Metabolomics Method Research Articles

Multi-omics reveal toxicity mechanisms underpinning nanoplastic in redclaw crayfish (Cherax quadricarinatus)

We investigated the effects of different nanoplastic (NP, size = 100 nm) concentrations on red crayfish (Cherax quadricarinatus) and examined toxicity mechanisms. We established four concentration groups (control (CK): 0 μg/L; Low: 100 μg/L; Medium: 500 μg/L; and High: 1000 μg/L) and analyzed toxicity effects in C. quadricarinatus hepatopancreas using histopathological, transcriptomic, metabolomic, and fluorescence methods. NP exposure caused histological lesions and oxidative stress in hepatopancreas, and also significantly decreased glutathione (GSH) (P < 0.05) but significantly increased malondialdehyde content (MDA) (P < 0.05) in NP-treated groups. By analyzing different metabolic indicators, total cholesterol (T-CHO) content significantly increased (P < 0.05) and triglyceride (TG) content significantly decreased in Medium and High (P < 0.05). Transcriptomic analyses revealed that NPs influenced apoptosis, drug metabolism-cytochrome P450, and P53 signaling pathways. Metabolomic analyses indicated some metabolic processes were affected by NPs, including bile secretion, primary bile acid biosynthesis, and cholesterol metabolism. Caspase 3, 8, and 9 distribution levels in hepatopancreatic tissues were also determined by immunofluorescence; positive caspase staining increased with increased NP concentrations. Additionally, by examining relative Bcl-2, Bax, Apaf-1, and p53 mRNA expression levels, Bcl-2 expression was significantly decreased with increasing NP concentrations; and the expression of Bcl-2 was increasing significantly with the NPs concentration increasing. Bax expression in Low, Medium, and High groups was also significantly higher when compared with the CK group (P < 0.05); with High group levels significantly higher than in Low and Medium groups (P < 0.05). P53 expression was significantly increased in Low, Medium, and High groups (P < 0.05). Thus, NPs induced apoptosis in C. quadricarinatus hepatopancreatic cells, concomitant with increasing NP concentrations. Therefore, we identified mechanisms underpinning NP toxicity in C. quadricarinatus and provide a theoretical basis for exploring NP toxicity in aquatic organisms.

Hollow-like three-dimensional structure of methyl orange-delaminated Ti3C2 MXene nanocomposite for high-performance electrochemical sensing of tryptophan.

Tryptophan(Trp) is being explored as a potential biomarker for various diseases associated with decreased tryptophan levels; however, metabolomic methods are expensive and time-consuming and require extensive sample analysis, making them urgently needed for trace detection. Toexploit the properties of Ti3C2 MXenes a rational porous methyl orange (MO)-delaminated Ti3C2 MXene was preparedvia a facile mixing process for the electrocatalytic oxidation of Trp. The hollow-like 3D structure with a more open structure and the synergistic effect of MO and conductive Ti3C2 MXene enhanced its electrochemical catalytic capability toward Trp biosensing. More importantly, MO can stabilize Ti3C2 MXene nanosheets through noncovalent π-π interactions and hydrogen bonding. Compared with covalent attachment, these non-covalent interactions preserve the electronic conductivity of the Ti3C2 MXene nanosheets. Finally, the addition of MO-derived nitrogen (N) and sulfur (S) atoms to Ti3C2 MXene enhanced the electronegativity and improved its affinity for specific molecules, resulting in high-performance electrocatalytic activity. The proposed biosensor exhibited a wide linear response in concentration ranges of 0.01-0.3 µM and 0.5-120 µM, with a low detection limit of 15 nM for tryptophan detection, and high anti-interference ability in complex media of human urine and egg white matrices. The exceptional abilities of the MO/Ti3C2 nanocatalyst make it a promising electrode material for the detection of important biomolecules.

