Metabolomic analysis of urine samples by UHPLC-QTOF-MS: Impact of normalization strategies

Untargeted Metabolomics and Soil Community Metagenomics Analyses Combined with Machine Learning Evaluation Uncover Geographic Differences in Ginseng from Different Locations

Panax ginseng C.A. Meyer, known as the "King of Herbs," has been used as a nutritional supplement for both food and medicine with the functions of relieving fatigue and improving immunity for thousands of years in China. In agricultural planting, soil environments of different geographical origins lead to obvious differences in the quality of ginseng, but the potential mechanism of the differences remains unclear. In this study, 20 key differential metabolites, including ginsenoside Rb1, glucose 6-phosphate, etc., were found in ginseng from 10 locations in China using an ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS)-untargeted metabolomics approach. The soil properties were analyzed and combined with metagenomics technology to explore the possible relationships among microbial elements in planting soil. Through Spearman correlation analysis, it was found that the top 10 microbial colonies with the highest abundance in the soil were significantly correlated with key metabolites. In addition, the relationship model established by the random forest algorithm and the quantitative relationship between soil microbial abundance and ginseng metabolites were successfully predicted. The XGboost model was used to determine 20(R)-ginseng Rg2 and 2'(R)-ginseng Rg3 as feature labeled metabolites, and the optimal ginseng production area was discovered. These results prove that the accumulation of metabolites in ginseng was influenced by microorganisms in the planting soil, which led to geographical differences in ginseng quality.

Kidney-tonifying blood-activating decoction delays ventricular remodeling in rats with chronic heart failure by regulating gut microbiota and metabolites and p38 mitogen-activated protein kinase/p65 nuclear factor kappa-B/aquaporin-4 signaling pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Myocardial infarction has likely contributed to the increased prevalence of heart failure(HF).As a result of ventricular remodeling and reduced cardiac function, colonic blood flow decreases, causing mucosal ischemia and hypoxia of the villous structure of the intestinal wall.This damage in gut barrier function increases bowel wall permeability, leading to fluid metabolism disorder,gut microbial dysbiosis, increased gut bacteria translocation into the circulatory system and increased circulating endotoxins, thus promoting a typical inflammatory state.Traditional Chinese Medicine plays a key role in the prevention and treatment of HF.Kidney-tonifying Blood-activating(KTBA) decoction has been proved for clinical treatment of chronic HF.However,the mechanism of KTBA decoction on chronic HF is still unclear.

AIMS OF THE STUDY

The effect of KTBA decoction on gut microbiota and metabolites and p38MAPK/p65NF-κB/AQP4 signaling in rat colon was studied to investigate the mechanism that KTBA decoction delays ventricular remodeling and regulates water metabolism disorder in rats with HF after myocardial infarction based on the theory of "Kidney Storing Essence and Conducting Water".

MATERIAL AND METHODS

In vivo,a rat model of HF after myocardial infarction was prepared by ligating the left anterior descending coronary artery combined with exhaustive swimming and starvation.The successful modeling rats were randomly divided into five groups:model group, tolvaptan group(gavaged 1.35mg/(kg•D) tolvaptan),KTBA decoction group(gavaged 15.75g/(kg•D) of KTBA decoction),KTBA decoction combined with SB203580(p38MAPK inhibitor) group(gavaged 15.75g/(kg•D) of KTBA decoction and intraperitoneally injected 1.5mg/(kg•D) of SB203580),and KTBA decoction combined with PDTC(p65NF-kB inhibitor) group(gavaged 15.75g/(kg•D) of KTBA decoction and intraperitoneally injected 120mg/(kg•D) of PDTC).The sham-operation group and model group were gavaged equal volume of normal saline.After 4 weeks of intervention with KTBA decoction,the effect of KTBA decoction on the cardiac structure and function of chronic HF model rats was observed by ultrasonic cardiogram.General state and cardiac index in rats were evaluated.Enzyme linked immunosorbent assay(ELISA) was used to measure N-terminal pro-brain natriuretic peptide (NT-proBNP) concentration in rat serum.Hematoxylin and eosin(H&E) staining,and transmission electron microscope(TEM) were used to observe the morphology and ultrastructure of myocardial and colonic tissue,and myocardial fibrosis was measured by Masson's staining.Cardiac E-cadherin level was detected by Western blot.The mRNA expression and protein expression levels of p38MAPK,I-κBα, p65NF-κB,AQP4,Occludin and ZO-1 in colonic tissue were detected by reverse transcription-quantitative real-time polymerase chain reaction(RT-qPCR) and immunohistochemistry. Protein expression of p38MAPK, p-p38MAPK,I-κBα,p-I-κBα,p65NF-κB, p-p65NF-κB,AQP4,Occludin and ZO-1 in rat colon was detected using Western blot.Colonic microbiota and serum metabolites were respectively analyzed by amplicon sequencing and liquid chromatography-mass spectrometry.In vitro, CCD-841CoN cell was placed in the ischemic solution under hypoxic conditions (94%N2,5%CO2,and 1%O2) in a 37 °C incubator to establish an ischemia and hypoxia model.The CCD-841CoN cells were divided into 7 groups, namely blank group and model group with normal rat serum plus control siRNA, tolvaptan group with rat serum containing tolvaptan plus control siRNA, KTBA group with rat serum containing KTBA plus control siRNA, KTBA plus p38MAPK siRNA group, KTBA plus p65NF-κB siRNA group,and KTBA plus AQP4siRNA group.After 24h and 48h of intervention with KTBA decoction,RT-qPCR,immunofluorescence and Western blot was used to detect the mRNA expression and protein expression levels of p38MAPK,I-κBα,p65NF-κB,AQP4, Occludin and ZO-1 in CCD-841CoN cells.

RESULTS

Compared with the model, KTBA decoction improved the general state, decraesed the serum NT-proBNP level,HW/BW ratio, LVIDd and LVIDs, increased E-cadherin level,EF and FS,reduced number of collagen fibers deposited in the myocardial interstitium,and recovered irregular arrangement of myofibril and swollen or vacuolated mitochondria with broken crista in myocardium.Moreover, KTBA decoction inhibited the expression of p38MAPK,I-κBα,and p65NF-κB and upregulated AQP4, Occludin and ZO-1 in colon tissues and CCD-841CoN cells.Additionally,p38siRNA or SB203580, p65siRNA or PDTC, and AQP4siRNA partially weakened the protective effects of KTBA in vitro and vivo.Notably,The LEfSe analysis results showed that there were six gut biomaker bacteria in model group, including Allobaculum, Bacillales,Turicibacter, Turicibacterales,Turicibacteraceae,and Bacilli. Besides, three gut biomaker bacteria containing Deltaproteobacteria, Desulfovibrionaceae,and Desulfovibrionales were enriched by KTBA treatment in chronic HF model.There were five differential metabolites, including L-Leucine,Pelargonic acid, Capsidiol,beta-Carotene,and L- Erythrulose, which can be regulated back in the same changed metabolic routes by the intervention of KTBA.L-Leucine had the positive correlation with Bacillales, Turicibacterales,Turicibacteraceae,and Turicibacter.L-Leucine significantly impacts Protein digestion and absorption, Mineral absorption,and Central carbon metabolism in cancer regulated by KTBA, which is involved in the expression of MAPK and tight junction in intestinal epithelial cells.

CONCLUSIONS

KTBA decoction manipulates the expression of several key proteins in the p38MAPK/p65NF-κB/AQP4 signaling pathway, modulates gut microbiota and metabolites toward a more favorable profile, improves gut barrier function, delays cardiomyocyte hypertrophy and fibrosis,and improves cardiac function.

Urine metabolite changes after cardiac surgery predict acute kidney injury

Background

Acute kidney injury (AKI) is a serious complication in patients undergoing cardiac surgery, with the underlying mechanism remaining elusive and a lack of specific biomarkers for cardiac surgery-associated AKI (CS-AKI).

Methods

We performed an untargeted metabolomics analysis of urine samples procured from a cohort of patients with or without AKI at 6 and 24 h following cardiac surgery. Based on the differential urinary metabolites discovered, we further examined the expressions of the key metabolic enzymes that regulate these metabolites in kidney during AKI using a mouse model of ischemia-reperfusion injury (IRI) and in hypoxia-treated tubular epithelial cells (TECs).

Results

The urine metabolomic profiles in AKI patients were significantly different from those in non-AKI patients, including upregulation of tryptophan metabolism- and aerobic glycolysis-related metabolites, such as l-tryptophan and d-glucose-1-phosphate, and downregulation of fatty acid oxidation (FAO) and tricarboxylic acid (TCA) cycle-related metabolites. Spearman correlation analysis showed that serum creatinine was positively correlated with urinary l-tryptophan and indole, which had high accuracy for predicting AKI. In animal experiments, we demonstrated that the expression of rate-limiting enzymes in glycolysis, such as hexokinase II (HK2), was significantly upregulated during renal IRI. However, the TCA cycle-related key enzyme citrate synthase was significantly downregulated after IRI. In vitro, hypoxia induced downregulation of citrate synthase in TECs. In addition, FAO-related gene peroxisome proliferator-activated receptor alpha (PPARα) was remarkably downregulated in kidney during renal IRI.

Conclusion

This study presents urinary metabolites related to CS-AKI, indicating the rewiring of the metabolism in kidney during AKI, identifying potential AKI biomarkers.

