Significant Differences In Metabolites Research Articles

Metabolic landscape and pathogenic insights: a comprehensive analysis of high ovarian response in infertile women undergoing in vitro fertilization.

In the realm of assisted reproduction, a subset of infertile patients demonstrates high ovarian response following controlled ovarian stimulation (COS), with approximately 29.7% facing the risk of Ovarian Hyperstimulation Syndrome (OHSS). Management of OHSS risk often necessitates embryo transfer cancellation, leading to delayed prospects of successful pregnancy and significant psychological distress. Regrettably, these patients have received limited research attention, particularly regarding their metabolic profile. In this study, we aim to utilize gas chromatography-mass spectrometry (GC-MS) to reveal these patients' unique serum metabolic profiles and provide insights into the disease's pathogenesis. We categorized 145 infertile women into two main groups: the CON infertility group from tubal infertility patients and the Polycystic Ovary Syndrome (PCOS) infertility group. Within these groups, we further subdivided them into four categories: patients with normal ovarian response (CON-NOR group), patients with high ovarian response and at risk for OHSS (CON-HOR group) within the CON group, as well as patients with normal ovarian response (PCOS-NOR group) and patients with high ovarian response and at risk for OHSS (PCOS-HOR group) within the PCOS group. Serum metabolic profiles were analyzed using GC-MS. The risk criteria for OHSS were: the number of developing follicles > 20, peak Estradiol (E2) > 4000pg/mL, and Anti-Müllerian Hormone (AMH) levels > 4.5ng/mL. The serum metabolomics analysis revealed four different metabolites within the CON group and 14 within the PCOS group. Remarkably, 10-pentadecenoic acid emerged as a discernible risk metabolite for the CON-HOR, also found to be a differential metabolite between CON-NOR and PCOS groups. cysteine and 5-methoxytryptamine were also identified as risk metabolites for the PCOS-HOR. Furthermore, KEGG analysis unveiled significant enrichment of the aminoacyl-tRNA biosynthesis pathway among the metabolites differing between PCOS-NOR and PCOS-HOR. Our study highlights significant metabolite differences between patients with normal ovarian response and those with high ovarian response and at risk for OHSS within both the tubal infertility control group and PCOS infertility group. Importantly, we observe metabolic similarities between patients with PCOS and those with a high ovarian response but without PCOS, suggesting potential parallels in their underlying causes.

Unveiling Metal Tolerance Mechanisms in Leersia hexandra Swartz under Cr/Ni Co-Pollution by Studying Endophytes and Plant Metabolites.

Heavy metal pollution poses significant environmental challenges, and understanding how plants and endophytic bacteria interact to mitigate these challenges is of utmost importance. In this study, we investigated the roles of endophytic bacteria, particularly Chryseobacterium and Comamonas, in Leersia hexandra Swartz (L. hexandra) in response to chromium and nickel co-pollution. Our results demonstrated the remarkable tolerance of Chryseobacterium and Comamonas to heavy metals, and their potential to become dominant species in the presence of co-pollution. We observed a close relationship between these endophytic bacteria and the significant differences in metabolites, particularly carbohydrates, flavonoids, and amino acids in L. hexandra. These findings shed light on the potential of endophytic bacteria to promote the production of aspartic acid and other metabolites in plants as a response to abiotic stressors. Furthermore, our study presents a new direction for plant and bioremediation strategies in heavy metal pollution and enhances our understanding of L. hexandra's mechanisms for heavy metal tolerance.

The effect of Lactococcus lactis CICC 23610 fermentation on the physicochemical properties and flavor formation of oat beverage

AbstractBackground and ObjectivesProbiotic fermentation may contribute to enhancing the flavor and nutrients of grain beverages. The aim of this study was to investigate the effect of Lactococcus lactis (L. lactis CICC 23610) fermentation on the physicochemical properties, flavor formation, and metabolomics of oat beverages.FindingsResults showed that L. lactis CICC 23610 grew rapidly in oat substrate and brought a surge in acidity, apparent viscosity, and β‐glucan content. The final amount of lactic acid, sweet amino acids, and umami amino acids metabolites was also increased. Meanwhile, 15 volatile flavor components (VFCs) were identified as key aroma compounds in fermented oat beverages. The levels of 2,3‐butanedione, propionic acid, hexanoic acid, and heptanone rose, giving the beverage a tart, creamy, and sweet flavor, and the undesirable odors of hexanal, n‐octanal, nonanal, and 2‐pentylfuran were reduced. In addition, significant differences in metabolites based on untargeted metabolomics analyses of oat beverages before and after fermentation were mainly focused on organic acids, fatty acids, and short peptides. The sensory analysis showed that the overall acceptability of fermented oat beverages was significantly improved.ConclusionsIt could be concluded that the effects of free amino acids (FAAs), organic acids, and VFCs on flavor were mainly reflected in three indicators of odor, acidity, and umami.Significance and NoveltyThe encouraging results confirmed that probiotic fermentation is a promising method to enhance the overall quality of oat beverages, providing valuable insights into future industrial upgrades of grain beverages.

