PubMed

Talanta. 2023 Oct 17;268(Pt 1):125318. doi: 10.1016/j.talanta.2023.125318. Online ahead of print.ABSTRACTConsistent retention time (tR) of metabolites is vital for identification in metabolomic analysis with ultrahigh-performance liquid-chromatography (UPLC). To minimize inter-experimental tR variations from the reversed-phase UPLC-MS, we developed an endogenous retention-index (endoRI) using in-sample straight-chain acylcarnitines with different chain-length (LC, C0-C26) without additives. The endoRI-corrections reduced the tR variations caused by the combined changes of mobile phases, gradients, flow-rates, elution time, columns and temperature from up to 5.1 min-0.2 min for most metabolites in a model metabolome consisting of 91 metabolites and multiple biological matrices including human serum, plasma, fecal, urine, A549 cells and rabbit liver extracts. The endoRI-corrections also reduced the inter-batch and inter-platform tR variations from 1.5 min to 0.15 min for 95 % of detected features in the above biological samples. We further established a quantitative model between tR and LC for predicting tR values of acylcarnitines when absent in samples. This makes it possible to compare metabolites' tR from different tR databases and the UPLC-based metabolomic data from different batches.PMID:37875029 | DOI:10.1016/j.talanta.2023.125318

J Nat Prod. 2023 Oct 24. doi: 10.1021/acs.jnatprod.3c00490. Online ahead of print.ABSTRACTNatural product reisolation is a bottleneck when discovering new bioactive chemical entities from nature. To overcome this issue, multi-informative approaches integrating several layers of data have been applied with promising results. In this study, integration of taxonomy, nontargeted metabolomics, and bioactivity information resulted in the selection of Scytalidium sp. IQ-074 and Diaporthe sp. IQ-053 to isolate new natural products active against hPTP1B1-400 and repurpose others as antibiotics. Strain IQ-074 was selected based on the hypothesis that investigating poorly studied and highly metabolic taxa could lead to the isolation of new chemical entities. A chemical investigation of IQ-074 resulted in the isolation of papyracillic acid A (14), 7-deoxypapyracillic acid A (15a and 15b), and linear polyketides scytalpolyols A-D (16-19). Compound 17 inhibited hPTP1B1-400 with a half-maximal inhibitory concentration of 27.0 ± 1.7 μM. Diaporthe sp. IQ-053 was selected based on its antibacterial properties against pathogenic strains. Its chemical investigation yielded dothiorelones A (20) and I (21), cytosporones B (22) and C (23), pestalotiopsone B (24), and diaporthalasin (25). Compounds 22 and 25 inhibited the growth of Staphylococcus aureus and Staphylococcus epidermidis 42R and moderately inhibited the growth of Acinetobacter baumannii A564, a pandrug-resistant bacterium.PMID:37875020 | DOI:10.1021/acs.jnatprod.3c00490

Plant Cell Physiol. 2023 Oct 24:pcad130. doi: 10.1093/pcp/pcad130. Online ahead of print.ABSTRACTXylem vessel cell differentiation is characterized by the deposition of a secondary cell wall (SCW) containing cellulose, hemicellulose and lignin. VASCULAR-RELATED NAC DOMAIN7 (VND7), a plant-specific NAC transcription factor, is a master regulator of xylem vessel cell differentiation in Arabidopsis (Arabidopsis thaliana). Previous metabolome analysis using the VND7-inducible system in tobacco BY-2 cells successfully revealed significant quantitative changes in primary metabolites during xylem vessel cell differentiation. However, the flow of primary metabolites is not yet well understood. Here, we performed metabolomic analysis of VND7-inducible Arabidopsis T87 suspension cells. Capillary electrophoresis time-of-flight mass spectrometry quantified 57 metabolites, and subsequent data analysis highlighted active changes in the levels of UDP-glucose and phenylalanine, which are building blocks of cellulose and lignin, respectively. In a metabolic flow analysis using stable carbon 13 (13C) isotope, the 13C labeling ratio specifically increased in 3-phosphoglycerate after 12 h of VND7 induction, followed by an increase in shikimate after 24 h of induction, while the inflow of 13C into lactate from pyruvate was significantly inhibited, indicating an active shift of carbon flow from glycolysis to the shikimate pathway during xylem vessel cell differentiation. In support of this notion, most glycolytic genes involved in the downstream of glyceraldehyde 3-phosphate were downregulated following the induction of xylem vessel cell differentiation, whereas genes for the shikimate pathway and phenylalanine biosynthesis were upregulated. These findings provide evidence for the active shift of carbon flow from primary metabolic pathways to the SCW polymer biosynthetic pathway at specific points during xylem vessel cell differentiation.PMID:37875012 | DOI:10.1093/pcp/pcad130

