Evaluation of Parallel Accumulation-Serial Fragmentation methods for metaproteomics using a model microbiome

Abstract

We present a multi-organism, ground-truth metaproteomic dataset generated using data-dependent acquisition Parallel Accumulation-Serial Fragmentation (ddaPASEF) and data-independent acquisition (diaPASEF) on a trapped ion mobility mass spectrometer. The dataset comprises 28 species (30 strains) spanning Archaea, Bacteria, Eukarya, and bacteriophages, assembled into an uneven mock community with a 400-fold dynamic range of organismal abundance. Four biological replicates were processed using a standardized sample preparation workflow and analyzed using described LC-MS conditions. Raw data, search outputs, protein coverage metrics, quantitative abundance estimates, and strain-specific peptide evidence are provided. The dataset enables evaluation of proteome depth, proteome coverage, quantitative reproducibility, and strain-level resolution across acquisition strategies. diaPASEF yielded broader peptide and protein detection and deeper sequence coverage, while both methods accurately quantified high-abundance organisms. Detection evidence for low-abundance bacteriophages and single-amino-acid-variant peptides is included to support benchmarking of taxonomic and strain-resolved analyses. This dataset provides a comprehensive reference for developing and validating metaproteomic workflows, protein inference strategies, and ion mobility-aware computational tools.