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

Mass spectrometry-based metaproteomics allows for the identification and quantification of thousands of proteins from clinical and environmental samples and is rapidly gaining importance in microbiome sciences. Metaproteomics researchers can measure taxonomic and functional abundances of microbiomes, shedding light on mechanistic details of microbiome interactions with their environment. However, metaproteomic analysis suffers from limited depth of coverage due to the presence of millions of peptides at lower abundance levels. Recent advances in data-independent acquisition mass spectrometry coupled with Parallel Accumulation-Serial Fragmentation (PASEF) technology offer improved depth of coverage. PASEF technology enables simultaneous accumulation of ions from multiple co-eluting peptides by combining ion mobility separation with dynamic quadrupole isolation, allowing efficient and selective fragmentation in a single scan. This boosts ion sampling efficiency and resolves overlapping signals with high sensitivity. In this study, we assessed proteome coverage, quantitative precision, and accuracy of Data-dependent acquisition (DDA) and Data-independent acquisition (DIA) methods coupled with the PASEF method. For this, we used a ground-truth mock community containing 28 species (30 strains) from all three domains of life and bacteriophages with a 400-fold dynamic range of organism abundance. Our results showed that diaPASEF demonstrated superior performance, identifying 168% more peptide precursors, 155% more peptides, and 66% more protein groups compared to ddaPASEF. Quantitative measurements showed improved precision with diaPASEF, with 26 out of 28 organisms exhibiting coefficient of variation values below 20%, compared to 24 organisms with ddaPASEF. Both ddaPASEF and diaPASEF methods accurately quantified the 22 most abundant organisms, while measurements of low-abundance bacteriophages showed significant deviation from expected values. Our findings demonstrate that diaPASEF provides enhanced depth of coverage and quantitative reliability for metaproteomics analysis, particularly beneficial for clinical and environmental microbiome studies where deeper functional characterization is essential. This study provides valuable benchmark data to facilitate the development of advanced bioinformatic methods for quantitative metaproteomics.