Project description:The effects of birth weight (BiW; low BiW [LBW] vs. high BiW [HBW]) and estimated breeding value (EBV) for protein deposition (low EBV [LBV] vs. high EBV [HBV]) on N retention, N efficiency, and concentrations of metabolites in plasma and urine related to N efficiency in growing pigs were studied. At an age of 14 wk, 10 LBW-LBV (BiW: 1.07 ± 0.09 [SD] kg; EBV: -2.52 ± 3.97 g/d, compared with an average crossbred pig with a protein deposition of 165 g/d), 10 LBW-HBV (BiW: 1.02 ± 0.13 kg; EBV: 10.47 ± 4.26 g/d), 10 HBW-LBV (BiW: 1.80 ± 0.13 kg; EBV: -2.15 ± 2.28 g/d), and 10 HBW-HBV (BiW: 1.80 ± 0.15 kg; EBV: 11.18 ± 3.68 g/d) male growing pigs were allotted to the experiment. The pigs were individually housed in metabolism cages and were subjected to an N balance study in two sequential periods of 5 d, after an 11-d dietary adaptation period. Pigs were assigned to a protein adequate (A) or protein restricted (R, 70% of A) regime in a change-over design. Pigs were fed 2.8 times the energy requirements for maintenance. Nontargeted metabolomics analyses were performed in urine and blood plasma samples. The N retention (in g/d) was higher in the HBW than in the LBW pigs (P < 0.001). The N retention (in g/[kg metabolic body weight (BW0.75) · d]) and N efficiency, however, were not affected by the BiW of the pigs. The N retention (P = 0.04) and N efficiency (P = 0.04) were higher in HBV than in LVB pigs on the A regime but were not affected by EBV in pigs on the R regime. Restricting the dietary protein supply with 30% decreased the N retention (P < 0.001) but increased the N efficiency (P = 0.003). Nontargeted metabolomics showed that a hexose, free amino acids (AA), and lysophosphatidylcholines were the most important metabolites in plasma for the discrimination between HBV and LBV pigs, whereas metabolites of microbial origin contributed to the discrimination between HBV and LBV pigs in urine. This study shows that BiW does not affect N efficiency in the later life of pigs. Nitrogen efficiency and N retention were higher in HBV than in LBV pigs on the A regime but similar in HBV and LBV pigs on the R regime. In precision feeding concepts aiming to further optimize protein and AA efficiency in pigs, the variation in EBV for protein deposition of pigs should be considered as a factor determining N retention, growth performance, and N efficiency.
Project description:Background/aimsFetal metabolism may be changed by the exposure to maternal factors, and the route to obesity may already set in utero. Cord blood metabolites might predict growth patterns and later obesity. We aimed to characterize associations of cord blood with birth weight, postnatal weight gain, and BMI in adolescence.MethodsOver 700 cord blood samples were collected from infants participating in the German birth cohort study LISAplus. Glycerophospholipid fatty acids (GPL-FA), polar lipids, non-esterified fatty acids (NEFA), and amino acids were analyzed with a targeted, liquid chromatography-tandem mass spectrometry based metabolomics platform. Cord blood metabolites were related to growth factors by linear regression models adjusted for confounding variables.ResultsCord blood metabolites were highly associated with birth weight. Lysophosphatidylcholines C16:1, C18:1, C20:3, C18:2, C20:4, C14:0, C16:0, C18:3, GPL-FA C20:3n-9, and GPL-FA C22:5n-6 were positively related to birth weight, while higher cord blood concentrations of NEFA C22:6, NEFA C20:5, GPL-FA C18:3n-3, and PCe C38:0 were associated with lower birth weight. Postnatal weight gain and BMI z-scores in adolescents were not significantly associated with cord blood metabolites after adjustment for multiple testing.ConclusionPotential long-term programming effects of the intrauterine environment and metabolism on later health cannot be predicted with profiling of the cord blood metabolome.
Project description:Urine has long been a "favored" biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS), direct flow injection mass spectrometry (DFI/LC-MS/MS), inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify) a total of: 209 (209) by NMR, 179 (85) by GC-MS, 127 (127) by DFI/LC-MS/MS, 40 (40) by ICP-MS and 10 (10) by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database containing the complete set of 2651 confirmed human urine metabolite species, their structures (3079 in total), concentrations, related literature references and links to their known disease associations are freely available at http://www.urinemetabolome.ca.
Project description:In recent years, some studies have described metabolic changes during human childbirth labor. Metabolomics today is recognized as a powerful approach in a prenatal research context, since it can provide detailed information during pregnancy and it may enable the identification of biomarkers with potential diagnostic or predictive. This is an observational, longitudinal, prospective cohort study of a total of 51 serial urine samples from 15 healthy pregnant women, aged 29-40 years, which were collected before the onset of labor (out of labor, OL). In the same women, during labor (in labor or dilating phase, IL-DP). Samples were analyzed by hydrophilic interaction ultra-performance liquid chromatography coupled with mass spectrometry (HILIC-UPLC-MS), a highly sensitive, accurate, and unbiased approach. Metabolites were then subjected to multivariate statistical analysis and grouped by metabolic pathway. This method was used to identify the potential biomarkers. The top 20 most discriminative metabolites contributing to the complete separation of OL and IL-DP were identified. Urinary metabolites displaying the largest differences between OL and IL-DP belonged to steroid hormone, particularly conjugated estrogens and amino acids much of this difference is determined by the fetal contribution. In addition, our results highlighted the efficacy of using urine samples instead of more invasive techniques to evaluate the difference in metabolic analysis between OL and IL-DP.
