Metabolomics Strategy Research Articles

Pseudo-targeted metabolomics analysis of the therapeutic effect of phenolics-rich extract from Se-enriched green tea (Camellia sinensis) on LPS-stimulated murine macrophage (RAW264.7)

Selenium (Se)-enriched green tea (Se-Te) has been recognized as a possible source of Se supplements, while the effect of Se enrichment on function of polyphenols in green tea is still unclear. In this study, a pseudo-targeted metabolomics strategy was carried out to reveal the regulatory mechanism of polyphenols extracted from Se-Te and regular green tea (Re-Te) on inflammatory response at cellular level. A novel analysis strategy using UHPLC/ESI Q-Orbitrap combined with MS-IOP was applied to profile the dynamic changes of metabolites in LPS-stimulated RAW264.7 macrophages during polyphenols incubation. A total of 128 characteristic variables (VIP > 1, p < 0.05) were screened in Se-Te group and the results of bioinformatics analysis and quantitative research indicated that in addition to the 6 conventional immune protective pathways involved in tea polyphenols, Se-enriched polyphenols were also participated in 3 unique antioxidant enzyme activation pathways, including phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism and pantothenate and CoA biosynthesis. The result of weight calculation based on topological analysis indicated that the promoting synthesis of antioxidant enzymes was the main mechanism of Se-Te polyphenols to inhibit inflammation. However, compared with Re-Te group, the intracellular B vitamin pathway in Se-Te group was disturbed, which is related to the fact that Se supplementation can promote the synthesis of selenoprotein and catalyze the reduction of thioredoxin by NADPH, thus blocking the signaling pathways of B vitamins. This study comprehensively explored the immune protective mechanism of polyphenols extracted from Se-Te and Re-Te under natural growth conditions, which could give a better understanding of the potential nutritional value of Se-Te as a widely used Se supplement.

Metabolomics-based screening and chemically identifying abundant stachydrine as quality characteristic of rare Leucosceptrum canum Smith honey

Leucosceptrum canum Smith honey (LcSH) is a rare and high-value monofloral honey. However, it is difficult to evaluate the authenticity of LcSH since there is little knowledge of its chemical composition. In the present research, we compared LcSH to other common honeys using a metabolomics strategy and screened a molecular feature with a mass of 143.0948 Da that was unique to LcSH. According to HR-MS and NMR spectroscopy, it was identified as stachydrine, which is well known to have a variety of pharmacological activities. The result was confirmed against a reference standard. A UHPLC-MS/MS method was developed to determine its concentration in honey samples. Stachydrine was abundant in LcSH compared to other honeys, ranging from 0.35 mg/g to 0.68 mg/g. Levels of stachydrine were measured 18 months after the initial sampling and did not show significant statistical differences (p < 0.01), suggesting it is chemically stable in LcSH. This study indicates that stachydrine is a useful characteristic component to evaluate and control LcSH authenticity.

Integration of Non-Targeted Metabolomics and Targeted Quantitative Analysis to Elucidate the Synergistic Antidepressant Effect of Bupleurum Chinense DC-Paeonia Lactiflora Pall Herb Pair by Regulating Purine Metabolism.

