PubMed

Heliyon. 2023 Mar;9(3):e14161. doi: 10.1016/j.heliyon.2023.e14161. Epub 2023 Feb 28.ABSTRACTBACKGROUND: Since the state of alarm was declared due to the COVID-19 pandemic, hospitals have been the main ones in charge of registering the therapeutic follow-up of affected people. The analysis of these data has allowed those different biochemical markers have been identified as predictors of the severity of the disease, but most of the published studies tend to be eminently descriptive and do not propose a biochemical hypothesis to explain the alteration of the results they are showing. Our objective is to recognize the main metabolic processes that are occurring in COVID-19 patients, as well as the identification of clinical parameters that are decisive to predict the severity of the disease.METHODS: A multivariate analysis was carried out from the clinical parameters collected in the database of the HM hospitals in Madrid, to determine the most relevant variables to predict the severity of the disease. Chemometric methods allow these variables to be obtained by applying a classification strategy with PLS-LDA.FINDINGS AND INTERPRETATION: The variables that most contribute to separation are age in men and, in both sexes, the concentration of lactate dehydrogenase, urea and C-reactive protein.Oxygen deficiency in the tissues, due to the loss of functionality of the lungs, could be affecting the muscle tissue with special severity. Inflammation and tissue damage is related to increased LDH and CRP. The loss of muscle mass and the increase in the concentration of urea and LDH is explained by the adaptation of muscle metabolism to this oxygen deficiency.FUNDING: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profits sectors.PMID:36873473 | PMC:PMC9972677 | DOI:10.1016/j.heliyon.2023.e14161

Pulm Circ. 2023 Mar 1;13(1):e12205. doi: 10.1002/pul2.12205. eCollection 2023 Jan.ABSTRACTIn pulmonary artery hypertension (PAH), emerging evidence suggests that metabolic abnormalities may be contributing to cellular dysfunction in PAH. Metabolic abnormalities such as glycolytic shift have been observed intracellularly in several cell types in PAH, including microvacular endothelial cells (MVECs). Concurrently, metabolomics of human PAH samples has also revealed a variety of metabolic abnormalities; however the relationship between the intracellular metabolic abnormalities and the serum metabolome in PAH remains under investigation. In this study, we utilize the sugen/hypoxia (SuHx) rodent model of PAH to examine the RV, LV and MVEC intracellular metabolome (using targeted metabolomics) in normoxic and SuHx rats. We additionally validate key findings from our metabolomics experiments with data obtained from cell culture of normoxic and SuHx MVECs, as well as metabolomics of human serum samples from two different PAH patient cohorts. Taken together, our data, spanning rat serum, human serum and primary isolated rat MVECs reveal that: (1) key classes of amino acids (specifically, branched chain amino acids-BCAA) are lower in the pre-capillary (i.e., RV) serum of SuHx rats (and humans); (2) intracellular amino acid levels (in particular BCAAs) are increased in SuHx-MVECs; (3) there may be secretion rather than utilization of amino acids across the pulmonary microvasculature in PAH and (4) an oxidized glutathione gradient is present across the pulmonary vasculature, suggesting a novel fate for increased glutamine uptake (i.e., as a source of glutathione). in MVECs in PAH. In summary, these data reveal new insight into the shifts in amino acid metabolism occurring across the pulmonary circulation in PAH.PMID:36873460 | PMC:PMC9978170 | DOI:10.1002/pul2.12205

