Non-targeted Metabolomics Study Research Articles

Potential nutritional and functional matters in yeast culture prepared by soybean meal fermentation.

Yeast culture (YC) is a product fermented on a specific medium, which is a type of postbiotic of anaerobic solid-state fermentation. Although YC has positive effects on the animal growth and health, it contains a variety of beneficial metabolites as dark matter, which have not been quantified. In the present study, liquid chromatography-tandem mass spectrometry is employed to identify the unknown metabolites. Following their identification, the important chemicals are quantified using HPLC-diode array detection methods. Non-targeted metabolomics studies showed that 670 metabolites in total were identified in YC, of which 23 metabolites significantly increased, including organic acids, amino acids, nucleosides and purines, isoflavones, and other substances. The chemical quantitative analysis showed that the contents of succinic acid, aminobutyric acid, glutamine, purine and daidzein increased by 84.42%, 51.07%, 100%, 68.85% and 4.60%, respectively. Therefore, the use of non-targeted metabolomics combined with chemical quantitative analysis to reveal the nutritional and functional substances of YC could help to elucidate the postbiotic mechanism and provide theoretical support for the regulation of the directional accumulation of beneficial metabolites. © 2024 Society of Chemical Industry.

Strategy to Empower Nontargeted Metabolomics by Triple-Dimensional Combinatorial Derivatization with MS-TDF Software.

Chemical derivatization is a widely employed strategy in metabolomics to enhance metabolite coverage by improving chromatographic behavior and increasing the ionization rates in mass spectroscopy (MS). However, derivatization might complicate MS data, posing challenges for data mining due to the lack of a corresponding benchmark database. To address this issue, we developed a triple-dimensional combinatorial derivatization strategy for nontargeted metabolomics. This strategy utilizes three structurally similar derivatization reagents and is supported by MS-TDF software for accelerated data processing. Notably, simultaneous derivatization of specific metabolite functional groups in biological samples produced compounds with stable but distinct chromatographic retention times and mass numbers, facilitating discrimination by MS-TDF, an in-house MS data processing software. In this study, carbonyl analogues in human plasma were derivatized using a combination of three hydrazide-based derivatization reagents: 2-hydrazinopyridine, 2-hydrazino-5-methylpyridine, and 2-hydrazino-5-cyanopyridine (6-hydrazinonicotinonitrile). This approach was applied to identify potential carbonyl biomarkers in lung cancer. Analysis and validation of human plasma samples demonstrated that our strategy improved the recognition accuracy of metabolites and reduced the risk of false positives, providing a useful method for nontargeted metabolomics studies. The MATLAB code for MS-TDF is available on GitHub at https://github.com/CaixiaYuan/MS-TDF.

Determination of bile acids in serum of pigs exposed to polychlorinated biphenyls by liquid chromatography-mass spectrometry

Exposure to polychlorinated biphenyls (PCBs) has been linked to dyslipidemia. Under acute exposure to PCBs, it has been observed that the secretion of bile acids (BAs) can be impacted, limiting (indirectly) lipid absorption in the gut. In this context, two non-targeted metabolomics studies on pig serum have recently suggested that BA concentrations may fluctuate under exposure to current non-dioxin-like (NDL)-PCB levels in food, reflecting the acute effects of such chronic exposure. The objective of this research is to implement a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for BA analysis in order to validate the findings of previous metabolomics studies, in which BA levels in serum samples from pigs exposed to environmental doses of NDL-PCBs were highlighted to be affected. The proposed LC-MS method involves the use of a C18-pentafluorophenyl LC column, which is not usually selected for the separation of BAs, but shows better performance for the separation of isomers than typical C18 columns. This LC-MS method shows excellent analytical performance such as low limits of detection (LODs) (≤1 ng/mL for most BAs) and good linearity (R2 > 0.994), while no matrix effect was observed. A total of 13 BAs have been quantified, while further BA isomers could be detected and semi-quantified. The application of this targeted LC-MS method confirmed previous findings, suggesting that exposure to low doses of NDL-PCBs decreases the concentration of BAs (i.e., glycochenodeoxycholic acid, hyodeoxycholic acid and taurochenodeoxycholic acid) while the effect on the precursors (cholic acid and chenodeoxycholic acid) is less pronounced.

