Projection in genomic analysis: A theoretical basis to rationalize tensor decomposition and principal component analysis as feature selection tools.

Identifying differentially expressed genes is difficult because of the small number of available samples compared with the large number of genes. Conventional gene selection methods employing statistical tests have the critical problem of heavy dependence of P-values on sample size. Although the recently proposed principal component analysis (PCA) and tensor decomposition (TD)-based unsupervised feature extraction (FE) has often outperformed these statistical test-based methods, the reason why they worked so well is unclear. In this study, we aim to understand this reason in the context of projection pursuit (PP) that was proposed a long time ago to solve the problem of dimensions; we can relate the space spanned by singular value vectors with that spanned by the optimal cluster centroids obtained from K-means. Thus, the success of PCA- and TD-based unsupervised FE can be understood by this equivalence. In addition to this, empirical threshold adjusted P-values of 0.01 assuming the null hypothesis that singular value vectors attributed to genes obey the Gaussian distribution empirically corresponds to threshold-adjusted P-values of 0.1 when the null distribution is generated by gene order shuffling. For this purpose, we newly applied PP to the three data sets to which PCA and TD based unsupervised FE were previously applied; these data sets treated two topics, biomarker identification for kidney cancers (the first two) and the drug discovery for COVID-19 (the thrid one). Then we found the coincidence between PP and PCA or TD based unsupervised FE is pretty well. Shuffling procedures described above are also successfully applied to these three data sets. These findings thus rationalize the success of PCA- and TD-based unsupervised FE for the first time.

A modified vaccinia Ankara vector-based vaccine protects macaques from SARS-CoV-2 infection, immune pathology, and dysfunction in the lungs.

A combination of vaccination approaches will likely be necessary to fully control the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Here, we show that modified vaccinia Ankara (MVA) vectors expressing membrane-anchored pre-fusion stabilized spike (MVA/S) but not secreted S1 induced strong neutralizing antibody responses against SARS-CoV-2 in mice. In macaques, the MVA/S vaccination induced strong neutralizing antibodies and CD8+ T cell responses, and conferred protection from SARS-CoV-2 infection and virus replication in the lungs as early as day 2 following intranasal and intratracheal challenge. Single-cell RNA sequencing analysis of lung cells on day 4 after infection revealed that MVA/S vaccination also protected macaques from infection-induced inflammation and B cell abnormalities and lowered induction of interferon-stimulated genes. These results demonstrate that MVA/S vaccination induces neutralizing antibodies and CD8+ T cells in the blood and lungs and is a potential vaccine candidate for SARS-CoV-2.

Monitoring Viral Entry in Real-Time Using a Luciferase Recombinant Vesicular Stomatitis Virus Producing SARS-CoV-2, EBOV, LASV, CHIKV, and VSV Glycoproteins.

Viral entry is the first stage in the virus replication cycle and, for enveloped viruses, is mediated by virally encoded glycoproteins. Viral glycoproteins have different receptor affinities and triggering mechanisms. We employed vesicular stomatitis virus (VSV), a BSL-2 enveloped virus that can incorporate non-native glycoproteins, to examine the entry efficiencies of diverse viral glycoproteins. To compare the glycoprotein-mediated entry efficiencies of VSV glycoprotein (G), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S), Ebola (EBOV) glycoprotein (GP), Lassa (LASV) GP, and Chikungunya (CHIKV) envelope (E) protein, we produced recombinant VSV (rVSV) viruses that produce the five glycoproteins. The rVSV virions encoded a nano luciferase (NLucP) reporter gene fused to a destabilization domain (PEST), which we used in combination with the live-cell substrate EndurazineTM to monitor viral entry kinetics in real time. Our data indicate that rVSV particles with glycoproteins that require more post-internalization priming typically demonstrate delayed entry in comparison to VSV G. In addition to determining the time required for each virus to complete entry, we also used our system to evaluate viral cell surface receptor preferences, monitor fusion, and elucidate endocytosis mechanisms. This system can be rapidly employed to examine diverse viral glycoproteins and their entry requirements.

OMA orthology in 2021: website overhaul, conserved isoforms, ancestral gene order and more.

OMA is an established resource to elucidate evolutionary relationships among genes from currently 2326 genomes covering all domains of life. OMA provides pairwise and groupwise orthologs, functional annotations, local and global gene order conservation (synteny) information, among many other functions. This update paper describes the reorganisation of the database into gene-, group- and genome-centric pages. Other new and improved features are detailed, such as reporting of the evolutionarily best conserved isoforms of alternatively spliced genes, the inferred local order of ancestral genes, phylogenetic profiling, better cross-references, fast genome mapping, semantic data sharing via RDF, as well as a special coronavirus OMA with 119 viruses from the Nidovirales order, including SARS-CoV-2, the agent of the COVID-19 pandemic. We conclude with improvements to the documentation of the resource through primers, tutorials and short videos. OMA is accessible at https://omabrowser.org.

How the COVID-19 Overcomes the Battle? An Approach to Virus Structure.

Coronaviruses primarily cause zoonotic infections, however in the past few decades several interspecies transmissions have occurred, the last one by SARS-CoV-2, causing COVID-19 pandemic, posing serious threat to global health. The SARS-CoV-2 spike (S) protein plays an important role in viral attachment, fusion and entry. However, other structural and non-structural SARS-CoV-2 proteins are potential influencers in virus pathogenicity. Among these proteins; Orf3, Orf8, and Orf10 show the least homology to SARSCoV proteins and therefore should be further studied for their abilities to modulate antiviral and inflammatory responses. Here, we discuss how SARS-COV-2 interacts with our immune system.