Challenges and recent advances in quantitative mass spectrometry-based metabolomics

The field of metabolomics has gained tremendous interest in recent years. Whether the goal is to discover biomarkers related to certain pathologies or to better understand the impact of a drug or contaminant, numerous studies have demonstrated how crucial it is to understand variations in metabolism. Detailed knowledge of metabolic variabilities can lead to more effective treatments, as well as faster or less invasive diagnostics. Exploratory approaches are often employed in metabolomics, using relative quantitation to look at perturbations between groups of samples. Most metabolomics studies have been based on metabolite profiling using relative quantitation, with very few studies using an approach for absolute quantitation. Using accurate quantitation facilitates the comparison between different studies, as well as enabling longitudinal studies. In this review, we discuss the most widely used techniques for quantitative metabolomics using mass spectrometry (MS). Various aspects will be addressed, such as the use of external and/or internal standards, derivatization techniques, in vivo isotopic labelling, or quantitative MS imaging. The principles, as well as the associated limitations and challenges, will be described for each approach.

Discovery of two novel bioactive algicidal substances from Brevibacillus sp. via metabolomics profiling and back-validation

Identifying potent bacterial algicidal agents is essential for the development of effective, safe, and economically viable algaecides. Challenges in isolating and purifying these substances from complex secretions have impeded progress in this field. Metabolomics profiling, an efficient strategy for identifying metabolites, was pioneered in identifying bacterial algicidal substances in this study. Extracellular secretions from different generations of the algicidal bacterium Brevibacillus sp. were isolated for comprehensive analysis. Specifically, a higher algicidal efficacy was observed in the secretion from Generation 3 (G3) of Brevibacillus sp. compared to Generation 1 (G1). Subsequent metabolomics profiling comparing G3 and 1 revealed 83 significantly up-regulated metabolites, of which 9 were identified as potential algicidal candidates. Back-validation highlighted the potency of 4-acetamidobutanoic acid (4-ABC) and 8-hydroxyquinoline (8-HQL), which exhibited robust algicidal activity with 3d-EC50 values of 6.40 mg/L and 92.90 µg/L, respectively. These substances disrupted photosynthetic activity in M. aeruginosa by ceasing electron transfer in PSⅡ, like the impact exerted by Brevibacillus sp. secretion. These findings confirmed that 4-ABC and 8-HQL were the main algicidal components derived from Brevibacillus sp.. Thus, this study presents a streamlined strategy for identifying bacterial algicidal substances and unveils two novel and highly active algicidal substances. ENVIRONMENTAL IMPLICATION: Harmful cyanobacterial blooms (HCBs) pose significant environmental problems and health effects to humans and other organisms. The increasing frequency of HCBs has emerged as a pressing global concern. Bacterial-derived algicidal substances are expected to serve as effective, safe, and economically viable algaecides against HCBs. This study presents a streamlined strategy for identifying bacterial algicidal substances and unveils two novel substances (4-ABC and 8-HQL). These two substances demonstrate remarkable algicidal activity and disrupt the photosynthetic system in M. aeruginosa. They hold potential as prospective algaecides for addressing HCBs.

Nontargeted metabolomics reveals sequential changes in amino acid and ferroptosis-related metabolism in Parkinson's disease

Parkinson's disease (PD) is inseparable from metabolic disorders but lacks assessment of specific metabolite alteration. To explore the sequential metabolic changes in PD progression, we evenly divided 78 C57BL/6 mice (10 weeks) into six groups (one control group and five experimental groups) and collected the hippocampus tissue of mice after treating with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine, and probenecid (twice a week) at five periods (1, 2, 3, 4, and 5 weeks) for metabolome analysis. Our study identified 567 differentially abundant metabolites (DAMs) (total 4348 metabolites). Compared with controls, 145, 146, 171, 208, and 213 DAMs were obtained from the five experimental groups, respectively. Notably, 40 shared DAMs were present in five experimental groups, of which 22 shared DAMs formed a new metabolic network based on amino acid metabolism. Compared with group W3, 84 DAMs were identified in group W5, including 12 unique DAMs. DAMs in different stages of PD were significantly enriched in amino acid metabolism pathway, lipid metabolism pathway, and ferroptosis pathway. l-Glutamine, spermidine, and l-tryptophan were the key hubs in the whole metabolic process of PD. N-Formyl-l-methionine gradually increased in abundance with PD progression, whereas 5-methylcytosine gradually decreased. The study emphasized the sequential changes in DAMs in PD progression, stimulating subsequent studies.

Tackling new psychoactive substances through metabolomics: UHPLC-HRMS study on natural and synthetic opioids in male and female murine models

Novel psychoactive substances (NPS) represent a broad class of drugs new to the illicit market that often allow passing drug-screening tests. They are characterized by a variety of structures, rapid transience on the drug scene and mostly unknown metabolic profiles, thus creating an ever-changing scenario with evolving analytical targets. The present study aims at developing an indirect screening strategy for NPS monitoring, and specifically for new synthetic opioids (NSOs), based on assessing changes in endogenous urinary metabolite levels as a consequence of the systemic response following their intake. The experimental design involved in-vivo mice models: 16 animals of both sex received a single administration of morphine or fentanyl. Urine was collected before and after administration at different time points; the samples were then analysed with an untargeted metabolomics LC-HRMS workflow. According to our results, the intake of opioids resulted in an elevated energy demand, that was more pronounced on male animals, as evidenced by the increase in medium and long chain acylcarnitines levels. It was also shown that opioid administration disrupted the pathways related to catecholamines biosynthesis. The observed alterations were common to both morphine and fentanyl: this evidence indicate that they are not related to the chemical structure of the drug, but rather on the drug class. The proposed strategy may reinforce existing NPS screening approaches, by identifying indirect markers of drug assumption.

Integrated bacterial transcriptome and host metabolome analysis reveals insights into "Candidatus Liberibacter asiaticus" population dynamics in the fruit pith of three citrus cultivars with different tolerance

"Candidatus Liberibacter asiaticus" (CLas), the causal agent of citrus Huanglongbing (HLB), is able to multiply to a high abundance in citrus fruit pith. However, little is known about the biological processes and phytochemical substances that are vital for CLas colonization and growth in fruit pith. In this study, CLas-infected fruit pith of three citrus cultivars ("Shatangju" mandarin, "Guanxi" pomelo, and "Shatian" pomelo) exhibiting different tolerance to CLas were collected and used for dual RNA-Seq and untargeted metabolome analysis. Comparative transcriptome analysis found that the activation of the CLas noncyclic TCA pathway and pathogenic-related effectors could contribute to the colonization and growth of CLas in fruit pith. The pre-established Type 2 prophage in the CLas genome and the induction of its CRISPR/cas system could enhance the phage resistance of CLas and, in turn, facilitate CLas population growth in fruit pith. CLas infection caused the accumulation of amino acids that were correlated with tolerance to CLas. The accumulation of most sugars and organic acids in CLas-infected fruit pith, which could be due to the phloem blockage caused by CLas infection, was thought to be beneficial for CLas growth in localized phloem tissue. The higher levels of flavonoids and terpenoids in the fruit pith of CLas-tolerant cultivars, particularly those known for their antimicrobial properties, could hinder the growth of CLas. This study advances our understanding of CLas multiplication in fruit pith and offers novel insight into metabolites that could be responsible for tolerance to CLas or essential to CLas population growth.IMPORTANCECitrus Huanglongbing (HLB, also called citrus greening disease) is a highly destructive disease currently threatening citrus production worldwide. HLB is caused by an unculturable bacterial pathogen, "Candidatus Liberibacter asiaticus" (CLas). However, the mechanism of CLas colonization and growth in citrus hosts is poorly understood. In this study, we utilized the fruit pith tissue, which was able to maintain the CLas at a high abundance, as the materials for dual RNA-Seq and untargeted metabolome analysis, aiming to reveal the biological processes and phytochemical substances that are vital for CLas colonization and growth. We provided a genome-wide CLas transcriptome landscape in the fruit pith of three citrus cultivars with different tolerance and identified the important genes/pathways that contribute to CLas colonization and growth in the fruit pith. Metabolome profiling identified the key metabolites, which were mainly affected by CLas infection and influenced the population dynamic of CLas in fruit pith.

Urine Metabolite Profiles after the Consumption of a Low- and a High-Digestible Protein Meal, and Comparison of Urine Normalization Techniques

In the context of dietary transition toward plant proteins, it is necessary to ensure protein security in populations. It would thus be of interest to identify biomarkers of altered protein digestibility in populations. We examined the association between urinary metabolites and the acute intake of low- or highly digestible protein in healthy volunteers. The urine samples were collected before and 9 h after the ingestion of a meal containing either no protein, zein (low-digestible) or whey protein isolate (highly digestible). The liquid chromatography-high resolution mass spectrometry metabolomics approach was used for the profiling of the urinary metabolites. For the standardization of metabolomics data sets, osmolality-based, standard normal variates (SNV) and probabilistic quotient normalization (PQN) techniques were used. The ANOVA-based factorial method, AComDim_ICA, was used for chemometrics analysis. The osmolality adjustment has a beneficial effect and the subsequent mathematical normalization improves the chemometric analysis further. Some changes in the urinary metabolomes were observed 9 h after the meal in the three groups. However, there was no difference in the urine metabolome between groups. No biomarker of protein digestibility can be identified after the ingestion of a single meal, even when marked differences in the digestion efficiency of protein have been observed.

