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Data independent acquisition (DIA) proteomics techniques have matured enormously in recent years, thanks to multiple technical developments in, for example, instrumentation and data analysis approaches. However, there are many improvements that are still possible for DIA data in the area of the FAIR (Findability, Accessibility, Interoperability and Reusability) data principles. These include more tailored data sharing practices and open data standards since public databases and data standards for proteomics were mostly designed with DDA data in mind. Here we first describe the current state of the art in the context of FAIR data for proteomics in general, and for DIA approaches in particular. For improving the current situation for DIA data, we make the following recommendations for the future: (i) development of an open data standard for spectral libraries; (ii) make mandatory the availability of the spectral libraries used in DIA experiments in ProteomeXchange resources; (iii) improve the support for DIA data in the data standards developed by the Proteomics Standards Initiative; and (iv) improve the support for DIA datasets in ProteomeXchange resources, including more tailored metadata requirements.

 

Mass spectrometry (MS) is by far the most used experimental approach in high-throughput proteomics. The ProteomeXchange (PX) consortium of proteomics resources (http://www.proteomexchange.org) was originally set up to standardize data submission and dissemination of public MS proteomics data. It is now 10 years since the initial data workflow was implemented. In this manuscript, we describe the main developments in PX since the previous update manuscript in Nucleic Acids Research was published in 2020. The six members of the Consortium are PRIDE, PeptideAtlas (including PASSEL), MassIVE, jPOST, iProX and Panorama Public. We report the current data submission statistics, showcasing that the number of datasets submitted to PX resources has continued to increase every year. As of June 2022, more than 34 233 datasets had been submitted to PX resources, and from those, 20 062 (58.6%) just in the last three years. We also report the development of the Universal Spectrum Identifiers and the improvements in capturing the experimental metadata annotations. In parallel, we highlight that data re-use activities of public datasets continue to increase, enabling connections between PX resources and other popular bioinformatics resources, novel research and also new data resources. Finally, we summarise the current state-of-the-art in data management practices for sensitive human (clinical) proteomics data.

 

Abstract We developed a resource, the Arabidopsis PeptideAtlas (www.peptideatlas.org/builds/arabidopsis/), to solve central questions about the Arabidopsis thaliana proteome, such as the significance of protein splice forms and post-translational modifications (PTMs), or simply to obtain reliable information about specific proteins. PeptideAtlas is based on published mass spectrometry (MS) data collected through ProteomeXchange and reanalyzed through a uniform processing and metadata annotation pipeline. All matched MS-derived peptide data are linked to spectral, technical, and biological metadata. Nearly 40 million out of ∼143 million MS/MS (tandem MS) spectra were matched to the reference genome Araport11, identifying ∼0.5 million unique peptides and 17,858 uniquely identified proteins (only isoform per gene) at the highest confidence level (false discovery rate 0.0004; 2 non-nested peptides ≥9 amino acid each), assigned canonical proteins, and 3,543 lower-confidence proteins. Physicochemical protein properties were evaluated for targeted identification of unobserved proteins. Additional proteins and isoforms currently not in Araport11 were identified that were generated from pseudogenes, alternative start, stops, and/or splice variants, and small Open Reading Frames; these features should be considered when updating the Arabidopsis genome. Phosphorylation can be inspected through a sophisticated PTM viewer. PeptideAtlas is integrated with community resources including TAIR, tracks in JBrowse, PPDB, and UniProtKB. Subsequent PeptideAtlas builds will incorporate millions more MS/MS data. 

Protein identification by tandem mass spectrometry sequence database searching is a standard practice in many proteomics laboratories. The de facto standard for the representation of sequence databases used as input to sequence database search tools is the FASTA format. The Human Proteome Organization's Proteomics Standards Initiative has developed an extension to the FASTA format termed the proteomics standards initiative extended FASTA format or PSI extended FASTA format (PEFF) where additional information such as structural annotations are encoded in the protein description lines. Comet has been extended to automatically analyze the post translational modifications and amino acid substitutions encoded in PEFF databases. Comet's PEFF implementation and example analysis results searching a HEK293 dataset against the neXtProt PEFF database are presented.