Non-targeted Metabolomic Profiling Research Articles

Secreted metabolome of porcine blastocysts encapsulated within in vitro 3D alginate hydrogel culture systems undergoing morphological changes provides insights into specific mechanisms involved in the initiation of porcine conceptus elongation.

The exact mechanisms regulating the initiation of porcine conceptus elongation are not known due to the complexity of the uterine environment. To identify contributing factors for initiation of conceptus elongation in vitro , this study evaluated differential metabolite abundance within media following culture of blastocysts within unmodified alginate (ALG) or Arg-Gly-Asp (RGD)-modified alginate hydrogel culture systems. Blastocysts were harvested from pregnant gilts, encapsulated within ALG or RGD or as non-encapsulated control blastocysts (CONT), and cultured. At the termination of 96h culture, media were separated into blastocyst media groups: non-encapsulated control blastocysts (CONT); ALG and RGD blastocysts with no morphological change (ALG- and RGD-); ALG and RGD blastocysts with morphological changes (ALG+ and RGD+) and evaluated for non-targeted metabolomic profiling by liquid chromatography (LC)-mass spectrometry (MS) techniques and gas chromatography-(GC-MS). Analysis of variance identified 280 (LC-MS) and 1 (GC-MS) compounds that differed (P <0.05), of which 134 (LC-MS) and 1 (GC-MS) were annotated. Metabolites abundance between ALG+ vs ALG-, RGD+ vs RGD-, and RGD+ vs ALG+ were further investigated to identify potential differences in metabolic processes during the initiation of elongation. This study identified changes in phospholipid, glycosphingolipid, lipid signalling, and amino acid metabolic processes as potential RGD-independent mechanisms of elongation and identified changes in lysophosphatidylcholine and sphingolipid secretions during RGD-mediated elongation. These results illustrate changes in phospholipid and sphingolipid metabolic processes and secretions may act as mediators of the RGD-integrin adhesion that promotes porcine conceptus elongation.

METABOLOMIC PROFILES FOR THE EXPLORATION OF BIOMARKERS IN SEVERE SARCOPENIA AMONG OLDER MEN

Abstract The pathophysiology of sarcopenia is complex and multifactorial; however, it has not been fully elucidated. This preliminary study explored novel biomarkers of severe sarcopenia through a metabolomic analysis of plasma metabolites in community-dwelling older men. Twenty older men (mean age: 81.9±2.8 years) were randomly selected from the Korean Frailty and Aging Cohort Study. Participants with severe sarcopenia were compared to healthy, age-, and body mass index-matched controls (n = 10 each). Severe sarcopenia was diagnosed using the Asian Working Group for Sarcopenia 2019 criteria. Non-targeted metabolomic profiling of plasma metabolites was performed using capillary electrophoresis time-of-flight mass spectrometry. Among the 191 plasma metabolic peaks, 10 metabolites differed significantly between healthy controls and participants with severe sarcopenia. The plasma concentrations of l-alanine, homocitrulline, n-acetylserine, gluconic acid, n-acetylalanine, proline, and sulfotyrosine were higher, while the concentrations of 4-methyl-2-oxovaleric acid, 3-methyl-2-oxovaleric acid, and tryptophan were lower in participants with severe sarcopenia than in healthy controls (all, p &amp;lt; 0.05). Of the 57 metabolites quantified in target metabolites, L-alanine (area under the receiver operating characteristic curve [AUC] = 0.760, p = 0.049), gluconic acid (AUC = 0.800, p = 0.023), proline (AUC = 0.785, p = 0.031), and tryptophan (AUC = 0.800, p = 0.023) predicted the presence of severe sarcopenia. In conclusion, plasma metabolomic analysis demonstrated significant changes in amino acid, arginine, proline, and pentose phosphate metabolism in participants with severe sarcopenia. The identified metabolites could be helpful in understanding the underlying pathophysiology of sarcopenia.

Association between abnormal plasma metabolism and brain atrophy in alcohol-dependent patients.

