Comprehensive NGS profiling to enable detection of ALK gene rearrangements and MET amplifications in non-small cell lung cancer.

Introduction: Next-generation sequencing (NGS) is currently widely used for biomarker studies and molecular profiling to identify concurrent alterations that can lead to the better characterization of a tumor's molecular landscape. However, further evaluation of technical aspects related to the detection of gene rearrangements and copy number alterations is warranted. Methods: There were 12 ALK rearrangement-positive tumor specimens from patients with non-small cell lung cancer (NSCLC) previously detected via fluorescence in situ hybridization (FISH), immunohistochemistry (IHC), and an RNA-based NGS assay, and 26 MET high gene copy number (GCN) cases detected by FISH, selected for this retrospective study. All 38 pre-characterized cases were reassessed utilizing the PGDx™ elio™ tissue complete assay, a 505 gene targeted NGS panel, to evaluate concordance with these conventional diagnostic techniques. Results: The detection of ALK rearrangements using the DNA-based NGS assay demonstrated excellent sensitivity with the added benefit of characterizing gene fusion partners and genomic breakpoints. MET copy number alterations were also detected; however, some discordances were observed likely attributed to differences in algorithm, reporting thresholds and gene copy number state. TMB was also assessed by the assay and correlated to the presence of NSCLC driver alterations and was found to be significantly lower in cases with NGS-confirmed canonical driver mutations compared with those without (p=0.0019). Discussion: Overall, this study validates NGS as an accurate approach for detecting structural variants while also highlighting the need for further optimization to enable harmonization across methodologies for amplifications.

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.

Distinct signatures of codon and codon pair usage in 32 primary tumor types in the novel database CancerCoCoPUTs for cancer-specific codon usage.

BACKGROUND: Gene expression is highly variable across tissues of multi-cellular organisms, influencing the codon usage of the tissue-specific transcriptome. Cancer disrupts the gene expression pattern of healthy tissue resulting in altered codon usage preferences. The topic of codon usage changes as they relate to codon demand, and tRNA supply in cancer is of growing interest. METHODS: We analyzed transcriptome-weighted codon and codon pair usage based on The Cancer Genome Atlas (TCGA) RNA-seq data from 6427 solid tumor samples and 632 normal tissue samples. This dataset represents 32 cancer types affecting 11 distinct tissues. Our analysis focused on tissues that give rise to multiple solid tumor types and cancer types that are present in multiple tissues. RESULTS: We identified distinct patterns of synonymous codon usage changes for different cancer types affecting the same tissue. For example, a substantial increase in GGT-glycine was observed in invasive ductal carcinoma (IDC), invasive lobular carcinoma (ILC), and mixed invasive ductal and lobular carcinoma (IDLC) of the breast. Change in synonymous codon preference favoring GGT correlated with change in synonymous codon preference against GGC in IDC and IDLC, but not in ILC. Furthermore, we examined the codon usage changes between paired healthy/tumor tissue from the same patient. Using clinical data from TCGA, we conducted a survival analysis of patients based on the degree of change between healthy and tumor-specific codon usage, revealing an association between larger changes and increased mortality. We have also created a database that contains cancer-specific codon and codon pair usage data for cancer types derived from TCGA, which represents a comprehensive tool for codon-usage-oriented cancer research. CONCLUSIONS: Based on data from TCGA, we have highlighted tumor type-specific signatures of codon and codon pair usage. Paired data revealed variable changes to codon usage patterns, which must be considered when designing personalized cancer treatments. The associated database, CancerCoCoPUTs, represents a comprehensive resource for codon and codon pair usage in cancer and is available at https://dnahive.fda.gov/review/cancercocoputs/ . These findings are important to understand the relationship between tRNA supply and codon demand in cancer states and could help guide the development of new cancer therapeutics.

In Silico Evaluation of Cyclophilin Inhibitors as Potential Treatment for SARS-CoV-2.

BACKGROUND: The advent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) provoked researchers to propose multiple antiviral strategies to improve patients' outcomes. Studies provide evidence that cyclosporine A (CsA) decreases SARS-CoV-2 replication in vitro and decreases mortality rates of coronavirus disease 2019 (COVID-19) patients. CsA binds cyclophilins, which isomerize prolines, affecting viral protein activity. METHODS: We investigated the proline composition from various coronavirus proteomes to identify proteins that may critically rely on cyclophilin's peptidyl-proline isomerase activity and found that the nucleocapsid (N) protein significantly depends on cyclophilin A (CyPA). We modeled CyPA and N protein interactions to demonstrate the N protein as a potential indirect therapeutic target of CsA, which we propose may impede coronavirus replication by obstructing nucleocapsid folding. RESULTS: Finally, we analyzed the literature and protein-protein interactions, finding evidence that, by inhibiting CyPA, CsA may impact coagulation proteins and hemostasis. CONCLUSIONS: Despite CsA's promising antiviral characteristics, the interactions between cyclophilins and coagulation factors emphasize risk stratification for COVID patients with thrombosis dispositions.

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.

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.

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.