Pseudomonas-associated bacteria play a key role in obtaining nutrition from bamboo for the giant panda (Ailuropoda melanoleuca)

Gut microbiota plays a vital role in obtaining nutrition from bamboo for giant pandas. However, low cellulase activity has been observed in the panda's gut. Besides, no specific pathway has been implicated in lignin digestion by gut microbiota of pandas. Therefore, the mechanism by which they obtain nutrients is still controversial. It is necessary to elucidate the precise pathways employed by gut microbiota of pandas to degrade lignin. Here, the metabolic pathways for lignin degradation in pandas were explored by comparing 209 metagenomic sequencing data from wild species with different feeding habits. Lignin degradation central pathways, including beta-ketoadipate and homogentisate pathway, were enriched in the gut of wild bamboo-eating pandas. The gut microbiome of wild bamboo-eating specialists was enriched with genes from pathways implicated in degrading ferulate and p-coumarate into acetyl-CoA and succinyl-CoA, which can potentially provide the raw materials for metabolism in pandas. Specifically, Pseudomonas, as the most dominant gut bacteria genus, was found to be the main bacteria to provide genes involved in lignin or lignin derivative degradation. Herein, three Pseudomonas-associated strains isolated from the feces of wild pandas showed the laccase, lignin peroxidase, and manganese peroxidase activity and extracellular lignin degradation ability in vitro. A potential mechanism for pandas to obtain nutrition from bamboo was proposed based on the results. This study provides novel insights into the adaptive evolution of pandas from the perspective of lignin metabolism.

IMPORTANCE

Although giant pandas only feed on bamboo, the mechanism of lignin digestion in pandas is unclear. Here, the metabolic pathways for lignin degradation in wild pandas were explored by comparing gut metagenomic from species with different feeding habits. Results showed that lignin degradation central pathways, including beta-ketoadipate and homogentisate pathway, were enriched in the gut of wild bamboo-eating pandas. Genes from pathways involved in degrading ferulate and p-coumarate via beta-ketoadipate pathway were also enriched in bamboo-eating pandas. The final products of the above process, such as acetyl-CoA, can potentially provide the raw materials for metabolism in pandas. Specifically, Pseudomonas, as the most dominant gut bacteria genus, mainly provides genes involved in lignin degradation. Herein, Pseudomonas-associated strains isolated from the feces of pandas could degrade extracellular lignin. These findings suggest that gut microbiome of pandas is crucial in obtaining nutrition from lignin via Pseudomonas, as the main lignin-degrading bacteria.

Predicting the final metabolic profile based on the succession-related microbiota during spontaneous fermentation of the starter for Chinese liquor making

Microbial inoculation is an effective way to improve the quality of fermented foods via affecting the microbiota structure. However, it is unclear how the inoculation regulates the microbiota structure, and it is still difficult to directionally control the microbiota function via the inoculation. In this work, using the spontaneous fermentation of the starter (Daqu) for Chinese liquor fermentation as a case, we inoculated different microbiota groups at different time points in Daqu fermentation, and analyzed the effect of the inoculation on the final metabolic profile of Daqu. The inoculated microbiota and inoculated time points both significantly affected the final metabolites via regulating the microbial succession (P < 0.001), and multiple inoculations can promote deterministic assembly. Twenty-seven genera were identified to be related to microbial succession, and drove the variation of 121 metabolites. We then constructed an elastic network model to predict the profile of these 121 metabolites based on the abundances of 27 succession-related genera in Daqu fermentation. Procrustes analysis showed that the model could accurately predict the metabolic abundances (average Spearman correlation coefficients >0.3). This work revealed the effect of inoculation on the microbiota succession and the metabolic profile. The established predicted model of metabolic profile would be beneficial for directionally improving the food quality.IMPORTANCEThis work revealed the importance of microbial succession to microbiota structure and metabolites. Multi-inoculations would promote deterministic assembly. It would facilitate the regulation of microbiota structure and metabolic profile. In addition, we established a model to predict final metabolites based on microbial genera related to microbial succession. This model was beneficial for optimizing the inoculation of the microbiota. This work would be helpful for controlling the spontaneous food fermentation and directionally improving the food quality.

People living with HIV display increased anti-apolipoprotein A1 auto-antibodies, inflammation, and kynurenine metabolites: a case-control study

Objective

This study aimed to study the relationship between auto-antibodies against apolipoprotein A1 (anti-apoA1 IgG), human immunodeficiency virus (HIV) infection, anti-retroviral therapy (ART), and the tryptophan pathways in HIV-related cardiovascular disease.

Design

This case-control study conducted in South Africa consisted of control volunteers (n = 50), people living with HIV (PLWH) on ART (n = 50), and untreated PLWH (n = 44). Cardiovascular risk scores were determined, vascular measures were performed, and an extensive biochemical characterisation (routine, metabolomic, and inflammatory systemic profiles) was performed.

Methods

Anti-apoA1 IgG levels were assessed by an in-house ELISA. Inflammatory biomarkers were measured with the Meso Scale Discovery® platform, and kynurenine pathway metabolites were assessed using targeted metabolomic profiling conducted by liquid chromatography-multiple reaction monitoring/mass spectrometry (LC-MRM/MS).

Results

Cardiovascular risk scores and vascular measures exhibited similarities across the three groups, while important differences were observed in systemic inflammatory and tryptophan pathways. Anti-apoA1 IgG seropositivity rates were 15%, 40%, and 70% in control volunteers, PLWH ART-treated, and PLWH ART-naïve, respectively. Circulating anti-apoA1 IgG levels were significantly negatively associated with CD4+ cell counts and positively associated with viremia and pro-inflammatory biomarkers (IFNγ, TNFα, MIPα, ICAM-1, VCAM-1). While circulating anti-apoA1 IgG levels were associated with increased levels of kynurenine in both control volunteers and PLWH, the kynurenine/tryptophan ratio was significantly increased in PLWH ART-treated.

Conclusion

HIV infection increases the humoral response against apoA1, which is associated with established HIV severity criteria and kynurenine pathway activation.

Evaluating the Effect of Data Merging and Postacquisition Normalization on Statistical Analysis of Untargeted High-Resolution Mass Spectrometry Based Urinary Metabolomics Data

Urine is one of the most widely used biofluids in metabolomic studies because it can be collected noninvasively and is available in large quantities. However, it shows large heterogeneity in sample concentration and consequently requires normalization to reduce unwanted variation and extract meaningful biological information. Biological samples like urine are commonly measured with electrospray ionization (ESI) coupled to a mass spectrometer, producing data sets for positive and negative modes. Combining these gives a more complete picture of the total metabolites present in a sample. However, the effect of this data merging on subsequent data analysis, especially in combination with normalization, has not yet been analyzed. To address this issue, we conducted a neutral comparison study to evaluate the performance of eight postacquisition normalization methods under different data merging procedures using 1029 urine samples from the Food Chain plus (FoCus) cohort. Samples were measured with a Fourier transform ion cyclotron resonance mass spectrometer (FT-ICR-MS). Normalization methods were evaluated by five criteria capturing the ability to remove sample concentration variation and preserve relevant biological information. Merging data after normalization was generally favorable for quality control (QC) sample similarity, sample classification, and feature selection for most of the tested normalization methods. Merging data after normalization and the usage of probabilistic quotient normalization (PQN) in a similar setting are generally recommended. Relying on a single analyte to capture sample concentration differences, like with postacquisition creatinine normalization, seems to be a less preferable approach, especially when data merging is applied.

Integrative analysis of transcriptome and metabolome reveals the sesquiterpenoids and polyacetylenes biosynthesis regulation in Atractylodes lancea (Thunb.) DC

Atractylodes lancea (Thunb.) is a perennial medicinal herb, with its dry rhizomes are rich in various sesquiterpenoids and polyacetylenes components (including atractylodin, atractylon and β-eudesmol). However, the contents of these compounds are various and germplasms specific, and the mechanisms of biosynthesis in A. lancea are still unknown. In this study, we identified the differentially expressed candidate genes and metabolites involved in the biosynthesis of sesquiterpenoids and polyacetylenes, and speculated the anabolic pathways of these pharmaceutical components by transcriptome and metabolomic analysis. In the sesquiterpenoids biosynthesis, a total of 28 differentially expressed genes (DEGs) and 6 differentially expressed metabolites (DEMs) were identified. The beta-Selinene is likely to play a role in the synthesis of atractylon and β-eudesmol. Additionally, the polyacetylenes biosynthesis showed the presence of 3 DEGs and 4 DEMs. Notably, some fatty acid desaturase (FAB2 and FAD2) significantly down-regulated in polyacetylenes biosynthesis. The gamma-Linolenic acid is likely involved in the biosynthesis of polyacetylenes and thus further synthesis of atractylodin. Overall, these studies have investigated the biosynthetic pathways of atractylodin, atractylon and β-eudesmol in A. lancea for the first time, and present potential new anchor points for further exploration of sesquiterpenoids and polyacetylenes compound biosynthesis pathways in A. lancea.