Bupleurum chinense DC (Chaihu)-Paeonia lactiflora Pall (Baishao) is among the most accepted herb pairs in many classic antidepressant prescriptions. Our previous study has shown that the Chaihu-Baishao herb pair (CBHP) had a better antidepressant effect than Chaihu or Baishao. Nevertheless, the synergistic antidepressant mechanism of this herb pair was not clearly understood. This study aimed to investigate the compatibility mechanism of Chaihu and Baishao for treating depression through a strategy of non-targeted metabolomics combined with targeted quantitative analysis and molecular biology techniques. First, the compatibility effects of CBHP were assessed by the chronic unpredictable mild stress (CUMS) rat model. Next, cortex metabolomics based on ultra-high-performance liquid chromatography combined with quadrupole orbitrap mass spectrometry (UPLC-Q-Orbitrap/MS) was used to discover the metabolic pathway that was synergistically regulated by CBHP. Based on the results of metabolomics analysis, metabolites were quantitatively validated by UPLC-MS/MS combined with the MRM mode in the crucial metabolic pathway. In addition, the signaling pathway associated with this metabolic pathway was detected by molecular biology techniques to further identify the biological meaning of the crucial metabolite on the synergistic antidepressant effect of CBHP. The antidepressant effect of CBHP was significantly better than that of Chaihu or Baishao single administrated in the behavioral test. According to cortex metabolomics, a total of 21 differential metabolites were screened out, and purine metabolism was selected as the crucial metabolic pathway by the enrichment analysis of differential metabolites. Subsequently, purine metabolism was confirmed as disorder in the CUMS group by targeted quantitative analysis, CBHP regulated more purine metabolites (six) than individual administration (two and two). The results showed that purine metabolism was modulated by CBHP through synergistically decreasing xanthine levels and inhibiting the conversion of xanthine dehydrogenase (XDH) to xanthine oxidase (XOD). Finally, the synergistic regulation effect of CBHP on xanthine synthesis was found to be related to inhibition of malondialdehyde (MDA) production, Nod-like receptor protein 3 (NLRP3) inflammasome expression, and interleukin (IL)-1β, IL-6, and tumor necrosis factor (TNF)-α secretion. The present study demonstrated that the regulation of purine metabolism, the suppression of oxidative stress, and inflammatory responses in the cortex were involved in the synergistic antidepressant effect of CBHP.

Multivariate Statistical Analysis of Metabolites in Anisodus tanguticus (Maxim.) Pascher to Determine Geographical Origins and Network Pharmacology.

Anisodus tanguticus (Maxim.) Pascher, has been used for the treatment of septic shock, analgesia, motion sickness, and anesthesia in traditional Tibetan medicine for 2,000 years. However, the chemical metabolites and geographical traceability and their network pharmacology are still unknown. A total of 71 samples of A. tanguticus were analyzed by Ultra–Performance Liquid Chromatography Q–Exactive Mass Spectrometer in combination with chemometrics developed for the discrimination of A. tanguticus from different geographical origins. Then, network pharmacology analysis was used to integrate the information of the differential metabolite network to explore the mechanism of pharmacological activity. In this study, 29 metabolites were identified, including tropane alkaloids, hydroxycinnamic acid amides and coumarins. Principal component analysis (PCA) explained 49.5% of the total variance, and orthogonal partial least-squares discriminant analysis (OPLS–DA) showed good discrimination (R2Y = 0.921 and Q2 = 0.839) for A. tanguticus samples. Nine differential metabolites accountable for such variations were identified through variable importance in the projection (VIP). Through network pharmacology, 19 components and 20 pathways were constructed and predicted for the pharmacological activity of A. tanguticus. These results confirmed that this method is accurate and effective for the geographic classification of A. tanguticus, and the integrated strategy of metabolomics and network pharmacology can explain well the “multicomponent—-multitarget” mechanism of A. tanguticus.

Identification of chemical components in Dianthus determined by widely targeted metabolomics

The chemical composition of the secondary metabolites is of great significance to the quality control of agricultural products. The genus Dianthus is famous for its beautiful flowers in the cut flower trade and also used in the traditional Chinese medicinal system and food market. However, the chemical composition in Dianthus is still unknown. The current study examined the levels of different metabolites of the flowers in Dianthus caryophyllus, Dianthus chinensis and Dianthus superbus via the use of the widely targeted metabolomic strategy. We obtained the structure and content of 423 metabolites in Dianthus, which included the primary and secondary metabolites. The principal component analysis was able to clearly seperate Dianthus caryophyllus, Dianthus chinensis and Dianthus superbus based on the flower metabolites. The differential metabolites can be categorised into 11 different classes, the majority were flavonoids, amino acids and their derivatives, phenolic acids and lipids. The results of this study provide important information for the effective use of Dianthus flowers in edible, medicinal and therapeutic aspects.

Metabolomics with multi-block modelling of mass spectrometry and nuclear magnetic resonance in order to discriminate Haplosclerida marine sponges.

