Recognizing species as a new focus of virus research

Shine: A novel strategy to extract specific, sensitive and well-conserved biomarkers from massive microbial genomic datasets

BACKGROUND

Concentrations of the pathogenic microorganisms' DNA in biological samples are typically low. Therefore, DNA diagnostics of common infections are costly, rarely accurate, and challenging. Limited by failing to cover updated epidemic testing samples, computational services are difficult to implement in clinical applications without complex customized settings. Furthermore, the combined biomarkers used to maintain high conservation may not be cost effective and could cause several experimental errors in many clinical settings. Given the limitations of recent developed technology, 16S rRNA is too conserved to distinguish closely related species, and mosaic plasmids are not effective as well because of their uneven distribution across prokaryotic taxa.

RESULTS

Here, we provide a computational strategy, Shine, that allows extraction of specific, sensitive and well-conserved biomarkers from massive microbial genomic datasets. Distinguished with simple concatenations with blast-based filtering, our method involves a de novo genome alignment-based pipeline to explore the original and specific repetitive biomarkers in the defined population. It can cover all members to detect newly discovered multicopy conserved species-specific or even subspecies-specific target probes and primer sets. The method has been successfully applied to a number of clinical projects and has the overwhelming advantages of automated detection of all pathogenic microorganisms without the limitations of genome annotation and incompletely assembled motifs. Using on our pipeline, users may select different configuration parameters depending on the purpose of the project for routine clinical detection practices on the website https://bioinfo.liferiver.com.cn with easy registration.

CONCLUSIONS

The proposed strategy is suitable for identifying shared phylogenetic markers while featuring low rates of false positive or false negative. This technology is suitable for the automatic design of minimal and efficient PCR primers and other types of detection probes.

Determinants of Virus Variation, Evolution, and Host Adaptation

Virus evolution is the change in the genetic structure of a viral population over time and results in the emergence of new viral variants, strains, and species with novel biological properties, including adaptation to new hosts. There are host, vector, environmental, and viral factors that contribute to virus evolution. To achieve or fine tune compatibility and successfully establish infection, viruses adapt to a particular host species or to a group of species. However, some viruses are better able to adapt to diverse hosts, vectors, and environments. Viruses generate genetic diversity through mutation, reassortment, and recombination. Plant viruses are exposed to genetic drift and selection pressures by host and vector factors, and random variants or those with a competitive advantage are fixed in the population and mediate the emergence of new viral strains or species with novel biological properties. This process creates a footprint in the virus genome evident as the preferential accumulation of substitutions, insertions, or deletions in areas of the genome that function as determinants of host adaptation. Here, with respect to plant viruses, we review the current understanding of the sources of variation, the effect of selection, and its role in virus evolution and host adaptation.

Towards Efficient and Accurate SARS-CoV-2 Genome Sequence Typing Based on Supervised Learning Approaches

Despite the active development of SARS-CoV-2 surveillance methods (e.g., Nextstrain, GISAID, Pangolin), the global emergence of various SARS-CoV-2 viral lineages that potentially cause antiviral and vaccine failure has driven the need for accurate and efficient SARS-CoV-2 genome sequence classifiers. This study presents an optimized method that accurately identifies the viral lineages of SARS-CoV-2 genome sequences using existing schemes. For Nextstrain and GISAID clades, a template matching-based method is proposed to quantify the differences between viral clades and to play an important role in classification evaluation. Furthermore, to improve the typing accuracy of SARS-CoV-2 genome sequences, an ensemble model that integrates a combination of machine learning-based methods (such as Random Forest and Catboost) with optimized weights is proposed for Nextstrain, Pangolin, and GISAID clades. Cross-validation is applied to optimize the parameters of the machine learning-based method and the weight settings of the ensemble model. To improve the efficiency of the model, in addition to the one-hot encoding method, we have proposed a nucleotide site mutation-based data structure that requires less computational resources and performs better in SARS-CoV-2 genome sequence typing. Based on an accumulated database of >1 million SARS-CoV-2 genome sequences, performance evaluations show that the proposed system has a typing accuracy of 99.879%, 97.732%, and 96.291% for Nextstrain, Pangolin, and GISAID clades, respectively. A single prediction only takes an average of <20 ms on a portable laptop. Overall, this study provides an efficient and accurate SARS-CoV-2 genome sequence typing system that benefits current and future surveillance of SARS-CoV-2 variants.

