Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics

NMR-based metabolomic signature: An important tool for the diagnosis and study of pathogenesis of autoimmune hepatitis

BACKGROUND AND AIMS

Metabolomics is used to predict, diagnose, and monitor metabolic disorders but altered metabolomic signatures have also been reported in diverse diseases, including autoimmune disorders. However, the metabolomic profile in autoimmune hepatitis (AIH) has not been investigated in depth. Therefore, we investigated the metabolomic signature of AIH and its significance as a diagnostic and pathogenetic tool.

APPROACH AND RESULTS

Metabolites in plasma samples from 50 patients with AIH at diagnosis, 43 healthy controls, 72 patients with primary biliary cholangitis (PBC), 26 patients with metabolic dysfunction-associated liver disease, and 101 patients with chronic viral hepatitis were determined by 1 H NMR (nuclear magnetic resonance) spectroscopy. Fifty-two metabolites were quantified, and metabolic pathway analysis was performed. Multivariate analysis revealed that AIH could be differentiated from healthy controls and each of the disease controls ( p <0.001). Fifteen metabolites differentiated AIH from disease controls (PBC+chronic viral hepatitis+metabolic dysfunction-associated liver disease) (95% sensitivity and 92% specificity). Ten distinct metabolic pathways were altered in AIH compared to disease controls. The metabolic pathway of branched-chain amino acids (lower valine, leucine, and isoleucine levels and their catabolic intermediates in PBC), methionine (lower methionine, 2-aminobutyrate, and 2-hydroxybutyrate levels in PBC), alanine-aspartate-glutamate (lower metabolites in PBC), and that of metabolites associated with gut microbiota (lower choline, betaine, and dimethylamine levels in PBC) were significantly different between AIH and PBC ( p <0.01).

CONCLUSIONS

1 H NMR spectroscopy could be a promising novel tool to diagnose and study AIH pathogenesis as there is no need for much sample handling, is highly reproducible with high sensitivity and specificity, and low cost.

Introducing 'identification probability' for automated and transferable assessment of metabolite identification confidence in metabolomics and related studies

Methods for assessing compound identification confidence in metabolomics and related studies have been debated and actively researched for the past two decades. The earliest effort in 2007 focused primarily on mass spectrometry and nuclear magnetic resonance spectroscopy and resulted in four recommended levels of metabolite identification confidence - the Metabolite Standards Initiative (MSI) Levels. In 2014, the original MSI Levels were expanded to five levels (including two sublevels) to facilitate communication of compound identification confidence in high resolution mass spectrometry studies. Further refinement in identification levels have occurred, for example to accommodate use of ion mobility spectrometry in metabolomics workflows, and alternate approaches to communicate compound identification confidence also have been developed based on identification points schema. However, neither qualitative levels of identification confidence nor quantitative scoring systems address the degree of ambiguity in compound identifications in context of the chemical space being considered, are easily automated, or are transferable between analytical platforms. In this perspective, we propose that the metabolomics and related communities consider identification probability as an approach for automated and transferable assessment of compound identification and ambiguity in metabolomics and related studies. Identification probability is defined simply as 1/N, where N is the number of compounds in a reference library or chemical space that match to an experimentally measured molecule within user-defined measurement precision(s), for example mass measurement or retention time accuracy, etc. We demonstrate the utility of identification probability in an in silico analysis of multi-property reference libraries constructed from the Human Metabolome Database and computational property predictions, provide guidance to the community in transparent implementation of the concept, and invite the community to further evaluate this concept in parallel with their current preferred methods for assessing metabolite identification confidence.

High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage

In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.

Wide-energy programmable microwave plasma-ionization for high-coverage mass spectrometry analysis

Although numerous ambient ionization mass spectroscopy technologies have been developed over the past 20 years to address diverse analytical circumstances, a single-ion source technique that can handle all analyte types is still lacking. Here, a wide-energy programmable microwave plasma-ionization mass spectrometry (WPMPI-MS) system is presented, through which MS analysis can achieve high coverage of substances with various characteristics by digitally regulating the microwave energy. In addition, ionization energy can be rapidly scanned using programmable waveforms, enabling the simultaneous detection of biomolecules, heavy metals, non-polar molecules, etc., in seconds. WPMPI-MS performs well in analyzing real samples, rapidly analyzing nine toxicological standards in one drop of serum, and demonstrating good quantification and liquid chromatography coupling capability. The WPMPI-MS has also been used to detect soil extracts, solid pharmaceuticals, and landfill leachate, further demonstrating its robust analytical capabilities for real samples. The prospective uses of the technology in biological and chemical analysis are extensive, and it is anticipated to emerge as a viable alternative to commercially available ion sources.

Unraveling the effects of drying techniques on chaya leaves: Metabolomics analysis of nonvolatile and volatile metabolites, umami taste, and antioxidant capacity

Chaya (Cnidoscolus chayamansa) leaves are known for their strong umami taste and widespread use as a dried seasoning. This study aimed to assess the impact of different drying methods [freeze drying (FD), vacuum drying, oven drying at 50 °C and 120 °C (OD120) and pan roasting (PR)] on the metabolome using mass spectrometry, umami intensity, and antioxidant properties of chaya leaves. The predominant volatile compound among all samples, 3-methylbutanal, exhibited the highest relative odor activity value (rOAV), imparting a malt-like odor, while hexanal (green grass-like odor) and 2-methylbutanal (coffee-like odor) are the second highest rOAV in the FD and PR samples, respectively. OD120 and PR samples possessed the highest levels of umami-tasting amino acids and 5'-ribonucleotides as well as the most intense umami taste, whereas FD samples exhibited the highest antioxidant capacity. These findings enhance our understanding of the aroma characteristics, umami taste, and antioxidant potential of processed chaya leaves.

Multidisciplinary approach combining food metabolomics and epidemiology identifies meglutol as an important bioactive metabolite in tempe, an Indonesian fermented food

This study introduces a multidisciplinary approach to investigate bioactive food metabolites often overlooked due to their low concentrations. We integrated an in-house food metabolite library (n = 494), a human metabolite library (n = 891) from epidemiological studies, and metabolite pharmacological databases to screen for food metabolites with potential bioactivity. We identified six potential metabolites, including meglutol (3-hydroxy-3-methylglutarate), an understudied low-density lipoprotein (LDL)-lowering compound. We further focused on meglutol as a case study to showcase the range of characterizations achievable with this approach. Green pea tempe was identified to contain the highest meglutol concentration (21.8 ± 4.6 mg/100 g). Furthermore, we identified a significant cross-sectional association between plasma meglutol (per 1-standard deviation) and lower LDL cholesterol in two Hispanic adult cohorts (n = 1,628) (β [standard error]: -5.5 (1.6) mg/dl, P = 0.0005). These findings highlight how multidisciplinary metabolomics can serve as a systematic tool for discovering and enhancing bioactive metabolites in food, such as meglutol, with potential applications in personalized dietary approaches for disease prevention.

Recent Advancement in NMR Based Plant Metabolomics: Techniques, Tools, and Analytical Approaches

Plant metabolomics, a rapidly advancing field within plant biology, is dedicated to comprehensively exploring the intricate array of small molecules in plant systems. This entails precisely gathering comprehensive chemical data, detecting numerous metabolites, and ensuring accurate molecular identification. Nuclear magnetic resonance (NMR) spectroscopy, with its detailed chemical insights, is crucial in obtaining metabolite profiles. Its widespread application spans various research disciplines, aiding in comprehending chemical reactions, kinetics, and molecule characterization. Biotechnological advancements have further expanded NMR's utility in metabolomics, particularly in identifying disease biomarkers across diverse fields such as agriculture, medicine, and pharmacology. This review covers the stages of NMR-based metabolomics, including historical aspects and limitations, with sample preparation, data acquisition, spectral processing, analysis, and their application parts.

Unveiling phenylpropanoid regulation: the role of DzMYB activator and repressor in durian (Durio zibethinus) fruit

KEY MESSAGE

DzMYB2 functions as an MYB activator, while DzMYB3 acts as an MYB repressor. They bind to promoters, interact with DzbHLH1, and influence phenolic contents, revealing their roles in phenylpropanoid regulation in durian pulps. Durian fruit has a high nutritional value attributed to its enriched bioactive compounds, including phenolics, carotenoids, and vitamins. While various transcription factors (TFs) regulate phenylpropanoid biosynthesis, MYB (v-myb avian myeloblastosis viral oncogene homolog) TFs have emerged as pivotal players in regulating key genes within this pathway. This study aimed to identify additional candidate MYB TFs from the transcriptome database of the Monthong cultivar at five developmental/postharvest ripening stages. Candidate transcriptional activators were discerned among MYBs upregulated during the ripe stage based on the positive correlation observed between flavonoid biosynthetic genes and flavonoid contents in ripe durian pulps. Conversely, MYBs downregulated during the ripe stage were considered candidate repressors. This study focused on a candidate MYB activator (DzMYB2) and a candidate MYB repressor (DzMYB3) for functional characterization. LC-MS/MS analysis using Nicotiana benthamiana leaves transiently expressing DzMYB2 revealed increased phenolic compound contents compared with those in leaves expressing green fluorescence protein controls, while those transiently expressing DzMYB3 showed decreased phenolic compound contents. Furthermore, it was demonstrated that DzMYB2 controls phenylpropanoid biosynthesis in durian by regulating the promoters of various biosynthetic genes, including phenylalanine ammonia-lyase (PAL), chalcone synthase (CHS), chalcone isomerase (CHI), and dihydroflavonol reductase (DFR). Meanwhile, DzMYB3 regulates the promoters of PAL, 4-coumaroyl-CoA ligase (4CL), CHS, and CHI, resulting in the activation and repression of gene expression. Moreover, it was discovered that DzMYB2 and DzMYB3 could bind to another TF, DzbHLH1, in the regulation of flavonoid biosynthesis. These findings enhance our understanding of the pivotal role of MYB proteins in regulating the phenylpropanoid pathway in durian pulps.