Metabolome and Transcriptome Association Analysis Reveals the Link Between Pigmentation and Nutrition Utilization in the Juveniles of Sea Cucumber Holothuria leucospilota

The sea cucumber Holothuria leucospilota is an economically and ecologically important tropical species. Following development into juveniles, H. leucospilota undergoes a color change from white to black, involving a pigmentation process for over a period of several months. In this study, a combination of liquid chromatography-tandem mass spectrometry (LC-MS/MS) and Next-Generation sequencing (NGS) were employed to investigate the changes in metabolomic and transcriptomic profiles during pigmentation in H. leucospilota juveniles. The metabolomic analysis identified a total of 341 metabolites, of which 52 were found to be differentially regulated (P < 0.05 and VIP > 1), with 27 being upregulated in white individuals and 25 in black individuals. Additionally, 632 differentially expressed genes (DEGs) were identified, with 380 genes upregulated in white samples and 252 genes upregulated in black samples. Interestingly, the melanin content and tyrosinase transcript levels did not display significant differences between the two groups. Metabolomic data suggested the involvement of the linoleic acid metabolic pathway in pigmentation. Transcriptomic analysis, coupled with realtime PCR validation, revealed a decrease in the transcript levels of digestive enzymes like α-amylase, maltase-glucoamylase, and trehalase after the juveniles changed to black. Furthermore, the mRNA expressions of major yolk proteins showed a decline, indicating a shift in the accumulation of protein nutrient sources. Overall, our findings suggest that during the pigmentation process in H. leucospilota, no significant changes were observed in the classical melanin pathway, while notable alterations were observed in their nutritional status. This study provides valuable insights into the regulatory mechanisms of pigmentation in marine organisms.

[A Preliminary Study on the Plasma Metabolomic Profiles of Patients Suffering From Acute Diquat Poisoning]

Objective

To analyze the plasma metabolomic features of patients suffering from acute diquat (DQ) poisoning and to explore the molecular mechanism and potential biomarkers of DQ poisoning.

Methods

A total of 7 patients suffering from acute DQ poisoning were enrolled in the DQ poisoning group. The poisoning of these patients occurred within a 12-h window at the time of enrollment. Meanwhile, 7 healthy immediate family members of the patients were enrolled as the normal controls. Liquid chromatography-mass spectrometry (LC-MS) was used to perform non-targeted metabolomic profiling of the plasma samples and to screen and identify differential metabolites and metabolic pathways.

Results

A total of 104 metabolites were screened and identified (P<0.05 and the variable importance in the projection [VIP]>1). Compared with those of the control group, 61 metabolites, such as sorbitol and galactitol, were up-regulated, and 43 metabolites, such as myo-inositol and gamma-glutamylcysteine, were down-regulated in the DQ poisoning group. Pathway enrichment analysis revealed changes in 11 metabolic pathways, including those for galactose metabolism and linoleic acid metabolism (P<0.05).

Conclusion

Metabolomics analysis of plasma samples from DQ poisoning patients shows that DQ mainly interferes with the metabolism of energy, amino acids, and lipids, thus causing metabolic disorders. Some potential biomarkers closely associated with oxidative stress and organ damage of the liver, kidney, and nervous system have been identified.

A benchmark study of data normalisation methods for PTR-TOF-MS exhaled breath metabolomics

Volatilomics is the branch of metabolomics dedicated to the analysis of volatile organic compounds in exhaled breath for medical diagnostic or therapeutic monitoring purposes. Real-time mass spectrometry (MS) technologies such as proton transfer reaction (PTR) MS are commonly used, and data normalisation is an important step to discard unwanted variation from non-biological sources, as batch effects and loss of sensitivity over time may be observed. As normalisation methods for real-time breath analysis have been poorly investigated, we aimed to benchmark known metabolomic data normalisation methods and apply them to PTR-MS data analysis. We compared seven normalisation methods, five statistically based and two using multiple standard metabolites, on two datasets from clinical trials for COVID-19 diagnosis in patients from the emergency department or intensive care unit. We evaluated different means of feature selection to select the standard metabolites, as well as the use of multiple repeat measurements of ambient air to train the normalisation methods. We show that the normalisation tools can correct for time-dependent drift. The methods that provided the best corrections for both cohorts were probabilistic quotient normalisation and normalisation using optimal selection of multiple internal standards. Normalisation also improved the diagnostic performance of the machine learning models, significantly increasing sensitivity, specificity and area under the receiver operating characteristic (ROC) curve for the diagnosis of COVID-19. Our results highlight the importance of adding an appropriate normalisation step during the processing of PTR-MS data, which allows significant improvements in the predictive performance of statistical models.Clinical trials: VOC-COVID-Diag (EudraCT 2020-A02682-37); RECORDS trial (EudraCT 2020-000296-21).

Metabolic Responses to Manganese Toxicity in Soybean Roots and Leaves

Soybean is one of the most crucial beans in the world. Although Mn (manganese) is a kind of important nutritive element helpful to plant growth and health, excess Mn is harmful to crops. Nevertheless, the effect of Mn toxicity on soybean roots and leaves metabolism is still not clear. To explore this, water culture experiments were conducted on the development, activity of enzyme, and metabolic process of soybeans under varying levels of Mn treatment (5 and 100 μM). Compared with the control, the soybeans under Mn stress showed inhibited growth and development. Moreover, the activity of superoxide dismutase (SOD), catalase (CAT), peroxidase (POD), ascorbate peroxidase (APX), and the soluble protein content in leaves and roots of soybean were all increased. However, soluble sugar and proline contents in soybean roots and leaves showed the opposite trend. In addition, the Mg (magnesium) and Fe (iron) ion contents in soybean leaves significantly decreased, and the Mn ion content greatly increased. In roots, the Mn and Fe ion content increased, whereas the Mg ion content decreased. Furthermore, the metabolomic analysis based on nontargeted liquid chromatography-mass spectrometry identified 136 and 164 differential metabolites (DMs) that responded to Mn toxicity in roots and leaves of soybean, respectively. These DMs might participate in five different primary metabolic pathways in soybean leaves and roots, suggesting that soybean leaves and roots demonstrate different kinds of reactions in response to Mn toxicity. These findings indicate that Mn toxicity will result in enzymes activity being changed and the metabolic pathway being seriously affected, hence inhibiting the development of soybean.

Multi-time point metabolomics reveals key metabolic features from the ultra-early stage of intracerebral hemorrhage in mice

Despite decades of intensive research, there are still very limited options for the effective treatment of intracerebral hemorrhage (ICH). Recently, mounting evidence has indicated that the ultra-early stage (<3 h), serving as the primary phase of ICH, plays a pivotal role and may even surpass other stages in terms of its significance. Therefore, uncovering the metabolic alterations induced by ICH in the ultra-early stage is of crucial importance. To investigate this, the collagenase ICH mouse model was employed in this study. ICH or sham-operated mice were euthanized at the ultra-early stage of 3 h and the acute stage of 24 h and 72 h after the operation. Then, the metabolic changes in the perihematomal tissues were detected by liquid chromatography coupled with tandem mass spectrometry. In total, alterations in the levels of 465 metabolites were detected. A total of 136 metabolites were significantly changed at 3 h. At 24 h and 72 h, the amounts were 132 and 126, respectively. Additionally, the key corresponding metabolic pathways for these time points were analyzed through KEGG. To gather additional information, quantitative real-time transcription polymerase chain reaction, enzyme-linked immunosorbent assay and Western blots were performed to validate the metabolic changes. Overall, ICH significantly alters important physiological functions such as cysteine metabolism, purine metabolism, synaptic alterations, the synaptic vesicle cycle, and the ATP-binding cassette transporter system. These might be the key pathologic mechanisms of the ultra-early stage induced by ICH.

Exploration and optimization of extraction, analysis and data normalization strategies for mass spectrometry-based DNA adductome mapping and modeling

Although interest in characterizing DNA damage by means of DNA adductomics has substantially grown, the field of DNA adductomics is still in its infancy, with room for optimization of methods for sample analysis, data processing and DNA adduct identification. In this context, the first objective of this study was to evaluate the use of hydrophilic interaction (HILIC) vs. reversed phase liquid chromatography (RPLC) coupled to high resolution mass spectrometry (HRMS) and thermal acidic vs. enzymatic hydrolysis of DNA followed by DNA adduct purification and enrichment using solid-phase extraction (SPE) or fraction collection for DNA adductome mapping. The second objective was to assess the use of total ion count (TIC) and median intensity (MedI) normalization compared to QC (quality control), iQC (internal QC) and quality control-based robust locally estimated scatterplot smoothing (LOESS) signal correction (QC-RLSC) normalization for processing of the acquired data. The results demonstrate that HILIC compared to RPLC allowed better modeling of the tentative DNA adductome, particularly in combination with thermal acidic hydrolysis and SPE (more valid models, with an average Q²(Y) and R²(Y) of 0.930 and 0.998, respectively). Regarding the need for data normalization and the management of (limited) system instability and signal drift, QC normalization outperformed TIC, MedI, iQC and LOESS normalization. As such, QC normalization can be put forward as the default data normalization strategy. In case of momentous signal drift and/or batch effects however, comparison to other normalization strategies (like e.g. LOESS) is recommended. In future work, further optimization of DNA adductomics may be achieved by merging of HILIC and RPLC datasets and/or application of 2D-LC, as well as the inclusion of Schiff base stabilization and/or fraction collection in the thermal acidic hydrolysis-SPE sample preparation workflow.