A comprehensive metabolomic strategy, integrating 1H NMR and MS-based multi-block modelling in conjunction with multi-informational molecular networking, has been developed to discriminate sponges of the order Haplosclerida, well known for being taxonomically contentious. An in-house collection of 33 marine sponge samples belonging to three families (Callyspongiidae, Chalinidae, Petrosiidae) and four different genera (Callyspongia, Haliclona, Petrosia, Xestospongia) was investigated using LC-MS/MS, molecular networking, and the annotations processes combined with NMR data and multivariate statistical modelling. The combination of MS and NMR data into supervised multivariate models led tothe discrimination of, out of the four genera, three groups based on the presence of metabolites, not necessarily previously described in the Haplosclerida order. Although these metabolomic methods have already been applied separately, it is the first time that a multi-block untargeted approach using MS and NMR has been combined with molecular networking and statistically analyzed, pointing out the pros and cons of this strategy.

Unveiling the mechanism of action of nature-inspired anti-cancer compounds using a multi-omics approach

The 2020 global cancer registry has ranked breast cancer (BCa) as the most commonly diagnosed type of cancer and the most common cause of cancer-related deaths in women worldwide. Increasing resistance and significant side effects continue to limit the efficacy of anti-BCa drugs, hence the need to identify new drug targets and to develop novel compounds to overcome these limitations. Nature-inspired anti-cancer compounds are becoming increasingly popular since they often provide a relatively safe and effective alternative. In this study, we employed multi-omics techniques to gain insights into the relevant mechanism of action of two recently identified new nature-inspired anti-cancer compounds (SIMR3066 and SIMR3058). Discovery proteomics analysis combined with LC-MS/MS-based untargeted metabolomics analysis was performed on compound-treated vs DMSO-treated (control) MCF-7 cells. Downstream protein functional enrichment analysis showed that most of the responsive proteins were functionally associated with antigen processing and neutrophil degranulation, RNA catabolism and protein folding as well as cytoplasmic vesicle lumen and mitochondrial matrix formation. Consistent with the proteomics findings, metabolomic pathway analysis suggested that the differentially abundant compounds indicated altered metabolic pathways such as glycolysis, the Krebs cycle and oxidative phosphorylation. Furthermore, metabolomics-based enriched-for-action pathway analysis showed that the two compounds associate with mercaptopurine, thioguanine and azathioprine related pathways. Lastly, integrated proteomics and metabolomics analysis revealed that treatment of BCa with SIMR3066 disrupts several signaling pathways including p53-mediated apoptosis and the circadian entertainment pathway. Overall, the multi-omics approach we used in this study indicated that it is a powerful tool in probing the mechanism of action of lead drug candidates. SignificanceIn this study we adopted a multi-omics (proteomics and metabolomics) strategy to learn more about the molecular mechanisms of action of nature-inspired potential anticancer drugs. Following treatment with SIMR3066 or SIMR3058, the integration of these multi-omics data sets revealed which biological pathways are altered in BCa cells. This study demonstrates that combining proteomics with metabolomics is a powerful method to investigate the mechanism of action of potential anticancer lead drug candidates.

A GC–MS-Based Metabolomic Strategy to Investigate the Protective Effects of Mulberry Polysaccharide on CCl4-Induced Acute Liver Injury in Mice

BackgroundMulberry (Morus alba) fruits of the woody mulberry tree (family: Moraceae Morus) is a type of mulberry fruit grown in the southern Xinjiang region, which polysaccharides have antioxidant and liver protective effects. This article further preliminary study on the protective effects of mulberry polysaccharide (MP) on liver.MethodA detection kit was used to assess serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), liver malondialdehyde (MDA), superoxide dismutase (SOD) and other indicators. Liver tissue sections were stained with hematoxylin and eosin (H&E) and observed under a microscope. The entire endogenous metabolite profiling was acquired via metabolomics strategy using gas chromatography-mass spectrometry (GC–MS) to assess the underlying protective mechanisms of MPs. ResultsResults indicated that MPs exerted a hepatoprotective effect on acute liver injury by decreasing serum ALT and AST levels, hepatic MDA, and restored hepatic SOD glutathione peroxidase (GSH-Px) activities. A total of 33 possible endogenous metabolites associated with lipid, glucose, and energy metabolism including amino acids, sugars, and fatty acids, were found.ConclusionThe results of the present study provide a reference for elucidating the protective mechanisms of MPs against acute liver injury.Graphical Abstract

Therapeutic Effect of Buyang Huanwu Decoction on the Gut Microbiota and Hippocampal Metabolism in a Rat Model of Cerebral Ischemia.