In this study, we aimed to characterize the plasma metabolic profiles of brain atrophy and alcohol dependence (s) and to identify the underlying pathogenesis of brain atrophy related to alcohol dependence. We acquired the plasma samples of alcohol-dependent patients and performed non-targeted metabolomic profiling analysis to identify alterations of key metabolites in the plasma of BA-ADPs. Machine learning algorithms and bioinformatic analysis were also used to identify predictive biomarkers and investigate their possible roles in brain atrophy related to alcohol dependence. A total of 26 plasma metabolites were significantly altered in the BA-ADPs group when compared with a group featuring alcohol-dependent patients without brain atrophy (NBA-ADPs). Nine of these differential metabolites were further identified as potential biomarkers for BA-ADPs. Receiver operating characteristic curves demonstrated that these potential biomarkers exhibited good sensitivity and specificity for distinguishing BA-ADPs from NBA-ADPs. Moreover, metabolic pathway analysis suggested that glycerophospholipid metabolism may be highly involved in the pathogenesis of alcohol-induced brain atrophy. This plasma metabolomic study provides a valuable resource for enhancing our understanding of alcohol-induced brain atrophy and offers potential targets for therapeutic intervention.

Abstract 15168: Plasma Metabolomic Profiling Identifies Markers of Cardiorespiratory Fitness Responsive to Endurance Exercise Training

Background: High-throughput metabolite profiling allows for the assessment of thousands of metabolites that may participate in exercise-related pathways. Here, we characterize plasma metabolite changes in healthy individuals undergoing endurance exercise training (ET) to identify biochemical features of VO 2 max and/or those responsive to ET. Methods: We measured 444 known metabolites and 3221 non-targeted metabolite peaks using liquid chromatography tandem mass spectrometry and VO 2 max using CPET before and after 20 weeks of supervised, endurance ET in 654 sedentary participants (mean age=34y; 39% self-identified Black) from the HERITAGE Study. Multivariate linear regression assessed the relation between metabolites and baseline VO 2 max (ml·kg –1 ·min –1 ), adjusting for age, sex, and race. Changes after ET were determined using paired t tests. We used a false discovery rate (q) &lt; 0.05 to determine statistical significance. Results: 494 metabolites were associated with VO 2 max, the majority (375/494) of which were non-targeted (unknown) metabolites with greater effect sizes than targeted peaks [β range: -29.66 - 17.80 and -22.76 - 12.87 for unknown and known metabolites]. We recapitulated known metabolite associations with VO 2 max including DMGV, branched chain amino acids, and uric acid ( Figure 1 ). 110 of 560 metabolites that changed after ET were associated with VO 2 max, including non-targeted peaks that concordantly changed after ET (e.g. metabolite peaks positively associated with VO 2 max that increased with ET; m/z 385.3056 and 695.5086; β for VO 2 max = 9.82 and -19.33, q= 5.56e-7 and 2.61e-17, and log fold-change = 0.03 and -0.01, q=9.58e-13 and 1.93e-4, respectively). Conclusions: We identified novel metabolite peaks associated with VO 2 max that concordantly changed after ET. Non-targeted metabolomic profiling reveals new markers related to VO 2 max and exercise response, motivating ongoing work to unambiguously identify these compounds.

Comprehensive review of composition distribution and advances in profiling of phenolic compounds in oilseeds.

A wide range of phenolic compounds participate in oilseed growth, regulate oxidative stability of corresponding vegetable oil, and serve as important minor food components with health-promoting effects. Composition distribution of phenolic compounds varied in oilseeds. Isoflavones, sinapic acid derivatives, catechin and epicatechin, phenolic alcohols, chlorogenic acid, and lignans were the main phenolic compounds in soybean, rapeseed, peanut skin, olive, sunflower seed, sesame and flaxseed, respectively. Among which, the total isoflavones content in soybean seeds reached from 1,431 to 2,130 mg/100 g; the main phenolic compound in rapeseed was sinapine, representing 70-90%; chlorogenic acid as the predominant phenolic compound in sunflower kernels, represented around 77% of the total phenolic content. With the rapid development of analytical techniques, it is becoming possible for the comprehensive profiling of these phenolic compounds from oilseeds. This review aims to provide recently developments about the composition distribution of phenolic compounds in common oilseeds, advanced technologies for profiling of phenolic compounds by the metabolomics approaches based on mass spectrometry. As there is still limited research focused on the comprehensive extraction and determination of phenolics with different bound-forms, future efforts should take into account the non-targeted, pseudo-targeted, and spatial metabolomic profiling of phenolic compounds, and the construction of phenolic compound database for identifying and quantifying new types of phenolic compounds in oilseeds and their derived products.

