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An approach to integrate metagenomics, metatranscriptomics and metaproteomics data in public resources
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  • Shengbo Wang,
  • Satwant Kaur,
  • Benoit J. Kunath,
  • Patrick May,
  • Lorna Richardson,
  • Paul Wilmes,
  • Robert D. Finn,
  • Juan Antonio Vizcaino
Shengbo Wang
European Bioinformatics Institute
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Satwant Kaur
European Bioinformatics Institute
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Benoit J. Kunath
University of Luxembourg
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Patrick May
University of Luxembourg
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Lorna Richardson
European Bioinformatics Institute
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Paul Wilmes
University of Luxembourg
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Robert D. Finn
European Bioinformatics Institute
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Juan Antonio Vizcaino
European Bioinformatics Institute

Corresponding Author:juan@ebi.ac.uk

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Abstract

The availability of public metaproteomics, metagenomics and metatranscriptomics data in public resources such as MGnify (for metagenomics/metatranscriptomics) and the PRIDE database (for metaproteomics), continues to increase. When these omics techniques are applied to the same samples, their integration offers new opportunities to understand the structure (metagenome) and functional expression (metatranscriptome and metaproteome) of the microbiome. Here, we describe a pilot study aimed at integrating public multi-meta-omics datasets from studies based on human gut and marine hatchery samples. Reference search databases (search DBs) were built using assembled metagenomic (and metatranscriptomic, where available) sequence data followed by de novo gene calling, using both data from the same sampling event and from independent samples. The resulting protein sets were evaluated for their utility in metaproteomics analysis. In agreement with previous studies, the highest number of peptide identifications was generally obtained when using search DBs created from the same samples. Data integration of the multi-omics results was performed in MGnify. For that purpose, the MGnify website was extended to enable the visualisation of the resulting peptide/protein information from three reanalysed metaproteomics datasets. A workflow (https://github.com/PRIDE-reanalysis/MetaPUF) has been developed allowing researchers to perform equivalent data integration, using paired multi-omics datasets. This is the first time that a data integration approach for multi-omics datasets has been implemented from public data available in the world-leading MGnify and PRIDE databases.
03 Jan 2025Submitted to PROTEOMICS
07 Jan 2025Submission Checks Completed
07 Jan 2025Assigned to Editor
07 Jan 2025Review(s) Completed, Editorial Evaluation Pending
10 Jan 2025Reviewer(s) Assigned