Covidex: An ultrafast and accurate tool for SARS-CoV-2 subtyping

The epidemiological surveillance of SARS-CoV-2 by means of whole-genome sequencing has revealed the emergence and co-existence of multiple viral lineages or subtypes throughout the world. Moreover, it has been shown that several subtypes of this virus display particular phenotypes, such as increased transmissibility or reduced susceptibility to neutralizing antibodies, leading to the denomination of Variants of Interest (VOI) or Variants of Concern (VOC). Thus, subtyping of SARS-CoV-2 is a crucial step for the surveillance of this pathogen. Here, we present Covidex, an open-source, alignment-free machine learning subtyping tool. It is a shiny web app that allows an ultra-fast and accurate classification of SARS-CoV-2 genome sequences into the three most used nomenclature systems (GISAID, Nextstrain, Pango lineages). It also categorizes input sequences as VOI or VOC, according to current definitions.

The program is cross-platform compatible and it is available via Source-Forge https://sourceforge.net/projects/covidex or via the web application http://covidex.unlu.edu.ar.

Bioinformatics of virus taxonomy: foundations and tools for developing sequence-based hierarchical classification

The genome sequence is the only characteristic readily obtainable for all known viruses, underlying the growing role of comparative genomics in organizing knowledge about viruses in a systematic evolution-aware way, known as virus taxonomy. Overseen by the International Committee on Taxonomy of Viruses (ICTV), development of virus taxonomy involves taxa demarcation at 15 ranks of a hierarchical classification, often in host-specific manner. Outside the ICTV remit, researchers assess fitting numerous unclassified viruses into the established taxa. They employ different metrics of virus clustering, basing on conserved domain(s), separation of viruses in rooted phylogenetic trees and pair-wise distance space. Computational approaches differ further in respect to methodology, number of ranks considered, sensitivity to uneven virus sampling, and visualization of results. Advancing and using computational tools will be critical for improving taxa demarcation across the virosphere and resolving rank origins in research that may also inform experimental virology.

COVID-19: comprehensive review on mutations and current vaccines

Viral outbreaks had been a threat for the human race for a long time. Several epidemics and pandemics have been reported in the past with serious consequences on human health and subsequent social and economic aspects. According to WHO, viral infections continue to be a major health concern globally. Novel coronavirus, SARS-CoV-2 (Severe acute respiratory syndrome coronavirus-2) causes the most recent infectious pandemic disease, COVID-19 (Coronavirus disease-19). As of now, there were 249 million infections of COVID-19 worldwide with a high mortality of more than 5 million deaths reported; and the number of new additional cases is drastically increasing. Development of therapies to treat the infected cases and prophylactic agents including vaccines that are effective towards different variants are crucial to curtail the COVID-19 pandemic. Owing to the fact that there is a high mortality and morbidity rate along with the risk of virus causing further epidemic outbursts, development of additional effective therapeutic and preventive strategies are highly warranted. Prevention, early detection and treatment will reduce the spread of COVID-19 pandemic. The present review highlights the novel mutations and therapeutic updates associated with coronaviruses along with the clinical manifestations-diagnosis, clinical management and, prophylactic and therapeutic strategies of COVID-19 infection.

The Bunyavirales: The Plant-Infecting Counterparts

Negative-strand (-) RNA viruses (NSVs) comprise a large and diverse group of viruses that are generally divided in those with non-segmented and those with segmented genomes. Whereas most NSVs infect animals and humans, the smaller group of the plant-infecting counterparts is expanding, with many causing devastating diseases worldwide, affecting a large number of major bulk and high-value food crops. In 2018, the taxonomy of segmented NSVs faced a major reorganization with the establishment of the order Bunyavirales. This article overviews the major plant viruses that are part of the order, i.e., orthospoviruses (Tospoviridae), tenuiviruses (Phenuiviridae), and emaraviruses (Fimoviridae), and provides updates on the more recent ongoing research. Features shared with the animal-infecting counterparts are mentioned, however, special attention is given to their adaptation to plant hosts and vector transmission, including intra/intercellular trafficking and viral counter defense to antiviral RNAi.