The underappreciated diversity of bile acid modifications.

The repertoire of modifications to bile acids and related steroidal lipids by host and microbial metabolism remains incompletely characterized. To address this knowledge gap, we created a reusable resource of tandem mass spectrometry (MS/MS) spectra by filtering 1.2 billion publicly available MS/MS spectra for bile-acid-selective ion patterns. Thousands of modifications are distributed throughout animal and human bodies as well as microbial cultures. We employed this MS/MS library to identify polyamine bile amidates, prevalent in carnivores. They are present in humans, and their levels alter with a diet change from a Mediterranean to a typical American diet. This work highlights the existence of many more bile acid modifications than previously recognized and the value of leveraging public large-scale untargeted metabolomics data to discover metabolites. The availability of a modification-centric bile acid MS/MS library will inform future studies investigating bile acid roles in health and disease.

Reverse metabolomics for the discovery of chemical structures from humans.

Determining the structure and phenotypic context of molecules detected in untargeted metabolomics experiments remains challenging. Here we present reverse metabolomics as a discovery strategy, whereby tandem mass spectrometry spectra acquired from newly synthesized compounds are searched for in public metabolomics datasets to uncover phenotypic associations. To demonstrate the concept, we broadly synthesized and explored multiple classes of metabolites in humans, including N-acyl amides, fatty acid esters of hydroxy fatty acids, bile acid esters and conjugated bile acids. Using repository-scale analysis1,2, we discovered that some conjugated bile acids are associated with inflammatory bowel disease (IBD). Validation using four distinct human IBD cohorts showed that cholic acids conjugated to Glu, Ile/Leu, Phe, Thr, Trp or Tyr are increased in Crohn's disease. Several of these compounds and related structures affected pathways associated with IBD, such as interferon-γ production in CD4+ T cells3 and agonism of the pregnane X receptor4. Culture of bacteria belonging to the Bifidobacterium, Clostridium and Enterococcus genera produced these bile amidates. Because searching repositories with tandem mass spectrometry spectra has only recently become possible, this reverse metabolomics approach can now be used as a general strategy to discover other molecules from human and animal ecosystems.

A Complete Pipeline for Untargeted Urinary Volatolomic Profiling with Sorptive Extraction and Dual Polar and Nonpolar Column Methodologies Coupled with Gas Chromatography Time-of-Flight Mass Spectrometry.

Volatolomics offers an opportunity for noninvasive detection and monitoring of human disease. While gas chromatography-mass spectrometry (GC-MS) remains the technique of choice for analyzing volatile organic compounds (VOCs), barriers to wider adoption in clinical practice still exist, including: sample preparation and introduction techniques, VOC extraction, throughput, volatolome coverage, biological interpretation, and quality control (QC). Therefore, we developed a complete pipeline for untargeted urinary volatolomic profiling. We optimized a novel extraction technique using HiSorb sorptive extraction, which exhibited high analytical performance and throughput. We achieved a broader VOC coverage by using HiSorb coupled with a set of complementary chromatographic methods and time-of-flight mass spectrometry. Furthermore, we developed a data preprocessing strategy by evaluating internal standard normalization, batch correction, and we adopted strict QC measures including removal of nonlinearly responding, irreproducible, or contaminated metabolic features, ensuring the acquisition of high-quality data. The applicability of this pipeline was evaluated in a clinical cohort consisting of pancreatic ductal adenocarcinoma (PDAC) patients (n = 28) and controls (n = 33), identifying four urinary candidate biomarkers (2-pentanone, hexanal, 3-hexanone, and p-cymene), which can successfully discriminate the cancer and noncancer subjects. This study presents an optimized, high-throughput, and quality-controlled pipeline for untargeted urinary volatolomic profiling. Use of the pipeline to discriminate PDAC from control subjects provides proof of principal of its clinical utility and potential for application in future biomarker discovery studies.

Faecal virome transplantation decreases symptoms of type 2 diabetes and obesity in a murine model.