J Am Soc Mass Spectrom. 2023 Oct 24. doi: 10.1021/jasms.3c00248. Online ahead of print.ABSTRACTLiquid chromatography-mass spectrometry (LC-MS) metabolomics studies produce high-dimensional data that must be processed by a complex network of informatics tools to generate analysis-ready data sets. As the first computational step in metabolomics, data processing is increasingly becoming a challenge for researchers to develop customized computational workflows that are applicable for LC-MS metabolomics analysis. Ontology-based automated workflow composition (AWC) systems provide a feasible approach for developing computational workflows that consume high-dimensional molecular data. We used the Automated Pipeline Explorer (APE) to create an AWC for LC-MS metabolomics data processing across three use cases. Our results show that APE predicted 145 data processing workflows across all the three use cases. We identified six traditional workflows and six novel workflows. Through manual review, we found that one-third of novel workflows were executable whereby the data processing function could be completed without obtaining an error. When selecting the top six workflows from each use case, the computational viable rate of our predicted workflows reached 45%. Collectively, our study demonstrates the feasibility of developing an AWC system for LC-MS metabolomics data processing.PMID:37874901 | DOI:10.1021/jasms.3c00248

Aging (Albany NY). 2023 Oct 23;15. doi: 10.18632/aging.205109. Online ahead of print.ABSTRACTCompared to replicative lifespan, epigenetic regulation of chronological lifespan (CLS) is less well understood in yeast. Here, by screening all the viable mutants of histone acetyltransferase (HAT) and histone deacetylase (HDAC), we demonstrate that Gcn5, functioning in the HAT module of the SAGA/SLIK complex, exhibits an epistatic relationship with the HDAC Hda1 to control the expression of starvation-induced stress response and respiratory cell growth. Surprisingly, the gcn5Δ mutants lose their colony-forming potential early in the stationary phase but display a longer maximum CLS than their WT counterparts, suggesting the contradictory roles of Gcn5 in lifespan regulation. Integrative analyses of the transcriptome, metabolome and ChIP assays reveal that Gcn5 is necessary for the activation of two regulons upon glucose starvation: the Msn2/4-/Gis1-dependent stress response and the Cat8-/Adr1-mediated metabolic reprogramming, to enable pro-longevity characteristics, including redox homeostasis, stress resistance and maximal storage of carbohydrates. The activation of Cat8-/Adr1-dependent regulon also promotes the pyruvate dehydrogenase (PDH) bypass, leading to acetyl-CoA synthesis, global and targeted H3K9 acetylation. Global H3K9 acetylation levels mediated by Gcn5 and Hda1 during the transition into stationary phase are positively correlated with senescent cell populations accumulated in the aged cell cultures. These data suggest that Gcn5 lies in the centre of a feed-forward loop between histone acetylation and starvation-induced gene expression, enabling stress resistance and homeostasis but also promoting chronological ageing concomitantly.PMID:37874684 | DOI:10.18632/aging.205109