Immunomodulatory effect of tibetan medicine compound extracts against ORFV in vitro by metabolomics

Ovine contagious pustular dermatitis (ORF) is one of the main diseases of sheep and is a zoonotic disease caused by Ovine contagious pustular dermatitis virus (ORFV) infection, posing a significant constraint on sheep breeding industry and human health. The Tibetan medical formulation composed of Polygonum leucoides, Polygonum xanthoxylum and Acanthophora rotunda significantly regulated lymphocyte immune function following ORFV stimulation, although the mechanism remains unclear. In order to study the immunomodulatory effects and mechanism of three Tibetan medicinal extracts (Polygonum leucoides, Polygonum xanthoxylum, and Acanthophora rotunda) against ORFV in vitro, sheep peripheral blood lymphocytes were isolated in vitro and treated with different concentrations of Tibetan medicine compound extract solution after ORFV infection. The cytokine expression levels in lymphocytes were measured at 4 h, 8 h and 12 h. Additionally endogenous metabolites in lymphocytes at 0 h, 4 h, 8 h and 12 h were quantified by untargeted metabolomics method. The results showed that, the extracts could regulate the lymphocyte immune factors altered by ORFV, and regulate the lymphocyte immune function through cysteine and methionine metabolic pathways as well as the pyrimidine metabolic pathways, potentially alleviating the immune evasion induced by ORFV.

Unlocking Biological Activity and Metabolomics Insights: Primary Screening of Cyanobacterial Biomass from a Tropical Reservoir.

Cyanobacterial harmful algal blooms can pose risks to ecosystems and human health worldwide due to their capacity to produce natural toxins. The potential dangers associated with numerous metabolites produced by cyanobacteria remain unknown. Only select classes of cyanopeptides have been extensively studied with the aim of yielding substantial evidence regarding their toxicity, resulting in their inclusion in risk management and water quality regulations. Information about exposure concentrations, co-occurrence, and toxic impacts of several cyanopeptides remains largely unexplored. We used liquid chromatography-mass spectrometry (LC-MS)-based metabolomic methods associated with chemometric tools (NP Analyst and Data Fusion-based Discovery), as well as an acute toxicity essay, in an innovative approach to evaluate the association of spectral signatures and biological activity from natural cyanobacterial biomass collected in a eutrophic reservoir in southeastern Brazil. Four classes of cyanopeptides were revealed through metabolomics: microcystins, microginins, aeruginosins, and cyanopeptolins. The bioinformatics tools showed high bioactivity correlation scores for compounds of the cyanopeptolin class (0.54), in addition to microcystins (0.54-0.58). These results emphasize the pressing need for a comprehensive evaluation of the (eco)toxicological risks associated with different cyanopeptides, considering their potential for exposure. Our study also demonstrated that the combined use of LC-MS/MS-based metabolomics and chemometric techniques for ecotoxicological research can offer a time-efficient strategy for mapping compounds with potential toxicological risk. Environ Toxicol Chem 2024;43:2222-2231. © 2024 SETAC.

Validation of two LC[sbnd]HRMS methods for large-scale untargeted metabolomics of serum samples: Strategy to establish method fitness-for-purpose

Untargeted metabolomics by LCHRMS is a powerful tool to enhance our knowledge of pathophysiological processes. Whereas validation of a bioanalytical method is customary in most analytical chemistry fields, it is rarely performed for untargeted metabolomics. This study aimed to establish and validate an analytical platform for a long-term, clinical metabolomics study. Sample preparation was performed with an automated liquid handler and four analytical methods were developed and evaluated. The validation study spanned three batches with twelve runs using individual serum samples and various quality control samples. Data was acquired with untargeted acquisition and only metabolites identified at level 1 were evaluated. Validation parameters were set to evaluate key performance metrics relevant for the intended application: reproducibility, repeatability, stability, and identification selectivity, emphasizing dataset intrinsic variance. Concordance of semi-quantitative results between methods was evaluated to identify potential bias. Spearman rank correlation coefficients (rs) were calculated from individual serum samples. Of the four methods tested, two were selected for validation. A total of 47 and 55 metabolites (RPLC-ESI+- and HILIC-ESI−-HRMS, respectively) met specified validation criteria. Quality assurance involved system suitability testing, sample release, run release, and batch release. The median repeatability and within-run reproducibility as coefficient of variation% for metabolites that passed validation on RPLC-ESI+- and HILIC-ESI−-HRMS were 4.5 and 4.6, and 1.5 and 3.8, respectively. Metabolites that passed validation on RPLC-ESI+-HRMS had a median D-ratio of 1.91, and 89 % showed good signal intensity after ten-fold dilution. The corresponding numbers for metabolites with the HILIC-ESI−-HRMS method was 1.45 and 45 %, respectively. The rs median ({range}) for metabolites that passed validation on RPLC-ESI+- was 0.93 (N = 9 {0.69–0.98}) and on HILIC-ESI−-HRMS was 0.93 (N = 22 {0.55–1.00}). The validated methods proved fit-for-purpose and the laboratory thus demonstrated its capability to produce reliable results for a large-scale, untargeted metabolomics study. This validation not only bolsters the reliability of the assays but also significantly enhances the impact and credibility of the hypotheses generated from the studies. Therefore, this validation study serves as a benchmark in the documentation of untargeted metabolomics, potentially guiding future endeavors in the field.