EClinicalMedicine. 2023 Apr;58:101884. doi: 10.1016/j.eclinm.2023.101884. Epub 2023 Feb 27.ABSTRACTBACKGROUND: We aimed to characterise the long-term health outcomes of survivors of severe acute respiratory syndrome (SARS) and determine their recovery status and possible immunological basis.METHODS: We performed a clinical observational study on 14 health workers who survived SARS coronavirus infection between Apr 20, 2003 and Jun 6, 2003 in Haihe Hospital (Tianjin, China). Eighteen years after discharge, SARS survivors were interviewed using questionnaires on symptoms and quality of life, and received physical examination, laboratory tests, pulmonary function tests, arterial blood gas analysis, and chest imaging. Plasma samples were collected for metabolomic, proteomic, and single-cell transcriptomic analyses. The health outcomes were compared 18 and 12 years after discharge. Control individuals were also health workers from the same hospital but did not infect with SARS coronavirus.FINDINGS: Fatigue was the most common symptom in SARS survivors 18 years after discharge, with osteoporosis and necrosis of the femoral head being the main sequelae. The respiratory function and hip function scores of the SARS survivors were significantly lower than those of the controls. Physical and social functioning at 18 years was improved compared to that after 12 years but still worse than the controls. Emotional and mental health were fully recovered. Lung lesions on CT scans remained consistent at 18 years, especially in the right upper lobe and left lower lobe lesions. Plasma multiomics analysis indicated an abnormal metabolism of amino acids and lipids, promoted host defense immune responses to bacteria and external stimuli, B-cell activation, and enhanced cytotoxicity of CD8+ T cells but impaired antigen presentation capacity of CD4+ T cells.INTERPRETATION: Although health outcomes continued to improve, our study suggested that SARS survivors still suffered from physical fatigue, osteoporosis, and necrosis of the femoral head 18 years after discharge, possibly related to plasma metabolic disorders and immunological alterations.FUNDING: This study was funded by the Tianjin Haihe Hospital Science and Technology Fund (HHYY-202012) and Tianjin Key Medical Discipline (Specialty) Construction Project (TJYXZDXK-063B, TJYXZDXK-067C).PMID:36873427 | PMC:PMC9969173 | DOI:10.1016/j.eclinm.2023.101884

Front Bioeng Biotechnol. 2023 Feb 17;11:1006246. doi: 10.3389/fbioe.2023.1006246. eCollection 2023.ABSTRACTBackground: With the development of chronic kidney disease (CKD), there are various changes in metabolites. However, the effect of these metabolites on the etiology, progression and prognosis of CKD remains unclear. Objective: We aimed to identify significant metabolic pathways in CKD progression by screening metabolites through metabolic profiling, thus identifying potential targets for CKD treatment. Methods: Clinical data were collected from 145 CKD participants. GFR (mGFR) was measured by the iohexol method and participants were divided into four groups according to their mGFR. Untargeted metabolomics analysis was performed via UPLC-MS/MSUPLC-MSMS/MS assays. Metabolomic data were analyzed by MetaboAnalyst 5.0, one-way ANOVA, principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA) to identify differential metabolites for further analysis. The open database sources of MBRole2.0, including KEGG and HMDB, were used to identify significant metabolic pathways in CKD progression. Results: Four metabolic pathways were classified as important in CKD progression, among which the most significant was caffeine metabolism. A total of 12 differential metabolites were enriched in caffeine metabolism, four of which decreased with the deterioration of the CKD stage, and two of which increased with the deterioration of the CKD stage. Of the four decreased metabolites, the most important was caffeine. Conclusion: Caffeine metabolism appears to be the most important pathway in the progression of CKD as identified by metabolic profiling. Caffeine is the most important metabolite that decreases with the deterioration of the CKD stage.PMID:36873366 | PMC:PMC9981652 | DOI:10.3389/fbioe.2023.1006246

Expo Health. 2023;15(1):33-51. doi: 10.1007/s12403-022-00470-8. Epub 2022 Mar 22.ABSTRACTMicro- and nanoplastics (MNPs) are recognized as emerging contaminants, especially in food, with unknown health significance. MNPs passing through the gastrointestinal tract have been brought in context with disruption of the gut microbiome. Several molecular mechanisms have been described to facilitate tissue uptake of MNPs, which then are involved in local inflammatory and immune responses. Furthermore, MNPs can act as potential transporters ("vectors") of contaminants and as chemosensitizers for toxic substances ("Trojan Horse effect"). In this review, we summarize current multidisciplinary knowledge of ingested MNPs and their potential adverse health effects. We discuss new insights into analytical and molecular modeling tools to help us better understand the local deposition and uptake of MNPs that might drive carcinogenic signaling. We present bioethical insights to basically re-consider the "culture of consumerism." Finally, we map out prominent research questions in accordance with the Sustainable Development Goals of the United Nations.PMID:36873245 | PMC:PMC9971145 | DOI:10.1007/s12403-022-00470-8

