Metabolite Database Research Articles

Metabolomic Profiling of Human Urine Samples Using LC-TIMS-QTOF Mass Spectrometry.

The identification of metabolites in biological samples is challenging due to their chemical and structural diversity. Ion mobility spectrometry (IMS) separates ionized molecules based on their mobility in a carrier buffer gas giving information about the ionic shape by measuring the rotationally averaged collision cross-section (CCS) value. This orthogonal descriptor, in combination with the m/z, isotopic pattern distribution, and MS/MS spectrum, has the potential to improve the identification of molecular molecules in complex mixtures. Urine metabolomics can reveal metabolic differences, which arise as a result of a specific disease or in response to therapeutic intervention. It is, however, complicated by the presence of metabolic breakdown products derived from a wide range of lifestyle and diet-related byproducts, many of which are poorly characterized. In this study, we explore the use of trapped ion mobility spectrometry (TIMS) via LC parallel accumulation with serial fragmentation (PASEF) for urine metabolomics. A total of 362 urine metabolites were characterized from 80 urine samples collected from healthy volunteers using untargeted metabolomics employing HILIC and RP chromatography. Additionally, three analytes (Trp, Phe, and Tyr) were selected for targeted quantification. Both the untargeted and targeted data was highly reproducible and reported CCS measurements for identified metabolites were robust in the presence of the urine matrix. A comparison of CCS values among different laboratories was also conducted, showing less than 1.3% ΔCCS values across different platforms. This is the first report of a human urine metabolite database compiled with CCS values experimentally acquired using an LC-PASEF TIMS-qTOF platform.

Metabonomic Study on the Plasma of High-Fat Diet-Induced Dyslipidemia Rats Treated with Ge Gen Qin Lian Decoction by Ultrahigh-Performance Liquid Chromatography-Mass Spectrometry.

Gegen Qinlian decoction (GGQLD) has a definite effect on T2DM in clinic, and it has the effect of lowering blood sugar, improving insulin resistance, and improving the blood lipid level of rats with dyslipidemia, but the intervention mechanism of GGQLD on dyslipidemia has not been clarified. The changes in endogenous metabolites in the plasma of high-fat diet-induced dyslipidemia rats treated with Ge Gen Qin Lian Decoction (GGQLD) were studied to elucidate the therapeutic effects and mechanism of action of GGQLD in dyslipidemia. Based on ultrahigh-performance liquid chromatography coupled with quadrupole-time-of-flight tandem mass spectrometry (UHPLC-Q-TOF-MS), the metabolic profiles of rat serum samples were collected. The rat model of dyslipidemia was induced by a 60% fat-fed high-fat diet. After feeding the rats with a high-fat diet for 4 weeks, dyslipidemia appeared. After 5 weeks of GGQLD (14.85 g kg−1) administration, the metabonomics of rats' plasma samples in the normal group, model group, and administration group were analyzed. Mass profiler professional (MPP), SIMCA-P 14.1, and Graphpad prism 6.0 software were used combined with METLIN biological database and human metabolite database HMDB to screen and identify endogenous biomarkers. Metaboanalyst 4.0 software was used by combining with HMDB and KEGG databases; the enrichment and metabolic pathway of biomarkers were analyzed to explore the metabolic mechanism of dyslipidemia rats induced by high-fat diet and the intervention mechanism of Gegen Qinlian decoction. After 5 weeks of administration of GGQLD, the levels of serum TC and TG were significantly decreased (P < 0.05, P < 0.01), while HDL-C and LDL-C were not significantly affected. After administration, the food intake of rats in the administration group decreased gradually, and the change trend of body weight gradually slowed down. The metabonomics of rat plasma samples results showed that 23 potential biomarkers including α-linolenic acid, arachidonic acid, and lysophosphatidylcholine were significantly changed in positive ion mode. Studies have shown that GGQLD has a significant lipid-lowering effect on dyslipidemia rats induced by a high-fat diet, and its preventive mechanism is related to tryptophan metabolism, fatty acid biosynthesis, α-linolenic acid metabolism, arachidonic acid, and glycerophosphatidyl metabolism pathway.