Buyang Huanwu decoction (BHD) is a well-known Chinese herbal prescription. It has been widely used in the clinical treatment of cerebral ischemia (CI) in China. However, the mechanism underlying the treatment of CI with BHD remains to be elucidated. In this study, we combined microbiomic and metabolomic strategies to explore the therapeutic effects of BHD on middle cerebral artery occlusion (MCAO) in rats. Our results showed that BHD could effectively improve neurological severity scores and alleviate neuronal damage in rats with MCAO. BHD could also reduce the level of peripheral proinflammatory cytokines and inhibit neuroinflammation. 16S rRNA sequencing showed that BHD could increase the relative abundances of the genera Lactobacillus, Faecalibacterium, Ruminococcaceae_UCG-002, etc., while decreasing the relative abundances of the genera Escherichia-Shigella, Klebsiella, Streptococcus, Coprococcus_2, Enterococcus, etc. Untargeted metabolomic analysis of hippocampal samples showed that 17 significantly differentially abundant metabolites and 9 enriched metabolic pathways were linked with BHD treatment. We also found that the regulatory effects of BHD on metabolites were correlated with the differentially abundant microbial taxa. The predicted function of the gut microbiota and the metabolic pathway enrichment results showed that purine metabolism, glutamatergic synapses, arginine and proline metabolism, and alanine, aspartic acid and glutamate metabolism were involved in the effects of BHD. These pathways may be related to pathological processes such as excitotoxicity, neuroinflammation, and energy metabolism disorder in CI. In summary, these findings suggest that regulation of hippocampal metabolism and of the composition and function of the gut microbiota may be important mechanisms underlying the effect of BHD in the treatment of CI.

Towards Bioprospection of Commercial Materials of Mentha spicata L. Using a Combined Strategy of Metabolomics and Biological Activity Analyses.

Spearmint (Mentha spicata L.) has been widely studied for its diversity of compounds for product generation. However, studies describing the chemical and biological characteristics of commercial spearmint materials from different origins are scarce. For this reason, this research aimed to bioprospecting spearmint from three origins: Colombia (Col), Mexico (Mex), and Egypt (Eg). We performed a biological activity analysis, such as FRAP, DPPH, and ABTS, inhibition potential of S. pyogenes, K. pneumoniae, E. coli, P. aeuroginosa, S. aureus, S aureus Methicillin-Resistant, and E. faecalis. Furthermore, we performed chemical assays, such as total polyphenol and rosmarinic acid, and untargeted metabolomics via HPLC-MS/MS. Finally, we developed a causality analysis to integrate biological activities with chemical analyses. We found significant differences between the samples for the total polyphenol and rosmarinic acid contents, FRAP, and inhibition analyses for Methicillin-Resistant S. aureus and E. faecalis. Also, clear metabolic differentiation was observed among the three commercial materials evaluated. These results allow us to propose data-driven uses for the three spearmint materials available in current markets.

Evaluation of Untargeted Metabolomic Strategy for the Discovery of Biomarker of Breast Cancer.

Discovery of disease biomarker based on untargeted metabolomics is informative for pathological mechanism studies and facilitates disease early diagnosis. Numerous of metabolomic strategies emerge due to different sample properties or experimental purposes, thus, methodological evaluation before sample analysis is essential and necessary. In this study, sample preparation, data processing procedure and metabolite identification strategy were assessed aiming at the discovery of biomarker of breast cancer. First, metabolite extraction by different solvents, as well as the necessity of vacuum-dried and re-dissolution, was investigated. The extraction efficiency was assessed based on the number of eligible components (components with MS/MS data acquired), which was more reasonable for metabolite identification. In addition, a simplified data processing procedure was proposed involving the OPLS-DA, primary screening for eligible components, and secondary screening with constraints including VIP, fold change and p value. Such procedure ensured that only differential candidates were subjected to data interpretation, which greatly reduced the data volume for database search and improved analysis efficiency. Furthermore, metabolite identification and annotation confidence were enhanced by comprehensive consideration of mass and MS/MS errors, isotope similarity, fragmentation match, and biological source confirmation. On this basis, the optimized strategy was applied for the analysis of serum samples of breast cancer, according to which the discovery of differential metabolites highly encouraged the independent biomarkers/indicators used for disease diagnosis and chemotherapy evaluation clinically. Therefore, the optimized strategy simplified the process of differential metabolite exploration, which laid a foundation for biomarker discovery and studies of disease mechanism.

