PubMed

Sci Total Environ. 2023 Sep 18:167129. doi: 10.1016/j.scitotenv.2023.167129. Online ahead of print.ABSTRACTAs pollution has attracted attention due to its wide distribution. An environmental concern that may be overlooked is that NPs additives are easily released into the environment due to their physical combination with NPs. However, the knowledge gaps still exist about the interfacial reactions of NPs and the additives (e.g. flame retardants) and the joint ecological effect. In the present study, fourier transform infrared (FTIR) spectrometer coupled with 2D correlation spectroscopy (2D-COS) analysis revealed the interfacial reactions between polystyrene nanoplastics (PSNPs) and Dechlorane Plus (DP). Results showed that carbon‑oxygen bonds and carbon‑chlorine bonds were the important binding sites during adhesion and DP could reduce the colloidal stability. Single and joint ecological effects of PSNPs and DP on the microalgae Chlorella vulgaris were further deliberated. Reduced photosynthetic efficiency (reduced Fv/Fm by 0.03 %), higher growth inhibition (16.15 %) and oxidative damage (increased ROS by 152 %) were observed in algae under co-exposure. Notably, DP could significantly increase the attachment of PSNPs to the surface of the algae. Metabolomics further revealed that co-exposure significantly down-regulated amino acid metabolism and tricarboxylic acid cycle (TCA) cycle, and up-regulated fatty acid metabolism. The present study provides new insights into the risk assessment of NPs in aquatic environment by investigating the interfacial reaction mechanism and combined ecotoxicity of NPs and additives.PMID:37730039 | DOI:10.1016/j.scitotenv.2023.167129

J Ethnopharmacol. 2023 Sep 18:117156. doi: 10.1016/j.jep.2023.117156. Online ahead of print.ABSTRACTETHNOPHARMACOLOGICAL RELEVANCE: Fungal pathogens can cause deadly invasive infections and have become a major global public health challenge. There is an urgent need to find new treatment options beyond established antifungal agents, as well as new drug targets that can be used to develop novel antifungal agents. Cinnamomum cassia is a tropical aromatic plant that has a wide range of applications in traditional Chinese medicine, especially in the treatment of bacterial and fungal infections.AIM OF THE STUDY: The present study aimed to explore the mechanism of action and functional components of Cinnamomum cassia essential oil (CEO) against Candida albicans using an integrated strategy combining network-based metabolomics and pharmacology, the greedy algorithm and molecular docking.MATERIALS AND METHODS: CEO was extracted using hydrodistillation and its chemical composition was identified by GC-MS. Cluster analysis was performed on the compositions of 19 other CEOs from the published literature, as well as the sample obtained in this study. The damages of C. albicans cells upon treatment with CEO was observed using a scanning electron microscope. The mechanisms of its antifungal effect at a subinhibitory concentration of 0.1 × MIC were determined using microbial metabolomics and network analysis. The functional components were studied using the greedy algorithm and molecular docking.RESULTS: A total of 69 compounds were identified in the chemical analysis of CEO, which accounted for 90% of the sample. The major compounds were terpenoids (34.04%), aromatic compounds (4.52%), aliphatic compounds (0.9%), and others. Hierarchical cluster analysis of the compositions of 20 essential oils extracted from Cinnamomum cassia grown in different geographical locations showed a wide diversity of chemical composition with four major chemotypes. CEO showed strong antifungal activity and caused destruction of cell membranes in a concentration-dependent way. Metabolic fingerprint analysis identified 29 metabolites associated with lipid metabolism, which were mapped to 23 core targets mainly involved in fatty acid biosynthesis and metabolism. Six antifungal functional components of CEO were identified through network construction, greedy algorithm and molecular docking, including trans-cinnamaldehyde, δ-cadinol, ethylcinnamate, safrole, trans-anethole, and trans-cinnamyl acetate, which showed excellent binding with specific targets of AKR1B1, PPARG, BCHE, CYP19A1, CYP2C19, QPCT, and CYP51A1.CONCLUSION: s: This study provides a systematic understanding of the antifungal activity of CEO and offers an integrated strategy for deciphering the potential metabolism and material foundation of complex component drugs.PMID:37729978 | DOI:10.1016/j.jep.2023.117156