Metabolomic Expression of Laryngeal and Hindlimb Muscles in Adult versus Senescent Rats.

(1) Determine the feasibility of obtaining a global, unbiased metabolomic profile on laryngeal muscle in a rat model; (2) evaluate the impact of biological aging on the laryngeal metabolome; and (3) characterize biochemical expression differences between aged and non-aged laryngeal and hindlimb muscle. Thyroarytenoid laryngeal muscle and plantaris hindlimb muscle were harvested from 5 young adult (9 months old) and 5 older adult (32 months old) F344BN rats. Tissue was processed and analyzed using LC-MS methods. Detected metabolites were compared to widely used metabolite databases and KEGG pathway enrichment was performed on significant metabolites. The greatest differences in metabolite expression were between laryngeal and limb muscle with 126 different metabolites found between laryngeal and limb within the young group and 149 different metabolites within the old group. Significant hits between muscle groups highlighted amino acid differences between these tissues. There were more robust differences with age in limb muscle compared to laryngeal muscle. Amino acid metabolism is a key difference between muscles of the limbs and larynx. Due to the number of differentially expressed metabolites between the 2 muscle groups, caution should be exercised when applying skeletal limb muscle physiology and biology concepts to the vocal muscles in both aged and non-aged musculoskeletal systems. Mechanisms underlying less robust effects of age on laryngeal muscle compared to limb muscle require elucidation.

The SistematX Web Portal of Natural Products: An Update.

Natural products and their secondary metabolites are promising starting points for the development of drug prototypes and new drugs, as many current treatments for numerous diseases are directly or indirectly related to such compounds. State-of-the-art, curated, integrated, and frequently updated databases of secondary metabolites are thus highly relevant to drug discovery. The SistematX Web Portal, introduced in 2018, is undergoing development to address this need and documents crucial information about plant secondary metabolites, including the exact location of the species from which the compounds were isolated. SistematX also allows registered users to log in to the data management area and gain access to administrative pages. This study reports recent updates and modifications to the SistematX Web Portal, including a batch download option, the generation and visualization of 1H and 13C nuclear magnetic resonance spectra, and the calculation of physicochemical (drug-like and lead-like) properties and biological activity profiles. The SistematX Web Portal is freely available at http://sistematx.ufpb.br.

UPLC-TOF-MS/MS-Based Metabolomics Analysis Reveals Species-Specific Metabolite Compositions in Pitchers of Nepenthes ampullaria, Nepenthes rafflesiana, and Their Hybrid Nepenthes × hookeriana.

Hybridization is key to the evolution and diversity of plants in nature. Nepenthaceae comprises a family of diverse tropical carnivorous pitcher plant species with extensive hybridization. However, there is no study to date on the metabolite expression of hybrids in this family. We performed a non-targeted metabolomics analysis of the pitchers of two Nepenthes species with different dietary habits, namely, the semi-detritivorous N. ampullaria and carnivorous N. rafflesiana with their hybrid (N. × hookeriana) for a comparative study. The whole-pitcher samples were extracted in methanol:chloroform:water (3:1:1) via sonication-assisted extraction and analyzed using ultra-performance liquid chromatography time-of-flight mass spectrometry (UPLC-TOF-MS) followed by data analysis to profile chemical compositions. A total of 1,441 metabolite features were profiled from the three species in which 43.3% of features in the hybrid samples were not found in either of its parents. The partial least squares discriminant analysis (PLS-DA) found 324 metabolite features with variable in projection (VIP) values greater than one in which 55 features were statistically significant. This showed that the hybrid is closer to N. rafflesiana, which is consistent to the previous study on gene and protein expressions. A total of 105 metabolites were putatively identified with manual searches using public metabolite databases. Phenols were detected to be the most abundant secondary metabolites due to a high flavonoid content, especially in N. rafflesiana. The most abundant feature 476.3s:449.102 was found to be the most significant VIP for distinguishing between the three species as a chemical marker. This is the first study comparing metabolites in the carnivory organs of different Nepenthes species with comprehensive profiling and putative identification. The differential metabolite compositions in the pitchers of different species might have ecological implications with the hybrid showing intermediate phenotype between the parents as well as manifesting unique metabolites. However, there is no clear evidence of metabolites related to the differences in dietary habits between the hybrid and the two parent species.