Non-targeted metabolomics study for discovery of hepatocellular carcinoma serum diagnostic biomarker

Hepatocellular carcinoma (HCC) is one of the most prevalent malignant cancers worldwide. Due to the asymptomatic features of HCC at early stages, patients are often diagnosed at advanced stages and missed effective treatment. Thus, there is an urgent need to identify sensitive and specific biomarkers for HCC early diagnosis. In the present study, an ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) approach was used to profile serum metabolites from HCC patients, liver cirrhosis (LC) patients, and normal controls (NC). Univariate and multivariate statistical analyses were performed to obtain the metabolomic differences of the three groups and select significantly changed metabolites that can be used as diagnostic biomarkers. In total, 757 differential metabolites were quantified among the three groups, and pathway enrichment analysis of these metabolites indicated that glycerophospholipid metabolism, pentose and glucuronate interconversions, phenylalanine, tyrosine and tryptophan biosynthesis, and linoleic acid metabolism were the most altered pathways involved in HCC development. Receiver operating characteristic (ROC) curve analysis was performed to select and evaluate the diagnostic biomarker performance. Seven metabolites were identified as potential biomarkers that can differentiate HCC from LC and NC, and LC from NC with the good diagnostic performance of area under the curve (AUC) from 0.890 to 0.990. In summary, our findings provide highly effective biomarker candidates to differentiate HCC from LC and NC, LC, and NC, which shed insight into HCC pathological mechanisms and will be helpful in better understanding and managing HCC.

Novel Insights into the Adverse Health Effects of per- and Polyfluoroalkyl Substances on the Kidney via Human Urine Metabolomics.

Per- and polyfluoroalkyl substances (PFAS) receive significant research attention due to their potential adverse effects on human health. Evidence shows that the kidney is one of the target organs of PFAS. In occupational exposure scenarios, high PFAS concentrations may adversely affect kidney metabolism, but whether this effect is reflected in the small metabolic molecules contained in urine remains unknown. In this study, 72 matched serum and urine samples from occupational workers of a fluorochemical manufactory as well as 153 urine samples from local residents were collected, and 23 PFAS levels were quantified. The concentrations of Σ23PFAS in the serum and urine samples of workers were 5.43 ± 1.02 μg/mL and 201 ± 46.9 ng/mL, respectively, while the Σ23PFAS concentration in the urine of the residents was 6.18 ± 0.76 ng/mL. For workers, high levels of urinary PFAS were strongly correlated with levels in serum (r = 0.57-0.93), indicating that urinary PFAS can be a good indicator for serum PFAS levels. Further, a urine nontargeted metabolomics study was conducted. The results of association models, including Bayesian kernel machine regression, demonstrated positive correlations between urinary PFAS levels and key small kidney molecules. A total of eight potential biomarkers associated with PFAS exposure were identified, and all of them showed significant positive correlations with markers of kidney function. These findings provide the first evidence that urine can serve as a matrix to indicate the adverse health effects of high levels of exposure to PFAS on the kidneys.

Discovery of biomarkers related to abnormal lipid metabolism in liver and serum and intervention mechanism of ginsenoside Rb_1 in hyperlipidemia rats based on non-targeted metabolomics

Through the non-targeted metabolomics study of endogenous substances in the liver and serum of hyperlipidemia rats, the biomarkers related to abnormal lipid metabolism in hyperlipidemia rats were found, and the target of ginsenoside Rb_1 in improving hyperlipidemia was explored and its mechanism was elucidated. The content of serum biochemical indexes of rats in each group was detected by the automatic biochemical analyzer. The metabolite profiles of liver tissues and serum of rats were analyzed by HPLC-MS. Principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) were used to compare and analyze the metabolic data in the normal group, the hyperlipidemia group, and the ginsenoside Rb_1 group, and screen potential biomar-kers. The related metabolic pathways were further constructed by KEGG database analysis. The results showed that hyperlipemia induced dyslipidemia in rats, which was alleviated by ginsenoside Rb_1. The non-targeted metabolomics results showed that there were 297 differential metabolites in the liver tissues of hyperlipidemia rats, 294 differential metabolites in the serum samples, and 560 diffe-rential metabolites in the hyperlipidemia rats treated by ginsenoside Rb_1. Perillic acid and N-ornithyl-L-taurine were common metabolites in the liver and serum samples, which could be used as potential biomarkers for ginsenoside Rb_1 in the improvement of hyperlipidemia. As revealed by pathway enrichment in the liver and serum, ginsenoside Rb_1 could participate in the metabolic pathway of choline in both the liver and serum. In addition, ginsenoside Rb_1 also participated in the ABC transporter, alanine, aspartic acid, and glutamate metabolism, protein digestion and absorption, β-alanine metabolism, taurine and hypotaurine metabolism, caffeine metabolism, valine, leucine, and isoleucine biosynthesis, arachidonic acid metabolism, and methionine and cysteine metabolism to improve dyslipidemia in rats.

