Oxaloacetate anaplerosis differently contributes to pathogenicity in plant pathogenic fungi Fusarium graminearum and F. oxysporum.

Anaplerosis refers to enzymatic reactions or pathways replenishing metabolic intermediates in the tricarboxylic acid (TCA) cycle. Pyruvate carboxylase (PYC) plays an important anaplerotic role by catalyzing pyruvate carboxylation, forming oxaloacetate. Although PYC orthologs are well conserved in prokaryotes and eukaryotes, their pathobiological functions in filamentous pathogenic fungi have yet to be fully understood. Here, we delve into the molecular functions of the ortholog gene PYC1 in Fusarium graminearum and F. oxysporum, prominent fungal plant pathogens with distinct pathosystems, demonstrating variations in carbon metabolism for pathogenesis. Surprisingly, the PYC1 deletion mutant of F. oxysporum exhibited pleiotropic defects in hyphal growth, conidiation, and virulence, unlike F. graminearum, where PYC1 deletion did not significantly impact virulence. To further explore the species-specific effects of PYC1 deletion on pathogenicity, we conducted comprehensive metabolic profiling. Despite shared metabolic changes, distinct reprogramming in central carbon and nitrogen metabolism was identified. Specifically, alpha-ketoglutarate, a key link between the TCA cycle and amino acid metabolism, showed significant down-regulation exclusively in the PYC1 deletion mutant of F. oxysporum. The metabolic response associated with pathogenicity was notably characterized by S-methyl-5-thioadenosine and S-adenosyl-L-methionine. This research sheds light on how PYC1-mediated anaplerosis affects fungal metabolism and reveals species-specific variations, exemplified in F. graminearum and F. oxysporum.

Cholesterol profiling reveals 7ß-hydroxycholesterol as a pathologically relevant peripheral biomarker of Alzheimer's disease.

AIM: Cholesterol homeostasis is associated with Alzheimer's disease (AD). Despite the multitude of cholesterol metabolites, little is known about which metabolites are directly involved in AD pathogenesis and can serve as its potential biomarkers. METHODS: To identify "hit" metabolites, steroid profiling was conducted in mice with different age, diet, and genotype and also in humans with normal cognition, mild cognitive impairment, and AD using gas chromatography-mass spectrometry. Then, using one of the "hit" molecules (7ß-hydroxycholesterol; OHC), molecular and histopathological experiment and behavioral testing were conducted in normal mice following its intracranial stereotaxic injection to see whether this molecule drives AD pathogenesis and causes cognitive impairment. RESULTS: The serum levels of several metabolites, including 7ß-OHC, were increased by aging in the 3xTg-AD unlike normal mice. Consistently, the levels of 7ß-OHC were increased in the hairs of patients with AD and were correlated with clinical severity. We found that 7ß-OHC directly affects AD-related pathophysiology; intrahippocampal injection of 7ß-OHC induced astrocyte and microglial cell activation, increased the levels of pro-inflammatory cytokines (TNF-alpha, IL-1ß, IL-6), and enhanced amyloidogenic pathway. Mice treated with 7ß-OHC also exhibited deficits in memory and frontal/executive functions assessed by object recognition and 5-choice serial reaction time task, respectively. CONCLUSIONS: Our results suggest that 7ß-OHC could serve as a convenient, peripheral biomarker of AD. As directly involved in AD pathogenesis, 7ß-OHC assay may help actualize personalized medicine in a way to identify an at-risk subgroup as a candidate population for statin-based AD treatment.

Discrimination of Cultivated Regions of Soybeans (Glycine max) Based on Multivariate Data Analysis of Volatile Metabolite Profiles.

