Vitamin A carotenoids, but not retinoids, mediate the impact of a healthy diet on gut microbial diversity.

BACKGROUND: Vitamin A is essential for physiological processes like vision and immunity. Vitamin A's effect on gut microbiome composition, which affects absorption and metabolism of other vitamins, is still unknown. Here we examined the relationship between gut metagenome composition and six vitamin A-related metabolites (two retinoid: -retinol, 4 oxoretinoic acid (oxoRA) and four carotenoid metabolites, including beta-cryptoxanthin and three carotene diols). METHODS: We included 1053 individuals from the TwinsUK cohort with vitamin A-related metabolites measured in serum and faeces, diet history, and gut microbiome composition assessed by shotgun metagenome sequencing. Results were replicated in 327 women from the ZOE PREDICT-1 study. RESULTS: Five vitamin A-related serum metabolites were positively correlated with microbiome alpha diversity (r = 0.15 to r = 0.20, p < 4 × 10-6). Carotenoid compounds were positively correlated with the short-chain fatty-acid-producing bacteria Faecalibacterium prausnitzii and Coprococcus eutactus. Retinol was not associated with any microbial species. We found that gut microbiome composition could predict circulating levels of carotenoids and oxoretinoic acid with AUCs ranging from 0.66 to 0.74 using random forest models, but not retinol (AUC = 0.52). The healthy eating index (HEI) was strongly associated with gut microbiome diversity and with all carotenoid compounds, but not retinoids. We investigated the mediating role of carotenoid compounds on the effect of a healthy diet (HEI) on gut microbiome diversity, finding that carotenoids significantly mediated between 18 and 25% of the effect of HEI on gut microbiome alpha diversity. CONCLUSIONS: Our results show strong links between circulating carotene compounds and gut microbiome composition and potential links to a healthy diet pattern.

Obesogenic High-Fat Diet and MYC Cooperate to Promote Lactate Accumulation and Tumor Microenvironment Remodeling in Prostate Cancer.

Cancer cells exhibit metabolic plasticity to meet oncogene-driven dependencies while coping with nutrient availability. A better understanding of how systemic metabolism impacts the accumulation of metabolites that reprogram the tumor microenvironment (TME) and drive cancer could facilitate development of precision nutrition approaches. Using the Hi-MYC prostate cancer mouse model, we demonstrated that an obesogenic high-fat diet (HFD) rich in saturated fats accelerates the development of c-MYC-driven invasive prostate cancer through metabolic rewiring. Although c-MYC modulated key metabolic pathways, interaction with an obesogenic HFD was necessary to induce glycolysis and lactate accumulation in tumors. These metabolic changes were associated with augmented infiltration of CD206+ and PD-L1+ tumor-associated macrophages (TAM) and FOXP3+ regulatory T cells, as well as with the activation of transcriptional programs linked to disease progression and therapy resistance. Lactate itself also stimulated neoangiogenesis and prostate cancer cell migration, which were significantly reduced following treatment with the lactate dehydrogenase inhibitor FX11. In patients with prostate cancer, high saturated fat intake and increased body mass index were associated with tumor glycolytic features that promote the infiltration of M2-like TAMs. Finally, upregulation of lactate dehydrogenase, indicative of a lactagenic phenotype, was associated with a shorter time to biochemical recurrence in independent clinical cohorts. This work identifies cooperation between genetic drivers and systemic metabolism to hijack the TME and promote prostate cancer progression through oncometabolite accumulation. This sets the stage for the assessment of lactate as a prognostic biomarker and supports strategies of dietary intervention and direct lactagenesis blockade in treating advanced prostate cancer. SIGNIFICANCE: Lactate accumulation driven by high-fat diet and MYC reprograms the tumor microenvironment and promotes prostate cancer progression, supporting the potential of lactate as a biomarker and therapeutic target in prostate cancer. See related commentary by Frigo, p. 1742.

Machine Learning Metabolomics Profiling of Dietary Interventions from a Six-Week Randomised Trial.

Metabolomics can uncover physiological responses to prebiotic fibre and omega-3 fatty acid supplements with known health benefits and identify response-specific metabolites. We profiled 534 stool and 799 serum metabolites in 64 healthy adults following a 6-week randomised trial comparing daily omega-3 versus inulin supplementation. Elastic net regressions were used to separately identify the serum and stool metabolites whose change in concentration discriminated between the two types of supplementations. Random forest was used to explore the gut microbiome's contribution to the levels of the identified metabolites from matching stool samples. Changes in serum 3-carboxy-4-methyl-5-propyl-2-furanpropanoate and indoleproprionate levels accurately discriminated between fibre and omega-3 (area under the curve (AUC) = 0.87 [95% confidence interval (CI): 0.63-0.99]), while stool eicosapentaenoate indicated omega-3 supplementation (AUC = 0.86 [95% CI: 0.64-0.98]). Univariate analysis also showed significant increases in indoleproprionate with fibre, 3-carboxy-4-methyl-5-propyl-2-furanpropanoate, and eicosapentaenoate with omega-3. Out of these, only the change in indoleproprionate was partly explained by changes in the gut microbiome composition (AUC = 0.61 [95% CI: 0.58-0.64] and Rho = 0.21 [95% CI: 0.08-0.34]) and positively correlated with the increase in the abundance of the genus Coprococcus (p = 0.005). Changes in three metabolites discriminated between fibre and omega-3 supplementation. The increase in indoleproprionate with fibre was partly explained by shifts in the gut microbiome, particularly Coprococcus, previously linked to better health.