Deciphering the metabolic profile and anti-colorectal cancer mechanism of Capilliposide A using ultra performance liquid chromatography mass spectrometry combined with non-targeted metabolomics studies

Colorectal cancer is a highly prevalent malignancy that threatens human health worldwide. Despite the availability of chemotherapy as a primary treatment option, individuals with CRC undergoing frequent chemotherapy are susceptible to developing drug resistance, which can result in poor treatment outcomes. Consequently, there is an urgent need to discover new bioactive compounds for the treatment of CRC. Capilliposide A is a triterpenoid saponin that is extracted from Lysimachia capillipes Hemsl. Although it has been reported that LC-A exhibits good bioactivity, its metabolic profile and potential mechanism underlying its anti-CRC effects remain unknown. In this study, the metabolic products of LC-A in rat plasma, feces, and urine were identified using an LC-MS platform. In addition, LC-MS-based metabolomics was employed to investigate the mechanism of LC-A against CRC. The results showed that LC-A significantly inhibited CRC cell proliferation, attenuated tumor growth, and alleviated metabolic abnormalities in CRC-bearing mice. Furthermore, the levels of p-cresol sulfate and phenylacetylglycine in CRC model plasma decreased, with an increment in sphingosine 1-phosphate, D-tryptophan, and L-2-aminoadipic acid. These metabolite levels can be reversed by LC-A treatment. These metabolite alterations were related to the sphingolipid and amino acid metabolic pathways, demonstrating that LC-A anti-CRC effects were regulated through the modulation of underlying metabolism. Additionally, seven metabolites of LC-A were characterized in rat feces, plasma, and urine. This study offers a scientific foundation for elucidating the metabolism of LC-A and its treatment of colorectal cancer.

Non-Targeted Metabolomic Study of Fetal Growth Restriction.

We aimed to explore the differential metabolites in amniotic fluid and its cells from fetuses with fetal growth restriction (FGR). A total of 28 specimens of amniotic fluid were collected, including 18 with FGR and 10 controls. Differential metabolites in all samples were detected by chromatography-mass spectrometry. Principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) were used to analyze the differences in metabolic spectra between the FGR and control groups through multidimensional and single-dimensional statistical analysis. The KEGG database was used for metabolic pathway enrichment analysis. Both PCA and OPLS-DA models showed a clear separation trend between FGR and control groups. We identified 27 differentially expressed metabolites in the amniotic fluid supernatant of the two groups (p < 0.05), of which 14 metabolites were up-regulated in the FGR group, and 13 metabolites, such as glutamate, phenylalanine, valine and leucine, were down-regulated. We also identified 20 differentially expressed metabolites in the amniotic fluid cell (p < 0.05), of which 9 metabolites, including malic acid, glycolic acid and D-glycerate, were up-regulated significantly and 11 metabolites, including glyceraldehyde, were down-regulated. Pathway analysis showed that most of the identified differential metabolites were involved in tricarboxylic acid cycle (TCA cycle), ABC transport, amino acid metabolism pathways and so on. The results indicated that many metabolic changes associated with FGR, which are mainly manifested by abnormal metabolism of amino acid in amniotic fluid and abnormal glucose metabolism including TCA cycle in amniotic fluid cells, respectively. Our findings provide more data for exploring the mechanism of FGR and the potential therapy targets.

Shades of Fine Dark Chocolate Colors: Polyphenol Metabolomics and Molecular Networking to Enlighten the Brown from the Black.