Soybean (Glycine max) is a major crop cultivated in various regions and consumed globally. The formation of volatile compounds in soybeans is influenced by the cultivar as well as environmental factors, such as the climate and soil in the cultivation areas. This study used gas chromatography-mass spectrometry (GC-MS) combined by headspace solid-phase microextraction (HS-SPME) to analyze the volatile compounds of soybeans cultivated in Korea, China, and North America. The multivariate data analysis of partial least square-discriminant analysis (PLS-DA), and hierarchical clustering analysis (HCA) were then applied to GC-MS data sets. The soybeans could be clearly discriminated according to their geographical origins on the PLS-DA score plot. In particular, 25 volatile compounds, including terpenes (limonene, myrcene), esters (ethyl hexanoate, butyl butanoate, butyl prop-2-enoate, butyl acetate, butyl propanoate), aldehydes (nonanal, heptanal, (E)-hex-2-enal, (E)-hept-2-enal, acetaldehyde) were main contributors to the discrimination of soybeans cultivated in China from those cultivated in other regions in the PLS-DA score plot. On the other hand, 15 volatile compounds, such as 2-ethylhexan-1-ol, 2,5-dimethylhexan-2-ol, octanal, and heptanal, were related to Korean soybeans located on the negative PLS 2 axis, whereas 12 volatile compounds, such as oct-1-en-3-ol, heptan-4-ol, butyl butanoate, and butyl acetate, were responsible for North American soybeans. However, the multivariate statistical analysis (PLS-DA) was not able to clearly distinguish soybeans cultivated in Korea, except for those from the Gyeonggi and Kyeongsangbuk provinces.

Comparative global metabolite profiling of xylose-fermenting Saccharomyces cerevisiae SR8 and Scheffersomyces stipitis.

Bioconversion of lignocellulosic biomass into ethanol requires efficient xylose fermentation. Previously, we developed an engineered Saccharomyces cerevisiae strain, named SR8, through rational and inverse metabolic engineering strategies, thereby improving its xylose fermentation and ethanol production. However, its fermentation characteristics have not yet been fully evaluated. In this study, we investigated the xylose fermentation and metabolic profiles for ethanol production in the SR8 strain compared with native Scheffersomyces stipitis. The SR8 strain showed a higher maximum ethanol titer and xylose consumption rate when cultured with a high concentration of xylose, mixed sugars, and under anaerobic conditions than Sch. stipitis. However, its ethanol productivity was less on 40 g/L xylose as the sole carbon source, mainly due to the formation of xylitol and glycerol. Global metabolite profiling indicated different intracellular production rates of xylulose and glycerol-3-phosphate in the two strains. In addition, compared with Sch. stipitis, SR8 had increased abundances of metabolites from sugar metabolism and decreased abundances of metabolites from energy metabolism and free fatty acids. These results provide insights into how to control and balance redox cofactors for the production of fuels and chemicals from xylose by the engineered S. cerevisiae.

Multi-omic characterization of laboratory-evolved Saccharomyces cerevisiae HJ7-14 with high ability of algae-based ethanol production.

In this study, an evolved Saccharomyces cerevisiae HJ7-14 with high ability of algae-based ethanol production was characterized by multi-omic approaches. Genome sequencing of the HJ7-14 revealed a point mutation in the GAL83 gene (G703A) involved in the catabolite repression as well as the galactose metabolism. Cultural and transcriptional analyses of a S. cerevisiae mutant with chromosomal GAL83(G703A) indicated that the catabolite repression onto the galactose metabolism was considerably relieved in all cell growth stages. Untargeted metabolomic approach revealed that metabolic phenotypes between the control D452-2 and HJ7-14 strains were clearly discriminated in time-dependent manner. Especially in early growth stage at 6 h, the HJ7-14 showed dramatic and coordinated alteration in central carbon and amino acid metabolisms. Through metabolomic re-organization, fold changes in fatty acid metabolism and metabolites related to stress response system were also found upon glucose depletion and active galactose utilization. Multi-omic characterization using genome sequencing, transcription, and metabolome profiling clearly unveiled that the GAL83 gene mutation partially relieved glucose-dependent catabolite repression and allowed the evolved HJ7-14 to efficiently convert algal sugars to ethanol. Our finding could be applicable for engineering of S. cerevisiae able to covert red algal biomass to other biofuels and biochemicals.

Suppression of Somatic Expansion Delays the Onset of Pathophysiology in a Mouse Model of Huntington's Disease.

