A high throughput metabolomics method and its application in female serum samples in a normal menstrual cycle based on liquid chromatography-mass spectrometry

Evaluating the Effect of Gestational Exposure to Perfluorohexane Sulfonate on Placental Development in Mice Combining Alternative Splicing and Gene Expression Analyses

BACKGROUND

Perfluorohexane sulfonate (PFHxS) is a frequently detected per- and polyfluoroalkyl substance in most populations, including in individuals who are pregnant, a period critical for early life development. Despite epidemiological evidence of exposure, developmental toxicity, particularly at realistic human exposures, remains understudied.

OBJECTIVES

We evaluated the effect of gestational exposure to human-relevant body burden of PFHxS on fetal and placental development and explored mechanisms of action combining alternative splicing (AS) and gene expression (GE) analyses.

METHODS

Pregnant ICR mice were exposed to 0, 0.03, and 0.3 μ g / kg / day  from gestational day 7 to day 17 via oral gavage. Upon euthanasia, PFHxS distribution was measured using liquid chromatography-tandem mass spectrometry. Maternal and fetal phenotypes were recorded, and histopathology was examined for placenta impairment. Multiomics was adopted by combining AS and GE analyses to unveil disruptions in mRNA quality and quantity. The key metabolite transporters were validated by quantitative real-time PCR (qRT-PCR) for quantification and three-dimensional (3D) structural simulation by AlphaFold2. Targeted metabolomics based on liquid chromatography-tandem mass spectrometry was used to detect amino acid and amides levels in the placenta.

RESULTS

Pups developmentally exposed to PFHxS exhibited signs of intrauterine growth restriction (IUGR), characterized by smaller fetal weight and body length (p < 0.01 ) compared to control mice. PFHxS concentration in maternal plasma was 5.01 ± 0.54  ng / mL . PFHxS trans-placenta distribution suggested dose-dependent transfer through placental barrier. Histopathology of placenta of exposed dams showed placental dysplasia, manifested with an attenuated labyrinthine layer area and deescalated blood sinus counts and placental vascular development index marker CD34. Combined GE and AS analyses pinpointed differences in genes associated with key biological processes of placental development, proliferation, metabolism, and transport in placenta of exposed dams compared to that of control dams. Further detection of placental key transporter gene expression, protein structure simulation, and amino acid and amide metabolites levels suggested that PFHxS exposure during pregnancy led to impairment of placental amino acid transportation.

DISCUSSION

The findings from this study suggest that exposure to human-relevant very-low-dose PFHxS during pregnancy in mice caused IUGR, likely via downregulating of placental amino acid transporters, thereby impairing placental amino acid transportation, resulting in impairment of placental development. Our findings confirm epidemiological findings and call for future attention on the health risk of this persistent yet ubiquitous chemical in the early developmental stage and provide a new approach for understanding gene expression from both quantitative and qualitative omics approaches in toxicological studies. https://doi.org/10.1289/EHP13217.

Metabolomics acts as a powerful tool for comprehensively evaluating vaccines approved under emergency: a CoronaVac retrospective study

Introduction

To control the COVID-19 pandemic, great efforts have been made to realize herd immunity by vaccination since 2020. Unfortunately, most of the vaccines against COVID-19 were approved in emergency without a full-cycle and comprehensive evaluation process as recommended to the previous vaccines. Metabolome has a close tie with the phenotype and can sensitively reflect the responses to stimuli, rendering metabolomic analysis have the potential to appraise and monitor vaccine effects authentically.

Methods

In this study, a retrospective study was carried out for 330 Chinese volunteers receiving recommended two-dose CoronaVac, a vaccine approved in emergency in 2020. Venous blood was sampled before and after vaccination at 5 separate time points for all the recipients. Routine clinical laboratory analysis, metabolomic and lipidomic analysis data were collected.

Results and discussion

It was found that the serum antibody-positive rate of this population was around 81.82%. Most of the laboratory parameters were slightly perturbated within the relevant reference intervals after vaccination. The metabolomic and lipidomic analyses showed that the metabolic shift after inoculation was mainly in the glycolysis, tricarboxylic acid cycle, amino acid metabolism, urea cycle, as well as microbe-related metabolism (bile acid metabolism, tryptophan metabolism and phenylalanine metabolism). Time-course metabolome changes were found in parallel with the progress of immunity establishment and peripheral immune cell counting fluctuation, proving metabolomics analysis was an applicable solution to evaluate immune effects complementary to traditional antibody detection. Taurocholic acid, lysophosphatidylcholine 16:0 sn-1, glutamic acid, and phenylalanine were defined as valuable metabolite markers to indicate the establishment of immunity after vaccination. Integrated with the traditional laboratory analysis, this study provided a feasible metabolomics-based solution to relatively comprehensively evaluate vaccines approved under emergency.

