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).

Synonymous ADAMTS13 variants impact molecular characteristics and contribute to variability in active protein abundance.

The effects of synonymous single nucleotide variants (sSNVs) are often neglected because they do not alter protein primary structure. Nevertheless, there is growing evidence that synonymous variations may affect messenger RNA (mRNA) expression and protein conformation and activity, which may lead to protein deficiency and disease manifestations. Because there are >21 million possible sSNVs affecting the human genome, it is not feasible to experimentally validate the effect of each sSNV. Here, we report a comprehensive series of in silico analyses assessing sSNV impact on a specific gene. ADAMTS13 was chosen as a model for its large size, many previously reported sSNVs, and associated coagulopathy thrombotic thrombocytopenic purpura. Using various prediction tools of biomolecular characteristics, we evaluated all ADAMTS13 sSNVs registered in the National Center for Biotechnology Information database of single nucleotide polymorphisms, including 357 neutral sSNVs and 19 sSNVs identified in patients with thrombotic thrombocytopenic purpura. We showed that some sSNVs change mRNA-folding energy/stability, disrupt mRNA splicing, disturb microRNA-binding sites, and alter synonymous codon or codon pair usage. Our findings highlight the importance of considering sSNVs when assessing the complex effects of ADAMTS13 alleles, and our approach provides a generalizable framework to characterize sSNV impact in other genes and diseases.

Structural, functional, and immunogenicity implications of F9 gene recoding.

Hemophilia B is a blood clotting disorder caused by deficient activity of coagulation factor IX (FIX). Multiple recombinant FIX proteins are currently approved to treat hemophilia B, and several gene therapy products are currently being developed. Codon optimization is a frequently used technique in the pharmaceutical industry to improve recombinant protein expression by recoding a coding sequence using multiple synonymous codon substitutions. The underlying assumption of this gene recoding is that synonymous substitutions do not alter protein characteristics because the primary sequence of the protein remains unchanged. However, a critical body of evidence shows that synonymous variants can affect cotranslational folding and protein function. Gene recoding could potentially alter the structure, function, and in vivo immunogenicity of recoded therapeutic proteins. Here, we evaluated multiple recoded variants of F9 designed to further explore the effects of codon usage bias on protein properties. The detailed evaluation of these constructs showed altered conformations, and assessment of translation kinetics by ribosome profiling revealed differences in local translation kinetics. Assessment of wild-type and recoded constructs using a major histocompatibility complex (MHC)-associated peptide proteomics assay showed distinct presentation of FIX-derived peptides bound to MHC class II molecules, suggesting that despite identical amino acid sequence, recoded proteins could exhibit different immunogenicity risks. Posttranslational modification analysis indicated that overexpression from gene recoding results in suboptimal posttranslational processing. Overall, our results highlight potential functional and immunogenicity concerns associated with gene-recoded F9 products. These findings have general applicability and implications for other gene-recoded recombinant proteins.

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.

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.

Ribosome profiling of HEK293T cells overexpressing codon optimized coagulation factor IX.

Ribosome profiling provides the opportunity to evaluate translation kinetics at codon level resolution. Here, we describe ribosome profiling data, generated from two HEK293T cell lines. The ribosome profiling data are composed of Ribo-seq (mRNA sequencing data from ribosome protected fragments) and RNA-seq data (total RNA sequencing). The two HEK293T cell lines each express a version of the F9 gene, both of which are translated into identical proteins in terms of their amino acid sequences. However, these F9 genes vary drastically in their codon usage and predicted mRNA structure. We also provide the pipeline that we used to analyze the data. Further analyzing this dataset holds great potential as it can be used i) to unveil insights into the composition and regulation of the transcriptome, ii) for comparison with other ribosome profiling datasets, iii) to measure the rate of protein synthesis across the proteome and identify differences in elongation rates, iv) to discover previously unidentified translation of peptides, v) to explore the effects of codon usage or codon context in translational kinetics and vi) to investigate cotranslational folding. Importantly, a unique feature of this dataset, compared to other available ribosome profiling data, is the presence of the F9 gene in two very distinct coding sequences.

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.

Sequence analysis of SARS-CoV-2 genome reveals features important for vaccine design.