A metabolomics study on carcinogenesis of ground-glass nodules.

This study aimed to identify differential metabolites and key metabolic pathways between lung adenocarcinoma (LUAD) tissues and normal lung (NL) tissues using metabolomics techniques, to discover potential biomarkers for the early diagnosis of lung cancer. Forty-five patients with primary ground-glass nodules (GGN) identified on computed tomography imaging and who were willing to undergo surgery at Shanghai General Hospital from December 2021 to December 2022 were recruited to the study. All participants underwent video thoracoscopy surgery with segmental or wedge resection of the lung. Tissue samples for pathological examination were collected from the site of ground-glass nodules (GGN) lesion and 3 cm away from the lesion (NL). The pathology results were 35 lung adenocarcinoma (LUAD) cases (13 invasive adenocarcinoma, 14 minimally invasive adenocarcinoma, and eight adenocarcinoma in situ), 10 benign samples, and 45 NL tissues. For the untargeted metabolomics technique, 25 LUAD samples were assigned as the case group and 30 NL tissues as the control group. For the targeted metabolomics technique, ten LUAD samples were assigned as the case group and 15 NL tissues as the control group. Samples were analyzed by untargeted and targeted metabolomics, with liquid chromatography-tandem mass spectrometry detection used as part of the experimental procedure. Untargeted metabolomics revealed 164 differential metabolites between the case and control groups, comprising 110 up regulations and 54 down regulations. The main metabolic differences found by the untargeted method were organic acids and their derivatives. Targeted metabolomics revealed 77 differential metabolites between the case and control groups, comprising 69 up regulations and eight down regulations. The main metabolic changes found by the targeted method were fatty acids, amino acids, and organic acids. The levels of organic acids such as lactic acid, fumaric acid, and malic acid were significantly increased in LUAD tissue compared to NL. Specifically, an increased level of L-lactic acid was found by both untargeted (variable importance in projection [VIP] = 1.332, fold-change [FC] = 1.678, q = 0.000) and targeted metabolomics (VIP = 1.240, FC = 1.451, q = 0.043). Targeted metabolomics also revealed increased levels of fumaric acid (VIP = 1.481, FC = 1.764, q = 0.106) and L-malic acid (VIP = 1.376, FC = 1.562, q = 0.012). Most of the 20 differential fatty acids identified were downregulated, including dodecanoic acid (VIP = 1.416, FC = 0.378, q = 0.043) and tridecane acid (VIP = 0.880, FC = 0.780, q = 0.106). Furthermore, increased levels of differential amino acids were found in LUAD samples. Lung cancer is a complex and heterogeneous disease with diverse genetic alterations. The study of metabolic profiles is a promising research field in this cancer type. Targeted and untargeted metabolomics revealed significant differences in metabolites between LUAD and NL tissues, including elevated levels of organic acids, decreased levels of fatty acids, and increased levels of amino acids. These metabolic features provide valuable insights into LUAD pathogenesis and can potentially serve as biomarkers for prognosis and therapy response.

Untargeted metabolomic, and proteomic analysis identifies metabolic biomarkers and pathway alterations in individuals with 22q11.2 deletion syndrome

IntroductionThe chromosome 22q11.2 deletion syndrome (22q11.2DS) is characterized by a well-defined microdeletion and is associated with a wide range of brain-related phenotypes including schizophrenia spectrum disorders (SCZ), autism spectrum disorders (ASD), anxiety disorders and attention deficit disorders (ADHD). The typically deleted region in 22q11.2DS contains multiple genes which haploinsufficiency has the potential of altering the protein and the metabolic profiles.Objectives Alteration in metabolic processes and downstream protein pathways during the early brain development may help to explain the increased prevalence of the observed neurodevelopmental phenotypes in 22q11.2DS. However, relatively little is known about the correlation of dysregulated protein/metabolite expression and neurobehavioral impairments in individuals who developed them over time.Methods In this study, we performed untargeted metabolic and proteomic analysis in plasma samples derived from 30 subjects including 16 participants with 22q11.2DS and 14 healthy controls (TD) enrolled in a longitudinal study, aiming to identify a metabolic and protein signature informing about the underlying mechanisms involved in disease development and progression. The metabolic and proteomic profiles were also compared between the participants with 22q11.2DS with and without various comorbidities, such as medical involvement, psychiatric conditions, and autism spectrum disorder (ASD) to detect potential changes among multiple specimens, collected overtime, with the aim to understand the basic underlying mechanisms involved in disease development and progression.ResultsWe observed a large number of statistically significant differences in metabolites between the two groups. Among them, the levels of taurine and arachidonic acid were significantly lower in 22q11.2DS compared to the TD group. In addition, we identified 16 proteins that showed significant changes in expression levels (adjusted P < 0.05) in 22q11.2DS as compared to TD, including those involved in 70 pathways such as gene expression, the PI3K-Akt signaling pathway and the complement system. Within participants with 22q11.2DS, no significant changes in those with and without medical or psychiatric conditions were observed.ConclusionTo our knowledge, this is the first report on plasma metabolic and proteomic profiling and on the identification of unique biomarkers in 22q11.2DS. These findings may suggest the potential role of the identified metabolites and proteins as biomarkers for the onset of comorbid conditions in 22q11.2DS. Ultimately, the altered protein pathways in 22q11.2DS may provide insights of the biological mechanisms underlying the neurodevelopmental phenotype and may provide missing molecular outcome measures in future clinical trials to assess early-diagnosis treatment and the efficacy of response to targeted treatment.