OBJECTIVE: Development of obesity and type 2 diabetes (T2D) are associated with gut microbiota (GM) changes. The gut viral community is predominated by bacteriophages (phages), which are viruses that attack bacteria in a host-specific manner. The antagonistic behaviour of phages has the potential to alter the GM. As a proof-of-concept, we demonstrate the efficacy of faecal virome transplantation (FVT) from lean donors for shifting the phenotype of obese mice into closer resemblance of lean mice. DESIGN: The FVT consisted of viromes with distinct profiles extracted from the caecal content of mice from different vendors that were fed a low-fat (LF) diet for 14 weeks. Male C57BL/6NTac mice were divided into five groups: LF (as diet control), high-fat (HF) diet, HF+ampicillin (Amp), HF+Amp+FVT and HF+FVT. At weeks 6 and 7 of the study, the HF+FVT and HF+Amp+FVT mice were treated with FVT by oral gavage. The Amp groups were treated with Amp 24 hours prior to first FVT treatment. RESULTS: Six weeks after first FVT, the HF+FVT mice showed a significant decrease in weight gain compared with the HF group. Further, glucose tolerance was comparable between the LF and HF+FVT mice, while the other HF groups all had impaired glucose tolerance. These observations were supported by significant shifts in GM composition, blood plasma metabolome and expression levels of genes associated with obesity and T2D development. CONCLUSIONS: Transfer of caecal viral communities from mice with a lean phenotype into mice with an obese phenotype led to reduced weight gain and normalised blood glucose parameters relative to lean mice. We hypothesise that this effect is mediated via FVT-induced GM changes.

Reclassification of Eubacterium hallii as Anaerobutyricum hallii gen. nov., comb. nov., and description of Anaerobutyricum soehngenii sp. nov., a butyrate and propionate-producing bacterium from infant faeces.

A bacterial strain designated L2-7T, phylogenetically related to Eubacterium hallii DSM 3353T, was previously isolated from infant faeces. The complete genome of strain L2-7T contains eight copies of the 16S rRNA gene with only 98.0-98.5 % similarity to the 16S rRNA gene of the previously described type strain E. hallii. The next closest validly described species is Anaerostipes hadrus DSM 3319T (90.7 % 16S rRNA gene similarity). A polyphasic taxonomic approach showed strain L2-7T to be a novel species, related to type strain E. hallii DSM 3353T. The experimentally observed DNA-DNA hybridization value between strain L2-7T and E. hallii DSM 3353T was 26.25 %, close to that calculated from the genomes (34.3 %). The G+C content of the chromosomal DNA of strain L2-7T was 38.6 mol%. The major fatty acids were C16 : 0, C16 : 1cis9 and a component with summed feature 10 (C18 : 1c11/t9/t6c). Strain L2-7T had higher amounts of C16 : 0 (30.6 %) compared to E. hallii DSM 3353T (19.5 %) and its membrane contained phosphatidylglycerol and phosphatidylethanolamine, which were not detected in E. hallii DSM 3353T. Furthermore, 16S rRNA gene phylogenetic analysis advocates that E. hallii DSM 3353T is misclassified, and its reclassification as a member of the family Lachnospiraceae is necessary. Using a polyphasic approach, we propose that E. hallii (=DSM 3353T=ATCC 27751T) be reclassified as the type strain of a novel genus Anaerobutyricum sp. nov., comb. nov. and we propose that strain L2-7T should be classified as a novel species, Anaerobutyricum soehngenii sp. nov. The type strain is L2-7T (=DSM 17630T=KCTC 15707T).

Dietary iron intake has long-term effects on the fecal metabolome and microbiome.

Iron is essential for life, but its imbalances can lead to severe health implications. Iron deficiency is the most common nutrient disorder worldwide, and iron dysregulation in early life has been found to cause long-lasting behavioral, cognitive, and neural effects. However, little is known about the effects of dietary iron on gut microbiome function and metabolism. In this study, we sought to investigate the impact of dietary iron on the fecal metabolome and microbiome by using mice fed with three diets with different iron content: an iron deficient, an iron sufficient (standard), and an iron overload diet for 7 weeks. Additionally, we sought to understand whether any observed changes would persist past the 7-week period of diet intervention. To assess this, all feeding groups were switched to a standard diet, and this feeding continued for an additional 7 weeks. Analysis of the fecal metabolome revealed that iron overload and deficiency significantly alter levels of peptides, nucleic acids, and lipids, including di- and tri-peptides containing branched-chain amino acids, inosine and guanosine, and several microbial conjugated bile acids. The observed changes in the fecal metabolome persist long after the switch back to a standard diet, with the cecal gut microbiota composition and function of each group distinct after the 7-week standard diet wash-out. Our results highlight the enduring metabolic consequences of nutritional imbalances, mediated by both the host and gut microbiome, which persist after returning to the original standard diets.

