Serum Branched-Chain Amino Acid Metabolites Increase in Males When Aerobic Exercise Is Initiated with Low Muscle Glycogen

This study used global metabolomics to identify metabolic factors that might contribute to muscle anabolic resistance, which develops when aerobic exercise is initiated with low muscle glycogen using global metabolomics. Eleven men completed this randomized, crossover study, completing two cycle ergometry glycogen depletion trials, followed by 24 h of isocaloric refeeding to elicit low (LOW; 1.5 g/kg carbohydrate, 3.0 g/kg fat) or adequate (AD; 6.0 g/kg carbohydrate 1.0 g/kg fat) glycogen. Participants then performed 80 min of cycling (64 ± 3% VO2 peak) while ingesting 146 g carbohydrate. Serum was collected before glycogen depletion under resting and fasted conditions (BASELINE), and before (PRE) and after (POST) exercise. Changes in metabolite profiles were calculated by subtracting BASELINE from PRE and POST within LOW and AD. There were greater increases (p < 0.05, Q < 0.10) in 64% of branched-chain amino acids (BCAA) metabolites and 69% of acyl-carnitine metabolites in LOW compared to AD. Urea and 3-methylhistidine had greater increases (p < 0.05, Q < 0.10) in LOW compared to AD. Changes in metabolomics profiles indicate a greater reliance on BCAA catabolism for substrate oxidation when exercise is initiated with low glycogen stores. These findings provide a mechanistic explanation for anabolic resistance associated with low muscle glycogen, and suggest that exogenous BCAA requirements to optimize muscle recovery are likely greater than current recommendations.

Abstract MP39: Metabolic And Gene Expression Profiling Reveal Disparities In Absorption And Metabolism Of Butyrate And Lysine In The Colon Of Spontaneously Hypertensive Rodents

Introduction: Metabolic dysregulation and gut dysbiosis are linked to hypertension. The proximal colon is the main site of metabolism and absorption of short chain fatty acid butyrate. Reduced circulating butyrate concurrently with elevated fecal levels have been reported in human and rodent hypertension. We tested the hypothesis that both the transport and metabolism of butyrate as well as the overall metabolic profile are dysregulated in the colon of the Spontaneously Hypertensive rats (SHR) compared to the Wistar Kyoto (WKY) rats. Methods: Proximal colons from adult male WKY and SHR were placed in oxygenated warmed Ussing chamber buffer containing dextrose, and physiologically relevant concentration of butyrate (40mM) was applied to the luminal side of the colon. Following 1hr incubation, butyrate levels from the luminal and basolateral sides of the Ussing chamber were measured with high performance liquid chromatography to establish butyrate colonic transport and metabolism. Global metabolomics was performed in Ussing chamber media and in the plasma of WKY and SHR to determine the overall metabolic profile. RNA-seq data in the gut epithelium of WKY and SHR was used to elucidate putative signaling pathways altered in rodent hypertension. Results: Both the colonic transport and metabolism of butyrate were significantly impaired in the SHR. In addition, global metabolomics identified reduced levels of essential amino acid L-lysine, among other metabolites, on the basolateral side of the Ussing chamber and in the plasma of the SHR compared to WKY. Enriched metabolite pathways disrupted in the SHR included lysine degradation. RNA-seq revealed differential expression of several fatty acid and amino acid transporters in the colonic epithelium of the SHR. Conclusion: Colonic transport and metabolism of butyrate are reduced in the SHR, accompanied by dysregulation in the metabolism of the essential amino acid lysine in the gut. This, coupled with reduced expression levels of several fatty acid and amino acid transporters in the gut, suggest aberrant host-microbiota communication and colonic metabolic dysfunction in the context of hypertension.