mSystems. 2023 Oct 24:e0072623. doi: 10.1128/msystems.00726-23. Online ahead of print.ABSTRACTCorticosteroids have become a choice for managing severe COVID-19, but the molecular mechanisms behind the response after corticosteroid administration remain incompletely understood. In order to unravel this, comparisons between temporal metabolic profiles in the plasma samples of methylprednisolone (MP)- and placebo-treated COVID-19 patients were performed at different time points. The patient plasma samples used were obtained from a double-blind, randomized, placebo-controlled Phase IIb clinical trial performed on severe COVID-19 patients in the Brazilian Amazon, where the patients received placebo or 0.5 mg/kg MP intravenously twice daily for 5 days. The MP treatment reduced the number of metabolites in the plasma of patients during follow-up. The longitudinal changes in the MP group were in eight metabolic pathways related to steroid hormones and eicosanoids. Direct comparison between the two groups, revealed differences at baseline, which peaked 5 days after initiation of MP treatment. The metabolic pathways differing between the two groups over time included galactose metabolism, glucose and gluconeogenesis, N-glycan metabolism, and prostaglandin formation from arachidonate. Deoxy-galactose, prostaglandin H2, sphingosine, and sphinganine exhibited differential trajectories by day 14 after initiating the MP treatment. Survival of MP-treated COVID-19 patients was associated with modulation of tryptophan metabolism and diminished levels of oxidized glutathione. Network analysis revealed that MP treatment is highly associated with alterations in pathways reflecting eicosanoid metabolism, such as arachidonic acid and prostaglandins. Curiously, there is a crosstalk between metabolomics, biochemistry, and cytokine components. Treatment of systemic and inflammatory conditions induced by SARS-CoV-2 viral infections with methylprednisolone modulates metabolic activity associated with tryptophan and inflammatory lipids.IMPORTANCEThe SARS-CoV-2 virus infection in humans induces significant inflammatory and systemic reactions and complications of which corticosteroids like methylprednisolone have been recommended as treatment. Our understanding of the metabolic and metabolomic pathway dysregulations while using intravenous corticosteroids in COVID-19 is limited. This study will help enlighten the metabolic and metabolomic pathway dysregulations underlying high daily doses of intravenous methylprednisolone in COVID-19 patients compared to those receiving placebo. The information on key metabolites and pathways identified in this study together with the crosstalk with the inflammation and biochemistry components may be used, in the future, to leverage the use of methylprednisolone in any future pandemics from the coronavirus family.PMID:37874139 | DOI:10.1128/msystems.00726-23

Pathophysiology. 2023 Sep 29;30(4):443-466. doi: 10.3390/pathophysiology30040033.ABSTRACTOne of the primary challenges regarding chronic kidney disease (CKD) diagnosis is the absence of reliable methods to detect early-stage kidney damage. A metabolomic approach is expected to broaden the current diagnostic modalities by enabling timely detection and making the prognosis more accurate. Analysis performed on urine has several advantages, such as the ease of collection using noninvasive methods and its lower protein and lipid content compared with other bodily fluids. This review highlights current trends in applied analytical methods, major discoveries concerning pathways, and investigated populations in the context of urine metabolomic research for CKD over the past five years. Also, we are presenting approaches, instrument upgrades, and sample preparation modifications that have improved the analytical parameters of methods. The onset of CKD leads to alterations in metabolism that are apparent in the molecular composition of urine. Recent works highlight the prevalence of alterations in the metabolic pathways related to the tricarboxylic acid cycle and amino acids. Including diverse patient cohorts, using numerous analytical techniques with modifications and the appropriate annotation and explanation of the discovered biomarkers will help develop effective diagnostic models for different subtypes of renal injury with clinical applications.PMID:37873853 | DOI:10.3390/pathophysiology30040033

Int J Neonatal Screen. 2023 Oct 20;9(4):60. doi: 10.3390/ijns9040060.ABSTRACTNewborn screening (NBS) of inborn errors of metabolism (IEMs) is based on the reference ranges established on a healthy newborn population using quantile statistics of molar concentrations of biomarkers and their ratios. The aim of this paper is to investigate whether multivariate independent component analysis (ICA) is a useful tool for the analysis of NBS data, and also to address the structure of the calculated ICA scores. NBS data were obtained from a routine NBS program performed between 2013 and 2022. ICA was tested on 10,213/150 free-diseased controls and 77/20 patients (9/3 different IEMs) in the discovery/validation phases, respectively. The same model computed during the discovery phase was used in the validation phase to confirm its validity. The plots of ICA scores were constructed, and the results were evaluated based on 5sd levels. Patient samples from 7/3 different diseases were clearly identified as 5sd-outlying from control groups in both phases of the study. Two IEMs containing only one patient each were separated at the 3sd level in the discovery phase. Moreover, in one latent variable, the effect of neonatal birth weight was evident. The results strongly suggest that ICA, together with an interpretation derived from values of the "average member of the score structure", is generally applicable and has the potential to be included in the decision process in the NBS program.PMID:37873851 | DOI:10.3390/ijns9040060

