Untargeted and targeted approaches are the traditional metabolomics workflows acquired for a wider understanding of the metabolome under focus. Both approaches have their strengths and weaknesses. The untargeted, for example, is maximizing the detection and accurate identification of thousands of metabolites, while the targeted is maximizing the linear dynamic range and quantification sensitivity. These workflows, however, are acquired separately, so researchers compromise either a low-accuracy overview of total molecular changes (i.e., untargeted analysis) or a detailed yet blinkered snapshot of a selected group of metabolites (i.e., targeted analysis) by selecting one of the workflows over the other. In this review, we present a novel single injection simultaneous quantitation and discovery (SQUAD) metabolomics that combines targeted and untargeted workflows. It is used to identify and accurately quantify a targeted set of metabolites. It also allows data retro-mining to look for global metabolic changes that were not part of the original focus. This offers a way to strike the balance between targeted and untargeted approaches in one single experiment and address the two’s limitations. This simultaneous acquisition of hypothesis-led and discovery-led datasets allows scientists to gain more knowledge about biological systems in a single experiment.

Metabolomics is now considered to be a wide-ranging, sensitive and practical approach to acquire useful information on the composition of a metabolite pool present in any organism, including plants. Investigating metabolomic regulation in plants is essential to understand their adaptation, acclimation and defense response to environmental stresses through the production of numerous metabolites. Moreover, metabolomics can be easily applied for the phenotyping of plants; and thus, it has great potential to be used in molecular breeding and genome editing programs to develop superior next generation crops. This review describes the recent analytical tools and techniques available to study plants metabolome, along with their significance of sample preparation using targeted and non-targeted method. Advanced analytical tools, like gas chromatography-mass spectrometry (GC-MS), liquid chromatography mass-spectroscopy (LC-MS), capillary electrophoresis-mass spectrometry (CE-MS), fourier transform ion cyclotron resonance-mass spectrometry (FTICR-MS) and matrix-assisted laser desorption/ionization (MALDI) have speed up metabolic profiling in plants. Further, we deliver a complete overview of bioinformatics tools and plant metabolome database that can be utilized to advance our knowledge to plant biology.

A remarkable feature of US federal investments in human genetics has been the availability of parallel funding for studies examining ethical, legal and social implications (ELSI). This funding has allowed ELSI researchers to develop new strategies to understand genetics, evaluate the benefits of genetic testing, and propose health policy that maximize the promise while minimizing harms. Despite successes, a consequence of this investment is the preoccupation with what is arguably the least actionable system of biomolecules, human DNA. In contrast, the most actionable system of biomolecules, the metabolome, is grossly understudied, despite its often more alarming ELSI.

Approaches to identification of metabolites have progressed from early biochemical pathway evaluation to modern high dimensional metabolomics which is a powerful tool to identify and characterize biomarkers of health and disease. While traditionally considered relevant in the context of classic metabolic diseases, immunometabolism has emerged as an important area of study as leukocytes generate key metabolites important to innate and adaptive immunity. Herein we discuss the metabolomic signatures and pathways perturbed during infection as well as vaccination. For example, changes in lipid and amino acid pathways (e.g., tryptophan, serine, and threonine) have been noted during infection while carbohydrate and bile acid pathways have shift upon vaccination. Metabolomics holds substantial promise to provide fresh insight into the molecular mechanisms underlying host response to infection and vaccination, and its integration with other systems biology platforms will add further impact to our studies of health and disease.

Leukemia represents as one of the most common primary malignancies of the hematologic system in both children’s and adults and remains a largely incurable or relapse disease. The elucidation of disease subtypes based on mutational profiling, has not improved clinical outcomes. IDH1/2 are key enzymes of TCA cycle that produces α-ketoglutarate (αKG), however their mutated version, are well reported in various cancer types including leukemia, produces D-2 hydroxyglutarate (D-2HG), an oncometabolite. Recently, some studies have shown that wild type IDH1 is highly expressed in non-small cell lung carcinoma (NSCLC), primary glioblastomas (GBM) and several hematological malignancies and corelates with disease progression. In this work, we have showed treatment of wild type IDH1 leukemia cells with specific IDH1 inhibitor switched leukemic cells towards gly-colysis from oxidative phosphorylation (OXPHOS) phenotype. We also noticed reduction in αKG in treated cells possible suggesting inhibition of IDH1 enzymatic activity. Further, we found that IDH1 inhibition reduces the metabolites related to one carbon metabolism, essential to maintain global methylation in leukemic cells. Finally, we observed that metabolic alteration in IDH1 inhibitor treated leukemic cells promotes reactive oxygen species (ROS) formation along with loss of mito-chondrial membrane potential, leading towards apoptosis in leukemic cells. Overall, we showed that wild type IDH1 targeting in leukemic cells promote metabolic alterations that can be exploited for combination therapies for better outcome.

Recently we have seen a relaxation of the historic restrictions on the use and subsequent research on the Cannabis plants, generally classified as Cannabis sativa and Cannabis indica. What research has been performed to date has centered on chemical analysis of plant flower products, namely cannabinoids and various terpenes that directly contribute to phenotypic characteristics of the female flowers. In addition, we have seen many groups recently completing genetic profiles of various plants of commercial value. To date, no comprehensive attempt has been made to profile the proteomes of these plants. We report herein our progress on constructing a comprehensive draft map of the Cannabis proteome. To date we have identified over 17,000 potential protein sequences. Unfortunately, no annotated genome of Cannabis plants currently exists. We present a method by which “next generation” DNA sequencing output and shotgun proteomics data can be combined to produce annotated FASTA files, bypassing the need for annotated genetic information altogether in traditional proteomics workflows. The resulting material represents the first comprehensive annotated protein FASTA for any Cannabis plant. Using this annotated database as reference we can refine our protein identifications, resulting in the confident identification of 13,000 proteins with putative function. Furthermore, we demonstrate that post-translational modifications play an important role in the proteomes of Cannabis flower, particularly lysine acetylation and protein glycosylation. To facilitate the evolution of analytical investigations into these plant materials, we have created a portal to host resources we have developed from proteomic and metabolomic analysis of Cannabis plant material as well as our results integrating these resources. All data for this project is available to view or download at www.CannabisDraftMap.Org

Hyperlipidaemia (HLP) is a disorder with disturbed lipid metabolism and a major risk factor for various diseases. This study focused on the effect of moxibustion with seed-sized moxa cone on HLP and the relative metabolites and pathways. Levels of total cholesterol (TC), triglyceride (TG) and low-density lipoprotein cholesterol (LDC-C) in healthy controls (HC), HLP patients, HLP patients before (BMT) and after (AMT) moxibustion treatment were measured. Using the liquid chromatograph-mass spectrometry (LC-MS) technique, we detected the plasma metabolites in the aforementioned groups. Pathway analysis was performed for the differential metabolites. Results revealed significantly high levels of TC, TG and LDC-C and low levels of HDC-C were measured in HLP compared to HC. After moxibustion treatment, the levels of TC and TG significantly decreased. Total 87 and 51 differential metabolites were identified in HLP vs HC and AMT vs BMT, respectively, and 21 were common differential metabolites. The differential metabolites in HLP vs HC and AMT vs BMT both significantly enriched in the pathways of Glycerophospholipid metabolism and Sphingolipid metabolism. In conclusion, moxibustion with seed-sized moxa cone effectively improved HLP, might be by affecting the levels of TC and TG, and the regulating of the Glycerophospholipid metabolismand Sphingolipid metabolism pathways.

The breeding of stress-tolerant cultivated plants that would allow for a reduction in harvest losses and undesirable decrease in quality attributes requires a new quality of knowledge on molecular markers associated with relevant agronomic traits, on quantitative metabolic responses of plants on stress challenges, and on the mechanisms controlling the biosynthesis of these molecules. By combining metabolomics with genomics, transcriptomics and proteomics datasets a more comprehensive knowledge of the composition of crop plants used for food or animal feed is possible. In order to optimize crop trait developments, to enhance crop yields and quality, as well as to guarantee nutritional and health factors, that provides the possibility to create functional food or feedstuffs, the knowledge about the plants’ metabolome is crucial. Next to classical metabolomics studies, this review focusses on several metabolomics based working techniques, such as sensomics, lipidomics, hormonomics and phytometabolomics, which were used to characterize metabolome alterations during abiotic and biotic stress, to find resistant food crops with a preferred quality or at least to produce functional food crops are highlighted.

The dysregulation of cellular metabolism is a hallmark of ageing. To understand the metabolic changes that occur as a consequence of the ageing process and to find biomarkers for age-related diseases, we conducted a metabolomic analysis of brain, heart, kidney, liver, lung and spleen in young (9-10 weeks) and old (96-104 weeks) wild type (mixed genetic background of 129/J and C57BL/6) mice using NMR spectroscopy. We found differences in metabolic fingerprints of all tissues and identified several metabolites to be altered in most tissues, suggesting that they may be universal biomarkers of ageing. In addition, we found distinct tissue-clustered sets of metabolites throughout the organism. The associated metabolic changes may reveal novel therapeutic targets for the treatment of ageing and age-related diseases. Moreover, the identified metabolite biomarkers could provide a sensitive molecular read-out to age determine the age of biologic tissues and to validate the effectiveness and potential off-target effects of senolytic drug candidates on both a systemic and tissue-specific level.

Detection of pancreatic cancer (PC) at a resectable stage is still difficult because of the lack of accurate detection tests. The development of accurate biomarkers in low or non-invasive biofluids is essential to enable frequent tests, which would help increase the opportunity of PC detection in early stages. Polyamines have been reported as possible biomarkers in urine and saliva samples in various cancers. Here, we analyzed salivary metabolites, including polyamines, using capillary electrophoresis-mass spectrometry. Salivary samples were collected from patients with PC (n=39), chronic pancreatitis (CP, n=14) and controls (C, n=26). Polyamines, such as spermine, N1-acetylspermidine, and N1-acetylspermine, showed a significant difference between PC and C, and the combination of four metabolites including N1-acetylspermidine showed high accuracy in discriminating PC from the other two groups. These data showed the potential of saliva as a screening test for PC.

Background: Atherosclerosis (AS) is a chronic progressive disease caused by lipometabolic disorder. However, the pathological characteristics and mechanism of AS have not been fully clarified. By high fat and cholesterol diet induction, Tibetan minipig could be developed to the AS model animal which had a very similar pathogenesis to human AS. Methods: Here, we built the AS model of Tibetan minipigs and identified the differential abundance metabolites in the development of AS based on untargeted metabolomics. Results: We found that the sphingolipid metabolism and glucose oxidation were enriched in the AS group and the phenylalanine metabolism was reduced in the AS group. Moreover, in the development of AS, gluconolactone was enriched in the late stage of AS whereas biopterin was enriched in the early stage of AS. Conclusion: Gluconolactone and biopterin could be potential biomarkers for indicating the development of AS. Our research provides novel clues for the metabolic mechanism of AS from the perspective of metabolomics.

Although numerous citrus varieties have recently been developed to enhance their quality, information on their quality characteristics is limited. We assessed the quality characteristics of Yellowball, a novel citrus variety, by evaluating its appearance, storability, sensory properties, functionality, and metabolite profiles and comparing these characteristics with those of its parent varieties: Haruka and Kiyomi. The metabolite profiles between the citrus varieties differed significantly, resulting in distinct physicochemical and functional qualities. The storability of Yellowball was significantly increased compared with that of its parent varieties owing to its strong antifungal activity and unique peel morphology, including the stoma and albedo layers. While we did not investigate the volatile compounds, overall functional activities, and detailed characteristics of each metabolite, our data provide valuable insights into the relationship between citrus metabolites, peel morphology, physicochemical properties, and storability and demonstrate the potential of Yellowball as a promising variety in the citrus industry.

Gas chromatography-coupled mass spectrometry (GC-MS) has been used in biomedical research to analyze volatile, non-polar, and polar metabolites in a wide array of sample types. Despite advances in technology, missing values are still common in metabolomics datasets and must be properly handled. We evaluated the performance of ten commonly used missing value imputation methods with metabolites analyzed on an HR GC-MS instrument. By introducing missing values into the complete (i.e., data without any missing values) NIST plasma dataset we demonstrate that Random Forest (RF), Glmnet Ridge Regression (GRR), and Bayesian Principal Component Analysis (BPCA) shared the lowest Root Mean Squared Error (RMSE) in technical replicate data. Further examination of these three methods in data from baboon plasma and liver samples demonstrated they all maintained high accuracy. Overall, our analysis suggests that any of the three imputation methods can be applied effectively to untargeted metabolomics datasets with high accuracy. However, it is important to note that imputation will alter the correlation structure of the dataset, and bias downstream regression coefficients and p-values.

Pattern analysis of salivary metabolic profile has been proven accurate to discriminate generalized periodontitis (GP) patients from healthy individuals (HI) as disease modifies the salivary concentrations of specific metabolites. Due to the scarcity of data in the literature, the aim of this study was to determine whether non-surgical periodontal therapy (NST) could change salivary metabolomic profile in GP to one more similar to HI. Unstimulated whole saliva of 11 HI and 12 GP patients were obtained prior to and 3 months after NST. Metabolic profiling was performed using Nuclear Magnetic Resonance (NMR) spectroscopy, followed by supervised multivariate statistical approach on entire saliva spectra and partial least square (PLS) discriminant analysis. In GP group, periodontal treatment improved all clinical parameters, but not all the diseased sites were eradicated. PLS revealed an accuracy of 100% in discriminating the metabolomic profile of each GP patient before and after NST. OPLS was able to discriminate the 3 groups of subjects with an accuracy of 85.6%. However the post-NST metabolic profile of GP patients could not be completely assimilated to that of HS. Although NST may produce significant changes in the metabolic profile, GP patients maintained a distinctive fingerprint compared to HI.

Peach is the third most important temperate fruit crop considering fruit production and harvested area in the world. Exporting peaches represents a challenge due to the long-distance export markets. This requires fruit to be placed in cold storage for a long time, which can induce a physiological disorder known as chilling injury (CI). The main symptom of CI is mealiness which is perceived as non-juicy fruit by consumers. The purpose of this work was to identify and compare the metabolic and lipid profile between two siblings from a contrasting population for juice content, at harvest and after 30 days at 0°C. A total of 119 metabolites and 189 lipids were identified, which showed significant differences of abundance including mainly in amino acids, sugars and lipids. Our results indicate that some of the top metabolites and lipids could be used as biomarkers associated with mealiness at harvest and after cold storage.

Major depressive disorder (MDD) is a serious mental illness with a heavy social burden, but its underlying molecular mechanisms remain unclear. Mass spectrometry (MS)-based metabolomics is providing new insights into the heterogeneous pathophysiology, diagnosis, treatment, and prognosis of MDD by revealing multi-parametric biomarker signatures at the metabolite level. In this comprehensive review, recent developments of MS-based metabolomics in MDD research are summarized from the perspective of analytical platforms (liquid chromatography-MS, gas chromatography-MS, supercritical fluid chromatography-MS, etc.), strategies (untargeted, targeted, and pseudotargeted metabolomics), key metabolite changes (monoamine neurotransmitters, amino acids, lipids, etc.), and antidepressant treatments (both western and traditional Chinese medicines). Depression sub-phenotypes, comorbid depression, and multi-omics approaches are also highlighted to stimulate further advances in MS-based metabolomics in the field of MDD research.