Pharmacol Res. 2023 Sep 18:106933. doi: 10.1016/j.phrs.2023.106933. Online ahead of print.ABSTRACTBoth environmental and genetic factors contribute to the etiology of autoimmune thyroid disease (AITD) including Graves' disease (GD) and Hashimoto's thyroiditis (HT). However, the exact pathogenesis and interactions that occur between environmental factors and genes remain unclear, and therapeutic targets require further investigation due to limited therapeutic options. To solve such problems, this study utilized single-cell transcriptome, whole transcriptome, full-length transcriptome (Oxford nanopore technology), and metabolome sequencing to examine thyroid lesion tissues from 2 HT patients and 2 GD patients as well as healthy thyroid tissue from 1 control subject. HT patients had increased ATF4-positive thyroid follicular epithelial (ThyFoEp) cells, which significantly increased endoplasmic reticulum stress. The enhanced sustained stress resulted in cell death mainly including apoptosis and necroptosis. The ATF4-based global gene regulatory network and experimental validation revealed that N6-methyladenosine (m6A) reader hnRNPC promoted the transcriptional activity, synthesis, and translation of ATF4 through mediating m6A modification of ATF4. Increased ATF4 expression initiated endoplasmic reticulum stress signaling, which when sustained, caused apoptosis and necroptosis in ThyFoEp cells, and mediated HT development. Targeting hnRNPC and ATF4 notably decreased ThyFoEp cell death, thus ameliorating disease progression. Collectively, this study reveals the mechanisms by which microenvironmental cells in HT and GD patients trigger and amplify the thyroid autoimmune cascade response. Furthermore, we identify new therapeutic targets for the treatment of autoimmune thyroid disease, hoping to provide a potential way for targeted therapy.PMID:37729957 | DOI:10.1016/j.phrs.2023.106933

Cell Rep Med. 2023 Sep 19;4(9):101011. doi: 10.1016/j.xcrm.2023.101011.ABSTRACTRisk prediction tools for pancreatic cancer are urgently sought to facilitate screening. Irajizad et al.1 describe the performance of a risk predication model based on circulating microbial- and non-microbial metabolites for assessment of 5-year pancreatic cancer risk.PMID:37729875 | DOI:10.1016/j.xcrm.2023.101011

Cell Rep Med. 2023 Sep 19;4(9):101194. doi: 10.1016/j.xcrm.2023.101194.ABSTRACTEmerging evidence implicates microbiome involvement in the development of pancreatic cancer (PaCa). Here, we investigate whether increases in circulating microbial-related metabolites associate with PaCa risk by applying metabolomics profiling to 172 sera collected within 5 years prior to PaCa diagnosis and 863 matched non-subject sera from participants in the Prostate, Lung, Colorectal, and Ovarian (PLCO) cohort. We develop a three-marker microbial-related metabolite panel to assess 5-year risk of PaCa. The addition of five non-microbial metabolites further improves 5-year risk prediction of PaCa. The combined metabolite panel complements CA19-9, and individuals with a combined metabolite panel + CA19-9 score in the top 2.5th percentile have absolute 5-year risk estimates of >13%. The risk prediction model based on circulating microbial and non-microbial metabolites provides a potential tool to identify individuals at high risk of PaCa that would benefit from surveillance and/or from potential cancer interception strategies.PMID:37729870 | DOI:10.1016/j.xcrm.2023.101194