Systematic review of metabolomic alterations in ulcerative colitis: unveiling key metabolic signatures and pathways.

Despite numerous metabolomic studies on ulcerative colitis (UC), the results have been highly variable, making it challenging to identify key metabolic abnormalities in UC. This study aims to uncover key metabolites and metabolic pathways in UC by analyzing existing metabolomics data. A systematic review. We conducted a comprehensive search in databases (PubMed, Cochrane Library, Embase, and Web of Science) and relevant study references for metabolomic research on UC up to 28 December 2022. Significant metabolite differences between UC patients and controls were identified, followed by an analysis of relevant metabolic pathways. This review incorporated 78 studies, identifying 2868 differentially expressed metabolites between UC patients and controls. The metabolites were predominantly from 'lipids and lipid-like molecules' and 'organic acids and derivatives' superclasses. We found 101 metabolites consistently altered in multiple datasets within the same sample type and 78 metabolites common across different sample types. Of these, 62 metabolites exhibited consistent regulatory trends across various datasets or sample types. Pathway analysis revealed 22 significantly altered metabolic pathways, with 6 pathways being recurrently enriched across different sample types. This study elucidates key metabolic characteristics in UC, offering insights into molecular mechanisms and biomarker discovery for the disease. Future research could focus on validating these findings and exploring their clinical applications.

Molecular mechanism underlying the degradation of tetracycline by Apiotrichum loubieri MFZ-16

Microbial degradation of tetracycline (TC) is promising owing to its high efficiency and low price; however, a thorough knowledge of its biotransformation is still lacking. In this study, we isolated a novel TC-degrading strain, Apiotrichum loubieri MFZ-16, from kennel soils. Response surface model analysis showed that MFZ-16 degraded TC by 97.93% at 34.54 ℃, pH 5.06%, and 12.93% inoculation. Liquid chromatography-mass spectrometry and principal component analyses revealed significant differences in metabolites between TC-salt media with and without MFZ-16. Furthermore, eight key intermediates of TC degradation were identified and their reaction processes were predicted. Transcriptome analysis revealed that MFZ-16 contained 137 functional genes involved in TC biodegradation. Three TC metabolic pathways, namely, the tyrosine, tryptophan, and D-glucose 1-phosphate metabolic pathways, were predicted, and the tyrosine and tryptophan metabolic pathways were predicted for the first time. These results suggest that A. loubieri strain MFZ-16 is an efficient and promising microbe for TC bioremediation. These findings would give a new insight into the mechanism of TC degradation.

CX43-Mediated Mitochondria Transfer Enhances the Stemness of Leukemia Stem Cells Though Metabolic Remodeling