Metabolomic profiles to explore biomarkers of severe sarcopenia in older men: A pilot study.

The pathophysiology of sarcopenia is complex and multifactorial; however, it has not yet been fully elucidated. Identifying metabolomic profiles may help clarify the mechanisms underlying sarcopenia. This pilot study explored potential noninvasive biomarkers of severe sarcopenia through metabolomic analysis in community-dwelling older men. Twenty older men (mean age: 81.9±2.8years) were selected from the Korean Frailty and Aging Cohort Study. Participants with severe sarcopenia (n=10) were compared with non-sarcopenic, age- and body mass index-matched controls (n=10). Severe sarcopenia was defined as low muscle mass, low muscle strength, and low physical performance using the Asian Working Group for Sarcopenia 2019 criteria. Non-targeted metabolomic profiling of plasma metabolites was performed using capillary electrophoresis time-of-flight mass spectrometry and absolute quantification was performed in target metabolites. Among 191 plasma metabolic peaks, the concentrations of 10 metabolites significantly differed between severe sarcopenia group and non-sarcopenic controls. The plasma concentrations of L-alanine, homocitrulline, N-acetylserine, gluconic acid, N-acetylalanine, proline, and sulfotyrosine were higher, while those of 4-methyl-2-oxovaleric acid, 3-methyl-2-oxovaleric acid, and tryptophan were lower in participants with severe sarcopenia than in non-sarcopenic controls (all, p<0.05). Among the 53 metabolites quantified as target metabolites, L-alanine (area under the receiver operating characteristic curve [AUC]=0.760; p=0.049), gluconic acid (AUC=0.800; p=0.023), proline (AUC=0.785; p=0.031), and tryptophan (AUC=0.800; p=0.023) determined the presence of severe sarcopenia. Plasma metabolomic analysis demonstrated that L-alanine, gluconic acid, proline, and tryptophan may be potential biomarkers of severe sarcopenia. The identified metabolites can provide new insights into the underlying pathophysiology of severe sarcopenia and serve as the basis for preventive interventions.

Untargeted ultra-high-resolution mass spectrometry metabolomic profiling of blood serum in bladder cancer

Bladder cancer (BC) is a common urological cancer of high mortality and recurrence rates. Currently, cystoscopy is performed as standard examination for the diagnosis and subsequent monitoring for recurrence of the patients. Frequent expensive and invasive procedures may deterrent patients from regular follow-up screening, therefore it is important to look for new non-invasive methods to aid in the detection of recurrent and/or primary BC. In this study, ultra-high-performance liquid chromatography coupled with ultra-high-resolution mass spectrometry was employed for non-targeted metabolomic profiling of 200 human serum samples to identify biochemical signatures that differentiate BC from non-cancer controls (NCs). Univariate and multivariate statistical analyses with external validation revealed twenty-seven metabolites that differentiate between BC patients from NCs. Abundances of these metabolites displayed statistically significant differences in two independent training and validation sets. Twenty-three serum metabolites were also found to be distinguishing between low- and high-grade of BC patients and controls. Thirty-seven serum metabolites were found to differentiate between different stages of BC. The results suggest that measurement of serum metabolites may provide more facile and less invasive diagnostic methodology for detection of bladder cancer and recurrent disease management.

The Effect of Dietary Carbohydrate and Fat Manipulation on the Metabolome and Markers of Glucose and Insulin Metabolism: A Randomised Parallel Trial.

High carbohydrate, lower fat (HCLF) diets are recommended to reduce cardiometabolic disease (CMD) but low carbohydrate high fat (LCHF) diets can be just as effective. The effect of LCHF on novel insulin resistance biomarkers and the metabolome has not been fully explored. The aim of this study was to investigate the impact of an ad libitum 8-week LCHF diet compared with a HCLF diet on CMD markers, the metabolome, and insulin resistance markers. n = 16 adults were randomly assigned to either LCHF (n = 8, <50 g CHO p/day) or HCLF diet (n = 8) for 8 weeks. At weeks 0, 4 and 8, participants provided fasted blood samples, measures of body composition, blood pressure and dietary intake. Samples were analysed for markers of cardiometabolic disease and underwent non-targeted metabolomic profiling. Both a LCHF and HCLF diet significantly (p < 0.01) improved fasting insulin, HOMA IR, rQUICKI and leptin/adiponectin ratio (p < 0.05) levels. Metabolomic profiling detected 3489 metabolites with 78 metabolites being differentially regulated, for example, an upregulation in lipid metabolites following the LCHF diet may indicate an increase in lipid transport and oxidation, improving insulin sensitivity. In conclusion, both diets may reduce type 2 diabetes risk albeit, a LCHF diet may enhance insulin sensitivity by increasing lipid oxidation.

