"METAGENOTE: a simplified web platform for metadata annotation of genomic samples and streamlined submission to NCBI's sequence read archive".

BACKGROUND: The improvements in genomics methods coupled with readily accessible high-throughput sequencing have contributed to our understanding of microbial species, metagenomes, infectious diseases and more. To maximize the impact of these genomics studies, it is important that data from biological samples will become publicly available with standardized metadata. The availability of data at public archives provides the hope that greater insights could be obtained through integration with multi-omics data, reproducibility of published studies, or meta-analyses of large diverse datasets. These datasets should include a description of the host, organism, environmental source of the specimen, spatial-temporal information and other relevant metadata, but unfortunately these attributes are often missing and when present, they show inconsistencies in the use of metadata standards and ontologies. RESULTS: METAGENOTE ( https://metagenote.niaid.nih.gov ) is a web portal that greatly facilitates the annotation of samples from genomic studies and streamlines the submission process of sequencing files and metadata to the Sequence Read Archive (SRA) (Leinonen R, et al, Nucleic Acids Res, 39:D19-21, 2011) for public access. This platform offers a wide selection of packages for different types of biological and experimental studies with a special emphasis on the standardization of metadata reporting. These packages follow the guidelines from the MIxS standards developed by the Genomics Standard Consortium (GSC) and adopted by the three partners of the International Nucleotides Sequencing Database Collaboration (INSDC) (Cochrane G, et al, Nucleic Acids Res, 44:D48-50, 2016) - National Center for Biotechnology Information (NCBI), European Bioinformatics Institute (EBI) and the DNA Data Bank of Japan (DDBJ). METAGENOTE then compiles, validates and manages the submission through an easy-to-use web interface minimizing submission errors and eliminating the need for submitting sequencing files via a separate file transfer mechanism. CONCLUSIONS: METAGENOTE is a public resource that focuses on simplifying the annotation and submission process of data with its corresponding metadata. Users of METAGENOTE will benefit from the easy to use annotation interface but most importantly will be encouraged to publish metadata following standards and ontologies that make the public data available for reuse.

Nephele: a cloud platform for simplified, standardized and reproducible microbiome data analysis.

Motivation: Widespread interest in the study of the microbiome has resulted in data proliferation and the development of powerful computational tools. However, many scientific researchers lack the time, training, or infrastructure to work with large datasets or to install and use command line tools. Results: The National Institute of Allergy and Infectious Diseases (NIAID) has created Nephele, a cloud-based microbiome data analysis platform with standardized pipelines and a simple web interface for transforming raw data into biological insights. Nephele integrates common microbiome analysis tools as well as valuable reference datasets like the healthy human subjects cohort of the Human Microbiome Project (HMP). Nephele is built on the Amazon Web Services cloud, which provides centralized and automated storage and compute capacity, thereby reducing the burden on researchers and their institutions. Availability and implementation: https://nephele.niaid.nih.gov and https://github.com/niaid/Nephele. Contact: darrell.hurt@nih.gov.

The Papillomavirus Episteme: a major update to the papillomavirus sequence database.

The Papillomavirus Episteme (PaVE) is a database of curated papillomavirus genomic sequences, accompanied by web-based sequence analysis tools. This update describes the addition of major new features. The papillomavirus genomes within PaVE have been further annotated, and now includes the major spliced mRNA transcripts. Viral genes and transcripts can be visualized on both linear and circular genome browsers. Evolutionary relationships among PaVE reference protein sequences can be analysed using multiple sequence alignments and phylogenetic trees. To assist in viral discovery, PaVE offers a typing tool; a simplified algorithm to determine whether a newly sequenced virus is novel. PaVE also now contains an image library containing gross clinical and histopathological images of papillomavirus infected lesions. Database URL: https://pave.niaid.nih.gov/.

NEP: web server for epitope prediction based on antibody neutralization of viral strains with diverse sequences.

Delineation of the antigenic site, or epitope, recognized by an antibody can provide clues about functional vulnerabilities and resistance mechanisms, and can therefore guide antibody optimization and epitope-based vaccine design. Previously, we developed an algorithm for antibody-epitope prediction based on antibody neutralization of viral strains with diverse sequences and validated the algorithm on a set of broadly neutralizing HIV-1 antibodies. Here we describe the implementation of this algorithm, NEP (Neutralization-based Epitope Prediction), as a web-based server. The users must supply as input: (i) an alignment of antigen sequences of diverse viral strains; (ii) neutralization data for the antibody of interest against the same set of antigen sequences; and (iii) (optional) a structure of the unbound antigen, for enhanced prediction accuracy. The prediction results can be downloaded or viewed interactively on the antigen structure (if supplied) from the web browser using a JSmol applet. Since neutralization experiments are typically performed as one of the first steps in the characterization of an antibody to determine its breadth and potency, the NEP server can be used to predict antibody-epitope information at no additional experimental costs. NEP can be accessed on the internet at http://exon.niaid.nih.gov/nep.

Hot money: Illuminating the financing of high-carbon infrastructure in the developing world.

Major infrastructure financiers will have to significantly decarbonize their investments to meet mounting promises to cut carbon emissions to "net-zero" by mid-century. We provide new details about those needed shifts. Using two World Bank databases of infrastructure projects throughout the developing world, and applying a methodology for imputing the projects' likely future carbon output, we assess the emissions profile of power-plant projects executed from 2018 through 2020 - the three years immediately preceding the spate of net-zero pledges. We find that approximately half the generation executed in those years is too carbon-intensive to align with keeping Earth's average temperature from exceeding 1.5°C above pre-industrial levels, largely because of the prevalence of new natural-gas-fired power plants. We also find new evidence of host countries' agency in shaping carbon trajectories: Much of the climate-misaligned financing is not foreign but domestic. And we find different institutions are financing infrastructure portfolios with significantly differing carbon intensities.