Plant Physiol Biochem. 2023 Sep 13;203:108035. doi: 10.1016/j.plaphy.2023.108035. Online ahead of print.ABSTRACTCoumarin is an allelochemical that is widely present in the plant kingdom and has great potential for weed control. However, its mechanisms of action remain largely unknown. This study employed metabolomic and transcriptomic analyses along with evaluations of amino acid profiles and related physiological indicators to investigate how coumarin inhibits the germination and seedling growth of Eleusine indica by modifying metabolic pathways. At 72 h of germination at 50 and 100 mg L-1 coumarin, E. indica had lower levels of soluble sugar and activities of amylases and higher levels of starch, O2-, H2O2, auxin (IAA) and abscisic acid (ABA) compared to the control. Metabolomic analysis demonstrated that coumarin treatments had a significant impact on the pathways associated with amino acid metabolism and transport and aminoacyl-tRNA biosynthesis. Exposure to coumarin induced significant alterations in the levels of 19 amino acids, with a decrease in 15 of them, including Met, Leu and γ-aminobutyric acid (GABA). Additionally, transcriptomic analysis showed that coumarin significantly disrupted several essential biological processes, including protein translation, secondary metabolite synthesis, and hormone signal transduction. The decrease in TCA cycle metabolite (cis-aconitate, 2-oxoglutarate, and malate) contents was associated with the suppression of transcription for related enzymes. Our findings indicate that the inhibition of germination and growth in E. indica by coumarin involves the suppression of starch conversion to sugars, modification of the amino acid profile, interference of hormone signalling and the induction of oxidative stress. The TCA cycle appears to be one of the most essential pathways affected by coumarin.PMID:37729857 | DOI:10.1016/j.plaphy.2023.108035

J Therm Biol. 2023 Sep 4;117:103702. doi: 10.1016/j.jtherbio.2023.103702. Online ahead of print.ABSTRACTMarine heatwaves (MHW) are projected for the foreseeable future, affecting aquaculture species, such as the New Zealand green-lipped mussel (Perna canaliculus). Thermal stress alters mussel physiology highlighting the adaptive capacity that allows survival in the face of heatwaves. Within this study, adult mussels were subjected to three different seawater temperature regimes: 1) low (sustained 18 °C), 2) medium MHW (18-24 °C, using a +1 °C per week ramp) and 3) high MHW (18-24 °C, using a +2 °C per week ramp). Sampling was performed over 11 weeks to establish the effects of temperature on P. canaliculus survival, condition, specific immune response parameters, and the haemolymph metabolome. A transient 25.5-26.5 °C exposure resulted in 61 % mortality, with surviving animals showing a metabolic adjustment within aerobic energy production, enabling the activation of molecular defence mechanisms. Utilisation of immune functions were seen within the cytology results where temperature stress affected the percentage of superoxide-positive haemocytes and haemocyte counts. From the metabolomics results an increase in antioxidant metabolites were seen in the high MHW survivors, possibly to counteract molecular damage. In the high MHW exposure group, mussels utilised anaerobic metabolism in conjunction with aerobic metabolism to produce energy, to uphold biological functions and survival. The effect of exposure time was mainly seen on very long-, and long chain fatty acids, with increases observed at weeks seven and eight. These changes were likely due to the membrane storage functions of fatty acids, with decreases at week eleven attributed to energy metabolism functions. This study supports the use of integrated analytical tools to investigate the response of marine organisms to heatwaves. Indeed, specific metabolic pathways and cellular markers are now highlighted for future investigations aimed at targeted measures. This research contributes to a larger program aimed to identify resilient mussel traits and support aquaculture management.PMID:37729747 | DOI:10.1016/j.jtherbio.2023.103702

J Hazard Mater. 2023 Sep 14;461:132550. doi: 10.1016/j.jhazmat.2023.132550. Online ahead of print.ABSTRACTControversial results are reported whereby biodegradation of polycyclic aromatic hydrocarbons (PAHs) can be promoted or inhibited by biochar amendment of soil. Metabolomics was applied to analyze the metabolic profiles of amendment with biochar (BB) and biochar inoculated with functional bacteria (Pseudomonas putida) (BP) involved in phenanthrene (PHE) degradation. Additionally, metagenomic analysis was utilized to assess the impact of different treatments on PHE degradation by soil microorganisms. Results indicated that BB treatment decreased the PHE biodegradation of the soil indigenous bacterial consortium, but BP treatment alleviated this inhibitory effect. Metabolomics revealed the differential metabolite 9-phenanthrol was absent in the BB treatment, but was found in the control group (CK), and in the treatment inoculated with the Pseudomonas putida (Ps) and the BP treatment. Metagenomic analysis showed that biochar decreased the abundance of the cytochrome P450 monooxygenase (CYP116), which was detected in the Pseudomonas putida, thus alleviating the inhibitory effect of biochar on PHE degradation. Moreover, a noticeable delayed increase of functional gene abundance and enzymes abundance in the BB treatment was observed in the PHE degradation pathway. Our findings elucidate the mechanism of inhibition with biochar amendment and the alleviating effect of biochar inoculated with degrading bacteria.PMID:37729712 | DOI:10.1016/j.jhazmat.2023.132550