As the SARS-CoV-2 pandemic is rapidly progressing, the need for the development of an effective vaccine is critical. A promising approach for vaccine development is to generate, through codon pair deoptimization, an attenuated virus. This approach carries the advantage that it only requires limited knowledge specific to the virus in question, other than its genome sequence. Therefore, it is well suited for emerging viruses, for which we may not have extensive data. We performed comprehensive in silico analyses of several features of SARS-CoV-2 genomic sequence (e.g., codon usage, codon pair usage, dinucleotide/junction dinucleotide usage, RNA structure around the frameshift region) in comparison with other members of the coronaviridae family of viruses, the overall human genome, and the transcriptome of specific human tissues such as lung, which are primarily targeted by the virus. Our analysis identified the spike (S) and nucleocapsid (N) proteins as promising targets for deoptimization and suggests a roadmap for SARS-CoV-2 vaccine development, which can be generalizable to other viruses.

In silico features of ADAMTS13 contributing to plasmatic ADAMTS13 levels in neonates with congenital heart disease.

INTRODUCTION: Risk factors contributing to heightened thrombosis in pediatric congenital heart disease (CHD) patients are not fully understood. Among the neonatal CHD population, those presenting with single ventricular physiology are at the highest risk for perioperative thrombosis. The von Willebrand factor and ADAMTS13 interactions have emerged as causative risk factors for pediatric stroke and could contribute to heightened thrombosis in CHD neonates. METHODS: This study investigates a cohort of children with single ventricle physiology and undergoing cardiac surgery, during which some patients developed thrombosis. In this cohort, we analyzed the relationship of several molecular features of ADAMTS13 with the plasma and activity levels in patients at risk of thrombosis. Additionally, in light of the natural antithrombotic activity of ADAMTS13, we have sequenced the ADAMTS13 gene for each patient and evaluated the role of genetic variants in determining the plasma ADAMTS13 levels using a series of in silico tools including Hidden Markov Models, EVmutation, and Rosetta. RESULTS: Lower ADAMTS13 levels were found in patients that developed thrombosis. A novel in silico analysis to assess haplotype effect of co-occurring variants identified alterations in relative surface area and solvation energy as important contributors. Our analysis suggested that beneficial or deleterious effect of a variant can be reasonably predicted by comprehensive analysis of in silico assessment and in vitro and/or in vivo data. CONCLUSION: Findings from this study add to our understanding the role of genetic features of ADAMTS13 in patients at high risk of thrombosis related to an imbalanced relation between VWF and ADAMTS13.

Sequence analysis of SARS-CoV-2 genome reveals features important for vaccine design.

As the SARS-CoV-2 pandemic is rapidly progressing, the need for the development of an effective vaccine is critical. A promising approach for vaccine development is to generate, through codon pair deoptimization, an attenuated virus. This approach carries the advantage that it only requires limited knowledge specific to the virus in question, other than its genome sequence. Therefore, it is well suited for emerging viruses for which we may not have extensive data. We performed comprehensive in silico analyses of several features of SARS-CoV-2 genomic sequence (e.g., codon usage, codon pair usage, dinucleotide/junction dinucleotide usage, RNA structure around the frameshift region) in comparison with other members of the coronaviridae family of viruses, the overall human genome, and the transcriptome of specific human tissues such as lung, which are primarily targeted by the virus. Our analysis identified the spike (S) and nucleocapsid (N) proteins as promising targets for deoptimization and suggests a roadmap for SARS-CoV-2 vaccine development, which can be generalizable to other viruses.

TissueCoCoPUTs: Novel Human Tissue-Specific Codon and Codon-Pair Usage Tables Based on Differential Tissue Gene Expression.

Protein expression in multicellular organisms varies widely across tissues. Codon usage in the transcriptome of each tissue is derived from genomic codon usage and the relative expression level of each gene. We created a comprehensive computational resource that houses tissue-specific codon, codon-pair, and dinucleotide usage data for 51 Homo sapiens tissues (TissueCoCoPUTs: https://hive.biochemistry.gwu.edu/review/tissue_codon), using transcriptome data from the Broad Institute Genotype-Tissue Expression (GTEx) portal. Distances between tissue-specific codon and codon-pair frequencies were used to generate a dendrogram based on the unique patterns of codon and codon-pair usage in each tissue that are clearly distinct from the genomic distribution. This novel resource may be useful in unraveling the relationship between codon usage and tRNA abundance, which could be critical in determining translation kinetics and efficiency across tissues. Areas of investigation such as biotherapeutic development, tissue-specific genetic engineering, and genetic disease prediction will greatly benefit from this resource.

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.

Effects of codon optimization on coagulation factor IX translation and structure: Implications for protein and gene therapies.