Exploring the Biogenic Transformation Mechanism of Polyphenols by Lactobacillus plantarum NCU137 Fermentation and Its Enhancement of Antioxidant Properties in Wolfberry Juice

This study investigated the transformation of polyphenols, including free and bound polyphenols during the fermentation of wolfberry juice by Lactobacillus plantarum NCU137. Results indicated that fermentation significantly increased the free polyphenols content and released bound polyphenols, enhancing the antioxidant activity. Analysis showed that there were 19 free polyphenols, mainly scopoletin, pyrogallol, and dihydroferulic acid, and 16 bound polyphenols, especially p-coumaric acid, feruloyl hexoside, and caffeic acid. A significant correlation was observed between the generation and degradation of polyphenols, and specific bound polyphenols peaked during the 24-48 h fermentation. Furthermore, reduced surface roughness and galacturonic acid content in wolfberry residue, along with increased pectinase activity, suggested substantial pectin degradation in the cell wall, which may be associated with the release of polyphenols, due to pectin serving as carriers for bound polyphenols. The fermentation also increased polyphenol oxidase and peroxidase activity, contributing to polyphenol breakdown. These findings provide insights for improving wolfberry juice production.

WTV2.0: A high-coverage plant volatilomics method with a comprehensive selective ion monitoring acquisition mode

Volatilomics is essential for understanding the biological functions and fragrance contributions of plant volatiles. However, the annotation coverage achieved using current untargeted and widely targeted volatomics (WTV) methods has been limited by low sensitivity and/or low acquisition coverage. Here, we introduce WTV 2.0, which enabled the construction of a high-coverage library containing 2111 plant volatiles, and report the development of a comprehensive selective ion monitoring (cSIM) acquisition method, including the selection of characteristic qualitative ions with the minimal ion number for each compound and an optimized segmentation method, that can acquire the smallest but sufficient number of ions for most plant volatiles, as well as the automatic qualitative and semi-quantitative analysis of cSIM data. Importantly, the library and acquisition method we developed can be self-expanded by incorporating compounds not present in the library, utilizing the obtained cSIM data. We showed that WTV 2.0 increases the median signal-to-noise ratio by 7.6-fold compared with the untargeted method, doubled the annotation coverage compared with the untargeted and WTV 1.0 methods in tomato fruit, and led to the discovery of menthofuran as a novel flavor compound in passion fruit. WTV 2.0 is a Python library with a user-friendly interface and is applicable to profiling of volatiles and primary metabolites in any species.

Sex-specific pharmacokinetic response to phytoestrogens in Drosophila melanogaster

Drosophila melanogaster, or the fruit fly, is widely used for modeling numerous human diseases, such as neurodegeneration, tumor development, cachexia, and intestinal dysfunction. It is a suitable model organism for research targeting the physiology and pathophysiology of the intestinal epithelial barrier and has also been used as a model organism for preliminary drug and bioactive nutrient screening. However, the application of D. melanogaster in research on drug bioavailability and pharmacokinetic properties has not yet been well explored. In this study, we applied D. melanogaster to investigate the absorption and excretion of the orally administered phytoestrogens daidzein, glycitein, genistein, and their glycosides. Therefore, we established a quick, noninvasive method to quantify compound retention in D. melanogaster, suitable for the investigation of a broad variety of potentially bioactive substances. We showed that fruit fly sex plays a key role in the metabolization, transportation, and excretion of phytoestrogenic isoflavones. In particular, female fruit flies retained significantly more isoflavones than male fruit flies, which was reflected in the greater metabolic impact of isoflavones on females. Male fruit flies excreted more isoflavones than females did, which was linked to the upregulation of the xenobiotic transporter gene Mdr50. We also demonstrated that micellized isoflavones were more bioavailable than powdered isoflavones, independent of sex, age or the addition of dietary fibers.

Integrated network pharmacology, molecular docking, and lipidomics to reveal the regulatory effect of Qingxuan Zhike granules on lipid metabolism in lipopolysaccharide-induced acute lung injury

Qingxuan Zhike granules (QXZKG), a traditional Chinese patent medication, has shown therapeutic potential against acute lung injury (ALI). However, the precise mechanism underlying its lung-protective effects requires further investigation. In this study, integrated network pharmacology, molecular docking, and lipidomics were used to elucidate QXZKG's regulatory effect on lipid metabolism in lipopolysaccharide-induced ALI. Animal experiments were conducted to substantiate the efficacy of QXZKG in reducing pro-inflammatory cytokines and mitigating pulmonary pathology. Network pharmacology analysis identified 145 active compounds that directly targeted 119 primary targets of QXZKG against ALI. Gene Ontology function analysis emphasized the roles of lipid metabolism and mitogen-activated protein kinase (MAPK) cascade as crucial biological processes. The MAPK1 protein exhibited promising affinities for naringenin, luteolin, and kaempferol. Lipidomic analysis revealed that 12 lipids showed significant restoration following QXZKG treatment (p < 0.05, FC >1.2 or <0.83). Specifically, DG 38:4, DG 40:7, PC O-40:8, TG 18:1_18:3_22:6, PI 18:2_20:4, FA 16:3, FA 20:3, FA 20:4, FA 22:5, and FA 24:5 were downregulated, while Cer 18:0;2O/24:0 and SM 36:1;2O/34:5 were upregulated in the QXZKG versus model groups. This study enhances our understanding of the active compounds and targets of QXZKG, as well as the potential of lipid metabolism in the treatment of ALI.

Multi-OMICS approaches in cancer biology: New era in cancer therapy

Innovative multi-omics frameworks integrate diverse datasets from the same patients to enhance our understanding of the molecular and clinical aspects of cancers. Advanced omics and multi-view clustering algorithms present unprecedented opportunities for classifying cancers into subtypes, refining survival predictions and treatment outcomes, and unravelling key pathophysiological processes across various molecular layers. However, with the increasing availability of cost-effective high-throughput technologies (HTT) that generate vast amounts of data, analyzing single layers often falls short of establishing causal relations. Integrating multi-omics data spanning genomes, epigenomes, transcriptomes, proteomes, metabolomes, and microbiomes offers unique prospects to comprehend the underlying biology of complex diseases like cancer. This discussion explores algorithmic frameworks designed to uncover cancer subtypes, disease mechanisms, and methods for identifying pivotal genomic alterations. It also underscores the significance of multi-omics in tumor classifications, diagnostics, and prognostications. Despite its unparalleled advantages, the integration of multi-omics data has been slow to find its way into everyday clinics. A major hurdle is the uneven maturity of different omics approaches and the widening gap between the generation of large datasets and the capacity to process this data. Initiatives promoting the standardization of sample processing and analytical pipelines, as well as multidisciplinary training for experts in data analysis and interpretation, are crucial for translating theoretical findings into practical applications.

Influence of Harvesting Stages on Phytonutrients and Antioxidant Properties of Leaves of Five Purple-Fleshed Sweet Potato (Ipomoea batatas) Genotypes

Sweet potatoes (Ipomoea batatas) are highly profitable, contribute to food security, and their leaves rich in phytonutrients. This study examined the optimal leaf harvesting stage by harvesting newly formed leaves (leaves 1 to 5) to achieve the highest concentration of carotenoids, phenolic compounds, antioxidant properties and mineral content. Leaves of five purple-fleshed sweet potato genotypes '2019-11-2' and '2019-1-1', 'Purple-purple', and from the USA '08-21P' and '16-283P' were harvested based on tuber life cycle [vegetative 8 weeks after planting (VS-8WAP), tuber initiation (TIS-12WAP), and tuber maturation phases (TMS-16WAP)]. At the 8WAP stage, leaves of genotype '2019-11-2' had the highest concentrations of cyanidin-caffeoyl-sophoroside-glucoside (17.64 mg/kg), cyanidin-caffeoyl-feruloyl-sophoroside-glucoside (41.51 mg/kg), peonidin-caffeoyl-hydroxybenzoyl-sophoriside-glucoside (45.25 mg/kg), and peonidin caffeoyl-feruloyl-sophoriside-glucoside (24.47 mg/kg), as well as antioxidant scavenging activity. In contrast, 'Purple-purple' harvested at TIS-12WAP showed the highest concentration of caffeoylquinic acid derivatives. Zeaxanthin, lutein, all trans-β-carotene, and cis-β-carotene are the most abundant carotenoids in genotype '08-21P' at VS-8WAP. As a result, local genotypes '2019-11-2' harvested at 8WAP and 'Purple-purple' harvested at 12WAP are potential sources of anthocyanins and caffeoylquinic acid derivatives. Conversely, USA's genotype '08-21P' at the VS-8WAP stage is an excellent source of carotenoids. The leaves of USA's '08-21P' genotype and the local '2019-11-2' genotype at TMS-16WAP exhibited the highest content of Fe and Mn, respectively. The study identified the optimal leaf stage for consumption of leaves and for use as a functional ingredient.