In Search of Complementary Extraction Methods for Comprehensive Coverage of the Escherichia coli Metabolome

Escherichia coli is an invaluable research tool for many fields of biology, in particular for the production of recombinant enzymes. However, the activity of many such recombinant enzymes cannot be determined using standard biochemical assays, as often, the relevant substrates are not known, or the products produced are not detectable. Today, the biochemical footprints of such unknown enzyme activities can be revealed via the analysis of the metabolomes of the recombinant E. coli clones in which they are expressed, using sensitive technologies such as mass spectrometry. However, before any metabolites can be identified, it is necessary to achieve as high a coverage of the potential metabolites present within E. coli as possible. We have therefore analyzed a wide range of different extraction methods against the cell free extracts of various recombinant E. coli clones. The results were analyzed to determine the minimum number of extractions that achieved high recovery and coverage of metabolites. Two methods were selected for further analysis due to their ability to produce not only high numbers of ions, but also wide mass coverage and a high degree of complementarity. One extraction method uses acetonitrile and water, in a 4:1 ratio, which is then dried down and reconstituted in the chromatography running buffer prior to injection onto the chromatography column, and the other extraction method uses a combination of methanol, water and chloroform, in a 3:1:1 ratio, which is injected directly onto the chromatography column. These two extraction methods were shown to be complementary to each other, as regards the respective metabolites extracted, and to cover a large range of metabolites.

PM2.5 exposure aggravates kidney damage by facilitating the lipid metabolism disorder in diabetic mice

Background

Ambient fine particulate matter ≤ 2.5 µm (PM2.5) air pollution exposure has been identified as a global health threat, the epidemiological evidence suggests that PM2.5 increased the risk of chronic kidney disease (CKD) among the diabetes mellitus (DM) patients. Despite the growing body of research on PM2.5 exposure, there has been limited investigation into its impact on the kidneys and the underlying mechanisms. Past studies have demonstrated that PM2.5 exposure can lead to lipid metabolism disorder, which has been linked to the development and progression of diabetic kidney disease (DKD).

Methods

In this study, db/db mice were exposed to different dosage PM2.5 for 8 weeks. The effect of PM2.5 exposure was analysis by assessment of renal function, pathological staining, immunohistochemical (IHC), quantitative real-time PCR (qPCR) and liquid chromatography with tandem mass spectrometry (LC-MS/MS) based metabolomic analyses.

Results

The increasing of Oil Red staining area and adipose differentiation related protein (ADRP) expression detected by IHC staining indicated more ectopic lipid accumulation in kidney after PM2.5 exposure, and the increasing of SREBP-1 and the declining of ATGL detected by IHC staining and qPCR indicated the disorder of lipid synthesisandlipolysis in DKD mice kidney after PM2.5 exposure. The expressions of high mobility group nucleosome binding protein 1 (HMGN1) and kidney injury molecule 1 (KIM-1) that are associated with kidney damage increased in kidney after PM2.5 exposure. Correlation analysis indicated that there was a relationship between HMGN1-KIM-1 and lipid metabolic markers. In addition, kidneys of mice were analyzed using LC-MS/MS based metabolomic analyses. PM2.5 exposure altered metabolic profiles in the mice kidney, including 50 metabolites. In conclusion the results of this study show that PM2.5 exposure lead to abnormal renal function and further promotes renal injury by disturbance of renal lipid metabolism and alter metabolic profiles.

Urinary Paraben Concentrations and Associations with the Periconceptional Urinary Metabolome: Untargeted and Targeted Metabolomics Analyses of Participants from the Early Pregnancy Study

BACKGROUND

Parabens, found in everyday items from personal care products to foods, are chemicals with endocrine-disrupting activity, which has been shown to influence reproductive function.

OBJECTIVES

This study investigated whether urinary concentrations of methylparaben, propylparaben, or butylparaben were associated with the urinary metabolome during the periconceptional period, a critical window for female reproductive function. Changes to the periconceptional urinary metabolome could provide insights into the mechanisms by which parabens could impact fertility.

METHODS

Urinary paraben concentrations were measured in paired pre- and postconception urine samples from 42 participants in the Early Pregnancy Study, a prospective cohort of 221 women attempting to conceive. We performed untargeted and targeted metabolomics analyses using ultrahigh-performance liquid chromatography quadrupole time-of-flight mass spectrometry. We used principal component analysis, orthogonal partial least-squares discriminant analysis, and permutation testing, coupled with univariate statistical analyses, to find metabolites associated with paraben concentration at the two time points. Potential confounders were identified with a directed acyclic graph and used to adjust results with multivariable linear regression. Metabolites were identified using fragmentation data.

RESULTS

Seven metabolites were associated with paraben concentration (variable importance to projection score > 1 , false discovery rate-corrected q -value < 0.1 ). We identified four diet-related metabolites to the Metabolomics Standards Initiative (MSI) certainty of identification level 2, including metabolites from smoke flavoring, grapes, and olive oil. One metabolite was identified to the class level only (MSI level 3). Two metabolites were unidentified (MSI level 4). After adjustment, three metabolites remained associated with methylparaben and propylparaben, two of which were diet-related. No metabolomic markers of endocrine disruption were associated with paraben concentrations.

DISCUSSION

This study identified novel relationships between urinary paraben concentrations and diet-related metabolites but not with metabolites on endocrine-disrupting pathways, as hypothesized. It demonstrates the feasibility of integrating untargeted metabolomics data with environmental exposure information and epidemiological adjustment for confounders. The findings underscore a potentially important connection between diet and paraben exposure, with applications to nutritional epidemiology and dietary exposure assessment. https://doi.org/10.1289/EHP12125.

The Urine Metabolome of R6/2 and zQ175DN Huntington's Disease Mouse Models

Huntington's disease (HD) is caused by the expansion of a polyglutamine (polyQ)-encoding tract in exon 1 of the huntingtin gene to greater than 35 CAG repeats. It typically has a disease course lasting 15-20 years, and there are currently no disease-modifying therapies available. Thus, there is a need for faithful mouse models of HD to use in preclinical studies of disease mechanisms, target validation, and therapeutic compound testing. A large variety of mouse models of HD were generated, none of which fully recapitulate human disease, complicating the selection of appropriate models for preclinical studies. Here, we present the urinary liquid chromatography-high-resolution mass spectrometry analysis employed to identify metabolic alterations in transgenic R6/2 and zQ175DN knock-in mice. In R6/2 mice, the perturbation of the corticosterone metabolism and the accumulation of pyrraline, indicative of the development of insulin resistance and the impairment of pheromone excretion, were observed. Differently from R6/2, zQ175DN mice showed the accumulation of oxidative stress metabolites. Both genotypes showed alterations in the tryptophan metabolism. This approach aims to improve our understanding of the molecular mechanisms involved in HD neuropathology, facilitating the selection of appropriate mouse models for preclinical studies. It also aims to identify potential biomarkers specific to HD.

LC-MS-based metabolomics reveals the mechanism of anti-gouty arthritis effect of Wuwei Shexiang pill

Wuwei Shexiang Pill (WSP) is a Tibetan traditional medicine, which has been demonstrated to exhibit potent anti-inflammatory and anti-gout effects. However, the specific pharmacological mechanism is not elucidated clearly. In the present study, liquid chromatography-mass spectrometry (LC-MS)-based metabolomics was applied to investigate the alteration of serum metabolites induced by WSP treatment in MSU-induced gouty rats. Subsequently, bioinformatics was utilized to analyze the potential metabolic pathway of the anti-gout effect of WSP. The pharmacodynamic data discovered that WSP could ameliorate ankle swelling and inflammatory cell infiltration, as well as downregulate the protein expression of IL-1β, p-NF-κB p65, and NLRP3 in the synovial membrane and surrounding tissues of gouty ankles. LC-MS-based metabolomics revealed that there were 30 differential metabolites in the serum between sham-operated rats and gouty ones, which were mainly involved in the metabolism of fructose and mannose, primary bile acid biosynthesis, and cholesterol metabolism. However, compared to the model group, WSP treatment upregulated 11 metabolic biomarkers and downregulated 31 biomarkers in the serum. KEGG enrichment analysis found that 27 metabolic pathways contributed to the therapeutic action of WSP, including linoleic acid metabolism, phenylalanine metabolism, and pantothenate and CoA biosynthesis. The comprehensive analysis-combined network pharmacology and metabolomics further revealed that the regulatory network of WSP against gout might be attributed to 11 metabolites, 7 metabolic pathways, 39 targets, and 49 active ingredients of WSP. In conclusion, WSP could ameliorate the inflammation of the ankle in MSU-induced gouty rats, and its anti-gout mechanism might be relevant to the modulation of multiple metabolic pathways, such as linoleic acid metabolism, phenylalanine metabolism, and pantothenate and CoA biosynthesis. This study provided data support for the secondary development of Chinese traditional patent medicine.

Comparison of ruminal microbiota, metabolomics, and milk performance between Montbéliarde×Holstein and Holstein cattle

Holstein cattle are well known for their high average milk yield but are more susceptible to disease and have lower fecundity than other breeds of cattle. The purpose of this study was to explore the relationship between ruminal metabolites and both milk performance and ruminal microbiota composition as a means of assessing the benefits of crossbreeding Montbéliarde and Holstein cattle. This experiment crossbred Holstein with Montbéliarde cattle, aimed to act as a reference for producing high-quality dairy products and improving the overall efficiency of dairy cattle breeding. Based on similar age, parity and lactation time, 46 cows were selected and divided into two groups (n  =  23 per group) for comparison experiment and fed the same formula: Montbéliarde×Holstein (MH, DIM  =  33.23  ±  5.61 d), Holstein (H, DIM  =  29.27  ±  4.23 d). Dairy herd improvement (DHI) data is an important basis for evaluating the genetic quality of bulls, understanding the quality level of milk, and improving feeding management. We collected the DHI data of these cows in the early lactation, middle lactation and late lactation period of 10  months. The results showed that the average milk production and protein content in Montbéliarde×Holstein were 1.76  kg (34.41  kg to 32.65  kg, p  >  0.05) and 0.1% (3.54 to 3.44%, p  <  0.05) higher than in Holstein cattle. Moreover, milk from Montbéliarde×Holstein cattle had lesser somatic cell score (1.66 to 2.02) than Holstein cattle (p  <  0.01). A total of 10 experimental cattle in early lactation were randomly selected in the two groups (Lactation time  =  92.70  ±  6.81), and ruminal fluid were collected by oral gastric tube. Using 16S rRNA microbial sequencing, we compared the ruminal microbiota composition and found that Montbéliarde×Holstein cattle had a lower abundance of Alphaproteobacteria (p  <  0.05) and higher abundance of Selenomonas than Holstein cattle (p  <  0.05). These bacteria play roles in protein degradation, nitrogen fixation and lactic acid degradation. The abundance of Succiniclasticum was also greater in Montbéliarde×Holstein cattle (p  =  0.053). Through ruminal metabolome analysis, we found that the levels of trans-ferulic acid, pyrrole-2-carboxylic acid, and quinaldic acid were significantly increased in Montbéliarde×Holstein cattle, while that of lathosterol was significantly decreased. The changes in the levels of these metabolites could confer improved antioxidant, anti-inflammatory, and antibacterial activities.