Synonymous codons occur with different frequencies in different organisms, a phenomenon termed codon usage bias. Codon optimization, a common term for a variety of approaches used widely by the biopharmaceutical industry, involves synonymous substitutions to increase protein expression. It had long been presumed that synonymous variants, which, by definition, do not alter the primary amino acid sequence, have no effect on protein structure and function. However, a critical mass of reports suggests that synonymous codon variations may impact protein conformation. To investigate the impact of synonymous codons usage on protein expression and function, we designed an optimized coagulation factor IX (FIX) variant and used multiple methods to compare its properties to the wild-type FIX upon expression in HEK293T cells. We found that the two variants differ in their conformation, even when controlling for the difference in expression levels. Using ribosome profiling, we identified robust changes in the translational kinetics of the two variants and were able to identify a region in the gene that may have a role in altering the conformation of the protein. Our data have direct implications for codon optimization strategies, for production of recombinant proteins and gene therapies.

Codon and Codon-Pair Usage Tables (CoCoPUTs): Facilitating Genetic Variation Analyses and Recombinant Gene Design.

Usage of sequential codon-pairs is non-random and unique to each species. Codon-pair bias is related to but clearly distinct from individual codon usage bias. Codon-pair bias is thought to affect translational fidelity and efficiency and is presumed to be under the selective pressure. It was suggested that changes in codon-pair utilization may affect human disease more significantly than changes in single codons. Although recombinant gene technologies often take codon-pair usage bias into account, codon-pair usage data/tables are not readily available, thus potentially impeding research efforts. The present computational resource (https://hive.biochemistry.gwu.edu/review/codon2) systematically addresses this issue. Building on our recent HIVE-Codon Usage Tables, we constructed a new database to include genomic codon-pair and dinucleotide statistics of all organisms with sequenced genome, available in the GenBank. We believe that the growing understanding of the importance of codon-pair usage will make this resource an invaluable tool to many researchers in academia and pharmaceutical industry.

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.

Building better drugs: developing and regulating engineered therapeutic proteins.

Most native proteins do not make optimal drugs and thus a second- and third-generation of therapeutic proteins, which have been engineered to improve product attributes or to enhance process characteristics, are rapidly becoming the norm. There has been unprecedented progress, during the past decade, in the development of platform technologies that further these ends. Although the advantages of engineered therapeutic proteins are considerable, the alterations can affect the safety and efficacy of the drugs. We discuss both the key technological innovations with respect to engineered therapeutic proteins and advancements in the underlying basic science. The latter would permit the design of science-based criteria for the prediction and assessment of potential risks and the development of appropriate risk management plans. This in turn holds promise for more predictable criteria for the licensure of a class of products that are extremely challenging to develop but represent an increasingly important component of modern medical practice.

A gene-specific method for predicting hemophilia-causing point mutations.

A fundamental goal of medical genetics is the accurate prediction of genotype-phenotype correlations. As an approach to develop more accurate in silico tools for prediction of disease-causing mutations of structural proteins, we present a gene- and disease-specific prediction tool based on a large systematic analysis of missense mutations from hemophilia A (HA) patients. Our HA-specific prediction tool, HApredictor, showed disease prediction accuracy comparable to other publicly available prediction software. In contrast to those methods, its performance is not limited to non-synonymous mutations. Given the role of synonymous mutations in disease and drug codon optimization, we propose that utilizing a gene- and disease-specific method can be highly useful to make functional predictions possible even for synonymous mutations. Incorporating computational metrics at both nucleotide and amino acid levels along with multiple protein sequence/structure alignment significantly improved the predictive performance of our tool. HApredictor is freely available for download at http://www.ncbi.nlm.nih.gov/CBBresearch/Przytycka/HA_Predict/index.htm.

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.

A splice variant of ADAMTS13 is expressed in human hepatic stellate cells and cancerous tissues.

Although ADAMTS13, the von Willebrand factor (VWF)-cleaving protease, is expressed in a range of tissues, the physiological significance of tissue-specific ADAMTS13 alternative splicing isoforms have yet to be clarified. Screening a panel of human tissues and cell lines revealed a spliced ADAMTS13 transcript in hepatic stellate cells and a hepatoma cell line that retains the 25th intron. A nonsense codon within the intron truncates the protease, which gains 64 novel amino acids in lieu of both CUB domains. This isoform, while retaining VWF-cleaving capability, accumulates intracellularly and its biological inaccessibility may prevent its participation in regulating haemostasis and other physiologic functions.