Metagenomic shotgun sequencing and metabolomic profiling identify specific human gut microbiota associated with diabetic retinopathy in patients with type 2 diabetes.

Diabetic retinopathy (DR) is a common microvascular complication of diabetes mellitus (DM) and is one of the leading causes of blindness among DM patients. However, the molecular mechanism involving DR remains unclear. A case-control study with age-, sex-, and duration-matched diabetic patients and controls was conducted, which included 15 type 2 DM (T2DM) patients with DR and 15 T2DM patients without DR. Shotgun sequencing and non-targeted metabolomic profiling analyses of fecal samples were performed, and comprehensive bioinformatics analyses were conducted. Using metagenomic analyses, we identified 293,460 unique genes in the non-DR group, while that in the DR group was 283,235, and the number of overlapping genes was 1,237,914. Regarding phylum levels, Actinobacteria decreased but Bacteroidetes increased in the DR group when compared with those in the control group. Regarding genus levels, Bifidobacterium and Lactobacillus decreased. Cellular processes, environmental information processes, and metabolism-related pathways were found at higher levels in the gut microbiome of DR patients. Using metabolomic analyses, we found 116 differentially expressed metabolites with a positive ion model and 168 differentially expressed metabolites with a negative ion model between the two groups. Kyoto Encyclopedia of Genes and Genomes annotation revealed six pathways with different levels between DR and diabetic controls, namely, cellular processes, environmental information processing, genetic information processing, human diseases, organismal systems and metabolism. Moreover, lysine biosynthesis and lysine degradation were enriched using a positive model, but histidine metabolism and β-alanine metabolism were enriched using a negative model. Together, the metagenomic profiles of DR patients indicated different gut microbiota compositions and characteristic fecal metabolic phenotypes in DR patients. Our findings of microbial pathways therefore provided potential etiological and therapeutic targets for DR patients.

High-Throughput Sequencing Combined with Metabonomics to Analyze the Effect of Heavy Metal Contamination on Farmland Soil Microbial Community and Function

Heavy metal contamination affects microbial composition and diversity. The interaction between heavy metal contamination and soil microorganisms has been a hot topic in ecological research. Battery manufacturing has been going on for over six decades in Xinxiang City, resulting in severe soil heavy metal contamination due to battery wastewater runoff. Few studies have investigated the effect of heavy metal contamination due to long-term battery wastewater runoff on microbial diversity and metabolomics in Xinxiang City. In this study, we collected samples from three heavy metal contaminated sites in Xinxiang City and found that Cd and Pb exceeded the recommended thresholds by 34-66 fold and 1.5-2.32 fold, respectively. High-throughput sequencing showed that Bacillus, Arthrobacter, Sphingomonas, and Streptomyces were the dominant bacteria genera, while Olpidium, Plectosphaerella, and Gibellulopsis were the dominant fungi genera, indicating that heavy metal contaminated soil in Xinxiang City was rich in heavy metal tolerant bacteria and fungi due to the long-term heavy metal stress. Correlation analysis showed that total Cu, DTPA extract Cu, and water soluble Pb were significant factors in bacterial diversity, while total Cd, total Ni, total Pb, total Zn, DTPA extract Cu, and water soluble Pb were significant factors in fungal diversity. To better understand the effect of heavy metal contamination on the metabolism of soil microorganisms, we conducted non-targeted metabolomic profiling, which showed significant differences in metabolites across the samples. Pathway enrichment analysis showed that these differential metabolites were involved in pathways such as metabolism, environmental information processing, and genetic Information Processing, which may play a role in heavy metal stress mitigation and environmental adaptation.