Concomitant investigation of crustacean amphipods lipidome and metabolome during the molting cycle by Zeno SWATH data-independent acquisition coupled with electron activated dissociation and machine learning

BACKGROUND

DIA (Data-Independent Acquisition) is a powerful technique in Liquid Chromatography coupled with high-resolution tandem Mass Spectrometry (LC-MS/MS) initially developed for proteomics studies and recently emerging in metabolomics and lipidomics. It provides a comprehensive and unbiased coverage of molecules with improved reproducibility and quantitative accuracy compared to Data-Dependent Acquisition (DDA). Combined with the Zeno trap and Electron-Activated Dissociation (EAD), DIA enhances data quality and structural elucidation compared to conventional fragmentation under CID. These tools were applied to study the lipidome and metabolome of the freshwater amphipod Gammarus fossarum, successfully discriminating stages and highlighting significant biological features. Despite being underused, DIA, along with the Zeno trap and EAD, holds great potential for advancing research in the omics field.

RESULTS

DIA combined with the Zeno trap enhances detection reproducibility compared to conventional DDA, improving fragmentation spectra quality and putative identifications. LC coupled with Zeno-SWATH-DIA methods were used to characterize molecular changes in reproductive cycle of female gammarids. Multivariate data analysis including Principal Component Analysis and Partial Least Square Discriminant Analysis successfully identified significant features. EAD fragmentation helped to identify unknown features and to confirm their molecular structure using fragmentation spectra database annotation or machine learning. EAD database matching accurately annotated five glycerophospholipids, including the position of double bonds on fatty acid chain moieties. SIRIUS database predicted structures of unknown features based on experimental fragmentation spectra to compensate for database incompleteness.

SIGNIFICANCE

Reproducible detection of features and confident identification of putative compounds are pivotal stages within analytical pipelines. The DIA approach combined with Zeno pulsing enhances detection sensitivity and targeted fragmentation with EAD in positive polarity provides orthogonal fragmentation information. In our study, Zeno-DIA and EAD thereby facilitated a comprehensive and insightful exploration of pertinent biological molecules associated with the reproductive cycle of gammarids. The developed methodology holds great promises for identifying informative biomarkers on the health status of an environmental sentinel species.

Photoperiod-Dependent Nutrient Accumulation in Rice Cultivated in Plant Factories: A Comparative Metabolomic Analysis

Plant factories offer a promising solution to some of the challenges facing traditional agriculture, allowing for year-round rapid production of plant-derived foods. However, the effects of conditions in plant factories on metabolic nutrients remain to be explored. In this study, we used three rice accessions (KongYu131, HuangHuaZhan, and Kam Sweet Rice) as objectives, which were planted in a plant factory with strict photoperiods that are long-day (12 h light/12 h dark) or short-day (8 h light/16 h dark). A total of 438 metabolites were detected in the harvested rice grains. The difference in photoperiod leads to a different accumulation of metabolites in rice grains. Most metabolites accumulated significantly higher levels under the short-day condition than the long-day condition. Differentially accumulated metabolites were enriched in the amino acids and vitamin B6 pathway. Asparagine, pyridoxamine, and pyridoxine are key metabolites that accumulate at higher levels in rice grains harvested from the short-day photoperiod. This study reveals the photoperiod-dependent metabolomic differences in rice cultivated in plant factories, especially the metabolic profiling of taste- and nutrition-related compounds.

MetaboAnalystR 4.0: a unified LC-MS workflow for global metabolomics

The wide applications of liquid chromatography - mass spectrometry (LC-MS) in untargeted metabolomics demand an easy-to-use, comprehensive computational workflow to support efficient and reproducible data analysis. However, current tools were primarily developed to perform specific tasks in LC-MS based metabolomics data analysis. Here we introduce MetaboAnalystR 4.0 as a streamlined pipeline covering raw spectra processing, compound identification, statistical analysis, and functional interpretation. The key features of MetaboAnalystR 4.0 includes an auto-optimized feature detection and quantification algorithm for LC-MS1 spectra processing, efficient MS2 spectra deconvolution and compound identification for data-dependent or data-independent acquisition, and more accurate functional interpretation through integrated spectral annotation. Comprehensive validation studies using LC-MS1 and MS2 spectra obtained from standards mixtures, dilution series and clinical metabolomics samples have shown its excellent performance across a wide range of common tasks such as peak picking, spectral deconvolution, and compound identification with good computing efficiency. Together with its existing statistical analysis utilities, MetaboAnalystR 4.0 represents a significant step toward a unified, end-to-end workflow for LC-MS based global metabolomics in the open-source R environment.

Identification of an epilepsy-linked gut microbiota signature in a pediatric rat model of acquired epilepsy

A dysfunctional gut microbiota-brain axis is emerging as a potential pathogenic mechanism in epilepsy, particularly in pediatric forms of epilepsy. To add new insights into gut-related changes in acquired epilepsy that develops early in life, we used a multi-omics approach in a rat model with a 56% incidence of epilepsy. The presence of spontaneous seizures was assessed in adult rats (n = 46) 5 months after status epilepticus induced by intra-amygdala kainate at postnatal day 13, by 2 weeks (24/7) ECoG monitoring. Twenty-six rats developed epilepsy (Epi) while the remaining 20 rats (No-Epi) did not show spontaneous seizures. At the end of ECoG monitoring, all rats and their sham controls (n = 20) were sacrificed for quantitative histopathological and immunohistochemical analyses of the gut structure, glia and macrophages, as well as RTqPCR analysis of inflammation/oxidative stress markers. By comparing Epi, No-Epi rats, and sham controls, we found structural, cellular, and molecular alterations reflecting a dysfunctional gut, which were specifically associated with epilepsy. In particular, the villus height-to-crypt depth ratio and number of Goblet cells were reduced in the duodenum of Epi rats vs both No-Epi rats and sham controls (p < 0.01). Villus height and crypt depth in the duodenum and jejunum (p < 0.01) were increased in No-Epi vs both Epi and sham controls. We also detected enhanced Iba1-positive macrophages, together with increased IL1b and NFE2L2 transcripts and TNF protein, in the small intestine of Epi vs both No-Epi and sham control rats (p < 0.01), denoting the presence of inflammation and oxidative stress. Astroglial GFAP-immunostaining was similar in all experimental groups. Metagenomic analysis in the feces collected 5 months after status epilepticus showed that the ratio of two dominant phyla (Bacteroidota-to-Firmicutes) was similarly increased in Epi and No-Epi rats vs sham control rats. Notably, the relative abundance of families, genera, and species associated with SCFA production differed in Epi vs No-Epi rats, describing a bacterial imprint associated with epilepsy. Furthermore, Epi rats showed a blood metabolic signature characterized by changes in lipid metabolism compared to both No-Epi and sham control rats. Our study provides new evidence of long-term gut alterations, along with microbiota-related metabolic changes, occurring specifically in rats that develop epilepsy after brain injury early in life.

Metabolomic profiling of serum and tongue coating of pregnant women with intrahepatic cholestasis in pregnancy

Intrahepatic cholestasis of pregnancy (ICP) is associated with an increased risk of cesarean section and adverse fetal outcomes. Currently, ICP diagnosis depends largely on serum levels of bile acids and lacks sensitivity and specificity for accurate diagnosis. Tongue diagnosis is an important diagnostic tool in traditional Chinese medicine (TCM) and is used in our clinic as complementary treatment and personalized medicine for ICP. However, the molecular basis of the manifestation of greasy white tongue coatings in ICP remains unknown. In this study, we performed untargeted metabolomic profiling of the serum, tongue coating, and saliva of 66 pregnant women, including 22 with ICP. The metabolomic profiles of the serum and tongue coatings showed marked differences between the two clinical groups. Forty-six differentially abundant metabolites were identified, and their relative concentrations correlated with total bile acid levels. These differential metabolites included bile acids, lipids, microbiota- and diet-related metabolites, and exposomes. Conventional biochemical markers, including serum aminotransferases and bilirubin, were not significantly increased in the ICP group, whereas the total cholesterol and triglyceride levels were significantly increased as early as the first trimester. Our data provide insights into the pathophysiology of ICP and implicate the gut-liver axis and environmental exposure. Tongue coating has the potential to be a non-invasive diagnostic approach. Further studies are required to validate the clinical utility of these findings.

Phytoconstituents of Androstachys johnsonii Prain Prevent Reactive Oxygen Species Production and Regulate the Expression of Inflammatory Mediators in LPS-Stimulated RAW 264.7 Macrophages

According to a survey, the medicinal use of Androstachys johnsonii Prain is kept secret by traditional healers. Considering that inflammation and oxidative stress are major risk factors for the progression of various chronic diseases and disorders, we resolved to investigate the antioxidant and anti-inflammatory potentials of A. johnsonii using in vitro and cell-based assays. The antioxidant activity of A. johnsonii hydroethanolic leaf extract (AJHLE) was evaluated using the ABTS, DPPH, and FRAP assays. Its cytotoxic effect was assessed on RAW 264.7 macrophages using an MTT assay. Then, its anti-inflammatory effect was evaluated by measuring the NO production and 15-LOX inhibitory activities. Moreover, its preventive effect on ROS production and its regulatory effect on the expression of pro-inflammatory mediators such as IL-1β, IL-10, TNF-α, and COX-2 were determined using established methods. AJHLE strongly inhibited radicals such as ABTS•+, DPPH•, and Fe3+-TPTZ with IC50 values of 9.07 µg/mL, 8.53 µg/mL, and 79.09 µg/mL, respectively. Additionally, AJHLE induced a significant (p < 0.05) cytotoxic effect at 100 µg/mL, and when tested at non-cytotoxic concentrations, it inhibited NO and ROS production in LPS-stimulated RAW 264.7 macrophages in a concentration-dependent manner. Furthermore, AJHLE showed that its anti-inflammatory action occurs via the inhibition of 15-LOX activity, the downregulation of COX-2, TNF-α, and IL-1β expression, and the upregulation of IL-10 expression. Finally, chemical investigation showed that AJHLE contains significant amounts of procyanidin, epicatechin, rutin, and syringic acid which support its antioxidant and anti-inflammatory activities. These findings suggest that A. johnsonii is a potential source of therapeutic agents against oxidative stress and inflammatory-related diseases.

