Metabolites最新文献

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Purpose: This study aimed to utilize genetically engineered Bacillus licheniformis for the production of ergothioneine (EGT). Given the value of EGT and the application of Bacillus licheniformis in enzyme preparation production, we cloned the key enzymes (EanA and EanB) from Chlorbium limicola. Through gene alignment, new ergothioneine synthase genes (EanAN and EanBN) were identified and then expressed in Bacillus licheniformis to construct strains. Additionally, we investigated the factors influencing the yield of EGT and made a comparison with Escherichia coli.

Methods: The relevant genes were cloned and transferred into Bacillus licheniformis. Fermentation experiments were conducted under different conditions for yield analysis, and the stability of this bacterium was also evaluated simultaneously.

Results: The constructed strains were capable of producing EGT. Specifically, the yield of the EanANBN strain reached (643.8 ± 135) mg/L, and its stability was suitable for continuous production.

Conclusions: Genetically engineered Bacillus licheniformis demonstrates potential in the industrial-scale production of EGT. Compared with Escherichia coli, it has advantages, thus opening up new possibilities for the application and market supply of EGT.

Background: Obstructive Sleep Apnea (OSA) is a prevalent sleep disorder characterized by intermittent upper airway obstruction, leading to significant health consequences. Traditional diagnostic methods, such as polysomnography, are time-consuming and resource-intensive. Objectives: This study explores the potential of proton-transfer-reaction mass spectrometry (PTR-MS) in identifying volatile organic compound (VOC) biomarkers for the non-invasive detection of OSA. Methods: Breath samples from 89 participants, including 49 OSA patients and 40 controls, were analyzed using PTR-MS. Significance analysis was performed between OSA patients and controls to identify potential biomarkers for OSA. To as-sess the differences in VOC concentrations between OSA patients and control subjects, the Wilcoxon rank-sum test was employed. partial least squares discriminant analysis (PLS-DA) analysis and heatmap plot was conducted to visualize the differentiation between OSA patients and control subjects based on their VOC profiles.In order to further investigate the correlation between identified biomarkers and the severity of OSA measured by Apnea-Hypopnea Index (AHI), regression analysis was conducted between biomarkers and AHI Index. Results: The results identified specific VOCs, including m045 (acetaldehyde), m095.950, and m097.071, which showed significant differences between OSA patients and controls. Advanced statistical analyses, including PLS-DA and correlation mapping, highlighted the robustness of these biomarkers, with m045 (acetaldehyde) specifically emerging as a potential biomarker associated with the AHI Index. Conclusions: This study underscores the potential of VOCs as biomarkers for identifying patients with severe AHI levels. The analysis of VOCs using PTR-MS presents a rapid, non-invasive, and cost-effective method that could be seamlessly integrated into clinical practice, allowing clinicians to better stratify patients based on their need for polysomnography and prioritize those requiring earlier testing. Future studies are necessary to validate these findings in larger cohorts and to explore the integration of PTR-MS with other diagnostic modalities for improved accuracy and clinical utility.

Charge-free gaseous molecules labeled with deuterium ²H (D) atoms elute earlier than their protium-analogs ¹H (H) from most stationary GC phases. This effect is known as the chromatographic H/D isotope effect (hdIE_C) and can be calculated by dividing the retention times (t_R) of the protiated (t_R(H) ) to those of the deuterated (t_R(D)) analytes: hdIE_C = t_R(H)/t_R(D). Analytes labeled with ¹³C, ¹⁵N or ¹⁸O have almost identical retention times and lack a chromatographic isotope effect. Derivatives of cis- and trans-analytes such as cis- and trans-fatty acids also differ in their retention times. Analytes that contain trans-C=C-double bonds elute earlier in gas chromatography-mass spectrometry (GC-MS) than their cis-C=C-double bonds containing congeners. The chromatographic cis/trans-effect (ctE_C) can be calculated by dividing the retention times of the cis- by those of the trans-analytes: ctE_C = t_R(c)/t_R(t). In the present work, the hdIE_C and ctE_C values of endogenous and exogenous substances were calculated from previously reported GC-MS analyses and found to range each between 1.0009 and 1.0400. The examination suggests that the H/D-isotope effects and the cis/trans-effects observed in GC-MS are based on differences in the inter-molecular interaction strengths of the analyte derivatives with the stationary phase of GC columns. The deuterium atoms, being larger than the H atoms of the analytes, attenuate the interaction of the skeleton of the molecules with the GC stationary phase. The angulation of trans-analytes decreases the interaction of the skeleton of the molecules with the GC stationary phase, as only parts of the molecules are close enough to the GC stationary phase to interact. Other chromatographic effects caused by hydrogen (H) and fluorine (F) atoms and by stereo-isomerism are considered to be based on a similar mechanism due to the different orientation of the side chains.

