Bioinformatics Workflow for Gonococcal Proteomics

Abstract

High-throughput quantitative proteomics unravels secrets of Neisseria gonorrhoeae biology by profiling proteome responses to environmental and endogenous cues and opens translational research paths through identification of vaccine candidates, drug targets/virulence factors, and biomarkers. Bioinformatics tools and databases are indispensable for downstream analysis of proteomic datasets to generate biologically meaningful outcomes. In this chapter, we present a workflow for proteomic data analysis with emphasis on publicly available resources, software systems, and tools that predict protein subcellular localization (CELLO, PSORTb v3.0, SOSUI-GramN, SignalP 4.1, LipoP 1.0, TMHMM 2.0) and functional annotation (EggNOG-mapper 4.5.1., DAVID v6.8, and KEGG) of N. gonorrhoeae proteins. This computational step-by-step procedure may help to foster new hypotheses and to provide insights into the structure–function relationship of proteins.