Metabolomics-Based Biomarkers for Frailty in Chinese Older Adults

Background Frailty is a clinical state characterized by decline in physiological function, and increased vulnerability to adverse outcomes. The biological mechanisms underlying frailty have been extensively studied in recent years. Advances in the multi-omics platforms have provided new information on the molecular mechanisms of frailty. Thus, identifying omics-based biomarkers is helpful for both exploring the physiological mechanisms of frailty and evaluating the risk of frailty development and progression. Objective To identify metabolomics biomarkers and possible pathogenic mechanisms for frailty with untargeted-metabolomics profiling. Methods LC-MS-based untargeted metabolomics analysis was performed on serum samples of 25 frail older inpatients and 49 non-frail older controls. The metabolomics profiling was compared between the two groups. Results We identified 349 metabolites belonging to 46 classes, in which 2 were increased and 3 were decreased in frail older adults. Citrate cycle (with up-regulated cis-Aconitic acid, Fumaric acid, L-Malic acid, and Isocitric acid), fatty acid metabolism (with up-regulated Palmitic acid and L-Palmitoylcarnitine) and tryptophan metabolism (with up-regulated 5-Hydroxy-L-tryptophan, L-Kynurenine, Kynurenic acid, and 5-Hydroxyindoleacetic acid) were significantly associated with frailty phenotype. Conclusions Our results revealed characteristics of metabolites of frailty in Chinese older adults. The citrate cycle related metabolites (Isocitrate, (s)-Malate, Fumarate and cis-Aconitate), saturated fat (Palmitic acid), unsaturated fatty acid (Arachidonate and Linoleic acid), and some essential amino acid (Tryptophan) might be candidate biomarkers for early diagnosis of frailty. Disorders of energy metabolism, lipotoxicity of saturated fatty acids, disturbances of unsaturated fatty acid metabolism, and increased degradation of tryptophan were potential mechanisms and therapeutic targets of frailty.

Metabolites of gut microbiome are associated with glucose metabolism in non-diabetic obese adults: a Chinese monozygotic twin study

Background Evidence suggests gut microbiome is associated with diabetes. However, it’s unclear whether the association remains in non-diabetic participants. A Chinese monozygotic twin study, in which the participants are without diabetes, and are not taking any medications, was conducted to explore the potential association. Methods Nine pairs of adult monozygotic twins were enrolled and divided into two twin-pair groups (a and b). Clinical and laboratory measurements were conducted. Visceral adipose tissue (VAT) was assessed. Fecal samples were collected to analyze the microbiome composition by 16S rDNA gene amplicon sequencing. Liquid chromatography mass spectrometry was performed to detect the metabolites. Results The participants aged 53 years old averagely, with 8 (88.9%) pairs were women. All the participants were obese with VAT higher than 100 cm2 (152.2 ± 31.6). There was no significant difference of VAT between the twin groups (153.6 ± 30.4 cm2 vs. 150.8 ± 29.5 cm2, p = 0.54). Other clinical measurements, including BMI, lipid profiles, fasting insulin and blood glucose, were also not significantly different between groups (p ≥ 0.056), whereas HbA1c level of group a is significantly higher than group b (5.8 ± 0.3% vs. 5.6 ± 0.2%, p = 0.008). The number and richness of OTUs are relatively higher in group a, and 13 metabolites were significantly different between two groups. Furthermore, several of the 13 metabolites could be significantly linked to special taxons. The potential pathway involved drug metabolism-other enzymes, Tryptophan metabolism and Citrate cycle. Conclusions Gut microbiome composition and their metabolites may modulate glucose metabolism in obese adults without diabetes, through Tryptophan metabolism, Citrate cycle and other pathways.

Dietary Supplementation With Creatine Pyruvate Alters Rumen Microbiota Protein Function in Heat-Stressed Beef Cattle

Creatine pyruvate (CrPyr) is a new multifunctional nutrient that can provide both pyruvate and creatine. It has been shown to relieve the heat stress of beef cattle by improving antioxidant activity and rumen microbial protein synthesis, but the mechanism of CrPyr influencing rumen fermentation remains unclear. This study aimed to combine 16S rDNA sequencing and metaproteomics technologies to investigate the microbial composition and function in rumen fluid samples taken from heat-stressed beef cattle treated with or without 60 g/day CrPyr. 16S rDNA sequencing revealed that there were no significant differences in the α-diversity indices between the two groups. By analyzing the level profiles of 700 distinct proteins, we found that the CrPyr administration increased the expression of enzymes involved in specific metabolic pathways including (i) fatty acid β-oxidation; (ii) interconversion from pyruvate to phosphoenolpyruvate, oxaloacetate, acetyl-CoA, and malate; (iii) glycolysis/gluconeogenesis and citrate cycle metabolism; and (iv) biosynthesis of amino acids. These results indicated that the increased generation of adenosine triphosphate during fatty acid β-oxidation or citrate cycle and the up-regulation synthesis of microbial protein in rumen of beef cattle treated with CrPyr may help decrease oxidative stress, regulate energy metabolism, and further improve the rumen fermentation characteristic under heat stress.

