Discriminant Metabolites Research Articles

Multi-omics approach to understand the impact of sun exposure on an in vitro skin ecosystem and evaluate a new broad-spectrum sunscreen.

A reconstructed human epidermal model (RHE) colonized with human microbiota and sebum was developed to reproduce the complexity of the skin ecosystem in vitro. The RHE model was exposed to simulated solar radiation (SSR) with or without SPF50+ sunscreen (with UVB, UVA, long-UVA, and visible light protection). Structural identification of discriminant metabolites was acquired by nuclear magnetic resonance and metabolomic fingerprints were identified using reverse phase-ultra high-performance liquid chromatography-high resolution mass spectrometry, followed by pathway enrichment analysis. Over 50 metabolites were significantly altered by SSR (p < 0.05, log2 values), showing high skin oxidative stress (glutathione and purine pathways, urea cycle) and altered skin microbiota (branched-chain amino acid cycle and tryptophan pathway). 16S and internal transcribed spacer rRNA sequencing showed the relative abundance of various bacteria and fungi altered by SSR. This study identified highly accurate metabolomic fingerprints and metagenomic modifications of sun-exposed skin to help elucidate the interactions between the skin and its microbiota. Application of SPF50+ sunscreen protected the skin ecosystem model from the deleterious effects of SSR and preserved the physiological interactions within the skin ecosystem. These innovative technologies could thus be used to evaluate the effectiveness of sunscreen.

Maize kernel metabolome involved in resistance to fusarium ear rot and fumonisin contamination.

Fusarium verticillioides poses a threat to worldwide maize production due to its ability to infect maize kernel and synthesize fumonisins that can be accumulated above safety levels for humans and animals. Maize breeding has been proposed as key tool to decrease kernel contamination with fumonisins, but metabolic studies complementary to genomic approaches are necessary to disclose the complexity of maize resistance. An untargeted metabolomic study was proposed using inbreds genetically related but with contrasting levels of resistance in order to uncover pathways implicated in resistance to Fusarium ear rot (FER) and fumonisin contamination in the maize kernel and to look for possible biomarkers. Metabolite determinations were performed in kernels collected at 3 and 10 days after inoculation with F. verticillioides (dat). Discriminant metabolites between resistant and susceptible RILs were rather found at 10 than 3 dat, although metabolite differences at later stages of colonization could be driven by subtle variations at earlier stages of infection. Within this context, differences for membrane lipid homeostasis, methionine metabolism, and indolacetic acid conjugation seemed highly relevant to distinguish between resistant and susceptible inbreds, confirming the polygenic nature of resistance to FER and fumonisin contamination in the maize kernels. Nevertheless, some specific metabolites such as the polyamine spermidine and/or the alkaloid isoquinoline seemed to be promising indirect selection traits to improve resistance to FER and reduce fumonisin accumulation. Therefore, in vitro and in vivo experiments will be necessary to validate the inhibitory effects of these compounds on fumonisins biosynthesis.

Taming Food-Drug Interaction Risk: Potential Inhibitory Effects of Citrus Juices on Cytochrome Liver Enzymes Can Safeguard the Liver from Overdose Paracetamol-Induced Hepatotoxicity.