High-quality dark chocolates (70% cocoa content) can have shades from light to dark brown color. This work aimed at revealing compounds that discriminate black and brown chocolates. From 37 fine chocolate samples from years 2019 and 2020 provided by Valrhona,8 dark black samples and 8 light brown samples were selected. A non-targeted metabolomics study was performed based on ultra-high performance liquid chromatography-high resolution mass spectrometry/mass spectrometry experiments, univariate, multivariate, and feature-based molecular networking analyses. Twenty-seven overaccumulated discriminating compounds were found for black chocolates. Among them, glycosylated flavanols including monomers and glycosylated A-type procyanidin dimers and trimers were highly representative. Fifty overaccumulated discriminating compounds were found for brown chocolates. Most of them were B-type procyanidins (from trimers to nonamers). These phenolic compounds may be partially related to the chocolate colors as precursors of colored compounds. This study increases the knowledge on the chemical diversity of dark chocolates by providing new information about the phenolic profiles of black and brown chocolates.

Integrated serum pharmacochemistry and metabolomics reveal potential effective components and mechanisms of Shengjiang Xiexin decoction in the treatment of Clostridium difficile infection

Shengjiang Xiexin Decoction (SXD) is a widely recognized formula in Traditional Chinese Medicine (TCM) for treating diarrhea and is commonly used in clinical practice. Clostridium difficile infection (CDI) is a type of antibiotic-associated diarrhea with a rising incidence rate that has severe consequences for humans. Recent clinical applications have found significant efficacy in using SXD as an adjunct to CDI treatment. However, the pharmacodynamic substance basis and therapeutic mechanism of SXD remain unclear. This study aimed to systematically analyze the metabolic mechanisms and key pharmacodynamic components of SXD in CDI mice by combining non-targeted metabolomics of Chinese medicine and serum medicinal chemistry. We established a CDI mouse model to observe the therapeutic effect of SXD on CDI. We investigated the mechanism of action and active substance composition of SXD against CDI by analyzing 16S rDNA gut microbiota, untargeted serum metabolomics, and serum pharmacochemistry. We also constructed a multi-scale, multifactorial network for overall visualization and analysis. Our results showed that SXD significantly reduced fecal toxin levels and attenuated colonic injury in CDI model mice. Additionally, SXD partially restored CDI-induced gut microbiota composition. Non-targeted serum metabolomics studies showed that SXD not only regulated Taurine and hypotaurine metabolism but also metabolic energy and amino acid pathways such as Ascorbate and aldarate metabolism, Glycerolipid metabolism, Pentose and glucuronate interconversions, as well as body and other metabolite production in the host. Through the implementation of network analysis methodologies, we have discerned that Panaxadiol, Methoxylutcolin, Ginsenoside-Rf, Suffruticoside A, and 10 other components serve as critical potential pharmacodynamic substance bases of SXD for CDI. This study reveals the metabolic mechanism and active substance components of SXD for the treatment of CDI mice using phenotypic information, gut microbiome, herbal metabolomics, and serum pharmacochemistry. It provides a theoretical basis for SXD quality control studies.

Cryptic Chemical Variation in a Marine Red Alga as Revealed by Nontargeted Metabolomics.

Many marine algae occupy habitats that are dark, deep, or encrusted on other organisms and hence are frequently overlooked by natural product chemists. However, exploration of less-studied organisms can lead to new opportunities for drug discovery. Genetic variation at the individual, species, genus, and population levels as well as environmental influences on gene expression enable expansion of the chemical repertoire associated with a taxonomic group, enabling natural product exploration using innovative analytical methods. A nontargeted LC-MS and 1H NMR spectroscopy-based metabolomic study of 32 collections of representatives of the calcareous red algal genus Peyssonnelia from coral reef habitats in Fiji and the Solomon Islands revealed significant correlations between natural products' chemistry, phylogeny, and biomedically relevant biological activity. Hierarchical cluster analysis (HCA) of LC-MS data in conjunction with NMR profiling and MS/MS-based molecular networking revealed the presence of at least four distinct algal chemotypes within the genus Peyssonnelia. Two Fijian collections were prioritized for further analysis, leading to the isolation of three novel sulfated triterpene glycosides with a rearranged isomalabaricane carbon skeleton, guided by the metabolomic data. The discovery of peyssobaricanosides A-C (15-17) from two Fijian Peyssonnelia collections, but not from closely related specimens collected in the Solomon Islands that were otherwise chemically and phylogenetically very similar, alludes to population-level variation in secondary metabolite production. Our study reinforces the significance of exploring unusual ecological niches and showcases marine red algae as a chemically rich treasure trove.

