Non-targeted urine metabolomics and associations with prevalent and incident type 2 diabetes

Better risk prediction and new molecular targets are key priorities in type 2 diabetes (T2D) research. Little is known about the role of the urine metabolome in predicting the risk of T2D. We aimed to use non-targeted urine metabolomics to discover biomarkers and improve risk prediction for T2D. Urine samples from two community cohorts of 1,424 adults were analyzed by ultra-performance liquid chromatography/mass spectrometry (UPLC-MS). In a discovery/replication design, three out of 62 annotated metabolites were associated with prevalent T2D, notably lower urine levels of 3-hydroxyundecanoyl-carnitine. In participants without diabetes at baseline, LASSO regression in the training set selected six metabolites that improved prediction of T2D beyond established risk factors risk over up to 12 years' follow-up in the test sample, from C-statistic 0.866 to 0.892. Our results in one of the largest non-targeted urinary metabolomics study to date demonstrate the role of the urine metabolome in identifying at-risk persons for T2D and suggest urine 3-hydroxyundecanoyl-carnitine as a biomarker candidate.Peer reviewe

Exploring the Bone Proteome to Help Explain Altered Bone Remodeling and Preservation of Bone Architecture and Strength in Hibernating Marmots

Periods of physical inactivity increase bone resorption and cause bone loss and increased fracture risk. However, hibernating bears, marmots, and woodchucks maintain bone structure and strength, despite being physically inactive for prolonged periods annually. We tested the hypothesis that bone turnover rates would decrease and bone structural and mechanical properties would be preserved in hibernating marmots (Marmota flaviventris). Femurs and tibias were collected from marmots during hibernation and in the summer following hibernation. Bone remodeling was significantly altered in cortical and trabecular bone during hibernation with suppressed formation and no change in resorption, unlike the increased bone resorption that occurs during disuse in humans and other animals. Trabecular bone architecture and cortical bone geometrical and mechanical properties were not different between hibernating and active marmots, but bone marrow adiposity was significantly greater in hibernators. Of the 506 proteins identified in marmot bone, 40 were significantly different in abundance between active and hibernating marmots. Monoaglycerol lipase, which plays an important role in fatty acid metabolism and the endocannabinoid system, was 98-fold higher in hibernating marmots compared with summer marmots and may play a role in regulating the changes in bone and fat metabolism that occur during hibernation

Metabolomics of sorghum roots during nitrogen stress reveals compromised metabolic capacity for salicylic acid biosynthesis

Sorghum (Sorghum bicolor [L.] Moench) is the fifth most productive cereal crop worldwide with some hybrids having high biomass yield traits making it promising for sustainable, economical biofuel production. To maximize biofuel feedstock yields, a more complete understanding of metabolic responses to low nitrogen (N) will be useful for incorporation in crop improvement efforts. In this study, 10 diverse sorghum entries (including inbreds and hybrids) were field-grown under low and full N conditions and roots were sampled at two time points for metabolomics and 16S amplicon sequencing. Roots of plants grown under low N showed altered metabolic profiles at both sampling dates including metabolites important in N storage and synthesis of aromatic amino acids. Complementary investigation of the rhizosphere microbiome revealed dominance by a single operational taxonomic unit (OTU) in an early sampling that was taxonomically assigned to the genus Pseudomonas. Abundance of this Pseudomonas OTU was significantly greater under low N in July and was decreased dramatically in September. Correlation of Pseudomonas abundance with root metabolites revealed a strong negative association with the defense hormone salicylic acid (SA) under full N but not under low N, suggesting reduced defense response. Roots from plants with N stress also contained reduced phenylalanine, a precursor for SA, providing further evidence for compromised metabolic capacity for defense response under low N conditions. Our findings suggest that interactions between biotic and abiotic stresses may affect metabolic capacity for plant defense and need to be concurrently prioritized as breeding programs become established for biofuels production on marginal soils

Comparison of Machine Learning Algorithms for Predictive Modeling of Beef Attributes Using Rapid Evaporative Ionization Mass Spectrometry (REIMS) Data

Ambient mass spectrometry is an analytical approach that enables ionization of molecules under open-air conditions with no sample preparation and very fast sampling times. Rapid evaporative ionization mass spectrometry (REIMS) is a relatively new type of ambient mass spectrometry that has demonstrated applications in both human health and food science. Here, we present an evaluation of REIMS as a tool to generate molecular scale information as an objective measure for the assessment of beef quality attributes. Eight different machine learning algorithms were compared to generate predictive models using REIMS data to classify beef quality attributes based on the United States Department of Agriculture (USDA) quality grade, production background, breed type and muscle tenderness. The results revealed that the optimal machine learning algorithm, as assessed by predictive accuracy, was different depending on the classification problem, suggesting that a “one size fits all” approach to developing predictive models from REIMS data is not appropriate. The highest performing models for each classification achieved prediction accuracies between 81.5–99%, indicating the potential of the approach to complement current methods for classifying quality attributes in beef

Glucose challenge metabolomics implicates medium-chain acylcarnitines in insulin resistance