ACS Omega. 2023 Feb 16;8(8):7722-7737. doi: 10.1021/acsomega.2c06469. eCollection 2023 Feb 28.ABSTRACTChronic kidney disease (CKD) is the end point of a number of systemic chronic diseases. The prevalence of CKD is increasing worldwide and recent epidemiological studies are showing the high prevalence of renal failure in CKD patients using complementary and alternative medicines (CAMs). Clinicians believe that biochemical profiles of CKD patients using CAM (referred here to as CAM-CKD) may be different compared to those on standard clinical treatment and should be managed differently. The present study aims to explore the potential of the NMR-based metabolomics approach to reveal the serum metabolic disparity between CKD and CAM-CKD patients with respect to normal control (NC) subjects and if the differential metabolic patterns can provide rationale for the efficacy and safety of standard and/or alternative therapies. Serum samples were obtained from 30 CKD patients, 43 CAM-CKD patients, and 47 NC subjects. The quantitative serum metabolic profiles were measured using 1D 1H CPMG NMR experiments performed at 800 MHz NMR spectrometer. The serum metabolic profiles were compared using various multivariate statistical analysis tools available on MetaboAnalyst (freely available web-based software) such as partial least-squares discriminant analysis (PLS-DA) and random forest (a machine learning) classification method. The discriminatory metabolites were identified based on variable importance in projection (VIP) statistics and further evaluated for statistical significance (i.e., p < 0.05) using either Student t-test or ANOVA statistics. PLS-DA models were capable of clustering CKD and CAM-CKD with considerably high values of Q 2 and R 2. Compared to CAM-CKD patients, the sera of CKD patients were characterized by (a) elevated levels of urea, creatinine, citrate, glucose, glycerol, and phenylalanine and phenylalanine-to-tyrosine ratio (PTR) and (b) decreased levels of various amino acids (such leucine, isoleucine, valine, and alanine), high-density lipoproteins, lactate, and acetate. These changes suggested that CKD patients manifest severe oxidative stress, hyperglycemia (with dampened glycolysis), increased protein energy wasting, and reduced lipid/membrane metabolism. Statistically significant and strong positive correlation of PTR with serum creatinine levels suggested the role of oxidative stress in the progression of kidney disease. Significant differences in metabolic patterns between CKD and CAM-CKD patients were observed. With respect to NC subjects, the serum metabolic changes were more aberrant in CKD patients compared to CAM-CKD patients. The aberrant metabolic changes in CKD patients with manifestations of higher oxidative stress compared to CAM-CKD patients could explain clinical discrepancies between CKD and CAM-CKD patients and further advocate the use of different treatment strategies for CKD and CAM-CKD patients.PMID:36872986 | PMC:PMC9979328 | DOI:10.1021/acsomega.2c06469

J Mass Spectrom Adv Clin Lab. 2023 Feb 17;28:35-46. doi: 10.1016/j.jmsacl.2023.02.002. eCollection 2023 Apr.ABSTRACTThe emerging disciplines of lipidomics and metabolomics show great potential for the discovery of diagnostic biomarkers, but appropriate pre-analytical sample-handling procedures are critical because several analytes are prone to ex vivo distortions during sample collection. To test how the intermediate storage temperature and storage period of plasma samples from K3EDTA whole-blood collection tubes affect analyte concentrations, we assessed samples from non-fasting healthy volunteers (n = 9) for a broad spectrum of metabolites, including lipids and lipid mediators, using a well-established LC-MS-based platform. We used a fold change-based approach as a relative measure of analyte stability to evaluate 489 analytes, employing a combination of targeted LC-MS/MS and LC-HRMS screening. The concentrations of many analytes were found to be reliable, often justifying less strict sample handling; however, certain analytes were unstable, supporting the need for meticulous processing. We make four data-driven recommendations for sample-handling protocols with varying degrees of stringency, based on the maximum number of analytes and the feasibility of routine clinical implementation. These protocols also enable the simple evaluation of biomarker candidates based on their analyte-specific vulnerability to ex vivo distortions. In summary, pre-analytical sample handling has a major effect on the suitability of certain metabolites as biomarkers, including several lipids and lipid mediators. Our sample-handling recommendations will increase the reliability and quality of samples when such metabolites are necessary for routine clinical diagnosis.PMID:36872954 | PMC:PMC9975683 | DOI:10.1016/j.jmsacl.2023.02.002