Study on mechanism of hepatoprotective effect of Chrysanthemum morifolium Ramat. based on metabolomics with network analysis and network pharmacology

Hangju (HJ), the dried flower heads of Chrysanthemum morifolium Ramat., has a significant hepatoprotective effect. However, its underlying protection mechanism against acute liver injury (ALI) has been unclear. An integrated strategy based on metabolomics with network analysis and network pharmacology was developed to explore the potential molecular mechanism of HJ on ALI protection. Firstly, differential endogenous metabolites were screened and identified by metabolomics approach and metabolic pathway analysis was performed by MetaboAnalyst. Secondly, marker metabolites were used to construct metabolite-response-enzyme-gene networks and discover hub metabolites and potential gene targets in network analysis. Thirdly, hub genes through the protein-protein interaction (PPI) network were acquired by the aid of network pharmacology. Finally, the gene targets were taken to intersect with the relevant active ingredients for validation by molecular docking. In total, 48 flavonoids were identified in HJ, which were associated with 8 potential therapeutic targets in network pharmacological analysis. Biochemistry and histopathology analysis demonstrated that HJ exerted hepatoprotective effects. 28 biomarkers were successfully identified as possible biomarkers for the prevention of ALI. The sphingolipid metabolic pathway and the glycerophospholipid metabolic pathway was considered a crucial signaling pathway by Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. In addition, phosphatidylcholine and sphingomyelin were considered as hub metabolites. Twelve enzymes and 38 genes were considered as potential targets in the network analysis. Based on the combined analysis above, HJ was shown to modulate 2 key upstream targets, including PLA2G2A and PLA2G4A. Molecular docking showed that active compounds of HJ had high binding affinity with these key targets. In conclusion, the flavonoid components of HJ can inhibit PLA2 and regulate glycerophospholipid and sphingolipid metabolism pathway to delay the pathological process of ALI, which may be a potential mechanism of HJ against ALI.

MetEx: A Targeted Extraction Strategy for Improving the Coverage and Accuracy of Metabolite Annotation in Liquid Chromatography-High-Resolution Mass Spectrometry Data

Liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is the most popular platform for untargeted metabolomics studies, but compound annotation is a challenge. In this work, we developed a new LC-HRMS data-targeted extraction method called MetEx for metabolite annotation. MetEx contains the retention time (t_R), MS1, and MS2 information of 30 620 metabolites from freely available spectral databases, including MoNA and KEGG. The t_R values of 95.4% of the compounds in our database were calculated by the GNN-RT model. The MS2 spectra of 39.4% compounds were also predicted using CFM-ID. MetEx was initially examined on a mixture of 634 standards, considering chemical coverage and accurate metabolite assignment, and later applied to human plasma (NIST SRM 1950), human urine, HepG2 cells, mouse liver tissue, and mouse feces. MetEx correctly assigned 252 out of 253 standards detected in our instruments. The platform also provided 8.0-44.2% more compounds in the biological samples compared to XCMS, MS-DIAL, and MZmine 2. MetEx is implemented and visualized in R and freely available at http://www.metaboex.cn/MetEx.

Quantitative structure-retention relationship for reliable metabolite identification and quantification in metabolomics using ion-pair reversed-phase chromatography coupled with tandem mass spectrometry

Hydrophilic metabolites are essential for all biological systems with multiple functions and their quantitative analysis forms an important part of metabolomics. However, poor retention of these metabolites on reversed-phase (RP) chromatographic column hinders their effective analysis with RPLC-MS methods. Herein, we developed a method for detecting hydrophilic metabolites using the ion-pair reversed-phase liquid-chromatography coupled with mass spectrometry (IPRP-LC-MS/MS) in scheduled multiple-reaction-monitoring (sMRM) mode. We first developed a hexylamine-based IPRP-UHPLC-QTOFMS method and experimentally measured retention time (t_R) for 183 hydrophilic metabolites. We found that t_Rs of these metabolites were dominated by their electrostatic potential depending upon the numbers and types of their ionizable groups. We then systematically investigated the quantitative structure-retention relationship (QSRR) and constructed QSRR models using the measured t_R. Subsequently, we developed a retention time predictive model using the random-forest regression algorithm (r² = 0.93, q² = 0.70, MAE = 1.28 min) for predicting metabolite retention time, which was applied in IPRP-UHPLC-MS/MS method in sMRM mode for quantitative metabolomic analysis. Our method can simultaneously quantify more than 260 metabolites. Moreover, we found that this method was applicable for multiple major biological matrices including biofluids and tissues. This approach offers an efficient method for large-scale quantitative hydrophilic metabolomic profiling even when metabolite standards are unavailable.