Urine Metabolites and Bioactive Compounds from Functional Food: Applications of Liquid Chromatography Mass Spectrometry

Bioactive compounds in functional foods, medicinal plants and others are considered attractive value-added molecules based on their wide range of bioactivity. It is clear that an important role is occupied by polyphenol, phenolic compounds and others. Urine is an effective biofluid to evaluate and monitor alterations in homeostasis and other processes related to metabolism. The current review provides a detailed description of the formation of urine in human body, various aspects relevant to sampling and analysis of urinary metabolites before presenting recent developments leveraging on metabolite profiling of urine. For the profiling of small molecules in urine, advancement of liquid chromatography mass tandem spectrometry (LC/MS/MS), establishment of standardized chemical fragmentation libraries, computational resources, data-analysis approaches with pattern recognition tools have made it an attractive option. The profiling of urinary metabolites gives an overview of the biomarkers associated with the diet and evaluates its biological effects. Metabolic pathways such as glycolysis, tricarboxylic acid cycle, amino acid metabolism, energy metabolism, purine metabolism and others can be evaluated. Finally, a combination of metabolite profiling with chemical standardization and bioassay in functional food and medicinal plants will likely lead to the identification of new biomarkers and novel biochemical insights.

Comprehensive investigation on volatile and non-volatile metabolites in low-salt doubanjiang with different fermentation methods

Doubanjiang is a well-known fermented condiment in China, but the high-salt concentration in its traditional manufacture process greatly lengthens the fermentation time, and leads to potential health risks. Here, the effects of salt reduction and co-inoculated starters (Tetragenococcus halophilus and Zygosaccharomyces rouxii) on the volatile metabolites (VMs) and non-volatile metabolites (NVMs) of doubanjiang were investigated using metabolomics technology and chemometrics analysis. Results showed that 75 VMs were identified, and 12 of them had significant aroma contribution (ROVAs ≥ 1). In addition, 106 NVMs were defined as significantly different metabolites (p < 0.05; VIP ≥ 1). Salt reduction could significantly increase the concentrations of VMs, but this strategy also promoted some undesirable odors like 2-phetylfuran and hexanoic acid, which could be totally suppressed by inoculation of starter. Moreover, the two starters improved amino acid, ester, and acid metabolites. This study provides a deeper insight into the development of low-salt fermented foods.

OSCA-finder: Redefining the assay of kidney disease diagnostic through metabolomics and deep learning

Liquid chromatography-mass spectrometry (LC-MS) is a platform for urine and blood sample analysis. However, the high variability in the urine sample reduced the confidence of metabolite identification. Therefore, pre and post-calibration operations are inevitable to ensure an accurate urine biomarker analysis. In this study, the phenomenon of a higher creatinine concentration variable in ureteropelvic junction obstruction (UPJO) patient urine samples than in healthy people was revealed, indicating the urine biomarker discovery of UPJO patients is not adapted to the creatinine calibrate strategy. Therefore, we proposed a pipeline "OSCA-Finder" to reshape the urine biomarker analysis. First, to ensure a more stable peak shape and total ion chromatography, we applied the product of osmotic pressure and injection volume as a calibration principle and integrated it with an online mixer dilution. Therefore, we obtained the most peaks and identified more metabolites in a urine sample with peak area group CV<30%. A data-enhanced strategy was applied to reduce the overfit while training a neural network binary classifier with an accuracy of 99.9%. Finally, seven accurate urine biomarkers combined with a binary classifier were applied to distinguish UPJO patients from healthy people. The results show that the UPJO diagnostic strategy based on urine osmotic pressure calibration has more potential than ordinary strategies.

Effect of orange solid waste diet on flesh quality and metabolic profile of common carp (Cyprinus carpio)

In this study, we aimed to evaluate the effects of solid waste of Citrus sinensis (SWC) supplementation in diet on common carp (Cyprinus carpio) flesh quality and the potential mechanisms underlying these effects. Four diets, each with different levels of SWC (0%, 5%, 10%, and 15%), were formulated and administered to C. carpio (48.83 ± 5.59 g) for 60 days. The results showed that SWC diet significantly enhanced specific growth rate, muscle sweetness (via sweet amino acids and sweet molecules), and the nutritional value of fish meat (increased protein, α-vitamin E, and allopurinol). Chromatography-mass spectrometry analyses indicated that SWC supplementation increased the essential amino acid content in the diet. In addition, SWC diet promoted biosynthesis of non-essential amino acids in muscle by enhancing glycolysis and the tricarboxylic acid cycle. In conclusion, SWC could be a cost-effective solution for providing nutritious and flavourful aquatic products.

Host-plant adaptation in xylophagous insect-microbiome systems: Contributionsof longicorns and gut symbionts revealed by parallel metatranscriptome

Adaptation to host plants is of great significance in the ecology of xylophagous insects. The specific adaptation to woody tissues is made possible through microbial symbionts. We investigated the potential roles of detoxification, lignocellulose degradation, and nutrient supplementation of Monochamus saltuarius and its gut symbionts in host plant adaptation using metatranscriptome. The gut microbial community structure of M. saltuarius that fed on the two plant species were found to be different. Plant compound detoxification and lignocellulose degradation genes have been identified in both beetles and gut symbionts. Most differentially expressed genes associated with host plant adaptations were up-regulated in larvae fed on the less suitable host (Pinus tabuliformis) compared to larvae fed on the suitable host (Pinus koraiensis). Our findings indicated that M. saltuarius and its gut microbes respond to plant secondary substances through systematic transcriptome responses, allowing them to adapt to unsuitable host plants.

Extending the breadth of saliva metabolome fingerprinting by smart template strategies and effective pattern realignment on comprehensive two-dimensional gas chromatographic data

Comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC × GC-TOFMS) is one the most powerful analytical platforms for chemical investigations of complex biological samples. It produces large datasets that are rich in information, but highly complex, and its consistency may be affected by random systemic fluctuations and/or changes in the experimental parameters. This study details the optimization of a data processing strategy that compensates for severe 2D pattern misalignments and detector response fluctuations for saliva samples analyzed across 2 years. The strategy was trained on two batches: one with samples from healthy subjects who had undergone dietary intervention with high/low-Maillard reaction products (dataset A), and the second from healthy/unhealthy obese individuals (dataset B). The combined untargeted and targeted pattern recognition algorithm (i.e., UT fingerprinting) was tuned for key process parameters, the signal-to-noise ratio (S/N), and MS spectrum similarity thresholds, and then tested for the best transform function (global or local, affine or low-degree polynomial) for pattern realignment in the temporal domain. Reliable peak detection achieved its best performance, computed as % of false negative/positive matches, with a S/N threshold of 50 and spectral similarity direct match factor (DMF) of 700. Cross-alignment of bi-dimensional (2D) peaks in the temporal domain was fully effective with a supervised operation including multiple centroids (reference peaks) and a match-and-transform strategy using affine functions. Regarding the performance-derived response fluctuations, the most promising strategy for cross-comparative analysis and data fusion included the mass spectral total useful signal (MSTUS) approach followed by Z-score normalization on the resulting matrix.

Combined metabolomics and gut microbiome to investigate the effects and mechanisms of Yuquan Pill on type 2 diabetes in rats

Yuquan Pill (YQP) is a traditional Chinese medicine (TCM) for the treatment of type 2 diabetes (T2DM) in China for many years, and has a beneficial clinical effect. In this study, the antidiabetic mechanism of YQP was investigated for the first time from the perspective of metabolomics and intestinal microbiota. After 28 days of high-fat feeding, rats were injected intraperitoneally with streptozotocin (STZ, 35 mg/kg) followed by a single oral administration of YQP 2.16 g/kg and metformin 200 mg/kg for 5 weeks. The results showed that YQP was effectively improved insulin resistance and alleviated hyperglycemia and hyperlipidemia associated with T2DM. YQP was found to regulate metabolism and gut microbiota in T2DM rats using untargeted metabolomics and gut microbiota integration. Forty-one metabolites and five metabolic pathways were identified, including Ascorbate and aldarate metabolism, Nicotinate and nicotinamide metabolism, Galactose metabolism, Pentose phosphate pathway and Tyrosine metabolism. YQP can regulate T2DM-induced dysbacteriosis by modulating the abundance of Firmicutes, Bacteroidetes, Ruminococcus, Lactobacillus. The restorative effects of YQP in rats with T2DM have been confirmed and provide a scientific basis for the clinical treatment of diabetic patients.