Background/Objectives: Respiratory viruses, including Influenza, RSV, and COVID-19, cause various respiratory infections. Distinguishing these viruses relies on diagnostic methods such as PCR testing. Challenges stem from overlapping symptoms and the emergence of new strains. Advanced diagnostics are crucial for accurate detection and effective management. This study leveraged nasopharyngeal metabolome data to predict respiratory virus scenarios including control vs. RSV, control vs. Influenza A, control vs. COVID-19, control vs. all respiratory viruses, and COVID-19 vs. Influenza A/RSV. Method: We proposed a stacking-based ensemble technique, integrating the top three best-performing ML models from the initial results to enhance prediction accuracy by leveraging the strengths of multiple base learners. Key techniques such as feature ranking, standard scaling, and SMOTE were used to address class imbalances, thus enhancing model robustness. SHAP analysis identified crucial metabolites influencing positive predictions, thereby providing valuable insights into diagnostic markers. Results: Our approach not only outperformed existing methods but also revealed top dominant features for predicting COVID-19, including Lysophosphatidylcholine acyl C18:2, Kynurenine, Phenylalanine, Valine, Tyrosine, and Aspartic Acid (Asp). Conclusions: This study demonstrates the effectiveness of leveraging nasopharyngeal metabolome data and stacking-based ensemble techniques for predicting respiratory virus scenarios. The proposed approach enhances prediction accuracy, provides insights into key diagnostic markers, and offers a robust framework for managing respiratory infections.

Cancer is one of the leading causes of death globally, and is ranked second in the United States. Early detection is crucial for more effective treatment and a higher chance of survival rates, reducing burdens on individuals and societies. Genitourinary cancers, in particular, face significant challenges in early detection. Finding new and cost-effective diagnostic methods is of clinical need. Metabolomic-based approaches, notably volatile organic compound (VOC) analysis, have shown promise in detecting cancer. VOCs are small organic metabolites involved in biological processes and disease development. They can be detected in urine, breath, and blood samples, making them potential candidates for sensitive and non-invasive alternatives for early cancer detection. However, developing robust VOC detection methods remains a hurdle. This review outlines the current landscape of major genitourinary cancers (kidney, prostate, bladder, and testicular), including epidemiology, risk factors, and current diagnostic tools. Furthermore, it explores the applications of using VOCs as cancer biomarkers, various analytical techniques, and comparisons of extraction and detection methods across different biospecimens. The potential use of VOCs in detection, monitoring disease progression, and treatment responses in the field of genitourinary oncology is examined.

Background/Objectives: Gardeniae Fructus (GF) has been widely used as both food and medicinal purposes for thousands of years, but their antioxidant properties and potential metabolite biomarkers remain unclear. Methods: The purposes of this study were to examine antioxidant activities of 21 GF varieties from different geographical origins in China and identify potential biomarkers of antioxidant properties using an untargeted LC-MS-based metabolomics approach. Results: The results demonstrate that metabolomics had the ability to trace the geographical origins of GF. We found that antioxidant activities varied with different varieties of GF, which was dependent on their chemical compositions. The key chemical categories were obtained as the primary contributors of the antioxidant activity, including prenol lipids, flavonoids, coumarins and derivatives, as well as steroids and steroid derivatives. In addition, adouetine Y, coagulin R 3-glucoside and epicatechin 3-glucoside were identified as potential biomarkers for the antioxidant activity of GF. Conclusions: Therefore, our study sheds light on the metabolic characteristics and biomarkers of the antioxidant properties of GF, contributing to the selection and cultivation of a high antioxidant variety.

Background: Alcoholic liver disease (ALD) is a significant global health concern, primarily resulting from chronic alcohol consumption, with oxidative stress as a key driver. The ethyl acetate extract of Cichorium glandulosum (CGE) exhibits antioxidant and hepatoprotective properties, but its detailed mechanism of action against ALD remains unclear. This study investigates the effects and mechanisms of CGE in alleviating alcohol-induced oxidative stress and liver injury.

Methods: Ultra-Performance Liquid Chromatography coupled with Quadrupole-Orbitrap Mass Spectrometry (UPLC-Q-Orbitrap-MS) was used to identify CGE components. A C57BL/6J mouse model of ALD was established via daily oral ethanol (56%) for six weeks, with CGE treatment at low (100 mg/kg) and high doses (200 mg/kg). Silibinin (100 mg/kg) served as a positive control. Liver function markers, oxidative stress indicators, and inflammatory markers were assessed. Transcriptomic and network pharmacology analyses identified key genes and pathways, validated by reverse transcription quantitative polymerase chain reaction (RT-qPCR) and Western blotting.