Background :Despite improvements in treatment options for acute myeloid leukemia (AML), chemotherapy resistance remains an important clinical concern with a high recurrence rate in patients.Leukemia stem cells (LSCs) play a decisive role in the relapse resistance of leukemia. Bone marrow mesenchymal stem cells(BMSCs) protect LSCs from being completely removed from the bone marrow, but the underlying mechanisms are poorly understood.In this study, we aimed to uncover the mechanism of BMSCs-regulated the stemness of leukemia stem cells through mitochondrial transfer mediated by Connexin43(CX43), thus providing a promising clinical therapy target. Methods: Primary BMSCs were isolated from the primary bone marrow specimens of patients with AML and cultured in MSCM culture base within 10% serum.CX43 overexpressing BMSCs (CX43-BMSCS) were constructed by lentivirus transfection.The efficiency of CX43 overexpression was verified by immunofluorescence, qPCR and Western Blot.In vitro, CX43-BMSCs and control BMSCs (EV-BMSCs) were cocultured with KG-1a cells.In some experiments,vincristine (1nM) was added to inhibit the mitochondrial transferring.Bidirectional mitochondrial transfer was detected by flow cytometry and confocal microscopy.The mechanism of mitochondria transfer was analyzed by inhibitor assays.The proliferation of KG-1a from the coculture system were assessed by Flow cytometry and EdU assay.After co-culture, the clone formation of KG-1a was detected by using semisolid cloning assay.The mitochondrial respiration of KG-1a was analyzed by using Seahorse.The transcriptomes of KG-1a after co-culture using RNA-seq.Finally,we verified our findings using LC-MS non-targeted metabolomics to detect the metabolites changes of KG-1a after co-culture. Results: Compared with Control-BMSCs and EV-BMSCs,the mRNA and protein expression levels of CX43 in CX43-MSCs were significantly increased (P&amp;lt;0.05).In the co-culture system without serum for 48h,BMSCs transfer mitochondria to KG-1a cells but receive no mitochondria from KG-1a.Moreover,CX43-BMSCs transferred more mitochondria to KG-1a than EV-BMSCs group (P&amp;lt;0.05),while there was no obvious mitochondrial transfer was observed in the transwell and 10% serum co-culture system.In addition,compared with EV-BMSCs,CX43-BMSCs significantly increased the proliferation and adhesion of KG-1a (P&amp;lt;0.05) and clone formation ability (P&amp;lt;0.05).Vincristine significantly reduced the mitochondrial transfer from CX43-BMSCs to KG-1a,and decreased the adhesion of CX43-BMSCs to KG-1a,as well as the proliferation and clone formation of KG-1a after co-culture.The metabolic capacity of KG-1a cells in CX43-BMSCs was significantly increased compared with EV-BMSCs (P&amp;lt;0.05),and this metabolic enhancement could be reversed by vincristine.Hierarchical cluster analysis (HC) of metabolites showed that there were significant differences in metabolites among treatment groups (p&amp;lt;0.05),showed unique metabolic characteristics related to CX43-induced changes.The GO analysis revealed that the enrichments occurring in KG-1a after co-cultured with CX43-BMSCs mainly included cell adhesion and migration,cell proliferation and regulation,signal transduction,PI3K/Akt pathway,transmembrane transport and intracellular protein metabolism.Metabolism-related pathways,like nucleotide metabolism,lipid metabolism and amino acid metabolism,were enriched in KG-1a after co-cultured with CX43-BMSCs.Furthermore,KG-1a after co-cultured with CX43-BMSCs showed up-regulated of promoting the proliferation and the stemness of AML-LSCs,including N-cadherin (CDH2),CD244,SLC43A2,CYBB and IGLL1. Conclusion: We show evidence that CX43 mediated mitochondria transfer from BMSCs to LSCs which promoting the adhesion of BMSCs to LSCs under nutrient deficiency condition,and then enhanced the proliferation and cloning ability of LSCs,altered gene expression profiles related to cell proliferation,adhesion,and energy metabolism,and increased the expression of genes related to maintaining stemness of LSCs, allows metabolic remodeling to regulate LSCs stemness, may be a potential therapeutic target for AML treatment. Keywords:Leukemia stem cells;Bone marrow microenvironment;Connexin;Mitochondrial transfer;Metabolic remodeling

Untargeted metabolomic profiling of dogs with myxomatous mitral valve disease and congestive heart failure shows metabolic differences associated with the presence of cardiac cachexia.

To determine the effects of cardiac cachexia on the metabolomic profile in dogs with myxomatous mitral valve disease (MMVD). 3 groups of dogs with MMVD enrolled between November 30, 2018, and April 7, 2022: (1) Dogs with congestive heart failure (CHF) and cachexia (CHF-cachexia group; n = 10); (2) dogs with CHF that had no cachexia (CHF-no cachexia group; n = 10); and (3) dogs with asymptomatic disease (American College of Veterinary Internal Medicine [ACVIM] Stage B2) with no cachexia (B2 group; n = 10). Metabolomic profiles were analyzed from serum samples using ultra-high-performance liquid chromatography-tandem mass spectroscopy. Dogs in the 3 groups were compared, with statistical significance defined as P < .05 with a low false discovery rate (q < .10) and nominal statistical significance defined as P < .05 but q > .10. Numerous metabolites were significantly (n = 201) or nominally significantly (n = 345) different between groups. For example, when comparing the CHF-cachexia vs CHF-no cachexia groups, lipids were the predominant metabolite differences, including many medium- and long-chain dicarboxylates and dicarboxylate acylcarnitines. For comparisons of the CHF-cachexia vs B2 groups and the CHF-no cachexia vs B2 groups, amino acids, nucleotides, and cofactors/vitamins were the predominant metabolite differences. Some significant metabolite differences were identified between dogs with and without cardiac cachexia.