Huntington's Disease (HD) is caused by inheritance of a single disease-length allele harboring an expanded CAG repeat, which continues to expand in somatic tissues with age. The inherited disease allele expresses a toxic protein, and whether further somatic expansion adds to toxicity is unknown. We have created an HD mouse model that resolves the effects of the inherited and somatic expansions. We show here that suppressing somatic expansion substantially delays the onset of disease in littermates that inherit the same disease-length allele. Furthermore, a pharmacological inhibitor, XJB-5-131, inhibits the lengthening of the repeat tracks, and correlates with rescue of motor decline in these animals. The results provide evidence that pharmacological approaches to offset disease progression are possible.

Loss of caveolin-1 expression in knock-in mouse model of Huntington's disease suppresses pathophysiology in vivo.

Loss of cholesterol homeostasis and altered vesicle trafficking have been detected in Huntington's disease (HD) cellular and animal models, yet the role of these dysfunctions in pathophysiology of HD is unknown. We demonstrate here that defects in caveolar-related cholesterol trafficking directly contribute to the mechanism of HD in vivo. We generated new mouse models that express mutant Huntington's protein (mhtt), but have partial or total loss of caveolin-1 (Cav1) expression. Fluorescence resonance energy transfer dequenching confirms a direct interaction between mhtt and Cav1. Mhtt-expressing neurons exhibited cholesterol accumulation and suppressed caveolar-related post-Golgi trafficking from endoplasmic reticulum/Golgi to plasma membrane. Loss or reduction of Cav1 expression in a knock-in HD mouse model rescues the cholesterol phenotype in neurons and significantly delays the onset of motor decline and development of neuronal inclusions. We propose that aberrant interaction between Cav1 and mhtt leads to altered cholesterol homeostasis and plays a direct causative role in the onset of HD pathophysiology in vivo.

LipidBlast in silico tandem mass spectrometry database for lipid identification.

Current tandem mass spectral libraries for lipid annotations in metabolomics are limited in size and diversity. We provide a freely available computer-generated tandem mass spectral library of 212,516 spectra covering 119,200 compounds from 26 lipid compound classes, including phospholipids, glycerolipids, bacterial lipoglycans and plant glycolipids. We show platform independence by using tandem mass spectra from 40 different mass spectrometer types including low-resolution and high-resolution instruments.

Comparative evaluation of extraction methods for simultaneous mass-spectrometric analysis of complex lipids and primary metabolites from human blood plasma.

Metabolomic results on human blood plasma largely depend on the sample preparation protocols employed for protein precipitation and metabolite extraction. Five different extraction methods were examined, which can be grouped into two categories, liquid-liquid extraction and protein precipitation methods, including long-standing protocols such as the Folch extraction and Bligh-Dyer extraction in comparison to modern methods such as the Matyash protocol and two global metabolite extraction methods. Extracts were subjected to analysis of blood plasma lipids and primary metabolites by using chip-based direct infusion nanoelectrospray tandem mass spectrometry and gas chromatography coupled to time-of-flight mass spectrometry, respectively. Optimal extraction schemes were evaluated based on the number of identified metabolites, extraction efficiency, compound diversity, reproducibility, and convenience for high-throughput sample preparations. Results showed that Folch and Matyash methods were equally valid and robust for lipidomic assessments while primary metabolites were better assessed by the protein precipitation methods with organic solvent mixtures.

System response of metabolic networks in Chlamydomonas reinhardtii to total available ammonium.

Drastic alterations in macronutrients are known to cause large changes in biochemistry and gene expression in the photosynthetic alga Chlamydomonas reinhardtii. However, metabolomic and proteomic responses to subtle reductions in macronutrients have not yet been studied. When ammonium levels were reduced by 25-100% compared with control cultures, ammonium uptake and growth rates were not affected at 25% or 50% nitrogen-reduction for 28 h. However, primary metabolism and enzyme expression showed remarkable changes at acute conditions (4 h and 10 h after ammonium reduction) compared with chronic conditions (18 h and 28 h time points). Responses of 145 identified metabolites were quantified using gas chromatography-time of flight mass spectrometry; 495 proteins (including 187 enzymes) were monitored using liquid chromatography-ion trap mass spectrometry with label-free spectral counting. Stress response and carbon assimilation processes (Calvin cycle, acetate uptake and chlorophyll biosynthesis) were altered first, in addition to increase in enzyme contents for lipid biosynthesis and accumulation of short chain free fatty acids. Nitrogen/carbon balance metabolism was found changed only under chronic conditions, for example in the citric acid cycle and amino acid metabolism. Metabolism in Chlamydomonas readily responds to total available media nitrogen with temporal increases in short-chain free fatty acids and turnover of internal proteins, long before nitrogen resources are depleted.