Comparative metabolic analysis between distant sea urchin hybrids (Heliocidaris crassispina ♀ × Strongylocentrotus intermedius ♂) and their parental purebred offspring

Gonadal traits and metabolite comparisons were performed between distant sea urchin hybrids (Heliocidaris crassispina♀ × Strongylocentrotus intermedius♂, HS hybrids) and their parental purebred offspring. The results indicated that 1) the gonadal color of the HS hybrids was somewhere between that of the parental purebred offspring, whereas the HS hybrids had a more delicate and compact gonadal structure compared to those of their parental purebred offspring; 2) a total of 85 significantly differential metabolites (SDMs) were observed in the gonads of the HS hybrid compared to that of their maternal purebred offspring, and a total of 474 SDMs were observed in the gonads of the HS hybrid compared to that of their paternal purebred offspring; 3) metabolic pathway analysis indicated that the number of differential pathways between the HS hybrids and their paternal purebred offspring was significantly higher than that in the HS hybrids or their maternal purebred offspring. Gonadal fatty acid absolute content analysis showed that there was no significant difference between the HS hybrids and their maternal purebred offspring, whereas the absolute contents of three saturated fatty acids (C22:0, C12:0 and C14:0) and two monounsaturated fatty acids (C20:1 and C14:1) exhibited a significant difference between the HS hybrids and their paternal purebred offspring. All observations in this study not only suggest that the HS hybrids can be a prospective aquaculture urchin species but also enrich the metabolite database and provide biomarker information from a metabolome aspect that may contribute to aquaculture potential and commercial-value evaluation of new sea urchin varieties.

Metabolomic profile associated with obstructive sleep apnoea severity in obese pregnant women with gestational diabetes mellitus: A pilot study.

Obstructive sleep apnoea (OSA) is prevalent in obese women with gestational diabetes mellitus (GDM). The present pilot study explored associations between OSA severity and metabolites in women with GDM. A total of 81 obese women with diet-controlled GDM had OSA assessment (median gestational age [GA] 29weeks). The metabolic profile was assayed from fasting serum samples via liquid chromatography-mass spectrometry (LC-MS) using an untargeted approach. Metabolites were extracted and subjected to an Agilent 1,290 UPLC coupled to an Agilent 6,545 quadrupole time-of-flight (Q-TOF) MS. Data were acquired using electrospray ionisation in positive and negative ion modes. The raw LC-MS data were processed using the OpenMS toolkit to detect and quantify features, and these features were annotated using the Human Metabolite Database. The feature data were compared with OSA status, apnea-hypopnea index (AHI), body mass index (BMI) and GA using "limma" in R. Correlation analyses of the continuous covariates were performed using Kendall's Tau test. The p values were adjusted for multiple testing using the Benjamini-Hochberg false discovery rate correction. A total of 42 women (51.8%) had OSA, with a median AHI of 9.1events/hr. There were no significant differences in metabolomics profiles between those with and without OSA. However, differential analyses modelling in GA and BMI found 12 features that significantly associated with the AHI. These features could be annotated to oestradiols, lysophospholipids, and fatty acids, with higher levels related to higher AHI. Metabolites including oestradiols and phospholipids may be involved in pathogenesis of OSA in pregnant women with GDM. A targeted approach may help elucidate our understanding of their role in OSA in this population.