Computational Metabolomics Tools Reveal Metabolic Reconfigurations Underlying the Effects of Biostimulant Seaweed Extracts on Maize Plants under Drought Stress Conditions.

Drought is one of the major abiotic stresses causing severe damage and losses in economically important crops worldwide. Drought decreases the plant water status, leading to a disruptive metabolic reprogramming that negatively affects plant growth and yield. Seaweed extract-based biostimulants show potential as a sustainable strategy for improved crop health and stress resilience. However, cellular, biochemical, and molecular mechanisms governing the agronomically observed benefits of the seaweed extracts on plants are still poorly understood. In this study, a liquid chromatography–mass spectrometry-based untargeted metabolomics approach combined with computational metabolomics strategies was applied to unravel the molecular ‘stamps’ that define the effects of seaweed extracts on greenhouse-grown maize (Zea mays) under drought conditions. We applied mass spectral networking, substructure discovery, chemometrics, and metabolic pathway analyses to mine and interpret the generated mass spectral data. The results showed that the application of seaweed extracts induced alterations in the different pathways of primary and secondary metabolism, such as phenylpropanoid, flavonoid biosynthesis, fatty acid metabolism, and amino acids pathways. These metabolic changes involved increasing levels of phenylalanine, tryptophan, coumaroylquinic acid, and linolenic acid metabolites. These metabolic alterations are known to define some of the various biochemical and physiological events that lead to enhanced drought resistance traits. The latter include root growth, alleviation of oxidative stress, improved water, and nutrient uptake. Moreover, this study demonstrates the use of molecular networking in annotating maize metabolome. Furthermore, the results reveal that seaweed extract-based biostimulants induced a remodeling of maize metabolism, subsequently readjusting the plant towards stress alleviation, for example, by increasing the plant height and diameter through foliar application. Such insights add to ongoing efforts in elucidating the modes of action of biostimulants, such as seaweed extracts. Altogether, our study contributes to the fundamental scientific knowledge that is necessary for the development of a biostimulants industry aiming for a sustainable food security.

UPLC-G2Si-HDMS Untargeted Metabolomics for Identification of Yunnan Baiyao's Metabolic Target in Promoting Blood Circulation and Removing Blood Stasis.

Yunnan Baiyao is a famous Chinese patent medicine in Yunnan Province. However, its mechanism for promoting blood circulation and removing blood stasis is not fully explained. Our study used metabonomics technology to reveal the regulatory effect of Yunnan Baiyao on small molecular metabolites in promoting blood circulation and removing blood stasis, and exploring the related urine biomarkers. The coagulation function, blood rheology, and pathological results demonstrated that after Yunnan Baiyao treatment, the pathological indexes in rats with epinephrine hydrochloride-induced blood stasis syndrome improved and returned to normal levels. This is the basis for the effectiveness of Yunnan Baiyao. UPLC-G2Si-HDMS was used in combination with multivariate statistical analysis to conduct metabonomic analysis of urine samples. Finally, using mass spectrometry technology, 28 urine biomarkers were identified, clarifying the relevant metabolic pathways that play a vital role in the Yunnan Baiyao treatment. These were used as the target for Yunnan Baiyao to promote blood circulation and remove blood stasis. This study showed that metabolomics strategies provide opportunities and conditions for a deep and systematic understanding of the mechanism of action of prescriptions.