Reconsidering repurposing: long-term metformin treatment impairs cognition in Alzheimer's model mice.

Metformin, a primary anti-diabetic medication, has been anticipated to provide benefits for Alzheimer's disease (AD), also known as "type 3 diabetes". Nevertheless, some studies have demonstrated that metformin may trigger AD pathology and even elevate AD risk in humans. Despite this, limited research has elucidated the behavioral outcomes of metformin treatment, which would hold significant translational value. Thus, we aimed to perform thorough behavioral research on the prolonged administration of metformin to mice: We administered metformin (300 mg/kg/day) to transgenic 3xTg-AD and non-transgenic (NT) C57BL/6 mice over 1 and 2 years, respectively, and evaluated their behaviors across multiple domains via touchscreen operant chambers, including motivation, attention, memory, visual discrimination, and cognitive flexibility. We found metformin enhanced attention, inhibitory control, and associative learning in younger NT mice (≤16 months). However, chronic treatment led to impairments in memory retention and discrimination learning at older age. Furthermore, metformin caused learning and memory impairment and increased levels of AMPKα1-subunit, ß-amyloid oligomers, plaques, phosphorylated tau, and GSK3ß expression in AD mice. No changes in potential confounding factors on cognition, including levels of motivation, locomotion, appetite, body weight, blood glucose, and serum vitamin B12, were observed in metformin-treated AD mice. We also identified an enhanced amyloidogenic pathway in db/db mice, as well as in Neuro2a-APP695 cells and a decrease in synaptic markers, such as PSD-95 and synaptophysin in primary neurons, upon metformin treatment. Our findings collectively suggest that the repurposing of metformin should be carefully reconsidered when this drug is used for individuals with AD.

Multistrain Probiotics Alleviate Diarrhea by Modulating Microbiome-Derived Metabolites and Serotonin Pathway.

Diarrhea, a common gastrointestinal symptom in health problems, is highly associated with gut dysbiosis. The purpose of this study is to demonstrate the effect of multistrain probiotics (Sensi-Biome) on diarrhea from the perspective of the microbiome-neuron axis. Sensi-Biome (Lactiplantibacillus plantarum, Bifidobacterium animalis subsp. lactis, Lactobacillus acidophilus, Streptococcus thermophilus, Bifidobacterium bifidum, and Lactococcus lactis) was administered in a 4% acetic acid-induced diarrhea rat model at concentrations of 1 × 108 (G1), 1 × 109 (G2), and 1 × 1010 CFU/0.5 mL (G3). Diarrhea-related parameters, inflammation-related cytokines, and stool microbiota analysis by 16S rRNA were evaluated. A targeted and untargeted metabolomics approach was used to analyze the cecum samples using liquid chromatography and orbitrap mass spectrometry. The stool moisture content (p < 0.001), intestinal movement rate (p < 0.05), and pH (p < 0.05) were significantly recovered in G3. Serotonin levels were decreased in the multistrain probiotics groups. The inflammatory cytokines, serotonin, and tryptophan hydroxylase expression were improved in the Sensi-Biome groups. At the phylum level, Sensi-Biome showed the highest relative abundance of Firmicutes. Short-chain fatty acids including butyrate, iso-butyrate, propionate, and iso-valeric acid were significantly modified in the Sensi-Biome groups. Equol and oleamide were significantly improved in the multistrain probiotics groups. In conclusion, Sensi-Biome effectively controls diarrhea by modulating metabolites and the serotonin pathway.

