The gut microbiome plays a key role in regulating the gut-skin axis, and host genetics partially influence this regulation. The study investigated the role of gut microbiota and host genetics in the gut-skin axis, focusing on the unusual \"coffee-like\" color phenotype observed in TYRP1 mutant Oujiang Color Common Carp. We employed comparative high-throughput omics data from wild-type and mutant fish to quantify the influence of both genetics and gut microbes on skin transcriptomic expression and blood metabolites. We found 525 differential metabolites (DMs) and 45 distinct gut microbial genera in TYRP1 mutant fish compared to wild type. Interaction and causal mediation analyses revealed a complex interplay. The TYRP1 mutation likely triggers an inflammatory pathway involving Acinetobacter bacteria, Leukotrience-C4 and Spermine. This inflammatory response appears to be counterbalanced by an anti-inflammatory cardiovascular genetic network. The net effect is the upregulation of COMT, PLG, C2, C3, F10, TDO2, MHC1, and SERPINF2, leading to unusual coffee-like coloration. This study highlights the intricate interplay between gut microbiota, host genetics, and metabolic pathways in shaping complex phenotypes.

UNASSIGNED: The interplay between gut microbiota and metabolites in the early stages of sepsis-induced acute kidney injury (SA-AKI) is not yet clearly understood. This study explores the characteristics and interactions of gut microbiota, and blood and urinary metabolites in patients with SA-AKI.
UNASSIGNED: Utilizing a prospective observational approach, we conducted comparative analyses of gut microbiota and metabolites via metabolomics and metagenomics in individuals diagnosed with SA-AKI compared to those without AKI (NCT06197828). Pearson correlations were used to identify associations between microbiota, metabolites, and clinical indicators. The Comprehensive Antibiotic Resistance Database was employed to detect antibiotic resistance genes (ARGs), while Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways informed on metabolic processes and microbial resistance patterns.
UNASSIGNED: Our study included analysis of four patients with SA-AKI and five without AKI. Significant disparities in bacterial composition were observed, illustrated by diversity indices (Shannon index: 2.0 ± 0.4 vs. 1.4 ± 0.6, P = 0.230; Simpson index: 0.8 ± 0.1 vs. 0.6 ± 0.2, P = 0.494) between the SA-AKI group and the non-AKI group. N6, N6, N6-Trimethyl-L-lysine was detected in both blood and urine metabolites, and also showed significant correlations with specific gut microbiota (Campylobacter hominis and Bacteroides caccae, R > 0, P < 0.05). Both blood and urine metabolites were enriched in the lysine degradation pathway. We also identified the citrate cycle (TCA cycle) as a KEGG pathway enriched in sets of differentially expressed ARGs in the gut microbiota, which exhibits an association with lysine degradation.
UNASSIGNED: Significant differences in gut microbiota and metabolites were observed between the SA-AKI and non-AKI groups, uncovering potential biomarkers and metabolic changes linked to SA-AKI. The lysine degradation pathway may serve as a crucial link connecting gut microbiota and metabolites.