Metabolomics insights into the interaction between Pseudomonas plecoglossicida and Epinephelus coioides

As a highly infectious epidemic in aquaculture, Pseudomonas plecoglossicida infection results in high mortality of teleosts and serious economic losses. Host–pathogen interactions shape the outcome of an infection, yet we still understand little about the molecular mechanism of these pathogen-mediated processes. Here, a P. plecoglossicida strain (NZBD9) and Epinephelus coioides were investigated as a model system to characterize pathogen-induced host metabolic remodeling over the course of infection. We present a non-targeted metabolomics profiling of E. coioides spleens from uninfected E. coioides and those infected with wild-type and clpV-RNA interference (RNAi) strains. The most significant changes of E. coioides upon infection were associated with amino acids, lysophospatidylcholines, and unsaturated fatty acids, involving disturbances in host nutritional utilization and immune responses. Dihydrosphingosine and fatty acid 16:2 were screened as potential biomarkers for assessing P. plecoglossicida infection. The silencing of the P. plecoglossicida clpV gene significantly recovered the lipid metabolism of infected E. coioides. This comprehensive metabolomics study provides novel insights into how P. plecoglossicida shape host metabolism to support their survival and replication and highlights the potential of the virulence gene clpV in the treatment of P. plecoglossicida infection in aquaculture.

Serum liquid metabolites reveals the heterogeneity in advanced lung adenocarcinoma patients with EGFR sensitizing mutations.

e21065 Background: There is a differential therapeutic efficacy of advanced lung adenocarcinoma (LUAD) patients with EGFR sensitizing mutations (mEGFR). This study aimed to explore the differences in serum liquid metabolites of EGFR mutation types and to provide further evidence for revealing the mechanism of the difference in efficacy. Methods: In total, 42 LUAD patients with mEGFR (19 deletions or 21 L858R mutations) who received EGFR-TKIs therapy were included. Prospectively collected serum samples before initial treatment were utilized to perform nontargeted liquid metabolomics profiling analyses under the application of Ultrahigh Performance Liquid Chromatography-Mass Spectrometry/Mass Spectrometry (UPLC-MS/MS). Multi-dimensional statistical methods such as partial least squares discrimination analysis (PLS-DA) were used to further screen and identify differential metabolites associated with EGFR mutation type. Results: The metabolic signature molecules in the metabolic profile were extracted, and a total of 1995 positive ion mode (ESI+) and 365 negative ion mode (ESI-) signature molecules were obtained. 29 metabolites displayed significant differences between the two groups, which belong to lipids including phosphatidylcholines (PCs), phosphatidylglycerol (PGs), phosphatidylethanolamine (PEs), ceramides (Cers) and sphingomyelins (SMs). Gene mutation subtypes change the proportion of saturated phospholipids and unsaturated phospholipids, with significantly higher saturated phospholipids in patients with the EGFR 21 L858R mutation. Then, pathway enrichment analysis was performed on the differential metabolites, mainly enriched in glycerophospholipid and sphingolipids metabolism pathway. Conclusions: This study not only demonstrates the heterogeneity of lipid metabolism among gene mutation subtypes, but also provides the possibility to reveal the mechanism of survival differences.

Metabolomic response to collegiate football participation: Pre- and Post-season analysis

Contact sports participation has been shown to have both beneficial and detrimental effects on health, however little is known about the metabolic sequelae of these effects. We aimed to identify metabolite alterations across a collegiate American football season. Serum was collected from 23 male collegiate football athletes before the athletic season (Pre) and after the last game (Post). Samples underwent nontargeted metabolomic profiling and 1131 metabolites were included for univariate, pathway enrichment, and multivariate analyses. Significant metabolites were assessed against head acceleration events (HAEs). 200 metabolites changed from Pre to Post (P < 0.05 and Q < 0.05); 160 had known identity and mapped to one of 57 pre-defined biological pathways. There was significant enrichment of metabolites belonging to five pathways (P < 0.05): xanthine, fatty acid (acyl choline), medium chain fatty acid, primary bile acid, and glycolysis, gluconeogenesis, and pyruvate metabolism. A set of 12 metabolites was sufficient to discriminate Pre from Post status, and changes in 64 of the 200 metabolites were also associated with HAEs (P < 0.05). In summary, the identified metabolites, and candidate pathways, argue there are metabolic consequences of both physical training and head impacts with football participation. These findings additionally identify a potential set of objective biomarkers of repetitive head injury.