Gut microbiota-derived indole compounds attenuate metabolic dysfunction-associated steatotic liver disease by improving fat metabolism and inflammation.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common chronic liver disease, and its prevalence has increased worldwide in recent years. Additionally, there is a close relationship between MASLD and gut microbiota-derived metabolites. However, the mechanisms of MASLD and its metabolites are still unclear. We demonstrated decreased indole-3-propionic acid (IPA) and indole-3-acetic acid (IAA) in the feces of patients with hepatic steatosis compared to healthy controls. Here, IPA and IAA administration ameliorated hepatic steatosis and inflammation in an animal model of WD-induced MASLD by suppressing the NF-κB signaling pathway through a reduction in endotoxin levels and inactivation of macrophages. Bifidobacterium bifidum metabolizes tryptophan to produce IAA, and B. bifidum effectively prevents hepatic steatosis and inflammation through the production of IAA. Our study demonstrates that IPA and IAA derived from the gut microbiota have novel preventive or therapeutic potential for MASLD treatment.

CYP2J2 and CYP2C19 are the major enzymes responsible for metabolism of albendazole and fenbendazole in human liver microsomes and recombinant P450 assay systems.

Albendazole and fenbendazole are broad-spectrum anthelmintics that undergo extensive metabolism to form hydroxyl and sulfoxide metabolites. Although CYP3A and flavin-containing monooxygenase have been implicated in sulfoxide metabolite formation, the enzymes responsible for hydroxyl metabolite formation have not been identified. In this study, we used human liver microsomes and recombinant cytochrome P450s (P450s) to characterize the enzymes involved in the formation of hydroxyalbendazole and hydroxyfenbendazole from albendazole and fenbendazole, respectively. Of the 10 recombinant P450s, CYP2J2 and/or CYP2C19 was the predominant enzyme catalyzing the hydroxylation of albendazole and fenbendazole. Albendazole hydroxylation to hydroxyalbendazole is primarily mediated by CYP2J2 (0.34 µl/min/pmol P450, which is a rate 3.9- and 8.1-fold higher than the rates for CYP2C19 and CYP2E1, respectively), whereas CYP2C19 and CYP2J2 contributed to the formation of hydroxyfenbendazole from fenbendazole (2.68 and 1.94 µl/min/pmol P450 for CYP2C19 and CYP2J2, respectively, which are rates 11.7- and 8.4-fold higher than the rate for CYP2D6). Correlation analysis between the known P450 enzyme activities and the rate of hydroxyalbendazole and hydroxyfenbendazole formation in samples from 14 human liver microsomes showed that albendazole hydroxylation correlates with CYP2J2 activity and fenbendazole hydroxylation correlates with CYP2C19 and CYP2J2 activities. These findings were supported by a P450 isoform-selective inhibition study in human liver microsomes. In conclusion, our data for the first time suggest that albendazole hydroxylation is primarily catalyzed by CYP2J2, whereas fenbendazole hydroxylation is preferentially catalyzed by CYP2C19 and CYP2J2. The present data will be useful in understanding the pharmacokinetics and drug interactions of albendazole and fenbendazole in vivo.

Evaluation and optimization of metabolome sample preparation methods for Saccharomyces cerevisiae.

Metabolome sampling is one of the most important factors that determine the quality of metabolomics data. The main steps in metabolite sample preparation include quenching and metabolite extraction. Quenching with 60% (v/v) cold methanol at -40 °C has been most commonly used for Saccharomyces cerevisiae, and this method was recently modified as "leakage-free cold methanol quenching" using pure methanol at -40 °C. Boiling ethanol (75%, v/v) and cold pure methanol are the most widely used extraction solvents for S. cerevisiae. In the present study, metabolome sampling protocols, including the above methods, were evaluated by analyzing 110 identified intracellular metabolites of S. cerevisiae using gas chromatography/time-of-flight mass spectrometry. According to our results, fast filtration followed by washing with an appropriate volume of water can minimize the metabolite loss due to cell leakage as well as the contamination by extracellular metabolites. For metabolite extraction, acetonitrile/water mixture (1:1, v/v) at -20 °C was the most effective. These results imply that the systematic evaluation of existing methods and the development of customized methods for each microorganism are critical for metabolome sample preparation to facilitate the reliable and accurate analysis of metabolome.