Diagnostic Performance of Sex-Specific Modified Metabolite Patterns in Urine for Screening of Prediabetes

AIMS/HYPOTHESIS

Large-scale prediabetes screening is still a challenge since fasting blood glucose and HbA_1c as the long-standing, recommended analytes have only moderate diagnostic sensitivity, and the practicability of the oral glucose tolerance test for population-based strategies is limited. To tackle this issue and to identify reliable diagnostic patterns, we developed an innovative metabolomics-based strategy deviating from common concepts by employing urine instead of blood samples, searching for sex-specific biomarkers, and focusing on modified metabolites.

METHODS

Non-targeted, modification group-assisted metabolomics by liquid chromatography-mass spectrometry (LC-MS) was applied to second morning urine samples of 340 individuals from a prediabetes cohort. Normal (n = 208) and impaired glucose-tolerant (IGT; n = 132) individuals, matched for age and BMI, were randomly divided in discovery and validation cohorts. ReliefF, a feature selection algorithm, was used to extract sex-specific diagnostic patterns of modified metabolites for the detection of IGT. The diagnostic performance was compared with conventional screening parameters fasting plasma glucose (FPG), HbA_1c, and fasting insulin.

RESULTS

Female- and male-specific diagnostic patterns were identified in urine. Only three biomarkers were identical in both. The patterns showed better AUC and diagnostic sensitivity for prediabetes screening of IGT than FPG, HbA_1c, insulin, or a combination of FPG and HbA_1c. The AUC of the male-specific pattern in the validation cohort was 0.889 with a diagnostic sensitivity of 92.6% and increased to an AUC of 0.977 in combination with HbA_1c. In comparison, the AUCs of FPG, HbA_1c, and insulin alone reached 0.573, 0.668, and 0.571, respectively. Validation of the diagnostic pattern of female subjects showed an AUC of 0.722, which still exceeded the AUCs of FPG, HbA_1c, and insulin (0.595, 0.604, and 0.634, respectively). Modified metabolites in the urinary patterns include advanced glycation end products (pentosidine-glucuronide and glutamyl-lysine-sulfate) and microbiota-associated compounds (indoxyl sulfate and dihydroxyphenyl-gamma-valerolactone-glucuronide).

CONCLUSIONS/INTERPRETATION

Our results demonstrate that the sex-specific search for diagnostic metabolite biomarkers can be superior to common metabolomics strategies. The diagnostic performance for IGT detection was significantly better than routinely applied blood parameters. Together with recently developed fully automatic LC-MS systems, this opens up future perspectives for the application of sex-specific diagnostic patterns for prediabetes screening in urine.

Metabolome-wide association study of serum exogenous chemical residues in a cohort with 5 major chronic diseases

BACKGROUND

Chronic diseases have become main killers affecting the health of human, and environmental pollution is a major health risk factor that cannot be ignored. It has been reported that exogenous chemical residues including pesticides, herbicides, fungicides, veterinary drugs and persistent organic pollutants are associated with chronic diseases. However, the evidence for their relationship is equivocal and the underlying mechanisms are unclear.

OBJECTIVES

We aim to investigate the linkages between serum exogenous chemical residues and 5 main chronic diseases including obesity, hyperuricemia, hypertension, diabetes and dyslipidemia, and further reveal the metabolic perturbations of chronic diseases related to exogenous chemical residue exposure, then gain potential mechanism insight at the metabolic level.

METHODS

LC-MS-based targeted and nontargeted methods were respectively performed to quantify exogenous chemical residues and acquire metabolic profiling of 496 serum samples from chronic disease patients. Non-parametric test, correlation and regression analyses were carried out to investigate the association between exogenous chemical residues and chronic diseases. Metabolome-wide association study combined with the meeting-in-the-middle strategy and mediation analysis was performed to reveal and explain exposure-related metabolic disturbances and their risk to chronic diseases.

RESULTS

In the association analysis of 106 serum exogenous chemical residues and 5 chronic diseases, positive associations of serum perfluoroalkyl substances (PFASs) with hyperuricemia were discovered while other associations were not significant. 240 exposure markers of PFASs and 84 disease markers of hyperuricemia were found, and 47 of them were overlapped and considered as putative effective markers. Serum uric acid, amino acids, cholesterol, carnitines, fatty acids, glycerides, glycerophospholipids, ceramides, and a part of sphingolipids were positively correlated with PFASs and associated with increased risk for hyperuricemia. Creatine, creatinine, glyceryl monooleate, phosphatidylcholine 36:6, phosphatidylethanolamine 40:6, cholesterol and sphingolipid 36:1;2O were significant markers which mediated the associations of the residues with hyperuricemia.