Insulin resistance (IR) predisposes to type 2 diabetes and cardiovascular disease but its causes are incompletely understood. Metabolic challenges like the oral glucose tolerance test (OGTT) can reveal pathogenic mechanisms. We aimed to discover associations of IR with metabolite trajectories during OGTT. In 470 non-diabetic men (age 70.6 ± 0.6 years), plasma samples obtained at 0, 30 and 120 minutes during an OGTT were analyzed by untargeted liquid chromatography-mass spectrometry metabolomics. IR was assessed with the hyperinsulinemic-euglycemic clamp method. We applied age-adjusted linear regression to identify metabolites whose concentration change was related to IR. Nine trajectories, including monounsaturated fatty acids, lysophosphatidylethanolamines and a bile acid, were significantly associated with IR, with the strongest associations observed for medium-chain acylcarnitines C10 and C12, and no associations with L-carnitine or C2-, C8-, C14- or C16-carnitine. Concentrations of C10- and C12-carnitine decreased during OGTT with a blunted decline in participants with worse insulin resistance. Associations persisted after adjustment for obesity, fasting insulin and fasting glucose. In mouse 3T3-L1 adipocytes exposed to different acylcarnitines, we observed blunted insulin-stimulated glucose uptake after treatment with C10- or C12-carnitine. In conclusion, our results identify medium-chain acylcarnitines as possible contributors to IR

Информационные технологии в археологии

Материалы XIV Междунар. науч. конф. студентов, магистрантов, аспирантов и молодых ученых, Гомель, 13–14 мая 2021 г

Effect of Insulin Resistance on Monounsaturated Fatty Acid Levels : A Multi-cohort Non-targeted Metabolomics and Mendelian Randomization Study

Insulin resistance (IR) and impaired insulin secretion contribute to type 2 diabetes and cardiovascular disease. Both are associated with changes in the circulating metabolome, but causal directions have been difficult to disentangle. We combined untargeted plasma metabolomics by liquid chromatography/mass spectrometry in three non-diabetic cohorts with Mendelian Randomization (MR) analysis to obtain new insights into early metabolic alterations in IR and impaired insulin secretion. In up to 910 elderly men we found associations of 52 metabolites with hyperinsulinemic-euglycemic clamp-measured IR and/or beta-cell responsiveness (disposition index) during an oral glucose tolerance test. These implicated bile acid, glycerophospholipid and caffeine metabolism for IR and fatty acid biosynthesis for impaired insulin secretion. In MR analysis in two separate cohorts (n = 2,613) followed by replication in three independent studies profiled on different metabolomics platforms (n = 7,824 / 8,961 / 8,330), we discovered and replicated causal effects of IR on lower levels of palmitoleic acid and oleic acid. A trend for a causal effect of IR on higher levels of tyrosine reached significance only in meta-analysis. In one of the largest studies combining "gold standard" measures for insulin responsiveness with non-targeted metabolomics, we found distinct metabolic profiles related to IR or impaired insulin secretion. We speculate that the causal effects on monounsaturated fatty acid levels could explain parts of the raised cardiovascular disease risk in IR that is independent of diabetes development.Peer reviewe

Portrait of a Pathogen: The Mycobacterium tuberculosis Proteome In Vivo

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), is a facultative intracellular pathogen that can persist within the host. The bacteria are thought to be in a state of reduced replication and metabolism as part of the chronic lung infection. Many in vitro studies have dissected the hypothesized environment within the infected lung, defining the bacterial response to pH, starvation and hypoxia. While these experiments have afforded great insight, the picture remains incomplete. The only way to study the combined effects of these environmental factors and the mycobacterial response is to study the bacterial response in vivo.We used the guinea pig model of tuberculosis to examine the bacterial proteome during the early and chronic stages of disease. Lungs were harvested thirty and ninety days after aerosol challenge with Mtb, and analyzed by liquid chromatography-mass spectrometry. To date, in vivo proteomics of the tubercle bacillus has not been described and this work has generated the first large-scale shotgun proteomic data set, comprising over 500 unique protein identifications. Cell wall and cell wall processes, and intermediary metabolism and respiration were the two major functional classes of proteins represented in the infected lung. These classes of proteins displayed the greatest heterogeneity indicating important biological processes for establishment of a productive bacterial infection and its persistence. Proteins necessary for adaptation throughout infection, such as nitrate/nitrite reduction were found at both time points. The PE-PPE protein class, while not well characterized, represented the third most abundant category and showed the most consistent expression during the infection.Cumulatively, the results of this work may provide the basis for rational drug design - identifying numerous Mtb proteins, from essential kinases to products involved in metal regulation and cell wall remodeling, all present throughout the course of infection

Improved Detection of Quantitative Differences Using a Combination of Spectral Counting and MS/MS Total Ion Current

Label-free quantitative strategies are commonly used in shotgun proteomics to detect differences in protein abundance between biological sample groups. Here, we have employed a combination of two such approaches, spectral counting (SpC) and average MS/MS total ion current (MS² TIC), for the analysis of rat kidney mitochondria in response to metabolic acidosis. In total, 49 proteins were observed to be significantly altered in response to metabolic acidosis (<i>p</i>-value < 0.05). Of these, 32 proteins were uniquely observed as significantly different by SpC, 14 by MS² TIC, and only 3 by both approaches. Western blot analysis was performed on a subset of these proteins to validate the observed abundance differences. This study illustrates the utility and ease of combining these two label-free quantitative approaches to increase the number of detected protein abundance differences in the shotgun analysis of complex biological samples