ABSTRACT: Search Engine for Antimicrobial Resistance: a cloud compatible pipeline and web interface for rapidly detecting antimicrobial resistance genes directly from sequence data
Project description:Here we designed a search-engine for single-cell epigenome profiles. We tested different application of search-engine using different data-sets including mESC scATAC-seq profile.
Project description:Mass spectrometry is a central technique in glycomic analysis. However, there is no generic software tool for automated, confident analysis of tandem-mass spectrometry based glycomic data. Here, we propose GlycoNote – a generic and reliable search engine for tandem-mass spectrometry based glycomics. A false discovery rate analysis based on iterative decoy searching was specifically designed for glycomic data analysis. We apply GlycoNote to the analyses of distinct glycomic samples, including human milk oligosaccharides, N/O-glycome from human cell line and polysaccharides from plant. To further demonstrate the general utility of GlycoNote, automated analyses of nonnative glycomes (N-glycome labeled with aniline and permethylated N-glycome) or atypical glycans (O-glycome with N-acetylneuraminic acid / N-glycome from C. elegans) were performed. More importantly, an open-search mode was introduced for the elucidation of component heterogeneity in samples. GlycoNote could be an important tool in the rapidly growing efforts toward comprehensive glycomic analysis.
Project description:A cross linking mass spectrometry search engine was developed and implemented into Thermo Proteome Discoverer. The search engine is capable to handle several linker types as well as data input formats. To demonstrate its ability processing Bruker -ion mobility data, synthetic peptides (Beveridge, et. al., Nat. Commun., 2020, doi: 10.1038/s41467-020-14608-2) were analyzed and the respective files are availible here.
Project description:Discovery of human leukocyte antigen (HLA) class I presented peptides of bacterial origin is essential to discover bacterial antigen targets as putative vaccine constituents. However, reliable identification of such HLA-presented bacterial epitopes are extremely low abundant compared to the host proteome. Here, we describe an upgraded bioinformatical workflow to enhance the confident detection of bacterial immunopeptides. Re-analysis of Listeria monocytogenes (Listeria)-infected cell cultures was searched by four search engines in parallel with follow-up by rescoring by MS2Rescore and integration of all search results. Boosting identification by both rescoring and integration, this delivered an additional 18 Listeria peptides (+26.5%) matching 15 different proteins (+35.7%) compared to the initial analysis. Moreover, conflicts between search engine results uncovered ambiguities in spectra-to-peptide assignments, in some cases with spectra assigned to human and Listeria peptides. Finally, we demonstrate how our workflow is compatible with timsTOF data acquisition, incorporating rescoring of ion mobility features using TIMS2Rescore.
Project description:Processing of the dataset of synthetic phosphopeptides by Savitzki et al. (MCP, 2011) using multiple search engines. Establishment of the D-score: a search engine independent MD-score.