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).

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.

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.

Epitope III, a highly conserved amino acid motif of 524APTYSW529 on the hepatitis C virus (HCV) E2 glycoprotein, resides in the critical loop that binds to the host receptor CD81, thus making it one of the most important antibody targets for blocking HCV infections. Here, we have determined the X-ray crystal structure of epitope III at a 2.0-Å resolution when it was captured by a site-specific neutralizing antibody, monoclonal antibody 1H8 (mAb1H8). The snapshot of this complex revealed that epitope III has a relatively rigid structure when confined in the binding grooves of mAb1H8, which confers the residue specificity at both ends of the epitope. Such a high shape complementarity is reminiscent of the "lock and key" mode of action, which is reinforced by the incompatibility of an antibody binding with an epitope bearing specific mutations. By subtly positioning the side chains on the three residues of Tyr527, Ser528, and Trp529 while preserving the spatial rigidity of the rest, epitope III in this cocrystal complex adopts a unique conformation that is different from previously described E2 structures. With further analyses of molecular docking and phage display-based peptide interactions, we recognized that it is the arrangements of two separate sets of residues within epitope III that create these discrete conformations for the epitope to interact selectively with either mAb1H8 or CD81. These observations thus raise the possibility that local epitope III conformational dynamics, in conjunction with sequence variations, may act as a regulatory mechanism to coordinate "mAb1H8-like" antibody-mediated immune defenses with CD81-initiated HCV infections.

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.

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.

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.

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.

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.

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.

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.

Photosynthetic microalgae hold great potential as light-driven heterologous protein expression hosts.In particular, the algal chloroplast is an ideal sub-cellular site for the compartmentalized synthesis and accumulation of high-value recombinant proteins. However, full integration of transplastomic algal biotechnology in the large-scale production of biocatalysts still suffers from major bottlenecks, such as genetic instability and pest contamination. To enhance the reliability of plastid-based algal expression platforms we developed a self-reinforcing genetic system in Chlamydomonas reinhardtii. We transformed the plastome with a bifunctional transgene encoding an in vivo cleavable fusion polypeptide composed of a hyperthermophilic cellulase and the phosphite dehydrogenase PTXD. The dual use of phosphite as a low-cost, environmentally friendly selective agent and fertilizer afforded axenic algal cultivation via mixotrophic metabolism and efficient expression of the hydrolytic enzyme. This study provides an example of chloroplast genetic engineering in which biosafety is integrated in the sustainable management of microalgal monocultures to produce enzymes with industrial applications.