Drought stress is a major abiotic factor affecting tomato production and fruit quality. However, the genes and metabolites associated with tomato responses to water deficiency and rehydration are poorly characterized. To identify the functional genes and key metabolic pathways underlying tomato responses to drought stress and recovery, drought-susceptible and drought-tolerant inbred lines underwent transcriptomic and metabolomic analyses. A total of 332 drought-responsive and 491 rehydration-responsive core genes were robustly differentially expressed in both genotypes. The drought-responsive and rehydration-responsive genes were mainly related to photosynthesis–antenna proteins, nitrogen metabolism, plant–pathogen interactions, and the MAPK signaling pathway. Various transcription factors, including homeobox-leucine zipper protein ATHB-12, NAC transcription factor 29, and heat stress transcription factor A-6b-like, may be vital for tomato responses to the water status. Moreover, 24,30-dihydroxy-12(13)-enolupinol, caffeoyl hawthorn acid, adenosine 5′-monophosphate, and guanosine were the key metabolites identified in both genotypes under drought and recovery conditions. The combined transcriptomic and metabolomic analysis highlighted the importance of 38 genes involved in metabolic pathways, biosynthesis of secondary metabolites, biosynthesis of amino acids, and ABC transporters for tomato responses to water stress. Our results provide valuable clues regarding the molecular basis of drought tolerance and rehydration. The data presented herein may be relevant for genetically improving tomato to enhance drought tolerance.

To understand the molecular mechanism underlying yellowing in pineapples during ripening, coupled with alterations in fruit quality, comprehensive metabolome and transcriptome investigations were carried out. These investigations were conducted using the pulp samples collected at three distinct stages of maturity: young fruit (YF), mature fruit (MF), and fully mature fruit (FMF). This study revealed a noteworthy increase in the levels of total phenols and flavones, coupled with a concurrent decline in lignin and total acid content, as the fruit transitioned from YF to FMF. Furthermore, the analysis yielded 167 differentially accumulated metabolites (DAMs) and 2194 differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes enrichment analysis based on DAMs and DEGs revealed that the biosynthesis of plant secondary metabolites, particularly the flavonol, flavonoid, and phenypropanoid pathways, plays a pivotal role in fruit yellowing. Additionally, a comprehensive regulatory network encompassing genes that contribute to metabolisms of flavones, flavonols, lignin, and organic acids was proposed. This network sheds light on the intricate processes that underlies fruit yellowing and quality alterations. These findings enhance our understanding of the regulatory pathways governing pineapple ripening and offer valuable scientific insight into the molecular breeding of pineapples.

Mulberry leaves are a classic herb commonly used in traditional Chinese medicine, and experience since ancient times has shown that leaves collected after frost have better medicinal properties. However, the characteristics of the changes of critical metabolic components in mulberry leaves, especially Morus nigra L., are still unknown. To further study the influence of harvesting time on the dynamic changes of metabolites, especially DNJ compounds and flavonoids, in mulberry leaves after frost. We used metabolomics technology to select 100+ metabolites as indexes to reflect the dynamic changes of metabolites in mulberry leaves comprehensively. The results showed significant differences in the effects of defrosting on the accumulation of metabolites in the leaves of Morus nigra L. and Morus alba L. The content of DNJ in the leaves of Morus nigra L. showed a decreasing trend after the frost, while flavonoids reached the peak of the second frost. For Morus alba L, DNJ showed an increasing trend after frost, especially reaching its peak one day after the second frost. Flavonoids mainly peak in the week before the frost. In addition, by analyzing the influence of picking time on metabolite accumulation in two mulberry leaves, it was concluded that higher DNJ alkaloids and flavonoids would be obtained in mulberry leaves collected in the morning. This study also provides scientific guidance for the optimum harvesting time of mulberry leaves.

Metabolomics is a powerful set of methods that uses analytical techniques to identify and quantify metabolites in biological samples, providing a snapshot of the metabolic state of a biological system. In medicine, metabolomics can help diagnose diseases, reveal molecular basis of a disease, and monitor treatment responses, while in agriculture, it can improve crop yields and plant breeding. However, animal metabolomics faces several challenges due to the complexity and diversity of animal metabolomes, the lack of standardized protocols, and the difficulty in interpreting metabolomic data. The current dataset includes quantitative metabolomic profiles of eye lens tissues from 26 bird species (111 specimens) that can aid researchers in developing new experiments, mathematical models, and integrations with other omics data. The dataset includes raw 1H NMR spectra, protocols for sample preparation, and data preprocessing with the final table containing information on 89 reliably identified and quantified metabolites. The dataset is quantitative, making it relevant for supplementing with new specimens or comparison groups, followed by data mining and expected new interpretations. It was obtained from bird specimens collected in compliance with ethical standards and reveals potential differences in metabolic pathways due to phylogenetic difference or environmental exposure.

Untargeted metabolomics is a powerful tool for measuring and understanding complex biological chemistries. However, employment, bioinformatics and downstream analysis of mass spectrometry (MS) data can be daunting for inexperienced users. Numerous open-source and free-to-use data processing and analysis tools exist for various untargeted MS approaches, including liquid chro-matography (LC), but choosing the ‘correct’ pipeline isn’t straight-forward. This tutorial, in con-junction with a user-friendly online guide presents a workflow for connecting these tools to process, analyse and annotate various untargeted MS datasets. The workflow is intended to guide explor-atory analysis in order to inform decision-making regarding costly and time-consuming down-stream targeted MS approaches. We provide practical advice concerning experimental design, organisation of data and downstream analysis, and offer details on sharing and storing valuable MS data for posterity. The workflow is editable and modular, allowing flexibility for updated/ changing methodologies and increased clarity and detail as user participation becomes more common. Hence, the authors welcome contributions and improvements to the workflow via the online repository. We believe that this workflow will streamline and condense complex mass-spectrometry approaches into easier, more manageable, analyses thereby generating opportunities for researchers previously discouraged by inaccessible and overly complicated software.

Cynomorium songaricum is an important endangered plant with significant medicinal and edible values. However, the lack of resources and quality variation have limited the comprehensive developments and sustainable utilization of C. songaricum. Here, we evaluated chemical and genetic traits of C. songaricum from the highly suitable habitat regions simulated with species distribution models. The PCA and NJ tree analyses displayed intraspecific variation in C. songaricum, that could be divided into two ecotypes: ecotype I and ecotype II. Furthermore, the LC-MS/MS-based metabolomic was used to identify and analyze the metabolites of two ecotypes. The results indicated that a total of 589 compounds were detected, 236 of which were significantly different between the two ecotypes. Specifically, the relative content and the kind of flavonoids were more abundant in ecotype I, which were closely associated with the medicinal activities. In contrast, amino acids and organic acids were more enriched in ecotype II, which may provide better nutritional quality and unique flavor. In summary, our findings demonstrate the ecotype division and chemical diversity of C. songaricum in China from different geographical regions and provide a reference for the development of germplasm and directed plant breeding of endangered medicinal plants.

Copper toxicity has been a selective pressure on the sea-ice bacteria due to its widespread occur-rence in Antarctica. Here, with a combined biochemical and metabolomic approach, the Cu2+ ad-aptation mechanisms of Antarctic bacteria were analyzed. Heavy metal resistance pattern of Pb2+ > Cu2+ > Cd2+ > Hg2+ > Zn2+ was observed. Copper treatment did increase the activity of antioxidants and enzymes, maintaining cellular redox state balance and normal cell division and growth. Metabolomics analysis demonstrated that fatty acids, amino acids, and carbohydrates played dominant roles in copper stress adaptation. The results indicated that the adaptation mechanisms of strain O5 to copper stress included protein synthesis and repair, accumulation of organic per-meable substances, up-regulation of energy metabolism, and formation of fatty acids. This study increases the resistance mechanism understanding of Antarctic strains to heavy metals in extreme environments.

Hypertrophic cardiomyopathy (HCM) is a common inherited heart disorder complicated by left ventricle outflow tract (LVOT) obstruction, which can be treated with surgical myectomy. To date, no reliable biomarkers for LVOT obstruction exist. To determine whether metabolomic biomarkers for obstruction can be identified, we conducted metabolomic profiling on plasma samples of 18 HCM patients before and after undergoing surgical myectomy to measure changes in the plasma metabolome in the postoperative state. Plasma was collected approximately 4 weeks before surgery at the preoperative visit and approximately 3 months after the surgery at the postoperative visit. We found that 215 metabolites were altered in the postoperative state (p-value < 0.05). Identified metabolites that were significantly reduced post-myectomy included metabolites of heme, such as bilirubin, and phenylacetylglutamine, a biomarker of urea cycle disorders, which suggests that liver and kidney function are improved in the postoperative state. Markers of arginine metabolism such as homoarginine and dimethylarginine are also decreased in the postoperative state, suggestive of reduction in nitric oxide production, inflammation and heart failure after surgery. 3-hydroxybutyrate (BHBA) was also decreased, suggesting possible increased fatty acid utilization and a return to normal heart function. 12 of these metabolites were notably significant after adjusting for multiple comparisons (q-value < 0.05), including bilirubin, PFOS, PFOA, 3,5-dichloro-2,6-dihydroxybenzoic acid, 2-hydroxylaurate, trigonelline and 6 unidentified compounds, which support improved kidney and liver function and increased lean soft tissue mass. These findings suggest improved organ metabolic function after surgical relief of LVOT obstruction in HCM and further underscore the beneficial systemic effects of surgical myectomy.

Omics technologies, viz., genomics, transcriptomics, proteomics, metabolomics, and phenomics, are becoming an integral part of virtually every commercial cereal breeding program because they provide substantial dividends per unit time in both pre-breeding and breeding phases. Continuous advances in cereal-omics promise—in combination with time efficiency—the cost benefits. In this review, we provide a comprehensive overview of the established cereal-omics methods in five major cereals, viz., rice, sorghum, maize, barley, and bread wheat. We cover the evolution of technologies in each omics section independently and concentrate on their use to improve economically important agronomic as well as biotic and abiotic stress-related traits. Advancements in the (1) identification, mapping, and sequencing of molecular/structural variants, (2) high-density transcriptomics data to study gene expression patterns, (3) global and targeted proteome profiling to study protein structure and interaction, (4) metabolomic profiling to quantify organ level small-density metabolites and their composition, and (5) high-resolution high-throughput image-based phenomics approaches are surveyed in this review.

Vascular pathogens are the causal agents of main diseases threatening the health and growth of olive crops worldwide. The use of endophytic microorganisms represents a challenging and promising strategy for management of vascular diseases in olive. Although current research has been focused on analyzing the structure and diversity of the endophytic microbial communities inhabiting the olive xylem, the characterization of this ecological niche has been overlooked and to date remain unexplored, despite that the characterization of the xylem sap composition is essential to unravel the nutritional requirements of xylem-limited microorganisms. In this study, branches from plantlets and adult olive trees of cultivars ‘Picual’ and ‘Arbequina' were selected to characterize the chemical composition of olive xylem sap extracted using a Scholander pressure chamber. Metabolome and ionome analyses of xylem sap were performed by proton nuclear magnetic resonance (NMR) spectroscopy-based and by inductively coupled plasma with optical emission spectroscopy (ICP-OES), respectively. Olive xylem sap metabolites included a higher relative percentage of sugars (54.35%), followed by alcohols (28.85%), amino acids (8.01%), organic acids (7.68%) and osmolytes (1.12%). Within each of these groups, the main metabolites in the olive xylem sap were mannitol, ethanol, glutamine, acetate and trigonelline, whereas K and Cl- were the main element and inorganic anion, respectively. Metabolomic profile varied when comparing olive plant age and genotype. The levels of glucose, fructose, sucrose and mannitol, choline, B and PO43 were significantly higher in adult trees than in plantlets for both olive genotypes, whereas NO3- and Rb content showed the opposite behavior. On the other hand, levels of aspartate, phenylalanine and Na were significantly higher in ‘Picual’ than in ‘Arbequina’ whereas Fe showed the opposite behavior but only for adult trees. Non-supervised hierarchical clustering analysis separated xylem sap composition firstly according to the plant age and then by the olive cultivar. Supervised PLS-DA analysis revealed that B, ethanol, Fe, Fructose, glucose, mannitol, sucrose and Sr were the most significative compounds discriminating adult trees from plantlets, whereas asparagine, aspartate, glutamate and phenylalanine or aspartate, arginine, ethanol and Sr were the most contributory compounds in the discrimination of both olive genotypes for adult trees or plantlets, respectively. Knowledge of the chemical composition of xylem sap will lead to a better understanding of the complex nutritional requirements of olive xylem-inhabiting microorganisms, including its vascular pathogens, and would allow the design of artificial growing media to improve culturing the olive microbiome.

Novel sensing technologies for liquid biopsies offer a promising prospect for the early detection of metabolic conditions through -omics techniques. Indeed, high-field NMR facilities are routinely used for metabolomics investigations on a range of biofluids in order to rapidly recognize unusual metabolic patterns in patients suffering from a range of diseases. However, these techniques are restricted by the prohibitively large size and cost of such facilities, suggesting a possible role for smaller, low-field NMR instruments in biofluid analysis. Herein we describe selected biomolecule validation on a low-field benchtop NMR spectrometer (60 MHz), and present an associated protocol for the analysis of biofluids on compact NMR instruments. We successfully detect common markers of diabetic control at low-to-medium concentrations through optimized experiments, including glucose (≤ 2.6 mmol./L) and acetone (25 μmol./L), and additionally in readily-accessible biofluids. We present a combined protocol for the analysis of these biofluids with low-field NMR spectrometers for metabolomics, and offer a perspective on the future of this technique appealing to point-of-care applications.

We previously reported how the loss of CHIP expression (Carboxyl terminus of Hsc70-Interacting Protein) during pressure overload resulted in robust cardiac dysfunction, accompanied by a failure to maintain ATP levels in the face of increased energy demand. In this study, we analyzed the cardiac metabolome after seven days of pressure overload and found an increase in long- and medium-chain fatty acid metabolites in wild-type hearts, a response that was attenuated in mice that lack expression of CHIP (CHIP^-/-). These findings suggest that CHIP may play an essential role in regulating oxidative metabolism, pathways that are regulated in part by the nuclear receptor PPARα (Peroxisome Proliferator-Activated Receptor alpha). Next, we challenged CHIP^-/- mice with the PPARα agonist, fenofibrate. Surprisingly, treating CHIP^-/- mice with fenofibrate for five weeks under non-pressure overload conditions resulted in a loss of skeletal muscle mass and a marked increase in cardiac fibrosis, accompanied by a decrease in cardiac function. Isolated CHIP^-/- cardiac fibroblasts treated with fenofibrate did not increase synthesis of collagen or TGFβ, suggesting that the fibrosis observed in CHIP^-/- hearts likely depends on signaling from other cell types or circulating factors. In conclusion, in the absence of functional CHIP expression, fenofibrate results in unexpected cardiac pathologies. These findings are particularly relevant to patients harboring loss-of-function mutations in CHIP and are consistent with a prominent role for CHIP in regulating cardiac metabolism.

Hypsizygus marmoreus has become one of the most popular edible mushrooms due to its high nu-tritional and economic value. Previous researchers found that Serratia odorifera could promote the growth of H. marmoreus by producing and secreting some of its inducers. However, the specific mechanism of action was still unclear. In this study, we found that exogenous addition of sterile fermentation filtrate (HZSO-1), quorum sensing (QS signaling molecules, 3-oxo-C6-HSL, cy-clo(Pro-Leu), and cyclo(Tyr-Leu) could significantly promote the growth of H. marmoreus, increase the number of clamp junctions, and the diameter of mycelium (P < 0.05). In addition, non-targeted metabolomic analysis has revealed that 706 metabolites were detected in the treated group. Of these, 307 metabolites were significantly different (P < 0.05). Compared with the control, 54 and 86 metabolites were significantly increased and decreased in the HZSO-1 group, respec-tively (P < 0.05). We speculated that the sterile fermentation filtrate of S. odorifera could mediate the carbohydrate and amino acid metabolism of H. marmoreus by influencing the pentose phosphate pathway (PPP) to increase the energy supply for the growth and development of the mycelium. The above results will further reveal the growth-promoting mechanism of S. odorifera on H. mar-moreus.