Impact of Lactation Stage on the Metabolite Composition of Bovine Milk.

Bovine milk is a nutrient-dense food and a major component of the human diet. Therefore, understanding the factors that impact its composition is of great importance. Applications of metabolomics provide in-depth analysis of the metabolite composition of milk. The objective of this research was to examine the impact of lactation stage on bovine milk metabolite levels. Metabolomic analysis of bovine milk powder samples across lactation (N = 18) was performed using nuclear magnetic resonance (1H-NMR) spectroscopy and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Forty-one metabolites were identified and quantified in the 1H-NMR spectra. Statistical analysis revealed that 17 metabolites were significantly different across lactation stages (FDR < 0.05), of which the majority had higher levels in early lactation. In total, 491 metabolites were measured using LC-MS/MS, of which 269 had significantly different levels across lactation (FDR < 0.05). Compound classes significantly affected by lactation stage included phosphatidylcholines (59%) and triglycerides (64%), of which 100% of phosphatidylcholines and 61% of triglycerides increased from early lactation onwards. Our study demonstrates significant differences in metabolites across the stages of lactation, with early-lactation milk having a distinct metabolomic profile. More research is warranted to further explore these compositional differences to inform animal feeding practice.

Induction and metabolomic analysis of hairy roots of Atractylodes lancea.

Atractylodes lancea is an important source of traditional Chinese medicines. Sesquiterpenoids are the key active compounds in A. lancea, and their presence determines the quality of the material. Hairy hoot (HR) culture is a potential method to produce medicinally active compounds industrially; however, the induction and metabolic profiling of A. lancea HR have not been reported. We found that optimal induction of A. lancea HR was achieved by Agrobacterium rhizogenes strain C58C1 using the young leaves of tissue culture seedlings in the rooting stage as explants. Ultra-performance liquid chromatography-tandem mass spectrometric analyses of the chemical compositions of HR and normal root (NR) led to the annotation of 1046 metabolites. Over 200 differentially accumulated metabolites were identified, with 41 found to be up-regulated in HR relative to NR and 179 down-regulated in HR. Specifically, atractylodin levels were higher in HR, while the levels of β-eudesmol and hinesol were higher in NR. Metabolic pathway analyses showed a significant difference in metabolites of the shikimate acid pathway between HR and NR. Five A. lancea compounds are potential biomarkers for evaluation of HR and NR quality. This study provides an important reference for the application of HR for the production of medicinally active compounds. KEY POINTS: • We established an efficient protocol for the induction of HR in A. lancea • HR was found to have a significantly higher amount of atractylodin than did NRs • Metabolic pathway analyses showed a significant difference in metabolites of the shikimate acid pathway between HR and NR.

Uncovering anti-influenza mechanism of Ophiocordyceps sinensis using network pharmacology, molecular pharmacology, and metabolomics.

Ophiocordyceps sinensis is a precious Chinese traditional herb with a long medicinal history. This study used UPLC-MS metabolomics to explore and compare the metabolic profiles of the stroma (OSBSz), sclerotium (OSBSh), and mycelium (OSBS) of O sinensis to analyze their differential metabolites and identified potential active components. Then combined with network pharmacology and molecular docking to explore the mechanism of differential metabolites with anti-influenza properties. The results indicate that the stroma, sclerotium, and mycelium showed significant differences in metabolites. The key pathways for differential metabolites were butanoate metabolism, thiamin metabolism, alanine, aspartate and glutamate metabolism, citrate cycle, and arginine biosynthesis. Protein-protein interaction analysis identified potential targets, including SRC, RHOA, HSP90AA1, VEGFA, ITGB1, PRKCA, and ITGA1, and the key protective pathways in-volved PI3K-Akt, HIF-1, influenza A, and Coronavirus disease 2019. The molecular docking results showed that the core metabolite D-(-)-glutamine has high binding affinity with SRC, RHOA, and EGFR, re-flecting the multi-component and multi-target network system of O sinensis. In short, the combination of metabonomics, network pharmacology and macromolecular docking technology provides a new way to explore the anti-influenza research of O sinensis. This is undoubtedly an important theoretical support for the clinical application of O sinensis in the future.

Metabolomic and Transcriptomic Analyses Reveal the Effects of Grafting on Nutritional Properties in Eggplant.