Non-targeted Metabolomics Profiling of Plasma Samples From Patients With Major Depressive Disorder.

BackgroundMajor depressive disorder (MDD) is a neuropsychiatric disorder caused by multiple factors. Although there are clear guidelines for the diagnosis of MDD, the direct and objective diagnostic methods remain inadequate thus far.MethodsThis study aims to discover peripheral biomarkers in patients with MDD and promote the diagnosis of MDD. Plasma samples of healthy controls (HCs, n = 52) and patients with MDD (n = 38) were collected, and then, metabolism analysis was performed using ultrahigh-performance liquid chromatography–tandem mass spectrometry (LC–MS/MS). Heatmap analysis was performed to identify the different metabolites. Meanwhile, receiver operating characteristic (ROC) curves of these differential metabolites were generated.ResultsSix differential metabolites were found by LC–MS/MS analysis. Three of these were increased, including L-aspartic acid (Asp), diethanolamine, and alanine. Three were decreased, including O-acetyl-L-carnitine (LAC), cystine, and fumarate. In addition, LAC, Asp, fumarate, and alanine showed large areas under the curve (AUCs) by ROC analysis.ConclusionThe study explored differences in peripheral blood between depressed patients and HCs. These results indicated that differential metabolites with large AUCs may have the potential to be promising biomarkers for the diagnosis of MDD.

The Gut Microbiome and Metabolites Are Altered and Interrelated in Patients With Rheumatoid Arthritis.

The relationship among the gut microbiome, global fecal metabolites and rheumatoid arthritis (RA) has not been systematically evaluated. In this study, we performed 16S rDNA sequencing and liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based nontargeted metabolomic profiling on feces of 26 untreated RA patients and 26 healthy controls. Twenty-six genera and forty-one MS2-identified metabolites were significantly altered in the RA patients. Klebsiella, Escherichia, Eisenbergiella and Flavobacterium were more abundant in the RA patients, while Fusicatenibacter, Megamonas and Enterococcus were more abundant in the healthy controls. Function prediction analysis demonstrated that the biosynthesis pathways of amino acids, such as L-arginine and aromatic amino acids, were depleted in the RA group. In the metabolome results, fecal metabolites including glycerophospholipids (PC(18:3(9Z,12Z,15Z)/16:1(9Z)), lysoPE 19:1, lysoPE 18:0, lysoPC(18:0/0:0)), sphingolipids (Cer(d18:0/16:0), Cer(d18:0/12:0), Cer(d18:0/14:0)), kynurenic acid, xanthurenic acid and 3-hydroxyanthranilic acid were remarkably altered between the RA patients and healthy controls. Dysregulation of pathways, such as tryptophan metabolism, alpha-linolenic acid metabolism and glycerophospholipid metabolism, may contribute to the development of RA. Additionally, we revealed that the gut microbiome and metabolites were interrelated in the RA patients, while Escherichia was the core genus. By depicting the overall landscape of the intestinal microbiome and metabolome in RA patients, our study could provide possible novel research directions regarding RA pathogenesis and targeted therapy.

A holistic comparison of flavor signature and chemical profile in different harvesting periods of Chrysanthemum morifolium Ramat. based on metabolomics combined with bioinformatics and molecular docking strategy.

Taiju and Duoju are products of Hangbaiju (HJ) obtained during different collection periods, and they have been commonly used as ingredients in tea beverages and dietary traditional Chinese medicine. This study reports an integrated strategy based on metabolomics, bioinformatics and molecular docking to further explore the effect of the harvesting period on the metabolic profile and clinical efficacy of HJ. Firstly, gas chromatography-mass spectrometry (GC-MS) and ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS) were employed for non-targeted metabolomics profiling of essential oils and flavonoids. A sequential window acquisition of all theoretical fragment-ion spectra information-dependent acquisition (SWATH-IDA) bi-directionally verified (SIBDV) method was developed that integrates the advantages of both SWATH and IDA in characterizing flavonoids. Chemometric methods were then used to screen potential chemical markers. Furthermore, HJ is effective in hepatoprotective functions. Therefore, hepatocellular-carcinoma-related differentially expressed genes were obtained using bioinformatics, and the corresponding proteins were molecularly docked with diagnostic chemical markers. In total, 78 volatile oils and 63 flavonoids were tentatively identified. The results allowed the selection of 11 metabolites (5 volatile oils and 6 flavonoids), which are nominated as novel markers for material authentication of Taiju and Duoju. Additionally, two proteins associated with hepatoma were screened using bioinformatics. All six flavonoid markers with binding energies of <-5 kcal mol-1 were considered to be anti-hepatoma biomarkers. Noticeably, in Taiju, the content of hydroxygenkwanin showed a downward trend, but the content of the other five flavonoids and the five flavored volatile difference compounds had an upward trend. This bestows a unique flavor profile on Taiju, leading to differences in sensory aroma and clinical efficacy in Taiju and Duoju. In conclusion, the transformation of secondary metabolites was the dominant trend during HJ growth. These findings lay the foundation for food development and distinguishing clinical applications.