Ionizing radiation exposure is known to induce molecular and cellular injury, inflicting a cascade of potentially catastrophic events leading to tissue and organ damage. Metabolomic analysis allows for the identification and quantification of small molecules downstream of genomic changes induced by radiation exposure. We aimed to characterize metabolomic changes that underscore the prefinal stage of lethally irradiated rhesus nonhuman primates (NHPs). Peripheral blood was drawn at baseline, post-exposure as well as at the preterminal stage of NHPs (immediately prior to death in moribund NHPs), which did not survive exposure with 7.2 Gy total-body radiation (LD70/60). Herein, we analyzed global metabolomic changes using ultra-performance liquid chromatography (UPLC) quadrupole time-of-flight mass spectrometry (QTOF-MS) in plasma samples of NHPs collected at various timepoints in relation to irradiation. The overall goal was to identify metabolic shifts present immediately prior to death. Our findings, for the first time, show that radiation induced significant time dependent metabolic perturbations when compared to pre-irradiation samples, particularly in the glycerophospholipid metabolism and steroid hormone biosynthesis and metabolism pathways. These findings provide valuable insights for identifying biomarkers for lethality, which may be helpful for triage during a mass casualty scenario.

Over the last several decades, China has continuously introduced Duroc boars and used them as breeding boars. Although this crossbreeding method has increased pork production, it has affected pork quality. Nowadays, one of the primary goals of industrial breeding and production systems is to enhance the quality of meat. This research adds to our understanding of the molecular mechanisms that control the quality of pork and may be used as a guide for future efforts to enhance meat quality. We investigated the genetic mechanisms of cross-breeding for meat quality improvement by combining transcriptome and metabolome analysis, using Chinese native Jiaxing black (JXB) pigs and crossbred Duroc × Duroc × Berkshire × JXB (DDBJ) pigs. In the longissimus Dorsi muscle, the content of inosinic acid, polyunsaturated fatty acid, and amino acids was considerably higher in JXB pigs in contrast with that of DDBJ pigs, whereas DDBJ pigs have remarkably greater levels of polyunsaturated fatty acids than JXB pigs. Differentially expressed genes (DEGs) and differential metabolites were identified using transcriptomic and metabolomic KEGG enrichment analyses. Differential metabolites mainly include amino acids, fatty acids, phospholipids. In addition, we found several DEGs that may explain differences in meat quality between the two pig types, including genes associated with lipid metabolism (e.g., DGKA, LIPG, and LPINI), fatty acid metabolism (e.g., ELOVL5, ELOVL4, and ACAT2), and amino acid metabolism (e.g., SLC7A2, SLC7A4). Combined with the DEGS-enriched signaling pathways, the regulatory mechanisms related to amino acids, fatty acids, and phospholipids were mapped. The abundant metabolic pathways and DEGs may provide insight into the specific molecular mechanism that regulates meat quality. Optimizing the composition of fatty acids, phospholipids, amino acids, and other compounds in pork is conducive to improving meat quality. Overall, these findings will give useful information and further groundwork for enhancing the meat quality that may be achieved via hybrid breeding.

Background: This study aimed to assess the relationship between age-related changes in Neuro-filament Light Chain (NFL), a marker of neuronal function, and various factors including muscle function, body composition, and metabolomic markers. Methods: The study included 40 partici-pants, aged 20 to 85 years. NFL levels were measured, and muscle function, body composition, and metabolomic markers were assessed. Results: NFL levels increased significantly with age, particularly in men. Negative correlations were found between NFL levels and measures of mus-cle function, such as grip strength, walking speed, and chair test performance, indicating a decline in muscle performance with increasing NFL. These associations were more pronounced in men. NFL levels also negatively correlated with muscle quality in men, as measured by 50 kHz phase angle. In terms of body composition, NFL was positively correlated with markers of fat mass and negatively correlated with markers of muscle mass, predominantly in men. Metabolomic analy-sis revealed significant associations between NFL levels and specific metabolites, with gen-der-dependent relationships observed. Conclusions: This study provides insights into the rela-tionship between circulating serum NFL, muscle function, and aging. The findings highlight gen-der differences and contribute to our understanding of age-related changes in neuronal function and their impact on muscle health.

Metabolomics is an advanced technology, still under development, with multiple research applications, especially in the field of health. Individual metabolic profiles, the functionality of the body, as well as its interaction with the environment can be established using this technology. The body's response to various external factors, including the food consumed and the nutrients it contains, has increased researchers' interest in nutrimetabolomics. Establishing correlations between diet and the occurrence of various diseases or even the development of personalized nutrition plans, could contribute to advances in precision medicine. The interdependence between humans, animals and the environment are of particular importance today, with the dramatic emergence and spread of zoonotic diseases, food, water and soil contamination, and the degradation of resources and habitats. All these events have led to an increase of risk factors for functional diseases, burdening global health. Thus, this study aimed to highlight the importance of metabolomics, in particular of nutrimetabolomics, as a technical solution for a holistic, collaborative, and precise approach for the advancement of the One Health strategy.

Our understanding of the long-term consequences of chronic ionising radiation for living organisms remains scarce. Modern molecular biology techniques are helpful tools for researching pollutant effects on biota. To reveal the molecular phenotype of plants growing under chronic radiation exposure, we sampled Vicia cracca L. plants in the Chernobyl Exclusion Zone and in areas with normal radiation backgrounds. We performed a detailed analysis of soil and gene expression patterns, and made coordinated multi-omics analyses of plant samples, including transcriptomics, proteomics, and metabolomics. Chronic exposure to ionising radiation induced complex and multidirectional changes, including significant alterations in the metabolism and gene expression patterns of irradiated plants. We revealed profound changes in carbon metabolism, nitrogen reallocation, and photosynthesis. These plants were characterised by increased DNA damage, redox imbalance, and stress response reactions. The upregulation of histones, chaperones, peroxidases, and secondary metabolism were noted.

;Yams are economic and medicinal crops with a long growth cycle, spanning between 9-11 months due to the prolonged tuber dormancy. Tuber dormancy has constituted a major constraint in yam production and genetic improvement. In this study, we performed non-targeted comparative metabolomic profiling of tubers of two white yam genotypes, (Obiaoturugo and TDr1100873), to identify metabolites and associated pathways that regulate yam tuber dormancy using gas chromatography-mass spectrometry (GC-MS). Yam tubers were sampled between 42 days after physiological maturity (DAPM) till tuber sprouting. The sampling points include 42-DAPM, 56-DAPM, 87DAPM, 101-DAPM, 115-DAPM, and 143-DAPM. A total of 949 metabolites were annotated, 559 in TDr1100873 and 390 in Obiaoturugo. 39 differentially accumulated metabolites (DAMs) were identified across the studied tuber dormancy stages in the two genotypes. 27 DAMs were conserved between the two genotypes, whereas, 5 DAMs were unique in the tubers of TDr1100873 and 7 DAMs were in the tubers of Obiaoturugo. The differentially accumulated metabolites (DAMs) spread across 14 major functional chemical groups. Amines and biogenic polyamines, amino acids and derivatives, Alcohols, flavonoids, alkaloids, phenols, esters, coumarins and phytohormone positively regulated yam tuber dormancy induction and maintenance, whereas, fatty acids, lipids, nucleotides, carboxylic acids, sugars, terpenoids, benzoquinones, and benzene derivatives positively regulated dormancy breaking and sprouting in tubers of both yam genotypes. Metabolite set enrichment analysis (MSEA) revealed that 12 metabolisms were significantly enriched during yam tuber dormancy stages. Metabolic pathway topology analysis further revealed that six metabolic pathways (linoleic acid metabolic pathway, phenylalanine metabolic pathway, galactose metabolic pathway, starch and sucrose metabolic pathway, alanine-aspartate-glutamine metabolic pathways and purine metabolic pathway) exerted significant impact on yam tuber dormancy regulation. This result provides vital insights into molecular mechanisms regulating yam tuber dormancy.

Pretreatment with non-convulsive dose of methionine sulfoximine (MSO) attenuated lithi-um-pilocarpine-induced (Li-Pilo) seizures in young rats [1]. We hypothesized that the effect of MSO results from a) glutamine synthetase block-mediated inhibition of conversion of Glu/Gln precursors to neurotransmitter Glu, and/or from b) altered synaptic Glu release. Pilo was admin-istered 60 min prior to sacrifice, MSO at 75 mg/kg, i.p., 2.5 h earlier. [1,2-13C]acetate and [U-13C]glucose were i.p.-injected either together with Pilo (onset) or 15 min before sacrifice (final phase). Their conversion to Glu and Gln in hippocampus and entorhinal cortex was followed us-ing [13C] gas chromatography-mass spectrometry. Release of in vitro loaded [3H]D-Asp from ex vi-vo brain slices was measured in continuously collected superfusates. Protein and mRNA expres-sion were measured by Western Blot and real-time PCR techniques, respectively. At no time point nor brain region did MSO modify incorporation of [13C] to Glu or Gln in Pilo-treated rats. MSO pretreatment decreased by ~37% high potassium-induced [3H]D-Asp release and reduced by ~50% the synaptic vesicular Glu transporter VGLUT1 protein, but not mRNA content in the hippo-campus. The results indicate that MSO at non-convulsive dose mitigates the initial Pilo-induced seizures by interfering with synaptic Glu-release but not with neurotransmitter Glu recycling.

Direct mass spectrometry-based metabolomics has been widely employed in the last years to characterize metabolic alterations underlying to Alzheimer’s disease development and progression. This high-throughput approach presents a great potential for fast and simultaneous fingerprinting of a vast number of metabolites, which can be applied to multiple biological samples such as serum/plasma, urine, cerebrospinal fluid and tissues. In this review article we present the main advantages and drawbacks of metabolomics based on direct mass spectrometry compared with conventional analytical techniques, and provide a comprehensive revision of the literature on the application of these tools in Alzheimer’s disease research.

Background: Diabetes is among the most prevalent diseases worldwide, of all the affected individuals a significant proportion of the population remains undiagnosed because of a lack of specific symptoms early in this disorder and inadequate diagnostics. Diabetes and its associated sequela, i.e., comorbidity are associated with microvascular and macrovascular complications. As diabetes is characterized by an altered metabolism of key metabolites and regulatory pathways. Metabolic phenotyping can provide us with a better understanding of the unique set of regulatory perturbations that predispose to diabetes and its associated comorbidities. Methodology: The present study utilizes the analytical platform NMR spectroscopy coupled with Random Forest statistical analysis to identify the discriminatory metabolites of diabetes (DB) and diabetes-related comorbidity (DC) along with the healthy control (HC) subjects. A combined and pairwise analysis was performed, between the serum samples of HC (n=50), and DB (n=38), and DC (n=35) individuals to identify the discriminatory metabolites responsible for class separation. The perturbed metabolites were further rigorously validated using t-test, AUROC analysis to examine the statistical significance of the identified metabolites. Results: The DB and DC patients were well discriminated from HC. However, 15 metabolites were found to be significantly perturbed in DC patients compared to DB, the identified panel of metabolites are TCA cycle (succinate, citrate), methylamine metabolism (trimethylamine, methylamine, betaine), -intermediates; energy metabolites (glucose, lactate, pyruvate); and amino acids (valine, arginine, glutamate, methionine, proline and threonine). The metabolites were further used to identify the perturbed metabolic pathway and correlation of metabolites in DC patients. Conclusion: The 1H NMR metabolomics may prove a promising technique to differentiate and predict diabetes and its comorbidities on their onset or progression by determining the altered levels of the metabolites in serum.

Metabolomic analysis of biological fluids and tissues has become an increasingly routine tool in the biological toolbox. However, challenges remain to be overcome, including developing strategies to maximise coverage of the metabolome without requiring large sample volumes. Here we describe a multimodal strategy that combines data using both LC-MS and GC-MS from a unique vial with a sample of plasma (20µl) or a sample of brain tissue (3mg). Using a split phase extraction the non-aqueous phase was analyzed by reversed phase (RP) LC-MS, whilst the aqueous phase was analyzed using hydrophilic liquid interaction chromatography (HILIC)LC-MS, with both phases also analysed using GC-MS after derivatization of the extract. Analytical performance was assessed in 7 rat cerebellum samples and a pilot study of 40 plasma samples (20 vs. 20: AD vs. healthy controls). The method, which uses four hours of instrument time, measured 20,707 metabolite features in brain samples and 17,266 in plasma samples, from those 44.1% features displayed CV’s below 15% and 75.2% below 30%. The method has potential to resolve subtle biological differences and to correlate metabolite composition directly to clinical outcomes including MMSE, age and ADCS-ADL. This method can acquire in the order of 20K metabolic features when low volumes are available.

Embryo quality evaluation during in vitro development is vital for the success of assisted reproductive technologies (ART). However, the subjective morphological assessment by embryologists may result in inconsistencies that affect the selection of the best embryo for transfer. To provide a more comprehensive evaluation of embryo quality, we performed the integration of embryo metabolomics with standardized morphokinetic classification. The culture medium of 55 embryos (from 21 couples undergoing ICSI) was collected at two timepoints (day 3 and 5). Samples were split into Good (n=29), Lagging (n=19) and Bad (n=10) according to embryo morphokinetic evaluation. Embryo metabolic performance was assessed by 1H-NMR, monitoring the variation of specific metabolites (pyruvate, lactate, alanine, glutamine, acetate, formate). Adjusted metabolite differentials were observed during the first three days of culture and found to be discriminative of embryo quality at the end of day 5. Pyruvate, alanine, glutamine, and acetate were major contributors to this discrimination. Good and Lagging embryos were found to export and accumulate pyruvate and glutamine in the 3 first days of culture, while Bad embryos consumed them. This suggests that Bad embryos have a less active metabolism than Good and Lagging embryos and these two metabolites as putative biomarkers for embryo quality. This study provides a more comprehensive evaluation of embryo quality and can lead to improvements in ART by enabling the selection of the best embryos. By combining morphological assessment and metabolomics, the selection of high-quality embryos with the potential to result in successful pregnancies may become more accurate and consistent.

(1) Background: Inflammatory bowel diseases (IBD) involve complex interactions between genetic factors, aberrant immune activation, and gut microbial dysbiosis. While metabolomic studies have focused on feces and serum, fewer investigations have examined the intestinal mucosa despite its crucial role in metabolite absorption and transport. The current study aimed to identify novel mucosal metabolic pathways that are altered during chronic colitis and to determine microbial contributions to such changes. (2) Methods: The chronic Dextran sulfate sodium (DSS) colitis was induced for five weeks in 7-9-week-old wild-type C57BL/6J male mice followed by microbial profiling with targeted 16srRNA sequencing service. Mucosal metabolite measurements were performed by Metabolon (Morrisville, NC). The data were analyzed using the bioinformatic tools Pathview, MetOrigin, and Metaboanalyst. (3) Results: Our novel findings demonstrated increases in several host- and mi-crobe-derived purine, pyrimidine, endocannabinoid, and ceramide metabolites in colitis. Origin analysis revealed microbial-related tryptophan metabolites kynurenine, anthranilate, 5-hydroxyindoleacetate, and C-glycosyltryptophan were significantly increased in colon mucosa during chronic inflammation and strongly correlated with disease activity. (4) Conclusions: These findings offer new insights into the pathophysiology of IBD and provide novel potential targets for microbial-based therapeutics.