Grafting has a significant impact on the botany properties, commercial character, disease resistance, and productivity of eggplants. However, the mechanism of phenotypic modulation on grafted eggplants is rarely reported. In this study, a widely cultivated eggplant (Solanum. melongena cv. 'Zheqie No.10') was selected as the scion and grafted, respectively, onto four rootstocks of TOR (S. torvum), Sa (S. aculeatissimum), SS (S. sisymbriifolium), and Sm64R (S. melongena cv. 'Qiezhen No. 64R') for phenotypic screening. Physiological and biochemical analysis showed the rootstock Sm64R could improve the fruit quality with the increasing of fruit size, yield, and the contents of total soluble solid, phenolic acid, total amino acid, total sugar, and vitamin C. To further investigate the improvement of fruit quality on Sm64R, a transcriptome and a metabolome between the Sm64R-grafted eggplant and self-grafted eggplant were performed. Significant differences in metabolites, such as phenolic acids, lipids, nucleotides and derivatives, alkaloids, terpenoids, and amino acids, were observed. Differential metabolites and differentially expressed genes were found to be abundant in three core pathways of nutritional qualities, including biosynthesis of phenylpropanoids, phospholipids, and nucleotide metabolism. Thus, this study may provide a novel insight into the effects of grafting on the fruit quality in eggplant.

Effects of extended transition milk feeding on blood metabolites of female Holstein dairy calves at 3 weeks of age: a liquid chromatography with tandem mass spectrometry-based metabolomics approach

Transition milk (TRM) is a rich source of bioactive components that promotes intestinal development and growth, and reduces the susceptibility to diarrhoea in calves. The objective of this study was to characterise the effects of replacing pasteurised waste milk (none-saleable milk containing antibiotic and/or drug residues) with pasteurised TRM for 3 wk on blood metabolites of dairy calves at 21 d of age. A total of 84 healthy newborn female Holstein calves was blocked by birth order and assigned randomly to four treatment groups with partial replacement of pasteurised waste milk by TRM (second milking after parturition) at 0 (0 L/day TRM + 6 L/day milk), 0.5 (0.5 L/day TRM + 5.5 L/day milk), 1 (1 L/day TRM + 5 L/day milk), or 2 L (2 L/day TRM + 4 L/day milk) for a 21-day period. Serum metabolome was determined by liquid chromatography with tandem mass spectrometry-based metabolomics analysis on a subset of 26 randomly selected individuals from calves fed pasteurised waste milk (CON, 6 L/d milk; n = 13) or TRM (2 L/d TRM + 4 L/d milk; n = 13) at 21 d of age. The identified metabolites (194 out of 265) were categorised according to chemical class and the number of metabolites per class in the serum, amongst which glycerophospholipids 16% (n = 43), fatty acyls 7% (n = 19), organic acids 7% (n = 18), organic heterocyclic compounds 5% (n = 13), benzenoids 5% (n = 12), sphingolipids 5% (n = 12), organic oxygen compounds 4% (n = 11), and nucleic acids 3% (n = 9), were the predominant types. Significant differences in metabolites were determined by the volcano plot. Applying the volcano plot, only two metabolites (ceramide and phosphatidylserine) were significantly different between CON and TRM. Overall, our results suggested that prolonged TRM feeding for 3 wk had little effect on the serum metabolome of the dairy calves. We speculate that the potential effects of feeding TRM for 3 wk compared with waste milk were spatially limited to affect the composition of the local gut microbial community and the growth or function of the intestinal epithelium, not allowing detection of the likely effects in the serum through a metabolomic approach.

Potential preventive markers in the intracerebral hemorrhage process are revealed by serum untargeted metabolomics in mice using hypertensive cerebral microbleeds.

Hypertensive cerebral microbleeds (HCMB) may be the early stage of hypertensive intracerebral hemorrhage (HICH), which is a serious threat to health due to its high mortality and disability rates. The early clinical symptoms of HCMB may not be significant. Moreover, it is difficult to achieve early diagnosis and intervention for targeted prevention of HICH. Although hypertension (HTN) is a predisposition for HCMB, it remains unclear whether there is any difference between hypertensive patients with or without HCMB. Therefore, we carried out liquid chromatography-mass spectrometry (LC-MS) to analyze early biomarkers for HCMB in mice with hypertension and to lay the foundation for early prevention of HICH in hypertensive patients. In total, 18 C57 male mice were randomly divided into the HCMB (n = 6), HTN (n = 6), and control groups (CON, n = 6). Hematoxylin-eosin and diaminobenzidine staining were used to assess the reliability of the model. The metabolite expression level and sample category stability were tested using the displacement test of orthogonal partial least squares discriminant analysis (OPLS-DA). Significant differences in metabolites were screened out using variable importance in the projection (VIP > 1), which were determined using the OPLS-DA model and the P-value of the t-test (P < 0.05) combined with the nonparametric rank-sum test. With an area under the curve (AUC) > 0.85 and a P-value of 0.05, the receiver operating characteristic curve (ROC) was used to further screen the distinct metabolites of HCMB. Compared with the HTN and CON groups, the HCMB group had significantly higher blood pressure and lower average body weight (P < 0.05). Through untargeted LC-MS analysis, 93 distinct metabolites were identified in the HCMB (P < 0.05, VIP > 1) group. Among these potential biomarkers, six significantly decreased and eight significantly increased differential metabolites were found. Meanwhile, we found that the HCMB group had statistically distinct arginine and purine metabolism pathways (P < 0.05), and citrulline may be the most significant possible biomarker of HCMB (AUC > 0.85, P < 0.05). All of these potential biomarkers may serve as early biomarkers for HICH in hypertension.