J Environ Qual. 2023 Sep 20. doi: 10.1002/jeq2.20515. Online ahead of print.ABSTRACTSustainable manure management technologies are needed, and combining anaerobic digestion (AD) for energy generation and aerobic composting (AC) to stabilize digestate and remove emerging contaminants (ECs), including veterinary pharmaceuticals and steroid hormones, is promising. This study identified post AD, AC operating conditions that maximized degradation of study ECs, expected to be present in cattle manure digested using treated municipal wastewater as the water source. Study ECs included sulfamethoxazole (SMX), chlortetracycline (CTC), oxytetracycline (OTC), estrone (E1), and naproxen (NPX). Composting conditions were simulated in bench-scale reactors, with microorganisms from digestate produced in an AD system (25L scale), by varying temperatures, pH, and carbon source compositions (representing food waste/manure co-digestion with different residence times). Results indicate maximum SMX biodegradation happened at 35°C, pH 7, and with high levels of easily degradable carbon (≥99, 99, 98%), and maximum E1 biodegradation occurred at 35°C, and with low levels of easily degradable carbon (≥97, 99%). Abiotic degradation was responsible for nearly complete removal of tetracyclines under all conditions and for partial degradation of NPX (between 20-48%). Microorganisms originating from the AD system putatively capable of SMX and E1 biodegradation, or of contributing to biodegradation during the AC phase, were identified, including phylotypes previously shown to biodegrade SMX (Brevundimonas and Alcaligenes). This article is protected by copyright. All rights reserved.PMID:37729590 | DOI:10.1002/jeq2.20515

Chem Res Toxicol. 2023 Sep 20. doi: 10.1021/acs.chemrestox.3c00158. Online ahead of print.ABSTRACTEpidemiological studies aim to assess associations between diseases and risk factors. Such investigations involve a large sample size and require powerful analytical methods to measure the effects of risk factors, resulting in a long analysis time. In this study, chemical exposure markers were detected as the main variables strongly affecting two components coming from a principal component analysis (PCA) exploration of the metabolomic data generated from urinary samples collected on a cohort of about 500 individuals using direct introduction coupled with a Fourier-transform ion cyclotron resonance instrument. The assignment of their chemical identity was first achieved based on their isotopic fine structures detected at very high resolution (Rp > 900,000). Their identification as dimethylbiguanide and sotalol was obtained at level 1, thanks to the available authentic chemical standards, tandem mass spectrometry (MS/MS) experiments, and collision cross section measurements. Epidemiological data confirmed that the subjects discriminated by PCA had declared to be prescribed these drugs for either type II diabetes or cardiac arrhythmia. Concentrations of these drugs in urine samples of interest were also estimated by rapid quantification using an external standard calibration method, direct introduction, and MS/MS experiments. Regression analyses showed a good correlation between the estimated drug concentrations and the scores of individuals distributed on these specific PCs. The detection of these chemical exposure markers proved the potential of the proposed high-throughput approach without any prior drug exposure knowledge as a powerful emerging tool for rapid and large-scale phenotyping of subjects enrolled in epidemiological studies to rapidly characterize the chemical exposome and adherence to medical prescriptions.PMID:37729183 | DOI:10.1021/acs.chemrestox.3c00158