Functional metabolomics revealed functional metabolic-characteristics of chronic hepatitis that is significantly differentiated from acute hepatitis in mice

Diagnosis and therapeutics of acute- and chronic- hepatitis (A-H and C-H) cannot be distinguished during clinical practice because functional molecular-characteristics of two conditions remains elusive. Here, we employed a functional metabolomics strategy to discover functional metabolites that can readily distinguish C-H from A-H in CCl4 treated mice. Metabolic-differentiation between A-H and C-H was identified as A-H was largely characterized by the dysregulated purine cycle and amino acid metabolism, while the disorders of hepatic taurine-conjugated bile acids and glycerolipid biosynthesis were observed with C-H. Excitingly, we found that the enhanced conversation of C18–22 PUFA-containing TAGs to MUFA-containing TAGs promoted the development of C-H, which was also closely associated with the changes of TCA intermediates regulated by gut microbiota (Muribaculaceae and Prevotellaceae). Such metabolic discovery on hepatitis was validated by the functional annotation of metabolic genes, as the decreased expressions of Slc27a2, Acaa1a and Acaa1b mostly account for the dysregulation of purine degradation with AH, then the lowered expressions of Cyp2e1, Cat, Slc27a5 and Klb are significantly related to the dysregulated bile acids with C-H. Collecting clinical samples from the patients with hepatitis to compare serum metabolomes with A-H and C-H mice, the determinant functional metabolites were identified to significantly distinguish C-H from A-H in both experimental and clinical settings, suggesting metabolic discovery with CCl4 treated mice could be further efficiently explored to guide clinical research of A-H and C-H. Collectively, our study is providing novel insight into distinctive metabolic-characteristics of A-H and C-H underlying the innovative diagnosis and therapeutics of hepatitis.

An integrated network pharmacology and cell metabolomics approach to reveal the role of rhein, a novel PPARα agonist, against renal fibrosis by activating the PPARα–CPT1A axis

BackgroundRhein, an anthraquinone compound, displays extensive antifibrotic effects; however, its potential mechanisms are not fully understood. In this study, we explored the underlying molecular mechanism of action of rhein. MethodAn integrated network pharmacology and cell metabolomics approach was developed based on network pharmacology and bioinformatics method, and then successfully applied to speculate the potential targets of rhein and construct a rhein–target–metabolic enzyme–metabolite network. Thereafter, the antifibrotic mechanism of rhein was validated in TGF-β- and oleic acid- induced HK-2 and NRK-52E cells in vitro as well as a unilateral ischemia–reperfusion injury Sprague-Dawley rat model. ResultsBased on the construction of the rhein–target–metabolic enzyme–metabolite network, we found that rhein played an antifibrotic role through the PPAR–α–CPT1A–l-palmitoyl–carnitine axis. In vitro experiments demonstrated that rhein effectively activated the expression of PPARα and its downstream proteins (CPT1A and ACOX1) to alleviate lipid accumulation and fibrosis development. In vivo experiments indicated that rhein attenuated renal fibrosis mainly by activating the fatty acid oxidation pathway and improving lipid metabolism. ConclusionTaken together, our findings reveal that rhein is a novel agonist of PPARα, which contributes to its renoprotection through the regulation of the PPARα–CPT1A axis. Moreover, our study provides a novel insight into an integrated network pharmacology–metabolomics strategy for uncovering the pharmacological mechanisms of drugs from the system perspective.

Discovery of processing-associated Q-marker of carbonized traditional Chinese medicine: An integrated strategy of metabolomics, systems pharmacology and in vivo high-throughput screening model

BackgroundCarbonized traditional Chinese medicine (TCM) is a kind of distinctive traditional medicine, which has been widely used to cure various bleeding syndromes in clinic for over 2000 years. However, there are no effective quality control methods developed on carbonized TCM so far. PurposeThis study aimed at developing a processing-associated quality marker (Q-marker) discovery strategy, which would enable to promote the quality control study of carbonized TCM. MethodsCarbonized Typhae Pollen (CTP), a typical carbonized TCM with fantastic efficacy of stanching bleeding and removing blood stasis, was used as an example. First, a ultraperformance liquid chromatography with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) method was established to characterize four types of CTP in different processing degrees. Second, chemometric method was applied to screen candidate Q-markers. Third, peak area changes and Aratio changes of each candidate markers in 57 batches samples were described (Traceability and Transitivity). Fourth, systems pharmacology and two high-throughput zebrafish models: cerebral hemorrhage model and thrombus model were used to furtherly screen Q-markers (Effectiveness). Finally, a ultraperformance liquid chromatographic coupled with triple quadrupole tandem mass spectrometry (UPLC-TQ-MS) method was established and applied to quantify Q-markers in additional 10 batches of CTP samples (Measurability). ResultsThe chemical profiles of Typhae Pollen during the carbonized process were investigated. Then, 12 candidate compounds were screened in chemometric part. Six Q-markers (isorhamnetin-3-O-neohesperidoside, isorhamnetin-3-O-rutinoside, kaempferol-3-O-neohesperidoside, naringenin, quercetin and isorhamnetin) were subsequently screened out using three principles of Q-markers combined with content changes and two in vivo zebrafish models. Their average contents in additional 10 batches of CTP were 316.8 μg/g, 13.7 μg/g, 6.1 μg/g, 197.8 μg/g, 12.9 μg/g and 199.3 μg/g, respectively. Their content proportion was about 25: 1: 0.5: 15: 1: 15. ConclusionA processing-associated Q-marker discovery strategy was developed for carbonized TCM. It might provide a novel insight to solve the problem of ‘Chao Tan Cun Xing’ in carbonized process.