FSMP-10. CYSTEINE INDUCES CYTOTOXICITY IN GLIOBLASTOMA THROUGH MITOCHONDRIAL HYDROGEN PEROXIDE PRODUCTION

Glioblastoma (GBM) is a poorly treatable disease with high mortality. Tumor metabolism in GBM is a critical mechanism responsible for growth because of upregulation of glucose, amino acid, and fatty acid utilization. However, little is known about the specific metabolic alterations in GBM that are targetable with FDA-approved compounds. To investigate metabolic signatures unique to GBM, we interrogated the TCGA and a cancer metabolite database for alterations in glucose and amino acid signatures in GBM relative to other human cancers and relative to low-grade glioma. From these analyses, we found that GBM exhibits the highest levels of cysteine and methionine pathway gene expression of 32 human cancers and that GBM exhibits high levels of cysteine metabolites compared to low-grade gliomas. To study the role of cysteine in GBM pathogenesis, we treated patient-derived GBM cells with FDA-approved cyst(e)ine-promoting compounds in vitro, including N-acetylcysteine (NAC) and the cephalosporin antibiotic, Ceftriaxone (CTX), which induces cystine import through system Xc transporter upregulation. Cysteine-promoting compounds, including NAC and CTX, inhibit growth of GBM cells, which is exacerbated by glucose deprivation. This growth inhibition is associated with reduced mitochondrial metabolism, manifest by reduction in ATP, NADPH/NADP+ ratio, mitochondrial membrane potential, and oxygen consumption rate. Mechanistic experiments revealed that cysteine compounds induce a rapid increase in the rate of H2O2 production in isolated GBM mitochondria, an effect blocked by the H2O2 scavenger, catalase. Such findings are consistent with reductive stress, a ROS-producing process whereby excess mitochondrial reducing equivalents prevent electron transfer to oxidized electron acceptors, inducing O2 reduction to H2O2. We show that cysteine-promoting compounds reduce cell growth and induce rapid mitochondrial toxicity in GBM, which may be due to reductive stress. This pathway is targetable with FDA-approved cysteine-promoting compounds and could synergize with glucose-lowering treatments, including the ketogenic diet, for GBM.

CyanoMetDB, a comprehensive public database of secondary metabolites from cyanobacteria

Harmful cyanobacterial blooms, which frequently contain toxic secondary metabolites, are reported in aquatic environments around the world. More than two thousand cyanobacterial secondary metabolites have been reported from diverse sources over the past fifty years. A comprehensive, publically-accessible database detailing these secondary metabolites would facilitate research into their occurrence, functions and toxicological risks. To address this need we created CyanoMetDB, a highly curated, flat-file, openly-accessible database of cyanobacterial secondary metabolites collated from 850 peer-reviewed articles published between 1967 and 2020. CyanoMetDB contains 2010 cyanobacterial metabolites and 99 structurally related compounds. This has nearly doubled the number of entries with complete literature metadata and structural composition information compared to previously available open access databases. The dataset includes microcytsins, cyanopeptolins, other depsipeptides, anabaenopeptins, microginins, aeruginosins, cyclamides, cryptophycins, saxitoxins, spumigins, microviridins, and anatoxins among other metabolite classes. A comprehensive database dedicated to cyanobacterial secondary metabolites facilitates: (1) the detection and dereplication of known cyanobacterial toxins and secondary metabolites; (2) the identification of novel natural products from cyanobacteria; (3) research on biosynthesis of cyanobacterial secondary metabolites, including substructure searches; and (4) the investigation of their abundance, persistence, and toxicity in natural environments.

Capturing Dioclea Reflexa Seed Bioactives on Halloysite Nanotubes and pH Dependent Release of Cargo against Breast (MCF-7) Cancers In Vitro

In this work, optimization parameters were developed to capture plant metabolites from Dioclea Reflexa (DR) seed ex-tracts onto halloysites nanotubes (HNTs). A one-step pool of the crude extracts at neutral pH from the HNT lumen failed to elicit a reduction in breast cancer, Michigan Cancer Foundation-7 (MCF-7) cell viability. However, the pH-dependent elution of metabolites revealed that the acidic pH samples exhibited profound antiproliferative effects on the cancer cells compared to the basic pH metabolites using both trypan blue dye exclusion assay and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) viability test. pH~5.2 samples demonstrated by half-maximal inhibitory concentration (IC50) of 0.8 mg and a cyclic voltammetry oxidation peak potential and current of 234 mV and 0.45 µA, respectively. This indicates that the cancer cells death could be attributed to membrane polarization/depolarization effects of the sample. Fluorescence-activated cell sorting (FACS) studies confirmed that the plant metabolites affected breast cancer apoptotic signaling pathways of cell death. The studies proved that plant metabolites could be captured using simplified screening procedures for rapid drug discovery purposes. Such procedures, however, would require the integration of affordable analytical tools to test and isolate individual metabolites. Our approach could be an important strategy to create a library and database of bioactive plant metabolites based on pH values.