Unbiased serum metabolomic analysis in cats with naturally occurring chronic enteropathies before and after medical intervention

Chronic enteropathies (CE) are common disorders in cats and the differentiation between the two main underlying diseases, inflammatory bowel disease (IBD) and low-grade intestinal T-cell lymphoma (LGITL), can be challenging. Characterization of the serum metabolome could provide further information on alterations of disease-associated metabolic pathways and may identify diagnostic or therapeutic targets. Unbiased metabolomics analysis of serum from 28 cats with CE (14 cats with IBD, 14 cats with LGITL) and 14 healthy controls identified 1,007 named metabolites, of which 129 were significantly different in cats with CE compared to healthy controls at baseline. Random Forest analysis revealed a predictive accuracy of 90% for differentiating controls from cats with chronic enteropathy. Metabolic pathways found to be significantly altered included phospholipids, amino acids, thiamine, and tryptophan metabolism. Several metabolites were found to be significantly different between cats with IBD versus LGITL, including several sphingolipids, phosphatidylcholine 40:7, uridine, pinitol, 3,4-dihydroxybenzoic acid, and glucuronic acid. However, random forest analysis revealed a poor group predictive accuracy of 60% for the differentiation of IBD from LGITL. Of 129 compounds found to be significantly different between healthy cats and cats with CE at baseline, 58 remained different following treatment.

Can Small Molecules Provide Clues on Disease Progression in Cerebrospinal Fluid from Mild Cognitive Impairment and Alzheimer's Disease Patients?

Alzheimer's disease (AD) is a complex and multifactorial neurodegenerative disease, which is currently diagnosed via clinical symptoms and nonspecific biomarkers (such as Aβ1-42, t-Tau, and p-Tau) measured in cerebrospinal fluid (CSF), which alone do not provide sufficient insights into disease progression. In this pilot study, these biomarkers were complemented with small-molecule analysis using non-target high-resolution mass spectrometry coupled with liquid chromatography (LC) on the CSF of three groups: AD, mild cognitive impairment (MCI) due to AD, and a non-demented (ND) control group. An open-source cheminformatics pipeline based on MS-DIAL and patRoon was enhanced using CSF- and AD-specific suspect lists to assist in data interpretation. Chemical Similarity Enrichment Analysis revealed a significant increase of hydroxybutyrates in AD, including 3-hydroxybutanoic acid, which was found at higher levels in AD compared to MCI and ND. Furthermore, a highly sensitive target LC-MS method was used to quantify 35 bile acids (BAs) in the CSF, revealing several statistically significant differences including higher dehydrolithocholic acid levels and decreased conjugated BA levels in AD. This work provides several promising small-molecule hypotheses that could be used to help track the progression of AD in CSF samples.

Plant necrotrophic bacterial disease resistance phenotypes, QTL, and metabolites identified through integrated genetic mapping and metabolomics in Solanum species

Most food crops are susceptible to necrotrophic bacteria that cause rotting and wilting diseases in fleshy organs and foods. All varieties of cultivated potato (Solanum tuberosum L.) are susceptible to diseases caused by Pectobacterium species, but resistance has been demonstrated in wild potato relatives including S. chacoense. Previous studies demonstrated that resistance is in part mediated by antivirulence activity of phytochemicals in stems and tubers. Little is known about the genetic basis of antivirulence traits, and the potential for inheritance and introgression into cultivated potato is unclear. Here, the metabolites and genetic loci associated with antivirulence traits in S. chacoense were elucidated by screening a sequenced S. tuberosum x S. chacoense recombinant inbred line (RIL) population for antivirulence traits of its metabolite extracts. Metabolite extracts from the RILs exhibited a quantitative distribution for two antivirulence traits that were positively correlated: quorum sensing inhibition and exo-protease inhibition, with some evidence of transgressive segregation, supporting the role of multiple loci and metabolites regulating these resistance-associated systems. Metabolomics was performed on the highly resistant and susceptible RILs that revealed 30 metabolites associated with resistance, including several alkaloids and terpenes. Specifically, several prenylated metabolites were more abundant in resistant RILs. We constructed a high-density linkage map with 795 SNPs mapped to 12 linkage groups, spanning a length of 1,507 cM and a density of 1 marker per 1.89 cM. Genetic mapping of the antivirulence and metabolite data identified five quantitative trait loci (QTLs) related to quorum sensing inhibition that explained 8-28% of the phenotypic variation and two QTLs for protease activity inhibition that explained 14-19% of the phenotypic variation. Several candidate genes including alkaloid, and secondary metabolite biosynthesis that are related to disease resistance were identified within these QTLs. Taken together, these data support that quorum sensing inhibition and exo-protease inhibition assays may serve as breeding targets to improve resistance to nectrotrophic bacterial pathogens in potato and other plants. The identified candidate genes and metabolites can be utilized in marker assisted selection and genomic selection to improve soft- rot and blackleg disease resistance.

Transcriptome and metabolome analyses of Streptococcus gordonii DL1 under acidic conditions

OBJECTIVES

Streptococcus gordonii is associated with the formation of biofilms, especially those that comprise dental plaque. Notably, S. gordonii DL1 causes infective endocarditis (IE). Colonization of this bacterium requires a mechanism that can tolerate a drop in environmental pH by producing acid via its own sugar metabolism. The ability to survive acidic environmental conditions might allow the bacterium to establish vegetative colonization even in the endocardium due to inflammation-induced lowering of pH, increasing the risk of IE. At present, the mechanism by which S. gordonii DL1 survives under acidic conditions is not thoroughly elucidated. The present study was thus conducted to elucidate the mechanism(s) by which S. gordonii DL1 survives under acidic conditions.

METHODS

We analyzed dynamic changes in gene transcription and intracellular metabolites in S. gordonii DL1 exposed to acidic conditions, using transcriptome and metabolome analyses.

RESULTS

Transcriptome analysis revealed upregulation of genes involved in heat shock response and glycolysis, and down regulation of genes involved in phosphotransferase systems and biosynthesis of amino acids. The most upregulated genes were a beta-strand repeat protein of unknown function (SGO_RS06325), followed by copper-translocating P-type ATPase (SGO_RS09470) and malic enzyme (SGO_RS01850). The latter two of these contribute to cytoplasmic alkalinization. S. gordonii mutant strains lacking each of these genes showed significantly reduced survival under acidic conditions. Metabolome analysis revealed that cytoplasmic levels of several amino acids were reduced.

CONCLUSIONS

S. gordonii survives the acidic conditions by recovering the acidic cytoplasm using the various activities, which are regulated at the transcriptional level.

Metabolomic approaches to explore chemodiversity in seeds of guaraná (Paullinia cupana) using UPLC-QTOF-MSE and NMR analysis

The growing interest in health and well-being has spurred the evolution of functional foods, which provide enhanced health benefits beyond basic nutrition. Guaraná seeds (Paullinia cupana) have been widely studied and used as a functional food due to their richness in caffeine, phenolic compounds, amino acids, and other nutrients. This has established guaraná as a significant food supplement, with Brazil being the largest producer of the world. This study aims to propose a set of analytical methods to chemically evaluate fifty-six different guaraná clones, from the Guaraná Germplasm Active Bank, to accommodate the diverse requirements of the food industry. Metabolomic approaches were employed, in which a non-target metabolomic analysis via UPLC-QTOF-MSE led to the annotation of nineteen specialized metabolites. Furthermore, targeted metabolomics was also used, leading to the identification and quantification of metabolites by NMR. The extensive data generated were subjected to multivariate analysis, elucidating the similarities and differences between the evaluated guaraná seeds, particularly concerning the varying concentration levels of the metabolites. The metabolomics approach based on the combination of UPLC-QTOF-MSE, NMR and chemometric tools provided sensitivity, precision and accuracy to establish the chemical profiles of guaraná seeds. In conclusion, evaluating and determining the metabolic specificities of different guarana clones allow for their application in the development of products with different levels of specific metabolites, such as caffeine. This caters to various purposes within the food industry. Moreover, the recognized pharmacological properties of the annotated specialized metabolites affirm the use of guarana clones as an excellent nutritional source.