Project description:Exposure to cigarette smoke during development is linked to neurodevelopmental delays and cognitive impairment including impulsivity, attention deficit disorder, and lower IQ. However, brain region specific biomolecular alterations induced by developmental cigarette smoke exposure (CSE) remain largely unexplored. In the current molecular phenotyping study, a mouse model of 'active' developmental CSE (serum cotinine > 50 ng/mL) spanning pre-implantation through third trimester-equivalent brain development (gestational day (GD) 1 through postnatal day (PD) 21) was utilized. Hippocampus tissue collected at the time of cessation of exposure was processed for gel-based proteomic and non-targeted metabolomic profiling with partial least squares-discriminant analysis (PLS-DA) for selection of features of interest. Ingenuity pathway analysis was utilized to identify candidate molecular and metabolic pathways impacted within the hippocampus. CSE impacted glycolysis, oxidative phosphorylation, fatty acid metabolism, and neurodevelopment pathways within the developing hippocampus.
Project description:Hydrolyzed protein diets are extensively used to treat chronic enteropathy (CE) in cats. However, the biochemical effects of such a diet on feline CE have not been characterized. In this study an untargeted 1H nuclear magnetic resonance spectroscopy-based metabolomic approach was used to compare the urinary, plasma, and fecal metabolic phenotypes of cats with CE to control cats with no gastrointestinal signs recruited at the Royal Veterinary College (RVC). In addition, the biomolecular consequences of a hydrolyzed protein diet in cats with CE was also separately determined in cats recruited from the RVC (n = 16) and the University of Bristol (n = 24) and whether these responses differed between dietary responders and non-responders. Here, plasma metabolites related to energy and amino acid metabolism significantly varied between CE and control cats in the RVC cohort. The hydrolyzed protein diet modulated the urinary metabolome of cats with CE (p = 0.005) in both the RVC and Bristol cohort. In the RVC cohort, the urinary excretion of phenylacetylglutamine, p-cresyl-sulfate, creatinine and taurine at diagnosis was predictive of dietary response (p = 0.025) although this was not observed in the Bristol cohort. Conversely, in the Bristol cohort plasma betaine, glycerol, glutamine and alanine at diagnosis was predictive of outcome (p = 0.001), but these same results were not observed in the RVC cohort. The biochemical signature of feline CE in the RVC cohort was consistent with that identified in human and animal models of inflammatory bowel disease. The hydrolyzed protein diet had the same effect on the urinary metabolome of cats with CE at both sites. However, biomarkers that were predictive of dietary response at diagnosis differed between the 2 sites. This may be due to differences in disease severity, disease heterogeneity, factors unrelated to the disease or small sample size at both sites. As such, further studies utilizing larger number of cats are needed to corroborate these findings.
Project description:Low birth weight puppies present an increased risk of neonatal mortality, morbidity, and some long-term health issues. Yet it has not been investigated if those alterations could be linked to the gut microbiota composition and evolution. 57 puppies were weighed at birth and rectal swabs were performed at 5 time points from birth to 28 days of age. Puppies were grouped into three groups based on their birth weight: low birth weight (LBW), normal birth weight (NBW) and high birth weight (HBW). 16S rRNA gene sequencing was used to highlight differences in the fecal microbiota. During the first three weeks, the relative abundance of facultative anaerobic bacteria such as E. coli, C. perfringens and Tyzzerella was higher in LBW feces, but they catch back with the other groups afterwards. HBW puppies showed higher abundances of Faecalibacterium and Bacteroides during the neonatal period, suggesting an earlier maturation of their microbiota. The results of this study suggest that birth weight impact the initial establishment of the gut microbiota in puppies. Innovative strategies would be desired to deal with altered gut microbiota in low birth weight puppies aiming to improve their survival and long term health.
Project description:Feline obesity elicits a plethora of metabolic responses leading to comorbidities, with potential reversal during weight loss. The specific metabolic alterations and biomarkers of organ dysfunction are not entirely understood. Untargeted, high-throughput metabolomic technologies may allow the identification of biological components that change with weight status in cats, increasing our understanding of feline metabolism. The objective of this study was to utilize untargeted metabolomic techniques to identify biomarkers and gain mechanistic insight into the serum metabolite changes associated with reduced food intake and weight loss in overweight cats. During a four-wk baseline period, cats were fed to maintain body weight. For 18 wk following baseline, cats were fed to lose weight at a rate of ~1.5% body weight/wk. Blood serum metabolites were measured at wk 0, 1, 2, 4, 8, 12, and 16. A total of 535 named metabolites were identified, with up to 269 of them being altered (p- and q-values < 0.05) at any time point. A principal component analysis showed a continual shift in metabolite profile as weight loss progressed, with early changes being distinct from those over the long term. The majority of lipid metabolites decreased with weight loss; however, ketone bodies and small lipid particles increased with weight loss. The majority of carbohydrate metabolites decreased with weight loss. Protein metabolites had a variable result, with some increasing, but others decreasing with weight loss. Metabolic mediators of inflammation, oxidative stress, xenobiotics, and insulin resistance decreased with weight loss. In conclusion, global metabolomics identified biomarkers of reduced food intake and weight loss in cats, including decreased markers of inflammation and/or altered macronutrient metabolism.