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MassIVE MSV000089620 - Critical Assessment of MetaProteome Investigation (CAMPI): A multi-lab comparison of established workflows

  • Metaproteomics, the study of the collective proteome within a microbial ecosystem, has substantially grown over the past few years. This growth comes from the increased awareness that it can powerfully supplement metagenomics and metatranscriptomics analyses. Although metaproteomics is more challenging than single-species proteomics, its added value has already been demonstrated in various biosystems, such as gut microbiomes or biogas plants. Because of the many challenges, a variety of metaproteomics workflows have been developed, yet it remains unclear what the impact of the choice of workflow is on the obtained results. Therefore, we set out to compare several well-established workflows in the first community-driven, multi-lab comparison in metaproteomics: the critical assessment of metaproteome investigation (CAMPI) study. In this benchmarking study, we evaluated the influence of different workflows on sample preparation, mass spectrometry acquisition, and bioinformatic analysis onMetaproteomics, the study of the collective proteome within a microbial ecosystem, has substantially grown over the past few years. This growth comes from the increased awareness that it can powerfully supplement metagenomics and metatranscriptomics analyses. Although metaproteomics is more challenging than single-species proteomics, its added value has already been demonstrated in various biosystems, such as gut microbiomes or biogas plants. Because of the many challenges, a variety of metaproteomics workflows have been developed, yet it remains unclear what the impact of the choice of workflow is on the obtained results. Therefore, we set out to compare several well-established workflows in the first community-driven, multi-lab comparison in metaproteomics: the critical assessment of metaproteome investigation (CAMPI) study. In this benchmarking study, we evaluated the influence of different workflows on sample preparation, mass spectrometry acquisition, and bioinformatic analysis on two samples: a simplified, lab-assembled human intestinal sample and a complex human fecal sample. We find that the same overall biological meaning can be inferred from the metaproteome data, regardless of the chosen workflow. Indeed, taxonomic and functional annotations were very similar across all sample-specific data sets. Moreover, this outcome was consistent regardless of whether protein groups or peptides, or differences at the spectrum or peptide level were used to infer these annotations. Where differences were observed, those originated primarily from different wet-lab methods rather than from different bioinformatic pipelines. The CAMPI study thus provides a solid foundation for benchmarking metaproteomics workflows, and will therefore be a key reference for future method improvement. [doi:10.25345/C5SX64D9M] [dataset license: CC0 1.0 Universal (CC0 1.0)]zeige mehrzeige weniger

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Metadaten
Autor*innen:Thilo MuthORCiD
Dokumenttyp:Forschungsdatensatz
Veröffentlichungsform:Graue Literatur
Sprache:Englisch
Titel des übergeordneten Werkes (Englisch):MassIVE (Mass Spectrometry Interactive Virtual Environment)
Jahr der Erstveröffentlichung:2021
Organisationseinheit der BAM:VP Vizepräsident
VP Vizepräsident / VP.1 eScience
Herausgeber (Institution):Bundesanstalt für Materialforschung und -prüfung (BAM)
Verlag:University of California
Verlagsort:San Diego
DDC-Klassifikation:Naturwissenschaften und Mathematik / Chemie / Analytische Chemie
Freie Schlagwörter:Benchmarking; Data set
Themenfelder/Aktivitätsfelder der BAM:Chemie und Prozesstechnik
Art der Ressource:Datensatz
DOI:10.25345/c5sx64d9m
Zugehöriger Identifikator:https://nbn-resolving.org/urn:nbn:de:kobv:b43-541220
Beschreibung der Datei(en) :Data set on Mass Spectrometry Interactive Virtual Environment (MassIVE ID: MSV000089620)
Verfügbarkeit des Dokuments:Datei für die Öffentlichkeit verfügbar ("Open Access")
Lizenz (Deutsch):License LogoCreative Commons - CC0 1.0 - Universell - Public Domain Dedication
Datum der Freischaltung:17.08.2023
Referierte Publikation:Nein
Schriftenreihen ohne Nummerierung:Forschungsdatensätze der BAM
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