Paracetamol overdose is the leading cause of drug-induced hepatotoxicity worldwide. Because of N-acetyl cysteine's limited therapeutic efficacy and safety, searching for alternative therapeutic substitutes is necessary. This study investigated four citrus juices: Citrus sinensis L. Osbeck var. Pineapple (pineapple sweet orange), Citrus reticulata Blanco × Citrus sinensis L. Osbeck (Murcott mandarin), Citrus paradisi Macfadyen var. Ruby Red (red grapefruit), and Fortunella margarita Swingle (oval kumquat) to improve the herbal therapy against paracetamol-induced liver toxicity. UHPLC-QTOF-MS/MS profiling of the investigated samples resulted in the identification of about 40 metabolites belonging to different phytochemical classes. Phenolic compounds were the most abundant, with the total content ranked from 609.18 to 1093.26 μg gallic acid equivalent (GAE)/mL juice. The multivariate data analysis revealed that phloretin 3',5'-di-C-glucoside, narirutin, naringin, hesperidin, 2-O-rhamnosyl-swertisin, fortunellin (acacetin-7-O-neohesperidoside), sinensetin, nobiletin, and tangeretin represented the crucial discriminatory metabolites that segregated the analyzed samples. Nevertheless, the antioxidant activity of the samples was 1135.91-2913.92 μM Trolox eq/mL juice, 718.95-3749.47 μM Trolox eq/mL juice, and 2304.74-4390.32 μM Trolox eq/mL juice, as revealed from 2,2'-azino-bis-3-ethylbenzthiazoline-6-sulfonic acid, ferric-reducing antioxidant power, and oxygen radical absorbance capacity, respectively. The in vivo paracetamol-induced hepatotoxicity model in rats was established and assessed by measuring the levels of hepatic enzymes and antioxidant biomarkers. Interestingly, the concomitant administration of citrus juices with a toxic dose of paracetamol effectively recovered the liver injury, as confirmed by normal sections of hepatocytes. This action could be due to the interactions between the major identified metabolites (hesperidin, hesperetin, phloretin 3',5'-di-C-glucoside, fortunellin, poncirin, nobiletin, apigenin-6,8-digalactoside, 6',7'-dihydroxybergamottin, naringenin, and naringin) and cytochrome P450 isoforms (CYP3A4, CYP2E1, and CYP1A2), as revealed from the molecular docking study. The most promising compounds in the three docking processes were hesperidin, fortunellin, poncirin, and naringin. Finally, a desirable food-drug interaction was achieved in our research to overcome paracetamol overdose-induced hepatotoxicity.

Changes of gut mycobiota in the third trimester of pregnant women with preeclampsia

Objective Studies recently acknowledged that the fungal community in the gut plays an important role in many inflammatory diseases of noninfectious origin. but the role of gut fungi in the pathogenesis of preeclampsia (PE) remains unknown. Methods We performed a case-case–control study to compare the gut mycobiota of PE, pregnancy with chronic hypertension (PCH), and the normal group (Normal pregnancy group without any underlying disease) by internal transcribed spacer sequencing. In addition, LC/MS was used to explore the relationship between the fecal metabolites and gut mycobiota. Results Compared with the PCH and the normal group, α diversity (represented the species abundance in a single sample) of mycobiota were lower in the PE group, but there was no statistically significant difference among these three groups. However, Linear discriminant analysis Effect Size (LEfSe) analysis found 3 differentially abundant fungal taxa in PE group when compared with the normal group. The gut metabolites of PE patients were significantly different from PCH and the normal group. Choline metabolism molecule glycerophosphocholine was the most discriminant metabolite between PE and the normal group. Correlation analysis found that Candida spp.was positively correlated with glycerophosphocholine which increased in PE. Conclusion We found that gut mycobiota changed in the third trimester of pregnant women with preeclampsia.

Serum Metabolome Signatures Characterizing Co-Infection of Plasmodium falciparum and HBV in Pregnant Women.

Plasmodium falciparum (P. falciparum) and hepatitis B virus (HBV) co-infection is on the rise among pregnant women in northern Ghana. Mono-infection with either of these two pathogens results in unique metabolic alterations. Thus, we aimed to explicate the effects of this co-infection on the metabolome signatures of pregnant women, which would indicate the impacted metabolic pathways and provide useful prognostic or diagnostic markers. Using an MS/MS-based targeted metabolomic approach, we determined the serum metabolome in pregnant women with P. falciparum mono-infection, HBV mono-infection, P. falciparum, and HBV co-infection and in uninfected (control) women. We observed significantly decreased sphingolipid concentrations in subjects with P. falciparum mono-infection, whereas amino acids and phospholipids were decreased in subjects with HBV mono-infection. Co-infections were found to be characterized distinctively by reduced concentrations of phospholipids and hexoses (mostly glucose) as well as altered pathways that contribute to redox homeostasis. Overall, PC ae C40:1 was found to be a good discriminatory metabolite for the co-infection group. PC ae C40:1 can further be explored for use in the diagnosis and treatment of malaria and chronic hepatitis B co-morbidity as well as to distinguish co-infections from cases of mono-infections.

