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MINI REVIEW article

Front. Microbiol.

Sec. Food Microbiology

Multi-Faceted Human Gut Microbiome Data Associated with Health and Nutrition

Provisionally accepted
Lucia MaistoLucia Maisto1Claudia TelegrafoClaudia Telegrafo1Francesco RubinoFrancesco Rubino2Monica SantamariaMonica Santamaria3Maria TrakaMaria Traka4Apollonia TulloApollonia Tullo1Jildau BouwmanJildau Bouwman5Elisabetta Sbisa'Elisabetta Sbisa'2Bachir BalechBachir Balech1*
  • 1institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, Consiglio Nazionale delle Ricerche (IBIOM-CNR), Bari, Italy
  • 2Institute for Biomedical Technologies, Consiglio Nazionale delle Ricerche (ITB-CNR), Bari, Italy
  • 3Department of Soil, Plant and Food Sciences (Di.S.S.P.A.), University of Bari, Bari, Italy
  • 4Food & Nutrition National Bioscience Research Infrastructure, Quadram Institute Bioscience, Norwich Research Park, Norwich, United Kingdom
  • 5Netherlands Organisation for Applied Scientific Research (TNO), Microbiology and Systems Biology, Leiden, Netherlands

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The microbiome, also considered as the hidden organ, is a fundamental ecosystem directly connected to disease and health status of human body. With the availability of high throughput DNA sequencing technologies, a growing number of studies from clinical and experimental (observation and intervention) samples is constantly revealing new findings on the relationship between human organs and their microbiomes. In such context, diet and nutrition are among key factors influencing microbiome composition, richness and functional behavior. In this review, we illustrate how microbiome related data and associated metadata are nowadays scattered across primary and specialized databases with different levels of curation, annotation and standardization limiting to some extent the possibility of deep data discovery, reuse, alignment and harmonization. Therefore, we describe the way FAIR (Findable, Accessible, Interoperable, Reusable) data principles would enhance the onset of novel scientific hypothesis and potential microbiome-targeted therapies by improving the standardization policies in data sources. Accordingly, using advanced semantic classification and data mining technologies based on suitable and comprehensive ontologies annotations of studies present in source databases or in scientific literature would further improve data and metadata enrichment, integration and alignment relevant to microbiome data associated with health, disease and nutrition.

Keywords: database, Diet, Disease, Dysbiosis, FAIR, Metagenomics

Received: 10 Oct 2025; Accepted: 30 Jan 2026.

Copyright: © 2026 Maisto, Telegrafo, Rubino, Santamaria, Traka, Tullo, Bouwman, Sbisa' and Balech. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Bachir Balech

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Supplementary Material