J Mass Spectrom Adv Clin Lab. 2023 Feb 17;28:47-55. doi: 10.1016/j.jmsacl.2023.02.003. eCollection 2023 Apr.ABSTRACTMass spectrometry focusing on small endogenous molecules has become an integral part of biomarker discovery in the pursuit of an in-depth understanding of the pathophysiology of various diseases, ultimately enabling the application of personalized medicine. While LC-MS methods allow researchers to gather vast amounts of data from hundreds or thousands of samples, the successful execution of a study as part of clinical research also requires knowledge transfer with clinicians, involvement of data scientists, and interactions with various stakeholders. The initial planning phase of a clinical research project involves specifying the scope and design, and engaging relevant experts from different fields. Enrolling subjects and designing trials rely largely on the overall objective of the study and epidemiological considerations, while proper pre-analytical sample handling has immediate implications on the quality of analytical data. Subsequent LC-MS measurements may be conducted in a targeted, semi-targeted, or non-targeted manner, resulting in datasets of varying size and accuracy. Data processing further enhances the quality of data and is a prerequisite for in-silico analysis. Nowadays, the evaluation of such complex datasets relies on a mix of classical statistics and machine learning applications, in combination with other tools, such as pathway analysis and gene set enrichment. Finally, results must be validated before biomarkers can be used as prognostic or diagnostic decision-making tools. Throughout the study, quality control measures should be employed to enhance the reliability of data and increase confidence in the results. The aim of this graphical review is to provide an overview of the steps to be taken when conducting an LC-MS-based clinical research project to search for small molecule biomarkers.PMID:36872952 | PMC:PMC9982001 | DOI:10.1016/j.jmsacl.2023.02.003

Liver Cancer. 2022 Jul 8;12(1):19-31. doi: 10.1159/000525911. eCollection 2023 Feb.ABSTRACTINTRODUCTION: The burden of metabolic (dysfunction) associated fatty liver disease (MAFLD) is rising mirrored by an increase in hepatocellular cancer (HCC). MAFLD and its sequelae are characterized by perturbations in lipid handling, inflammation, and mitochondrial damage. The profile of circulating lipid and small molecule metabolites with the development of HCC is poorly characterized in MAFLD and could be used in future studies as a biomarker for HCC.METHODS: We assessed the profile of 273 lipid and small molecule metabolites by ultra-performance liquid chromatography coupled to high-resolution mass spectrometry in serum from patients with MAFLD (n = 113) and MAFLD-associated HCC (n = 144) from six different centers. Regression models were used to identify a predictive model of HCC.RESULTS: Twenty lipid species and one metabolite, reflecting changes in mitochondrial function and sphingolipid metabolism, were associated with the presence of cancer on a background of MAFLD with high accuracy (AUC 0.789, 95% CI: 0.721-0.858), which was enhanced with the addition of cirrhosis to the model (AUC 0.855, 95% CI: 0.793-0.917). In particular, the presence of these metabolites was associated with cirrhosis in the MAFLD subgroup (p < 0.001). When considering the HCC cohort alone, the metabolic signature was an independent predictor of overall survival (HR 1.42, 95% CI: 1.09-1.83, p < 0.01).CONCLUSION: These exploratory findings reveal a metabolic signature in serum which is capable of accurately detecting the presence of HCC on a background of MAFLD. This unique serum signature will be taken forward for further investigation of diagnostic performance as biomarker of early stage HCC in patients with MAFLD in the future.PMID:36872928 | PMC:PMC9982340 | DOI:10.1159/000525911

J Vet Pharmacol Ther. 2023 Mar 5. doi: 10.1111/jvp.13121. Online ahead of print.ABSTRACTCurrent treatment options for feline epilepsy are limited to medications that require administration of multiple doses per day or administration of a capsule or large tablet. Expanding the current treatment options could improve patient and owner compliance and optimize seizure control. Topiramate has been used sparingly in veterinary medicine, and limited pharmacokinetic studies have focused on immediate release formulations in dogs. If effective and safe, topiramate extended-release (XR) could broaden the current treatment options for feline epilepsy. The aims of this two-phase study were to establish single-dose pharmacokinetics for topiramate XR in cats, identify a dosing regimen that maintains steady-state plasma drug concentrations within a reference range extrapolated from human medicine (5-20 μg/mL), and evaluate the safety of topiramate XR in cats following multidose administration. Topiramate XR administered orally at 10 mg/kg once daily for 30 days was sufficient to achieve the desired concentrations in all cats. While no clinically apparent adverse effects were observed, four out of eight cats developed subclinical anemia, calling into question the safety of topiramate XR with chronic administration. Further studies are necessary to better understand the potential adverse effects and overall efficacy of topiramate XR for the treatment of feline epilepsy.PMID:36872425 | DOI:10.1111/jvp.13121