Exploring applications of non-targeted analysis in the characterization of the prenatal exposome

Capturing the breadth of chemical exposures in utero is critical in understanding their long-term health effects for mother and child. We explored methodological adaptations in a Non-Targeted Analysis (NTA) pipeline and evaluated the effects on chemical annotation and discovery for maternal and infant exposure. We focus on lesser-known/underreported chemicals in maternal and umbilical cord serum analyzed with liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF/MS). The samples were collected from a demographically diverse cohort of 296 maternal-cord pairs (n = 592) recruited in San Francisco Bay area. We developed and evaluated two data processing pipelines, primarily differing by detection frequency cut-off, to extract chemical features from non-targeted analysis (NTA). We annotated the detected chemical features by matching with EPA CompTox Chemicals Dashboard (n = 860,000 chemicals) and Human Metabolome Database (n = 3140 chemicals) and applied a Kendrick Mass Defect filter to detect homologous series. We collected fragmentation spectra (MS/MS) on a subset of serum samples and matched to an experimental MS/MS database within the MS-Dial website and other experimental MS/MS spectra collected from standards in our lab. We annotated ~72 % of the features (total features = 32,197, levels 1-4). We confirmed 22 compounds with analytical standards, tentatively identified 88 compounds with MS/MS spectra, and annotated 4862 exogenous chemicals with an in-house developed annotation algorithm. We detected 36 chemicals that appear to not have been previously reported in human blood and 9 chemicals that were reported in less than five studies. Our findings underline the importance of NTA in the discovery of lesser-known/unreported chemicals important to characterize human exposures.

Potentially compromised systemic and local lactate metabolic balance in glaucoma, which could increase retinal glucose and glutamate concentrations

To investigate the association between lactate metabolism and glaucoma, we conducted a multi-institutional cross-sectional clinical study and a retinal metabolomic analysis of mice with elevated intraocular pressure (IOP) induced by intracameral microbead injection. We compared lactate concentrations in serum and aqueous humor in age-matched 64 patients each with primary open-angle glaucoma (POAG) and cataract. Neither serum nor aqueous humor lactate concentrations differed between the two groups. Multiple regression analysis revealed that only body mass index showed a significant positive correlation with serum and aqueous humor lactate concentration in POAG patients (rs = 0.376, P = 0.002, and rs = 0.333, P = 0.007, respectively), but not in cataract patients. L-Lactic acid was one of the most abundantly detected metabolites in mouse retinas with gas chromatography and mass spectrometry, but there were no significant differences among control, 2-week, and 4-week IOP elevation groups. After 4 weeks of elevated IOP, D-glucose and L-glutamic acid ranked as the top two for a change in raised concentration, roughly sevenfold and threefold, respectively (ANOVA, P = 0.004; Tukey-Kramer, P < 0.05). Glaucoma may disrupt the systemic and intraocular lactate metabolic homeostasis, with a compensatory rise in glucose and glutamate in the retina.

UPLC-QTOF-MSE based metabolomics and chemometrics study of the pitaya processing

The search for knowledge related to the Pitaya (Hylocereus polyrhizus [F.A.C. Weber] Britton & Rose, family Cactaceae) is commonly due to its beneficial health properties e aesthetic values. But process to obtain pitaya pulp is a first and important step in providing information for the subsequent use of this fruit as colorant, for example. Therefore, the effects of the pulping process on the metabolomic and chemometric profile of non-volatile compounds of pitaya were assessed for the first time. The differences in metabolic fingerprints using UPLC-QTOF-MSE and multivariate modeling (PCA and OPLS-DA) was performed in the following treatments: treatment A, which consists of pelled pitaya and no ascorbic acid addition during pulping; treatment B, use of unpelled pitaya added of ascorbic acid during pulping; and control, unpelled pitaya and no ascorbic acid addition during pulping. For the metabolomic analysis, UPLC-QTOF-MSE shows an efficient method for the simultaneous determination of 35 non-volatile pitaya metabolites, including isorhamnetin glucosyl rhamnosyl isomers, phyllocactin isomers, 2'-O-apiosyl-phylocactin and 4'-O-malonyl-betanin. In addition, the chemometric analysis efficiently distinguished the metabolic compounds of each treatment applied and shows that the use of unpelled pitaya added of ascorbic acid during pulping has an interesting chemical profile due to the preservation or formation of compounds, such as those derived from betalain, and higher yields, which is desirable for the food industry.

Predicting Retention Time in Unified-Hydrophilic-Interaction/Anion-Exchange Liquid Chromatography High-Resolution Tandem Mass Spectrometry (Unified-HILIC/AEX/HRMS/MS) for Comprehensive Structural Annotation of Polar Metabolome

The accuracy of the structural annotation of unidentified peaks obtained in metabolomic analysis using liquid chromatography/tandem mass spectrometry (LC/MS/MS) can be enhanced using retention time (RT) information as well as precursor and product ions. Unified-hydrophilic-interaction/anion-exchange liquid chromatography high-resolution tandem mass spectrometry (unified-HILIC/AEX/HRMS/MS) has been recently developed as an innovative method ideal for nontargeted polar metabolomics. However, the RT prediction for unified-HILIC/AEX has not been developed because of the complex separation mechanism characterized by the continuous transition of the separation modes from HILIC to AEX. In this study, we propose an RT prediction model of unified-HILIC/AEX/HRMS/MS, which enables the comprehensive structural annotation of polar metabolites. With training data for 203 polar metabolites, we ranked the feature importance using a random forest among 12,420 molecular descriptors (MDs) and constructed an RT prediction model with 26 selected MDs. The accuracy of the RT model was evaluated using test data for 51 polar metabolites, and 86.3% of the ΔRTs (difference between measured and predicted RTs) were within ±1.50 min, with a mean absolute error of 0.80 min, indicating high RT prediction accuracy. Nontargeted metabolomic data from the NIST SRM 1950-Metabolites in frozen human plasma were analyzed using the developed RT model and in silico MS/MS prediction, resulting in a successful structural estimation of 216 polar metabolites, in addition to the 62 identified based on standards. The proposed model can help accelerate the structural annotation of unknown hydrophilic metabolites, which is a key issue in metabolomic research.

UHPLC-MS metabolomic profile and in silico pharmacokinetic approach of Kalanchoe daigremontiana Raym.-Hamet & H. Perrier aqueous extracts

Throughout humanity's development, the medicinal use of plants has evolved as an observational and empirical matter; Yorubá culture uses Kalanchoe sp. as universal antidotes. They are believed to be "ewé òdúndún" or plants of goodness and are traditionally and religiously used in preparations to treat diseases and physiological disorders. Our main goals were to determine the comparative phytochemical composition panel of two Kalanchoe daigremontiana Raym.-Hamet & H. Perrier aqueous extracts through UHPLC-MS metabolomic approaches and highlight the drug-likeness properties of the most abundant compounds in the complex mixture prepared according to its traditional uses. K. daigremontiana leaf aqueous extracts were prepared by cold water maceration (Kd1) or decoction (Kd2). The metabolomics analysis of the extracts was performed through UHPLC-ESI-MS/MS acquisition in positive and negative modes. An in-house database was built with molecules found in plants from the Crassulaceae family and was applied to the annotation step. Our analysis identified 132 compounds, showcasing variations between negative (ESI(-)) and positive (ESI(+)) ionization modes. Notably, flavonoids such as quercetin and kaempferol glycosides, known for their potent antioxidant properties, were abundant in both extracts. Additionally, bufadienolides, associated with diverse biological activities, were present. Both extracts presented similar phytochemical compositions in terms of the number of compounds. Differential analysis revealed significantly higher intensities for specific molecules in both Kd1 and Kd2 extracts. Considering the relative abundance, Kd1 showed a significant amount of Fatty Acids and Steroids concerning Kd2. Additionally, the 15 most abundant compounds were analyzed using in silico pharmacokinetic and toxicity algorithms (SwissADME, pkCSM, and LAZAR) to predict their drug-likeness profile. The fifteen most abundant molecules (Corchorifatty acid F; 9,12,13-TriHOME; Acetylsagittatin A; Apiin; Kaempferol; L-Malic acid; 19-Oxodesacetylcinobufagin; Lucyoside Q; (12 S,13 S)-Epoxylinolenic acid; Isocitric acid; 4''-O-Acetylafzelin; Hellebrigenin; Senedigitalene; Blumenol C and Sativoside R2) had their ADMET in silico profiles predicted using computational tools. Importantly, our in silico assessments pinpointed six promising compounds with favorable absorption, pharmacokinetics, and drug-likeness properties, suggesting their potential as bioactive agents. This finding underscores the significance of these traditional aqueous extracts in folk medicine. In conclusion, our study not only supports the traditional use of Kalanchoe spp. but also sheds light on the safety and pharmacological potential of these extracts. By exploring different extraction methods and employing metabolomics, we have gained valuable insights into the bioactivity and safety of plant extracts, which can guide future research in this field.

Sucrose and Mannans Affect Arabidopsis Shoot Gravitropism at the Cell Wall Level

Gravitropism is the plant organ bending in response to gravity. Gravitropism, phototropism and sufficient mechanical strength define the optimal position of young shoots for photosynthesis. Etiolated wild-type Arabidopsis seedlings grown horizontally in the presence of sucrose had a lot more upright hypocotyls than seedlings grown without sucrose. We studied the mechanism of this effect at the level of cell wall biomechanics and biochemistry. Sucrose strengthened the bases of hypocotyls and decreased the content of mannans in their cell walls. As sucrose is known to increase the gravitropic bending of hypocotyls, and mannans have recently been shown to interfere with this process, we examined if the effect of sucrose on shoot gravitropism could be partially mediated by mannans. We compared cell wall biomechanics and metabolomics of hypocotyls at the early steps of gravitropic bending in Col-0 plants grown with sucrose and mannan-deficient mutant seedlings. Sucrose and mannans affected gravitropic bending via different mechanisms. Sucrose exerted its effect through cell wall-loosening proteins, while mannans changed the walls' viscoelasticity. Our data highlight the complexity of shoot gravitropism control at the cell wall level.

