Microbiomes, defined by communities of microorganisms, have emerged as significant contributors to broad areas of life, such as human health, agriculture, pollution remediation, and bioenergy production. While mass spectrometry (MS)-based metaproteomics provides direct insight into the functions performed by microbial community members, the simultaneous analysis of hundreds to thousands of proteomes presents challenges distinct from those of single-organism proteomics. The complexity and wide dynamic abundance range of microbial community samples require analysis methods capable of identifying and quantifying the low-abundance, taxon-specific peptides that are necessary for revealing taxon-function relationships. The newest generation of MS platforms, such as the asymmetric track lossless (Astral) analyzer system, offers advances in speed and sensitivity that could greatly enhance metaproteomic studies. However, a systematic evaluation of metaproteome analysis of a defined microbial community using the Astral has not been previously described. To this end, we leveraged a taxonomic ground-truth microbial community comprising 30 organisms spanning a wide dynamic abundance range to benchmark performance. We evaluated the depth, precision, and accuracy of data-independent acquisition (DIA)-MS analysis using the Astral, including an assessment of the value of high-field asymmetric waveform ion mobility spectrometry (FAIMS). Performance of the Astral was compared to that of an Orbitrap Fusion. Overall, the Astral improved depth and accuracy while maintaining acceptable precision. Operating in FAIMS mode mode increased peptide identifications while decreasing precision and throughput. Our results show the Astral to be a promising platform for the metaproteomic analysis of complex microbial communities comprising organisms across a large dynamic abundance range.
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Nightingale et al. (2026) studied this question.
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