Int Urol Nephrol. 2023 Sep 20. doi: 10.1007/s11255-023-03779-8. Online ahead of print.ABSTRACTBACKGROUND: As chronic kidney disease (CKD) progresses, metabolites undergo diverse transformations. Nevertheless, the impact of these metabolic changes on the etiology, progression, and prognosis of CKD remains uncertain. Our objective is to conduct a metabolomics analysis to scrutinize metabolites and identify significant metabolic pathways implicated in CKD progression, thereby pinpointing potential therapeutic targets for CKD management.METHODS: We recruited 145 patients with CKD and determined their mGFR by measuring the plasma iohexol clearance, whereupon we partitioned them into four groups based on their mGFR values. Non-targeted metabolomics analysis was conducted using UPLC-MS/MS assays. Differential metabolites were identified via one-way ANOVA, PCA, PLS-DA, and OPLS-DA analyses employing the MetaboAnalyst 5.0 platform. Ultimately, we performed differential metabolite pathway enrichment analysis, using both the MetaboAnalyst 5.0 platform and the MBRole2.0 database.RESULTS: According to the findings of the MBRole2.0 and MetaboAnalyst 5.0 enrichment analysis, six amino acid metabolism pathways were discovered to have significant roles in the progression of CKD, with the glycine, serine, and threonine metabolism pathway being the most prominent. The latter enriched 14 differential metabolites, of which six decreased while two increased concomitantly with renal function deterioration.CONCLUSIONS: The metabolic analysis unveiled that glycine, serine, and threonine metabolism plays a pivotal role in the progression of CKD. Specifically, glycine was found to increase while serine decreased with the deterioration of CKD.PMID:37728808 | DOI:10.1007/s11255-023-03779-8

mBio. 2023 Sep 20:e0175823. doi: 10.1128/mbio.01758-23. Online ahead of print.ABSTRACTClimate change is causing an increase in drought in many soil ecosystems and a loss of soil organic carbon. Calcareous soils may partially mitigate these losses via carbon capture and storage. Here, we aimed to determine how irrigation-supplied soil moisture and perennial plants impact biotic and abiotic soil properties that underpin deep soil carbon chemistry in an unfertilized calcareous soil. Soil was sampled up to 1 m in depth from irrigated and planted field treatments and was analyzed using a suite of omics and chemical analyses. The soil microbial community composition was impacted more by irrigation and plant cover treatments than by soil depth. By contrast, metabolomes, lipidomes, and proteomes differed more with soil depth than treatments. Deep soil (>50 cm) had higher soil pH and calcium concentrations and higher levels of organic acids, bicarbonate, and triacylglycerides. By contrast, surface soil (0-5 cm) had higher concentrations of soil organic matter, organic carbon, oxidizable carbon, and total nitrogen. Surface soils also had higher amounts of sugars, sugar alcohols, phosphocholines, and proteins that reflect osmotic and oxidative stress responses. The lipidome was more responsive to perennial tall wheatgrass treatments compared to the metabolome or proteome, with a striking change in diacylglyceride composition. Permanganate oxidizable carbon was more consistently correlated to metabolites and proteins than soil organic and inorganic carbon and soil organic matter. This study reveals specific compounds that reflect differences in organic, inorganic, and oxidizable soil carbon fractions that are impacted by interactions between irrigation-supplied moisture and plant cover in calcareous soil profiles. IMPORTANCE Carbon is cycled through the air, plants, and belowground environment. Understanding soil carbon cycling in deep soil profiles will be important to mitigate climate change. Soil carbon cycling is impacted by water, plants, and soil microorganisms, in addition to soil mineralogy. Measuring biotic and abiotic soil properties provides a perspective of how soil microorganisms interact with the surrounding chemical environment. This study emphasizes the importance of considering biotic interactions with inorganic and oxidizable soil carbon in addition to total organic carbon in carbonate-containing soils for better informing soil carbon management decisions.PMID:37728606 | DOI:10.1128/mbio.01758-23

Pol J Vet Sci. 2023 Sep 20;26(3):511-520. doi: 10.24425/pjvs.2023.145053.ABSTRACTHome dental care is a key element of periodontal therapy in veterinary patients. Among many strategies of passive home dental care there is a supplementation of animal diet with seaweed Ascophyllum nodosum which have been shown to reduce both calculus and plaque accumulation after oral administration in both dogs and cats. Ascophyllum nodosum contains numerous biologically active ingredients, including micro-elements, vitamins, and several other compounds, however the exact mechanism of its beneficial action remains unclear. The very first metabolomic data suggest that it could change the composition of dog saliva. Several products containing Ascophyllum nodosum had been assessed clinically according to standards and requirements provided by the Veterinary Oral Health Council. The conducted clinical trials in dogs and cats revealed that Ascophyllum nodosum exerts the strongest preventive action as powder, followed by dental bites and dry pet food. The data concerning its curative action are limited to one study in cats in which no beneficial action has been observed. Based on available clinical data it is recommended to administer Ascophyllum nodosum to dogs and cats after oral cavity prophylactic procedure to reduce the recurrence of plaque and calculus formation.PMID:37727971 | DOI:10.24425/pjvs.2023.145053