A non-targeted metabolomics study on serum of occupational people exposed with nanometer titanium dioxide particles (TiO(2)-NPs)

Objective: To study the changes of serum metabolic profile of occupational people exposed with nanometer titanium dioxide particles (TiO(2)-NPs), and to explore the biomarkers and injury mechanism of TiO(2)-NPs health effects. Methods: From June 2020 to June 2021, a TiO(2)-NPs production enterprise was selected as the research site by a typical sampling method, 64 people in the TiO(2)-NPs exposure group were selected from the enterprise, and 62 people of the logistics administrative staff in the same enterprise were selected as the control group, and blood samples were collected using non-anticoagulant blood collection tubes. After the samples were methanol-precipitated, the untargeted metabolomic data was collected by ultra-high performance liquid chromatography time-of-flight mass spectrometry, and biomarkers were screened and metabolic pathway analysis was performed. Results: 46 different metabolites were screened out by P<0.05 and variable importance projection index (VIP) value >1, mainly including glycerides, sphingomyelin, glycerophospholipid, fatty acyl, etc.; By ROC analysis to determine 3-hydroxy-4, 5-dimethyl-2 (5H) - furanone, 4-aminobiphenyl, heptanoylcarnitine, Hexadecanedioic acid mono-L-carnitine ester, Ibutilide, LysoPA (18∶1 (9Z) /0∶0), LysoPC (18∶0), PC (16∶0/16∶0), PC (16∶0/20: 4 (5Z, 8Z, 11Z, 14Z) ), PC (P-18∶1 (9Z) /P-18∶1 (9Z) ) 10 candidate biomarkers; involving changes in 4 metabolic pathways, namely glycerophospholipid metabolism, sphingolipid metabolism, phenylalanine, tyrosine and tryptophan acid biosynthesis, linoleic acid metabolism. Conclusion: Occupational exposure to TiO(2)-NPs has a significant impact on serum metabolic profiles.

Comprehensive Metabolome Analysis Identified Novel Biomarkers for the Diagnosis and Prognosis of Diffuse Large B-Cell Lymphoma