Obesity (Silver Spring). 2023 Mar 5. doi: 10.1002/oby.23687. Online ahead of print.ABSTRACTOBJECTIVE: Liver fat associates with obesity-related metabolic disturbances and may precede incident diseases. Metabolomic profiles of liver fat in the UK Biobank were investigated.METHODS: Regression models assessed the associations between 180 metabolites and proton density liver fat fraction (PDFF) measured 5 years later through magnetic resonance imaging, as the difference (in SD units) of each log metabolite measure with 1-SD higher PDFF among those without chronic disease and not taking statins, and by diabetes and cardiovascular diseases.RESULTS: After accounting for confounders, multiple metabolites were associated positively with liver fat (p < 0.0001 for 152 traits), particularly extremely large and very large lipoprotein particle concentrations, very low-density lipoprotein triglycerides, small high-density lipoprotein particles, glycoprotein acetyls, monounsaturated and saturated fatty acids, and amino acids. Extremely large and large high-density lipoprotein concentrations had strong inverse associations with liver fat. Associations were broadly comparable among those with versus without vascular metabolic conditions, although negative, rather than positive, associations were observed between intermediate-density and large low-density lipoprotein particles among those with BMI ≥25 kg/m2 , diabetes, or cardiovascular diseases. Metabolite principal components showed a 15% significant improvement in risk prediction for PDFF relative to BMI, which was twice as great (but nonsignificant) compared with conventional high-density lipoprotein cholesterol and triglycerides.CONCLUSIONS: Hazardous metabolomic profiles are associated with ectopic hepatic fat and are relevant to risk of vascular-metabolic disease.PMID:36872307 | DOI:10.1002/oby.23687

Zhongguo Zhong Yao Za Zhi. 2023 Feb;48(4):1043-1053. doi: 10.19540/j.cnki.cjcmm.20221024.401.ABSTRACTThis paper aimed to study the effect of Dalbergia cochinchinensis heartwood on plasma endogenous metabolites in rats with ligation of the left anterior descending coronary artery, and to analyze the mechanism of D. cochinchinensis heartwood in improving acute myocardial ischemic injury. The stability and consistency of the components in the D. cochinchinensis heartwood were verified by the establishment of fingerprint, and 30 male SD rats were randomly divided into a sham group, a model group, and a D. cochinchinensis heartwood(6 g·kg~(-1)) group, with 10 rats in each group. The sham group only opened the chest without ligation, while the other groups established the model of ligation. Ten days after administration, the hearts were taken for hematoxylin-eosin(HE) staining, and the content of heart injury indexes in the plasma creatine kinase isoenzyme(CK-MB) and lactate dehydrogenase(LDH), energy metabolism-related index glucose(Glu) content, and vascular endothelial function index nitric oxide(NO) was determined. The endogenous metabolites were detected by ultra-high-performance liquid chromatography-time-of-flight-mass spectrometry(UPLC-Q-TOF-MS). The results showed that the D. cochinchinensis heartwood reduced the content of CK-MB and LDH in the plasma of rats to relieve myocardial injury, reduced the content of Glu in the plasma, improved myocardial energy metabolism, increased the content of NO, cured the vascular endothelial injury, and promoted vasodilation. D. cochinchinensis heartwood improved the increase of intercellular space, myocardial inflammatory cell infiltration, and myofilament rupture caused by ligation of the left anterior descending coronary artery. The metabolomic study showed that the content of 26 metabolites in the plasma of rats in the model group increased significantly, while the content of 27 metabolites decreased significantly. Twenty metabolites were significantly adjusted after the administration of D. cochinchinensis heartwood. D. cochinchinensis heartwood can significantly adjust the metabolic abnormality in rats with ligation of the left anterior descending coronary artery, and its mechanism may be related to the regulation of cardiac energy metabolism, NO production, and inflammation. The results provide a corresponding basis for further explaining the effect of D. cochinchinensis on the acute myocardial injury.PMID:36872275 | DOI:10.19540/j.cnki.cjcmm.20221024.401