The Sizes and Composition of HDL-Cholesterol Are Significantly Associated with Inflammation in Rheumatoid Arthritis Patients.

Rheumatoid arthritis (RA), a chronic inflammatory disease, carries a significant burden of atherosclerotic cardiovascular diseases (ASCVD). With their heterogeneous composition, high-density lipoprotein (HDL) particles have varied athero-protective properties, and some may even increase ASCVD risk. In this prospective and cross-sectional study, we aimed to examine the relationship between HDL sizes/metabolites and inflammation in RA. Using 1H-NMR-based lipid/metabolomics, differential HDL-related metabolites were identified between RA patients and healthy control (HC) subjects and between RA patients with and without anti-citrullinated peptide antibodies (ACPA). The correlation between the discriminative HDL-related metabolites and C-reactive protein (CRP) was evaluated in RA patients. RA patients demonstrated higher particle number, lipids, cholesterol, cholesterol ester, free cholesterol, and phospholipids in large/very large-sized HDLs. ACPA-positive patients had higher L-HDL-C and L-HDL-CE but lower small-/medium-sized HDL-TG levels than ACPA-negative patients. An inverse correlation was found between CRP levels and small-sized HDLs. Janus kinase inhibitor treatment was associated with increased serum small-sized HDL-related metabolites and decreased CRP levels. We are the first to reveal the significant associations between RA inflammation and HDL sizes/metabolites. A potential link between ACPA positivity and changes in serum levels of HDL-related metabolites was also observed in RA patients.

Stachydrine, N-acetylornithine and trimethylamine N-oxide levels as candidate milk biomarkers of maternal consumption of an obesogenic diet during lactation.

We aimed to evaluate whether improving maternal diet during lactation in diet-induced obese rats reverts the impact of western diet (WD) consumption on the metabolome of milk and offspring plasma, as well as to identify potential biomarkers of these conditions. Three groups of dams were followed: control-dams (CON-dams), fed with standard diet (SD); WD-dams, fed with WD prior and during gestation and lactation; and reversion-dams (REV-dams), fed as WD-dams but moved to SD during lactation. Metabolomic analysis was performed in milk at lactation days 5, 10, and 15, and in plasma from their male and female offspring at postnatal day 15. Milk of WD-dams presented, throughout lactation and compared to CON-dams, altered profiles of amino acids and of the carnitine pool, accompanied by changes in other polar metabolites, being stachydrine, N-acetylornithine, and trimethylamine N-oxide the most relevant and discriminatory metabolites between groups. The plasma metabolome profile was also altered in the offspring of WD-dams in a sex-dependent manner, and stachydrine, ergothioneine and the acylcarnitine C12:1 appeared as the top three most discriminating metabolites in both sexes. Metabolomic changes were largely normalized to control levels both in the milk of REV-dams and in the plasma of their offspring. We have identified a set of polar metabolites in maternal milk and in the plasma of the offspring whose alterations may indicate maternal intake of an unbalanced diet during gestation and lactation. Levels of these metabolites may also reflect the beneficial effects of implementing a healthier diet during lactation.

Cross-Sectional Study: New Approach for Diagnostic Identification of Non-Robust Older Adult.

The aging biomarkers are alternatives and none of them can act as a strong predictor of frailty during the progression of aging. Several studies reveal the relationship between metabolites and frailty or gut microbiota and frailty. However, the connection between metabolites and gut microbiota in non-robust older adults has not been discussed yet. The study aims to combine the findings of serum metabolites and gut microbiota in non-robust subjects as a possible diagnostic biomarker. Frailty-related assessments are conducted to ensure the discrimination of non-robustness. The serum and fecal are collected for serum metabolomics and gut microbiota analysis. Robust and non-robust subjects show very different gut microbial compositions. Among the gut microbial differences, Escherichia/Shigella and its higher taxonomic ranks are found to have the most discriminative abundance among compared groups. More importantly, the abundance of Escherichia/Shigella is found to be positively correlated (p < 0.05) with the level of discriminant metabolites, such as serum oxoglutarate, glutamic acid, and 1-methyladenosine. These results indicate the obvious interrelation between gut microbiota and serum metabolites in non-robust older adults. Besides, the findings suggest that Escherichia/Shigella can be a potential biomarker candidate for robustness sub-phenotypic identification.

