Sequence-Based Bioinformatics Approaches to Predict Virus-Host Relationships in Archaea and Eukaryotes

Viral metagenomics is independent of lab culturing and capable of investigating viromes of virtually any given environmental niches. While numerous sequences of viral genomes have been assembled from metagenomic studies over the past years, the natural hosts for the majority of these viral contigs have not been determined. Different computational approaches have been developed to predict hosts of bacteria phages. Nevertheless, little progress has been made in the virus-host prediction, especially for viruses that infect eukaryotes and archaea. In this study, by analyzing all documented viruses with known eukaryotic and archaeal hosts, we assessed the predictive power of four computational approaches in viral host prediction. The use of the following biological relationships among viruses and hosts were explored: 1. Sequence similarity between virus and host genome, where direct genetic interactions between viruses and hosts are assumed to leave traces of historical infections. 2. Co-evolution between viruses and hosts, where the viral dependency on their hosts for replication is assumed to result in similar genomic features including nucleotide composition and codon usage. 3. Sequence similarity between viruses, where closely related viruses are assumed to infect the same hosts. And 4. genomic feature similarities between viruses based on nucleotide compositions and dinucleotide/codon/bi-codon usage biases. We assume that viruses with similar genomic features tend to share the same hosts. We showed that using any of the four approaches produced better predictions than uninformed guesses, indicating that our current knowledge of virus-host interaction and co-evolution can be exploited to help predict natural hosts among eukaryotes and archaea for viral contigs. Overall, the third and fourth approaches (prediction based on virus-virus genomic sequence similarity and genomic feature similarity) had the highest prediction accuracy. The second approach (prediction based on virus-host co-evolution) has the least predictive power. We also discuss the biological underpinnings of different predictive power shown in each of these approaches. We anticipate a significant increase in predictive capacity as more training data and knowledge of virus-host relationships are accumulated in the future. Advisor: Juan Cu

Prevalence of Epistasis in the Evolution of Influenza A Surface Proteins

The surface proteins of human influenza A viruses experience positive selection to escape both human immunity and, more recently, antiviral drug treatments. In bacteria and viruses, immune-escape and drug-resistant phenotypes often appear through a combination of several mutations that have epistatic effects on pathogen fitness. However, the extent and structure of epistasis in influenza viral proteins have not been systematically investigated. Here, we develop a novel statistical method to detect positive epistasis between pairs of sites in a protein, based on the observed temporal patterns of sequence evolution. The method rests on the simple idea that a substitution at one site should rapidly follow a substitution at another site if the sites are positively epistatic. We apply this method to the surface proteins hemagglutinin and neuraminidase of influenza A virus subtypes H3N2 and H1N1. Compared to a non-epistatic null distribution, we detect substantial amounts of epistasis and determine the identities of putatively epistatic pairs of sites. In particular, using sequence data alone, our method identifies epistatic interactions between specific sites in neuraminidase that have recently been demonstrated, in vitro, to confer resistance to the drug oseltamivir; these epistatic interactions are responsible for widespread drug resistance among H1N1 viruses circulating today. This experimental validation demonstrates the predictive power of our method to identify epistatic sites of importance for viral adaptation and public health. We conclude that epistasis plays a large role in shaping the molecular evolution of influenza viruses. In particular, sites with , which would normally not be identified as positively selected, can facilitate viral adaptation through epistatic interactions with their partner sites. The knowledge of specific interactions among sites in influenza proteins may help us to predict the course of antigenic evolution and, consequently, to select more appropriate vaccines and drugs

Fighting viral infections and virus-driven tumors with cytotoxic CD4+ T cells

CD4+ T cells have been and are still largely regarded as the orchestrators of immune responses, being able to differentiate into distinct T helper cell populations based on differentiation signals, transcription factor expression, cytokine secretion, and specific functions. Nonetheless, a growing body of evidence indicates that CD4+ T cells can also exert a direct effector activity, which depends on intrinsic cytotoxic properties acquired and carried out along with the evolution of several pathogenic infections. The relevant role of CD4+ T cell lytic features in the control of such infectious conditions also leads to their exploitation as a new immunotherapeutic approach. This review aims at summarizing currently available data about functional and therapeutic relevance of cytotoxic CD4+ T cells in the context of viral infections and virus-driven tumors

Inactivation of pathogens on food and contact surfaces using ozone as a biocidal agent

This study focuses on the inactivation of a range of food borne pathogens using ozone as a biocidal agent. Experiments were carried out using Campylobacter jejuni, E. coli and Salmonella enteritidis in which population size effects and different treatment temperatures were investigate

Replicative homeostasis II: Influence of polymerase fidelity on RNA virus quasispecies biology: Implications for immune recognition, viral autoimmunity and other "virus receptor" diseases