High blood cholesterol levels are one of the main risks for atherosclerotic disease. A purified aqueous extract of Fucus vesiculosus, characterized as rich in phlorotannins and peptides, was described as having the capacity to inhibit cholesterol biosynthesis and intestinal absorption. In this work, the effect of this extract on intestinal cells metabolites and proteins was analysed, aiming to expand the knowledge about its mode of action targeting cholesterol metabolism, in particular exogenous cholesterol absorption and transport. Caco-2 cells differentiated into enterocytes were exposed to the purified aqueous extract of F. vesiculosus and analysed by undirected metabolomics and proteomics. The results of the metabolomic analysis showed only statistically significant differences in glutathione content of the cells exposed to the extract relatively to the control cells, with a decreased glutathione expression in exposed cells. The proteomic analysis showed an increased expression for cells exposed to the extract of NPC1, an important protein known to be involved in cholesterol transport. To extent of our knowledge this is the first study using untargeted metabolomics and proteomic analysis to study the effect of F. vesiculosus on differentiated Caco-2 cells, which aims to provide some insight about the molecular mechanism of extract compounds on intestinal cells.

Energy metabolism, including alterations in energy intake and expenditure, is closely related to aging and longevity. Metabolomics studies have recently unraveled changes in metabolite composition in plasma and tissues during aging and have provided critical information to elucidate the molecular basis of aging process. However, the metabolic changes in tissues responsible for food intake and lipid storage have remained unexplored. In this study, we aimed to investigate aging-related metabolic alterations in these tissues. To fill this gap, we employed NMR-based metabolomics in several tissues, including different parts of the intestine (duodenum, jejunum, ileum) and brown/white adipose tissues (BAT, WAT) of young (9-10 weeks) and old (96-104 weeks) wild-type (mixed genetic background of 129/J and C57BL/6) mice. We further included plasma and skeletal muscle of the same mice to verify previous results. Strikingly, we found that duodenum, jejunum, ileum, and WAT do not metabolically age. In contrast, plasma, skeletal muscle, and BAT show a strong metabolic aging phenotype. Overall, we provide first insights into the metabolic changes of tissues essential for nutrient uptake and lipid storage and have identified biomarkers for metabolites that could be further explored to study the molecular mechanisms of aging.

To allow for a broad survey of subtle metabolic shifts in wine caused by rootstock and irrigation, an integrated metabolomics-based workflow followed by quantitation was developed. This workflow was particularly useful when applied to a poorly studied variety cv. Chambourcin. Allowing volatile metabolites that otherwise may have been missed with a targeted analysis to be included, this approach allowed deeper modeling of treatment differences which then could be used to identify important compounds. Wines produced on a per vine basis, over two years, were analyzed using SPME-GC-MS/MS. From the 382 and 221 features that differed significantly among rootstocks in 2017 and 2018 respectively, we tentatively identified 94 compounds by library search and retention index, with 22 confirmed and quantified using authentic standards. Own-rooted Chambourcin differed from other root-systems for multiple volatile compounds with fewer dif-ferences among grafted vines. For example, the average concentration of β-Damascenone present in own-rooted vines (9.49 µg/L) was significantly lower in other rootstocks (8.59 µg/L), whereas mean Linalool was significantly higher in 1103P rootstock compared to own-rooted. β-Damascenone was higher in regulated deficit irrigation (RDI) than other treatments. The workflow outlined not only was shown to be useful for scientific investigation, but also in creating a protocol for analysis that would ensure differences of interest to industry are not missed.

Typhoid fever is a major public health burden which causes substantial global morbidity and mortality due to lack of decisive diagnostic protocols. The capacity of commonly use diagnostic test to validate the absence of typhoid fever is controversial. This study explores to evaluate new techniques for typhoid diagnosis and proposed a harmonised suitable standardized composite reference to be adopted. Published peer-reviewed articles indexed in PubMed, MEDLINE and Google scholar were reviewed for hospital-based studies. This study reveals new typhoid diagnostic techniques such as proteomics, serology, Rapid Diagnostic tests (RDTs), transcriptomics, genomics, and metabolomics. 34.4% of the studies use prospective study design. The study result establishes that, Widal test has a moderate diagnostic accuracy with average percentage sensitivity (52.9%), specificity (54%), positive predictive value (PPV) (56.8%) as well as negative predictive value (NPV) (55.6%) when compared with 29.4%, 28%, 29.5%, and 27.8% of Typhidot respectively. The findings showed a statistically significant difference on the sensitivity between Widal and Typhidot t (40) = 2.639, p = 0.012 at p<0.05 using independent sample t-test. When there is no perfect reference standard that has an optimal diagnostic accuracy, the need for a harmonised suitable standardized composite reference is essential. Hence, this study recommends that, peripheral blood culture with established sensitivity of 60% and Widal test with average sensitivity of 52.9% be adopted as a consensus composite reference standard for typhoid fever diagnosis in other to improve confidence in prevalence estimates.

In the interest of developing more effective and safer anti-Tuberculosis treatment, we aimed for a better understanding of the antimycobacterial action of ciprofloxacin against Mycobacterium tuberculosis (Mtb). We used GCxGC-TOF-MS and well described metabolomics statistical approaches, to investigate and compare the metabolic profiles of Mtb in the presence and absence of the drug. The metabolites that best describe the differences between the compared groups were identified as markers characterizing the changes induced by ciprofloxacin. Malic acid was ranked as the most significantly altered metabolite marker induced by ciprofloxacin, indicative of an inhibition of the tricarboxylic acid (TCA) and glyoxylate cycle of Mtb. The altered fatty acid, myo-inositol and triacylglycerol metabolism seen in this group, supports the previous observations of ciprofloxacin action on the Mtb cell wall. Furthermore, the altered pentose phosphate intermediates, glycerol metabolism markers, glucose accumulation, and the reduction in the glucogenic amino acids specifically, indicates a flux towards DNA (as well as cell wall) repair, also supporting previous findings of DNA damage caused by ciprofloxacin. This study further provides insights useful for designing network whole-system strategies for the identification of possible modes of actions of various drugs and possibly adaptations by Mtb resulting in resistance.

Rocas Atoll is a unique environment in the Equatorial Atlantic Ocean, hosting a large number of endemic species and studies on the chemical diversity emerging from this biota are rather scarce. Therefore, the present work aims to assess the metabolomic diversity and pharmacological potential of the microbiota from Rocas Atoll. A total of 76 bacteria were isolated and cultured in liquid culture media to obtain crude extracts. About one third (34%) of these extracts were considered cytotoxic against human colon adenocarcinoma HCT-116 cell line. 16S rRNA gene sequencing analysis revealed that the bacteria producing cytotoxic extracts are mainly from the Actinobacteria phylum, including Streptomyces, Salinispora, Nocardiopsis and Brevibacterium genera, and in a smaller proportion from Firmicutes phylum (Bacillus). The search in the GNPS spectral library unveiled a high chemodiversity being produced by these bacteria, including rifamycins, antimycins, desferrioxamines, ferrioxamines, surfactins, surugamides, staurosporine and saliniketals, along with several unidentified compounds. Using an original approach, molecular network successfully highlighted groups of compounds responsible for the cytotoxicity of crude extracts. DEREPLICATOR+, a recently developed in silico tool (GNPS), allowed the identification of derivatives of the macrolide novonestimycin, as the cytotoxic compounds into the extracts produced by Streptomyces BRB-298 and BRB-302. Overall, these results highlighted the pharmacological potential of bacteria from this singular Atoll.

Rice (Oryza sativa L.) processing yields ~60 million metric tons of bran annually. Rice genes producing bran metabolites of nutritional and human health importance were assessed across 17 diverse cultivars from seven countries using non-targeted metabolomics and resulted in 378-430 metabolites. Gambiaka cultivar had the highest number and Njavara had the lowest number of metabolites. The 71 rice bran compounds of significant variation by cultivar included 21 amino acids, seven carbohydrates, two metabolites from cofactors and vitamins, 33 lipids, six nucleotides, and two secondary metabolites. Tryptophan, -ketoglutarate, γ-tocopherol/β-tocopherol and γ-tocotrienol are example bran metabolites with extensive cultivar variation and genetic information. 34 rice bran components that varied between cultivars linked to 535 putative biosynthetic genes using to the OryzaCyc 4.0, Plant Metabolic Network database. Rice genes responsible for bran composition with animal and human health importance is available for rice breeding programs to utilize in crop improvement.

Model animals are employed in experiments as substitutes for human tissues and fluids, particularly when accessing particular human samples (such as cerebrospinal fluid, brain, ocular tissues, etc.) poses significant challenges or is ethically constrained. Nonhuman primates are frequently regarded as superior animal models for investigating human ophthalmological diseases. However, despite this recognition, the metabolomic composition of ocular tissues in non-human primates remains predominantly unexplored. In this work, we present a dataset on metabolite concentrations in serum and ocular tissues, including aqueous humor (AH), vitreous humor (VH), and lens, in two Macaque species: crab-eating macaque (Macaca fascicularis) and rhesus macaque (Macaca mulatta). A total of 99 compounds were quantified in 45 samples, shedding light on the previously unknown metabolomic profiles of primate eye tissues.

China Xihu Longjing tea famous for its good flavor and quality. However, the related metabolites information except flavonoids is largely deficient. Different processing methods of China Xihu Longjing tea fixing both by machine at first and second step(A1), first step by machine and second step by hand(A2), first step by hand and second step by machine(A3), both by hand at first and second step (A4) were compared using a UHPLC-QE-MS-based metabolomics approach. Liquid chromatography-mass spectrometry was used to analyze the metabolic profiles of the processed samples. A total of 490 metabolites (3 alkaloids, 3 anthracenes, 15 benzene and substituted derivatives, 2 benzopyrans, 13 coumarins and derivatives, 128 flavonoids, 4 furanoid lignans, 16 glycosides and derivatives, 5 indoles and derivatives, 18 isocoumarins and derivatives, 4 chalcones and dihydrochalcones, 4 naphthopyrans, 3 nucleosides, 78 organic acids and derivatives, 55 organooxygen compounds, 5 phenols, 109 prenol lipids, 3 saccharolipids, 3 steroids and steroid derivatives, 17 tannins) were identified. The different metabolism profiles were distinguished using PCA and OPLS-DA. There were differences in the types and contents of metabolites, especially flavonoids, furanoid lignans, glycosides and derivatives, organic acids and derivatives and organooxygen compounds. There was a positive correlation between flavonoid metabolism and amino acid metabolism. However, there was a negative correlation between flavonoid metabolism and amino acid metabolism, which had the same trend as prenol lipids metabolism, tannin.This study provides new valuable information for regarding differences in the metabolite profile of China Xihu Longjing tea processed based on machine fixing and manual fixing methods.

The advancement of mass spectrometry technologies has revolutionised plant metabolomics research by enabling the acquisition of raw metabolomics data. However, the identification, analysis, and visualisation of these data require specialised tools. Existing solutions lack a dedicated plant-specific metabolite database and pose usability challenges. To address these limitations, we developed PlantMetSuite, a web-based tool for comprehensive metabolomics analysis and visualisation. PlantMetSuite encompasses interactive bioinformatics tools and databases specifically tailored for plant metabolomics data, facilitating upstream-to-downstream analysis in metabolomics and supporting integrative multi-omics investigations. PlantMetSuite can be accessed directly through a user's browser without the need for installation or programming skills. The tool is freely available at https://plantmetsuite.verygenome.com/ and will undergo regular updates and expansions to incorporate additional libraries and newly published metabolomics analysis methods. The tool's significance lies in empowering researchers with an accessible and customisable platform for unlocking plant metabolomics insights.

Plasma-activated water (PAW) is an emerging and promising green technology in the agriculture sector during recent years. The aim of this study was to examine the influence of the spraying of PAW and amino acid fertilizer concentrations on the physiological, biochemical and phytochemical characteristics of German chamomile varieties under field conditions. Method: The experiment was performed during 2020–2021 as a factorial using a randomized complete block design with three replications, in an arid and warm region. The factors contained five fertilizer levels (0 (control), 1, 2, 3 ml·L−1 amino acid and PAW) and three German chamomile cultivars Bona, Bodegold, Lianka). Physiological, biochemical and phytochemical traits such as plant height, fresh and dried flower weight, chlorophyll a, b, carotenoids, CHN elements, C:N ratio, total protein, amino acid profile, essential oil yield, apigenin content and major secondary metabolites were examined. Results: The ANOVA indicated that the impact of the cultivar and fertilizer was significant on all physiological, biochemical and phytochemical studied parameters. The amino acid fertilizer and PAW enhanced physiological features, hydrogen, C:N ratio, essential oil yield, apigenin content and main phytochemical compositions like chamazulene and α-bisabolol, but it had no incremental effect on the carbon, nitrogen, and total protein percentage. Conclusion: Findings revealed that the application of foliar amino acid fertilizer and PAW treatments improves physiological, biochemical and phytochemical parameters in German chamomile cultivars under field conditions.

Turmeric, Curcuma longa L., is a type of medicinal plant characterized by its perennial nature and rhizomatous growth. It is a member of the Zingiberaceae family and is distributed across the world’s tropical and subtropical climates, especially in South Asia. Its rhizomes are highly valued for food supplements, spices, flavoring agents, and yellow dye in South Asia since ancient times. It exhibits a diverse array of therapeutic qualities that encompass its ability to combat diabetes, reduce inflammation, act as an antioxidant, exhibit anticancer properties, and promote anti-aging effects. In this study, organic extracts of C. longa rhizomes were subjected to HPLC separation followed by mass spectrometry analysis. The Global Natural Product Social Molecular Networking (GNPS) approach was utilized for the first time in this ethnobotanically important species to conduct an in-depth analysis of its metabolomes based on their fragments. A total of 30 metabolites including 16 diarylheptanoids, 1 diarylpentanoid, 3 bisabolocurcumin ethers, 4 sesquiterpenoids, 4 cinnamic acid derivatives, and 2 fatty acid derivatives were identified. Among 16 diarylheptanoids identified in this study, five of them are reported for the first time in this species.

The growing worldwide cancer incidence, coupled to the increasing occurrence of multidrug cancer resistance, requires a continuous effort towards the identification of new leads for cancer management. In this work, two C-scorpionate complexes, [FeCl2(κ3-Tpm)] (1) and [Co(κ3-TpmOH)2] (2), (Tpm = hydrotris(pyrazol-1-yl)methane and TpmOH = 2,2,2-tris(pyrazol-1-yl)ethanol), are studied as potential scaffolds for future anti-cancer drug development. Their cytotoxicity and cell migration inhibitory activity are analyzed, and an untargeted metabolomics approach is em-ployed to elucidate the biological processes significantly affected by these two complexes, using two tumoral cell lines (B16 and HCT116) and a non-tumoral cell line (HaCaT). While [FeCl2(κ3-Tpm)] did not display a significant cytotoxicity, [Co(κ3-TpmOH)2] was particularly cy-totoxic against the B16 cell line. While [Co(κ3-TpmOH)2] significantly inhibited cell migration in all tested cell lines, [FeCl2(κ3-Tpm)] displayed a mixed activity. From a metabolomics perspective, exposure to [FeCl2(κ3-Tpm)] is associated with changes in various metabolic pathways involving tyrosine, where iron-dependent enzymes are particularly relevant. On the other hand, [Co(κ3-TpmOH)2] is associated with dysregulation of cell adhesion and membrane structural pathways, suggesting its antiproliferative and anti-migration properties can be due to changes in the overall cellular adhesion mechanisms.