Receptor and metabolic insights on the ability of caffeine to prevent alcohol-induced stimulation of mesolimbic dopamine transmission.

The consumption of alcohol and caffeine affects the lives of billions of individuals worldwide. Although recent evidence indicates that caffeine impairs the reinforcing properties of alcohol, a characterization of its effects on alcohol-stimulated mesolimbic dopamine (DA) function was lacking. Acting as the pro-drug of salsolinol, alcohol excites DA neurons in the posterior ventral tegmental area (pVTA) and increases DA release in the nucleus accumbens shell (AcbSh). Here we show that caffeine, via antagonistic activity on A2A adenosine receptors (A2AR), prevents alcohol-dependent activation of mesolimbic DA function as assessed, in-vivo, by brain microdialysis of AcbSh DA and, in-vitro, by electrophysiological recordings of pVTA DA neuronal firing. Accordingly, while the A1R antagonist DPCPX fails to prevent the effects of alcohol on DA function, both caffeine and the A2AR antagonist SCH 58261 prevent alcohol-dependent pVTA generation of salsolinol and increase in AcbSh DA in-vivo, as well as alcohol-dependent excitation of pVTA DA neurons in-vitro. However, caffeine also prevents direct salsolinol- and morphine-stimulated DA function, suggesting that it can exert these inhibitory effects also independently from affecting alcohol-induced salsolinol formation or bioavailability. Finally, untargeted metabolomics of the pVTA showcases that caffeine antagonizes alcohol-mediated effects on molecules (e.g. phosphatidylcholines, fatty amides, carnitines) involved in lipid signaling and energy metabolism, which could represent an additional salsolinol-independent mechanism of caffeine in impairing alcohol-mediated stimulation of mesolimbic DA transmission. In conclusion, the outcomes of this study strengthen the potential of caffeine, as well as of A2AR antagonists, for future development of preventive/therapeutic strategies for alcohol use disorder.

Receptor and metabolic insights on the ability of caffeine to prevent alcohol-induced stimulation of mesolimbic dopamine transmission.

The consumption of alcohol and caffeine affects the lives of billions of individuals worldwide. Although recent evidence indicates that caffeine impairs the reinforcing properties of alcohol, a characterization of its effects on alcohol-stimulated mesolimbic dopamine (DA) function was lacking. Acting as the pro-drug of salsolinol, alcohol excites DA neurons in the posterior ventral tegmental area (pVTA) and increases DA release in the nucleus accumbens shell (AcbSh). Here we show that caffeine, via antagonistic activity on A2A adenosine receptors (A2AR), prevents alcohol-dependent activation of mesolimbic DA function as assessed, in-vivo, by brain microdialysis of AcbSh DA and, in-vitro, by electrophysiological recordings of pVTA DA neuronal firing. Accordingly, while the A1R antagonist DPCPX fails to prevent the effects of alcohol on DA function, both caffeine and the A2AR antagonist SCH 58261 prevent alcohol-dependent pVTA generation of salsolinol and increase in AcbSh DA in-vivo, as well as alcohol-dependent excitation of pVTA DA neurons in-vitro. However, caffeine also prevents direct salsolinol- and morphine-stimulated DA function, suggesting that it can exert these inhibitory effects also independently from affecting alcohol-induced salsolinol formation or bioavailability. Finally, untargeted metabolomics of the pVTA showcases that caffeine antagonizes alcohol-mediated effects on molecules (e.g. phosphatidylcholines, fatty amides, carnitines) involved in lipid signaling and energy metabolism, which could represent an additional salsolinol-independent mechanism of caffeine in impairing alcohol-mediated stimulation of mesolimbic DA transmission. In conclusion, the outcomes of this study strengthen the potential of caffeine, as well as of A2AR antagonists, for future development of preventive/therapeutic strategies for alcohol use disorder.

Clearing the plate: a strategic approach to mitigate well-to-well contamination in large-scale microbiome studies.