Curr Res Food Sci. 2023 Sep 10;7:100590. doi: 10.1016/j.crfs.2023.100590. eCollection 2023.ABSTRACTChicken meat spoilage is a significant concern for food safety and quality, and this study aims to predict the spoilage point of chicken breast meat through various attributes and metabolites. Chicken meat was stored in anaerobic packaging at 4 °C for 13 days, and various meat quality attributes (pH, drip loss, color, volatile basic nitrogen [VBN], total aerobic bacteria [TAB], and metabolites) were examined. First, the spoiled point (VBN >20 mg/100 g and/or TAB >7 log CFU/g) of the chicken breast meat was determined. Using univariate and multivariate analyses, twenty-four candidate metabolites were identified. A receiver operating characteristic (ROC) analysis was used to validate the obtained binary logistic regression model using nine metabolites (proline, methionine, glutamate, threonine, acetate, uridine 5'-monophosphate, hypoxanthine, glycine, and glutamine). The results showed a high area under the ROC curve value (0.992). Thus, this study confirmed the predictability of spoilage points in chicken breast meat through these nine metabolites.PMID:37727874 | PMC:PMC10506101 | DOI:10.1016/j.crfs.2023.100590

ERJ Open Res. 2023 Sep 18;9(5):00206-2023. doi: 10.1183/23120541.00206-2023. eCollection 2023 Sep.ABSTRACTBACKGROUND: Although rapid screening for and diagnosis of coronavirus disease 2019 (COVID-19) are still urgently needed, most current testing methods are long, costly or poorly specific. The objective of the present study was to determine whether or not artificial-intelligence-enhanced real-time mass spectrometry breath analysis is a reliable, safe, rapid means of screening ambulatory patients for COVID-19.METHODS: In two prospective, open, interventional studies in a single university hospital, we used real-time, proton transfer reaction time-of-flight mass spectrometry to perform a metabolomic analysis of exhaled breath from adults requiring screening for COVID-19. Artificial intelligence and machine learning techniques were used to build mathematical models based on breath analysis data either alone or combined with patient metadata.RESULTS: We obtained breath samples from 173 participants, of whom 67 had proven COVID-19. After using machine learning algorithms to process breath analysis data and further enhancing the model using patient metadata, our method was able to differentiate between COVID-19-positive and -negative participants with a sensitivity of 98%, a specificity of 74%, a negative predictive value of 98%, a positive predictive value of 72% and an area under the receiver operating characteristic curve of 0.961. The predictive performance was similar for asymptomatic, weakly symptomatic and symptomatic participants and was not biased by COVID-19 vaccination status.CONCLUSIONS: Real-time, noninvasive, artificial-intelligence-enhanced mass spectrometry breath analysis might be a reliable, safe, rapid, cost-effective, high-throughput method for COVID-19 screening.PMID:37727677 | PMC:PMC10505950 | DOI:10.1183/23120541.00206-2023

Front Physiol. 2023 Sep 1;14:1252972. doi: 10.3389/fphys.2023.1252972. eCollection 2023.ABSTRACTInsulin affects metabolic processes in different organs, including the skin. The sebaceous gland (SG) is an important appendage in the skin, which responds to insulin-mediated signals, either directly or through the insulin growth factor 1 (IGF-1) axis. Insulin cues are differently translated into the activation of metabolic processes depending on several factors, including glucose levels, receptor sensitivity, and sebocyte differentiation. The effects of diet on both the physiological function and pathological conditions of the SG have been linked to pathways activated by insulin and IGF-1. Experimental evidence and theoretical speculations support the association of insulin resistance with acne vulgaris, which is a major disorder of the SG. In this review, we examined the effects of insulin on the SG function and their implications in the pathogenesis of acne.PMID:37727660 | PMC:PMC10505787 | DOI:10.3389/fphys.2023.1252972