Metabolomics Analysis and Diagnosis of Lung Cancer: Insights from Diverse Sample Types

Lung cancer is a highly fatal disease that poses a significant global health burden. The absence of characteristic clinical symptoms frequently results in the diagnosis of most patients at advanced stages of lung cancer. Although low-dose computed tomography (LDCT) screening has become increasingly prevalent in clinical practice, its high rate of false positives continues to present a significant challenge. In addition to LDCT screening, tumor biomarker detection represents a critical approach for early diagnosis of lung cancer; unfortunately, no tumor marker with optimal sensitivity and specificity is currently available. Metabolomics has recently emerged as a promising field for developing novel tumor biomarkers. In this paper, we introduce metabolic pathways, instrument platforms, and a wide variety of sample types for lung cancer metabolomics. Specifically, we explore the strengths, limitations, and distinguishing features of various sample types employed in lung cancer metabolomics research. Additionally, we present the latest advances in lung cancer metabolomics research that utilize diverse sample types. We summarize and enumerate research studies that have investigated lung cancer metabolomics using different metabolomic sample types. Finally, we provide a perspective on the future of metabolomics research in lung cancer. Our discussion of the potential of metabolomics in developing new tumor biomarkers may inspire further study and innovation in this dynamic field.

Identification of ethyl vanillin in strawberry (Fragaria × ananassa) using a targeted metabolomics strategy: From artificial to natural

Improving flavor can be an important goal of strawberry through breeding that is enhanced through the accurate identification and quantification of flavor compounds. Herein, a targeted metabolomics strategy was developed using liquid-liquid extraction, an in-house standard database, and GC-MS/MS analysis. The database consisted of key food odorants (KFOs), artificial flavor compounds (AFCs) and volatiles. A total of 131 flavor compounds were accurately identified in Medallion® 'FL 16.30-128' strawberry. Importantly, ethyl vanillin was identified for the first time in natural food. Multiple techniques, including GC-MS, GC-MS/MS and UPLC-MS/MS were applied to ensure the identification. The ethyl vanillin in the Medallion® samples were determined in a range of concentrations from 0.070 ± 0.0006 µg/kg to 0.1372 ± 0.0014 µg/kg by using stable isotope dilution analysis. The identification of ethyl vanillin in strawberry implys the future commercial use a natural flavor compound and the potential to identify genes and proteins associated with its biosynthesis.

MSdeCIpher: A Tool to Link Data from Complementary Ionization Techniques in High-Resolution GC-MS to Identify Molecular Ions

Electron ionization (EI) and molecular ion-generating techniques like chemical ionization (CI) are complementary ionization methods in gas chromatography (GC)-mass spectrometry (MS). However, manual curation effort and expert knowledge are required to correctly assign molecular ions to fragment spectra. MSdeCIpher is a software tool that enables the combination of two separate datasets from fragment-rich spectra, like EI-spectra, and soft ionization spectra containing molecular ion candidates. Using high-resolution GC-MS data, it identifies and assigns molecular ions based on retention time matching, user-defined adduct/neutral loss criteria, and sum formula matching. To our knowledge, no other freely available or vendor tool is currently capable of combining fragment-rich and soft ionization datasets in this manner. The tool's performance was evaluated on three test datasets. When molecular ions are present, MSdeCIpher consistently ranks the correct molecular ion for each fragment spectrum in one of the top positions, with average ranks of 1.5, 1, and 1.2 in the three datasets, respectively. MSdeCIpher effectively reduces candidate molecular ions for each fragment spectrum and thus enables the usage of compound identification tools that require molecular masses as input. It paves the way towards rapid annotations in untargeted analysis with high-resolution GC-MS.

The Roles of Functional Amino Acids in Plant Growth and Development

Plants incorporate acquired carbon and nitrogen into amino acid metabolism, whereby the building blocks of proteins and the precursors of various metabolites are produced. This fundamental demand requires tight amino acid metabolism to sustain physiological homeostasis. There is increasing evidence that amino acid metabolism undergoes plastic alteration to orchestrate specific growth and developmental events. Consequently, there has been a gradual exploration of the interface at which amino acid metabolism and plant morphogenesis are mutually affected. This research progress offers an opportunity to explore amino acid metabolism, with the goal to understand how it can be modulated to serve special cellular needs and regulate specific growth and developmental pathways. Continuous improvements in the sensitivity and coverage of metabolomics technology, along with the development of chemoinformatics, have allowed the investigation of these research questions. In this review, we summarize the roles of threonine, serine, arginine and γ-aminobutyric acid as representative examples of amino acids relevant to specific developmental processes in plants ('functional amino acids'). Our objective is to expand perspectives regarding amino acid metabolism beyond the conventional view that it is merely life-supporting machinery.

Plant response to heavy metal stress toxicity: the role of metabolomics and other omics tools

Metabolomic investigations offers a significant foundation for improved comprehension of the adaptability of plants to reconfigure the key metabolic pathways and their response to changing climatic conditions. Their application to ecophysiology and ecotoxicology help to assess potential risks caused by the contaminants, their modes of action and the elucidation of metabolic pathways associated with stress responses. Heavy metal stress is one of the most significant environmental hazards affecting the physiological and biochemical processes in plants. Metabolomic tools have been widely utilised in the massive characterisation of the molecular structure of plants at various stages for understanding the diverse aspects of the cellular functioning underlying heavy metal stress-responsive mechanisms. This review emphasises on the recent progressions in metabolomics in plants subjected to heavy metal stresses. Also, it discusses the possibility of facilitating effective management strategies concerning metabolites for mitigating the negative impacts of heavy metal contaminants on the growth and productivity of plants.

Fuzi decoction treats chronic heart failure by regulating the gut microbiota, increasing the short-chain fatty acid levels and improving metabolic disorders

Fuzi decoction (FZD) is clinically used to treat chronic heart failure (CHF) in China, but the mechanism underlying FZD treatment in CHF remains unclear. Here, we investigated the potential mechanism underlying FZD treatment of CHF in rats. First, the compounds in FZD-containing serum of rats were identified, and 16 S rRNA sequencing and GC-MS-based untargeted metabolomics analysis were then performed. The levels of fecal short-chain fatty acids (SCFAs) were determined and compared, and fecal microbiota transplantation (FMT) was used to verify the role of the gut microbiota. Our results identified 27 in FD-containing serum. FZD increased the Firmicutes-to-Bacteroidetes ratio and the Lactobacillus abundance and affected the β diversity of the gut microbiota in rats with CHF. Differential species analysis showed that Lactobacillus and Prevotella were biomarkers of FZD treatment of CHF. Untargeted metabolomics analysis revealed that FZD affected valine, leucine and isoleucine biosynthesis; galactose metabolism; and aminoacyl-tRNA biosynthesis in rats with CHF. Furthermore, FZD significantly increased the acetic acid, propionic acid, butyric acid and isopentanoic acid levels in the feces of rats with CHF. Correlation analysis showed that the butyric acid and Lactobacillus levels had the strongest correlation in the control, sham and high-dose FZD (HFZD) groups, and many microbiota components were closely related to differentially abundant metabolites. FMT revealed that the fecal microbiota obtained from the HFZD group changed the heart rate; the brain natriuretic peptide (BNP), acetic acid, propionic acid, butyric acid, and metabolite levels; and the gut microbiota in rats with CHF. In summary, our study revealed that the mechanism of action of FZD in CHF treatment may be related to improvements in the gut microbiota, elevations in the SCFA content and the regulation of valine, leucine, and isoleucine biosynthesis; galactose metabolism; and other metabolic pathways.

A Metabolites Merging Strategy (MMS): Harmonization to Enable Studies' Intercomparison

Metabolomics encounters challenges in cross-study comparisons due to diverse metabolite nomenclature and reporting practices. To bridge this gap, we introduce the Metabolites Merging Strategy (MMS), offering a systematic framework to harmonize multiple metabolite datasets for enhanced interstudy comparability. MMS has three steps. Step 1: Translation and merging of the different datasets by employing InChIKeys for data integration, encompassing the translation of metabolite names (if needed). Followed by Step 2: Attributes' retrieval from the InChIkey, including descriptors of name (title name from PubChem and RefMet name from Metabolomics Workbench), and chemical properties (molecular weight and molecular formula), both systematic (InChI, InChIKey, SMILES) and non-systematic identifiers (PubChem, CheBI, HMDB, KEGG, LipidMaps, DrugBank, Bin ID and CAS number), and their ontology. Finally, a meticulous three-step curation process is used to rectify disparities for conjugated base/acid compounds (optional step), missing attributes, and synonym checking (duplicated information). The MMS procedure is exemplified through a case study of urinary asthma metabolites, where MMS facilitated the identification of significant pathways hidden when no dataset merging strategy was followed. This study highlights the need for standardized and unified metabolite datasets to enhance the reproducibility and comparability of metabolomics studies.