TCA-phospholipid-glycolysis targeted triple therapy effectively suppresses ATP production and tumor growth in glioblastoma.

Rationale: Glioblastoma (GBM) displays a complex metabolic reprogramming in cancer cells. Adenosine triphosphate (ATP) is one of the central mediators of cell metabolism and signaling. GBM cells generate ATP by glycolysis and the tricarboxylic acid (TCA) cycle associated with oxidative phosphorylation (OXPHOS) through the breaking-down of pyruvate or fatty acids to meet the growing energy demand of cancer cells. Therefore, it's urgent to develop novel treatments targeting energy metabolism to hinder tumor cell proliferation in GBM.Methods: Non-targeted metabolomic profiling analysis was utilized to evaluate cell metabolic reprogramming using a small molecule inhibitor (SMI) EPIC-0412 treatment. Cellular oxygen consumption rate (OCR) and the total proton efflux rate (PER), as well as ATP concentration, were tracked to study metabolic responses to specifically targeted inhibitors, including EPIC-0412, arachidonyl trifluoromethyl ketone (AACOCF3), and 2 deoxy-D-glucose (2-DG). Cancer cell proliferation was assessed by CCK-8 measurements and colony formation assay. Additionally, flow cytometry, immunoblotting (IB), and immunofluorescence (IF) analyses were performed with GBM cells to understand their tumorigenic properties under treatments. Finally, the anticancer effects of this combination therapy were evaluated in the GBM mouse model by convection-enhanced delivery (CED).Results: We found that SMI EPIC-0412 could effectively perturb the TCA cycle, which participated in the combination therapy of cytosolic phospholipase A2 (cPLA2)-inhibitor AACOCF3, and hexokinase II (HK2)-inhibitor 2-DG to disrupt the GBM energy metabolism for targeted metabolic treatments. ATP production was significantly declined in glioma cells when treated with monotherapy (EPIC-0412 or AACOCF3), dual therapy (EPIC-0412 + AACOCF3), or triple therapy (EPIC-0412 + AACOCF3 +2-DG) regimen. Our experiments revealed that these therapies hindered glioma cell proliferation and growth, leading to the reduction in ATP production and G0/G1 cell cycle arrest. We demonstrated that the combination therapy effectively extended the survival of cerebral tumor-bearing mice.Conclusion: Our findings indicate that the TCA-phospholipid-glycolysis metabolism axis can be blocked by specific inhibitors that significantly disrupt the tumor energy metabolism and suppress tumor proliferation in vitro and in vivo, suggesting that targeting ATP synthesis inhibition in cancer cells might be an attractive therapeutic avenue in GBM management.

Non-targeted metabolomic profiling of filamentous cyanobacteria Aphanizomenon flos-aquae exposed to a concentrated culture filtrate of Microcystis aeruginosa