PSC-db: A Structured and Searchable 3D-Database for Plant Secondary Compounds.

Plants synthesize a large number of natural products, many of which are bioactive and have practical values as well as commercial potential. To explore this vast structural diversity, we present PSC-db, a unique plant metabolite database aimed to categorize the diverse phytochemical space by providing 3D-structural information along with physicochemical and pharmaceutical properties of the most relevant natural products. PSC-db may be utilized, for example, in qualitative estimation of biological activities (Quantitative Structure-Activity Relationship, QSAR) or massive docking campaigns to identify new bioactive compounds, as well as potential binding sites in target proteins. PSC-db has been implemented using the open-source PostgreSQL database platform where all compounds with their complementary and calculated information (classification, redundant names, unique IDs, physicochemical properties, etc.) were hierarchically organized. The source organism for each compound, as well as its biological activities against protein targets, cell lines and different organism were also included. PSC-db is freely available for public use and is hosted at the Universidad de Talca.

Systems Biology and Multi‐Omics

Systems Biology and Multi‐Omics

MALDI TOF Mass Spectrometry Imaging of Blood Smear: Method Development and Evaluation.

The aim of this study was to develop and evaluate matrix assisted LASER desorption ionization (MALDI) time-of-flight (TOF) mass spectrometry imaging (MSI) of blood smear. Integrated light microscope and MALDI IT-TOF mass spectrometer, together with a matrix sublimation device, were used for analysis of blood smears coming from healthy male donors. Different blood plasma removal, matrix deposition, and instrumental settings were evaluated using the negative and positive ionization modes while agreement between the light microscopy images and the lateral distributions of cellular marker compounds served as the MSI quality indicator. Red and white blood cells chemical composition was analyzed using the differential m/z expression. Five seconds of exposure to ethanol followed by the 5 min of 9-aminoacridine or α-cyano-4-hydroxycinnamic acid deposition, together with two sets of instrumental settings, were selected for the MALDI TOF MSI experiments. Application of the thin and transparent matrix layers assured good correspondence between the LASER footprints and the preselected regions of interest. Cellular marker m/z signals coincided well with the appropriate cells. A metabolite databases search using the differentially expressed m/z produced hits which were consistent with the respective cell types. This study sets the foundations for application of blood smear MALDI TOF MSI in clinical diagnostics and research.

DiaNat-DB: a molecular database of antidiabetic compounds from medicinal plants

Natural products are an invaluable source of molecules with a large variety of biological activities. Interest in natural products in drug discovery is documented in an increasing number of publications of bioactive secondary metabolites. Among those, medicinal plants are one of the most studied for this endeavor. An ever thriving area of opportunity within the field concerns the discovery of antidiabetic natural products. As a result, a vast amount of secondary metabolites are isolated from medicinal plants used against diabetes mellitus but whose information has not been organized systematically yet. Several research articles enumerate antidiabetic compounds, but the lack of a chemical database for antidiabetic metabolites limits their application in drug development. In this work, we present DiaNat-DB, a comprehensive collection of 336 molecules from medicinal plants reported to have in vitro or in vivo antidiabetic activity. We also discuss a chemoinformatic analysis of DiaNat-DB to compare antidiabetic drugs and natural product databases. To further explore the antidiabetic chemical space based on DiaNat compounds, we searched for analogs in ZINC15, an extensive database listing commercially available compounds. This work will help future analyses, design, and development of new antidiabetic drugs. DiaNat-DB and its ZINC15 analogs are freely available at http://rdu.iquimica.unam.mx/handle/20.500.12214/1186.

Latin American databases of natural products: biodiversity and drug discovery against SARS-CoV-2.