Metabolomics insights into the effects of pre-pregnancy lead exposure on bone metabolism in pregnant rats

Today's women of childbearing age with a history of high lead (Pb) exposure in childhood have large Pb body burdens, which increases Pb release during pregnancy by promoting bone Pb mobilisation. The purpose of this study was to investigate the metabolic mechanisms underlying bone Pb mobilisation and explore the bone metabolism-related pathways during pregnancy. Drinking water containing 0.05% sodium acetate or Pb acetate was provided to weaned female rats for 4 weeks followed by a 4-week washout period, and then rats were co-caged with healthy males of the same age until pregnancy. Blood and bone tissues of the female rats were collected at gestational day (GD) 3 (early pregnancy), GD 10 (middle pregnancy), and GD 17 (late pregnancy), respectively. Pb and calcium concentrations, biomarkers for bone turnover, bone microstructure, serum metabolomics, and metabolic indicators were intensively analyzed. The results demonstrated that pre-pregnancy Pb exposure elevated blood lead levels (BLLs) at GD17, accompanied by a negative correlation between BLLs and trabecular bone Pb levels. Meanwhile, Pb-exposed rats had low bone mass and aberrant bone architecture with a larger number of mature osteoclasts (OCs) compared to the control group. Moreover, the metabolomics uncovered that Pb exposure caused mitochondrial dysfunction, such as enhanced oxidative stress and inflammatory response, and suppressed energy metabolism. Additionally, the levels of ROS, MDA, IL-1β, and IL-18 involved in redox and inflammatory pathways of bone tissues were significantly increased in the Pb-exposed group, while antioxidant SOD and energy metabolism-related indicators including ATP levels, Na+-K+-ATPase, and Ca2+-Mg2+-ATPase activities were significantly decreased. In conclusion, pre-pregnancy Pb exposure promotes bone Pb mobilisation and affects bone microstructure in the third trimester of pregnancy, which may be attributed to OC activation and mitochondrial dysfunction.

Evidence of abnormality in glutathione metabolism in the airways of preterm born children with a history of bronchopulmonary dysplasia

Preterm-born children are at risk of long-term pulmonary deficits, including those who developed bronchopulmonary dysplasia (BPD) in infancy, however the underlying mechanisms remain poorly understood. We characterised the exhaled breath condensate (EBC) metabolome from preterm-born children, both with and without BPD. Following spirometry, EBC from children aged 7-12 years, from the Respiratory Health Outcomes in Neonates study, were analysed using Time-of-Flight Mass Spectrometry. Metabolite Set Enrichment Analysis (MSEA) linked significantly altered metabolites to biological processes. Linear regression models examined relationships between metabolites of interest and participant demographics. EBC was analysed from 214 children, 144 were born preterm, including 34 with BPD. 235 metabolites were detected, with 38 above the detection limit in every sample. Alanine and pyroglutamic acid were significantly reduced in the BPD group when compared to preterm controls. MSEA demonstrated a reduction in glutathione metabolism. Reduced quantities of alanine, ornithine and urea in the BPD group were linked with alteration of the urea cycle. Linear regression revealed significant associations with BPD when other characteristics were considered, but not with current lung function parameters. In this exploratory study of the airway metabolome, preterm-born children with a history of BPD had changes consistent with reduced antioxidant mechanisms suggesting oxidative stress.

Deeper insights into the effects of low dietary levels of polychlorinated biphenyls on pig metabolism using gas chromatography-high resolution mass spectrometry metabolomics

Polychlorinated biphenyls (PCBs) are a class of contaminants of great concern, linked to the development of many chronic diseases. Adverse effects of PCBs have been documented in humans after accidental and massive exposure. However, little is known about the effect of chronic exposure to low-dose PCB mixtures, and studies regarding scattered lifetime exposures to non-dioxin-like (NDL)-PCBs are especially missing. In this work, serum samples from pigs chronically exposed through their diet during 22 days to Aroclor 1260 (i.e. a commercially available mixture of NDL-PCBs) underwent a metabolomics analysis using gas chromatography-high resolution mass spectrometry (GC-HRMS), with the objective to investigate the effect of exposure to low doses of NDL-PCBs (few ng/kg body weight (b.w.) per day). The study showed that the serum profiles of 84 metabolites are significantly altered by the administration of Aroclor 1260, of which 40 could be identified at level 1. The aggregate interpretation of the results of this study, together with the outcome of a previous one involving LC-HRMS profiling, provided a substantial and concise overview of the effect of low dose exposure to NDL-PCBs, reflecting the hepatotoxic and neurotoxic effects already reported in literature at higher and longer exposures. These results are intended to contribute to the debate on the current toxicological reference values for these substances.

Chitosan-based coating enriched with melezitose alters primary metabolites in fresh-cut pineapple during storage

Demand for minimally processed fresh fruit is increasing due to its convenience. However, the distribution of fresh-cut fruits is limited because of their short shelf life. Pineapple, a popular tropical fruit, sold in fresh-cut form has a shelf life of approximately 5-7 days at 4 °C. Chitosan, an edible coating, is commonly used to prolong the shelf life of food products. Similarly, the sugar melezitose has been reported to change during pineapple ripening and may play a role in regulating the shelf life of pineapple. However, the direct effects of this sugar have yet to be studied. The objective of this study was to investigate the effect of chitosan coating with melezitose to prolong the shelf life of fresh-cut pineapple. Full-ripe Bogor pineapples from Okinawa, Japan, were cut into cubes and soaked in either chitosan 1.25%, melezitose 5 mg/L, or chitosan+melezitose and stored for 5 days under dark conditions (23.6 ± 0.5 °C; relative humidity, 40.0 ± 10.4%). None of the treatments significantly altered the weight loss or color changes in the fresh-cut fruit. However, treatment significantly altered the primary metabolites, namely quinic acid, sucrose, and xylitol based on orthogonal projection to latent structures data with the screening from p-value score. Moreover, cell-wall metabolism is possibly affected in pineapple cut fruit treated by chitosan-melezitose as shown from metabolite sets enrichment analysis. This study showed that chitosan added with melezitose might have potential to prolong the shelf-life of fresh-cut pineapple, providing a basis for further post-harvest studies of the whole pineapple fruit.

Identification of potential quality markers in Indonesia's Arabica specialty coffee using GC/MS-based metabolomics approach

INTRODUCTION

The cupping test is a widely used method for quality assessment of Arabica coffee. However, the cupping test is limited by the low number of certified panelists and the low throughput. Therefore, an analytical-based quality assessment may be a promising tool to complement the cupping test. A present, there is no report investigating quality marker candidates, focusing only on "specialty" grade Arabica coffee from Indonesia.

OBJECTIVE

This study identified the potential quality marker(s) in Arabica Specialty coffee at different stages (green beans, roasted beans, and brewed coffee.

METHODS

The metabolite profiles of ten different Arabica specialty-grade coffees were analyzed with different cup scores using gas chromatography-mass spectrometry (GC/MS). From the ten samples, green coffee beans, roasted coffee beans, and brewed coffee were selected. In addition, an orthogonal projection to latent structure (OPLS) regression analysis was conducted to obtain a potential quality marker based on the variable importance in projection (VIP). The potential quality marker(s) were validated by GC/MS metabolome profiling and OPLS analysis of different sets of samples consisting of 35 Arabica specialty-grade coffee samples.

RESULTS

In Arabica coffee samples, the OPLS model of the three stages showed galactinol to have a high VIP score. Galactinol showed a consistent positive correlation with cup scores at all stages of coffee production (green beans, roasted beans, and brewed coffee). The correlation suggests galactinol is a potential quality marker after further validation using different samples.

CONCLUSION

GC/MS combined with OPLS regression analysis suggested galactinol as a quality marker and provide an early screening method for Arabica coffee quality that complements the cupping test performed by certified panelists.

Investigating the Metabolism of Plants Germinated in Heavy Water, D2O, and H218O-Enriched Media Using High-Resolution Mass Spectrometry

Mass spectrometry has been an essential technique for the investigation of the metabolic pathways of living organisms since its appearance at the beginning of the 20th century. Due to its capability to resolve isotopically labeled species, it can be applied together with stable isotope tracers to reveal the transformation of particular biologically relevant molecules. However, low-resolution techniques, which were used for decades, had limited capabilities for untargeted metabolomics, especially when a large number of compounds are labelled simultaneously. Such untargeted studies may provide new information about metabolism and can be performed with high-resolution mass spectrometry. Here, we demonstrate the capabilities of high-resolution mass spectrometry to obtain insights on the metabolism of a model plant, Lepidium sativum, germinated in D2O and H218O-enriched media. In particular, we demonstrated that in vivo labeling with heavy water helps to identify if a compound is being synthesized at a particular stage of germination or if it originates from seed content, and tandem mass spectrometry allows us to highlight the substructures with incorporated isotope labels. Additionally, we found in vivo labeling useful to distinguish between isomeric compounds with identical fragmentation patterns due to the differences in their formation rates that can be compared by the extent of heavy atom incorporation.