Metabolic Reprogramming of Barley in Response to Foliar Application of Dichlorinated Functional Analogues of Salicylic Acid as Priming Agents and Inducers of Plant Defence

Designing innovative biological crop protection strategies to stimulate natural plant immunity is motivated by the growing need for eco-friendly alternatives to conventional biocidal agrochemicals. Salicylic acid (SA) and analogues are known chemical inducers of priming plant immunity against environmental stresses. The aim of the study was to study the metabolic reprogramming in barley plants following an application of three proposed dichlorinated inducers of acquired resistance. 3,5-Dichloroanthranilic acid, 2,6-dichloropyridine-4-carboxylic acid, and 3,5-dichlorosalicylic acid were applied to barley at the third leaf stage of development and harvested at 12, 24, and 36 h post-treatment. Metabolites were extracted using methanol for untargeted metabolomics analyses. Samples were analysed by ultra-high performance liquid chromatography coupled to high-definition mass spectrometry (UHPLC-HDMS). Chemometric methods and bioinformatics tools were used to mine and interpret the generated data. Alterations in the levels of both primary and secondary metabolites were observed. The accumulation of barley-specific metabolites, hordatines, and precursors was observed from 24 h post-treatment. The phenylpropanoid pathway, a marker of induced resistance, was identified among the key mechanisms activated by the treatment with the three inducers. No salicylic acid or SA derivatives were annotated as signatory biomarkers; instead, jasmonic acid precursors and derivatives were found as discriminatory metabolites across treatments. The study highlights differences and similarities in the metabolomes of barley after treatment with the three inducers and points to the triggering chemical changes associated with defence and resistance. This report is the first of its kind, and the knowledge acquired provides deeper insight into the role of dichlorinated small molecules as inducers of plant immunity and can be used in metabolomics-guided plant improvement programmes.

Metabolomic profiling to identify early urinary biomarkers and metabolic pathway alterations in autosomal dominant polycystic kidney disease.

Autosomal dominant polycystic kidney disease (ADPKD) is characterized by the formation of numerous fluid-filled cysts that lead to progressive loss of functional nephrons. Currently, there is an unmet need for diagnostic and prognostic indicators of early stages of the disease. Metabolites were extracted from the urine of patients with early-stage ADPKD (n = 48 study participants) and age- and sex-matched normal controls (n = 47) and analyzed by liquid chromatography-mass spectrometry. Orthogonal partial least squares-discriminant analysis was used to generate a global metabolomic profile of early ADPKD for the identification of metabolic pathway alterations and discriminatory metabolites as candidates of diagnostic and prognostic biomarkers. The global metabolomic profile exhibited alterations in steroid hormone biosynthesis and metabolism, fatty acid metabolism, pyruvate metabolism, amino acid metabolism, and the urea cycle. A panel of 46 metabolite features was identified as candidate diagnostic biomarkers. Notable putative identities of candidate diagnostic biomarkers for early detection include creatinine, cAMP, deoxycytidine monophosphate, various androgens (testosterone; 5-α-androstane-3,17,dione; trans-dehydroandrosterone), betaine aldehyde, phosphoric acid, choline, 18-hydroxycorticosterone, and cortisol. Metabolic pathways associated with variable rates of disease progression included steroid hormone biosynthesis and metabolism, vitamin D3 metabolism, fatty acid metabolism, the pentose phosphate pathway, tricarboxylic acid cycle, amino acid metabolism, sialic acid metabolism, and chondroitin sulfate and heparin sulfate degradation. A panel of 41 metabolite features was identified as candidate prognostic biomarkers. Notable putative identities of candidate prognostic biomarkers include ethanolamine, C20:4 anandamide phosphate, progesterone, various androgens (5-α-dihydrotestosterone, androsterone, etiocholanolone, and epiandrosterone), betaine aldehyde, inflammatory lipids (eicosapentaenoic acid, linoleic acid, and stearolic acid), and choline. Our exploratory data support metabolic reprogramming in early ADPKD and demonstrate the ability of liquid chromatography-mass spectrometry-based global metabolomic profiling to detect metabolic pathway alterations as new therapeutic targets and biomarkers for early diagnosis and tracking disease progression of ADPKD.NEW & NOTEWORTHY To our knowledge, this study is the first to generate urinary global metabolomic profiles from individuals with early-stage ADPKD with preserved renal function for biomarker discovery. The exploratory dataset reveals metabolic pathway alterations that may be responsible for early cystogenesis and rapid disease progression and may be potential therapeutic targets and pathway sources for candidate biomarkers. From these results, we generated a panel of candidate diagnostic and prognostic biomarkers of early-stage ADPKD for future validation.

