Spectral entropy as a measure of the metaproteome complexity.

Autor: Duan H; School of Pharmaceutical Sciences, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada.; Ottawa Institute of Systems Biology, University of Ottawa, Ottawa, Ontario, Canada., Ning Z; School of Pharmaceutical Sciences, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada.; Ottawa Institute of Systems Biology, University of Ottawa, Ottawa, Ontario, Canada., Zhang A; School of Pharmaceutical Sciences, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada.; Ottawa Institute of Systems Biology, University of Ottawa, Ottawa, Ontario, Canada., Figeys D; School of Pharmaceutical Sciences, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada.; Ottawa Institute of Systems Biology, University of Ottawa, Ottawa, Ontario, Canada.
Jazyk: angličtina
Zdroj: Proteomics [Proteomics] 2024 Aug; Vol. 24 (16), pp. e2300570. Date of Electronic Publication: 2024 May 25.
DOI: 10.1002/pmic.202300570
Abstrakt: The diversity and complexity of the microbiome's genomic landscape are not always mirrored in its proteomic profile. Despite the anticipated proteomic diversity, observed complexities of microbiome samples are often lower than expected. Two main factors contribute to this discrepancy: limitations in mass spectrometry's detection sensitivity and bioinformatics challenges in metaproteomics identification. This study introduces a novel approach to evaluating sample complexity directly at the full mass spectrum (MS1) level rather than relying on peptide identifications. When analyzing under identical mass spectrometry conditions, microbiome samples displayed significantly higher complexity, as evidenced by the spectral entropy and peptide candidate entropy, compared to single-species samples. The research provides solid evidence for the complexity of microbiome in proteomics indicating the optimization potential of the bioinformatics workflow.
(© 2024 The Author(s). Proteomics published by Wiley‐VCH GmbH.)
Databáze: MEDLINE
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