Introduction Phenolic acids are important phenolic compounds widespread in foods, contributing to nutritional and organoleptic properties. Factors affceting individual variability The bioavailability of these compounds depends on their free or conjugated presence in food matrices, which is also affected by food processing. Phenolic acids undergo metabolism by the host and residing intestinal microbiota, which causes conjugations and structural modifications of the compounds. Human responses, metabolite profiles and health responses of phenolics, show considerable individual variation, which is affected by absorption, metabolism and genetic variations of subjects. Opinion A better understanding of the gut-host interplay and microbiome biochemistry is becoming highly relevant in understanding the impact of diet and its constituents. It is common to study metabolism and health benefits separately, with some exceptions; however, it should be preferred that health responders and non-responders are studied in combination with explanatory metabolite profiles and gene variants. This approach could turn interindividual variation from a problem in human research to an asset for research on personalized nutrition.

Metabolomics analysis generates vast arrays of data, necessitating comprehensive workflows involving expertise in analytics, biochemistry and bioinformatics in order to provide coherent and high-quality data that enable discovery of robust and biologically significant metabolic findings. In this protocol article, we introduce notame, an analytical workflow for non-targeted metabolic profiling approaches, utilizing liquid chromatography–mass spectrometry analysis. We provide an overview of lab protocols and statistical methods that we commonly practice for the analysis of nutritional metabolomics data. The paper is divided into three main sections: the first and second sections introducing the background and the study designs available for metabolomics research and the third section describing in detail the steps of the main methods and protocols used to produce, preprocess and statistically analyze metabolomics data and, finally, to identify and interpret the compounds that have emerged as interesting.

Alterations in the gut microbiota composition have been associated with a range of neurodevelopmental, neurodegenerative, and neuropsychiatric disorders. The gut microbes transform and metabolize dietary- and host-derived molecules generating a diverse group of metabolites with local and systemic effects. The bi-directional communication between brain and the microbes residing in the gut, the so-called gut–brain axis, consists of a network of immunological, neuronal, and endocrine signaling pathways. Although the full variety of mechanisms of the gut–brain crosstalk is yet to be established, the existing data demonstrates that a single metabolite or its derivatives are likely among the key inductors within the gut–brain axis communication. However, more research is needed to understand the molecular mechanisms underlying how gut microbiota associated metabolites alter brain functions, and to examine if different interventional approaches targeting the gut microbiota could be used in prevention and treatment of neurological disorders, as reviewed herein. Abbreviations: 4-EPS 4-ethylphenylsulfate; 5-AVA(B) 5-aminovaleric acid (betaine); Aβ Amyloid beta protein; AhR Aryl hydrocarbon receptor; ASD Autism spectrum disorder; BBB Blood–brain barrier; BDNF Brain-derived neurotrophic factor; CNS Central nervous system; GABA ɣ-aminobutyric acid; GF Germ-free; MIA Maternal immune activation; SCFA Short-chain fatty acid; 3M-4-TMAB 3-methyl-4-(trimethylammonio)butanoate; 4-TMAP 4-(trimethylammonio)pentanoate; TMA(O) Trimethylamine(- N -oxide); TUDCA Tauroursodeoxycholic acid; ZO Zonula occludens proteins

Sourdough fermentation by lactic acid bacteria is commonly used in bread baking, affecting several attributes of the final product. We analyzed whole-grain wheat and rye breads and doughs prepared with baker’s yeast or a sourdough starter including Candida milleri, Lactobacillus brevis and Lactobacillus plantarum using non-targeted metabolic profiling utilizing LC–QTOF–MS. The aim was to determine the fermentation-induced changes in metabolites potentially contributing to the health-promoting properties of whole-grain wheat and rye. Overall, we identified 118 compounds with significantly increased levels in sourdough, including branched-chain amino acids (BCAAs) and their metabolites, small peptides with high proportion of BCAAs, microbial metabolites of phenolic acids and several other potentially bioactive compounds. We also identified 69 compounds with significantly decreased levels, including phenolic acid precursors, nucleosides, and nucleobases. Intensive sourdough fermentation had a higher impact on the metabolite profile of whole-grain rye compared to milder whole-grain wheat sourdough fermentation. We hypothesize that the increased amount of BCAAs and potentially bioactive small peptides may contribute to the insulin response of rye bread, and in more general, the overall protective effect against T2DM and CVD.