A cross-sectional study identifying disparities in serum metabolic profiles among hypertensive patients with ISH, IDH and SDH subtypes.

It has been well acknowledged that disordered intestinal microflora and their fermented products play crucial role during the development of hypertension (HTN). Aberrant profiles of fecal bacteria have been documented in subjects with isolated systolic HTN (ISH) and isolated diastolic HTN (IDH) previously. Nevertheless, evidence regarding the association of metabolic products in the bloodstream with ISH, IDH and combined systolic and diastolic HTN (SDH) remains scarce. We performed a cross-sectional study and conducted untargeted liquid chromatography-mass spectrometry (LC/MS) analysis on serum samples of 119 participants, including 13 subjects with normotension (SBP < 120/DBP < 80 mm Hg), 11 individuals with ISH (SBP ≥ 130/DBP < 80 mm Hg), 27 patients with IDH (SBP < 130/DBP ≥ 80 mm Hg), and 68 SDH patients (SBP ≥ 130, DBP ≥ 80 mm Hg). Here, the results showed clearly separated clusters in PLS-DA and OPLS-DA score plots for patients suffering from ISH, IDH and SDH when compared with normotension controls. The ISH group was characterized by elevated levels of 3,5-tetradecadien carnitine and notable reduction of maleic acid. While IDH patients were enriched with metabolites in L-lactic acid and depleted in citric acid. Stearoylcarnitine was identified to be specifically enriched in SDH group. The differentially abundant metabolites between ISH and controls were involved in tyrosine metabolism pathways, and in biosynthesis of phenylalanine for those between SDH and controls. Potential linkages between the gut microbial and serum metabolic signatures were detected within ISH, IDH and SDH groups. Furthermore, we found the association of discriminatory metabolites with the characteristics of patients. Our findings demonstrate disparate blood metabolomics signatures across ISH, IDH and SDH, with differentially enriched metabolites and potential functional pathways identified, reveal the underlying microbiome and metabolome network in HTN subtypes, and provide potential targets for disease classification and therapeutic strategy in clinical practice.

Small molecule bio-signature in childhood intra-thoracic tuberculosis identified by metabolomics.

The diagnosis of pediatric tuberculosis (TB) remains a major challenge, hence the evaluation of new tools for improved diagnostics is urgently required. We investigated the serum metabolic profile of children with culture-confirmed intra-thoracic TB (ITTB) (n = 23) and compared it with those of non-TB controls (NTCs) (n = 13) using proton NMR spectroscopy-based targeted and untargeted metabolomics approaches. In targeted metabolic profiling, five metabolites (histidine, glycerophosphocholine, creatine/phosphocreatine, acetate, and choline) differentiated TB children from NTCs. Additionally, seven discriminatory metabolites (N-α-acetyl-lysine, polyunsaturated fatty acids, phenylalanine, lysine, lipids, glutamate + glutamine, and dimethylglycine) were identified in untargeted metabolic profiling. The pathway analysis revealed alterations in six metabolic pathways. The altered metabolites were associated with impaired protein synthesis, hindered anti-inflammatory and cytoprotective mechanisms, abnormalities in energy generation processes and membrane metabolism, and deregulated fatty acid and lipid metabolisms in children with ITTB. The diagnostic significance of the classification models obtained from significantly distinguishing metabolites showed sensitivity, specificity, and area under the curve of 78.2%, 84.6%, and 0.86, respectively, in the targeted profiling and 92.3%, 100%, and 0.99, respectively, in the untargeted profiling. Our findings highlight detectable metabolic changes in childhood ITTB; however, further validation is warranted in a large cohort of the pediatric population.

