Protein Sequence Annotation Tool (PSAT): a centralized web-based meta-server for high-throughput sequence annotations

Journal Article · Wed Jan 20 04:00:00 UTC 2016 · BMC Bioinformatics

DOI: https://doi.org/10.1186/s12859-016-0887-y · OSTI ID:1618521

Leung, Elo; Huang, Amy; Cadag, Eithon; Montana, Aldrin; Soliman, Jan Lorenz; Zhou, Carol L. Ecale

Abstract Background Here we introduce the Protein Sequence Annotation Tool (PSAT), a web-based, sequence annotation meta-server for performing integrated, high-throughput, genome-wide sequence analyses. Our goals in building PSAT were to (1) create an extensible platform for integration of multiple sequence-based bioinformatics tools, (2) enable functional annotations and enzyme predictions over large input protein fasta data sets, and (3) provide a web interface for convenient execution of the tools. Results In this paper, we demonstrate the utility of PSAT by annotating the predicted peptide gene products of Herbaspirillum sp. strain RV1423, importing the results of PSAT into EC2KEGG, and using the resulting functional comparisons to identify a putative catabolic pathway, thereby distinguishing RV1423 from a well annotated Herbaspirillum species. This analysis demonstrates that high-throughput enzyme predictions, provided by PSAT processing, can be used to identify metabolic potential in an otherwise poorly annotated genome. Conclusions PSAT is a meta server that combines the results from several sequence-based annotation and function prediction codes, and is available at http://psat.llnl.gov/psat/ . PSAT stands apart from other sequence-based genome annotation systems in providing a high-throughput platform for rapid de novo enzyme predictions and sequence annotations over large input protein sequence data sets in FASTA. PSAT is most appropriately applied in annotation of large protein FASTA sets that may or may not be associated with a single genome.

• Sponsoring Organization: USDOE
• OSTI ID: 1618521
• Journal Information: BMC Bioinformatics, Journal Name: BMC Bioinformatics Journal Issue: 1 Vol. 17; ISSN 1471-2105
• Publisher: Springer Science + Business MediaCopyright Statement
• Country of Publication: United Kingdom
• Language: English