Lactobacillus plantarum has been observed to play a crucial role in shaping the sensory properties of chili sauce. However, the specific taste-active metabolites responsible for the desirable flavor profile of chili sauce remain inadequately characterized. This study employed a combination of metabolomics and web-based computational tools analysis to investigate the dynamic changes in taste-active metabolites during chili sauce fermentation. Initially, metabolites were rapidly annotated using a feature-based molecular network, leading to the tentative annotation of 206 metabolites, of which a significant proportion had not been previously reported. Subsequently, the VirtualTaste tool identified dihydrosphingosine, lactic acid, isoleucine, phytosphingosine, and gluconic acid as potential taste markers for quality control. Finally, pathway enrichment analysis revealed that these components were primarily associated with amino acid tRNA, phenylalanine, tyrosine, and tryptophan biosynthesis, as well as sphingolipid metabolism. This study provides valuable insights into the mechanisms underlying the formation of the distinctive flavor of chili sauce.

Type 2 diabetes mellitus(T2DM) is an increasingly prevalent and serious health problem. Its onset is typically associated with metabolic disorders and disturbances in the gut microbiota. Previous studies have reported the anti-T2DM effects of Pueraria thomsonii Radix as a functional food. However, the mechanism of action is still unknown. In this study, the effects of Pueraria thomsonii Radix water extract(PTR) on db/db mice were evaluated by pharmacology, metabolomics, and 16S rRNA gene sequencing. The results showed that PTR could improve the body weight of mice, reduce fasting blood glucose(FBG), urinary glucose(UGLU), homeostasis model assessment insulin resistance(HOMA-IR), urinary albumin/creatinine ratio(UACR), and reduce pancreatic tissue damage. Metabolomics showed that the Model group produced 109 differential metabolites, of which 74 could be regulated by PTR. 16S rRNA sequencing was done in fecal samples and results showed that PTR could reduce the Firmicutes/Bacteroidetes ratio(F/B) associated with obesity and regulate 3 beneficial bacteria and 1 harmful bacteria. In conclusion, the results showed that PTR could ameliorate T2DM symptoms, metabolic disorder, and gut microbiota imbalance of db/db mice, and it was superior to metformin in some aspects. We suggested for the first time that γ-aminobutyric(GABA) may be involved in the regulation of the microbiota-gut-brain axis(MGB) and thus affect the metabolic disorders associated with T2DM. This study will provide a scientific basis for the development of functional food with PTR.

The frequency of non-alcoholic fatty liver disease (NAFLD) has exacerbated setting diagnostic challenges, which increases the need for reliable non-invasive diagnostic tools. Due to the importance of gut-liver axis in the progression of NAFLD, studies try to reveal microbial signatures in NAFLD, evaluate them as diagnostic biomarkers and to predict the disease progression. The gut microbiome affects human physiology by processing the ingested food to bioactive metabolites. These molecules can penetrate the portal vein and the liver to promote or prevent hepatic fat accumulation. Here findings of human fecal metagenomic and metabolomic studies in relation to NAFLD are reviewed. The studies present mostly distinct and even contradictory findings on microbial metabolites and functional genes in NAFLD. The most reproducing microbial biomarkers are increased lipopolysaccharides and peptidoglycan biosynthesis, enhanced degradation of lysine, increased levels of branched chain amino acids as well as altered lipid and carbohydrate metabolism. Among other causes, the discrepancies between the studies may be related to the obesity status of the patients and severity of NAFLD. In none of the studies except one, diet was considered, though it is an important factor driving the gut microbiota metabolism. The future studies should consider diet in the analyses.

The blood-brain barrier (BBB) is a selectively permeable boundary that separates the circulating blood from the extracellular fluid of the brain and is an essential component for brain homeostasis. In glioblastoma (GBM), the BBB of peritumoral vessels is often disrupted. Pericytes, being important to maintain the BBB integrity, can be functionally modified by GBM cells by inducing proliferation and cell motility via the TGF-β-mediated induction of central epithelial to mesenchymal transition (EMT) factors., We demonstrate that pericytes strengthen the integrity of the BBB in primary endothelial cell/pericyte co-cultures as in vitro BBB model, using TEER measurement of the barrier integrity. In contrast, this effect was abrogated by TGF-β or conditioned medium from TGF-β secreting GBM cells, finally leading to the disruption of a so far intact and tight BBB. TGF-β dramatically changed the metabolic behavior of pericytes, such as shutting down the TCA cycle, driving energy generation from oxidative phosphorylation towards glycolysis, and by shifting the cells towards the activation of pathways that are necessary to produce molecules used for proliferation and cell division. Furthermore, combined metabolomics and RNASeq analyses indicated that the observed functional changes of TGF-β-treated pericytes are closely connected with their behavior.

Viral infections cause metabolic dysregulation in the infected organism. The present study used metabolomics techniques and machine learning algorithms to retrospectively analyze the alter-ations of a broad panel of metabolites in the serum and urine of a cohort of 126 patients hospi-talized with COVID-19. Results were compared with those of 50 healthy subjects and 45 COVID-19 negative patients but with bacterial infectious diseases. Metabolites were analyzed by gas chro-matography coupled to quadrupole time-of-flight mass spectrometry. The main metabolites al-tered in the sera of COVID-19 patients were those of pentose glucuronate interconversion, ascorbate and fructose metabolism, nucleotide sugars, and nucleotide and amino acid metabolism. Alterations in serum maltose, mannonic acid, xylitol, or glyceric acid metabolites segregated positive patients from the control group with high diagnostic accuracy, while succinic acid seg-regated positive patients from those with other disparate infectious diseases. Increased lauric acid concentrations were associated with severity of infection and death. Urine analyses could not discriminate between groups. Targeted metabolomics and machine learning algorithms facilitated the exploration of the metabolic alterations underlying COVID-19 infection, and to identify po-tential biomarkers for the diagnosis and prognosis of the disease.

Over the past decade, studies have demonstrated the importance of bioactive metabolites derived from the microbiota in the regulation of physiological processes essential for homeostasis and the maintenance of human health. Strategies to modulate the production of these metabolites in the gastrointestinal tract hold promise for combating dysbiosis or inflammatory bowel disease. Metabolic engineering of probiotics could be one of these solutions. In this work, we engineered Escherichia coli Nissle 1917 (EcN) to overproduce spermidine, a metabolite known for its anti-immunosenescence and anti-inflammatory properties. Using a rational synthetic biology approach coupled with analysis by high resolution mass spectrometry, we designed in several steps and validated engineered probiotics overproducing and excreting spermidine. Based on our results, we first added the enzyme substrate putrescine and showed the overproduction of spermidine and decided to add a transporter limiting the production of the acetylated form of spermidine. Next, we used untargeted metabolomics to study the impact of engineering on the central metabolism of E. coli Nissle. Untargeted metabolomics appears to be a good strategy to optimize the metabolic engineering of probiotic strains and thus accelerate their development for personalized medicine.

Background: Omega-3 polyunsaturated fatty acids (PUFAs) are increasingly reported to improve chronic neuroinflammatory diseases in peripheral and central nervous systems. Specifically, docosahexaenoic acid (DHA) protects nerve cells from noxious stimuli in vitro and in vivo. Recent reports link PUFA supplementation to improving painful diabetic neuropathy (pDN) symptoms. However, the molecular mechanism behind omega-3 PUFAs ameliorating pDN symptoms is lacking. Therefore, we sought to determine the distinct cellular pathways that omega-3 PUFAs dietary supplementation promotes in reducing painful neuropathy in type 2 diabetes mellitus (DM2) patients. Methods: Forty volunteers diagnosed with type 2 diabetes were enrolled in the "En Balance-PLUS" diabetes education study. The volunteers participated in weekly lifestyle/nutrition education and daily supplementation with 1,000 mg DHA and 200 mg eicosapentaenoic acid. The Short-Form McGill Pain Questionnaire validated clinical determination of baseline and post-intervention pain complaints. Laboratory and untargeted metabolomics analyses were conducted using blood plasma collected at baseline and after three months of participation in the dietary regimen. The metabolomics data was analyzed using random forest, hierarchical cluster, ingenuity pathway analysis, and metabolic pathway mapping. Results: We found that metabolites involved in oxidative stress and glutathione production shifted significantly to a more anti-inflammatory state post supplementation. Example of these metabolites include cystathionine (+90%), S-methylmethionine (+9%), glycine cysteine-glutathione disulfide (+157%) cysteinylglycine (+19%), glutamate (-11%), glycine (+11%) and arginine (+13.4%). In addition, the levels of phospholipids associated with improved membrane fluidity such as linoleoyl-docosahexaenoyl-glycerol (18:2/22:6) (+253 %) were significantly increased. Ingenuity pathway analysis suggested several key bio functions associated with omega-3 PUFA supplementation such as formation of reactive oxygen species (p = 4.38 × 10-4, z-score = -1.96), peroxidation of lipids (p = 2.24 × 10-5, z-score = -1.944), Ca2+ transport (p = 1.55 × 10-4, z-score = -1.969), excitation of neurons (p = 1.07 ×10-4, z-score = -1.091), and concentration of glutathione (p = 3.06 × 10-4, z-score = 1.974). Conclusion: The reduction of pro-inflammatory and oxidative stress pathways following omega-3 PUFAS supplementation is consistent with using omega-3 PUFAs as a complementary dietary strategy as part of the overall treatment of painful diabetic neuropathy.

Shiga toxigenic E. coli (STEC) are an important cause of foodborne disease globally with many outbreaks linked to the consumption of contaminated foods such as leafy greens. Existing methods for STEC detection and isolation are time-consuming. Rapid methods may assist in preventing contaminated products from reaching consumers. This proof-of-concept study aimed to determine if a metabolomics approach could be used to detect STEC contamination in spinach. Using untargeted metabolic profiling, the bacterial pellets and supernatants arising from bacterial and inoculated spinach enrichments were investigated for the presence of unique metabolites that enabled categorization of three E. coli risk groups. A total of 109 and 471 metabolite features were identified in bacterial and inoculated spinach enrichments, respectively. Supervised OPLS-DA analysis demonstrated clear dis-crimination between bacterial enrichments containing different risk groups. Further analysis of the spinach enrichments determined that pathogen risk groups 1 and 2 could be easily discriminated from the other groups, though some clustering of risk groups 1 and 2 was observed, likely representing their genomic similarity. Biomarker discovery identified metabolites that were significantly associated with risk groups and may be appropriate targets for potential biosensor development. This study has confirmed that metabolomics can be used to identify the presence of pathogenic E. coli likely to be implicated in human disease.

Carvacrol has long been studied for its natural antifungal potential and food preservative. But the exact mode of its action remained highly complex as a general, but especially for Penicillium digitatum (P. digitatum) largely remained unexplored. Herein, a 1H-NMR-based metabolomic technique was used to investigate the antifungal mechanism of carvacrol. The metabolomic profiling data showed that alanine, aspartate, glutamate and glutathione metabolism were imbalanced in the fungal hyphae. A strong positive correlation was seen between aspartate, glutamate, alanine and glutamine, while negative correlation among glutathione and lactate. These metabolic changes revealed that carvacrol-induced oxidative stress had disturbed the energy production and amino acid metabolism of P. digitatum. Current study will improve the understanding of the metabolic changes posed by plant-based fungicides in order to control citrus fruit green mold caused by P. digitatum. Moreover, the study will provided certain experimental and theoretical basis for the development of novel citrus fruit preservatives.

Background: Plasma metabolites are associated with cognitive and physical function in the elderly. Because cerebral small vessel disease (SVD) and neurodegeneration are common causes of cognitive and physical function decline, the primary objective of this study was to investigate the associations of six plasma metabolites (two plasma phosphatidylcholines [PCs]: PC aa C36:5 and PC aa 36:6 and four sphingomyelins [SMs]: SM C26:0, SM [OH] C22:1, SM [OH] C22:2, SM [OH] C24:1) with magnetic resonance imaging (MRI) features of cerebral SVD and neurodegeneration in older adults. Methods: This study included 238 older adults in the Atherosclerosis Risk in Communities study at the fifth exam. Multiple linear regression was used to assess the association of each metabolite (log-transformed) in separate models with MRI measures except lacunar infarcts, for which binary logistic regression was used. Results: Higher concentrations of plasma PC aa C36:5 had adverse associations with MRI features of cerebral SVD (odds ratio of 1.69 [95% confidence interval: 1.01, 2.83] with lacunar infarct, and beta of 0.16 log [cm³] [0.02, 0.30] with log [White Matter Hyperintensities (WMH) volume]) while higher concentrations of 3 plasma SM (OH)s were associated with higher total brain volume (beta of 12.0 cm³ [5.5, 18.6], 11.8 cm³ [5.0, 18.6], and 7.3 cm³ [1.2, 13.5] for SM [OH] C22:1, SM [OH] C22:2, and SM [OH] C24:1, respectively). Conclusions: This study identified associations between certain plasma metabolites and brain MRI measures of SVD and neurodegeneration in older adults, particularly higher SM (OH) concentrations with higher total brain volume.

Microbial competition within plant tissues affects invading pathogens' fitness. Metabolomics is a great tool for studying their biochemical interactions by identifying accumulated metabolites. Xylella fastidiosa, a Gram-negative bacterium causing Pierce's disease (PD) in grapevines, secretes various virulence factors including cell wall degrading enzymes, adhesion proteins, and quorum sensing molecules. These factors, along with outer membrane vesicles, contribute to its pathogenicity. Previous studies demonstrated that co-inoculating X. fastidiosa with Paraburkholderia phytofirmans strain PsJN suppressed PD symptoms. Here, we further investigated the interaction between the phytopathogen and the endophyte by analyzing the exometabolome of wild-type X. fastidiosa and a diffusible signaling factor (DSF) mutant lacking quorum sensing, cultivated with 20% P. phytofirmans spent media. LC-MS and MAGI were used to detect and map metabolites to genomes revealing a total of 121 metabolites, of which 25 were further investigated. These metabolites potentially relate to host adaptation, virulence, and pathogenicity. Notably, this study presents the first comprehensive profile of X. fastidiosa in the presence of P. phytofirmans spent media. The results highlight that P. phytofirmans and the absence of a functional quorum sensing affect the ratios of glutamine to glutamate (Gln:Glu) in X. fastidiosa. Additionally, two compounds with plant metabolism and growth properties, 2-Aminoisobutyric acid and Gibberellic Acid, were downregulated when X. fastidiosa interacted with P. phytofirmans. These findings suggest that P. phytofirmans-mediated disease suppression involves modulation of the exometabolome of X. fastidiosa, impacting plant immunity.

For Lentinula edodes, its characteristic flavor is the key determinant for consumer pref-erences. However, the tissue-specific volatile flavor variations of the fruiting body have been overlooked. Here, we comprehensively investigated volatile flavor profiles of different tissues including the pileus skin, context, gill and stipe of the fruiting body of two widely cultivated L. edodes strains (T2 and 0912). We show that the eight-carbon and sulfur com-pounds, which represented 43.2-78.0% and 1.4-42.9% to the total volatile emissions for strain 0912 and T2, dominated their volatiles profiles. The sulfur compounds could rep-resent 32.2% and 42.9% to the total volatile emissions for the context of the strain 0912 and T2, respectively, whereas only represented 1.4% for the stipes of the strain 0912 and 9.0% for the skin of strain T2. Proportions of the predominant C8 compounds (1-Octen-3-one, 1-Octen-3-ol and 3-Octanone) and sulfur compounds (Lenthionine, 1,2,4-Trithiolane, Di-methyl disulfide and Dimethyl trisurfide) changed depending on tissues and strains. We further reveal that the overall volatile flavor profiles varied greatly in different tissues and strains. With machine learning algorithm, we show that volatile profiles could 100% pre-dict strains 0912 and T2. The prediction accuracy for different tissues could also reach 100%. Our results highlight the tissue-specific volatile flavor variations of the L. edodes fruiting body.