Zhongguo Zhong Yao Za Zhi. 2023 Feb;48(3):811-822. doi: 10.19540/j.cnki.cjcmm.20220830.502.ABSTRACTChildren's fever is often accompanied by food accumulation. Traditional Chinese medicine believes that removing food stagnation while clearing heat of children can effectively avoid heat damage. To systematically evaluate the efficacy of Xiaoer Chiqiao Qingre Granules(XRCQ) in clearing heat and removing food accumulation and explore its potential mechanism, this study combined suckling SD rats fed with high-sugar and high-fat diet with injection of carrageenan to induce rat model of fever and food accumulation. This study provided references for the study on the pharmacodynamics and mechanism of XRCQ. The results showed that XRCQ effectively reduced the rectal temperature of suckling rats, improved the inflammatory environment such as the content of interleukin-1β(IL-1β), interleukin-2(IL-2), interferon-γ(IFN-γ), white blood cells, and monocytes. XRCQ also effectively repaired intestinal injury and enhanced intestinal propulsion function. According to the confirmation of its efficacy of clearing heat, the thermolytic mechanism of XRCQ was further explored by non-targeted and targeted metabolomics methods based on LTQ-Orbitrap MS/MS and UPLC-QQQ-MS/MS. Non-target metabolomics analysis of brain tissue samples was performed by QI software combined with SIMCA-P software, and 22 endogenous metabolites that could be significantly regulated were screened out. MetaboAnalyst pathway enrichment results showed that the intervention mechanism was mainly focused on tyrosine metabolism, tricarboxylic acid cycle, inositol phosphate metabolism, and other pathways. At the same time, the results of targeted metabolomics of brain tissue samples showed that XRCQ changed the vitality of digestive system, and inhibited abnormal energy metabolism and inflammatory response, playing a role in clearing heat and removing food stagnation from multiple levels.PMID:36872245 | DOI:10.19540/j.cnki.cjcmm.20220830.502

Food Chem. 2023 Mar 3;416:135795. doi: 10.1016/j.foodchem.2023.135795. Online ahead of print.ABSTRACTTo investigate the effects of "golden flora" amount on the sensory quality, metabolites and bioactivities of Fu brick tea (FBT), FBT samples with different "golden flora" amounts were prepared from the same materials by adjusting the water content before pressing. With the increase of "golden flora" in samples, the tea liquor color changed from yellow to orange red and the astringent taste gradually diminished. Targeted analysis demonstrated that (-)-epigallocatechin gallate, (-)-epicatechin gallate, and most amino acids gradually decreased as the increase of "golden flora". Seventy differential metabolites were identified by untargeted analysis. Among them, sixteen compounds including two Fuzhuanins and four EPSFs were positively correlated with "golden flora" amount (P < 0.05). The FBT samples with "golden flora" exhibited significantly higher inhibitory potency on α-amylase and lipase than the samples without "golden flora". Our results provide a theoretical basis of guiding FBT processing based on desired sensory quality and metabolites.PMID:36871505 | DOI:10.1016/j.foodchem.2023.135795

J Pharm Biomed Anal. 2023 Mar 1;228:115320. doi: 10.1016/j.jpba.2023.115320. Online ahead of print.ABSTRACTA new approach is developed for the reliable classification of Calculus bovis along with the identification of willfully contaminated C. bovis species and the quantification of unclaimed adulterants. Guided by a principal component analysis, NMR data mining achieved a near-holistic chemical characterization of three types of authenticated C. bovis, including natural C. bovis (NCB), in vitro cultured C. bovis (Ivt-CCB), and artificial C. bovis (ACB). In addition, species-specific markers used for quality evaluation and species classification were confirmed. That is, the content of taurine in NCB is near negligible, while choline and hyodeoxycholic acid are characteristic for identifying Ivt-CCB and ACB, respectively. Besides, the peak shapes and chemical shifts of H2-25 of glycocholic acid could assist in the recognition of the origins of C. bovis. Based on these discoveries, a set of commercial NCB samples, macroscopically identified as problematic species, was examined with deliberately added sugars and outliers discovered. Absolute quantification of the identified sugars was realized by qHNMR using a single, nonidentical internal calibrant (IC). This study represents the first systematic study of C. bovis metabolomics via an NMR-driven methodology, which advances the toolbox for quality control of TCM and provides a more definitive reference point for future chemical and biological studies of C. bovis as a valuable materia medica.PMID:36871364 | DOI:10.1016/j.jpba.2023.115320

