The development of SDRF-Metaproteomics metadata standards: harmonizing efforts from proteomics and metagenomics

Sharing data and resources has fundamentally transformed the life sciences, particularly in the fields of proteomics and metaproteomics. Public data availability has enabled novel reanalyses and interpretations, but the lack of comprehensive metadata limits the potential of these shared resources. The development of the Sample and Data Relationship Format for Proteomics (SDRF-Proteomics), co-developed by EuBIC-MS and HUPO-PSI, aimed to address this, though this format is incomplete for the protein analysis of microbial communities.

Therefore, the Metaproteomics Initiative is proposing SDRF-Metaproteomics metadata standards tailored for three commonly studied microbial environments: the human gut, soil, and water. It"s important to note that these standards serve as pilot projects and can be further extended to include other environments as well. Each of these metadata standards contains attributes that are not included in SDRF-Proteomics, but are present in the metadata standards used in metagenomics, commonly known as the minimum information about any (x) sequence (MIxS) specifications developed by the Genomics Standards Consortium. Examples are details about the diet from the patient (human gut), and the depth or elevation of the sampling site (soil and water). We aim to, once approved, integrate these standards in lesSDRF, a tool developed to simplify the process of metadata annotation.

To conclude, the introduction of SDRF-Metaproteomics metadata standards marks, to our knowledge, the first attempt of standardizing metadata reporting in metaproteomics. By harmonizing SDRF-Proteomics (what is known but incomplete), with what closely related fields do (MIxS in metagenomics), we address the critical gap in comprehensive data annotation for microbial community protein analysis. The tailored metadata standards for the human gut, soil, and water environments not only enhance data consistency and usability but also pave the way for more accurate and meaningful interpretations and comparisons of metaproteomic data. As these standards gain acceptance and integration through tools like lesSDRF, this will only increase.