CONCLUSIONS

Our study demonstrated a significantly positive association between PFASs exposure and hyperuricemia. The most significant metabolic abnormality was lipid metabolism which not only was positively associated with PFASs, but also increased the risk of hyperuricemia.

Advantages of omics technology for evaluating cadmium toxicity in zebrafish

In the last decade, several advancements have been made in omics technologies and they have been applied extensively in diverse research areas. Especially in toxicological research, omics technology can efficiently and accurately generate relevant data on the molecular dynamics associated with adverse outcomes. Toxicomics is defined as the combination of toxicology and omics technologies and encompasses toxicogenomics, toxicoproteomics, and toxicometabolomics. This paper reviews the trend of applying omics technologies to evaluate cadmium (Cd) toxicity in zebrafish (D. rerio). Cd is a toxic heavy metal posing several environmental concerns; however, it is being used widely in everyday life. Zebrafish embryos and larvae are employed as standard models for many toxicity tests because they share 71.4% genetic homology with humans. This study summarizes the toxicity of Cd on the nerves, liver, heart, skeleton, etc. of zebrafish and introduces detailed omics techniques to understand the results of the toxicomic studies. Finally, the trend of toxicity evaluation in the zebrafish model of Cd based on omics technology is presented.

Metabolomic Characterization Reveals ILF2 and ILF3 Affected Metabolic Adaptions in Esophageal Squamous Cell Carcinoma

Esophageal cancer (EC) is a common malignant disease in eastern countries. However, a study of the metabolomic characteristics associated with other biological factors in esophageal squamous cell carcinoma (ESCC) is limited. Interleukin enhancer binding factor 2 (ILF2) and ILF3, double-stranded RNA-binding proteins, have been reported to contribute to the occurrence and development of various types of malignancy. Nevertheless, the underlying functions of ILF2 and ILF3 in ESCC metabolic reprogramming have never been reported. This study aimed to contribute to the metabolic characterization of ESCC and to investigate the metabolomic alterations associated with ILF2 and ILF3 in ESCC tissues. Here, we identified 112 differential metabolites, which were mainly enriched in phosphatidylcholine biosynthesis, fatty acid metabolism, and amino acid metabolism pathways, based on liquid chromatography–mass spectrometry and capillary electrophoresis–mass spectrometry approaches using ESCC tissues and paired para-cancer tissues from twenty-eight ESCC patients. In addition, ILF2 and ILF3 expression were significantly elevated in EC tissues compared to the histologically normal samples, and closely associated with PI3K/AKT and MAPK signaling pathways in ESCC. Moreover, in ESCC tissues with a high ILF2 expression, several short-chain acyl-carnitines (C3:0, C4:0, and C5:0) related to the BCAA metabolic pathway and long-chain acyl-carnitines (C14:0, C16:0, C16:0-OH, and C18:0) involved in the oxidation of fatty acids were obviously upregulated. Additionally, a series of intermediate metabolites involved in the glycolysis pathway, including G6P/F6P, F1,6BP, DHAP, G3P, and 2,3BPG, were remarkably downregulated in highly ILF3-expressed ESCC tissues compared with the corresponding para-cancer tissues. Overall, these findings may provide evidence for the roles of ILF2 and ILF3 during the process of ESCC metabolic alterations, and new insights into the development of early diagnosis and treatment for ESCC. Further investigation is needed to clarify the underlying mechanism of ILF2 and ILF3 on acyl-carnitines and the glycolysis pathway, respectively.

Plasma Metabolomics for Discovery of Early Metabolic Markers of Prostate Cancer Based on Ultra-High-Performance Liquid Chromatography-High Resolution Mass Spectrometry

BACKGROUND

The prevention and early screening of PCa is highly dependent on the identification of new biomarkers. In this study, we investigated whether plasma metabolic profiles from healthy males provide novel early biomarkers associated with future risk of PCa.

METHODS

Using the Supplémentation en Vitamines et Minéraux Antioxydants (SU.VI.MAX) cohort, we identified plasma samples collected from 146 PCa cases up to 13 years prior to diagnosis and 272 matched controls. Plasma metabolic profiles were characterized using ultra-high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS).