As research into the relationship between the gut microbiome and health continues to evolve, probiotics are garnering increasing interest among consumers. Fermentation is rec-ognized as an efficacious biotechnology for augmenting the nutritional and functional at-tributes of foods. In this study, the ameliorative effects of Lycium barbarum L. lyophilized powder fermented with Lactobacillus plantarum NXU0011 (LP+Ly) on dextran sodium sul-fate (DSS)-induced ulcerative colitis (UC) in mice were investigated employing immuno-histochemistry, qRT-PCR, macrogenomics, and metabolomics. The results revealed that LP+Ly intervention significantly ameliorated histopathological inflammation in the ulcer-ated colon, diminished the expression of inflammatory markers such as IL-6, P-STAT3, and miR-214, and enhanced the diversity of intestinal flora in the mouse model group. Moreover, there was an increase in abundance of beneficial bacteria, including Lactobacillus, Prevotella, and Akkermansia. Metabolomic analysis indicated that 15 metabolites, including citrulline, D-xylose, and α-ketoisovaleric acid, exhibited significant variations following LP+Ly inter-vention. The metabolic pathways that displayed substantial differences included tryptophan biosynthesis, arginine biosynthesis, and amino sugar and nucleotide sugar metabolism. By modulating arginine biosynthesis, LP+Ly effectively improved the intestinal inflammatory state, thus mitigating the effects of UC.

Coptisine (Cop) exerts a neuroprotective effect in central nervous system disease, particularly ischemic stroke. However, its protective mechanism is still unclear. This study aimed to investigate the protective effect of Cop on cerebral ischemia-reperfusion (IR) rats with a middle cerebral artery occlusion model by integrating a gas chromatography-mass spectrometry (GC-MS) based metabolomics approach with biochemical assessment. Our results showed that Cop could improve neurobehavioral function and decrease the ischemia size in IR rats. In addition, Cop was found to decrease inflammatory mediators (e.g., prostaglandin D2 (PGD2) and tumor necrosis factor-α (TNF-α) and attenuate oxidative stress response (e.g., increase the superoxide dismutase (SOD) expression and decrease 8-iso-PGF2α level). Furthermore, GC-MS based cerebrospinal fluid (CSF) metabolomics analysis indicated that Cop influenced the level of glycine, 2,3,4-trihydroxybutyric acid, oleic acid, glycerol, and ribose during IR injury. Cop exhibited a good neuroprotective effect against cerebral IR injury and metabolic alterations which might be mediated through its antioxidant and anti-inflammatory property.

Panax ginseng C. A. Meyer (P. ginseng), has been widely used in traditional Chinese medicine (TCM). It contains a number of chemical components and possesses a variety of pharmacological activities. Alzheimer's disease (AD) is neurodegenerative disease that creates a huge burden on the lives and health of individuals. In recent years, studies have indicated that the chemical components of P. ginseng, especially ginsenosides, play a pronounced positive role in the prevention and treatment of neurological diseases. This review aimed to summarize currently studies on chemical components and the mechanisms action in AD intervention treatment of P. ginseng, especially ginsenosides. In this review, the components of P. ginseng and their respective active effects were first introduced. Then the key molecular mechanisms and signaling pathways of P. ginseng were introduced, and its different active ingredients in the prevention and treatment of Alzheimer's disease-related pathogenesis were also summarized from the pathogenesis of AD Aβ generation and aggregation, hyperphosphorylation of tau protein，oxidant stress，neuroinflammation，mitochondrial damage，disorder of neurotransmitter and gut microbiota. Signaling pathway networks related to the action of ginseng active ingredients was constructed, which could serve as a therapeutic target for Alzheimer's disease. In addition to a detailed report on P. ginseng in improving Alzheimer's disease-related pathogenesis, the application of the current technology, spatial metabonomics in AD therapeutics and diagnostics were later discussed. Spatial metabonomics could be applied to investigate the multi-target intervention of P. ginseng on Alzheimer's disease. Research perspectives for the study of P. ginseng in the treatment of Alzheimer's disease were provided for further studies.

The most aggressive primary malignant brain tumor in adults is glioblastoma (GBM), which has poor overall survival (OS). There is a high relapse rate among patients with GBM despite maxi-mally safe surgery, radiation therapy, temozolomide (TMZ), and aggressive treatment. Hence, there is an urgent and unmet clinical need for new approaches to managing GBM. The current study identified modules (MYC, EGFR, PIK3CA, SUZ12, and SPRK2) involved in GBM disease through the NeDRex plugin. Furthermore, hub genes were identified in a comprehensive interaction network containing 7,560 proteins related to GBM disease and 3,860 proteins associated with signaling pathways involved in GBM. By integrating the results of the aforementioned analyses and performing centrality analysis again, eleven key genes involved in GBM disease were identi-fied. ProteomicsDB or Gliovis databases were used for determining the gene expression in normal or tumor brain tissue. The NetworkAnalyst and the mGWAS-Explorer tools identified miRNAs, SNPs, and metabolites associated with these 11 genes. Moreover, a literature review of recent studies revealed other lists of metabolites related to GBM disease. The enrichment analysis of iden-tified genes, miRNAs, and metabolites associated with GBM disease was done using ExpressAna-lyst, miEAA, and MetaboAnalyst tools. Further investigation of metabolite roles in GBM was done through the pathway, joint pathway, and network analyses. The results of this study identified 11 genes (UBC, HDAC1, CTNNB1, TRIM28, CSNK2A1, RBBP4, TP53, APP, DAB1, PINK1, and RELN), five miRNAs (hsa-mir-221-3p, hsa-mir-30a-5p, hsa-mir-15a-5p, hsa-mir-130a-3p, hsa-let-7b-5p), six metabolites (HDL, N6-acetyl-L-lysine, cholesterol, formate, N, N-dimethylglycine/xylose and X2. piperidinone) and 15 distinct signaling pathways that play an indispensable role in the GBM disease development. To establish early diagnostic methods and plan personalized GBM treatment strategies, the identified top genes-miRNAs and metabolite signatures can be targeted.

Cyanobacteria are microorganisms able to adapt to a wide variety of environmental conditions and abiotic stresses. They produce a very large number of metabolites that can participate in the adaptation of cyanobacteria to a large range of resources such as light, temperature, or nutrient. The metabolites variation is one way to understand the physiological status and adaptation of cells. In this study, we aim to understand how the diversity and the dynamics of the whole metabolome is dependent of the growth phases and under control of abiotic factors (e.g. light intensity and temperature). The cyanobacteria Aliinostoc sp. PMC 882.14 was selected for its large number of biosynthetic gene clusters. Metabolomes were analyzed by using mass spectrometry (qTOF-MS/MS) combined with untargeted analysis to investigate the metabolite dynamics. Significant variations were characterized between exponential and stationary phases, whatever the culture conditions (“control”, “higher light”, or “higher temperature”). ”Higher light” and “higher temperature” favored the synthesis of metabolites belonging to the same molecular families. Among highly regulated metabolites, we observe the presence of mycosporine-like amino acids (MAAs), and various variants of somamides, microginins, and microviridins. Through Aliinostoc sp. PMC 882.14, this study shows the importance of knowing the physiological state of cyanobacteria for comparative global metabolomics and questions the regulation processes involve into metabolite families production. Our results also open up new perspectives in the context of the production of targeted bioactive metabolites.

Stable isotope-assisted approaches can improve untargeted LC-HRMS metabolomics studies. Here, we demonstrate at the example of chemically stressed wheat that metabolome-wide internal standardization by globally 13C-labeled metabolite extract (GLMe-IS) of experimental-condition-matched biological samples can help to improve coverage of treatment-relevant metabolites and aid in the post-acquisition assessment of putative matrix effects in samples obtained upon different treatments. For this, native extracts of toxin- and mock-treated (control) wheat ears were standardized by the addition of uniformly-13C-labeled wheat ear extracts that were cultivated under similar experimental conditions (toxin-treatment and control) and measured with LC-HRMS. The results show that 996 wheat-derived metabolites were detected with the non-condition-matched 13C-labeled metabolite extract, while another 68 were only covered by the experimental-condition-matched GLMe-IS. Additional testing is performed with the assumption that GLMe-IS enables compensation for matrix effects. Although on average no severe matrix differences between both experimental conditions were found, individual metabolites may be affected as is demonstrated by wrong decisions with respect to the classification of significantly altered metabolites. When GLMe-IS was applied to compensate for matrix effects, 272 metabolites showed significantly altered levels between treated and control samples, 42 of which would not have been classified as such without GLMe-IS.

The COVID-19 pandemic has raised questions about indirect impact in pregnant women on the development of their future children. Investigating the characteristics of lipid metabolism in the "mother-placenta-fetus" system can give information about the pathophysiology of COVID-19 infection during pregnancy. 234 women were included in study. Maternal plasma, cord blood, amniotic fluid lipidome were analyzed using HPLC-MS/MS. Differences in lipid profile were searched by Manna-Whitney and Kruskall-Wallis test, diagnostic model based on logistic regres-sion were bilt by AIC. Elevation levels of lysophospholipids, triglycerides, sphingomyelins, and oxidized lipids was registered in patients’ after COVID-19 maternal and cord plasma. An increase in maternal plasma sphingomyelins and oxidized lipids was observed in cases of infection during the second trimester. In amniotic fluid, compared to the control group, nine lipids are reduced, six lipids are elevated. Levels of phosphoglycerides, lysophosphoglycerides, and phosphatidylinosi-tols decreased during infection in the second and third trimesters of pregnancy. Newborn’s health diagnostic model based on maternal plasma were developed for each group and exhibit good di-agnostic value (AUC> 0.85). Maternal and cord plasma’s lipidome changes during delivery, asso-ciated with Covid-19 infection during pregnancy, are synergistic. The most significant disturbances occur with infections in the second trimester of pregnancy.

Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex and debilitating disease with a significant global prevalence of over 65 million individuals. It affects various systems, including the immune, neurological, gastrointestinal, and circulatory systems. Studies have shown abnormalities in immune cell types, increased inflammatory cytokines, and brain abnormalities. Further research is needed to identify consistent biomarkers and develop targeted therapies. A multidisciplinary approach is essential for diagnosing, treating, and managing this complex disease. The current study aims at employing explainable artificial intelligence (XAI) and machine learning (ML) techniques to identify discriminative metabolites for ME/CFS. Material and Methods: The present study used a metabolomics dataset of CFS patients and healthy controls, including 26 healthy controls and 26 ME/CFS patients aged 22-72. The dataset encapsulated 768 metabolites, classified into nine metabolic super-pathways: amino acids, carbohydrates, cofactors, vitamins, energy, lipids, nucleotides, peptides, and xenobiotics. Random forest-based feature selection and Bayesian Approach based-hyperparameter optimization were implemented on the target data. Four different ML algorithms [Gaussian Naive Bayes (GNB), Gradient Boosting Classifier (GBC), Logistic regression (LR) and Random Forest Classifier (RFC)] were used to classify individuals as ME/CFS patients and healthy individuals. XAI approaches were applied to clinically explain the prediction decisions of the optimum model. Performance evaluation was performed using the indices of accuracy, precision, recall, F1 score, Brier score, and AUC. Results: The metabolomics of C-glycosyltryptophan, oleoylcholine, cortisone, and 3-hydroxydecanoate were determined to be crucial for ME/CFS diagnosis. The RFC learning model outperformed GNB, GBC, and LR in ME/CFS prediction using the 1000 iteration bootstrapping method, achieving 98% accuracy, precision, recall, F1 score, 0.01 Brier score, and 99% AUC. Conclusion: RFC model proposed in this study correctly classified and evaluated ME/CFS patients through the selected biomarker candidate metabolites. The methodology combining ML and XAI can provide a clear interpretation of risk estimation for ME/CFS, helping physicians intuitively understand the impact of key metabolomics features in the model.

Breast cancer (BC) is the most common malignancy and the second cause of cancer specific death in women from high-income countries. More than 70% of all breast cancer are hormone receptor-positive BC, and elevated estrogen circulating in blood has been proved to be a strong risk for BC development. This is due to its contribution to enhance proliferation of cancerous cells, angiogenesis and metastasis stimulation and therapy resistance. The estrogen (E) metabolism–gut microbiome axis is functional with underlying individual variations in E levels. It is reasonable that the estrobolome (bacterial genes whose products are capable of metabolizing E) could contribute to the risk of hormone-driven malignancies including BC and may serve as a potential biomarker and target. Gut microbial β -glucuronidase (GUS) enzymes have been suggested to be involved in the estrobolome. Furthermore, bacterial GUS enzymes within the gastrointestinal tract have been postulated to contribute to hormone breast cancer. In this review, we discuss the recent knowledge about the role of GUS enzyme in the pathogenesis of breast cancer. We focus on the role of GUS in (i)-the microbioma and estrogen metabolism, (ii) diet, estrobolome, and the BC development, (iii) other activities of the bacterial β-glucuronidase, and (iv) the new molecular target for BC therapeutic application.

Graviera is a very popular yellow hard cheese produced in mainland Greece and the Aegean islands, and in three PDO (Protected Denomination of Origin) locations. Apart from geographic location, milk type and production practices are also factors that affect cheese composition, and make this dairy product unique in taste and aroma. In this work, 1H NMR spectroscopy in combination with chemometrics has been used to determine the metabolite profile (40 compounds) of graviera cheese produced in different geographic locations, with emphasis on cheeses produced on the island of Crete. Organic acids and amino acids were the main components quantified in the polar cheese fraction, while the fatty acid composition of the lipid fraction was also obtained. Analysis of Variance (Anova) of the dataset showed that γ-aminobutyric acid (GABA), conjugated linoleic acids (CLA) and linoleic acid differentiate gravieras produced in different areas of Crete, and that total amino acid content was higher in cheeses produced in eastern Crete. Targeted Discriminant Analysis models classified gravieras produced in mainland Greece, Cyclades and Crete based on differences in 1,2-diglycerides, sterols, GABA and fatty acid composition. Targeted and untargeted OPLS-DA models were capable of differentiating between gravieras produced in the island of Crete and hold promise as the basis for the authentication of PDO graviera products.

Background & Aims: Non-alcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) have been linked to changes in amino acid (ΑΑ) levels. The current observational study sought to investigate the relationship between plasma AA concentrations in a NAFLD population and MRI parameters reflecting inflammation and fibrosis, inflammatory and oxidative stress markers, and disease-related anthropometric and biochemical indicators. Approach & Results: Plasma AA levels were quantified with liquid chromatography in 97 NAFLD patients from the MAST4HEALTH study. Medical, anthropometric and lifestyle characteristics were collected and biochemical parameters, as well as inflammatory and oxidative stress biomarkers were measured. In total, males and subjects with higher MRI-proton density fat fraction (MRI-PDFF) exhibited higher plasma AA levels compared to females and subjects with lower PDFF respectively. Several associations of AAs with disease related markers were revealed, with the more prominent ones being those of aromatic amino acids with log-PDFF (beta: 1.190E-02, p-Value: 0.001) and log-ALT (beta: 7.55E-03, p-Value: 0.001), of branched amino acids with log-insulin (beta: 1.97E-03, p-Value: 1.16E-04) and of ethanolamine (beta: 0.036, p-Value: 3.65E-04) and L-ornithine (beta: 5.4E-04, p-Value: 0.021) with log-total antioxidant status (TAS). Conclusions: Plasma AA levels varied according to sex, BMI, and several MRI clinical factors. Furthermore, significant relationships were demonstrated between AA and several disease indicators, such as MRI parameters, biochemical and oxidative stress indices, showing the potential utility of AAs as diagnostic dis-ease-related indicators activity.