Large-scale studies are essential to answer questions about complex microbial communities that can be extremely dynamic across hosts, environments, and time points. However, managing acquisition, processing, and analysis of large numbers of samples poses many challenges, with cross-contamination being the biggest obstacle. Contamination complicates analysis and results in sample loss, leading to higher costs and constraints on mixed sample type study designs. While many researchers opt for 96-well plates for their workflows, these plates present a significant issue: the shared seal and weak separation between wells leads to well-to-well contamination. To address this concern, we propose an innovative high-throughput approach, termed as the Matrix method, which employs barcoded Matrix Tubes for sample acquisition. This method is complemented by a paired nucleic acid and metabolite extraction, utilizing 95% (vol/vol) ethanol to stabilize microbial communities and as a solvent for extracting metabolites. Comparative analysis between conventional 96-well plate extractions and the Matrix method, measuring 16S rRNA gene levels via quantitative polymerase chain reaction, demonstrates a notable decrease in well-to-well contamination with the Matrix method. Metagenomics, 16S rRNA gene amplicon sequencing (16S), and untargeted metabolomics analysis via liquid chromatography-tandem mass spectrometry (LC-MS/MS) confirmed that the Matrix method recovers reproducible microbial and metabolite compositions that can distinguish between subjects. This advancement is critical for large-scale study design as it minimizes well-to-well contamination and technical variation, shortens processing times, and integrates with automated infrastructure for enhancing sample randomization and metadata generation. IMPORTANCE: Understanding dynamic microbial communities typically requires large-scale studies. However, handling large numbers of samples introduces many challenges, with cross-contamination being a major issue. It not only complicates analysis but also leads to sample loss and increased costs and restricts diverse study designs. The prevalent use of 96-well plates for nucleic acid and metabolite extractions exacerbates this problem due to their wells having little separation and being connected by a single plate seal. To address this, we propose a new strategy using barcoded Matrix Tubes, showing a significant reduction in cross-contamination compared to conventional plate-based approaches. Additionally, this method facilitates the extraction of both nucleic acids and metabolites from a single tubed sample, eliminating the need to collect separate aliquots for each extraction. This innovation improves large-scale study design by shortening processing times, simplifying analysis, facilitating metadata curation, and producing more reliable results.

Pathogenic Bacteroides fragilis strains can emerge from gut-resident commensals.

Bacteroides fragilis is a prominent member of the human gut microbiota, playing crucial roles in maintaining gut homeostasis and host health. Although it primarily functions as a beneficial commensal, B. fragilis can become pathogenic. To determine the genetic basis of its duality, we conducted a comparative genomic analysis of 813 B. fragilis strains, representing both commensal and pathogenic origins. Our findings reveal that pathogenic strains emerge across diverse phylogenetic lineages, due in part to rapid gene exchange and the adaptability of the accessory genome. We identified 16 phylogenetic groups, differentiated by genes associated with capsule composition, interspecies competition, and host interactions. A microbial genome-wide association study identified 44 genes linked to extra-intestinal survival and pathogenicity. These findings reveal how genomic diversity within commensal species can lead to the emergence of pathogenic traits, broadening our understanding of microbial evolution in the gut.

plantMASST - Community-driven chemotaxonomic digitization of plants.

Understanding the distribution of hundreds of thousands of plant metabolites across the plant kingdom presents a challenge. To address this, we curated publicly available LC-MS/MS data from 19,075 plant extracts and developed the plantMASST reference database encompassing 246 botanical families, 1,469 genera, and 2,793 species. This taxonomically focused database facilitates the exploration of plant-derived molecules using tandem mass spectrometry (MS/MS) spectra. This tool will aid in drug discovery, biosynthesis, (chemo)taxonomy, and the evolutionary ecology of herbivore interactions.

Empirically establishing drug exposure records directly from untargeted metabolomics data.

