The gut microbiome is indispensable for the host physiological functioning. Yet, the impact of non-nutritious dietary compounds on the human gut microbiota and the role of the gut microbes in their metabolism and potential adverse biological effects have been overlooked. Identifying potential hazards and benefits would contribute to protecting and harnessing the gut microbiome’s role in supporting human health. We discuss the evidence on the potential detrimental impact of certain food additives and microplastics on the gut microbiome and health endpoints, with a focus on underlying mechanisms and causality. We provide recommendations for the incorporation of gut microbiome science in food risk assessment and identify knowledge and tools needed to fulfill the gaps. The incorporation of gut microbiome endpoints to safety assessments, together with well-established toxicity and mutagenicity studies, might better inform the risk assessment of certain contaminants in food, and/or food additives.

BACKGROUND: With a society increasingly demanding alternative protein food sources, new strategies for evaluating protein safety issues, such as their allergenic potential, are needed. Large-scale and systemic studies on allergenic proteins are hindered by the limited and non-harmonized clinical information available for these substances in dedicated databases. A clearly missing key information is that representing the symptomatology of the allergens, especially given in terms of standard vocabularies, that would allow connecting with other biomedical resources to carry out different studies related to human health. In this work, we have generated the first resource with a comprehensive annotation of allergens’ symptomatology, using a text-mining approach that extracts significant co-mentions between these entities from the scientific literature. METHODS: The main resource of biomedical literature (PubMed, ~36 million abstracts) was mined to automatically extract relationships between allergens and clinical symptoms. The annotations are given in terms of standard vocabularies in widely used biomedical databases. The method identifies statistically significant co-mentions between the textual descriptions of the two types of entities in the literature as indication of relationship. RESULTS: 1,180 clinical signs extracted from the Human Phenotype Ontology (HPO), the Medical Subject Heading (MeSH) terms of PubMed together with other allergen-specific symptoms, were linked to 1,036 unique allergens annotated in the two main allergen-related public databases via 14,009 relationships. CONCLUSIONS: This resource could serve as a starting point for a future manually curated compilation of allergen symptomatology. The annotations are publicly available through an interactive web interface at [https://csbg.cnb.csic.es/CoMent_allergen/](https://csbg.cnb.csic.es/CoMent_allergen/).