Enabling high-sensitivity live single-cell mass spectrometry using an integrated electrical lysis and nano electrospray ionization interface

BackgroundLive single-cell metabolomic studies encounter inherent difficulties attributed to the limited sample volume, minimal compound quantity, and insufficient sensitivity in the Mass Spectrometry (MS) method used to obtain single-cell data. However, understanding cellular heterogeneity, functional diversity, and metabolic processes within individual cells is essential. Exploring how individual cells respond to stimuli, including drugs, environmental changes, or signaling molecules, offers insights into biology, oncology, and drug discovery. Efficient release of cell contents (lysis) is vital for accurate metabolite detection at the single-cell level. Despite this, traditional approaches in live single cell metabolomics methods do not emphasize efficient lysis to prevent sample dilution. Instead, current live single cell metabolomics methods use direct infusion to introduce the cell into the mass spectrometry without prior chromatographic separation or a lysis step, which adversely affects sensitivity and metabolic coverage. ResultsTo address this, we developed an integrated single-cell electrical lysis and nano spray (SCEL-nS) platform coupled to an Orbitrap MS capable of efficiently lysing a single cell after being sampled with specially manufactured micropipettes. Lysis efficiency was validated by comparing live cell stain fluorescent intensities of intact and electrically lysed cells through microscopy imaging. The SCEL-nS platform successfully induced the breakdown of a single cell, significantly reducing the live cell stain's fluorescent intensity indicating cell membrane breakdown. Additionally, SCEL-nS was validated by measuring single cells spiked with the anti-cancer drug tamoxifen by MS. SCEL-nS use resulted in statistically significant increase in the peak measured by the method compared to the traditional non-lysis method. SignificanceOverall, our results demonstrate that the newly incorporated SCEL-nS platform achieved higher sensitivities compared to traditional live single cell analysis methods.

Rapid Analysis of Colonic Metabolomics in High-Fat Diet Mice by Extraction Electrospray Ionization Mass Spectrometry (EESI-MS).

Propolis exhibits significant anti-inflammatory, antidiabetic, and antiobesity properties in both mouse models and clinical applications. However, the underlying metabolic mechanisms remain poorly understood. Traditional metabolomic methods that rely on chromatographic separation require complex preprocessing steps and extended detection periods. In this study, we employed extraction electrospray ionization mass spectrometry combined with multivariate analysis to directly profile metabolites in the colon tissue of mice. Our findings demonstrate the efficacy of ethanol extract of propolis (EEP) in mitigating weight gain, reducing inflammatory cytokines, and improving insulin resistance induced by a high-fat diet. Additionally, EEP enhanced glucose tolerance. Through collision-induced dissociation experiments, we identified 26 metabolites, with 4-hydroxyphenylacetic acid, protocatechuic acid, caffeic acid, ferulic acid, hippuric acid, histidine, and tryptophan emerging as potential biomarkers. Notably, tryptophan exhibited the highest content at 8.25 mg/g. Our research facilitates rapid profiling of colon metabolites, underscoring its significant potential for broader applications in animal metabolomic studies.

Explore the mechanisms of triterpenoids from Ganoderma lucidum in the protection against Alzheimer's disease via microbiota-gut-brain axis with the aid of network pharmacology

Ganoderma lucidum (Curtis) P. Karst.(G. lucidum) is a kind of fungi, which also a traditional Chinese medicine used for “wisdom growth” in China. Triterpenoids from G. lucidum (GLTs) are one of the main active ingredients. Based on the strategy of early intervention on Alzheimer's disease (AD) and the inextricable association between disordered gut microbiota and metabolites with AD, this study aimed to explore the mechanisms of GLTs in the protection against AD via microbiota-gut-brain axis with the aid of network pharmacology. In this study, LC-MS/MS was used to identify the main active ingredients of GLTs. Network pharmacology was used to predict the potential target and validated with Caco-2 cell model. D-galactose was used to induce the slow-onset AD on rats. Metabolomics methods basing on GC-MS combined with 16S rRNA sequencing technology was used to carry out microbiota-gut-metabolomics analysis in order to reveal the potential mechanisms of GLTs in the protection of AD. As results, GLTs showed a protection against AD effect on rats by intervening administration. The mechanisms were inextricably linked to GLTs interference with the balance of gut microbiota and metabolites. The main fecal metabolites involved were short-chain fatty acids and aromatic amino acid metabolites.