Metabolome-Wide Reprogramming Modulated by Wnt/ß-Catenin Signaling Pathway.

A family of signal transduction pathways known as wingless type (Wnt) signaling pathways is essential to developmental processes like cell division and proliferation. Mutation in Wnt signaling results in a variety of diseases, including cancers of the breast, colon, and skin, metabolic disease, and neurodegenerative disease; thus, the Wnt signaling pathways have been attractive targets for disease treatment. However, the complicatedness and large involveness of the pathway often hampers pinpointing the specific targets of the metabolic process. In our current study, we investigated the differential metabolic regulation by the overexpression of the Wnt signaling pathway in a timely-resolved manner by applying high-throughput and un-targeted metabolite profiling. We have detected and annotated 321 metabolite peaks from a total of 36 human embryonic kidney (HEK) 293 cells using GC-TOF MS and LC-Orbitrap MS. The un-targeted metabolomic analysis identified the radical reprogramming of a range of central carbon/nitrogen metabolism pathways, including glycolysis, TCA cycle, and glutaminolysis, and fatty acid pathways. The investigation, combined with targeted mRNA profiles, elucidated an explicit understanding of activated fatty acid metabolism (ß-oxidation and biosynthesis). The findings proposed detailed mechanistic biochemical dynamics in response to Wnt-driven metabolic changes, which may help design precise therapeutic targets for Wnt-related diseases.

Integrated-Omics Study on the Transcriptomic and Metabolic Changes of Bacillus licheniformis, a Main Microorganism of Fermented Soybeans, According to Alkaline pH and Osmotic Stress.

Bacillus licheniformis has been widely utilized in the food industry as well as various agricultural industries. In particular, it is a main microorganism of fermented soybeans. In this study, the changes of the metabolome and transcriptome of B. licheniformis KACC15844, which had been isolated from fermented soybeans, were investigated depending on alkaline pH (BP) and a high salt concentration (BS) using an integrated-omics technology, focusing on leucine metabolism. Overall, carbohydrate (glycolysis, sugar transport, and overflow) and amino acid (proline, glycine betaine, and serine) metabolisms were strongly associated with BS, while fatty acid metabolism, malate utilization, and branched-chain amino acid-derived volatiles were closely related to BP, in both gene and metabolic expressions. In particular, in leucine metabolism, the formation of 3-methylbutanoic acid, which has strong cheesy odor notes, was markedly increased in BP compared to the other samples. This study provided information on how specific culture conditions can affect gene expressions and metabolite formations in B. licheniformis using an integrated-omics approach.

Integrative metabolomics of plasma and PBMCs identifies distinctive metabolic signatures in Behçet's disease.

BACKGROUND: Behçet's disease (BD) is a systemic inflammatory disease that involves various organs. The clinical manifestation-based diagnosis of BD is a time-consuming process, which makes it difficult to distinguish from patients with similar symptoms. Moreover, an authentic biomarker has not been developed for accurate diagnosis yet. Our current study investigated the unique metabolic signatures of BD and explored biomarkers for precise diagnosis based on an untargeted metabolomic approach. METHODS: Integrative metabolomic and lipidomic profiling was performed on plasma samples of BD patients (n = 40), healthy controls (HCs, n = 18), and disease controls (DCs, n = 17) using GC-TOF MS and LC-Orbitrap MS. Additionally, the lipid profiles of 66 peripheral blood mononuclear cells (PBMCs) were analyzed from 29 BD patients, 18 HCs, and 19 DCs. RESULTS: Plasma metabolic dysfunction in BD was determined in carbohydrate, hydroxy fatty acid, and polyunsaturated fatty acid metabolisms. A plasma biomarker panel with 13 compounds was constructed, which simultaneously distinguished BD from HC and DC (AUCs ranged from 0.810 to 0.966). Dysregulated PBMC metabolome was signatured by a significant elevation in lysophosphatidylcholines (LPCs) and ether-linked lysophosphatidylethanolamines (EtherLPEs). Ten PBMC-derived lipid composites showed good discrimination power (AUCs ranged from 0.900 to 0.973). Correlation analysis revealed a potential association between disease activity and the metabolites of plasma and PBMC, including sphingosine-1 phosphate and EtherLPE 18:2. CONCLUSIONS: We identified metabolic biomarkers from plasma PBMC, which selectively discriminated BD from healthy control and patients with similar symptoms (recurrent mouth ulcers with/without genital ulcers). The strong correlation was determined between the BD activity and the lipid molecules. These findings may lead to the development for diagnostic and prognostic biomarkers based on a better understanding of the BD pathomechanism.