The global threat of COVID-19 has led to the increasing use of metabolomics to study SARS-CoV-2 infection in humans and animals. Despite this, understanding SARS-CoV-2's metabolome during infection remains difficult and incomplete. Here, metabolic responses were characterized from sampled nasal washes collected from an asymptomatic ferret model (n = 20) at different time points before and after the SARS-CoV-2 challenge using an LC-MS-based metabolomics approach. Multivariate analysis of the nasal wash metabolome data resulted in several statistically significant features being observed. Despite no effects of gender or interaction between gender and time on the time course of SARS-CoV-2 infection, 16 metabolites were significantly different at every time point post-infection. Among these altered metabolites, the relative abundance of taurine was elevated post infection which could be an indication of hepatotoxicity, while the accumulation of sialic acids could indicate SARS-CoV-2 invasion. The pathway analysis identified several pathways influenced by SARS-CoV-2 infection. Of these, sugar, glycan, and amino acid metabolisms were the key altered pathways in the upper respiratory channel during infection. These findings provide some new insights into the progression of SARS-CoV-2 infection in ferrets at the metabolic level which could be useful for the development of early clinical diagnosis tools and new or repurposed drug therapies.

Phospholipid metabolism, including phosphatidylcholine (PC) biosynthesis, is crucial for various biological functions and is associated to longevity. Phosphatidylethanolamine N-methyltransferase (PEMT) is a protein that catalyzes the biosynthesis of PC, the levels of which change in various organs such as brain and kidney during aging. However, the role of PEMT for systemic PC supply is not fully understood. To address how PEMT affects aging-associated energy metabolism in tissues responsible for nutrient absorption, lipid storage and energy consumption, we employed NMR-based metabolomics to study liver, plasma, intestine (duodenum, jejunum, ileum), brown/white adipose tissues (BAT, WAT), and skeletal muscle of young (9–10 weeks) and old (96–104 weeks) wild-type (WT) and PEMT knockout (KO) mice. We found that the effect of PEMT-knockout was tissue-specific and age-dependent. Deficiency of PEMT affected the metabolome of all tissues examined, among which the metabolome of BAT from both young and aged KO mice was dramatically changed in comparison to WT mice, whereas the metabolome of jejunum was only slightly affected. As for aging, the absence of PEMT increased the divergence of metabolome during aging of liver, WAT, duodenum and ileum and decreased the impact on skeletal muscle. Overall, our results suggest that PEMT plays a previously unexplored critical role in both aging and energy metabolism.

A major challenge in the clinical management of patients with mesial temporal lobe epilepsy (MTLE) is identifying those who do not respond to antiseizure medication (ASM), allowing for the timely pursuit of alternative treatments, such as epilepsy surgery. Here, we investigated changes in plasma metabolites as biomarkers of pharmacoresistance in patients with MTLE. Furthermore, we used the metabolomics data to gain insights into the mechanisms underlying MTLE and response to ASM. We performed an untargeted metabolomic method using magnetic resonance spectroscopy and multi- and univariate statistical analyses to compare data obtained from plasma samples of 28 patients with MTLE compared to 28 controls. The patients were further divided according to response to ASM: 20 patients were refractory to treatment, and eight were responsive to ASM. We only included patients using carbamazepine in combination with clobazam. We compared the group of patients with controls and found that the profiles of glucose (p = 0.01), saturated lipids (p = 0.0002), isoleucine (p = 0.0001), β-hydroxybutyrate (p = 0.0003), and proline (p = 0.02) were different in patients compared to controls (p &lt; 0.05). In addition, lipoproteins (p = 0.05), lactate (p = 0.05), glucose (p = 0.05), unsaturated lipids (p = 0.05), isoleucine (p = 0.05), and proline (p = 0.05), could discriminate between the two groups of patients classified according to response to ASM. The identified metabolites were linked to different biological pathways related to cell energy metabolism, and pathways linked to inflammatory processes and the modulation of neurotransmitter release and activity in MTLE. In contrast, we found that pyruvate metabolism may be linked to resistance to ASM. In conclusion, in addition to insights into the mechanisms underlying MTLE and the response to treatment with ASM, our results suggest that plasma metabolites may be used as biomarkers of disease and response to ASM in patients with MTLE. These findings warrant further studies exploring the clinical use of metabolites to assist in decision-making when treating patients with MTLE.

In the era of multi-omic sciences, dogma on singular cause-effect in physio-pathological processes is overcome and system biology approaches have been providing new perspectives to see through. In this context, extracellular vesicles (EVs) are offering a new level of complexity, given their role in cellular communication and their activity as mediators of specific signals to target cells or tissues. Indeed, their heterogeneity in terms of content, function, origin and potentiality contribute to the cross-interaction of almost every molecular process occurring in a complex system. Such features make EVs proper biological systems being, therefore, optimal targets of omic sciences. Currently, most studies focus on dissecting EVs content in order to either characterize it or to explore its role in various pathogenic processes at transcriptomic, proteomic, metabolomic, lipidomic and genomic levels. Despite valuable results are being provided by individual omic studies, the categorization of EVs biological data might represent a limit to be overcome. For this reason, a multi-omic integrative approach might contribute to explore EVs function, their tissue-specific origin and their potentiality. This review summarizes the state-of-the-art of EVs omic studies, addressing recent research on the integration of EVs multi-level biological data and challenging developments in EVs origin.

COVID-19 is a contagious respiratory disease that is causing significant global morbidity and mortality. Understanding the impact of a SARS-CoV-2 infection on the host metabolism is still in its infancy but of great importance. Herein, we investigated the metabolic response during viral shedding and post-shedding in an asymptomatic SARS-CoV-2 ferret model (n=6) challenged with two SARS-CoV-2 isolates. Virological and metabolic analyses were performed on (minimally invasive) collected oral swabs, rectal swabs, and nasal washes. Fragments of SARS-CoV-2 RNA were only found in the nasal wash samples in four of the six ferrets, and in the samples collected 3 to 9 days post-infection (referred to as viral shedding). Central carbon metabolism metabolites were analyzed during viral shedding and post-shedding periods using a dynamic MRM (dMRM) database and method. Subsequent untargeted metabolomics and lipidomics of the same samples were performed using an LC-QToF-MS methodology, building upon the identified differentiated central carbon metabolism metabolites. Multivariate analysis of the acquired data identified 29 significant metabolites and three lipids that were subjected to pathway enrichment and impact analysis. The presence of viral shedding coincided with the challenge dose administered and significant changes in the citric acid cycle, purine metabolism, and pentose phosphate pathways, amongst others, in the host nasal wash samples. An elevated immune response in the host was also observed between the two isolates studied. These results support other reported metabolomic-based findings found in clinical observational studies and indicate the utility of metabolomics applied to ferrets for further COVID-19 research that advances early diagnosis of asymptomatic and mild clinical COVID-19 infections, in addition to assessing the effectiveness of new or re-purposed drug therapies.

Physical frailty and sarcopenia (PF&S) are hallmarks of aging that share a common pathogenic background. Perturbations in protein/amino acid metabolism may play a role in the development of PF&S. In this preliminary study, 68 community-dwellers aged 70 years and older, 38 with PF&S and 30 non-sarcopenic, non-frail controls (nonPF&S), were enrolled. A panel of 37 serum amino acids and derivatives was assayed by UPLC-MS. Partial Least Squares Discriminant Analysis (PLS-DA) was used to characterize the amino acid profile of PF&S. The optimal complexity of the PLS-DA model was found to be three latent variables. The proportion of correct classification was 76.6 ± 3.9% (75.1 ± 4.6% for enrollees with PF&S; 78.5 ± 6.0% for controls). Older adults with PF&S were characterized by higher levels of asparagine, aspartic acid, citrulline, ethanolamine, glutamic acid, sarcosine, and taurine. The profile of nonPF&S individuals was defined by higher levels of α-aminobutyric acid and methionine. Distinct profiles of circulating amino acids and derivatives characterize older individuals with PF&S. The dissection of these patterns may provide novel insights into the role played by protein/amino acid perturbations in the disabling cascade and possible new targets for interventions.

Background: The official standard for quality control of honey is currently based on physicochemical properties. However, this method is time-consuming, cost intensive, and do not lead to information on the originality of honey. This study aims to classify raw stingless bee honeys by bee species origins as a potential classifier using NMR-LCMS-based metabolomics approach. Methods: Raw stingless bee honeys were analysed and classified by bee species origins using proton nuclear magnetic resonance (1H NMR) spectroscopy and an ultra-high performance liquid chromatography-quadrupole time of flight mass spectrometry (UHPLC-QTOF MS) in combination with chemometrics tools. Results: The honey samples were able to be classified into three different groups based on the bee species origins of Heterotrigona itama, Geniotrigona thoracica, and Tetrigona apicalis. D-Fructofuranose (H. itama honey), β-D-Glucose, D-Xylose, α-D-Glucose (G. thoracica honey), and L-Lactic acid, Acetic acid, L-Alanine (T. apicalis honey) identified via 1H NMR data and the diagnostic ions of UHPLC-QTOF MS were characterized as the discriminant metabolites or putative chemical markers. Conclusion: It could be suggested that the quality of honey in terms of originality and purity can be rapidly determined using classification technique by bee species origins via 1H NMR- and UHPLC-QTOF MS-based metabolomics approach.

A high intake of carbohydrates, associated with obesity, is one of the major causes of fatty liver disease in humans. This study investigated how high carbohydrate intake induces fatty liver disease in Blunt snout bream (Megalobrama amblycephala). Blunt snout bream were fed a high-carbohydrate diet (HCBD) for 60 days. Their growth indices were evaluated, and the transcriptomes, metabolites, biochemistry, and histology of their blood and livers were analyzed. The final weight, weight gain, specific growth rate, and feed conversion ratio were all higher in the HCBD group than in the control group, but not significantly so (P > 0.05). The hepatosomatic index (HSI) differed significantly in the two groups (P < 0.05), and the metabolomics results showed that a high carbohydrate intake induced significant increases in plasma α/β-glucose, succinate, and tyrosine, which could increase hepatic glycogen and triglyceride. Low levels of betaine were also found in the livers of the HCBD group. The histology and blood biochemistry results suggested abnormal liver, with excessive lipid accumulation and liver damage. A transcriptome analysis and quantitative reverse transcription–PCR (RT–qPCR) indicated that the expression of the factors INSR, IRS, PI3K, PDK, AKT, ACC, IL6, AP1, ChREBP-MLX, PEPCK, and FBP in the insulin signaling pathway was significantly upregulated and that of SOCS3, GSK3β, and AMPK significantly downregulated in the HCBD. This pattern is associated with the nonalcoholic fatty liver disease (NAFLD) pathway. This study extends our understanding of how high carbohydrate causes increased fat deposition in the liver, enhanced glycolysis (α/β-glucose) in the plasma, and reduced betaine in the liver. This leads to activation of hepatocyte insulin resistance and lipogenesis by regulating the expression of genes related to fatty liver disease.

Human influenza A viruses (IAVs) cause global pandemics and epidemics. These viruses evolve rapidly, making current treatment options ineffective. To identify novel modulators of IAV-host interactions, we re-analyzed our recent transcriptomics, metabolomics, proteomics, phosphoproteomics, and genomics/virtual ligand screening data. We identified 713 potential modulators targeting 200 cellular and two viral proteins. Anti-influenza activity for 48 of them has been reported previously, whereas the antiviral efficacy of the remaining 665 is unknown. Studying anti-influenza efficacy, immuno-modulating properties and potential resistance of these compounds or their combinations may lead to the discovery of novel modulators of IAV-host interactions, which might be more effective than the currently available anti-influenza therapeutics.

Benign Paroxysmal Positional Vertigo (BPPV) represents the most frequent cause of peripheral vertigo. In most cases it is successfully treated by canalith repositioning procedure (CRP), but it is often followed by a continuous lightheadedness in absence of vertigo or nystagmus (residual dizziness, RD). Our aim is to describe the clinical effectiveness and the urine metabolomics profile treating these patients by a polyphenol compound supplementation. We enrolled 30 patients reporting RD after BPPV successfully treated using CRP. A supplementation with a Polyphenol compound was administered for 60 days, and patients were evaluated after 30 and 60 days of treatment by a self-administered questionnaires (Visual Analog Scales for Dizziness and Nausea, Dizziness Handicap Inventory, DHI) and by urine metabolomics analysis performed by 1H-NMR spectroscopy and multivariate followed by univariate analysis. Most patients reported an excellent or good efficacy of RD with a significant decrease for VAS and DHI values. The metabolomics analysis identified six significant metabolites related to the treatment: 1-methylnicotinamide, anserine, Hippurate, lysine, methyl succinate, and urea indicating an inflammatory activities and antioxidant properties of the polyphenol compound. These preliminary data suggest that supplementation with a polyphenol compound cold induces some metabolic changes that can help recover RD. However, the future steps will require confirmation with a more significant cohort of patients and an extension of the metabolomic evaluation to other problems concerning the different clinical aspects of BPPV, such as the high relapse found in a high percentage of patients.

(1) Background: The typical transporter protein, P-glycoprotein (P-gp), has been proven to be associated with multidrug resistance (MDR). Pyxinol and 24S-Pyxinol amino acid ester derivatives had been demonstrated to be promising P-gp inhibitors for reversal of tumor MDR in KBV cells, however, their roles in MDR reversal in other tumor-resistant cells are still unclear. (2) Methods: In the present study, we synthesized 40 amino acid ester derivatives of Pyxinol and 24S-Pyxinol. The MDR reversal effects of these derivatives were evaluated in A549/Tax, MCF-7/ADR, and HCT-8/VCR cells using the CCK-8 assay. Subsequently, western blot assay, intracellular Rhodamine123 (Rh123) accumulation assay and P-gp ATPase activity assay were utilized to investigate the effects of active compound on P-gp. Molecular docking was used to predict the possible binding patterns of active compound to P-gp. Moreover, based on UPLC-Q/TOF-MS cellular metabolomics technology to identify endogenous differential metabolites and metabolic pathways associated with tumor MDR effects of the active compound. (3) Results: The results of the CCK-8 assay showed that compounds 8, 14, 16, 17, 18, 23, 25, 34, 36, 37 exhibited strong MDR reversal effect in A549/Tax, MCF-7/ADR and HCT-8/VCR cells, which were screened by reversal fold (RF) greater than 5. Among them, 10 μM of derivative 37 (new compound) showed the outstanding activity (RF: 15.31) in reversing MDR in A549/Tax cells. Compound 37 could act as a substrate for P-gp and inhibit the efflux function of P-gp by competitively binding to the binding site of antitumor drugs. Meanwhile, the molecular docking results confirmed that compound 37 was identified to under-go high-affinity binding to the drug binding site of P-gp. In addition, 14 endogenous differential metabolites and 6 metabolic pathways involved closely associated with the reversal of tumor MDR effects of compound 37 were identified. (4) Conclusions: Overall, a new candidate compound 37 (24S-3-L-threonyl-Pyxinol) could be provided for reversing tumor MDR by this study.

Vitamin E, a potent antioxidant, is a necessary and complex micronutrient for cows. During the transition period, vitamin E deficiency (VED) is among the highest prevalent micronutrient deficits in dairy cows. It may eventually result in oxidative stress and immunological malfunction, and it increases the risk of peripartum disorders. At present, detailed data on blood metabolites in VED cows are limited. Consequently, the purpose of this research was to examine the alterations in the serum metabolic profile of VED cows throughout the early postpartum period. Using comprehensive 1H nuclear magnetic resonance (1H NMR), the alterations in serum metabolic activities of VED cows were analyzed. In total, 28 multiparous Holstein cows were assigned according to serum α-tocopherol (α-Toc) concentrations into a normal (α-Toc ≥ 4 μg/mL, n = 14) and VED (α-Toc &lt; 3 μg/mL, n = 14) groups at 21 days postpartum, and their blood samples were collected for biochemical and 1H NMR analyses. A t-test on independent samples as well as multivariate statistics were used to assess the findings. In comparison with normal cows, VED cows showed significantly worse body condition scores, milk yield, and dry matter intake (p &lt; 0.05). Significantly higher levels of serum non-esterified fatty acids, aspartate aminotransferase, low-density lipoprotein, and malonaldehyde were found in VED-affected cows, as well as lesser concentrations of serum albumin, high-density lipoprotein, and total antioxidant capacity in comparison with normal cows (p &lt; 0.01), while other vitamins and minerals concentrations showed no distinction between the groups (p &gt; 0.05). Furthermore, 24 upregulated serum metabolites were identified under VED conditions. The metabolomics pathway analysis of these metabolites demonstrated that a global metabolic response to VED in cows was represented by changes in 11 metabolic pathways, comprising energy, carbohydrate, and amino acid metabolism. These outcomes suggest that VED cows were more likely to experience a negative energy balance characterized by alterations of common systemic metabolic processes and develop oxidative stress, inflammation, and ultimately liver injury. This study provides the first evidence of metabolic changes in cows with VED.

