Reusable tutorials for using cloud-based computing environments for the analysis of bacterial gene expression data from bulk RNA sequencing.

This manuscript describes the development of a resource module that is part of a learning platform named "NIGMS Sandbox for Cloud-based Learning" https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox at the beginning of this Supplement. This module delivers learning materials on RNA sequencing (RNAseq) data analysis in an interactive format that uses appropriate cloud resources for data access and analyses. Biomedical research is increasingly data-driven, and dependent upon data management and analysis methods that facilitate rigorous, robust, and reproducible research. Cloud-based computing resources provide opportunities to broaden the application of bioinformatics and data science in research. Two obstacles for researchers, particularly those at small institutions, are: (i) access to bioinformatics analysis environments tailored to their research; and (ii) training in how to use Cloud-based computing resources. We developed five reusable tutorials for bulk RNAseq data analysis to address these obstacles. Using Jupyter notebooks run on the Google Cloud Platform, the tutorials guide the user through a workflow featuring an RNAseq dataset from a study of prophage altered drug resistance in Mycobacterium chelonae. The first tutorial uses a subset of the data so users can learn analysis steps rapidly, and the second uses the entire dataset. Next, a tutorial demonstrates how to analyze the read count data to generate lists of differentially expressed genes using R/DESeq2. Additional tutorials generate read counts using the Snakemake workflow manager and Nextflow with Google Batch. All tutorials are open-source and can be used as templates for other analysis.

Color-Flu Fluorescent Reporter Influenza A Viruses Allow for In Vivo Studies of Innate Immune Function in Zebrafish.

Influenza virus infection can cause severe respiratory disease and is estimated to cause millions of illnesses annually. Studies on the contribution of the innate immune response to influenza A virus (IAV) to viral pathogenesis may yield new antiviral strategies. Zebrafish larvae are useful models for studying the innate immune response to pathogens, including IAV, in vivo. Here, we demonstrate how Color-flu, four fluorescent IAV strains originally developed for mice, can be used to study the host response to infection by simultaneously monitoring infected cells, neutrophils, and macrophages in vivo. Using this model, we show how the angiotensin-converting enzyme inhibitor, ramipril, and mitophagy inhibitor, MDIVI-1, improved survival, decreased viral burden, and improved the respiratory burst response to IAV infection. The Color-flu zebrafish larvae model of IAV infection is complementary to other models where the dynamics of infection and the response of innate immune cells can be visualized in a transparent host in vivo.

Conserved sequence features in intracellular domains of viral spike proteins.

Viral spike proteins mutate frequently, but conserved features within these proteins often have functional importance and can inform development of anti-viral therapies which circumvent the effects of viral sequence mutations. Through analysis of large numbers of viral spike protein sequences from several viral families, we found highly (>99%) conserved patterns within their intracellular domains. The patterns generally consist of one or more basic amino acids (arginine or lysine) adjacent to a cysteine, many of which are known to undergo acylation. These patterns were not enriched in cellular proteins in general. Molecular dynamics simulations show direct electrostatic and hydrophobic interactions between these conserved residues in hemagglutinin (HA) from influenza A and B and the phosphoinositide PIP2. Super-resolution microscopy shows nanoscale colocalization of PIP2 and several of the same viral proteins. We propose the hypothesis that these conserved viral spike protein features can interact with phosphoinositides such as PIP2.

Remarkably High Repeat Content in the Genomes of Sparrows: The Importance of Genome Assembly Completeness for Transposable Element Discovery.

Transposable elements (TE) play critical roles in shaping genome evolution. Highly repetitive TE sequences are also a major source of assembly gaps making it difficult to fully understand the impact of these elements on host genomes. The increased capacity of long-read sequencing technologies to span highly repetitive regions promises to provide new insights into patterns of TE activity across diverse taxa. Here we report the generation of highly contiguous reference genomes using PacBio long-read and Omni-C technologies for three species of Passerellidae sparrow. We compared these assemblies to three chromosome-level sparrow assemblies and nine other sparrow assemblies generated using a variety of short- and long-read technologies. All long-read based assemblies were longer (range: 1.12 to 1.41 Gb) than short-read assemblies (0.91 to 1.08 Gb) and assembly length was strongly correlated with the amount of repeat content. Repeat content for Bell's sparrow (31.2% of genome) was the highest level ever reported within the order Passeriformes, which comprises over half of avian diversity. The highest levels of repeat content (79.2% to 93.7%) were found on the W chromosome relative to other regions of the genome. Finally, we show that proliferation of different TE classes varied even among species with similar levels of repeat content. These patterns support a dynamic model of TE expansion and contraction even in a clade where TEs were once thought to be fairly depauperate and static. Our work highlights how the resolution of difficult-to-assemble regions of the genome with new sequencing technologies promises to transform our understanding of avian genome evolution.