Impact of dry-off and lyophilized Aloe arborescens supplementation on plasma metabolome of dairy cows

Positive effects have been observed as a result of Aloe arborescens supplementation in the dry-off phase in dairy cows. Metabolomic approaches can provide additional information about animal physiology. Thus, we characterized plasma metabolome around dry-off in 12 cows supplemented (AL) or not (CTR) with 10 g/d of lyophilized A. arborescens with an untargeted metabolomic approach. Overall, 1658 mass features were annotated. Regardless of treatment, multivariate statistics discriminated samples taken before and after dry-off. Overall, 490 metabolites were different between late lactation and early dry period, of which 237 were shared between AL and CTR. The most discriminant compounds (pentosidine and luteolin 7-O-glucoside) were related to the more fibrous diet. Pathway analysis indicated that pyrimidine and glycerophospholipid metabolisms were down-accumulated, suggesting reduced rumen microbial activity and liver load. Samples from AL were discriminated from CTR either the day of dry-off or 7 days after. At dry-off, aloin and emodin were the most discriminant metabolites, indicating that Aloe's bioactive compounds were absorbed. Seven days later, 534 compounds were different between groups, and emodin was among the most impacted. Pathway analysis highlighted that glycerophospholipid, pyrimidine, and folate metabolisms were affected. These results might indicate that Aloe has positive effects on liver function and a modulatory effect on rumen fermentation.

An integrated strategy by chemical characterization, in vivo metabolism, chemical isolation, and activity evaluation to target discovery of potential active substances in traditional Chinese medicine: Mori Fructus as an example

Mori Fructus (MF) is a famous edible fruit of Morus alba L. as well as traditional Chinese medicine (TCM). Moreover, exposure behavior of complex components in vivo is a necessary way to elucidate active substances in TCMs. However, the effective discovery of active ingredients from MF in vivo is still a challenge for researchers. In this study, an integrated strategy with chemical characterization, in vivo metabolism, chemical isolation, and activity evaluation was established and applied in targeted discovery of potential lipid-lowering substances in MF. First, an ultra-performance liquid chromatography with quadrupole time-of-flight mass spectrometry method was established to characterize various chemical components in MF extract. Second, with the automatic matching (in-house database), discriminant ions analysis and metabolite software prediction, the metabolic profiling of different types of MF was elucidated in vivo. And the compounds from MF with high MS response in vivo were discovered. Third, according to LC-MS information of fractions, these compounds were isolated and identified by NMR. Finally, the isolated compounds were evaluated for the lipid-lowering activity on determination of triglyceride levels in high fructose-induced HepG2 cells at different concentrations. And PCSK9 inhibitory and LDL-R promoting activity were measured by western blot experiment. As a result, a total of 72 constituents were characterized in MF. After oral administration of MF extract, 16 prototypes and 33 metabolites were rapidly screened out. And the metabolism features of alkaloids, flavonols and organic acids were further revealed. Six alkaloids (morusimic acid A-D, G, F), with high MS response in vivo and no reference standards on the market, were isolated guided by LC-MS and identified by NMR. Among them, morusimic acid A, B, G and F could reduce triglyceride levels in fructose-induced HepG2 cells. Moreover, with western blot experiment, morusimic acid A, B, G and F could inhibit the expression of PCSK9 protein. And morusimic acid A, B and F could increase the expression of LDL-R protein. This work provides meaningful information for the discovery of potential compounds in MF for the treatment of obesity and hyperlipidemia, along with a new approach for exploring effective compounds from complex systems.

Urinary Metabolomics Identified Metabolic Perturbations Associated with Gutka, a Smokeless Form of Tobacco.