Front Physiol. 2023 Sep 1;14:1207390. doi: 10.3389/fphys.2023.1207390. eCollection 2023.ABSTRACTObjective: This study aimed to investigate the plasma metabolic profile of patients with extracranial arteriovenous malformations (AVM). Method: Plasma samples were collected from 32 AVM patients and 30 healthy controls (HC). Ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) was employed to analyze the metabolic profiles of both groups. Metabolic pathway enrichment analysis was performed through Kyoto Encyclopedia of Genes and Genomes (KEGG) database and MetaboAnalyst. Additionally, machine learning algorithms such as Least Absolute Shrinkage and Selection Operator (LASSO) and random forest (RF) were conducted to screen characteristic metabolites. The effectiveness of the serum biomarkers for AVM was evaluated using a receiver-operating characteristics (ROC) curve. Result: In total, 184 differential metabolites were screened in this study, with 110 metabolites in positive ion mode and 74 metabolites in negative mode. Lipids and lipid-like molecules were the predominant metabolites detected in both positive and negative ion modes. Several significant metabolic pathways were enriched in AVMs, including lipid metabolism, amino acid metabolism, carbohydrate metabolism, and protein translation. Through machine learning algorithms, nine metabolites were identify as characteristic metabolites, including hydroxy-proline, L-2-Amino-4-methylenepentanedioic acid, piperettine, 20-hydroxy-PGF2a, 2,2,4,4-tetramethyl-6-(1-oxobutyl)-1,3,5-cyclohexanetrione, DL-tryptophan, 9-oxoODE, alpha-Linolenic acid, and dihydrojasmonic acid. Conclusion: Patients with extracranial AVMs exhibited significantly altered metabolic patterns compared to healthy controls, which could be identified using plasma metabolomics. These findings suggest that metabolomic profiling can aid in the understanding of AVM pathophysiology and potentially inform clinical diagnosis and treatment.PMID:37727659 | PMC:PMC10505742 | DOI:10.3389/fphys.2023.1207390

Front Nutr. 2023 Sep 1;10:1244692. doi: 10.3389/fnut.2023.1244692. eCollection 2023.ABSTRACTBACKGROUND: The Aronia melanocarpa fruit is emerging as a health food owing to its high polyphenolic content and associated antioxidant activity. Antioxidant-rich foods, such as Aronia fruit, may counter inflammatory stimuli and positively modulate the gut microbiome. However, a comprehensive study characterizing the impact of Aronia fruit supplementation has not been completed. Therefore, we completed analyses measuring the metabolic, microbial, and inflammatory effects of a diet supplemented with Aronia fruit juice.METHOD: Humanized mice were generated by colonizing gnotobiotic mice with microbiomes from human donors presenting disparate inflammation levels. Blood and fecal samples were collected throughout the course of an 8-week dietary intervention with either Aronia juice or a carbohydrate-matched beverage alone (2 weeks) or in combination with a high-fat diet to induce inflammation (6 weeks). Samples were analyzed using 16S rRNA gene sequencing (stool) and liquid chromatography-mass spectrometry (serum).RESULTS: We demonstrated transfer of microbiome composition and diversity and metabolic characteristics from humans with low and high inflammation levels to second-generation humanized mice. Aronia supplementation provided robust protection against high-fat diet induced metabolic and microbiome changes that were dependent in part on microbiome donor. Aronia induced increases in bacteria of the Eggerthellaceae genus (7-fold) which aligns with its known ability to metabolize (poly)phenols and in phosphatidylcholine metabolites which are consistent with improved gut barrier function. The gut microbiome from a low inflammation phenotype donor provided protection against high-fat diet induced loss of microbiome β-diversity and global metabolomic shifts compared to that from the high inflammation donor.CONCLUSION: These metabolic changes elucidate pathway-specific drivers of reduced inflammation stemming from both Aronia and the gut microbiota.PMID:37727634 | PMC:PMC10505616 | DOI:10.3389/fnut.2023.1244692