Serum-Urine Matched Metabolomics for Predicting Progression of Henoch-Schonlein Purpura Nephritis

Henoch-Schonlein purpura nephritis (HSPN) is a common glomerulonephritis secondary to Henoch-Schonlein purpura (HSP) that affects systemic metabolism. Currently, there is a rarity of biomarkers to predict the progression of HSPN. This work sought to screen metabolic markers to predict the progression of HSPN via serum-urine matched metabolomics. A total of 90 HSPN patients were enrolled, including 46 HSPN (+) patients with severe kidney damage (persistent proteinuria >0.3 g/day) and 44 HSPN (–) patients without obvious symptoms (proteinuria < 0.3 g/day). Untargeted metabolomics was determined by liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-Q/TOF-MS). A total of 38 and 50 differential metabolites were, respectively, identified in serum and urine from the comparison between HSPN (+) and HSPN (–) patients. Altered metabolic pathways in HSPN (+) mainly included glycerophospholipid metabolism, pyruvate metabolism, and citrate cycle. A panel of choline and cis-vaccenic acid gave areas under the curve of 92.69% in serum and 72.43% in urine for differential diagnosis between HSPN (+) and HSPN (–). In addition, the two metabolites showed a significant association with clinical indices of HSPN. These results suggest that serum-urine matched metabolomics comprehensively characterized the metabolic differences between HSPN (+) and HSPN (–), and choline and cis-vaccenic acid could serve as biomarkers to predict HSPN progression.

Genomic Analysis of Curtobacterium Flaccumfaciens Reveals the Differences Between Pathogenic and Nonpathogenic Strains

Purpose Curtobacterium flaccumfaciens is a Gram-positive bacterium which has been isolated from different plants and abiotic environment. Curtobacterium. flaccumfaciens pv. flaccumfaciens (Cff) is a pathogenic bacterium that infects legume, which is causing great economic losses. At the genomic level, the metabolic and phylogenetic characteristics, and differences in pathogenicity between pathogenic and nonpathogenic C. flaccumfaciens strains have not been analyzed in detail. Methods Therefore, in order to discuss the differences in genome, phylogeny, gene function and mobile genetic elements between pathogenic and nonpathogenic strains, pangenomics and comparative genomics were used in this study to analyze 12 C. flaccumfaciens strains. Result The pangenome of C. flaccumfaciens is open. Phylogenetic analysis showed that there was no correlation between the phylogeny and pathogenicity of C. flaccumfaciens. KAAS annotation of the core genome shows that the citrate cycle was incomplete. In addition, gene islands analysis of the three pathogenicity-related genes encoding for pectate lyase, serine protease and cellulases showed that they only existed in the Cffs and LMG3645 strains. LMG3645 might be a pathogenic strain. Conclusion This study clearly and reliably revealed the differences between the pathogenic and nonpathogenic strains of C. flaccumfaciens at the genomic level, and paves the way for further research on its pathogenicity.

Metabolic flux partitioning between the TCA cycle and glyoxylate shunt combined with a reversible methyl citrate cycle provide nutritional flexibility for Mycobacterium tuberculosis

The utilisation of multiple host-derived carbon substrates is required by Mycobacterium tuberculosis (Mtb) to successfully sustain a tuberculosis infection thereby identifying the Mtb specific metabolic pathways and enzymes required for carbon co-metabolism as potential drug targets. Metabolic flux represents the final integrative outcome of many different levels of cellular regulation that contribute to the flow of metabolites through the metabolic network. It is therefore critical that we have an in-depth understanding of the rewiring of metabolic fluxes in different conditions. Here, we employed 13C-metabolic flux analysis using stable isotope tracers (13C and 2H) and lipid fingerprinting to investigate the metabolic network of Mtb growing slowly on physiologically relevant carbon sources in a steady state chemostat. We demonstrate that Mtb is able to efficiently co-metabolise combinations of either cholesterol or glycerol along with C2 generating carbon substrates. The uniform assimilation of the carbon sources by Mtb throughout the network indicated no compartmentalization of metabolism in these conditions however there were substrate specific differences in metabolic fluxes. This work identified that partitioning of flux between the TCA cycle and the glyoxylate shunt combined with a reversible methyl citrate cycle as the critical metabolic nodes which underlie the nutritional flexibility of Mtb. These findings provide new insights into the metabolic architecture that affords adaptability of Mtb to divergent carbon substrates.ImportanceEach year more than 1 million people die of tuberculosis (TB). Many more are infected but successfully diagnosed and treated with antibiotics, however antibiotic-resistant TB isolates are becoming ever more prevalent and so novel therapies are urgently needed that can effectively kill the causative agent. Mtb specific metabolic pathways have been identified as an important drug target in TB. However the apparent metabolic plasticity of this pathogen presents a major obstacle to efficient targeting of Mtb specific vulnerabilities and therefore it is critical to define the metabolic fluxes that Mtb utilises in different conditions. Here, we used 13C-metabolic flux analysis to measure the metabolic fluxes that Mtb uses whilst growing on potential in vivo nutrients. Our analysis identified selective use of the metabolic network that included the TCA cycle, glyoxylate shunt and methyl citrate cycle. The metabolic flux phenotypes determined in this study improves our understanding about the co-metabolism of multiple carbon substrates by Mtb identifying a reversible methyl citrate cycle and the glyoxylate shunt as the critical metabolic nodes which underlie the nutritional flexibility of Mtb.

