The protease ADAMTS13 (a disintegrin and metalloprotease with thrombospondin type 1 repeat) cleaves multimers of von Willebrand factor, thus regulating platelet aggregation. ADAMTS13 deficiency leads to the fatal disorder thrombotic thrombocytopenic purpura (TTP). It has been observed that cyclosporin A (CsA) treatment, particularly in transplant patients, may sometimes be linked to the development of TTP. Until now, the reason for such a link was unclear. Here we provide evidence demonstrating that cyclophilin B (CypB) activity plays an important role in the secretion of active ADAMTS13. We found that CsA, an inhibitor of CypB, reduces the secretion of ADAMTS13 and leads to conformational changes in the protein resulting in diminished ADAMTS13 proteolytic activity. A direct, functional interaction between CypB (which possesses peptidyl-prolyl cis-trans isomerase (PPIase) and chaperone functions) and ADAMTS13 is demonstrated using immunoprecipitation and siRNA knockdown of CypB. Finally, CypB knock-out mice were found to have reduced ADAMTS13 levels. Taken together, our findings indicate that cyclophilin-mediated activity is an important factor affecting secretion and activity of ADAMTS13. The large number of proline residues in ADAMTS13 is consistent with the important role of cis-trans isomerization in the proper folding of this protein. These results altogether provide a novel mechanistic explanation for CsA-induced TTP in transplant patients.

Multiple in silico tools predict phenotypic manifestations in congenital thrombotic thrombocytopenic purpura.

Congenital thrombotic thrombocytopenic purpura (cTTP) is a rare, recessively inherited genetic disorder with varying clinical presentation that is caused by ADAMTS13 mutations. Several studies have found limited associations between ADAMTS13 mutations and cTTP phenotype. The use of in silico tools that examine multiple mutation characteristics may better predict phenotype. We analysed 118 ADAMTS13 mutations found in 144 cTTP patients reported in the literature and examined associations of several mutation characteristics, including N-terminal proximity, the evolutionary conservation of the affected amino acid position, as well as amino acid charge/phosphorylation and genetic codon usage to disease phenotype. Structure-altering mutations were examined for their impact on ADAMTS13 function based on existing ADAMTS13 crystallographic data (AA 77-685). Our in silico data indicate that: (i) The position of the mutation in the N- or C-terminus, (ii) evolutionary conservation and (iii) codon usage of the affected mutation position are associated with disease parameters, such as age of onset, organ damage and fresh frozen plasma prophylaxis. In conclusion, the usage of multiple in silico tools presents a promising strategy in refining predictions for the diverse presentation of cTTP. Enhancing our utilization of in silico tools to find genotype-phenotype associations will create better-tailored approaches for individual patient treatment.

Implementing computational methods in tandem with synonymous gene recoding for therapeutic development.

Synonymous gene recoding, the substitution of synonymous variants into the genetic sequence, has been used to overcome many production limitations in therapeutic development. However, the safety and efficacy of recoded therapeutics can be difficult to evaluate because synonymous codon substitutions can result in subtle, yet impactful changes in protein features and require sensitive methods for detection. Given that computational approaches have made significant leaps in recent years, we propose that machine-learning (ML) tools may be leveraged to assess gene-recoded therapeutics and foresee an opportunity to adapt codon contexts to enhance some powerful existing tools. Here, we examine how synonymous gene recoding has been used to address challenges in therapeutic development, explain the biological mechanisms underlying its effects, and explore the application of computational platforms to improve the surveillance of functional variants in therapeutic design.

In silico methods for predicting functional synonymous variants.

Single nucleotide variants (SNVs) contribute to human genomic diversity. Synonymous SNVs are previously considered to be "silent," but mounting evidence has revealed that these variants can cause RNA and protein changes and are implicated in over 85 human diseases and cancers. Recent improvements in computational platforms have led to the development of numerous machine-learning tools, which can be used to advance synonymous SNV research. In this review, we discuss tools that should be used to investigate synonymous variants. We provide supportive examples from seminal studies that demonstrate how these tools have driven new discoveries of functional synonymous SNVs.