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.

Research Progress and Trends in Metabolomics of Fruit Trees.

Metabolomics is an indispensable part of modern systems biotechnology, applied in the diseases’ diagnosis, pharmacological mechanism, and quality monitoring of crops, vegetables, fruits, etc. Metabolomics of fruit trees has developed rapidly in recent years, and many important research results have been achieved in combination with transcriptomics, genomics, proteomics, quantitative trait locus (QTL), and genome-wide association study (GWAS). These research results mainly focus on the mechanism of fruit quality formation, metabolite markers of special quality or physiological period, the mechanism of fruit tree’s response to biotic/abiotic stress and environment, and the genetics mechanism of fruit trait. According to different experimental purposes, different metabolomic strategies could be selected, such as targeted metabolomics, non-targeted metabolomics, pseudo-targeted metabolomics, and widely targeted metabolomics. This article presents metabolomics strategies, key techniques in metabolomics, main applications in fruit trees, and prospects for the future. With the improvement of instruments, analysis platforms, and metabolite databases and decrease in the cost of the experiment, metabolomics will prompt the fruit tree research to achieve more breakthrough results.

Application of metabolomics analysis to aid in understanding the pathogenicity of different lineages and different serotypes of Listeria monocytogenes

Listeria monocytogenes is a foodborne pathogen with high mortality in young children, elderly persons, pregnant women, and immune-compromised individuals. Most human listeriosis cases are associated with four serotypes (1/2a, 1/2b, 1/2c and 4b) within lineages I and II. The intracellular metabolic changes in L. monocytogenes from different lineages and serotypes remain unclear. Here, a non-targeted metabolomics strategy, based on ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) coupled with chemometrics was performed to analyze the metabolic fluctuations in the lineages and serotypes of L. monocytogenes. In the aggregate, 93 L. monocytogenes isolates (two lineages and four serotypes) were investigated, and a total of 48 differential biomarker metabolites were identified. Twenty differential metabolites were observed at the lineage level, while the others were found at the serotype level. At the lineage level, significantly lower contents (fold change [FC] = 3.60) of γ-aminobutyric acid (GABA) was found in lineage II strains, as compared to lineage I strains. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis showed that different substances between lineages I and II participated in multiple metabolic pathways, among which pyrimidine metabolism, purine metabolism, and aminoacyl-tRNA biosynthesis were significantly enriched. The major significantly upregulated (P < 0.05) metabolites, including uridine 5′-monophosphate, uridine, guanosine monophosphate, and guanosine, in lineage II strains affect the synthesis of DNA and RNA. At the serotype level, the upregulation of urea precursor substances produced by the purine metabolism pathway in serotype 4b strains may be one reason for the increased virulence of serotype 4b strains, compared to other serotype strains. In addition, the upregulation of pyridoxine in the vitamin B6 pathway in 4b strains was also observed. The differential metabolic pathway of 1/2a and 1/2c strains is nucleotide metabolism, which could lead to differences in the biosynthesis of DNA and RNA of the strain and further affect the growth and proliferation of strains.

GC–MS Based Metabolomics Strategy for Cost-Effective Valorization of Agricultural Waste: Groundnut Shell Extracts and Their Biological Inhibitory Potential

GC–MS Based Metabolomics Strategy for Cost-Effective Valorization of Agricultural Waste: Groundnut Shell Extracts and Their Biological Inhibitory Potential