BACKGROUND: Left ventricular diastolic dysfunction (LVDD) is an important precursor of heart failure (HF), but little is known about its relationship with gut dysbiosis and microbial-related metabolites. By leveraging the multi-omics data from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a study with population at high burden of LVDD, we aimed to characterize gut microbiota associated with LVDD and identify metabolite signatures of gut dysbiosis and incident LVDD.
RESULTS: We included up to 1996 Hispanic/Latino adults (mean age: 59.4 years; 67.1% female) with comprehensive echocardiography assessments, gut microbiome, and blood metabolome data. LVDD was defined through a composite criterion involving tissue Doppler assessment and left atrial volume index measurements. Among 1996 participants, 916 (45.9%) had prevalent LVDD, and 212 out of 594 participants without LVDD at baseline developed incident LVDD over a median 4.3 years of follow-up. Using multivariable-adjusted analysis of compositions of microbiomes (ANCOM-II) method, we identified 7 out of 512 dominant gut bacterial species (prevalence > 20%) associated with prevalent LVDD (FDR-q < 0.1), with inverse associations being found for Intestinimonas_massiliensis, Clostridium_phoceensis, and Bacteroide_coprocola and positive associations for Gardnerella_vaginali, Acidaminococcus_fermentans, Pseudomonas_aeruginosa, and Necropsobacter_massiliensis. Using multivariable adjusted linear regression, 220 out of 669 circulating metabolites with detection rate > 75% were associated with the identified LVDD-related bacterial species (FDR-q < 0.1), with the majority being linked to Intestinimonas_massiliensis, Clostridium_phoceensis, and Acidaminococcus_fermentans. Furthermore, 46 of these bacteria-associated metabolites, mostly glycerophospholipids, secondary bile acids, and amino acids, were associated with prevalent LVDD (FDR-q < 0.1), 21 of which were associated with incident LVDD (relative risk ranging from 0.81 [p = 0.001, for guanidinoacetate] to 1.25 [p = 9 × 10-5, for 1-stearoyl-2-arachidonoyl-GPE (18:0/20:4)]). The inclusion of these 21 bacterial-related metabolites significantly improved the prediction of incident LVDD compared with a traditional risk factor model (the area under the receiver operating characteristic curve [AUC] = 0.73 vs 0.70, p = 0.001). Metabolite-based proxy association analyses revealed the inverse associations of Intestinimonas_massilliensis and Clostridium_phoceensis and the positive association of Acidaminococcus_fermentans with incident LVDD.
CONCLUSIONS: In this study of US Hispanics/Latinos, we identified multiple gut bacteria and related metabolites linked to LVDD, suggesting their potential roles in this preclinical HF entity. Video Abstract.

Gut dysbiosis has been linked with both HIV infection and diabetes, but its interplay with metabolic and inflammatory responses in diabetes, particularly in the context of HIV infection, remains unclear.
We first conducted a cross-sectional association analysis to characterize the gut microbial, circulating metabolite, and immune/inflammatory protein features associated with diabetes in up to 493 women (~ 146 with prevalent diabetes with 69.9% HIV +) of the Women\'s Interagency HIV Study. Prospective analyses were then conducted to determine associations of identified metabolites with incident diabetes over 12 years of follow-up in 694 participants (391 women from WIHS and 303 men from the Multicenter AIDS Cohort Study; 166 incident cases were recorded) with and without HIV infection. Mediation analyses were conducted to explore whether gut bacteria-diabetes associations are explained by altered metabolites and proteins.
Seven gut bacterial genera were identified to be associated with diabetes (FDR-q <  0.1), with positive associations for Shigella, Escherichia, Megasphaera, and Lactobacillus, and inverse associations for Adlercreutzia, Ruminococcus, and Intestinibacter. Importantly, the associations of most species, especially Adlercreutzia and Ruminococcus, were largely independent of antidiabetic medications use. Meanwhile, 18 proteins and 76 metabolites, including 3 microbially derived metabolites (trimethylamine N-oxide, phenylacetylglutamine (PAGln), imidazolepropionic acid (IMP)), 50 lipids (e.g., diradylglycerols (DGs) and triradylglycerols (TGs)) and 23 non-lipid metabolites, were associated with diabetes (FDR-q <  0.1), with the majority showing positive associations and more than half of them (59/76) associated with incident diabetes. In mediation analyses, several proteins, especially interleukin-18 receptor 1 and osteoprotegerin, IMP and PAGln partially mediate the observed bacterial genera-diabetes associations, particularly for those of Adlercreutzia and Escherichia. Many diabetes-associated metabolites and proteins were altered in HIV, but no effect modification on their associations with diabetes was observed by HIV.
Among individuals with and without HIV, multiple gut bacterial genera, blood metabolites, and proinflammatory proteins were associated with diabetes. The observed mediated effects by metabolites and proteins in genera-diabetes associations highlighted the potential involvement of inflammatory and metabolic perturbations in the link between gut dysbiosis and diabetes in the context of HIV infection.