Much of the worlds' population is in active or imminent danger from established infectious pathogens, while sporadic and pandemic infections by these and emerging agents threaten everyone. RNA polymerases (RNA(pol)) generate enormous genetic and consequent antigenic heterogeneity permitting both viruses and cellular pathogens to evade host defences. Thus, RNA(pol )causes more morbidity and premature mortality than any other molecule. The extraordinary genetic heterogeneity defining viral quasispecies results from RNA(pol )infidelity causing rapid cumulative genomic RNA mutation a process that, if uncontrolled, would cause catastrophic loss of sequence integrity and inexorable quasispecies extinction. Selective replication and replicative homeostasis, an epicyclical regulatory mechanism dynamically linking RNApol fidelity and processivity with quasispecies phenotypic diversity, modulating polymerase fidelity and, hence, controlling quasispecies behaviour, prevents this happening and also mediates immune escape. Perhaps more importantly, ineluctable generation of broad phenotypic diversity after viral RNA is translated to protein quasispecies suggests a mechanism of disease that specifically targets, and functionally disrupts, the host cell surface molecules – including hormone, lipid, cell signalling or neurotransmitter receptors – that viruses co-opt for cell entry. This mechanism – "Viral Receptor Disease (VRD)" – may explain so-called "viral autoimmunity", some classical autoimmune disorders and other diseases, including type II diabetes mellitus, and some forms of obesity. Viral receptor disease is a unifying hypothesis that may also explain some diseases with well-established, but multi-factorial and apparently unrelated aetiologies – like coronary artery and other vascular diseases – in addition to diseases like schizophrenia that are poorly understood and lack plausible, coherent, pathogenic explanations

Systematic Experimental Determination of Functional Constraints on Proteins and Adaptive Potential of Mutations: A Dissertation

Sequence-function relationship is a fundamental question for many branches of modern biomedical research. It connects the primary sequence of proteins to the function of proteins and fitness of organisms, holding answers for critical questions such as functional consequences of mutations identified in whole genome sequencing and adaptive potential of fast evolving pathogenic viruses and microbes. Many different approaches have been developed to delineate the genotype-phenotype map for different proteins, but are generally limited by their throughput or precision. To systematically quantify the fitness of large numbers of mutations, I modified a novel high throughput mutational scanning approach (EMPIRIC) to investigate the fitness landscape of mutations in important regions of essential proteins from the yeast or RNA viruses. Using EMPIRIC, I analyzed the interplay of the expression level and sequence of Hsp90 on the yeast growth and revealed latent effect of mutations at reduced expression levels of Hsp90. I also examined the functional constraint on the receptor binding site of the Env of Human Immunodeficiency Virus (HIV) and uncovered enhanced receptor binding capacity as a common pathway for adaptation of HIV to laboratory conditions. Moreover, I explored the adaptive potential of neuraminidase (NA) of influenza A virus to a NA inhibitor, oseltamivir, and identified novel oseltamivir resistance mutations with distinct molecular mechanisms. In summary, I applied a high throughput functional genomics approach to map the sequence-function relationship in various systems and examined the evolutionary constraints and adaptive potential of essential proteins ranging from molecular chaperones to drug-targetable viral proteins

Pathogenicity of the H1N1 influenza virus enhanced by functional synergy between the NPV100I and NAD248N pair

By comparing and measuring covariations of viral protein sequences from isolates of the 2009 pH1N1 influenza A virus (IAV), specific substitutions that co-occur in the NP-NA pair were identified. To investigate the effect of these co-occurring substitution pairs, the V100I substitution in NP and the D248N substitution in NA were introduced into laboratory-adapted WSN IAVs. The recombinant WSN with the covarying NPV100I-NAD248N pair exhibited enhanced pathogenicity, as characterized by increased viral production, increased death and inflammation of host cells, and high mortality in infected mice. Although direct interactions between the NPV100I and NAD248N proteins were not detected, the RNA-binding ability of NPV100I was increased, which was further strengthened by NAD248N, in expression-plasmid- transfected cells. Additionally, the NAD248N protein was frequently recruited within lipid rafts, indirectly affecting the RNA-binding ability of NP as well as viral release. Altogether, our data indicate that the covarying NPV100I-NAD248N pair obtained from 2009 pH1N1 IAV sequence information function together to synergistically augment viral assembly and release, which may explain the observed enhanced viral pathogenicity. © 2019 Kim et al.11Ysciescopu

The International Virus Bioinformatics Meeting 2023

The 2023 International Virus Bioinformatics Meeting was held in Valencia, Spain, from 24–26 May 2023, attracting approximately 180 participants worldwide. The primary objective of the conference was to establish a dynamic scientific environment conducive to discussion, collaboration, and the generation of novel research ideas. As the first in-person event following the SARS-CoV-2 pandemic, the meeting facilitated highly interactive exchanges among attendees. It served as a pivotal gathering for gaining insights into the current status of virus bioinformatics research and engaging with leading researchers and emerging scientists. The event comprised eight invited talks, 19 contributed talks, and 74 poster presentations across eleven sessions spanning three days. Topics covered included machine learning, bacteriophages, virus discovery, virus classification, virus visualization, viral infection, viromics, molecular epidemiology, phylodynamic analysis, RNA viruses, viral sequence analysis, viral surveillance, and metagenomics. This report provides rewritten abstracts of the presentations, a summary of the key research findings, and highlights shared during the meeting