Gutka, a form of smokeless tobacco, is widely used in the Indian subcontinent and in other regions of South Asia. Smokeless tobacco exposure is most likely to increase the incidence of oral cancer in the Indian population, and metabolic changes are a hallmark of cancer. The development of biomarkers for early detection and better prevention measures for smokeless tobacco users at risk of oral cancer can be aided by studying urinary metabolomics and offering insight into altered metabolic profiles. This study aimed to investigate urine metabolic alterations among smokeless tobacco users using targeted LC-ESI-MS/MS metabolomics approaches to better understand the effects of smokeless tobacco on human metabolism. Smokeless tobacco users' specific urinary metabolomics signatures were extracted using univariate, multivariate analysis and machine learning methods. Statistical analysis identified 30 urine metabolites significantly associated with metabolomic alterations in humans who chew smokeless tobacco. Receiver operator characteristic (ROC) curve analysis evidenced the 5 most discriminatory metabolites from each approach that could differentiate between smokeless tobacco users and controls with higher sensitivity and specificity. An analysis of multiple-metabolite machine learning models and single-metabolite ROC curves revealed discriminatory metabolites capable of distinguishing smokeless tobacco users from nonusers more effectively with higher sensitivity and specificity. Furthermore, metabolic pathway analysis depicted several dysregulated pathways in smokeless tobacco users, including arginine biosynthesis, beta-alanine metabolism, TCA cycle, etc. This study devised a novel strategy to identify exposure biomarkers among smokeless tobacco users by combining metabolomics and machine learning algorithms.

Performance comparison of three scaling algorithms in NMR-based metabolomics analysis.

Unit variance (UV) scaling, mean centering (CTR) scaling, and Pareto (Par) scaling are three commonly used algorithms in the preprocessing of metabolomics data. Based on our NMR-based metabolomics studies, we found that the clustering identification performances of these three scaling methods were dramatically different as tested by the spectra data of 48 young athletes' urine samples, spleen tissue (from mice), serum (from mice), and cell (from Staphylococcus aureus) samples. Our data suggested that for the extraction of clustering information, UV scaling could serve as a robust approach for NMR metabolomics data for the identification of clustering analysis even with the existence of technical errors. However, for the purpose of discriminative metabolite identification, UV scaling, CTR scaling, and Par scaling could equally extract discriminative metabolites efficiently based on the coefficient values. Based on the data presented in this study, we propose an optimal working pipeline for the selection of scaling algorithms in NMR-based metabolomics analysis, which has the potential to serve as guidance for junior researchers working in the NMR-based metabolomics research field.

Uveal Melanoma Patients Have a Distinct Metabolic Phenotype in Peripheral Blood.

Uveal melanomas (UM) are detected earlier. Consequently, tumors are smaller, allowing for novel eye-preserving treatments. This reduces tumor tissue available for genomic profiling. Additionally, these small tumors can be hard to differentiate from nevi, creating the need for minimally invasive detection and prognostication. Metabolites show promise as minimally invasive detection by resembling the biological phenotype. In this pilot study, we determined metabolite patterns in the peripheral blood of UM patients (n = 113) and controls (n = 46) using untargeted metabolomics. Using a random forest classifier (RFC) and leave-one-out cross-validation, we confirmed discriminatory metabolite patterns in UM patients compared to controls with an area under the curve of the receiver operating characteristic of 0.99 in both positive and negative ion modes. The RFC and leave-one-out cross-validation did not reveal discriminatory metabolite patterns in high-risk versus low-risk of metastasizing in UM patients. Ten-time repeated analyses of the RFC and LOOCV using 50% randomly distributed samples showed similar results for UM patients versus controls and prognostic groups. Pathway analysis using annotated metabolites indicated dysregulation of several processes associated with malignancies. Consequently, minimally invasive metabolomics could potentially allow for screening as it distinguishes metabolite patterns that are putatively associated with oncogenic processes in the peripheral blood plasma of UM patients from controls at the time of diagnosis.

Untargeted Metabolomics Combined with Sensory Analysis to Evaluate the Chemical Changes in Coppa Piacentina PDO during Different Ripening Times.

