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CAMPI

ABSTRACT: Critical Assessment of Metaproteome Investigation (CAMPI): a Multi-Lab Comparison of Established Workflows

PROVIDER: PRJEB42466 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	final.contigs.fasta.gz	Fasta.gz
	final.contigs.fasta.gz	Fasta.gz
	ERR5100215.fasta.gz	Fasta.gz
	ERR5235368.fasta.gz	Fasta.gz
	ERR5235286.fasta.gz	Fasta.gz

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Critical Assessment of Metaproteome Investigation (CAMPI): a Multi-Lab Comparison of Established Workflows

Project description: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 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.

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