Metabolomic profiles in relapsing-remitting and progressive multiple sclerosis compared to healthy controls: a five-year follow-up study.

Multiple sclerosis (MS) is a disease of the central nervous system associated with immune dysfunction, demyelination, and neurodegeneration. The disease has heterogeneous clinical phenotypes such as relapsing-remitting MS (RRMS) and progressive multiple sclerosis (PMS), each with unique pathogenesis. Metabolomics research has shown promise in understanding the etiologies of MS disease. However, there is a paucity of clinical studies with follow-up metabolomics analyses. This 5-year follow-up (5YFU) cohort study aimed to investigate the metabolomics alterations over time between different courses of MS patients and healthy controls and provide insights into metabolic and physiological mechanisms of MS disease progression. A cohort containing 108 MS patients (37 PMS and 71 RRMS) and 42 controls were followed up for a median of 5years. Liquid chromatography-mass spectrometry (LC-MS) was applied for untargeted metabolomics profiling of serum samples of the cohort at both baseline and 5YFU. Univariate analyses with mixed-effect ANCOVA models, clustering, and pathway enrichment analyses were performed to identify patterns of metabolites and pathway changes across the time effects and patient groups. Out of 592 identified metabolites, the PMS group exhibited the most changes, with 219 (37%) metabolites changed over time and 132 (22%) changed within the RRMS group (Bonferroni adjusted P < 0.05). Compared to the baseline, there were more significant metabolite differences detected between PMS and RRMS classes at 5YFU. Pathway enrichment analysis detected seven pathways perturbed significantly during 5YFU in MS groups compared to controls. PMS showed more pathway changes compared to the RRMS group.

Targeted metabolomics analysis for serum Helicobacter pylori -positive based on LC-MS/MS.

Helicobacter pylori (H. pylori), as a harmful bacteria associated with gastric cancer, can have adverse effects on human normal flora and metabolism. However, the effects of H. pylori on human metabolism have not been fully elucidated. 13 C breathing test was used as the basis for distinguishing negative and positive groups. Serum samples were collected from the two groups for targeted quantitative metabolomics detection, and multidimensional statistics were used, including partial least squares discriminant analysis (PLS-DA), principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA), and differential metabolites were screened. Unidimensional statistics combined with multidimensional statistics were used to further screen potential biomarkers, and finally pathway analysis was performed. SPSS 21.0 software package was used for statistical analysis of experimental data. Multivariate statistical analysis such as PLS-DA, PCA and OPLS-DA was performed using Simca-P 13.0 to search for differential metabolites. This study confirmed that Helicobacter pylori caused significant changes in human metabolism. In this experiment, 211 metabolites were detected in the serum of the two groups. Multivariate statistical analysis showed that PCA of metabolites was not significantly different between the two groups. PLS-DA indicated that the serum of the two groups were well clustered. There were significant differences in metabolites between OPLS-DA groups. By setting the VIP threshold as 1 and the corresponding P value < 0.05, a total of 40 metabolites were screened in this study. P < 0.05 and| log2FC | > 0 (FC, the Fold Change) together as a unidimensional statistical filter condition. The analysis found that the expression of 15 metabolites such as Propionic acid, Acetic acid, Adipic acid increased, and the metabolism of 6 products such as DCA, 4-Hydroxyphenylpyruvic acid, Pyruvic acid decreased. P < 0.05, FDR < 0.5,|log2FC|> 1 and OPLSDA_VIP > 1 together as a condition of filter screen potential biomarkers. Four potential biomarkers were screened, which were Sebacic acid, Isovaleric acid, (DCA, Indole-3-carboxylic acid). Finally, the different metabolites were brought into the SMPDB library for the corresponding pathway enrichment analysis. The significant abnormal metabolic pathways were taurine and subtaurine metabolism, tyrosine metabolism, glycolysis or gluconeogenesis, pyruvate metabolism, etc. CONCLUSIONS: This study shows that H. pylori has an impact on human metabolism. Not only a variety of metabolites have significant changes, but also metabolic pathways are abnormal, which may be the reason for the high risk of H. pylori causing gastric cancer.