Background Metabolic reprogramming is a major hallmark of cancer, providing tumor cells with vital energy and metabolites. Diffuse large B-cell lymphoma (DLBCL) is metabolically heterogeneous, and there was also evidence that altered metabolism is associated with tumor progression and prognosis. This study was aimed to assess the characteristics of metabolic reprogramming and novel biomarkers in DLBCL, thereby proposing a novel therapeutic strategy for DLBCL. Methods Serum sample were obtained from100 patients with newly diagnosed DLBCL and 70 age-gender matched healthy controls in the study. Non-targeted metabolomics studies were performed based on liquid mass spectrometry (LC-MS) technology. The normalized peak areas (normalized by IS) metabolites were introduced into SIMCA software for multivariate statistical analysis. Metabolomic pathway analysis of metabolic biomarkers was performed using MetbraAnalyst5.0. Results We first analyzed differential metabolite profiles in the serum of DLBCL patients. The metabolites detected in positive and negative ion modes were analyzed separately. Compared to the healthy control, DLBCL patients were featured with a specific metabolic profile, indicating the differential metabolism in disease state. We then established a model containing metabolic information by orthogonal partial least squares discriminant analysis (OPLS-DA) and tested its ability to identify new samples in seven cross-validations. The variable importance in the projection (VIP) was also calculated for each metabolite. We further screened for differentially expressed metabolites by plotting collapsed changes (fold change>1.5 or <0.667, p<0.05). In DLBCL patients, 33 up-regulated metabolomes and 48 down-regulated metabolites were detected in positive ion mode, while 19 up-regulated metabolites and 29 down-regulated metabolites were in negative ion mode. Enrichment analyses showed that differential metabolites were mainly enriched in D-Glutamine and D-glutamate metabolism, caffeine metabolism, and ascorbate and aldarate metabolism. We then attempted to verify whether the differential metabolites had diagnostic value in DLBCL patients. By using random forest analysis, 2-Phenylpropionicacid, 4-oxododecanedioicacid, cis-4-Hydroxy-D-proline, Hypoxanthine Octanedioicacid under positive ion mode, and Xanthosine, Subericacid, Diethyloxalpropionate, 4-Oxoproline Azelaicacid under negative ion mode, were screened out as potential biomarkers. Based on the above biomarkers, diagnostic models were developed and revealed the mean accuracies of 0.9460 in positive mode and 0.943 in negative mode. Receiver operating characteristic (ROC) curves then verified the significant sensitivity and specificity of the diagnostic models. Notably, the Area Under Curve（AUC）of the combined diagnostic model was superior to that of each metabolite, indicating that combined model values could significantly improve the diagnostic performance in DLBCL. Further investigations were aimed to explore the correlation of metabolite profiles with clinical features in DLBCL. Venn diagram profiled the differential metabolites between patients with GCB-like DLBCL and ABC-like DLBCL. Correlation analysis then suggested that the differential metabolites were correlated with clinical prognostic indicators in DLBCL patients. In particular, D-Glucuronic acid and Lignoceric acid were significantly associated with Ki-67 expression (tumor proliferation index), cis-4-Hydroxy-D-proline was significantly associated with LDH and β2-MG, and 2-Phenylpropionic acid significantly correlated with LDH, PLT and ALB. Conclusions Our study revealed the metabolic profile of DLBCL and found a relatively high diagnostic value of metabolite-based diagnostic models constructed. Furthermore, the combination with clinical data suggests that D-glucuronide, lignoceric acid, cis-4-hydroxy-D-proline and 2-phenylpropionic acid may be potential prognosis-related biomarkers in DLBCL. Targeting metabolic reprogramming is expected to provide novel strategies for the treatment of DLBCL. Keywords DLBCL, metabolomics, biomarkers, D-glucuronide, tumor Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Nontargeted metabolomics study and pharmacodynamic evaluation of bidirectional fermentation for Ganoderma lucidum with Marsdenia tenacissima.

Lung cancer is one of the malignant tumors with the fastest incidence rate and mortality growth and the greatest threat to human health and life. Marsdenia tenacissima is an antitumor of Chinese medicine. However, Marsdenia tenacissima has low bioavailability in the human body and most of its main active substances are aglycones, such as Tenacigenin A, Tenacigenin B. This study aims to produce biotransformation products rich in pungent saponins by using Marsdenia tenacissima as a fermentation medium of Ganoderma lucidum. Non-targeted metabolomics analysis was carried out on the fermentation products after the optimization process. A total of 249 differential metabolites were detected, and the content of saponins increased from 0.1% to 0.41% and most of them were tenacigenin. Furthermore, the biotransformation of C21 steroidal glycosides in Marsdenia tenacissima was the central reaction in this fermentation process. Pharmacodynamics resewed that the anticancer effect of Marsdenia tenacissima was significantly enhanced after fermentation, mainly through inhibiting the growth and apoptosis of cancer cells.

The Changes of Microbial Communities and Key Metabolites after Early Bursaphelenchus xylophilus Invasion of Pinus massoniana.

Pine wood nematode, Bursaphelenchus xylophilus, is a worldwide pest of pine trees, spreading at an alarming rate and with great ecological adaptability. In the process of causing disease, the nematode causes metabolic disorders and changes in the endophytic microbial community of the pine tree. However, the changes at the pine nidus during early nematode invasion have not been well studied, especially the differential metabolites, in Pinus massoniana, the main host of B. xylophilus in China. In this study, we analyzed the endophytic bacterial and fungal communities associated with healthy and B. xylophilus-caused wilted pine trees. The results show that 1333 bacterial OTUs and 502 fungal OTUs were annotated from P. massoniana stem samples. The abundance of bacterial communities in pine trees varies more following infection by B. xylophilus, but the abundance changes of fungal communities are less visible. There were significant differences in endophytic microbial diversity between wilted and healthy P. massoniana. In wilted pine trees, Actinobacteria and Bacteroidia were differential indicators of bacterial communities, whereas, in healthy pine trees, Rhizobiales in the Proteobacteria phylum were the major markers of bacterial communities. Meanwhile, the differential markers of fungal communities in healthy pines are Malasseziales, Tremellales, Sordariales, and Fusarium, whereas Pleosporaceae is the key marker of fungal communities in wilted pines. Our study examines the effect of changes in the endophytic microbial community on the health of pine trees that may be caused by B. xylophilus infection. In parallel, a non-targeted metabolomic study based on liquid mass spectrometry (LC-MS) technology was conducted on pine trees inoculated with pine nematodes and healthy pine trees with a view to identifying key compounds affecting early pine lesions. Ultimately, 307 distinctly different metabolites were identified. Among them, the riboflavin metabolic pathway in pine trees may play a key role in the early pathogenesis of pine wood nematode disease.