Gut metabolomics and 16S rRNA sequencing analysis of the effects of arecoline on non-alcoholic fatty liver disease in rats

Introduction: Non-alcoholic fatty liver disease (NAFLD) has gradually become the primary cause of fatty liver disease. Betel nuts have been used to treat gastrointestinal diseases.

Methods: In the present study, we analyzed the pathology, serology, gut flora, and metabolites in a rat model of NAFLD, with and without betel nut alkaloid treatment, using an integrated approach involving pathology, serological testing, 16S rRNA gene sequencing, and ultra-performance liquid chromatography-mass spectrometry metabolomics.

Results: Two rats were used for model validation. Thirty SD rats were included and divided into the normal group (C group), NAFLD model group (M group), low-dose group, medium-dose group (T group), and high-dose group with intraperitoneal injection of arecoline. The expression of blood lipids was significantly downregulated at all three arecoline concentrations (p &lt; 0.05). Alpha-diversity analysis of the intestinal flora showed significant differences among the three groups, with a significant reduction in population diversity in the M group and a recovery of population diversity after arecoline treatment. At the phylum level, the relative abundance of Firmicutes was significantly higher in the T group and Proteobacteria in the M group. The KEGG metabolic pathways included polyketide sugar unit biosynthesis and hypertrophic cardiomyopathy. Thirty-three significantly different metabolites were identified among the groups. Significantly different metabolites between groups T and M included indolepyruvate, 2-deoxystreptamine, sakuranetin, glycyl-leucine, and riboflavin. The KEGG metabolic pathway suggested a potential role for arachidonic acid metabolism, serotonergic synapses, neuroactive ligand-receptor interactions, tyrosine metabolism, and regiomelanin. Vitamin digestion and absorption, as well as regulation of lipolysis in adipocytes, were the main metabolic pathways that distinguished the T vs. M groups. PGE2 is involved in several metabolic pathways. Correlation analysis showed that 29 bacterial species were significantly associated with PGE2 levels in the M and T groups. Vagococcus, Lawsonia, Christensenella, unidentified Erysipelotrichaceae, unidentified Coriobacteriaceae, and five other bacterial groups are unique in the PGE2 metabolic pathway regulated by arecoline.

Discussion: Arecoline has lipid-lowering effects and may exert therapeutic effects in NAFLD through intestinal metabolites and intestinal flora, as well as through the Butyricicoccus/Christensenella/Coriobacteriaceae-COX2/PGE2 pathway. Thus, arecoline may represent a potential drug or target for NAFLD treatment.

Pre-analytical aspects in metabolomics of human biofluids - sample collection, handling, transport, and storage

Metabolomics is the field of omics research that offers valuable insights into the complex composition of biological samples. It has found wide application in clinical diagnostics, disease investigation, therapy prediction, monitoring of treatment efficiency, drug discovery, or in-depth analysis of sample composition. A suitable study design constitutes the fundamental requirements to ensure robust and reliable results from the study data. The study design process should include a careful selection of conditions for each experimental step, from sample collection to data analysis. The pre-analytical variability that can introduce bias to the subsequent analytical process, decrease the outcome reliability, and confuse the final results of the metabolomics research, should also be considered. Herein, we provide key information regarding the pre-analytical variables affecting the metabolomics studies of biological fluids that are the most desirable type of biological samples. Our work offers a practical review that can serve and guide metabolomics pre-analytical design. It indicates pre-analytical factors, which can introduce artificial data variation and should be identified and understood during experimental design (through literature overview or analytical experiments).

Young adult male LEW.1WR1 rats have reduced beta cell area and develop glucose intolerance

Prediabetes affects 1 in 3 American adults and is characterized by insulin resistance, insulin hypersecretion, and impaired glucose tolerance. Weanling LEW.1WR1 (1WR1) rats have increased blood insulin concentrations, so we hypothesized that young adult 1WR1 rats would develop impaired glucose tolerance due to the poor regulation of insulin. We monitored glucose tolerance, insulin tolerance, and weight gain for 10 weeks to assess if there was a decline in glucose processing over time. 1WR1 rats were significantly more glucose intolerant after 8 weeks. 1WR1 rats had increased body mass, yet abdominal fat mass was not significantly increased. Although the 1WR1 rats had increased circulating insulin and glucagon protein levels, 1WR1 rat beta cell area was significantly reduced. There may be underlying insulin resistance as evidenced by dysfunctional insulin regulation during fasting. Understanding the metabolic phenotype of this rat model can provide insight into the human pathophysiological changes that increase susceptibility to glucose intolerance and prediabetes.

Metabolomics-Based Mechanistic Insights into Revealing the Adverse Effects of Pesticides on Plants: An Interactive Review

In plant biology, metabolomics is often used to quantitatively assess small molecules, metabolites, and their intermediates in plants. Metabolomics has frequently been applied to detect metabolic alterations in plants exposed to various biotic and abiotic stresses, including pesticides. The widespread use of pesticides and agrochemicals in intensive crop production systems is a serious threat to the functionality and sustainability of agroecosystems. Pesticide accumulation in soil may disrupt soil-plant relationships, thereby posing a pollution risk to agricultural output. Application of metabolomic techniques in the assessment of the biological consequences of pesticides at the molecular level has emerged as a crucial technique in exposome investigations. State-of-the-art metabolomic approaches such as GC-MS, LC-MS/MS UHPLC, UPLC-IMS-QToF, GC/EI/MS, MALDI-TOF MS, and ¹H-HR-MAS NMR, etc., investigating the harmful effects of agricultural pesticides have been reviewed. This updated review seeks to outline the key uses of metabolomics related to the evaluation of the toxicological impacts of pesticides on agronomically important crops in exposome assays as well as bench-scale studies. Overall, this review describes the potential uses of metabolomics as a method for evaluating the safety of agricultural chemicals for regulatory applications. Additionally, the most recent developments in metabolomic tools applied to pesticide toxicology and also the difficulties in utilizing this approach are discussed.

A cross-validation based approach for estimating specific gravity in elementary-school aged children using a nonlinear model

Environmental research often relies on urinary biomarkers which require dilution correction to accurately measure exposures. Specific gravity (SG) and creatinine (UCr) are commonly measured urinary dilution factors. Epidemiologic studies may assess only one of these measures, making it difficult to pool studies that may otherwise be able to be combined. Participants from the National Health and Nutrition Examination Survey 2007-2008 cycle were used to perform k-fold validation of a nonlinear model estimating SG from UCr. The final estimated model was applied to participants from the School Inner-City Asthma Intervention Study, who submitted urinary samples to the Children's Health Exposure Analysis Resource. Model performance was evaluated using calibration metrics to determine how closely the average estimated SG was to the measured SG. Additional models, with interaction terms for age, sex, body mass index, race/ethnicity, relative time of day when sample was collected, log transformed 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), and asthma status were estimated and assessed for improvement. The association between monobenzyl phthalate (MBZP) and asthma symptom days, controlling for measured UCr, measured SG, and each estimated SG were compared to assess validity of the estimated SG. The model estimating SG from UCr alone, resulted in a beta estimate of 1.10 (95% CI: 1.01, 1.19), indicating agreement between model-predicted SG and measured SG. Inclusion of age and sex in the model improved estimation (β = 1.06, 95% CI: 0.98, 1.15). The full model accounting for all interaction terms with UCr resulted in the best agreement (β = 1.01, 95% CI: 0.93,1.09). Associations between MBZP and asthma symptoms days, controlling for each estimated SG, were within the range of effect estimates when controlling for measured SG and measured UCr (Rate ratios = 1.28-1.34). Our nonlinear modeling provides opportunities to estimate SG in studies that measure UCr or vice versa, enabling data pooling despite differences in urine dilution factors.

Combined metabolomic and transcriptomic analysis reveals key components of OsCIPK17 overexpression improves drought tolerance in rice

Oryza Sativa is one of the most important food crops in China, which is easily affected by drought during its growth and development. As a member of the calcium signaling pathway, CBL-interacting protein kinase (CIPK) plays an important role in plant growth and development as well as environmental stress. However, there is no report on the function and mechanism of OsCIPK17 in rice drought resistance. We combined transcriptional and metabonomic analysis to clarify the specific mechanism of OsCIPK17 in response to rice drought tolerance. The results showed that OsCIPK17 improved drought resistance of rice by regulating deep roots under drought stress; Response to drought by regulating the energy metabolism pathway and controlling the accumulation of citric acid in the tricarboxylic acid (TCA) cycle; Our exogenous experiments also proved that OsCIPK17 responds to citric acid, and this process involves the auxin metabolism pathway; Exogenous citric acid can improve the drought resistance of overexpression plants. Our research reveals that OsCIPK17 positively regulates rice drought resistance and participates in the accumulation of citric acid in the TCA cycle, providing new insights for rice drought resistance.

Hybridization alters the gut microbial and metabolic profile concurrent with modifying intestinal functions in Tunchang pigs

Introduction

Hybridization has been widely used among Chinese wild boars to improve their growth performance and maintain meat quality. Most studies have focused on the genetic basis for such variation. However, the differences in the gut environment between hybrid and purebred boars, which can have significant impacts on their health and productivity, have been poorly understood.

Methods

In the current study, metagenomics was used to detect the gut microbial diversity and composition in hybrid Batun (BT, Berkshire × Tunchang) pigs and purebred Tunchang (TC) pigs. Additionally, untargeted metabolomic analysis was used to detect differences in gut metabolic pathways. Furthermore, multiple molecular experiments were conducted to demonstrate differences in intestinal functions.