Rhizosphere Microbial Community and Metabolites of Susceptible and Resistant Tobacco Cultivars to Bacterial Wilt

Soil-borne diseases are closely related to rhizosphere microecosystem. While, plant species and genotypes are important factors affected rhizosphere microecosystem. In this study, the rhizosphere soil microbial community and metabolites of susceptible and resistant tobacco cultivars were investigated. The results showed that there were significant differences in the rhizosphere microbial community and metabolites between susceptible cultivar Yunyan87 and resistant cultivar Fandi3. Furthermore, the rhizosphere soil of Fandi3 showed a higher microbial diversity than that of Yunyan87. The abundance of R. solanacearum was much higher in the rhizosphere soil of Yunyan87 than in the rhizosphere soil of Fandi3, resulting in a higher disease incidence and index. While the abundance of beneficial bacteria in the rhizosphere soil of Fandi3 were higher than that of Yunyan87. Additionally, there were significant differences in metabolites between Yunyan87 and Fandi3 cultivars, and 4-hydroxybenzaldehyde, 3-hydroxy-4-methoxybenzoic acid, vamillic aldehyde, benzoic acid, 4-hydroxybenzyl alcohol, p-hydroxybenzoic acid and phthalic acid were notably high in Yunyan87. Redundancy analysis (RDA) indicated that the rhizosphere microbial community of Fandi3 and Yunyan87 were highly correlated with various environmental factors and metabolites. Overall, susceptible and resistant tobacco cultivars had different impact on rhizosphere microbial community and metabolites. The results expand our understanding of the roles of tobacco cultivars in plant-micro-ecosystem interactions, and provide a basis for the control of tobacco bacterial wilt.

Metabolomic profiling of overnight peritoneal dialysis effluents predicts the peritoneal equilibration test type

This study primarily aimed to evaluate whether peritoneal equilibration test (PET) results can be predicted through the metabolomic analysis of overnight peritoneal dialysis (PD) effluents. From a total of 125 patients, overnight PD effluents on the day of the first PET after PD initiation were analyzed. A modified 4.25% dextrose PET was performed, and the PET type was categorized according to the dialysate-to-plasma creatinine ratio at the 4-h dwell time during the PET as follows: high, high average, low average, or low transporter. Nuclear magnetic resonance (NMR)-based metabolomics was used to analyze the effluents and identify the metabolites. The predictive performances derived from the orthogonal projection to latent structure discriminant analysis (OPLS-DA) modeling of the NMR spectrum were estimated by calculating the area under the curve (AUC) using receiver operating characteristic curve analysis. The OPLS-DA score plot indicated significant metabolite differences between high and low PET types. The relative concentrations of alanine and creatinine were greater in the high transporter type than in the low transporter type. The relative concentrations of glucose and lactate were greater in the low transporter type than in the high transporter type. The AUC of a composite of four metabolites was 0.975 in distinguish between high and low PET types. Measured PET results correlated well with the total NMR metabolic profile of overnight PD effluents.

Brain metabolites measured with magnetic resonance spectroscopy in pediatric concussion and orthopedic injury: An Advancing Concussion Assessment in Pediatrics (A-CAP)study.

Millions of children sustain a concussion annually. Concussion disrupts cellular signaling and neural pathways within the brain but the resulting metabolic disruptions are not well characterized. Magnetic resonance spectroscopy (MRS) can examine key brain metabolites (e.g., N-acetyl Aspartate (tNAA), glutamate (Glx), creatine (tCr), choline (tCho), and myo-Inositol (mI)) to better understand these disruptions. In this study, we used MRS to examine differences in brain metabolites between children and adolescents with concussion versus orthopedic injury. Children and adolescents with concussion (n=361) or orthopedic injury (OI) (n=184) aged 8 to 17 years were recruited from five emergency departments across Canada. MRS data were collected from the left dorsolateral prefrontal cortex (L-DLPFC) using point resolved spectroscopy (PRESS) at 3T at a mean of 12 days post-injury (median 10 days post-injury, range 2-33 days). Univariate analyses for each metabolite found no statistically significant metabolite differences between groups. Within each analysis, several covariates were statistically significant. Follow-up analyses designed to account for possible confounding factors including age, site, scanner,vendor, time since injury, and tissue type (and interactions as appropriate) did not find any metabolite group differences. In the largest sample of pediatric concussion studied with MRS to date, we found no metabolite differences between concussion and OI groups in the L-DLPFC. We suggest that at 2 weeks post-injury in a general pediatric concussion population, brain metabolites in the L-DLPFC are not specifically affected by brain injury.