The global prevalence of insulin resistance (IR) is increasing continuously, influencing metabolic parameters and fertility as well. The metabolic changes due to IR can alter the molecular composition of plasma and other body fluids. Follicular fluid (FF) is derived mainly from plasma, and it is a critical microenvironment for the developing oocytes. It contains various metabolites and amino acids, and the quality of the oocytes is linked at least partially to amino acid metabolism. Our goal was to determine quantitatively the amino acid (AA) profile of FF in IVF patients and to compare IR and non-insulin resistance (NIR) groups to investigate the AA changes in their FF. By UHPLC-based method we quantified the main 20 amino acids from human FF samples in the IR and NIR groups. Several amino acids (aspartate, glycine, glutamate, and cysteine) differed significantly (p&lt;0.05 or less) between the two groups. The most significant alterations between the IR and NIR groups were related to the glutathione metabolic pathway involving glycine, serine, and threonine. Since insulin resistance alters the amino acid composition of the FF, the oocytes may undergo metabolism-induced changes resulting in poor oocyte quality and less fertility in the insulin resistance groups.

Cathodic protection is widely used to protect metal structures from corrosion and is commonly applied on marine structures in seaports using sacrificial galvanic anodes. These anodes, either in Zinc, or preferen-tially nowadays in Al-Zn-In alloys, are expected to corrode instead of the metal to be protected. This leads to the release of specific dissolved species, Zn2+, Al3+, In3+ and solid phases like Al(OH)3. Few studies were conducted on the effects of anodes on marine organisms and concluded that further detailed investiga-tions are needed in controlled environments. We therefore propose an experimental approach to evaluate the effects of Zn and Al-Zn-In anodes on oysters stabulated in tanks, under conditions approaching those used in the ports. We chose a non-targeted metabolomic approach, using UHPLC coupled to HRMS, to study the effects on the entire metabolome, without any a priori. A modelling study of the chemical species, corresponding to the deg-radation products of the anodes, likely to be present near the exposed oysters, was also included. We identified 16 and 2 metabolites modulated by Zn- and Al-Zn-In-anodes respectively, involved in bi-ological functions, such as energy metabolism, osmoregulation, oxidative stress, lipid, nucleotide nucle-oside and amino acid metabolisms, defense and signaling pathways.

The ‘inverse problem’ of mass spectrometric molecular identification (‘given a mass spectrum, calculate/predict the 2D structure of the molecule whence it came’) is largely unsolved, and is especially acute in metabolomics where many small molecules remain unidentified. This is largely because the number of experimentally available electrospray mass spectra of small molecules is quite limited. However, the forward problem (‘calculate a small molecule’s likely fragmentation and hence at least some of its mass spectrum from its structure alone’) is much more tractable, because the strengths of different chemical bonds are roughly known. This kind of molecular identification problem may be cast as a language translation problem in which the source language is a list of high-resolution mass spectral peaks and the ‘translation’ a representation (for instance in SMILES) of the molecule. It is thus suitable for attack using the deep neural networks known as transformers. We here present MassGenie, a method that uses a transformer-based deep neural network, trained on ~6 million chemical structures with augmented SMILES encoding and their paired molecular fragments as generated in silico, explicitly including the protonated molecular ion. This architecture (containing some 400 million elements) is used to predict the structure of a molecule from the various fragments that may be expected to be observed when some of its bonds are broken. Despite being given essentially no detailed nor explicit rules about molecular fragmentation methods, isotope patterns, rearrangements, neutral losses, and the like, MassGenie learns the effective properties of the mass spectral fragment and valency space, and can generate candidate molecular structures that are very close or identical to those of the ‘true’ molecules. We also use VAE-Sim, a previously published variational autoencoder, to generate candidate molecules that are ‘similar’ to the top hit. In addition to using the ‘top hits’ directly, we can produce a rank order of these by ‘round-tripping’ candidate molecules and comparing them with the true molecules, where known. As a proof of principle, we confine ourselves to positive electrospray mass spectra from molecules with a molecular mass of 500Da or lower, including those in the last CASMI challenge (for which the results are known), getting 49/93 (53%) precisely correct. The transformer method, applied here for the first time to mass spectral interpretation, works extremely effectively both for mass spectra generated in silico and on experimentally obtained mass spectra from pure compounds. It seems to act as a Las Vegas algorithm, in that it either gives the correct answer or simply states that it cannot find one. The ability to create and to ‘learn’ millions of fragmentation patterns in silico, and therefrom generate candidate structures (that do not have to be in existing libraries) directly, thus opens up entirely the field of de novo small molecule structure prediction from experimental mass spectra.

Previous research has shown that propolis has immunomodulatory activity. Extracts from two UK propolis samples were assessed for their anti-inflammatory activities by investigating their ability to alter the production of the cytokines tumour necrosis factor-α (TNF-α), interleukin-1β (IL-1β), IL-6 and IL-10 from mouse bone marrow derived macrophages co-stimulated with lipopolysaccharide (LPS). The propolis extracts suppressed secretion of IL-1β and IL-6 with less effect on TNFα. In addition, propolis reduced the levels of nitric oxide formed by LPS-stimulated macrophages. Metabolomic profiling was carried out by liquid chromatography (LC) coupled with mass spectrometry (MS) on a ZIC-pHILIC column. LPS increased the levels of intermediates involved in nitric oxide biosynthesis; propolis lowered many of these. Also, LPS produced an increase in itaconate and citrate and propolis treatment increased itaconate still further while greatly reducing citrate levels. Moreover, LPS treatment increased levels of GSH and intermediates in its biosynthesis while propolis treatment boosted these still further. In addition, propolis treatment greatly increased levels of UDP-sugar conjugates. Overall, the results showed that propolis extracts exert an anti-inflammatory effect by inhibition of pro-inflammatory cytokines and by metabolic reprogramming of LPS activity in macrophages.

Acylsugars constitute an abundant class of pest- and pathogen-protective Solanaceae family plant specialized metabolites produced in secretory glandular trichomes. Solanum pennellii produces copious triacylated sucrose and glucose esters, and the core biosynthetic pathway producing these compounds was previously characterized. We performed untargeted metabolomic analysis of S. pennellii surface metabolites from accessions spanning the species range, which indicated geographic trends in acylsugar profile and revealed two compound classes previously undescribed from this species, tetraacylglucoses and flavonoid aglycones. A combination of ultrahigh performance liquid chromatography high resolution mass spectrometry (UHPLC-HR-MS) and NMR spectroscopy identified variations in number, length, and branching pattern of acyl chains, and the proportion of sugar cores in acylsugars among accessions. The new dimensions of acylsugar variation revealed by this analysis further indicate variation in the biosynthetic and degradative pathways responsible for acylsugar accumulation. These findings provide a starting point for deeper investigation of acylsugar biosynthesis, an understanding of which can be exploited through crop breeding or metabolic engineering strategies to improve endogenous defenses of crop plants.

Hang-ju was one of five officinal varieties of Flos chrysanthemum for its edible and potable usage. Besides Flos Chrysanthemum (FL), there were also Bud Chrysanthemum (BC) and Fetal Chrysanthemum (FC) at the early and late stage of buds, respectively, in the consumption market of Hang-ju with higher prices. Whether the quality and efficiency of BC and FC was superior to FL or merely consumption misunderstandings? Three commercial products of Hongxinju, a representive cultivar of Hang-ju were studied with a GC-MS based metabolomics approach, complemented with morphology, contents of moisture and protein and the anti-oxidant activity, to reveal the metabolic alterations of violate components in Hongxinju in different flowering stage and at different processing periods. It revealed that most of the violate components were increased from fresh FC to FL, and the low-boiling fractions, inflammatory methyl arachidonate and air-polluting component of ethylbenzene were declined while the representative components with pungent flavor and cool nature of a-curcumene and (Z,Z,Z)-9,12,15-octadecatrienoic acid, vision improving carotenol of rhodopin and high-boiling fractions were elevated after processed in final FL compared with that in BC and/or FC. Though the content of protein and anti-oxidative capacity of final BC and FC were nearly equal to those of FL, in comprehensive consideration of the representative components related with the efficiency in heat cooling and vision improving, as well as the representative components related with inflammation and air-pollution, final FL was recommended other than BC and FC in the practice of medicine with the yield and quality integrated into account.

As metabolomics is widely used in the study of disease mechanisms, more and more studies have found that metabolites play an important role in the occurrence of diseases. The aim of this study is to investigate the effects and mechanisms of quercetin in high-fat-sucrose diet (HFD)-induced nonalcoholic fatty liver disease (NAFLD) development using nontargeted metabolomics. A rat model of NAFLD was established by feeding with a HFD for 30 and 50 days. Results indicated quercetin exhibited hepatoprotective activity in HFD-induced NAFLD rats in 30 days by regulating fatty acids related metabolites (adrenic acid, etc.), inflammation related metabolites (arachidonic acid, etc.), oxidative stress related metabolites (2-hydroxybutyric acid) and other differential metabolites (citric acid, etc.). However, quercetin couldn’t improve NAFLD in 50 days maybe it couldn’t reverse the inflammation condition induced by long-term high-fat diet. These data indicate that dietary quercetin may be beneficial to NAFLD at early stages. Furthermore, combining metabolomics and experimental approaches opens up avenues of effects and mechanisms of drugs for complex diseases.

Bibliometric studies on inherited metabolic diseases(IMDs) didn't exist in the literature.Our research aims to conduct a bibliometric study to determine the current status,trending topics,and missing points of publications on IMDs.Between 1968-2023, we conducted a literature search with keyword "inherited metabolic disease" in the SCOPUS-database.We included research articles in medicine written in English,published in the final section.We created our data pool using VoSviewer, SciMAT, and Rstudio software programs for bibliometric parameters of the articles that met the inclusion criteria.We performed bibliometric analysis of the data with R-package "bibliometrix" and BibExcel programs.We included 2702 research articles published on IMDs.Top three countries that have written the most articles in this field are; USA(n= 501), United Kingdom(n=182), and China(n= 172).The most preferred keywords by the authors were;newborn screening(n=54), mutation(n=43), phenylketonuria(n=42), children(n=35), genetics(n= 34) and maple syrup urine disease(n=32).Trending topics were osteoporosis, computed tomography, bone marrow transplantation in the early years of the study, chronic kidney disease, urea cycle disorders, next-generation sequencing, newborn screening, and familial hypercholesterolemia in the final years of the study. This study provides clinicians with a new perspective showing that molecular and genetic studies in inherited metabolic diseases will play an essential role in diagnosis and treatment in the future.

The increasing prevalence of depression worldwide requires more effectiveness in therapy approaches and a molecular understanding of antidepressants mode of action. We carried out untargeted metabolomics of the prefrontal cortex of rats exposed to chronic social isolation (CSIS), a rat model of depression, and/or fluoxetine treatment using liquid chromatography-high resolution mass spectrometry. The behavioral phenotype was assessed by the forced swim test. To analyze metabolomics data, univariate and multivariate analysis and biomarker capacity assessment using the classical receiver operating characteristic (ROC) curve were used. Support vector machine-linear kernel (SVM-LK), as a machine-learning algorithm was performed for binary classification. Upregulated myo-inositol following CSIS may represent a potential marker of depressive phenotype. Effective fluoxetine treatment reversed depressive-like behavior and increased sedoheptulose 7-phosphate, hypotaurine, and acetyl-L-carnitine contents, which were identified as potential markers. We identified 4 or 10 marker candidates with ROC curve greater than 0.9 for CSIS or fluoxetine effectiveness designation. SVM-LK has given accuracy of 61.50%, or 93.30%, and 7 or 25 predictive metabolites for CSIS vs. control and fluoxetine-treated CSIS vs. CSIS classification. Overall, metabolic fingerprints combined with ROC curve and SVM-LK may represent a new approach to identifying potential markers or predicting metabolites for group designation or classification.

Cutaneous melanoma (CM) patients respond better to immune checkpoint inhibitors (ICI) than mucosal and uveal melanoma patients (MM/UM). Aiming to explore these differences and understand the distinct response to ICI, we evaluated the serum metabolome of advanced CM, MM, and UM patients. Levels of 115 metabolites were analyzed in samples collected before ICI, using a targeted metabolomics platform. In our analysis, molecules involved in the tryptophan-kynurenine axis distinguished UM/MM from CM. UM/MM patients had higher levels of 3-hydroxykynurenine (3-HKyn), whilst patients with CM were found to have higher levels of kynurenic acid (KA). The KA/3-HKyn ratio was significantly higher in CM versus the other subtypes. UM, the most ICI-resistant subtype, was also associated with higher levels of sphingomyelin-d18:1/22:1 and the polyamine spermine (SPM). Overall survival was prolonged in patients with lower SPM levels. Our study revealed distinct metabolomic profile between the most resistant melanoma subtypes, UM and MM, compared to CM. Alterations within the kynurenine pathway, polyamine metabolism and sphingolipid metabolic pathway may contribute to the poor response to ICI. Understanding the different metabolomic profiles introduces opportunities for novel therapies with potential synergic activity to ICI, to improve responses of UM/MM.

BACKGROUND. Two sequelae of non-alcoholic steatohepatitis (NASH), ESLD and HCC, have become the leading causes for liver transplantation in the Western. The present study aims to approach the cellular metabolic disturbances involved in NASH progression that are associated with microbiota community changes. METHODS. Metabolic effects and microbiota community changes were explored in the murine with NASH progression by blocking the Na/K-ATPase/Src/reactive oxygen amplification loop using the synthetic targeting peptide pNaKtide. DNA from the terminal ileum microbiota habitat was obtained and amplified by PCR to develop DNA bacterial phylogenic sequence analysis of wild type and treated animals at 12, 24 and 48 weeks. Induced changes by pSrc normalization at 24 weeks were correlated with liver morphological changes, intestinal CD4+/CD8+ ratio, and liver macrophage CD14+ expression. Differences among groups were evaluated by ANOVA/t-test and Principal Component Analysis (PCA). RESULTS. Microbiota communities varied significantly at all time points (12, 24 and 48 weeks), with an increase of Verrucomicrobia and a decrease of Bacteroidetes and Firmicutes in the HFD group. Microbiota community changes regressed to their wild-type state at 24 weeks on treated animals, and those changes were associated with a decrease in liver inflammation and senescence, lower ileum CD4+/CD8+ T cells and higher liver CD14+ cells (p<0.05). Concomitantly, the metabolic disturbances in our diet-induced NASH model were normalized by NKA/Src signaling blockage and exercise with a paucity of apoptotic activity, mitigation of cell senescence, and regression of liver fibrosis (p<0.01). CONCLUSIONS. pSrc inhibition at caveolar α1-Na/K-ATPase rescinded NASH-related metabolic disturbances establishing resident physiological microbiota communities with concomitant paucity on apoptotic activity and regression of liver fibrosis; effects that were associated with both gut and liver T-lymphocyte responses.