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The popularity of plant-based meat alternatives (PBMAs) has sparked a contentious debate about their influence on intestinal homeostasis compared to traditional animal-based meats. This study aims to explore the changes in gut microbial metabolites (GMMs) induced by the gut microbiota on different digested patties: beef meat and pea-protein PBMA. After digesting in vitro, untargeted metabolomics revealed 32 annotated metabolites, such as carnitine and acylcarnitines correlated with beef meat, and 45 annotated metabolites, like triterpenoids and lignans, linked to our PBMA. Secondly, (un)targeted approaches highlighted differences in GMM patterns during colonic fermentations. Our findings underscore significant differences in amino acids and their derivatives. Beef protein fermentation resulted in higher production of methyl-histidine, gamma-glutamyl amino acids, indoles, isobutyric and isovaleric acids. In contrast, PBMAs exhibit a significant release of N-acyl amino acids and unique dipeptides, like phenylalanine-arginine. This research offers valuable insights into how PBMAs and animal-based proteins differently modulate intestinal microenvironments.

Lactic acid bacteria (LAB) are involved in producing a considerable number of fermented products consumed worldwide. Many of those LAB fermented foods are recognized as beneficial for human health due to probiotic LAB or their metabolites produced during food fermentation or after food digestion. In this review, we aim to gather and discuss available information on the health-related effects of LAB-fermented foods. In particular, we focused on the most widely consumed LAB-fermented foods such as yoghurt, kefir, cheese, and plant-based products such as sauerkrauts and kimchi.

Dietary patterns, microbiome dysbiosis, and gut microbial metabolites (GMMs) have a pivotal role in the homeostasis of intestinal epithelial cells and in disease progression, such as that of colorectal cancer (CRC). Although GMMs and microorganisms have crucial roles in many biological activities, models for deciphering diet–microbiome–host relationships are largely limited to animal models. Thus, intestinal organoids (IOs) have provided unprecedented opportunities for the generation of in vitro platforms with the sufficient level of complexity to model physiological and pathological diet–microbiome–host conditions. Overall, IO responses to GMM metabolites and microorganisms can provide new insights into the mechanisms by which those agents may prevent or trigger diseases, significantly extending our knowledge of diet–microbiome–host interactions.

The life sciences are currently being transformed by an unprecedented wave of developments in molecular analysis, which include important advances in instrumental analysis as well as biocomputing. In light of the central role played by metabolism in nutrition, metabolomics is rapidly being established as a key analytical tool in human nutritional studies. Consequently, an increasing number of nutritionists integrate metabolomics into their study designs. Within this dynamic landscape, the potential of nutritional metabolomics (nutrimetabolomics) to be translated into a science, which can impact on health policies, still needs to be realized. A key element to reach this goal is the ability of the research community to join, to collectively make the best use of the potential offered by nutritional metabolomics. This article, therefore, provides a methodological description of nutritional metabolomics that reflects on the state-of-the-art techniques used in the laboratories of the Food Biomarker Alliance (funded by the European Joint Programming Initiative “A Healthy Diet for a Healthy Life” (JPI HDHL)) as well as points of reflections to harmonize this field. It is not intended to be exhaustive but rather to present a pragmatic guidance on metabolomic methodologies, providing readers with useful “tips and tricks” along the analytical workflow.