Results

As a result of hybridization in TC pigs, a microbial change was observed, especially in Prevotella and Lactobacillus. Significant differences were found in gut metabolites, including fatty acyls, steroids, and steroid derivatives. Furthermore, the function of the intestinal barrier was decreased by hybridization, while the function of nutrient metabolism was increased.

Discussion

Evidences were shown that hybridization changed the gut microbiome, gut metabolome, and intestinal functions of TC pigs. These findings supported our hypothesis that hybridization altered the gut microbial composition, thereby modifying the intestinal functions, even the host phenotypes. Overall, our study highlights the importance of considering the gut microbiome as a key factor in the evaluation of animal health and productivity, particularly in the context of genetic selection and breeding programs.

Maternal antibiotic treatment during pregnancy attenuates the transport and absorption of maternal antibody IgG through TLR4 and TLR2 receptor

Maternal antibody IgG, the main antibody in colostrum, plays an important role in neonates protection. Commensal microbiota is closely related to host antibody repertoire. However, there are few reports on how maternal gut microbiota affects maternal antibody IgG transfer. In the present study, we investigated the effects of altering the gut microbiota (treated with antibiotics during pregnancy) on maternal IgG transportation and offspring absorption and explored its underlying mechanisms. Results showed that antibiotic treatment during pregnancy significantly decreased maternal cecal microbial richness (Chao1 and Obesrved species) and diversity (Shannon and Simpson). Plasma metabolome enriched significant changes in the process of bile acid secretion pathway, and the concentration of deoxycholic acid, a secondary metabolite of microorganisms was lowered. Flow cytometry analysis indicated that antibiotic treatment promoted the number of B cells and abated the number of T, DC and M1 cells in intestinal lamina propria of dams. Surprisingly, the serum IgG level in antibiotic treated dams was significantly increased, while IgG contents in colostrum was decreased. Moreover, pregnancy antibiotic treatment in dams was reduced the expression of FcRn, TLR4 and TLR2 in breast of dams and in duodenum and jejunum of neonates. Furthermore, TLR4^-/- and TLR2^-/- knock-out mice showed a lower FcRn expression in breast of dams and in duodenum and jejunum of neonates. These findings suggest that maternal intestine bacteria may affect the maternal IgG transfer through regulating the breast TLR4 and TLR2 of dams.

The untargeted urine volatilome for biomedical applications: methodology and volatilome database

Chemically diverse in compounds, urine can give us an insight into metabolic breakdown products from foods, drinks, drugs, environmental contaminants, endogenous waste metabolites, and bacterial by-products. Hundreds of them are volatile compounds; however, their composition has never been provided in detail, nor has the methodology used for urine volatilome untargeted analysis. Here, we summarize key elements for the untargeted analysis of urine volatilome from a comprehensive compilation of literature, including the latest reports published. Current achievements and limitations on each process step are discussed and compared. 34 studies were found retrieving all information from the urine treatment to the final results obtained. In this report, we provide the first specific urine volatilome database, consisting of 841 compounds from 80 different chemical classes.

Combined Metabolomic and Transcriptomic Analysis Reveals Allantoin Enhances Drought Tolerance in Rice

Drought is a misfortune for agriculture and human beings. The annual crop yield reduction caused by drought exceeds the sum of all pathogens. As one of the gatekeepers of China's "granary", rice is the most important to reveal the key drought tolerance factors in rice. Rice seedlings of Nipponbare (Oryza sativa L. ssp. Japonica) were subjected to simulated drought stress, and their root systems were analyzed for the non-targeted metabolome and strand-specific transcriptome. We found that both DEGs and metabolites were enriched in purine metabolism, and allantoin accumulated significantly in roots under drought stress. However, few studies on drought tolerance of exogenous allantoin in rice have been reported. We aimed to further determine whether allantoin can improve the drought tolerance of rice. Under the treatment of exogenous allantoin at different concentrations, the drought resistant metabolites of plants accumulated significantly, including proline and soluble sugar, and reactive oxygen species (ROS) decreased and reached a significant level in 100 μmol L^-1. To this end, a follow-up study was identified in 100 μmol L^-1 exogenous allantoin and found that exogenous allantoin improved the drought resistance of rice. At the gene level, under allantoin drought treatment, we found that genes of scavenge reactive oxygen species were significantly expressed, including peroxidase (POD), catalase (CATA), ascorbate peroxidase 8 (APX8) and respiratory burst oxidase homolog protein F (RbohF). This indicates that plants treated by allantoin have better ability to scavenge reactive oxygen species to resist drought. Alternative splicing analysis revealed a total of 427 differentially expressed alternative splicing events across 320 genes. The analysis of splicing factors showed that gene alternative splicing could be divided into many different subgroups and play a regulatory role in many aspects. Through further analysis, we restated the key genes and enzymes in the allantoin synthesis and catabolism pathway, and found that the expression of synthetase and hydrolase showed a downward trend. The pathway of uric acid to allantoin is completed by uric acid oxidase (UOX). To find out the key transcription factors that regulate the expression of this gene, we identified two highly related transcription factors OsERF059 and ONAC007 through correlation analysis. They may be the key for allantoin to enhance the drought resistance of rice.

Metabolite quantification: A fluorescence-based method for urine sample normalization prior to 1H-NMR analysis

INTRODUCTION

Metabolomics is a multi-discipline approach to systems biology that provides a snapshot of the metabolic status of a cell, tissue, or organism. Metabolomics uses mass spectroscopy (MS) and nuclear magnetic resonance (NMR) to analyze biological samples for low molecular weight metabolites.

OBJECTIVE

Normalize urine sample pre-acquisition to perform a targeted quantitative analysis of selected metabolites in rat urine.

METHODS

Urine samples were provided from rats on a control diet (n = 10) and moderate sucrose diet (n = 8) collected in a metabolic cage during an eight hour fast. Urine from each sample was prepared by two different methods. One sample was a non-normalized sample of 1200 µL and the second sample was a variable volume-normalized to the concentration of urobilin in a standard sample of urine. The urobilin concentration in all samples was determined by fluorescence. Ten metabolites for each non-normalized and normalized urine sample were quantified by integration to an internal standard of DSS.

RESULTS

Both groups showed an improvement in pH range going from non-normalized to normalized samples. In the group on the control diet, eight metabolites had significant improvement in range, while the remaining two metabolites had insignificant improvement in range comparing the non-normalized sample to the normalized sample. In the group on the moderate sucrose diet all ten metabolites showed significant improvement in range going from non-normalized to normalized samples.

CONCLUSIONS

These findings describe a pre-acquisition method of urine normalization to adjust for differences in hydration state of each organism. This results in a narrower concentration range in a targeted analysis.

A combination of plasma membrane sterol biosynthesis and autophagy is required for shade-induced hypocotyl elongation

Plant growth ultimately depends on fixed carbon, thus the available light for photosynthesis. Due to canopy light absorption properties, vegetative shade combines low blue (LB) light and a low red to far-red ratio (LRFR). In shade-avoiding plants, these two conditions independently trigger growth adaptations to enhance light access. However, how these conditions, differing in light quality and quantity, similarly promote hypocotyl growth remains unknown. Using RNA sequencing we show that these two features of shade trigger different transcriptional reprogramming. LB induces starvation responses, suggesting a switch to a catabolic state. Accordingly, LB promotes autophagy. In contrast, LRFR induced anabolism including expression of sterol biosynthesis genes in hypocotyls in a manner dependent on PHYTOCHROME-INTERACTING FACTORs (PIFs). Genetic analyses show that the combination of sterol biosynthesis and autophagy is essential for hypocotyl growth promotion in vegetative shade. We propose that vegetative shade enhances hypocotyl growth by combining autophagy-mediated recycling and promotion of specific lipid biosynthetic processes.

Plants subject to vegetative shade receive a low quantity of blue light (LB) and a low ratio of red to far-red light (LFLR). Here the authors show that while LB induces autophagy, LFLR leads to changes in lipid metabolism, and propose that these processes may contribute to shade avoidance responses.

Impact of PM2.5 exposure on plasma metabolome in healthy adults during air pollution waves: A randomized, crossover trial

Air pollution, especially PM_2.5 (particulate matter with an aerodynamic diameter ≤2.5 µm) in China, is severe and related to a variety of diseases while the potential mechanisms have not been clearly clarified yet. This study was conducted using a randomized crossover trial protocol among young and healthy college students. Plasma samples were collected before, during, and post two typical air pollution waves with a washout interval of at least 2 weeks under true and sham air purification treatments, respectively. A total of 144 blood samples from 24 participants were included in the final analysis. Metabolomics analysis for the plasma samples was completed by Ultrahigh Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS). Orthogonal Partial Least Squares Discrimination Analysis (OPLS-DA) and linear mixed-effect models were used to identify the differentially expressed metabolites and their associations with PM_2.5 exposure. MetaboAnalyst 5.0 was further used to conduct pathway enrichment analysis and correlation analysis of differentially expressed metabolites. A total of 40 metabolites were identified to be differentially expressed between the true and sham air purification treatments, and eleven metabolites showed consistent significant changes upon outdoor, indoor, and time-weighted personal PM_2.5 exposures. Short-term exposure to PM_2.5 may cause disturbances in metabolic pathways such as linoleic acid metabolism, arachidonic acid metabolism, and tryptophan metabolism.