Targeted metabolomics analysis of postoperative delirium

Postoperative delirium is the most common complication among older adults undergoing major surgery. The pathophysiology of delirium is poorly understood, and no blood-based, predictive markers are available. We characterized the plasma metabolome of 52 delirium cases and 52 matched controls from the Successful Aging after Elective Surgery (SAGES) cohort (N = 560) of patients ≥ 70 years old without dementia undergoing scheduled major non-cardiac surgery. We applied targeted mass spectrometry with internal standards and pooled controls using a nested matched case-control study preoperatively (PREOP) and on postoperative day 2 (POD2) to identify potential delirium risk and disease markers. Univariate analyses identified 37 PREOP and 53 POD2 metabolites associated with delirium and multivariate analyses achieved significant separation between the two groups with an 11-metabolite prediction model at PREOP (AUC = 83.80%). Systems biology analysis using the metabolites with differential concentrations rendered “valine, leucine, and isoleucine biosynthesis” at PREOP and “citrate cycle” at POD2 as the most significantly enriched pathways (false discovery rate < 0.05). Perturbations in energy metabolism and amino acid synthesis pathways may be associated with postoperative delirium and suggest potential mechanisms for delirium pathogenesis. Our results could lead to the development of a metabolomic delirium predictor.

Gut microbiome and serum metabolome alterations in isolated dystonia

Background Dystonia is a complex neurological movement disorder characterised by involuntary muscle contractions. The relationship between the gut microbiota and isolated dystonia remains poorly explored. Methods We collected faeces and blood samples to study the microbiome and the serum metabolome from a cohort of 57 drug-naïve isolated dystonia patients and 27 age- and environment-matched healthy individuals. We first sequenced the V4 regions of the 16S rDNA gene from all faeces samples. Further, we performed metagenomic sequencing of gut microbiome and non-targeted metabolomics profiling of serum from dystonia patients with significant dysbiosis. Results Gut microbial β-diversity was significantly different, with a more heterogeneous community structure among dystonia individuals than healthy controls, while no difference in α-diversity was found. Gut microbiota in dystonia patients was enriched with Blautia obeum, Dorea longicatena and Eubacterium hallii, but depleted with Bacteroides vulgatus and Bacteroides plebeius. Metagenomic sequencing revealed that genes related to the citrate cycle, vitamin B6 and glycan metabolism were less abundant in dystonia, while genes linked to purine and tryptophan biosynthesis were more abundant. Serum metabolome analysis revealed altered levels of tyrosine and glutamate. The integrative analysis of the gut microbiome and serum metabolomics identified dystonia-associated gut microbial species linked to changes in serum metabolites, reflecting the effect of the gut microbiome on metabolic activity in isolated dystonia. Conclusion This study is the first to reveal gut microbial dysbiosis in dystonia patients. Our findings identified previously unknown links between intestinal microbiota alterations, circulating amino acids and dystonia, providing new insight into the pathogenesis of isolated dystonia.

Plasma Metabolomics Characteristic of Gout Patients With Regular Glucose, Blood Pressure, and Blood Lipid

BackgroundGout is a metabolic disease and is the most common form of inflammatory arthritis affecting men. However, the pathogenesis of gout is still uncertain, and novel biomarkers are needed for early prediction and diagnosis of gout. The aim of this study is to reveal the metabolic alterations in plasma of gout patients and discover novel molecular biomarkers for early diagnosis. MethodsMetabonomics was employed to screen and identify novel biomarkers of gout based on human plasma. Ultra High-Pressure Liquid Chromatography-Mass Spectrometry (UHPLC-MS) and orthogonal signal correction partial least squares discriminate analysis (OPLS-DA) were also used for metabonomics study. Kyoto Encyclopedia of Genes and Genomes (KEGG) and MetaboAnalyst were used for pathway enrichment analysis.ResultsIn this study, 51 metabolites in positive ion mode and 39 metabolites in negative ion mode were selected as remarkable significant variables between gout and healthy control group. Four unique pathways were found, namely Citrate cycle (TCA cycle), cysteine and methionine metabolism and alanine, aspartate, and glutamate metabolism. A total of 7 metabolites with AUC>0.75 were involved in the above three metabolic pathways, including L-Malic acid，Pyruvate，cis-Aconitate, Cysteine-S-sulfate, L-2-Aminobutyric acid, L-Methionine, Succinic semialdehyde.ConclusionThe present study identified the plasma metabolomics characteristic of gout through UHPLC-MS. The differential metabolites pathways of gout screened out were involved in Citrate cycle (TCA cycle), cysteine and methionine metabolism and alanine, aspartate, and glutamate metabolism. The metabolomics characteristic of gout could provide novel insights into the pathogenesis of gout.