Fast Targeted Metabolomics for Analyzing Metabolic Diversity of Bacterial Indole Derivatives in ME/CFS Gut Microbiome.

Disruptions in microbial metabolite interactions due to gut microbiome dysbiosis and metabolomic shifts may contribute to Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and other immune-related conditions. The aryl hydrocarbon receptor (AhR), activated upon binding various tryptophan metabolites, modulates host immune responses. This study investigates whether the metabolic diversity-the concentration distribution-of bacterial indole pathway metabolites can differentiate bacterial strains and classify ME/CFS samples. A fast targeted liquid chromatography-parallel reaction monitoring method at a rate of 4 minutes per sample was developed for large-scale analysis. This method revealed significant metabolic differences in indole derivatives among B. uniformis strains cultured from human isolates. Principal component analysis identified two major components (PC1, 68.9%; PC2, 18.7%), accounting for 87.6% of the variance and distinguishing two distinct B. uniformis clusters. The metabolic difference between clusters was particularly evident in the relative contributions of indole-3-acrylate and indole-3-aldehyde. We further measured concentration distributions of indole derivatives in ME/CFS by analyzing fecal samples from 10 patients and 10 healthy controls using the fast targeted metabolomics method. An AdaBoost-LOOCV model achieved moderate classification success with a mean LOOCV accuracy of 0.65 (Control: precision of 0.67, recall of 0.60, F1-score of 0.63; ME/CFS: precision of 0.64, recall of 0.7000, F1-score of 0.67). These results suggest that the metabolic diversity of indole derivatives from tryptophan degradation, facilitated by the fast targeted metabolomics and machine learning, is a potential biomarker for differentiating bacterial strains and classifying ME/CFS samples. Mass spectrometry datasets are accessible at the National Metabolomics Data Repository (ST002308, DOI: 10.21228/M8G13Q; ST003344, DOI: 10.21228/M8RJ9N; ST003346, DOI: 10.21228/M8RJ9N).

Spatial metabolomics method to reveal the differences in chemical composition of raw and honey-fried Stemona tuberosa Lour. by using UPLC-Orbitrap Fusion MS and desorption electrospray ionization mass spectrometry imaging.

Stemona tuberosa Lour. (ST) is a significant traditional Chinese medicine (TCM) renowned for its antitussive and insecticidal properties. ST is commonly subjected to processing in clinical practice before being utilized as a medicinal substance. Currently, the customary technique for processing ST is honey-fried. Nevertheless, the specific variations in chemical constituents of ST before and after honey-fried remain unclear. This work aimed to analyze the variations in chemical constituents of ST before and after honey-fried and to study the distribution of differential markers in the roots. UPLC-Orbitrap Fusion MS combined with molecular network analysis was used to analyze the metabolome of ST and honey-fried ST (HST) and to screen the differential metabolites by multivariate statistical analysis. Spatial metabolomics was applied to study the distribution of differential metabolites by desorption electrospray ionization mass spectrometry imaging (DESI-MSI). The ST and HST exhibited notable disparities, with 56 and 61 chemical constituents found from each, respectively. After processing, the types of alkaloids decreased, and 12 differential metabolites were screened from the common compounds. The notable component variations were epibisdehydro-tuberostemonine J, neostenine, tuberostemonine, croomine, neotuberostemonine, and so forth. MSI visualized the spatial distribution of differential metabolites. Our research provided a rapid and effective visualization method for the identification and spatial distribution of metabolites in ST. Compared with the traditional method, this method offered more convincing data supporting the processing mechanism investigations of Stemona tuberosa from a macroscopic perspective.

Integrated Proteomics and Metabolomics Reveal Altered Metabolic Regulation of Xanthobacter autotrophicus under Electrochemical Water-Splitting Conditions.