BACKGROUND: Separately, both exercise and protein ingestion have been shown to alter the blood and urine metabolome. This study goes a step further and examines changes in the metabolome derived from blood, urine and muscle tissue extracts in response to resistance exercise combined with ingestion of three different protein sources.
METHODS: In an acute parallel study, 52 young males performed one-legged resistance exercise (leg extension, 4 × 10 repetitions at 10 repetition maximum) followed by ingestion of either cricket (insect), pea or whey protein (0.25 g protein/kg fat free mass). Blood and muscle tissue were collected at baseline and three hours after protein ingestion. Urine was collected at baseline and four hours after protein ingestion. Mixed-effects analyses were applied to examine the effect of the time (baseline vs. post), protein (cricket, pea, whey), and time x protein interaction.
RESULTS: Nuclear magnetic resonance (NMR)-based metabolomics resulted in the annotation and quantification of 25 metabolites in blood, 35 in urine and 21 in muscle tissue. Changes in the muscle metabolome after combined exercise and protein intake indicated effects related to the protein source ingested. Muscle concentrations of leucine, methionine, glutamate and myo-inositol were higher after intake of whey protein compared to both cricket and pea protein. The blood metabolome revealed changes in a more ketogenic direction three hours after exercise reflecting that the trial was conducted after overnight fasting. Urinary concentration of trimethylamine N-oxide was significantly higher after ingestion of cricket than pea and whey protein.
CONCLUSIONS: The blood, urine and muscle metabolome showed different and supplementary responses to exercise and ingestion of the different protein sources, and in synergy the summarized results provided a more complete picture of the metabolic state of the body.

METHODS: Consuming goat milk is known to benefit high-fat diet-fed and streptozocin (STZ)-induced diabetic rats, but the underlying mechanisms are unknown. This study is conducted to investigate the metabolic effects of a goat milk diet (a form of goat milk powder) on glucose homeostasis and pancreatic conditions in a mouse model of Type 2 diabetes mellitus (T2DM) induced by STZ.
RESULTS: T2DM mice are fed with a goat-milk-based diet containing 10.3% w/w goat milk powder for 10 weeks for investigating the in vivo effects; a β-cell line MIN6 cells are used to test the in vitro effects of digested goat milk (DGM). Goat milk diet improves the deleterious effects of STZ on fasting glucose levels and glucose tolerance, accelerates pancreatic structure recovery, and alters blood metabolites in mice. Based on the significant differences observed in metabolites, the key pathways, metabolite regulatory enzymes, metabolite molecular modules, and biochemical reactions are identified as critical integrated pathways. DGM promotes the cell activity, glucose transportation, and AKT activation in cultured STZ-treated MIN6 cells in vitro.
CONCLUSIONS: Goat milk diet improves glucose homeostasis and pancreatic conditions of T2DM mice, in association with improved blood metabolite profiles and activation of pancreatic AKT pathway.

Pregnancy and postpartum are periods of intense changes in women\'s metabolism. The knowledge of the metabolites and maternal factors underlying these changes is limited.
We aimed to investigate the maternal factors that could influence serum metabolome changes from late pregnancy to the first months of postpartum.
Sixty-eight healthy women from a Brazilian prospective cohort were included. Maternal blood and general characteristics were collected during pregnancy (28-35 wk) and postpartum (27-45 d). A targeted metabolomics approach was applied to quantify 132 serum metabolites, including amino acids, biogenic amines, acylcarnitines, lysophosphatidylcholines (LPC), diacyl phosphatidylcholines (PC), alkyl:acyl phosphatidylcholines (PC-O), sphingomyelins with (SM) and without hydroxylation [SM(OH)], and hexoses. Metabolome changes from pregnancy to postpartum were measured as log2 fold change (log2FC), and simple linear regressions were employed to evaluate associations between maternal variables and metabolite log2FC. Multiple comparison-adjusted P values of < 0.05 were considered significant.
Of 132 metabolites quantified in serum, 90 changed from pregnancy to postpartum. Most metabolites belonging to PC and PC-O classes decreased, whereas most LPC, acylcarnitines, biogenic amines, and a few amino acids increased in postpartum. Maternal prepregnancy body mass index (ppBMI) showed positive associations with leucine and proline. A clear opposite change pattern was observed for most metabolites across ppBMI categories. Few phosphatidylcholines were decreased in women with normal ppBMI, while an increase was observed in women with obesity. Similarly, women with high postpartum levels of total cholesterol, LDL cholesterol, and non-HDL cholesterol showed increased sphingomyelins, whereas a decrease was observed for women with lower levels of those lipoproteins.
The results revealed several maternal serum metabolomic changes from pregnancy to postpartum, and the maternal ppBMI and plasma lipoproteins were associated with these changes. We highlight the importance of the nutritional care of women prepregnancy to improve their metabolic risk profile.