Comparative Analysis of Volatile and Non-Volatile Metabolites Derived from Bacillus subtilis Strains Producing Different Levels of Biogenic Amines.

Biogenic amines (BAs), which are mainly generated by the microbial decarboxylation of amino acids, are important nitrogen compounds in fermented foods because of their toxicology. However, amino acids, the precursors of BAs, also play an important role in generating volatile and non-volatile metabolites, which are strongly associated with quality indicators for foods. Bacillus subtilis is one of dominant fermentative microorganism in various fermented foods and is well known as a BA-producing bacterium. In this study, B. subtilis strains which have different BAs-producing capacities, higher level of BAs production strain (BH) and lower level of BAs production strain (BL), were applied to compare the formations of volatile and non-volatile metabolite profiles according to cultivation times. In this study, histamine, putrescine, and spermidine were detected in all strains, however, 2-phenylethylamine was detected only in BH. Partial least squares discriminant analysis (PLS-DA) was applied to investigate the difference of metabolic profiles according to strains. In BH, some amino acids (phenylalanine, leucine, and threonine) and related volatile metabolites (3-methylbutanoic acid, pyrazines, styrene, and 1H-indole) were produced higher levels. On the other hand, BL produced significantly higher contents of metabolites associated with metabolism of fatty acids and nucleotides. It is necessary to consider the formation of metabolites in terms of quality as well as that of BAs during fermentation.

Comprehensive Evaluation System for Post-Metabolic Activity of Potential Thyroid-Disrupting Chemicals.

Endocrine-disrupting chemicals (EDCs) are compounds that disturb hormonal homeostasis by binding to receptors. EDCs are metabolized through hepatic enzymes, causing altered transcriptional activities of hormone receptors, and thus necessitating the exploration of the potential endocrine-disrupting activities of EDC-derived metabolites. Accordingly, we have developed an integrative workflow for evaluating the post-metabolic activity of potential hazardous compounds. The system facilitates the identification of metabolites that exert hormonal disruption through the integrative application of an MS/MS similarity network and predictive biotransformation based on known hepatic enzymatic reactions. As proof-of-concept, the transcriptional activities of 13 chemicals were evaluated by applying the in vitro metabolic module (S9 fraction). Identified among the tested chemicals were three thyroid hormone receptor (THR) agonistic compounds that showed increased transcriptional activities after phase I+II reactions (T3, 309.1 ± 17.3%; DITPA, 30.7 ± 1.8%; GC-1, 160.6 ± 8.6% to the corresponding parents). The metabolic profiles of these three compounds showed common biotransformation patterns, particularly in the phase II reactions (glucuronide conjugation, sulfation, GSH conjugation, and amino acid conjugation). Data-dependent exploration based on molecular network analysis of T3 profiles revealed that lipids and lipid-like molecules were the most enriched biotransformants. The subsequent subnetwork analysis proposed 14 additional features, including T4 in addition to 9 metabolized compounds that were annotated by prediction system based on possible hepatic enzymatic reaction. The other 10 THR agonistic negative compounds showed unique biotransformation patterns according to structural commonality, which corresponded to previous in vivo studies. Our evaluation system demonstrated highly predictive and accurate performance in determining the potential thyroid-disrupting activity of EDC-derived metabolites and for proposing novel biotransformants.