RESULTS

Orthogonal partial least squares discriminant analysis (OPLS-DA) discriminated PCa cases from controls, with a median area under the receiver operating characteristic curve (AU-ROC) of 0.92 using a 1000-time repeated random sub-sampling validation. Sparse Partial Least Squares Discriminant Analysis (sPLS-DA) identified the top 10 most important metabolites (p < 0.001) discriminating PCa cases from controls. Among them, phosphate, ethyl oleate, eicosadienoic acid were higher in individuals that developed PCa than in the controls during the follow-up. In contrast, 2-hydroxyadenine, sphinganine, L-glutamic acid, serotonin, 7-keto cholesterol, tiglyl carnitine, and sphingosine were lower.

CONCLUSION

Our results support the dysregulation of amino acids and sphingolipid metabolism during the development of PCa. After validation in an independent cohort, these signatures may promote the development of new prevention and screening strategies to identify males at future risk of PCa.

Metabolome-Genome-Wide Association Study (mGWAS) Reveals Novel Metabolites Associated with Future Type 2 Diabetes Risk and Susceptibility Loci in a Case-Control Study in a Chinese Prospective Cohort

In a Chinese prospective cohort, 500 patients with new-onset type 2 diabetes (T2D) within 4.61 years and 500 matched healthy participants are selected as case and control groups, and randomized into discovery and validation sets to discover the metabolite changes before T2D onset and the related diabetogenic loci. A serum metabolomics analysis reveals that 81 metabolites changed significantly before T2D onset. Based on binary logistic regression, eight metabolites are defined as a biomarker panel for T2D prediction. Pipecolinic acid, carnitine C14:0, epinephrine and phosphatidylethanolamine 34:2 are first found associated with future T2D. The addition of the biomarker panel to the clinical markers (BMI, triglycerides, and fasting glucose) significantly improves the predictive ability in the discovery and validation sets, respectively. By associating metabolomics with genomics, a significant correlation (p < 5.0 × 10-8) between eicosatetraenoic acid and the FADS1 (rs174559) gene is observed, and suggestive correlations (p < 5.0 × 10-6) between pipecolinic acid and CHRM3 (rs535514), and leucine/isoleucine and WWOX (rs72487966) are discovered. Elevated leucine/isoleucine levels increased the risk of T2D. In conclusion, multiple metabolic dysregulations are observed to occur before T2D onset, and the new biomarker panel can help to predict T2D risk.

In situ detection and imaging of lysophospholipids in zebrafish using matrix-assisted laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry

In this paper, a matrix-assisted laser desorption/ionization (MALDI) Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) (MALDI-FTICR-MS) imaging method was developed to rapid and in situ detect the spatial distribution of lysophospholipids (LPLs) in zebrafish. The combination of MALDI with ultrahigh-resolution FTICR-MS achieves the MS imaging of LPLs with a mass resolution up to 50 000, which allows accurate identification and clear spatial visualization of LPLs in complex biological tissues. A series of lysophosphatidylcholines (LPCs) was detected using positive ion detection mode, and their concentration differences and spatial distributions were clearly visualized in different parts of zebrafish tissue. The method is rapid, simple, and efficient, being a desirable way to understand the spatial distribution of LPLs in biosome.

Broad Metabolome Alterations Associated with the Intake of Oral Contraceptives Are Mediated by Cortisol in Premenopausal Women

The use of oral contraceptives (OCs) has been associated with elevated blood cortisol concentrations. However, metabolic downstream effects of OC intake are not well described. Here, we aimed to determine if the blood metabolome is associated with the use of OCs and to estimate if these associations might be statistically mediated by serum cortisol concentrations. Plasma metabolites measured with the Biocrates AbsoluteIDQ p180 Kit and serum cortisol concentrations measured by an immunoassay were determined in 391 premenopausal women (116 OC users) participating in two independent cohorts of the Study of Health in Pomerania (SHIP). After correction for multiple testing, 27 metabolites were significantly associated with OC intake in SHIP-TREND (discovery cohort), of which 25 replicated in SHIP-2. Inter alia, associated metabolites included 12 out of 38 phosphatidylcholines with diacyl residue, 7 out of 14 lysophosphatidylcholines and 5 out of 21 amino acids. The associations with phosphatidylcholines were statistically mediated by cortisol, whereas lysophosphatidylcholines showed no mediation effect. The results represent a step toward a better understanding of the metabolic consequences of OC intake. Connecting cortisol with metabolic consequences of OC intake could help to understand the mechanisms underlying adverse effects. The blood metabolome may serve as a biomarker for identifying users at high risk for developing such adverse effects.

