Evolution of the vesicular stomatitis viruses: Divergence and codon usage bias

Phylodynamics of Alagoas vesiculovirus in Brazil

The vesicular stomatitis virus belongs to the Rhabdoviridae family, genus Vesiculovirus. Four species (New Jersey, Indiana, Cocal, and Alagoas) are responsible for disease outbreaks in Western Hemisphere countries. In Brazil, the Alagoas virus is responsible for the main outbreaks of the disease, mainly in the states of the Northeast, Midwest, and Southeast regions of the country. The present study aimed to perform the genetic characterization of 41 vesicular stomatitis virus samples. RNA was extracted using Trizol and used to amplify part of gene P. Amplicons were sequenced using the Sanger method. The phylogenetic trees generated showed that Alagoas vesiculoviruses were positioned into three groups: group A formed by the first virus isolate; group B by isolates from states in the Northeast region; and group C by isolates from the states of Bahia, Goiás, and Tocantins. Their divergence to date has generated the formation of two genotypes evolving independently in regions that until the present study had little geographic overlap.

Codon usage divergence of important functional genes in Mycobacterium tuberculosis

Sequence characteristics are usually used to explain the adaptive ability to hosts, metabolism, genetic diversity, drug resistance, and infectivity of Mycobacterium tuberculosis. Exploring the codon usage pattern of coding sequences in Mycobacterium tuberculosis is of great significance. In the present study, two hundred random complete genomes of Mycobacterium tuberculosis were downloaded from the National Center for Biotechnology Information database. The important codon usage pattern, such as the codon bias index, the effective number of codons, the relative synonymous codon usage as well as the base component, of twenty one specific functional genes were counted or calculated. The differences of the relative synonymous codon usage values among those functional genes, and the summation of the standard deviations of codon usage parameters were used to evaluate the divergence degree of the concerned genes. The results show that among the concerned genes, 1) all genes are high GC sequences, the codon usage frequency corresponding to each amino acid of these functional genes had a significant bias; 2) the genes of those with high effective number of codons, such as the coding sequences of Myco-bacterial membrane protein large family, usually have higher divergences; and 3) genes with lower divergences, such as the ag85A and the sigH, are usually highly conserved and are often used as drug target genes. The findings of the present work would improve new understandings on the evolution of Mycobacterium tuberculosis and on the measures to prevent and control tuberculosis from the gene engineering.

Evolution of Potato virus X

Potato virus X (PVX) is the type potexvirus of economic significance. The pathogen is distributed worldwide, threatening solanaceous plants in particular. Based on the coat protein (CP) gene, PVX isolates are classified into two major genotypes (I and II). To gain more insights into the molecular epidemiology and evolution of PVX, recombination analyses were conducted and significant signals were detected. Bayesian coalescent method was then applied to the time-stamped entire CP sequences. According to the estimates, the global subtype I-1 went into expansion in the 20th century and was evolving at a moderate rate. Based on the CP phylogenies, a divergence scenario was proposed for PVX. Surveys of codon usage variation showed that PVX genes had additional bias independent of compositional constraint. In codon preference, PVX was both similar to and different from the three major hosts, potato (Solanum tuberosum), tobacco (Nicotiana tabacum), and tomato (S. lycopersicum). Moreover, the suppression of CpG and UpA dinucleotide frequencies was observed in PVX.

Deciphering the co-adaptation of codon usage between respiratory coronaviruses and their human host uncovers candidate therapeutics for COVID-19

Coronavirus disease 2019 (COVID-19) has caused thousands of deaths worldwide and has become an urgent public health concern. The extraordinary interhuman transmission of this disease has urged scientists to examine the various facets of its pathogenic agent, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Herein, based on publicly available genomic data, we analyzed the codon usage co-adaptation profiles of SARS-CoV-2 and other respiratory coronaviruses (CoVs) with their human host, identified CoV-responsive human genes and their functional roles on the basis of both the relative synonymous codon usage (RSCU)-based correlation of viral genes with human genes and differential gene expression analysis, and predicted potential drugs for COVID-19 treatment based on these genes. The relatively high codon adaptation index (CAI) values (>0.70) signposted the gene expressivity efficiency of CoVs in human. The ENc-GC3 plot indicated that SARS-CoV-2 genome was under strict selection pressure while SARS-CoV and MERS-CoV were under selection and mutational pressures. The RSCU-based correlation analysis indicated that the viral genomes shared similar codons with a panoply of human genes. The merging of RSCU-based correlation data and SARS-CoV-2-responsive differentially expressed genes allowed the identification of human genes potentially affected by SARS-CoV-2 infection. Functional enrichment analysis indicated that these genes were enriched in biological processes and pathways related to host response to viral infection and immune response. Using the drug-gene interaction database, we screened a list of drugs that could target these genes as potential COVID-19 therapeutics. Our findings not only will contribute in vaccine development but also provide a useful set of drugs that could guide practitioners in strategical monitoring of COVID-19. We recommend practitioners to scrupulously screen this list of predicted drugs in order to authenticate those qualified for treating COVID-19 symptoms.