In this study, we evaluated 3444 Latin American natural products using cheminformatic tools. We also characterized 196 compounds for the first time from the flora of El Salvador that were compared with the databases of secondary metabolites from Brazil, Mexico, and Panama, and 42 969 compounds (natural, semi-synthetic, synthetic) from different regions of the world. The overall analysis was performed using drug-likeness properties, molecular fingerprints of different designs, two parameters similarity, molecular scaffolds, and molecular complexity metrics. It was found that, in general, Salvadoran natural products have a large diversity based on fingerprints. Simultaneously, those belonging to Mexico and Panama present the greatest diversity of scaffolds compared to the other databases. This study provided evidence of the high structural complexity that Latin America's natural products have as a benchmark. The COVID-19 pandemic has had a negative effect on a global level. Thus, in the search for substances that may influence the coronavirus life cycle, the secondary metabolites from El Salvador and Panama were evaluated by docking against the endoribonuclease NSP-15, an enzyme involved in the SARS CoV-2 viral replication. We propose in this study three natural products as potential inhibitors of NSP-15.

Seasonal variation of polycyclic aromatic hydrocarbon metabolites in bile of white perch Morone americana from two Chesapeake Bay tributaries.

Polycyclic aromatic hydrocarbon (PAH) accumulation in the bile is a reliable biomarker of recent exposure to environmental PAH and elevated concentrations have been identified as significant risk factors for hepatic disease in some fish species. Recent surveys (spring 2019) revealed a high incidence of hepatic lesions in white perch Morone americana from Chesapeake Bay, but this initial survey did not detect an association between PAH metabolites and lesions. Seasonal sampling of fish was extended through the winter 2020 to increase the metabolite and hepatic lesion database and better understand annual PAH exposures to white perch. Naphthalenes, phenanthrenes, and benzo[a]pyrenes (equivalents) were analyzed in bile specimens (n = 400) using high-performance liquid chromatography with fluorescence detection. Mean concentrations of metabolites were highest in fish collected from the urbanized Severn River in summer and were lowest in fish from the more rural Choptank River in winter. Variance in metabolite concentrations were primarily due to location and season. Seasonal fluctuations in water temperature, river discharge, or feeding status had little influence on the pattern of metabolite concentrations observed. The results suggest higher exposures of fish to environmental PAH in the more developed Severn River with significant increases during summer, which could correspond to a spike in seasonal recreational motor boat use or other human activities. A better understanding of the factors that contribute to variability in PAH metabolism and the enterohepatic biliary circulation in white perch will improve the usefulness of biliary metabolites as a biomarker of PAH exposure in Chesapeake Bay and elsewhere.

High Coverage Profiling of Carboxylated Metabolites in HepG2 Cells Using Secondary Amine-Assisted Ultrahigh-Performance Liquid Chromatography Coupled to High-Resolution Mass Spectrometry.

Carboxylic metabolites are an important class of metabolites, which widely exist in mammals with various types. Chemical isotope labeling liquid chromatography-mass spectrometry (CIL-LC-MS) has been widely used for the detection of carboxylated metabolites. However, high coverage analysis of carboxylated metabolites in biological samples is still challenging due to improper reactivity and selectivity of labeling reagents to carboxylated metabolites. In this study, we used N-methylphenylethylamine (MPEA) to label various types of carboxylated metabolites including short-chain fatty acids (SCFAs), medium-chain fatty acids (MCFAs), long-chain fatty acids (LCFAs), polycarboxylic acids (polyCAs), amino acids (AAs), and aromatic acids. Additionally, metabolites containing other functional groups, such as phenol, sulfhydryl, and phosphate groups, could not be labeled under the conditions of MPEA labeling. After MPEA labeling, the detection sensitivity of carboxylic acids was increased by 1-2 orders of magnitude, and their chromatographic retention on a reversed-phase (RP) column was enhanced (RT > 3 min). Under optimized labeling conditions, we used MPEA and d3-N-methylphenylethylamine (d3-MPEA) for high coverage screening of carboxylated metabolites in HepG2 cells by ultrahigh-performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS). As a result, a total of 403 potential carboxylated metabolites were obtained of which 68 were confirmed based on our established in-house chemically labeled metabolite database (CLMD). SCFAs, MCFAs, LCFAs, polyCAs, AAs, and aromatic acids were all detected in HepG2 cell extracts. Due to the successful identification of AAs, the current method increased the coverage of carboxylated metabolites compared with our previous work. Moreover, 133 and 109 carboxylated metabolites with changed contents were obtained in HepG2 cells incubated with curcumin and R-3-hydroxybutyric acid, respectively. In general, our established method realized high coverage analysis of carboxylated metabolites in HepG2 cells.