[Liquid chromatography-mass spectrometry-based metabolomics study of the efficacy of Chinese medicine asthma-relieving decoction on respiratory syncytial virus infection]

Respiratory syncytial virus (RSV) can cause lower respiratory tract infections, such as bronchiolitis in infants. In China, traditional asthma-relieving medicine has numerous clinical applications in the treatment of RSV infections. However, due to the complexity of the traditional Chinese medicine system, its therapeutic mechanism and main pharmacological components remain unclear. Metabolomics can be used to analyze the efficacy of traditional Chinese medicine to provide modern scientific evidence for such treatments. In this study, an animal model experiment was performed with seven groups of three-week-old rats. The model group and five intervention groups were inoculated nasally with RSV for three consecutive days, and the normal group was treated with the same amount of saline for three consecutive days under the same conditions. In parallel, the five intervention groups were treated separately with the following via intragastric administration for seven consecutive days: asthma-relieving traditional Chinese medicine decoction, its three constituent agents (ascending (xuan) therapy, descending (jiang) therapy, pyretic clearing (qing) therapy), and ribavirin. Both normal group and RSV model group were administered with normal saline via intragastric administration as controls for seven consecutive days. The fundus plasma of rats in each group was collected on day 0, day 3, and day 7. Liquid chromatography-mass spectrometry-based untargeted metabolomics analysis was performed to investigate the changes in the metabolome after RSV infection, the effects of the asthma-relieving decoction on the regulation of metabolites related to RSV infection, and the primary source of efficacy. The detected metabolite ions were corrected using internal standards. Multivariate analysis of ions with an RSD value of less than 30% in quality control (QC) samples was used to construct principal component analysis models to monitor the overall metabolic changes of each group. The results showed that, during RSV infection and treatment, the asthma-relieving decoction and the positive control ribavirin had similar effects on the overall metabolic regulation of RSV-infected rats. Among the three asthma-relieving decoction constituent agents, the ascending (xuan) therapy agents which was composed of ephedra and ginkgo had a closer metabolic regulation effect with asthma-relieving decoction, and might be the main source of pharmacological efficacy. Based on the retention time, m/z value and tandem mass spectra in the database established by our laboratory, a total of 150 metabolites were identified. Paired t-tests were performed using data of the identified metabolites before and after RSV infection in each group, and it was found that 83 metabolite levels significantly changed after RSV infection, indicating that RSV infection could lead to disorders of multiple metabolic pathways in rats. The altered pathways included aminoacyl-tRNA biosynthesis, phenylalanine, tyrosine, and tryptophan biosynthesis, primary bile acid biosynthesis, phenylalanine metabolism and sphingomyelin metabolism. On the third day, the asthma-relieving decoction had regulatory effects on several metabolites such as bile acids, amino acids, organic acids, lipids, etc. Among the three asthma-relieving decoction constituent agents, the ascending (xuan) therapy agents had more similar effects on the regulation of metabolites with the asthma-relieving decoction. On the other hand, the descending (jiang) therapy agents and pyretic clearing (qing) therapy agents down-regulated the abnormal increase in acylcarnitine caused by the RSV infection. Additionally, both asthma-relieving decoction and its constituent agents could maintain the stability of the immune system and metabolism of the intestinal flora in rats. This study used metabolomics to evaluate the efficacy of an asthma-relieving decoction and demonstrate the metabolites and the corresponding changes after asthma-relieving decoction-based treatment. It provides theoretical support for research on the therapeutic mechanism and active ingredients of asthma-relieving decoction.

Protein Requirements of Pre-Menopausal Female Athletes: Systematic Literature Review

This systematic literature review aimed to determine the protein requirements of pre-menopausal (e.g., 18-45 years) female athletes and identify if the menstrual cycle phase and/or hormonal contraceptive use influence protein requirements. Four databases were searched for original research containing pre-menopausal female athletes that ingested protein alongside exercise. The Academy of Nutrition and Dietetics Quality Criteria Checklist was used to determine study quality. Fourteen studies, which included 204 recreationally active or competitive females, met the eligibility criteria for inclusion in this review, and all were assessed as positive quality. The estimated average requirement (EAR) for protein intake of pre-menopausal recreational and/or competitive female athletes is similar for those undertaking aerobic endurance (1.28-1.63 g/kg/day), resistance (1.49 g/kg/day) and intermittent exercise (1.41 g/kg/day) of ~60-90 min duration. The optimal acute protein intake and influence of menstrual cycle phase or hormonal contraceptive use on protein requirements could not be determined. However, pre- and post-exercise protein intakes of 0.32-0.38 g/kg have demonstrated beneficial physiological responses in recreational and competitive female athletes completing resistance and intermittent exercise. The protein requirements outlined in this review can be used for planning and assessing protein intakes of recreational and competitive pre-menopausal female athletes.