This study aimed to investigate the changes in the blood metabolic profiles of grazing yaks during the cold season to reveal their physiological status and seek the nutrients needed to be supplemented. Six castrated yaks (3 years old) with 166.8 kg (standard deviation = 5.3) of liveweight grazed in the Qinghai-Tibetan Plateau were used as experimental animals without supplementary feeding. Blood samples of each animal were collected in October and December 2015, and March 2016 for the analysis of serum biochemicals and metabolome. Results showed serum indices involved in protein metabolism in grazing yaks showed greater differences during the cold season than the metabolisms of energy or minerals. Cold stress in December had minor effects on the serum metabolic profiles of yaks compared with those in October. Yaks in October and December shared seven differential serum metabolites and enrichments of the \"arachidonic acid metabolism\" and \"glycine, serine, and threonine metabolism\" pathways compared with those in March caused by the shortage of feeds. Summarily, the nutrient deficiency would be influential on the physiological status of grazing yaks during the cold season, especially on the protein metabolism, which could be improved by supplementary feeds.

BACKGROUND: The establishment of non-invasive diagnostic method for multiple ovulation prediction is helpful to improve the efficiency of multiple ovulation. The blood hormones and metabolites would be suitable indexes for this subject.
METHODS: In this study, 86 estrus ewes (65 of induced estrus (IE) and 21 of spontaneous estrus (SE)) were selected and the blood samples were collected at the day before follicle-stimulating hormone (FSH) injection (1st) and before artificial insemination (2nd). The serum reproductive hormones ofFSH, luteinizing hormone (LH), 17β-Estradiol (E2), progesterone (P4) and anti-Mullerian hormone (AMH) were measured through enzyme linked immunosorbent assay (ELISA) and the untargeted metabolomics analysis was processed through LC-MS/MS. The embryos were collected after 6.5 days of artificial insemination.
RESULTS: In total, 975 and 406 embryos were collected in IE and SE group, respectively. The analysis of reproductive hormones showed that concentrations of FSH, E2 and AMH were positive correlated with the embryo yield while concentrations of LH and P4 were negative correlated in both group at 1st detection. At 2nd detection, the trends of reproductive hormones were similar with 1st except P4, which was positive correlated with embryo yield. The metabolomics analysis showed that 1158 metabolites (721 in positive iron mode and 437 in negative iron mode) were detected and 617 were annotated. In 1st comparation of high and low embryonic yield populations, 56 and 53 differential metabolites were identified in IE and SE group, respectively. The phosphatidyl choline (PC) (19:0/20:5) and PC (18:2/18:3) were shared in two groups. In 2nd comparation, 48 and 49 differential metabolites were identified in IE and SE group, respectively. The PC (18:1/18:2) and pentadecanoic acid were shared. Most differential metabolites were significantly enriched in amino acid, fatty acid metabolism, digestive system secretion and ovarian steroidogenesis pathways.
CONCLUSIONS: This study showed that FSH, P4, AMH, the PC relevant metabolites and some anomic acids could be potential biomarkers for embryonic yield prediction in ovine multiple ovulation. The results would help to explain the relation between blood material and ovarian function and provide a theoretical basis for the multiple ovulation prediction.

METHODS: Habitual diet may be reflected in metabolite profiles that can improve accurate assessment of dietary exposure and further enhance our understanding of their link to health conditions. The study aims to explore the relationship of habitual food intake with blood and urine metabolites in adolescents and young adults.
METHODS: The study population comprises 228 participants (94 males and 134 females) of the DONALD study. Dietary intake is assessed by yearly repeated 3d-food records. Habitual diet is estimated as the average consumption of 23 food groups in adolescence. Using an untargeted metabolomics approach, the study quantifies 2638 metabolites in plasma and 1407 metabolites in urine. In each sex, unique diet-metabolite associations using orthogonal projection to latent structures (oPLS) and random forests (RF) is determined.
RESULTS: Six metabolites in agreement between oPLS and RF in urine, one in female (vanillylmandelate to processed/other meat) and five in males (indole-3-acetamide, and N6-methyladenosine to eggs; hippurate, citraconate/glutaconate, and X - 12111 to vegetables) are observed. No association in blood in agreement is observed.
CONCLUSIONS: A limited reflection of habitual food group intake by single metabolites in urine and not in blood is observed. The explored biomarkers should be confirmed in additional studies.