Global biochemical analysis of plasma, serum and whole blood collected using various anticoagulant additives

Introduction Analysis of blood for the evaluation of clinically relevant biomarkers requires precise collection and sample handling by phlebotomists and laboratory staff. An important consideration for the clinical application of metabolomics are the different anticoagulants utilized for sample collection. Most studies that have characterized differences in metabolite levels in various blood collection tubes have focused on single analytes. We define analyte levels on a global metabolomics platform following blood sampling using five different, but commonly used, clinical laboratory blood collection tubes (i.e., plasma anticoagulated with either EDTA, lithium heparin or sodium citrate, along with no additive (serum), and EDTA anticoagulated whole blood). Methods Using an untargeted metabolomics platform we analyzed five sample types after all had been collected and stored at -80°C. The biochemical composition was determined and differences between the samples established using matched-pair t-tests. Results We identified 1,117 biochemicals across all samples and detected a mean of 1,036 in the sample groups. Compared to the levels of metabolites in EDTA plasma, the number of biochemicals present at statistically significant different levels (p<0.05) ranged from 452 (serum) to 917 (whole blood). Several metabolites linked to screening assays for rare diseases including acylcarnitines, bilirubin and heme metabolites, nucleosides, and redox balance metabolites varied significantly across the sample collection types. Conclusions Our study highlights the widespread effects and importance of using consistent additives for assessing small molecule levels in clinical metabolomics. The biochemistry that occurs during the blood collection process creates a reproducible signal that can identify specimens collected with different anticoagulants in metabolomic studies. Impact statement In this manuscript, normal/healthy donors had peripheral blood collected using multiple anticoagulants as well as serum during a fasted blood draw. Global metabolomics is a new technology being utilized to draw clinical conclusions and we interrogated the effects of different anticoagulants on the levels of biochemicals from each of the donors. Characterizing the effects of the anticoagulants on biochemical levels will help researchers leverage the information using global metabolomics in order to make conclusions regarding important disease biomarkers.

Comprehensive Meta-Analysis of COVID-19 Global Metabolomics Datasets

The novel coronavirus SARS-CoV-2 has spread across the world since 2019, causing a global pandemic. The pathogenesis of the viral infection and the associated clinical presentations depend primarily on host factors such as age and immunity, rather than the viral load or its genetic variations. A growing number of omics studies have been conducted to characterize the host immune and metabolic responses underlying the disease progression. Meta-analyses of these datasets have great potential to identify robust molecular signatures to inform clinical care and to facilitate therapeutics development. In this study, we performed a comprehensive meta-analysis of publicly available global metabolomics datasets obtained from three countries (United States, China and Brazil). To overcome high heterogeneity inherent in these datasets, we have (a) implemented a computational pipeline to perform consistent raw spectra processing; (b) conducted meta-analyses at pathway levels instead of individual feature levels; and (c) performed visual data mining on consistent patterns of change between disease severities for individual studies. Our analyses have yielded several key metabolic signatures characterizing disease progression and clinical outcomes. Their biological interpretations were discussed within the context of the current literature. To the best of our knowledge, this is the first comprehensive meta-analysis of global metabolomics datasets of COVID-19.

HPLC-HRMS Global Metabolomics Approach for the Diagnosis of “Olive Quick Decline Syndrome” Markers in Olive Trees Leaves

Olive quick decline syndrome (OQDS) is a multifactorial disease affecting olive plants. The onset of this economically devastating disease has been associated with a Gram-negative plant pathogen called Xylella fastidiosa (Xf). Liquid chromatography separation coupled to high-resolution mass spectrometry detection is one the most widely applied technologies in metabolomics, as it provides a blend of rapid, sensitive, and selective qualitative and quantitative analyses with the ability to identify metabolites. The purpose of this work is the development of a global metabolomics mass spectrometry assay able to identify OQDS molecular markers that could discriminate between healthy (HP) and infected (OP) olive tree leaves. Results obtained via multivariate analysis through an HPLC-ESI HRMS platform (LTQ-Orbitrap from Thermo Scientific) show a clear separation between HP and OP samples. Among the differentially expressed metabolites, 18 different organic compounds highly expressed in the OP group were annotated; results obtained by this metabolomic approach could be used as a fast and reliable method for the biochemical characterization of OQDS and to develop targeted MS approaches for OQDS detection by foliage analysis.