Liquid Chromatography-Mass Spectrometry-Based Tissue Metabolic Profiling Reveals Major Metabolic Pathway Alterations and Potential Biomarkers of Lung Cancer

Unclarified molecular mechanism and lack of practical diagnosis biomarkers hinder the effective treatment of non-small-cell lung cancer. Herein, we performed liquid chromatography-mass spectrometry-based nontargeted metabolomics analysis in 131 patients with their lung tissue pairs to study the metabolic characteristics and disordered metabolic pathways in lung tumor. A total of 339 metabolites were identified in metabolic profiling. Also, 241 differential metabolites were found between lung carcinoma tissues (LCTs) and paired distal noncancerous tissues; amino acids, purine metabolites, fatty acids, phospholipids, and most of lysophospholipids significantly increased in LCTs, while 3-phosphoglyceric acid, phosphoenolpyruvate, 6-phosphogluconate, and citrate decreased. Additionally, pathway enrichment analysis revealed that energy, purine, amino acid, lipid, and glutathione metabolism are markedly disturbed in lung cancer (LCa). Using binary logistic regression, we further defined candidate biomarkers for different subtypes of lung tumor. Xanthine and PC 35:2 were selected as combinational biomarkers for distinguishing benign from malignant lung tumors with a 0.886 area under curve (AUC) value, and creatine, myoinositol and LPE 16:0 were defined as combinational biomarkers for discriminating adenocarcinoma from squamous cell lung carcinoma with a 0.934 AUC value. Overall, metabolic characterization and pathway disturbance demonstrated apparent metabolic reprogramming in LCa. The defined candidate metabolite marker panels are useful for subtyping of lung tumors to assist clinical diagnosis.

Development of an LC-MS multivariate nontargeted methodology for differential analysis of the peptide profile of Asian hornet venom (Vespa velutina nigrithorax): application to the investigation of the impact of collection period variation

Insect venom is a highly complex mixture of bioactive compounds, containing proteins, peptides, and small molecules. Environmental factors can alter the venom composition and lead to intraspecific variation in its bioactivity properties. The investigation of discriminating compounds caused by variation impacts can be a key to manage sampling and explore the bioactive compounds. The present study reports the development of a peptidomic methodology based on UHPLC-ESI-QTOF-HRMS analysis followed by a nontargeted multivariate analysis to reveal the profile variance of Vespa velutina venom collected in different conditions. The reliability of the approach was enhanced by optimizing certain XCMS data processing parameters and determining the sample peak threshold to eliminate the interfering features. This approach demonstrated a good repeatability and a criterion coefficient of variation (CV) > 30% was set for deleting nonrepeatable features from the matrix. The methodology was then applied to investigate the impact of collection period variation. PCA and PLS-DA models were used and validated by cross-validation and permutation tests. A slight discrimination was found between winter and summer hornet venom in two successive years with 10 common discriminating compounds. Graphical abstract.

Capturing the Geoherbalism Differentiation in Wild Paris polyphylla var. yunnanensis Raw Materials through the Application of Multispectral Information Fusion Combined with Chemometrics

Paris polyphylla var. yunnanensis is a famous medicinal plant distributed in some Asian countries. This species has attracted a great deal of attention and is often used as raw materials in traditional medicine practices. With the purpose of gaining insight into the geoherbalism of wild P. polyphylla var. yunnanensis, a total of 183 dried rhizome samples from eight different regions including 16 typical or nontypical natural habitats have been analyzed by multispectral information fusion based on ultraviolet and Fourier transform infrared spectroscopies combined with partial least squares discriminant analysis (PLS-DA) and hierarchical cluster analysis. From the results, the use of multispectral information fusion strategy could improve the correct classification of samples, and good classification performances have been shown according to PLS-DA models. The discrimination of samples was obtained successfully with respect to the typical and nontypical natural habitats, different collection areas of typical natural habitats, and various sampling sites in nontypical natural habitats. Additionally, the similarities among samples were presented as well. Overall, the rhizome of wild P. polyphylla var. yunnanensis exhibited various regional dependence and individual differences according to the geographical origins, and the relatively appropriate growth region with better quality consistency of samples was preliminarily selected. This study also revealed that the developed multispectral information fusion method has the potential to be a reliable analytical methodology for capturing the geoherbalism differentiation in wild P. polyphylla var. yunnanensis. Furthermore, it could provide more chemical evidence for the critical supplement of quality evaluation on P. polyphylla var. yunnanensis.

