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Updated: Sep 2, 2025

An Aquatic Microbial Metaproteomics Workflow: From Cells to Tryptic Peptides Suitable for Tandem Mass Spectrometry-based Analysis
Published on: September 15, 2015
FreshOmics: A manually curated and standardized -omics database for investigating freshwater microbiomes
Corinne Biderre-Petit1, Jean-Christophe Charvy1, Gisèle Bronner1
1CNRS, Laboratoire Microorganismes: Génome et Environnement, Université Clermont Auvergne, Clermont-Ferrand, France.
Abstract:
Freshwater is a critical resource for human survival but severely threatened by anthropogenic activities and climate change. These changes strongly impact the abundance and diversity of the microbial communities which are key players in the functioning of these aquatic ecosystems. Although widely documented since the emergence of high-throughput sequencing approaches, the information on these natural microbial communities is scattered among thousands of publications and it is therefore difficult to investigate the temporal dynamics and the spatial distribution of microbial taxa within or across ecosystems. To fill this gap and in the FAIR principles context we built a manually curated and standardized microbial freshwater -omics database (FreshOmics). Based on recognized ontologies (ENVO, MIMICS, GO, ISO), FreshOmics describes 29 different types of freshwater ecosystems and uses standardized attributes to depict biological samples, sequencing protocols and article attributes for more than 2487 geographical locations across 71 countries around the world. The database contains 24,808 sequence identifiers (i.e., Run_Id / Exp_ID, mainly from SRA/DDBJ SRA/ENA, GSA and MG-RAST repositories) covering all sequence-based -omics approaches used to investigate bacteria, archaea, microbial eukaryotes, and viruses. Therefore, FreshOmics allows accurate and comprehensive analyses of microbial communities to answer questions related to their roles in freshwater ecosystems functioning and resilience, especially through meta-analysis studies. This collection also highlights different sort of errors in published works (e.g., wrong coordinates, sample type, material, spelling).
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