A systems toxicological analysis of oxybenzone effects on the metabolic physiology of embryo-larval zebrafish (Danio rerio)

• Embryo-larval zebrafish were exposed to two concentrations of oxybenzone. • The low dose oxybenzone caused a two-fold increase in larval metabolic rate. • RNA-sequencing analysis indicated effects on metabolism and biological regulation. • Transcriptomics and metabolic rate data was used to parameterize metabolic models. • Simulation of disrupted glycerolipid metabolism explained bioenergetics effects. Oxybenzone is an emerging aquatic pollutant whose widespread use has contributed to its detection in the surface waters and body-burdens of exposed biota. In this study, the sub-lethal toxicity effects of oxybenzone were studied at the environmentally relevant concentrations of 0.6 and 5.2 µg/L (including 0.01% DMSO as the solvent control). An integrative in vivo and in silico experimental approach was taken to study the effects of exposure on the metabolic physiology of larval zebrafish ( Danio rerio ) after 7 days of exposure (from 2 to 9 days post fertilization). The use of whole-organism respirometry showed a statistically significant ∼2x increase in metabolic rate for the 0.6 µg/L treatment group, with no significant differences between the solvent control versus 5.2 µg/L oxybenzone treatment level. The analysis of whole-transcriptome RNA-sequencing data showed functional categories related to metabolism (metabolic enzymes) and biological regulation (genome regulation, cell signaling) to be highly dysregulated. The transcriptomics changes for metabolic enzyme genes were used to parameterize in silico stoichiometric metabolic models for each treatment group. Flux balance analysis (FBA) simulations for each metabolic model revealed glycerolipid metabolism to be highly affected under the low dose oxybenzone exposure. The further analysis of core metabolic pathways revealed elevated flux through the esterification reactions of glycerolipid metabolism, producing triglycerides. The elevated in vivo metabolic rate observed for 0.6 µg/L oxybenzone is explainable by the elevated catalytic activities of the esterification reactions. Furthermore, the disruption of glycerolipid metabolism predicted by our in silico analysis agrees with the results of non-targeted metabolomics studies performed by other authors, and which demonstrate oxybenzone exposure to cause dyslipidemia and affect glycerophospholipid metabolism. Therefore, the methods of our study provide a framework for integrated biological pathways-based toxicological analysis.

Alismatis Rhizoma methanolic extract-Effects on metabolic syndrome and mechanisms of triterpenoids using a metabolomic and lipidomic approach.

Alismatis rhizoma is a traditional Chinese medicine. Studies have demonstrated that Alismatis rhizoma also has therapeutic effects on metabolic syndrome. However, the pharmacodynamic material basis and mechanism are still unclear. First, UHPLC/Q-Orbitrap MS was used to detect the chemical components of the Alismatis rhizoma extract, and 31 triterpenoids and 2 sesquiterpenes were preliminarily identified. Then, to investigate the mechanism of the Alismatis rhizoma extract on metabolic syndrome, a mouse model of metabolic syndrome induced by high-fructose drinks was established. The results of serum biochemical analysis showed that the levels of TG, TC, LDL-C, and UA after the Alismatis rhizoma extract treatment were markedly decreased. 1H-NMR was used to conduct non-targeted metabolomics studies. A total of 20 differential metabolites were associated with high-fructose–induced metabolic syndrome, which were mainly correlated with 11 metabolic pathways. Moreover, UHPLC/Q-Orbitrap MS lipidomics analysis found that a total of 53 differential lipids were screened out. The results showed that Alismatis rhizoma extract mainly reduces the synthesis of glycerophospholipid and ceramide and improves the secretion of bile acid. This study shows that the Alismatis rhizoma extract can treat metabolic syndrome mainly by inhibiting energy metabolism, amino acid metabolism, and regulating bile acid to reduce phospholipid content.