Sex matters: a focus on the impact of biological sex on metabolomic profiles and dietary interventions

The metabolomic profile of a biofluid can be altered by dietary intake, exercise and disease processes and, thus provides an important tool for the study of many physiological processes. However, in addition to perturbation due to disease, the metabolomic profile of urine and plasma has also been shown to vary due to many intrinsic physiological factors such as age, sex, hormonal status and diurnal variation. Characterisation of this normal degree of variation in the metabolomic profiles of human biofluids is a necessary and important step in the development of metabolomics for use in nutrition-related research. The current review focuses on the impact of sex on the metabolomic profile. A number of studies have reported that sex impacts metabolites such as amino acids, lipids, sugars and keto acids. Furthermore, we examine the effect of the menstrual cycle on the metabolomic profile. Responses to dietary interventions can also differ between the sexes and highlighting this is important for the development of the field of precision nutrition.

Development of a metabolic pathway-based pseudo-targeted metabolomics method using liquid chromatography coupled with mass spectrometry

The pseudo-targeted metabolomics approach was developed recently which combined the advantages of untargeted and targeted analysis. However, the current pseudo-targeted analysis method has limitations due to the technical characteristics. In this study, a novel metabolic pathway-based pseudo-targeted approach was proposed for urine metabolomics analysis using an ultra-high-performance liquid chromatography (UPLC)-MS/MS system operated in the multiple reaction monitoring (MRM) mode. MRM ion pairs were acquired from urine samples through untargeted analysis using UPLC-HRMS, as well as by searching for metabolites in related pathways in relevant databases and from previous relevant research, including amino acids, fatty acids, nucleosides, carnitines, glycolysis metabolites, and steroids. This improved pseudo-targeted method exhibited good repeatability and precision, and no complicated peak alignment was required. As a proof of concept, the developed novel method was applied to the discovery of urine biomarkers for patients with esophageal squamous cell carcinoma (ESCC). The results showed that ESCC patients had altered acylcarnitines, amino acids, nucleosides, and steroid derivative levels et al. compared to those of healthy controls. The novelty of this study lies in the fact that it provides an approach for acquiring MRM ion pairs not only from untargeted MS analysis but also from targeted searching for metabolites in related metabolic pathways. By improving the detection limit of low-abundance metabolites, it enlarges the range for the discovery of potential biomarkers. Our work provides a foundation for achieving pseudo-targeted metabolomics analysis on the widely used LC-MS/MS MRM platform.

Changes in Plasma Acylcarnitine and Lysophosphatidylcholine Levels Following a High-Fructose Diet: A Targeted Metabolomics Study in Healthy Women

Background: The consumption of high amounts of fructose is associated with metabolic diseases. However, the underlying mechanisms are largely unknown. Objective: To determine the effects of high fructose intake on plasma metabolomics. Study design: We enrolled 12 healthy volunteers (six lean and six obese women, age 24–35 years) in a crossover intervention study. All participants carried out three diets: (1) low fructose (<10 g/day); (2) high fructose (100 g/day) from natural food sources (fruit); and (3) high fructose (100 g/day) from high fructose syrup (HFS). Outcome measures: The primary outcome was changes in plasma metabolites measured by targeted metabolomics. Results: High compared to low fructose diets caused a marked metabolite class separation, especially because of changes in acylcarnitine and lysophosphatidylcholine levels. Both high fructose diets resulted in a decrease in mean acylcarnitine levels in all subjects, and an increase in mean lysophosphatidylcholine and diacyl-phosphatidylcholine levels in obese individuals. Medium chain acylcarnitines were negatively correlated with serum levels of liver enzymes and with the fatty liver index. Discussion: The metabolic shifts induced by high fructose consumption suggest an inhibition of mitochondrial β-oxidation and an increase in lipid peroxidation. The effects tended to be more pronounced following the HFS than the fruit diet.

Differentiation and comparison of Wolfiporia cocos raw materials based on multi-spectral information fusion and chemometric methods

In order to achieve the target of deeper insight into the differentiation and comparison of Wolfiporia cocos, a total of 350 samples including distinct growth patterns, various collection regions and different medicinal parts were investigated using multi-spectral information fusion based on ultraviolet (UV) and Fourier transform infrared (FT-IR) spectroscopies coupled with chemometrics. From the results, the discrimination of samples was obtained successfully and good classification performances were shown according to partial least squares discriminant analysis (PLS-DA) models. Comparatively, the distinctness of chemical information in the two medicinal parts of W. cocos were much more than that in the same part with different growth patterns and collection areas. Meanwhile, an interesting finding suggested that growth patterns rather than geographical origins could be the dominant factor to effect the chemical properties of the same part samples, especially for the epidermis. Compared with the epidermis samples, there were better quality consistency for the inner part of W. cocos. Totally, this study demonstrated that the developed method proved to be reliable to perform comparative analysis of W. cocos. Moreover, it could provide more comprehensive chemical evidence for the critical supplement of quality assessment on the raw materials of W. cocos.