Influenza Research Database: An integrated bioinformatics resource for influenza virus research

The Influenza Research Database (IRD) is a U.S. National Institute of Allergy and Infectious Diseases (NIAID)-sponsored Bioinformatics Resource Center dedicated to providing bioinformatics support for influenza virus research. IRD facilitates the research and development of vaccines, diagnostics and therapeutics against influenza virus by providing a comprehensive collection of influenza-related data integrated from various sources, a growing suite of analysis and visualization tools for data mining and hypothesis generation, personal workbench spaces for data storage and sharing, and active user community support. Here, we describe the recent improvements in IRD including the use of cloud and high performance computing resources, analysis and visualization of user-provided sequence data with associated metadata, predictions of novel variant proteins, annotations of phenotype-associated sequence markers and their predicted phenotypic effects, hemagglutinin (HA) clade classifications, an automated tool for HA subtype numbering conversion, linkouts to disease event data and the addition of host factor and antiviral drug components. All data and tools are freely available without restriction from the IRD website at https://www.fludb.org.National Institutes of Health/National Institute for Allergy and Infectious Diseases [HHSN272201400028C]. Funding for open access charge: J. Craig Venter Institute

Global Transcriptome Profiling of the Pine Shoot Beetle, Tomicus yunnanensis (Coleoptera: Scolytinae)

Background: The pine shoot beetle Tomicus yunnanensis (Coleoptera: Scolytinae) is an economically important pest of Pinus yunnanensis in southwestern China. Developed resistance to insecticides due to chemical pesticides being used for a long time is a factor involved in its serious damage, which poses a challenge for management. In addition, highly efficient adaptation to divergent environmental ecologies results in this pest posing great potential threat to pine forests. However, the molecular mechanisms remain unknown as only limited nucleotide sequence data for this species is available. Methodology/Principal Findings: In this study, we applied next generation sequencing (Illumina sequencing) to sequence the adult transcriptome of T. yunnanensis. A total of 51,822,230 reads were obtained. They were assembled into 140,702 scaffolds, and 60,031 unigenes. The unigenes were further functionally annotated with gene descriptions, Gene Ontology (GO), Clusters of Orthologous Groups (COG), and Kyoto Encyclopedia of Genes and Genome (KEGG). In total, 80,932 unigenes were classified into GO, 13,599 unigenes were assigned to COG, and 33,875 unigenes were found in KO categories. A biochemical pathway database containing 219 predicted pathways was also created based on the annotations. In depth analysis of the data revealed a large number of genes related to insecticides resistance and heat shock protein genes associated with environmental stress. Conclusions/Significance: The results facilitate the investigations of molecular resistance mechanisms to insecticides an

Why proteins without an α-crystallin domain should not be included in the human small heat shock protein family HSPB

The presence of an α-crystallin domain documents the evolutionary relatedness of the ubiquitous family of small heat shock proteins. Sequence and three-dimensional structure provide no evidence for the presence of such a domain in HSPC034, recently proposed as the 11th member of the human HSPB family. Also, phylogenetic analyses detect no relationship between HSPC034 and the human HSPB1–10 sequences. Arguments are provided as to why inclusion in the HSPB family of proteins like HSPC034, which resemble small heat shock proteins in being heat-inducible and having chaperone-like properties and a low monomeric mass, but are evolutionarily unrelated, is misleading and confusing

SARS-CoV-2 infection of the oral cavity and saliva

Despite signs of infection-including taste loss, dry mouth and mucosal lesions such as ulcerations, enanthema and macules-the involvement of the oral cavity in coronavirus disease 2019 (COVID-19) is poorly understood. To address this, we generated and analyzed two single-cell RNA sequencing datasets of the human minor salivary glands and gingiva (9 samples, 13,824 cells), identifying 50 cell clusters. Using integrated cell normalization and annotation, we classified 34 unique cell subpopulations between glands and gingiva. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral entry factors such as ACE2 and TMPRSS members were broadly enriched in epithelial cells of the glands and oral mucosae. Using orthogonal RNA and protein expression assessments, we confirmed SARS-CoV-2 infection in the glands and mucosae. Saliva from SARS-CoV-2-infected individuals harbored epithelial cells exhibiting ACE2 and TMPRSS expression and sustained SARS-CoV-2 infection. Acellular and cellular salivary fractions from asymptomatic individuals were found to transmit SARS-CoV-2 ex vivo. Matched nasopharyngeal and saliva samples displayed distinct viral shedding dynamics, and salivary viral burden correlated with COVID-19 symptoms, including taste loss. Upon recovery, this asymptomatic cohort exhibited sustained salivary IgG antibodies against SARS-CoV-2. Collectively, these data show that the oral cavity is an important site for SARS-CoV-2 infection and implicate saliva as a potential route of SARS-CoV-2 transmission

Conserved cell types with divergent features in human versus mouse cortex.

Elucidating the cellular architecture of the human cerebral cortex is central to understanding our cognitive abilities and susceptibility to disease. Here we used single-nucleus RNA-sequencing analysis to perform a comprehensive study of cell types in the middle temporal gyrus of human cortex. We identified a highly diverse set of excitatory and inhibitory neuron types that are mostly sparse, with excitatory types being less layer-restricted than expected. Comparison to similar mouse cortex single-cell RNA-sequencing datasets revealed a surprisingly well-conserved cellular architecture that enables matching of homologous types and predictions of properties of human cell types. Despite this general conservation, we also found extensive differences between homologous human and mouse cell types, including marked alterations in proportions, laminar distributions, gene expression and morphology. These species-specific features emphasize the importance of directly studying human brain