Biological-inorganic hybrid systems are a growing class of technologies that combine microorganisms with materials for a variety of purposes, including chemical synthesis, environmental remediation, and energy generation. These systems typically consider microorganisms as simple catalysts for the reaction of interest; however, other metabolic activity is likely to have a large influence on the system performance. The investigation of biological responses to the hybrid environment is thus critical to the future development and optimization. The present study investigates this phenomenon in a recently reported hybrid system that uses electrochemical water splitting to provide reducing equivalents to the nitrogen-fixing bacteria Xanthobacter autotrophicus for efficient reduction of N2 to biomass that may be used as fertilizer. Using integrated proteomic and metabolomic methods, we find a pattern of differentiated metabolic regulation under electrochemical water-splitting (hybrid) conditions with an increase in carbon fixation products glycerate-3-phosphate and acetyl-CoA that suggests a high energy availability. We further report an increased expression of proteins of interest, namely, those responsible for nitrogen fixation and assimilation, which indicate increased rates of nitrogen fixation and support previous observations of faster biomass accumulation in the hybrid system compared to typical planktonic growth conditions. This work complicates the inert catalyst view of biological-inorganic hybrids while demonstrating the power of multiomics analysis as a tool for deeper understanding of those systems.

Nano-Characterization, Composition Analysis, and Anti-Inflammatory Activity of American-Ginseng-Derived Vesicle-like Nanoparticles.

Medicinal plant-derived vesicle-like nanoparticles can carry chemical components and exert intercellular activity due to the encapsulation of nanostructures. American ginseng is well known as a traditional herb and is commonly used in clinical decoctions. However, the nano-characteristics and chemical composition of American-ginseng-derived vesicle-like nanoparticles (AGVNs) in decoctions are unclear. In this study, the gradient centrifugation method was used to extract and isolate AGVNs. A metabolomic method based on high-resolution mass spectrometry was established to analyze small molecules loaded in AGVNs. Zebrafish and RAW264.7 cells were employed to investigate the anti-inflammatory effects of AGVNs. The results showed that the particle size of AGVNs was generally 243.6 nm, and the zeta potential was -14.5 mV. AGVNs were found to contain 26 ginsenosides (14 protopanaxadiols, 11 protopanaxatriols, and 1 oleanolic acid). Ginsenoside Rb1 and malonyl-ginsenoside Rb1 tended to be enriched in AGVNs. Moreover, AGVNs were found to exert anti-inflammatory effects by reducing macrophage migration in zebrafish and regulating inflammatory factor (NO, TNF-α, IL-6, IL-10) secretion in RAW 264.7 cells. The characterization and analysis of AGVNs provide references and data that support the development of nanoscale anti-inflammatory substances from medicinal plants.

Revealing the key antioxidant compounds and potential action mechanisms of Chinese Cabernet Sauvignon red wines by integrating UHPLC-QTOF-MS-based untargeted metabolomics, network pharmacology and molecular docking approaches

In recent years, red wine drinking has become more popular in China owing to its antioxidant effects. However, the key antioxidant compounds and their action mechanisms of Chinese red wines are still unclear. Herein, the antioxidant activities and chemical compositions of 45 Chinese Cabernet Sauvignon red wine samples were determined using chemical antioxidant assays and an UHPLC-QTOF-MS-based untargeted metabolomics method. The key antioxidant compounds in red wines and potential action mechanisms were revealed by integrating network pharmacology and molecular docking approaches. Results showed that there are 8 key antioxidant compounds in the red wine samples. These compounds are involved in several metabolic pathways in the body, particularly PI3K/AKT. What's more, they bind to the core antioxidant targets through hydrogen bonding and hydrophobic interaction. Among them, myricetin, laricitrin, 2,3,8-tri-O-methylellagic acid and AKT1 have the highest binding energies. This study could provide the theoretical basis for further investigation of physiological activities and functions of Chinese red wines.

