Abstract
Eight Assemblage A strains from the protozoan parasite Giardia duodenalis were analysed using label-free quantitative shotgun proteomics, to evaluate inter- and intra-assemblage variation and complement available genetic and transcriptomic data. Isolates were grown in biological triplicate in axenic culture, and protein extracts were subjected to in-solution digest and online fractionation using Gas Phase Fractionation (GPF). Recent reclassification of genome databases for subassemblages was evaluated for database-dependent loss of information, and proteome composition of different isolates was analysed for biologically relevant assemblage-independent variation. The data from this study are related to the research article “Quantitative proteomics analysis of Giardia duodenalis Assemblage A – a baseline for host, assemblage and isolate variation” published in Proteomics (Emery et al., 2015 [1]).
Highlights
Eight Assemblage A strains from the protozoan parasite Giardia duodenalis were analysed using label-free quantitative shotgun proteomics, to evaluate inter- and intra-assemblage variation and complement available genetic and transcriptomic data
Isolates were grown in biological triplicate in axenic culture, and protein extracts were subjected to in-solution digest and online fractionation using Gas Phase Fractionation (GPF)
Recent reclassification of genome databases for subassemblages was evaluated for databasedependent loss of information, and proteome composition of different isolates was analysed for biologically relevant assemblage-independent variation
Summary
Data from a proteomic baseline study of Assemblage A in Giardia duodenalis Eight Assemblage A strains from the protozoan parasite Giardia duodenalis were analysed using label-free quantitative shotgun proteomics, to evaluate inter- and intra-assemblage variation and complement available genetic and transcriptomic data. Isolates were grown in biological triplicate in axenic culture, and protein extracts were subjected to in-solution digest and online fractionation using Gas Phase Fractionation (GPF).
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