Despite extensive efforts, extracting information on medication exposure from clinical records remains challenging. To complement this approach, we developed the tandem mass spectrometry (MS/MS) based GNPS Drug Library. This resource integrates MS/MS data for drugs and their metabolites/analogs with controlled vocabularies on exposure sources, pharmacologic classes, therapeutic indications, and mechanisms of action. It enables direct analysis of drug exposure and metabolism from untargeted metabolomics data independent of clinical records. Our library facilitates stratification of individuals in clinical studies based on the empirically detected medications, exemplified by drug-dependent microbiota-derived N-acyl lipid changes in a cohort with human immunodeficiency virus. The GNPS Drug Library holds potential for broader applications in drug discovery and precision medicine.

microbeMASST: a taxonomically informed mass spectrometry search tool for microbial metabolomics data.

microbeMASST, a taxonomically informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbe-derived metabolites and relative producers without a priori knowledge will vastly enhance the understanding of microorganisms' role in ecology and human health.

Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data.

Feature-based molecular networking (FBMN) is a popular analysis approach for liquid chromatography-tandem mass spectrometry-based non-targeted metabolomics data. While processing liquid chromatography-tandem mass spectrometry data through FBMN is fairly streamlined, downstream data handling and statistical interrogation are often a key bottleneck. Especially users new to statistical analysis struggle to effectively handle and analyze complex data matrices. Here we provide a comprehensive guide for the statistical analysis of FBMN results, focusing on the downstream analysis of the FBMN output table. We explain the data structure and principles of data cleanup and normalization, as well as uni- and multivariate statistical analysis of FBMN results. We provide explanations and code in two scripting languages (R and Python) as well as the QIIME2 framework for all protocol steps, from data clean-up to statistical analysis. All code is shared in the form of Jupyter Notebooks ( https://github.com/Functional-Metabolomics-Lab/FBMN-STATS ). Additionally, the protocol is accompanied by a web application with a graphical user interface ( https://fbmn-statsguide.gnps2.org/ ) to lower the barrier of entry for new users and for educational purposes. Finally, we also show users how to integrate their statistical results into the molecular network using the Cytoscape visualization tool. Throughout the protocol, we use a previously published environmental metabolomics dataset for demonstration purposes. Together, the protocol, code and web application provide a complete guide and toolbox for FBMN data integration, cleanup and advanced statistical analysis, enabling new users to uncover molecular insights from their non-targeted metabolomics data. Our protocol is tailored for the seamless analysis of FBMN results from Global Natural Products Social Molecular Networking and can be easily adapted to other mass spectrometry feature detection, annotation and networking tools.

Early-life differences in the gut microbiota composition and functionality of infants at elevated likelihood of developing autism spectrum disorder.

Evidence from cross-sectional human studies, and preliminary microbial-based intervention studies, have implicated the microbiota-gut-brain axis in the neurobiology of autism spectrum disorder (ASD). Using a prospective longitudinal study design, we investigated the developmental profile of the fecal microbiota and metabolome in infants with (n = 16) and without (n = 19) a family history of ASD across the first 36 months of life. In addition, the general developmental levels of infants were evaluated using the Mullen Scales of Early Learning (MSEL) test at 5 and 36 months of age, and with ADOS-2 at 36 months of age. At 5 months of age, infants at elevated-likelihood of ASD (EL) harbored less Bifidobacterium and more Clostridium and Klebsiella species compared to the low-likelihood infants (LL). Untargeted metabolic profiling highlighted that LL infants excreted a greater amount of fecal γ-aminobutyric acid (GABA) at 5 months, which progressively declined with age. Similar age-dependent patterns were not observed in the EL group, with GABA being consistently low across all timepoints. Integrated microbiome-metabolome analysis showed a positive correlation between GABA and Bifidobacterium species and negative associations with Clostridium species. In vitro experiments supported these observations demonstrating that bifidobacteria can produce GABA while clostridia can consume it. At the behavioral level, there were no significant differences between the EL and LL groups at 5 months. However, at 36 months of age, the EL group had significantly lower MSEL and ADOS-2 scores compared to the LL group. Taken together, the present results reveal early life alterations in gut microbiota composition and functionality in infants at elevated-likelihood of ASD. These changes occur before any behavioral impairments can be detected, supporting a possible role for the gut microbiota in emerging behavioral variability later in life.

Transfer of antibiotics and their metabolites in human milk: Implications for infant health and microbiota.