Nitrogen-fixing bacteria promote growth and bioactive components accumulation of Astragalus mongholicus by regulating plant metabolism and rhizosphere microbiota

BackgroundThe excessive application of chemical fertilizers in the cultivation of Astragalus mongholicus Bunge results in a reduction in the quality of the medicinal plant and compromises the sustainable productivity of the soil. PGPB inoculant is a hot topic in ecological agriculture research. In the cultivation of Astragalus mongholicus, the screened nitrogen-fixing bacteria can promote plant growth, however, whether it can promote the accumulation of main bioactive components remains unknown. In this study, mixed inoculants containing 5 strains of growth promoting bacteria (Rhizobium T16, Sinorhizobium T21, Bacillus J1, Bacillus G4 and Arthrobacter J2) were used in the field experiment. The metabolic substances in the root tissues of Astragalus mongholicus were identified during the harvest period by non-targeted metabolomics method, and the differential metabolites between groups were identified by statistical analysis. Meanwhile, high-throughput sequencing was performed to analyze the changes of rhizosphere soil and endophytic microbial community structure after mixed microbial treatment.ResultsThe results of non-targeted metabolism indicated a significant increase in the levels of 26 metabolites after treatment including 13 flavonoids, 3 saponins and 10 other components. The contents of three plant hormones (abscisic acid, salicylic acid and spermidine) also increased after treatment, which presumed to play an important role in regulating plant growth and metabolism. Studies on endosphere and rhizosphere bacterial communities showed that Rhzobiaceae, Micromonosporaceae, and Hypomicrobiaceae in endophytic, and Oxalobactereae in rhizosphere were significantly increased after treatment. These findings suggest their potential importance in plant growth promotion and secondary metabolism regulation.ConclusionsThis finding provides a basis for developing nitrogen-fixing bacteria fertilizer and improving the ecological planting efficiency of Astragalus mongholicus.

A diverse proteome is present and enzymatically active in metabolite extracts

Metabolite extraction is the critical first-step in metabolomics experiments, where it is generally regarded to inactivate and remove proteins. Here, arising from efforts to improve extraction conditions for polar metabolomics, we discover a proteomic landscape of over 1000 proteins within metabolite extracts. This is a ubiquitous feature across several common extraction and sample types. By combining post-resuspension stable isotope addition and enzyme inhibitors, we demonstrate in-extract metabolite interconversions due to residual transaminase activity. We extend these findings with untargeted metabolomics where we observe extensive protein-mediated metabolite changes, including in-extract formation of glutamate dipeptide and depletion of total glutathione. Finally, we present a simple extraction workflow that integrates 3 kDa filtration for protein removal as a superior method for polar metabolomics. In this work, we uncover a previously unrecognized, protein-mediated source of observer effects in metabolomics experiments with broad-reaching implications across all research fields using metabolomics and molecular metabolism.

Internal Standard Addition System for Online Breath Analysis.

Breath analysis with secondary electrospray ionization (SESI) coupled to mass spectrometry (MS) is a sensitive method for breath metabolomics. To enable quantitative assessments using SESI-MS, a system was developed to introduce controlled amounts of gases into breath samples and carry out standard addition experiments. The system combines gas standard generation through controlled evaporation, humidification, breath dilution, and standard injection with the help of mass-flow controllers. The system can also dilute breath, which affects the signal of the detected components. This response can be used to filter out contaminating compounds in an untargeted metabolomics workflow. The system's quantitative capabilities have been shown through standard addition of pyridine and butyric acid into breath in real time. This system can improve the quality and robustness of breath data.

Integrating metabolomics and bioinformatics to reveal the mechanism of Epimedium-induced liver injury.

Epimedium is a traditional Chinese medicine with a wide range of clinical applications; however, there have been numerous reports of adverse reactions in recent years. The most common side effect of Epimedium is liver injury. In this study, the liquid chromatography-mass spectrometry (LC-MS) method has been established to study the components of Epimedium and to identify the components absorbed into the blood of rats. Bioinformatics was used to screen out potential toxic components, and the integrating metabolomics method was used to explore the molecular mechanism of Epimedium-induced liver injury. The chemical constituents of Epimedium were identified by LC-MS, and 62 compounds were obtained, including 57 flavonoids, four organic acids and one alkaloid. The toxicity network of "Epimedium-component-target-liver injury" was constructed using bioinformatics research methods, and then the key hepatotoxic component icaritin was identified. Integrating metabolomics was used to investigate the changes in the metabolic profile of L-02 cells with different durations of icaritin administration compared with the control group, and 106 different metabolites were obtained. A total of 14 potential biomarkers significantly associated with cell survival were screened by Pearson correlation analysis combined with the L-02 cell survival rate. Our study preliminarily revealed the mechanism of hepatotoxicity induced by Epimedium.

A Combined Metabolome and Transcriptome Reveals the Lignin Metabolic Pathway during the Developmental Stages of Peel Coloration in the 'Xinyu' Pear.