Microcystis and Aphanizomenon are two toxic cyanobacteria genera, which frequently cause blooms in freshwater lakes. In some cases, succession of these two genera was observed in natural water bodies. Among the diverse factors contributing to such succession of dominant cyanobacterial genera, an allelopathic effect was proposed to be involved after the growth inhibitory effect of several Microcystis species on A. flos-aquae was investigated. However, the response of target species exposed to Microcystis are poorly described. In the present study, we used two toxic cyanobacteria strains, Aphanizomenon flos-aquae (Aph1395) and Microcystis aeruginosa strain 905 (Ma905) as research subjects. Aph1395 was inhibited with a necessarily concentrated culture filtrate of Ma905 (MA905-SPE), and the response of the inhibited Aph1395 cells was explored via non-targeted metabolomic profiling. In total, 3735 features were significantly different in the Aph1395 treated with Ma905-SPE vs. those treated with BG11 medium. Among them, the annotations of 146 differential features were considered to be confident via MS/MS spectrum matching analysis. Based on the reported physiological functions of the annotated differential features, we proposed a putative model that in the growth-inhibited Aph1395, a suite of increased or decreased features with activities in apoptosis, growth inhibition, and stress response processes contributed to, or defended against, the allelopathic effect caused by Ma905. Our findings provide insights into the interaction between the bloom forming cyanobacterial species that share the same ecological environment.

Atrazine exposure and recovery alter the intestinal structure, bacterial composition and intestinal metabolites of male Pelophylax nigromaculatus

The pesticide atrazine poses a potential threat to the health of frogs living in farmland areas. The exposure concentration in traditional pesticide experiments is usually constant, while pesticide pollution in actual water may fluctuate due to periodic or seasonal application. We examined the effects of different concentrations of atrazine (50, 100 and 500 μg/L) over a 14-day exposure and a 7-day recovery on intestinal histology, bacterial composition and intestinal metabolites of male Pelophylax nigromaculatus. HE staining revealed that after a 14-day atrazine exposure, the 100 μg/L and 500 μg/L groups showed obvious cysts and significantly decreased intestinal crypt depth and villus height. After a 7-day recovery, the damaged intestine in the 100 μg/L group was partially recovered, while in the 500 μg/L exposure group there was no improvement. 16S rRNA gene analysis of intestinal bacteria showed that 500 μg/L atrazine exposure significantly caused a persistent decrease in bacterial α diversity. Compared to the control and other atrazine exposure groups, the 500 μg/L group showed significant changes in the relative abundance of predominant bacteria. In addition, most dominant bacteria in the 500 μg/L recovery group showed significant differences with the 50 μg/L and 100 μg/L recovery groups. Nontargeted metabolomics profiling based on UPLC/MS analysis showed that atrazine exposure and recovery induced changes in the intestinal metabolic profile. The changes in metabolites were mainly related to purine/pyrimidine metabolism, glycine, serine and threonine metabolism, and arginine and proline metabolism. In general, these pathways were closely related to energy metabolism and amino acid metabolism. These results suggest that the short-term exposure to 500 μg/L atrazine causes persistent harm to intestinal health. This study is an important step toward a better understanding of the toxic effects of atrazine exposure and recovery in frog intestines.

Traffic-related air pollution and endurance exercise: Characterizing non-targeted serum metabolomics profiling

Although the exposure to traffic-related air pollution (TRAP) has emerged as one of main problem worldwide to inhabitants’ health in urban centers, its impact on metabolic responses during exercise is poorly understood. The aim of study was to characterize the profile of non-target serum metabolomics during prolonged exercise performed under TRAP conditions. Ten healthy men completed two 90 min constant-load cycling trials under conditions of either TRAP or filtered air. Experimental trials were performed in a chamber located on an avenue with a high volume of vehicle traffic. Blood samples were taken at 30 min, 60 min, and 90 min of exercise. Based on Nuclear Magnetic Resonance metabolomics, the non-target analysis was used to assess the metabolic profile. Twelve, 16 and 18 metabolites were identified as discriminants. These were: at 30 min of exercise, the coefficient of determination (R2) 0.98, the predictive relevance, (Q2) 0.12, and the area under the curve (AUC) 0.91. After 60 min of exercise: (R2: 0.99, Q2: 0.09, AUC: 0.94); and at 90 min of exercise (R2: 0.91, Q2: <0.01, AUC: 0.89), respectively. The discriminant metabolites were then considered for the target analysis, which demonstrated that the metabolic pathways of glycine and serine metabolism (p = 0.03) had been altered under TRAP conditions at 30 min of exercise; arginine and proline metabolism (p = 0.04) at 60 min of exercise; and glycolysis (p = 0.05) at 90 min of exercise. The present results suggest that exposure to TRAP during prolonged exercise leads to a significant change in metabolomics, characterized by a transitional pattern and lastly, impairs the glucose metabolism.