Photosynthetic, antioxidative, and metabolic adjustments of a crop plant to elevated levels of La and Ce exposure

Rare earth elements (REEs) have been widely applied as fertilizers in farmland of China for decades to improve the yield and quality of crops. Unfortunately, adverse effects on plants have been observed due to overdosing with REEs. Until now, the toxicology of REEs was mainly evaluated based on phenotypic responses, but knowledge gaps still exist concerning their metabolic effects. Here, the physiological responses and nontargeted metabolomics studies were combined to systematically explore the potential effects of La and Ce on a crop plant, wheat Triticum aestivum. It was observed that REEs accumulated in the shoots of wheat, with significant reduction of the shoot biomass at higher exposure doses. The disturbance of photosynthesis and induced oxidative stress were identified by analyzing indicators of the photosynthetic (chlorophyll a/b, carotenoid and rubisco) and antioxidant systems (POD, CAT, SOD, GSH and MDA). Furthermore, the global metabolic profiles of REEs treatment groups and the non-exposed control group were screened and compared, and the metabolomic disturbance of REEs was dose-dependent. A high overlap of significantly changed metabolites and matched disturbed biological pathways was found between La and Ce treatments, indicating similarity of their toxicity mechanism in wheat shoots. Generally, the perturbed metabolomic pathways were mainly related to carbohydrate, amino acid and nucleotide/side metabolism, suggesting a disturbance of carbon and nitrogen metabolism, which finally affected the growth of wheat. We thus proved the potential adverse effect of inappropriate application of REEs in crop plants and postulated metabolomics as a feasible tool to identify the underlying toxicological mechanisms.

Food authentication in the routine laboratory: Determination of the geographical origin of white asparagus using a simple targeted LC-ESI-QqQ-MS/MS approach

In the last decade, research efforts to develop non-targeted metabolomics strategies, especially for the detection of various food authenticity parameters, have increased significantly. However, such methods are hardly implemented in routine analysis so far, which is due to the relatively expensive equipment as well as the lack of reference databases. The present study describes the downstream process for converting a non-targeted metabolomics study into a simple targeted approach suitable for routine analysis. Using 20 marker compounds and random forest algorithm (RF), the geographical origin of 140 asparagus samples from five regions (Germany, Poland, the Netherlands, Greece/Spain, and Peru) was determined. With a prediction accuracy of 76%, the targeted method provided only a slightly worse result than the non-targeted method and significantly better results than the isotope ratio mass spectrometry (IRMS), which is currently used for comparable issues.

Toxicity and Metabolomic Impact of Cobalt, Chromium, and Nickel Exposure on HepaRG Hepatocytes.

Cobalt, chromium, and nickel are used in orthopedic prostheses. They can be released, accumulate in many organs, and be toxic. The aim of this study is to evaluate the cytotoxicity of these metals on human hepatocytes and to improve our knowledge of their cellular toxicity mechanisms by metabolomic analysis. HepaRG cells were incubated for 48 h with increasing concentrations of metals to determine their IC50. Then, a nontargeted metabolomic study using liquid chromatography-high-resolution mass spectrometry (LC-HRMS) was done at IC50 and at a lower concentration (100 nM), near to those found in the blood and liver of patients with prostheses. IC50 were defined at 940, 2, and 1380 μM for Co, Cr, and Ni, respectively. In vitro, Cr appears to be much more toxic than Co and Ni. Metabolomic analysis revealed the disruption of metabolic pathways from the low concentration of 100 nM, in particular tryptophan metabolism and lipid metabolism illustrated by an increase in phenylacetylglycine, a marker of phospholipidosis, for all three metals. They also appear to be responsible for oxidative stress. Dysregulation of these pathways impacts hepatocyte metabolism and may result in hepatotoxicity. Further investigations on accessible biological matrices should be conducted to correlate our in vitro results with the clinical data of prostheses-bearing patients.