Sand pear is the main cultivated pear species in China, and brown peel is a unique feature of sand pear. The formation of brown peel is related to the activity of the cork layer, of which lignin is an important component. The formation of brown peel is intimately associated with the biosynthesis and accumulation of lignin; however, the regulatory mechanism of lignin biosynthesis in pear peel remains unclear. In this study, we used a newly bred sand pear cultivar 'Xinyu' as the material to investigate the biosynthesis and accumulation of lignin at nine developmental stages using metabolomic and transcriptomic methods. Our results showed that the 30 days after flowering (DAF) to 50DAF were the key periods of lignin accumulation according to data analysis from the assays of lignin measurement, scanning electron microscope (SEM) observation, metabolomics, and transcriptomics. Through weighted gene co-expression network analysis (WGCNA), positively correlated modules with lignin were identified. A total of nine difference lignin components were identified and 148 differentially expressed genes (DEGs), including 10 structural genes (PAL1, C4H, two 4CL genes, HCT, CSE, two COMT genes, and two CCR genes) and MYB, NAC, ERF, and TCP transcription factor genes were involved in lignin metabolism. An analysis of RT-qPCR confirmed that these DEGs were involved in the biosynthesis and regulation of lignin. These findings further help us understand the mechanisms of lignin biosynthesis and provide a theoretical basis for peel color control and quality improvement in pear breeding and cultivation.

Metabolomics-based search for lung cancer markers among patients with different smoking status

Tobacco smoking is the main etiological factor of lung cancer (LC), which can also cause metabolome disruption. This study aimed to investigate whether the observed metabolic shift in LC patients was also associated with their smoking status. Untargeted metabolomics profiling was applied for the initial screening of changes in serum metabolic profile between LC and chronic obstructive pulmonary disease (COPD) patients, selected as a non-cancer group. Differences in metabolite profiles between current and former smokers were also tested. Then, targeted metabolomics methods were applied to verify and validate the proposed LC biomarkers. For untargeted metabolomics, a single extraction-dual separation workflow was applied. The samples were analyzed using a liquid chromatograph-high resolution quadrupole time-of-flight mass spectrometer. Next, the selected metabolites were quantified using liquid chromatography-triple-quadrupole mass spectrometry. The acquired data confirmed that patients’ stratification based on smoking status impacted the discriminating ability of the identified LC marker candidates. Analyzing a validation set of samples enabled us to determine if the putative LC markers were truly robust. It demonstrated significant differences in the case of four metabolites: allantoin, glutamic acid, succinic acid, and sphingosine-1-phosphate. Our research showed that studying the influence of strong environmental factors, such as tobacco smoking, should be considered in cancer marker research since it reduces the risk of false positives and improves understanding of the metabolite shifts in cancer patients.

Study on Oleum cinnamomi Inhibiting Cutibacterium acnes and Its Covalent Inhibition Mechanism.

Oleum cinnamomi (OCM) is a volatile component of the Cinnamomum cassia Presl in the Lauraceae family, which displays broad-spectrum antibacterial properties. It has been found that OCM has a significant inhibitory effect against Cutibacterium acnes (C. acnes), but the precise target and molecular mechanism are still not fully understood. In this study, the antibacterial activity of OCM against C. acnes and its potential effect on cell membranes were elucidated. Metabolomics methods were used to reveal metabolic pathways, and proteomics was used to explore the targets of OCM inhibiting C. acnes. The yield of the OCM was 3.3% (w/w). A total of 19 compounds were identified, representing 96.213% of the total OCM composition, with the major constituents being phenylpropanoids (36.84%), sesquiterpenoids (26.32%), and monoterpenoids (15.79%). The main component identified was trans-cinnamaldehyde (85.308%). The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of OCM on C. acnes were 60 µg/mL and 180 µg/mL, respectively. The modified proteomics results indicate that cinnamaldehyde was the main bioactive ingredient within OCM, which covalently modifies the ABC transporter adenosine triphosphate (ATP)-binding protein and nicotinamide adenine dinucleotide (NADH)-quinone oxidoreductase, hindering the amino acid transport process, and disrupting the balance between NADH and nicotinamide adenine dinucleoside phosphorus (NAD+), thereby hindering energy metabolism. We have reported for the first time that OCM exerts an antibacterial effect by covalent binding of cinnamaldehyde to target proteins, providing potential and interesting targets to explore new control strategies for gram-positive anaerobic bacteria.