Antibiotics are an essential tool for perinatal care. While antibiotics can play a life-saving role for both parents and infants, they also cause collateral damage to the beneficial bacteria that make up the host gut microbiota. This is especially true for infants, whose developing gut microbiota is uniquely sensitive to antibiotic perturbation. Emerging evidence suggests that disruption of these bacterial populations during this crucial developmental window can have long-term effects on infant health and development. Although most current studies have focused on microbial disruptions caused by direct antibiotic administration to infants or prenatal exposure to antibiotics administered to the mother, little is known about whether antibiotics in human milk may pose similar risks to the infant. This review surveys current data on antibiotic transfer during lactation and highlights new methodologies to assess drug transfer in human milk. Finally, we provide recommendations for future work to ensure antibiotic use in lactating parents is safe and effective for both parents and infants.

Ex vivo study of molecular changes of stained teeth following hydrogen peroxide and peroxymonosulfate treatments.

White teeth can give confidence and tend to be associated with a healthier lifestyle in modern society. Therefore, tooth-bleaching strategies have been developed, including the use of hydrogen peroxide. Recently, peroxymonosulfate has been introduced as an alternative bleaching method to hydrogen peroxide. Although both chemicals are oxidizing agents, their effects on the molecular composition of the stained teeth are yet unknown. In this study, the molecular profiles of teeth bleached with hydrogen peroxide and peroxymonosulfate were compared using Liquid Chromatography-Tandem Mass Spectrometry. Statistical analyses were used to assess the samples. In addition, reference spectral libraries and in silico tools were used to perform metabolite annotation. Overall, principal component analysis showed a strong separation between control and hydrogen peroxide and peroxymonosulfate samples (p < 0.001). The analysis of molecular changes revealed amino acids and dipeptides in stained teeth samples after hydrogen peroxide and peroxymonosulfate treatments. Noteworthy, the two bleaching methods led to distinct molecular profiles. For example, diterpenoids were more prevalent after peroxymonosulfate treatment, while a greater abundance of alkaloids was detected after hydrogen peroxide treatment. Whereas non-bleached samples (controls) showed mainly lipids. Therefore, this study shows how two different tooth-whitening peroxides could affect the molecular profiles of human teeth.

A Taxonomically-informed Mass Spectrometry Search Tool for Microbial Metabolomics Data.

MicrobeMASST, a taxonomically-informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbial-derived metabolites and relative producers, without a priori knowledge, will vastly enhance the understanding of microorganisms' role in ecology and human health.

Variation of volatile organic compound levels within ambient room air and its impact upon the standardisation of breath sampling.

The interest around analysis of volatile organic compounds (VOCs) within breath has increased in the last two decades. Uncertainty remains around standardisation of sampling and whether VOCs within room air can influence breath VOC profiles. To assess the abundance of VOCs within room air in common breath sampling locations within a hospital setting and whether this influences the composition of breath. A secondary objective is to investigate diurnal variation in room air VOCs. Room air was collected using a sampling pump and thermal desorption (TD) tubes in the morning and afternoon from five locations. Breath samples were collected in the morning only. TD tubes were analysed using gas chromatography coupled with time-of-flight mass spectrometry (GC-TOF-MS). A total of 113 VOCs were identified from the collected samples. Multivariate analysis demonstrated clear separation between breath and room air. Room air composition changed throughout the day and different locations were characterized by specific VOCs, which were not influencing breath profiles. Breath did not demonstrate separation based on location, suggesting that sampling can be performed across different locations without affecting results.

Post-weaning A1/A2 ß-casein milk intake modulates depressive-like behavior, brain µ-opioid receptors, and the metabolome of rats.

The postnatal period is critical for brain and behavioral development and is sensitive to environmental stimuli, such as nutrition. Prevention of weaning from maternal milk was previously shown to cause depressive-like behavior in rats. Additionally, loss of dietary casein was found to act as a developmental trigger for a population of brain opioid receptors. Here, we explore the effect of exposure to milk containing A1 and A2 ß-casein beyond weaning. A1 but not A2 ß-casein milk significantly increased stress-induced immobility in rats, concomitant with an increased abundance of Clostridium histolyticum bacterial group in the caecum and colon of A1 ß-casein fed animals, brain region-specific alterations of µ-opioid and oxytocin receptors, and modifications in urinary biochemical profiles. Moreover, urinary gut microbial metabolites strongly correlated with altered brain metabolites. These findings suggest that consumption of milk containing A1 ß-casein beyond weaning age may affect mood via a possible gut-brain axis mechanism.