Ripening time is known to drive the chemical and sensory profiles of dry meat products, thus potentially affecting the final quality of the product. Starting from these background conditions, the aim of this work was to shed light, for the first time, on the chemical modifications of a typical Italian PDO meat product-namely, Coppa Piacentina-during ripening, to find correlations between its sensory quality and the biomarker compounds related to the progress of ripening. The ripening time (from 60 to 240 days) was found to deeply modify the chemical composition of this typical meat product, providing potential biomarkers of both oxidative reactions and sensory attributes. The chemical analyses revealed that there is typically a significant decrease in the moisture content during ripening, likely due to increased dehydration. In addition, the fatty acid profile showed that the distribution of polyunsaturated fatty acids significantly (p < 0.05) decreased during ripening, because of their high susceptibility to oxidation and conversion to intermediate and secondary molecules. An untargeted metabolomics approach, coupled with unsupervised and supervised multivariate statistics, highlighted a significant impact (prediction scores > 1) of lipid oxidation during ripening time, with some metabolites (such as γ -glutamyl-peptides, hydroperoxy-fatty acids, and glutathione) being particularly discriminant in predicting the changes observed. The discriminant metabolites were coherent with the progressive increase of peroxide values determined during the entire ripening period. Finally, the sensory analysis outlined that the highest degree of ripening provided greater color intensity of the lean part, slice firmness, and chewing consistency, with glutathione and γ-glutamyl-glutamic acid establishing the highest number of significant correlations with the sensory attributes evaluated. Taken together, this work highlights the importance and validity of untargeted metabolomics coupled with sensory analysis to investigate the comprehensive chemical and sensory changes to dry meat during ripening.

Fecal Volatile Metabolomics Predict Gram-Negative Late-Onset Sepsis in Preterm Infants: A Nationwide Case-Control Study.

Early detection of late-onset sepsis (LOS) in preterm infants is crucial since timely treatment initiation is a key prognostic factor. We hypothesized that fecal volatile organic compounds (VOCs), reflecting microbiota composition and function, could serve as a non-invasive biomarker for preclinical pathogen-specific LOS detection. Fecal samples and clinical data of all preterm infants (≤30 weeks' gestation) admitted at nine neonatal intensive care units in the Netherlands and Belgium were collected daily. Samples from one to three days before LOS onset were analyzed by gas chromatography-ion mobility spectrometry (GC-IMS), a technique based on pattern recognition, and gas chromatography-time of flight-mass spectrometry (GC-TOF-MS), to identify unique metabolites. Fecal VOC profiles and metabolites from infants with LOS were compared with matched controls. Samples from 121 LOS infants and 121 matched controls were analyzed using GC-IMS, and from 34 LOS infants and 34 matched controls using GC-TOF-MS. Differences in fecal VOCs were most profound one and two days preceding Escherichia coli LOS (Area Under Curve; p-value: 0.73; p = 0.02, 0.83; p < 0.002, respectively) and two and three days before gram-negative LOS (0.81; p < 0.001, 0.85; p < 0.001, respectively). GC-TOF-MS identified pathogen-specific discriminative metabolites for LOS. This study underlines the potential for VOCs as a non-invasive preclinical diagnostic LOS biomarker.

β-Cyclocitral-Mediated Metabolic Changes Optimize Growth and Defense Responses in Solanum lycopersicum L.

β-cyclocitral (βCC) is one of the significant oxidative products of β-carotene. It primes plants for multiple stress acclimation without compromising plant growth. Metabolic reorganization is necessary to maintain a balance between growth and defense. However, the βCC-mediated changes in a plant's metabolic network are unknown. Here, we demonstrate how βCC-induced metabolic changes enable Solanum lycopersicum L. (tomato) plants to promote defense and maintain growth under stress. An analysis of early (0-240 min) and late (72 h) changes in the tomato metabolome after βCC-treatment using liquid chromatography and tandem mass spectrometry identified 57 compounds. A principal coordinate analysis suggested that βCC treatment significantly changes the metabolite profile. A variable importance in projection (VIP) analysis revealed 16 and 19 discriminant metabolites from early and late samples, respectively (VIP ≥ 1.0). Upregulated metabolites were mainly amino acids and phytophenols. Pathway enrichment analysis showed that βCC treatment influenced amino acid metabolism at early and later times; however, phenylpropanoid and isoquinoline biosynthesis were influenced only at the later time. A 66.6% similarity in the upregulated metabolites of βCC- and simulated-herbivory-treated plants confirmed βCC's role against herbivores. We conclude that βCC steers a temporal separation in amino acids and defense metabolite accumulation that optimizes resource allocation to growth and defense.