Zhonghua Wei Zhong Bing Ji Jiu Yi Xue. 2023 Oct;35(10):1111-1115. doi: 10.3760/cma.j.cn121430-20230418-00294.ABSTRACTAcute kidney injury (AKI) is caused by a variety of diseases, which leads to acute renal function decline, azotemia, water and electrolyte disorders and acid-base balance disorders. Metabolomics is a research method that can quantitatively analyze all metabolites in an organism and find the relative relationship between metabolites and physiological and pathological changes. In recent years, several metabolites screened based on metabolomics have been proposed as potential biomarkers to assess the early development and prognosis of AKI and for the discovery of unknown potential therapeutic targets. Based on metabolomics, this paper reviews the risk prediction, early diagnosis, disease monitoring, prognosis assessment and the application of corresponding drugs for AKI, so as to provide reference for precision medicine.PMID:37873720 | DOI:10.3760/cma.j.cn121430-20230418-00294

Am J Physiol Gastrointest Liver Physiol. 2023 Oct 24. doi: 10.1152/ajpgi.00091.2023. Online ahead of print.ABSTRACTMetal transporter SLC39A14/ZIP14 is localized on the basolateral side of the intestine, functioning to transport metals from blood to intestine epithelial cells. Deletion of Slc39a14/Zip14 causes spontaneous intestinal permeability with low-grade chronic inflammation, mild hyperinsulinemia, and greater body fat with insulin resistance in adipose. Importantly, antibiotic treatment reverses the adipocyte phenotype of Slc39a14/Zip14 knockout (KO), suggesting a potential gut microbial role in the metabolic alterations in the Slc39a14/Zip14 KO mice. Here, we investigated the hypothesis that increased intestinal permeability and subsequent metabolic alterations in the absence of Zip14 could be in part due to alterations in gut microbial composition. Dietary metals have been shown to be involved in the regulation of gut microbial diversity and composition. However, studies linking the action of intestinal metal transporters to gut microbial regulation are lacking. We showed the influence of deletion of metal transporter Slc39a14/Zip14 on gut microbiome composition and how ZIP14-linked changes to gut microbiome community composition are correlated with changes in host metabolism. Deletion of Slc39a14/Zip14 generated Zn-deficient epithelial cells and luminal content in the entire intestinal tract; a shift in gut microbial composition that partially overlapped with changes previously associated with obesity and inflammatory bowel disease (IBD); increased the fungi/bacteria ratio in the gut microbiome; altered the host metabolome; and shifted host energy metabolism toward glucose utilization. Collectively, our data suggest a potential pre-disease microbial susceptibility state dependent on host gene Slc39a14/Zip14 that contributes to intestinal permeability, a common trait of IBD, and metabolic disorders such as obesity and type-2 diabetes.PMID:37873588 | DOI:10.1152/ajpgi.00091.2023

J Endocr Soc. 2023 Aug 24;7(9):bvad110. doi: 10.1210/jendso/bvad110. eCollection 2023 Aug 2.ABSTRACT[This corrects the article DOI: 10.1210/jendso/bvad091.].PMID:37873502 | PMC:PMC10590642 | DOI:10.1210/jendso/bvad110