Results: UPLC-Q-Orbitrap-MS identified 81 CGE compounds, mainly including terpenoids, flavonoids, and phenylpropanoids. CGE significantly ameliorated liver injury by reducing alanine aminotransferase (ALT), aspartate aminotransferase (AST), and alkaline phosphatase (ALP) levels and enhancing antioxidative markers such as total antioxidant capacity (T-AOC) and total superoxide dismutase (T-SOD) while lowering hepatic malondialdehyde (MDA) levels. Inflammation was mitigated through reduced levels of Tumor Necrosis Factor Alpha (TNF-α), Interleukin-1 Beta (IL-1β), and C-X-C Motif Chemokine Ligand 10 (CXCL-10). Transcriptomic and network pharmacology analysis revealed seven key antioxidant-related genes, including HMOX1, RSAD2, BCL6, CDKN1A, THBD, SLC2A4, and TGFβ3, validated by RT-qPCR. CGE activated the P21/Nuclear Factor Erythroid 2-Related Factor 2 (Nrf2)/Heme Oxygenase-1 (HO-1) signaling axis, increasing P21, Nrf2, and HO-1 protein levels while suppressing Kelch-like ECH-associated Protein 1 (Keap1) expression.

Conclusions: CGE mitigates oxidative stress and liver injury by activating the P21/Nrf2/HO-1 pathway and regulating antioxidant genes. Its hepatoprotective effects and multi-target mechanisms highlight CGE's potential as a promising therapeutic candidate for ALD treatment.

Background/objectives: Hyperlipidemia is a serious risk factor for cardiovascular diseases and liver steatosis. In this work, we explored the effect of an herbal formula (CBF) containing immature Ceratonia siliqua pods and Ocimum basilicum extracts on lipid metabolism disorders and lipoprotein-rich plasma (LRP) oxidation in mice.

Methods: The phenolic composition was determined using HPLC-DAD analysis. The antioxidant activity was studied using various in vitro methods. Acute toxicity was evaluated in mice. Importantly, the effect of the CBF on lipid metabolism disorders was investigated in a high-fat diet (HFD) hyperlipidemia mouse model. An in silico study was carried out to predict underlying mechanisms.

Results: The HPLC analysis revealed gallic acid, cinnamic acid, and naringenin as major phenolics of the carob pod aqueous extract. Concerning the basil hydro-ethanolic extract, rosmarinic, chicoric, caftaric, and caffeic acids were the main phenolics. Accordingly, the CBF prevented LRP oxidation in a concentration-dependent manner. This formula is not toxic in mice (LD₅₀ > 2000 mg/kg body weight). Moreover, animals administered the CBF at 200 mg/kg/day presented a significant decline in their body weight gain, adipose tissue weight, plasma total cholesterol, low-density lipoprotein cholesterol (LDL-C) level, and glycaemia after 10 weeks' treatment. Accordingly, the CBF decreased the plasma atherogenic index and the LDL-C to HDL-C ratio and reduced the level of fats accumulated in the liver. The molecular docking study revealed that chicoric, rosmarinic, and caftaric acids, and naringenin bound particularly strongly to many proteins involved in the regulation of lipid and cholesterol metabolism. This includes the HMG-CoA reductase, PPARα/γ, PCSK9, Cyp7a1, and ATP-citrate lyase.

Conclusions: The CBF could be a good source of natural supplements, functional foods, and pharmaceuticals effective in managing hyperlipidemia and oxidative stress and preventing their related cardiovascular disorders.

Background: The frequent occurrence of extreme temperature events causes significant economic losses to the livestock industry. Therefore, delving into the differences in the physiological and molecular mechanisms of heat stress across different sheep breeds is crucial for developing effective management and breeding strategies.

Methods: This study explores the differences in heat tolerance mechanisms between Hu sheep and Xinggao sheep by comparing their growth performance under normal and heat stress conditions, as well as examining the differences in physiological, biochemical, and antioxidant indicators related to heat tolerance, serum metabolomics, and gut microbiomics in a heat stress environment.

Results: The results indicate that with changes in the temperature-humidity index (THI), Hu sheep exhibit superior stability in respiratory rate (RR) and rectal temperature (RT) fluctuations compared to Xinggao sheep. In terms of biochemical indicators and antioxidant capacity, the levels of creatinine (Cr) and superoxide dismutase (SOD) in Hu sheep serum are significantly higher than those in Xinggao sheep. In comparison, alkaline phosphatase (ALP) and malondialdehyde (MDA) levels are significantly lower. Metabolomic results showed that, compared to Hu sheep, Xinggao sheep exhibited higher cortisol (COR) and dopamine (DA) levels under heat stress conditions, a stronger lipid mobilization capacity, and elevated levels of tricarboxylic acid (TCA) cycle-related metabolites. Furthermore, gut microbiome analysis results indicate that Hu sheep demonstrate stronger cellulose degradation capabilities, as evidenced by significantly higher abundances of microorganisms such as Ruminococcus, Fibrobacter, and Bacteroidales_RF16_group, compared to Xinggao sheep.

Conclusions: In summary, Hu sheep exhibit stronger heat tolerance compared to Xinggao sheep. These findings provide an important theoretical basis for the breeding and selection of heat-tolerant meat sheep varieties and offer strong support for the region's livestock industry in addressing the challenges posed by global warming.