FAIR Mitochondrial Data: Open Resources for Integrative Research in Bioenergetics and Disease

This Research Topic is part of our FAIR series. For other Research Topics in the series, please see below:FAIR Metabolomics: Open Datasets, Shared Standards, and the Road to AI-Ready DataFAIR RNA Data: Open Resources for Transcriptomics, Structure, and Regulatory Network ResearchFAIR Genomics: Standards, Repositories, and Reproducibility in Chromatin and Genome ResearchFAIR Cell Biology Data: From Image Archives to Interoperable Signalling DatasetsFAIR Structural Data in the Age of AI: From Deposition to DiscoveryMaking Glycan Data FAIR: Addressing the Interoperability Gap in GlycoscienceMitochondrial research sits at the convergence of bioenergetics, genetics, cell biology, and disease, producing a rich but fragmented landscape of data types: respirometry measurements, mitochondrial proteomes, mtDNA sequencing datasets, imaging of mitochondrial dynamics, and functional readouts from disease models. Community resources such as MitoCarta and MitoXplorer provide important reference points, but the broader ecosystem of mitochondrial data remains poorly connected and difficult to reuse across studies and model systems.This Research Topic focuses on advancing FAIR data practices in mitochondrial biology, from standardised metadata for bioenergetics assays and consistent reporting of respiratory chain measurements, to interoperability between mitochondrial proteomics datasets and cross-species integration of mtDNA variant data. Standardisation of respirometry data from platforms such as the Seahorse XF Analyser, where community reporting norms remain underdeveloped, is a particular priority. Standardisation of respiratory chain complex activity assay data, where protocols vary considerably across laboratories, is an area where community reporting norms could immediately improve cross-study comparability.We also welcome contributions addressing FAIR sharing of mitochondrial morphology, mitophagy, and membrane potential datasets, and submissions that link mitochondrial data to variant databases such as MITOMAP and to rare disease patient registries. FAIR² Data Articles presenting openly deposited mitochondrial datasets, including those enabling AI-driven discovery in rare mitochondrial diseases, are strongly encouraged. KEY THEMESStandardised metadata and reporting for respirometry and bioenergetics assay dataFAIR deposition of mitochondrial proteomics and mtDNA sequencing datasetsCross-species integration of mitochondrial variant data (MITOMAP, ClinVar)Interoperability between mitochondrial morphology, dynamics, and functional datasetsFAIR practices for Seahorse XF Analyser and related bioenergetics platform dataLinking mitochondrial data to rare disease patient registries and phenotypic databasesOpen datasets for mitophagy, membrane potential, and ROS profiling studiesAI-driven discovery in mitochondrial disease enabled by FAIR-compliant open data Topic editors: Antentor Hinton, Joyonna Gamble-George, Prasanna Katti, Mohd Khan, Andrea Marshall Source: https://www.frontiersin.org/research-topics/82996/fair-mitochondrial-data-open-resources-for-integrative-research-in-bioenergetics-and-disease