bioRxiv. 2023 Oct 2:2023.10.02.560557. doi: 10.1101/2023.10.02.560557. Preprint.ABSTRACTHow the microaerobic pathogen Campylobacter jejuni establishes its niche and expands in the gut lumen during infection is poorly understood. Using six-week-old ferrets as a natural disease model, we examined this aspect of C. jejuni pathogenicity. Unlike mice, which require significant genetic or physiological manipulation to become colonized with C. jejuni , ferrets are readily infected without the need to disarm the immune system or alter the gut microbiota. Disease after C. jejuni infection in ferrets reflects closely how human C. jejuni infection proceeds. Rapid growth of C. jejuni and associated intestinal inflammation was observed within two-three days of infection. We observed pathophysiological changes that were noted by cryptic hyperplasia through the induction of tissue repair systems, accumulation of undifferentiated amplifying cells on the colon surface, and instability of HIF-1α in colonocytes, which indicated increased epithelial oxygenation. Metabolomic analysis demonstrated that lactate levels in colon content were elevated in infected animals. A C. jejuni mutant lacking lctP , which encodes an L-lactate transporter, was significantly decreased for colonization during infection. Lactate also influences adhesion and invasion by C. jejuni to a colon carcinoma cell line (HCT116). The oxygenation required for expression of lactate transporter ( lctP ) led to discovery of a putative thiol based redox switch regulator (LctR) that may repress lctP transcription under anaerobic conditions. Our work provides new insights into the pathogenicity of C. jejuni .SIGNIFICANCE: There is a gap in knowledge about the mechanisms by which C. jejuni populations expand during infection. Using an animal model which accurately reflects human infection without the need to alter the host microbiome or the immune system prior to infection, we explored pathophysiological alterations of the gut after C. jejuni infection. Our study identified the gut metabolite L-lactate as playing an important role as a growth substrate for C. jejuni during acute infection. We identified a DNA binding protein, LctR, that binds to the lctP promoter and may repress lctP expression, resulting in decreased lactate transport under low oxygen levels. This work provides new insights about C. jejuni pathogenicity.PMID:37873437 | PMC:PMC10592923 | DOI:10.1101/2023.10.02.560557

medRxiv. 2023 Oct 2:2023.09.30.23296261. doi: 10.1101/2023.09.30.23296261. Preprint.ABSTRACTHeart failure with preserved ejection fraction (HFpEF) accounts for >50% of all heart failure world-wide and remains a major unmet medical need. The most effective recently approved treatments were first developed for diabetes, suggesting metabolic defects are paramount. Myocardial metabolomics in human HFpEF has identified reduced fatty acid and branched chain amino acid catabolism, but the status of glycolysis is unknown. Here we performed targeted metabolomics and protein analysis of glycolytic pathway enzymes in myocardial biopsies of patients with HFpEF versus HF with reduced ejection fraction (HFrEF0 or non-failing controls. Glucose was increased in HFpEF myocardium, but immediate downstream glycolytic metabolites (glucose-6 phosphate, fructose 1,6 diphosphate), were more reduced in HFpEF than the other groups, as were their associated synthetic enzymes hexokinase and phosphofructokinase. Pyruvate was also reduced in HFpEF versus controls. These changes were either not present or substantially less so in HFrEF. Suppression of proximal glycolysis was also coupled to lower metabolites and proteins in the pentose phosphate pathway but was independent of diabetes or obesity. These findings support marked metabolic inflexibility in HFpEF and identifies very proximal blockade in glucose metabolism. Efforts to improve metabolic use of carbohydrates in HFpEF will likely need to target these proximal glycolytic enzymes.PMID:37873321 | PMC:PMC10593049 | DOI:10.1101/2023.09.30.23296261

medRxiv. 2023 Oct 2:2023.09.30.23296386. doi: 10.1101/2023.09.30.23296386. Preprint.ABSTRACTA growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short-or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease, and highlight contemporary challenges and opportunities associated with such efforts.PMID:37873294 | PMC:PMC10592990 | DOI:10.1101/2023.09.30.23296386

bioRxiv. 2023 Oct 9:2023.10.06.561131. doi: 10.1101/2023.10.06.561131. Preprint.ABSTRACTCancer cells depend on nicotinamide adenine dinucleotide phosphate (NADPH) to combat oxidative stress and support reductive biosynthesis. One major NAPDH production route is the oxidative pentose phosphate pathway (committed step: glucose-6-phosphate dehydrogenase, G6PD). Alternatives exist and can compensate in some tumors. Here, using genetically-engineered lung cancer model, we show that ablation of G6PD significantly suppresses Kras G12D/+ ;Lkb1 -/- (KL) but not Kras G12D/+ ;p53 -/- (KP) lung tumorigenesis. In vivo isotope tracing and metabolomics revealed that G6PD ablation significantly impaired NADPH generation, redox balance and de novo lipogenesis in KL but not KP lung tumors. Mechanistically, in KL tumors, G6PD ablation caused p53 activation that suppressed tumor growth. As tumor progressed, G6PD-deficient KL tumors increased an alternative NADPH source, serine-driven one carbon metabolism, rendering associated tumor-derived cell lines sensitive to serine/glycine depletion. Thus, oncogenic driver mutations determine lung cancer dependence on G6PD, whose targeting is a potential therapeutic strategy for tumors harboring KRAS and LKB1 co-mutations.PMID:37873106 | PMC:PMC10592603 | DOI:10.1101/2023.10.06.561131

