- Responding to Zika Virus Spread - 2016
- NIAID Bioinformatics Resources on the Front Line of Research Combatting Antimicrobial Resistance (AMR) - 2016
- Antiviral Resistance Data and Analysis in ViPR and IRD - 2016
- Support for FungiDB—October 2014
- Responding to the Ebola Outbreak—October 2014
The NIAID-funded ViPR Bioinformatics Resource Center launched a new Zika virus portal to provide quick access to bioinformatics tools and workbench for analysis of Zika virus data. New Zika sequences and additional associated metadata is retrieved, curated, and released on a weekly basis through ViPR. Immune epitope, gene, protein, and protein structure for information Zika virus is available through the ViPR website. The ViPR Scientific Team has coordinated with the JCVI sequencing center and international collaborators to gather and curate 90 complete Zika virus genome sequence from 22 countries.
The NIAID-funded VectorBase Bioinformatics Resource Center launched a new Zika virus portal to provide quick access to bioinformatics tools and data resources for analysis of Aedes aegypti and Aedes albopictus – the arthropod vectors for Zika virus transmission. Genome assemblies, mitochondrial genomes, and predicted gene sets are available for both species of mosquito along with tools aimed at the study of arthropod vectors.
NIAID Bioinformatics Resources on the Front Line of Research Combatting Antimicrobial Resistance (AMR)
To gain new insights into the acquisition, transmission, and mechanisms of antimicrobial resistance (AMR) researchers require advanced data analysis services and visualization tools. PATRIC, the NIAID-funded Bioinformatics Resource Center for bacterial pathogens has focused on the emerging needs to couple analysis and visualization tools with the analysis of AMR-related and other system-level omics data in a user-friendly manner to facilitate rapid characterization of clinical genomes and metagenomes.
PATRIC has focused AMR curation efforts to provide users with the ability to rapidly recognize and project unknown ARM genome features to new genomes in an automated fashion, and to use comparative genomics approaches for the discovery of new resistance mechanisms. All new AMR-related functions entered in the databases will be annotated with those functions in newly analyzed genomes, and annotations to genomes similar to PATRIC references will automatically include AMR annotations from the reference genome. These tools will enable the quick recognition of AMR-related functions in genomes analyzed through PATRIC and the use of comparative genomics approaches for the discovery of new mechanisms of resistance.
Most recently PATRIC has developed a machine learning based computational tool to predict AMR-related genomic features and phenotypes in Acinetobacter, Mycobacterium, Staphylococcus and Streptococcus. This work was published in Nature Scientific Reports in June 2016. This technique is the first step in moving beyond culture-based AMR detection techniques and may enable swifter clinical response and accelerate the identification and discovery of antibiotic resistance mechanisms. PATRIC Antibiotic Resistance Search
Antiviral Resistance Data and Analysis in ViPR and IRDThe Bioinformatics Resource Centers for Viruses and Influenza, ViPR and IRD, are developing a comprehensive infrastructure for antiviral drug data management and analysis. Antiviral drug data, including descriptive drug information, 3D structures for drug/protein target complexes, specific drug interaction sites, and antiviral resistance mutations, have been curated, integrated, and made accessible on the ViPR and IRD websites. Utilizing their Phenotypic Variant Type computational pipeline, ViPR/IRD has developed a novel sequence-based prediction tool for antiviral drug resistance. This tool annotates user-provided sequences with curated antiviral drug data to enable users to predict whether a viral strain is potentially sensitive or resistant to an antiviral drug. This prediction tool is available for Hepatitis C Virus, Picornaviridae, and Herpeseviridae. External link to the tool can be found here(link is external).
For more information on Bioinformatics Resource Centers, contact Dr. Alison Yao
EuPathDB has received funding through the NIAID Bioinformatics Resource Centers program to expand informatics support for Ascomycota, Basidiomycota, Zygomycota, and Chytrid fungal species. FungiDB, which uses the same infrastructure and user interface as EuPathDB, contains sequence and annotation for over 70 species including many human pathogens from the Coccidiodes and Cryptococcus genera. The range of organisms available through FungiDB are informative to many NIAID-supported researchers based on their phylogenetic position and/or experimental utility as model organisms, with extensive genomic and phenotyping data providing insight into pathogenic species.
There is more information at FungiDB.
The NIAID-funded ViPR Bioinformatics Resource Center launched a new Ebolavirus portal to provide quick access to bioinformatics tools and workbench for analysis of Ebolavirus data. New Ebolavirus sequences and additional associated metadata, including clinical phenotype data, will be retrieved, curated and released on a daily basis through ViPR. The ViPR Scientific Team conducted a genome sequence variation analysis using data available in ViPR from the 2014 outbreak to determine the sequence diversity and evolution of the Ebolavirus. For more information, please visit the Scientific Report.