Reviewing the metabolome coverage provided by LC-MS: Focus on sample preparation and chromatography-A tutorial

Metabolomics has become an invaluable tool for both studying metabolism and biomarker discovery. The great technical advances in analytical chemistry and bioinformatics have considerably increased the number of measurable metabolites, yet an important part of the human metabolome remains uncovered. Among the various MS hyphenated techniques available, LC-MS stands out as the most used. Here, we aimed to show the capabilities of LC-MS to uncover part of the metabolome and how to best proceed with sample preparation and LC to maximise metabolite detection. The analyses of various open metabolite databases served us to estimate the size of the already detected human metabolome, the expected metabolite composition of most used human biospecimens and which part of the metabolome can be detected when LC-MS is used. Based on an extensive review and on our experience, we have outlined standard procedures for LC-MS analysis of urine, cells, serum/plasma, tissues and faeces, to guide in the selection of the sample preparation method that best matches with one or more LC techniques in order to get the widest metabolome coverage. These standard procedures may be a useful tool to explore, at a glance, the wide spectrum of possibilities available, which can be a good starting point for most of the LC-MS metabolomic studies.

Investigation of pathogenesis and therapeutic targets of acute myeloid leukemia based on untargeted plasma metabolomics and network pharmacology approach

Acute myeloid leukemia (AML) is a malignant disease originating from bone marrow hematopoietic stem cells, characterized by anemia, hemorrhage, fever, and infection, with low survival rate. However, the pathogenesis of AML is not fully understood at present. In this work, an integrated approach based untargeted metabolomics and network pharmacology was adopted to elucidate the pathogenesis of AML. Metabolic profiling of plasma samples from 14 patients and 16 healthy individuals were performed based on UHPLC-MS platform. As a result, 23 metabolites were identified by using the human metabolite database based on PLS-DA (partial least squares discriminant analysis) and independent sample test. And metabolic pathways related to AML mainly included fatty acid metabolism, amino acid metabolism, energy metabolism and lipid metabolism. Meanwhile, biomarkers-targets-pathways-disease network was constructed, 75 biomarker targets and 122 disease targets were identified. Furthermore, 30 pathways were predicted, some of which were consistent with these in metabolomics. This is the first time that metabolomics and network pharmacology approach have been combined to investigate the pathogenesis and therapeutic targets of AML. ALDH, CYP2E1 and CYP3A4 were potential therapeutic targets for AML, which provide available way to elucidate the pathogenesis and treatment of AML.

Elucidation of Gut Microbiota-Associated Lipids Using LC-MS/MS and 16S rRNA Sequence Analyses.

SummaryHost-microbiota interactions create a unique metabolic milieu that modulates intestinal environments. Integration of 16S ribosomal RNA (rRNA) sequences and mass spectrometry (MS)-based lipidomics has a great potential to reveal the relationship between bacterial composition and the complex metabolic network in the gut. In this study, we conducted untargeted lipidomics followed by a feature-based molecular MS/MS spectral networking to characterize gut bacteria-dependent lipid subclasses in mice. An estimated 24.8% of lipid molecules in feces were microbiota-dependent, as judged by > 10-fold decrease in antibiotic-treated mice. Among these, there was a series of unique and microbiota-related lipid structures, including acyl alpha-hydroxyl fatty acid (AAHFA) that was newly identified in this study. Based on the integrated analysis of 985 lipid profiles and 16S rRNA sequence data providing 2,494 operational taxonomic units, we could successfully predict the bacterial species responsible for the biosynthesis of these unique lipids, including AAHFA.