ArXiv. 2023 Oct 12:arXiv:2310.07990v1. Preprint.ABSTRACTBACKGROUND: Missing data is a common challenge in mass spectrometry-based metabolomics, which can lead to biased and incomplete analyses. The integration of whole-genome sequencing (WGS) data with metabolomics data has emerged as a promising approach to enhance the accuracy of data imputation in metabolomics studies.METHOD: In this study, we propose a novel method that leverages the information from WGS data and reference metabolites to impute unknown metabolites. Our approach utilizes a multi-view variational autoencoder to jointly model the burden score, polygenetic risk score (PGS), and linkage disequilibrium (LD) pruned single nucleotide polymorphisms (SNPs) for feature extraction and missing metabolomics data imputation. By learning the latent representations of both omics data, our method can effectively impute missing metabolomics values based on genomic information.RESULTS: We evaluate the performance of our method on empirical metabolomics datasets with missing values and demonstrate its superiority compared to conventional imputation techniques. Using 35 template metabolites derived burden scores, PGS and LD-pruned SNPs, the proposed methods achieved r2-scores > 0.01 for 71.55% of metabolites.CONCLUSION: The integration of WGS data in metabolomics imputation not only improves data completeness but also enhances downstream analyses, paving the way for more comprehensive and accurate investigations of metabolic pathways and disease associations. Our findings offer valuable insights into the potential benefits of utilizing WGS data for metabolomics data imputation and underscore the importance of leveraging multi-modal data integration in precision medicine research.PMID:37873011 | PMC:PMC10593076

J Food Sci. 2023 Oct 23. doi: 10.1111/1750-3841.16784. Online ahead of print.ABSTRACTFoliar spraying to improve the quality of fruits is a general approach nowadays. In this study, 10 ppm nano-selenium (nano-Se) diluted with distilled water was sprayed on peach leaves every 10 days for a total of 7 sprays during the fruit set period. And then their fruit quality was compared with that of control group. It was found that the firmness, soluble solid concentration, total phenol, and proanthocyanidin content of the peaches were raised after the nano-Se treatment. Moreover, the ascorbic acid glutathione loop (ASA-GSH loop) was fully activated in the nano-Se treated group, and the associated antioxidant capacity and enzyme activity were significantly increased. Metabolomics revealed that nano-Se could upregulate some metabolites, such as phenylalanine, naringenin, and pinocembrin, to fully activate the metabolism of phenylpropanoids. Further, based on transcriptomics, nano-Se treatment was found to affect fruit quality by regulating genes related to phenylpropanoid metabolism, such as arogenate/prephenate dehydratase (ADT), genes related to abscisic acid metabolism such as (+)-abscisic acid 8'-hydroxylase (CYP707A), and some transcription factors such as MYB. Based on the comprehensive analysis of physicochemical indicators, metabolomics, and transcriptomics, it was found that nano-Se improved fruit quality by activating phenylpropanoid metabolism and enhancing antioxidant capacity. This work provides insights into the mechanism of the effect of nano-Se fertilizer on peach fruit quality. PRACTICAL APPLICATION: The firmness and soluble solid concentration of peaches are higher after nano-Se treatment, which is more in line with people's demand for hard soluble peaches like "Yingzui." The antioxidant capacity, antioxidant substance content, and antioxidant enzyme activity of nano-Se-treated peaches are higher, with potential storage resistance and health effects on human body. The mechanism of nano-Se affecting peach quality was analyzed by metabolomics and transcriptomics, which is a reference and guide for the research and application of nano-Se.PMID:37872835 | DOI:10.1111/1750-3841.16784