Awakening the natural capability of psicose production in Escherichia coli

Due to the rampant rise in obesity and diabetes, consumers are desperately seeking for ways to reduce their sugar intake, but to date there are no options that are both accessible and without sacrifice of palatability. One of the most promising new ingredients in the food system as a non-nutritive sugar substitute with near perfect palatability is D-psicose. D-psicose is currently produced using an in vitro enzymatic isomerization of D-fructose, resulting in low yield and purity, and therefore requiring substantial downstream processing to obtain a high purity product. This has made adoption of D-psicose into products limited and results in significantly higher per unit costs, reducing accessibility to those most in need. Here, we found that Escherichia coli natively possesses a thermodynamically favorable pathway to produce D-psicose from D-glucose through a series of phosphorylation-epimerization-dephosphorylation steps. To increase carbon flux towards D-psicose production, we introduced a series of genetic modifications to pathway enzymes, central carbon metabolism, and competing metabolic pathways. In an attempt to maximize both cellular viability and D-psicose production, we implemented methods for the dynamic regulation of key genes including clustered regularly interspaced short palindromic repeats inhibition (CRISPRi) and stationary-phase promoters. The engineered strains achieved complete consumption of D-glucose and production of D-psicose, at a titer of 15.3 g L-1, productivity of 2 g L-1 h-1, and yield of 62% under test tube conditions. These results demonstrate the viability of whole-cell catalysis as a sustainable alternative to in vitro enzymatic synthesis for the accessible production of D-psicose.

Dissecting the human gut microbiome to better decipher drug liability: A once-forgotten organ takes center stage

BACKGROUND

The gut microbiome is a diverse system within the gastrointestinal tract composed of trillions of microorganisms (gut microbiota), along with their genomes. Accumulated evidence has revealed the significance of the gut microbiome in human health and disease. Due to its ability to alter drug/xenobiotic pharmacokinetics and therapeutic outcomes, this once-forgotten "metabolic organ" is receiving increasing attention. In parallel with the growing microbiome-driven studies, traditional analytical techniques and technologies have also evolved, allowing researchers to gain a deeper understanding of the functional and mechanistic effects of gut microbiome.

AIM OF REVIEW

From a drug development perspective, microbial drug metabolism is becoming increasingly critical as new modalities (e.g., degradation peptides) with potential microbial metabolism implications emerge. The pharmaceutical industry thus has a pressing need to stay up-to-date with, and continue pursuing, research efforts investigating clinical impact of the gut microbiome on drug actions whilst integrating advances in analytical technology and gut microbiome models. Our review aims to practically address this need by comprehensively introducing the latest innovations in microbial drug metabolism research- including strengths and limitations, to aid in mechanistically dissecting the impact of the gut microbiome on drug metabolism and therapeutic impact, and to develop informed strategies to address microbiome-related drug liability and minimize clinical risk.

KEY SCIENTIFIC CONCEPTS OF REVIEW

We present comprehensive mechanisms and co-contributing factors by which the gut microbiome influences drug therapeutic outcomes. We highlight in vitro, in vivo, and in silico models for elucidating the mechanistic role and clinical impact of the gut microbiome on drugs in combination with high-throughput, functionally oriented, and physiologically relevant techniques. Integrating pharmaceutical knowledge and insight, we provide practical suggestions to pharmaceutical scientists for when, why, how, and what is next in microbial studies for improved drug efficacy and safety, and ultimately, support precision medicine formulation for personalized and efficacious therapies.

Linking MS1 and MS2 signals in positive and negative modes of LC-HRMS in untargeted metabolomics using the ROIMCR approach

Data-independent acquisition (DIA) mode in liquid chromatography (LC) high-resolution mass spectrometry (HRMS) has emerged as a powerful strategy in untargeted metabolomics for detecting a broad range of metabolites. However, the use of this approach also represents a challenge in the analysis of the large datasets generated. The regions of interest (ROI) multivariate curve resolution (MCR) approach can help in the identification and characterization of unknown metabolites in their mixtures by linking their MS1 and MS2 DIA spectral signals. In this study, it is proposed for the first time the analysis of MS1 and MS2 DIA signals in positive and negative electrospray ionization modes simultaneously to increase the coverage of possible metabolites present in biological systems. In this work, this approach has been tested for the detection and identification of the amino acids present in a standard mixture solution and in fish embryo samples. The ROIMCR analysis allowed for the identification of all amino acids present in the analyzed mixtures in both positive and negative modes. The methodology allowed for the direct linking and correspondence between the MS signals in their different acquisition modes. Overall, this approach confirmed the advantages and possibilities of performing the proposed ROIMCR simultaneous analysis of mass spectrometry signals in their differing acquisition modes in untargeted metabolomics studies.

Metabolomics Point out the Effects of Carfilzomib on Aromatic Amino Acid Biosynthesis and Degradation

(1) Carfilzomib (Cfz) is an antineoplastic agent indicated for the treatment of multiple myeloma. However, its beneficial action is attenuated by the occurrence of cardiotoxicity and nephrotoxicity as the most common adverse effects. Presently, there is well-established knowledge on the pathomechanisms related to these side effects; however, the research on the metabolic alterations provoked by the drug is limited. (2) An in vivo simulation of Cfz-induced toxicity was developed in (i) Cfz-treated and (ii) control mice. An RP-HRMS-based protocol and an advanced statistical treatment were used to investigate the impact of Cfz on the non-polar metabolome. (3) The differential analysis classified the Cfz-treated and control mice and resulted in a significant number of identified biomarkers with AUC > 0.9. The drug impaired the biosynthesis and degradation of aromatic amino acids (AAA) and led to alterations of uremic toxins in the renal and urine levels. Furthermore, the renal degradation of tryptophan was affected, inducing its degradation via the kynurenine pathway. (4) The renal levels of metabolites showed impaired excretion and degradation of AAAs. Cfz was, finally, correlated with the biosynthesis of renal dopamine, explaining the biochemical causes of water and ion retention and the increase in systolic pressure.

Improvement of the functional value of green soybean (edamame) using germination and tempe fermentation: A comparative metabolomics study

Green soybean, also known as edamame, is a legume with high nutritional and functional value. Despite its growing popularity and potential health benefits, the functionality of green soybean has not been thoroughly studied. Previous research on the functionality of green soybean has largely focused on a limited number of specific, well-studied, bioactive metabolites, without comprehensively investigating the metabolome of this legume. Additionally, very few studies have explored the improvement of the functional value of green soybean. This study aimed to investigate the metabolome profile of green soybean, identify bioactive metabolites, and to further explore the potential improvement of the identified bioactive metabolites using germination and tempe fermentation. A total of 80 metabolites were annotated from green soybean using GC-MS and HPLC-PDA-MS. Among them, 16 important bioactive metabolites were identified: soy isoflavones daidzin, glycitin, genistin, malonyl daidzin, malonyl genistin, malonyl glycitin, acetyl daidzin, acetyl genistin, acetyl glycitin, daidzein, glycitein, and genistein, as well as other metabolites including 3,4-dihydroxybenzoic acid, 3-hydroxyanthranillic acid, 3-hydroxy-3-methylglutaric acid (meglutol), and 4-aminobutyric acid (GABA). Germination and tempe fermentation techniques were employed to potentially improve the concentrations of these bioactive metabolites. While showing improvements in amino acid contents, germination process did not improve bioactive metabolites significantly. In contrast, tempe fermentation was found to significantly increase the concentrations of daidzein, genistein, glycitein, acetyl genistin, acetyl daidzin, 3-hydroxyanthranillic acid, and meglutol (>2-fold increase with p < 0.05) while also improving amino acid levels. This study highlights the potentials of germination and fermentation to improve the functionality of legumes, particularly green soybean.

Comparative polar and lipid plasma metabolomics differentiate KSHV infection and disease states

BACKGROUND

Kaposi sarcoma (KS) is a neoplastic disease etiologically associated with infection by the Kaposi sarcoma-associated herpesvirus (KSHV). KS manifests primarily as cutaneous lesions in individuals due to either age (classical KS), HIV infection (epidemic KS), or tissue rejection preventatives in transplantation (iatrogenic KS) but can also occur in individuals, predominantly in sub-Saharan Africa (SSA), lacking any obvious immune suppression (endemic KS). The high endemicity of KSHV and human immunodeficiency virus-1 (HIV) co-infection in Africa results in KS being one of the top 5 cancers there. As with most viral cancers, infection with KSHV alone is insufficient to induce tumorigenesis. Indeed, KSHV infection of primary human endothelial cell cultures, even at high levels, is rarely associated with long-term culture, transformation, or growth deregulation, yet infection in vivo is sustained for life. Investigations of immune mediators that distinguish KSHV infection, KSHV/HIV co-infection, and symptomatic KS disease have yet to reveal consistent correlates of protection against or progression to KS. In addition to viral infection, it is plausible that pathogenesis also requires an immunological and metabolic environment permissive to the abnormal endothelial cell growth evident in KS tumors. In this study, we explored whether plasma metabolomes could differentiate asymptomatic KSHV-infected individuals with or without HIV co-infection and symptomatic KS from each other.

METHODS

To investigate how metabolic changes may correlate with co-infections and tumorigenesis, plasma samples derived from KSHV seropositive sub-Saharan African subjects in three groups, (A) asymptomatic (lacking neoplastic disease) with KSHV infection only, (B) asymptomatic co-infected with KSHV and HIV, and (C) symptomatic with clinically diagnosed KS, were subjected to analysis of lipid and polar metabolite profiles RESULTS: Polar and nonpolar plasma metabolic differentials were evident in both comparisons. Integration of the metabolic findings with our previously reported KS transcriptomics data suggests dysregulation of amino acid/urea cycle and purine metabolic pathways, in concert with viral infection in KS disease progression.

CONCLUSIONS

This study is, to our knowledge, the first to report human plasma metabolic differentials between in vivo KSHV infection and co-infection with HIV, as well as differentials between co-infection and epidemic KS.