Arch Anim Nutr. 2023 Sep 19:1-19. doi: 10.1080/1745039X.2023.2247824. Online ahead of print.ABSTRACTSilage fermentation is a complicated biochemical process involving interactions between microbes and metabolites. However, the overall metabolome feature of ensiled forage and its response to lactic acid bacteria inoculation is poorly understood. Hence, in this study metabolome profiles of whole-plant corn silage inoculated with or without Lactiplantibacillus plantarum were characterised via solid-phase microextraction/gas chromatography/mass spectrometry (SPME-GC-MS), gas chromatography/time-of-flight mass spectrometry (GC-TOF-MS), and Liquid chromatography/Q Exactive HFX mass spectrometry (LC-QE-MS/MS) analysis. There were 2087 identified metabolites including 1143 reliably identified metabolites in fresh and ensiled whole-plant corn. After ensiling, the increased metabolites in whole-plant corn were mainly composed of organic acids, volatile organic compounds (VOC), benzene and substituted derivatives, carboxylic acids and derivatives, fatty acyls, flavonoids, indoles and derivatives, organooxygen compounds (including amines and amides), phenols, pyridines and derivatives, and steroids and steroid derivatives, which includes neurotransmitters and metabolites with aromatic, antioxidant, anti-inflammatory, and antimicrobial activities. Phenylacetaldehyde was the most abundant aromatic metabolite after ensiling. L-isoleucine and oxoproline were the major free amino acids in silage. Ensiling markedly increased the relative abundances of 3-phenyllactic acid, chrysoeriol, 6-O-acetylaustroinulin, acetylcholine, γ-aminobutyric acid, pyridoxine, and alpha-linoleic acid. Inoculation with L. plantarum remarkably changed silage VOC composition, and essential amino acids, 3-phenyllactic acid, and cinnamaldehyde compared with untreated silage. The present study does not only provide a deeper insight into metabolites of the ensiled whole-plant corn but also reveals metabolites with specific biological functions that could be much helpful in screening novel lactic acid bacteria to well ensile forages. Inoculation with L. plantarum significantly affects the metabolome in ensiled whole-plant corn.PMID:37726873 | DOI:10.1080/1745039X.2023.2247824

BMC Bioinformatics. 2023 Sep 19;24(1):348. doi: 10.1186/s12859-023-05485-9.ABSTRACTBACKGROUND: Plant secondary metabolites are highly valued for their applications in pharmaceuticals, nutrition, flavors, and aesthetics. It is of great importance to elucidate plant secondary metabolic pathways due to their crucial roles in biological processes during plant growth and development. However, understanding plant biosynthesis and degradation pathways remains a challenge due to the lack of sufficient information in current databases. To address this issue, we proposed a transfer learning approach using a pre-trained hybrid deep learning architecture that combines Graph Transformer and convolutional neural network (GTC) to predict plant metabolic pathways.RESULTS: GTC provides comprehensive molecular representation by extracting both structural features from the molecular graph and textual information from the SMILES string. GTC is pre-trained on the KEGG datasets to acquire general features, followed by fine-tuning on plant-derived datasets. Four metrics were chosen for model performance evaluation. The results show that GTC outperforms six other models, including three previously reported machine learning models, on the KEGG dataset. GTC yields an accuracy of 96.75%, precision of 85.14%, recall of 83.03%, and F1_score of 84.06%. Furthermore, an ablation study confirms the indispensability of all the components of the hybrid GTC model. Transfer learning is then employed to leverage the shared knowledge acquired from the KEGG metabolic pathways. As a result, the transferred GTC exhibits outstanding accuracy in predicting plant secondary metabolic pathways with an average accuracy of 98.30% in fivefold cross-validation and 97.82% on the final test. In addition, GTC is employed to classify natural products. It achieves a perfect accuracy score of 100.00% for alkaloids, while the lowest accuracy score of 98.42% for shikimates and phenylpropanoids.CONCLUSIONS: The proposed GTC effectively captures molecular features, and achieves high performance in classifying KEGG metabolic pathways and predicting plant secondary metabolic pathways via transfer learning. Furthermore, GTC demonstrates its generalization ability by accurately classifying natural products. A user-friendly executable program has been developed, which only requires the input of the SMILES string of the query compound in a graphical interface.PMID:37726702 | DOI:10.1186/s12859-023-05485-9