New Phytol. 2023 Oct 23. doi: 10.1111/nph.19332. Online ahead of print.ABSTRACTC4 plants typically operate a CO2 concentration mechanism from mesophyll (M) cells into bundle sheath (BS) cells. NADH dehydrogenase-like (NDH) complex is enriched in the BS cells of many NADP-malic enzyme (ME) type C4 plants and is more abundant in C4 than in C3 plants, but to what extent it is involved in the CO2 concentration mechanism remains to be experimentally investigated. We created maize and rice mutants deficient in NDH function and then used a combination of transcriptomic, proteomic, and metabolomic approaches for comparative analysis. Considerable decreases in growth, photosynthetic activities, and levels of key photosynthetic proteins were observed in maize but not rice mutants. However, transcript abundance for many cyclic electron transport (CET) and Calvin-Benson cycle components, as well as BS-specific C4 enzymes, was increased in maize mutants. Metabolite analysis of the maize ndh mutants revealed an increased NADPH : NADP ratio, as well as malate, ribulose 1,5-bisphosphate (RuBP), fructose 1,6-bisphosphate (FBP), and photorespiration intermediates. We suggest that by optimizing NADPH and malate levels and adjusting NADP-ME activity, NDH functions to balance metabolic and redox states in the BS cells of maize (in addition to ATP supply), coordinating photosynthetic transcript abundance and protein content, thus directly regulating the carbon flow in the two-celled C4 system of maize.PMID:37872738 | DOI:10.1111/nph.19332

BMC Genomics. 2023 Oct 23;24(1):630. doi: 10.1186/s12864-023-09725-3.ABSTRACTBackground Puccinia arachidis fungus causes rust disease in the peanut plants (Arachis hypogaea L.), which leads to high yield loss. Metabolomic profiling of Arachis hypogaea was performed to identify the pathogen-induced production of metabolites involved in the defense mechanism of peanut plants. In this study, two peanut genotypes, one susceptible (JL-24) and one resistant (GPBD-4) were inoculated with Puccinia arachidis fungal pathogen. The metabolic response was assessed at the control stage (0 day without inoculation), 2 DAI (Day after inoculation), 4 DAI and 6 DAI by Gas Chromatography-Mass Spectrometry (GC-MS). Results About 61 metabolites were identified by NIST library, comprising sugars, phenols, fatty acids, carboxylic acids and sugar alcohols. Sugars and fatty acids were predominant in leaf extracts compared to other metabolites. Concentration of different metabolites such as salicylic acid, mannitol, flavonoid, 9,12-octadecadienoic acid, linolenic acid and glucopyranoside were higher in resistant genotype than in susceptible genotype during infection. Systemic acquired resistance (SAR) and hypersensitive reaction (HR) components such as oxalic acid was elevated in resistant genotype during pathogen infection. Partial least square-discriminant analysis (PLS-DA) was applied to GC-MS data for revealing metabolites profile between resistant and susceptible genotype during infection. Conclusion The phenol content and oxidative enzyme activity i.e. catalase, peroxidase and polyphenol oxidase were found to be very high at 4 DAI in resistant genotype (p-value < 0.01). This metabolic approach provides information about bioactive plant metabolites and their application in crop protection and marker-assisted plant breeding.PMID:37872498 | DOI:10.1186/s12864-023-09725-3

Nat Metab. 2023 Oct;5(10):1656-1672. doi: 10.1038/s42255-023-00903-x. Epub 2023 Oct 23.ABSTRACTMetabolomic epidemiology is the high-throughput study of the relationship between metabolites and health-related traits. This emerging and rapidly growing field has improved our understanding of disease aetiology and contributed to advances in precision medicine. As the field continues to develop, metabolomic epidemiology could lead to the discovery of diagnostic biomarkers predictive of disease risk, aiding in earlier disease detection and better prognosis. In this Review, we discuss key advances facilitated by the field of metabolomic epidemiology for a range of conditions, including cardiometabolic diseases, cancer, Alzheimer's disease and COVID-19, with a focus on potential clinical utility. Core principles in metabolomic epidemiology, including study design, causal inference methods and multi-omic integration, are briefly discussed. Future directions required for clinical translation of metabolomic epidemiology findings are summarized, emphasizing public health implications. Further work is needed to establish which metabolites reproducibly improve clinical risk prediction in diverse populations and are causally related to disease progression.PMID:37872285 | DOI:10.1038/s42255-023-00903-x