ACS Nano. 2023 Mar 5. doi: 10.1021/acsnano.2c11790. Online ahead of print.ABSTRACTCrop disease represents a serious and increasing threat to global food security. Lanthanum oxide nanomaterials (La2O3 NMs) with different sizes (10 and 20 nm) and surface modifications (citrate, polyvinylpyrrolidone [PVP], and poly(ethylene glycol)) were investigated for their control of the fungal pathogen Fusarium oxysporum (Schl.) f. sp cucumerinum Owen on six-week-old cucumber (Cucumis sativus) in soil. Seed treatment and foliar application of the La2O3 NMs at 20-200 mg/kg (mg/L) significantly suppressed cucumber wilt (decreased by 12.50-52.11%), although the disease control efficacy was concentration-, size-, and surface modification-dependent. The best pathogen control was achieved by foliar application of 200 mg/L PVP-coated La2O3 NMs (10 nm); disease severity was decreased by 67.6%, and fresh shoot biomass was increased by 49.9% as compared with pathogen-infected control. Importantly, disease control efficacy was 1.97- and 3.61-fold greater than that of La2O3 bulk particles and a commercial fungicide (Hymexazol), respectively. Additionally, La2O3 NMs application enhanced cucumber yield by 350-461%, increased fruit total amino acids by 295-344%, and improved fruit vitamin content by 65-169% as compared with infected controls. Transcriptomic and metabolomic analyses revealed that La2O3 NMs: (1) interacted with calmodulin, subsequently activating salicylic acid-dependent systemic acquired resistance; (2) increased the activity and expression of antioxidant and related genes, thereby alleviating pathogen-induced oxidative stress; and (3) directly inhibited in vivo pathogen growth. The findings highlight the significant potential of La2O3 NMs for suppressing plant disease in sustainable agriculture.PMID:36871293 | DOI:10.1021/acsnano.2c11790

J Cheminform. 2023 Mar 4;15(1):32. doi: 10.1186/s13321-023-00695-y.ABSTRACTMapping the chemical space of compounds to chemical structures remains a challenge in metabolomics. Despite the advancements in untargeted liquid chromatography-mass spectrometry (LC-MS) to achieve a high-throughput profile of metabolites from complex biological resources, only a small fraction of these metabolites can be annotated with confidence. Many novel computational methods and tools have been developed to enable chemical structure annotation to known and unknown compounds such as in silico generated spectra and molecular networking. Here, we present an automated and reproducible Metabolome Annotation Workflow (MAW) for untargeted metabolomics data to further facilitate and automate the complex annotation by combining tandem mass spectrometry (MS2) input data pre-processing, spectral and compound database matching with computational classification, and in silico annotation. MAW takes the LC-MS2 spectra as input and generates a list of putative candidates from spectral and compound databases. The databases are integrated via the R package Spectra and the metabolite annotation tool SIRIUS as part of the R segment of the workflow (MAW-R). The final candidate selection is performed using the cheminformatics tool RDKit in the Python segment (MAW-Py). Furthermore, each feature is assigned a chemical structure and can be imported to a chemical structure similarity network. MAW is following the FAIR (Findable, Accessible, Interoperable, Reusable) principles and has been made available as the docker images, maw-r and maw-py. The source code and documentation are available on GitHub ( https://github.com/zmahnoor14/MAW ). The performance of MAW is evaluated on two case studies. MAW can improve candidate ranking by integrating spectral databases with annotation tools like SIRIUS which contributes to an efficient candidate selection procedure. The results from MAW are also reproducible and traceable, compliant with the FAIR guidelines. Taken together, MAW could greatly facilitate automated metabolite characterization in diverse fields such as clinical metabolomics and natural product discovery.PMID:36871033 | DOI:10.1186/s13321-023-00695-y

J Dairy Sci. 2023 Mar 2:S0022-0302(23)00097-8. doi: 10.3168/jds.2022-22681. Online ahead of print.ABSTRACTSole hemorrhage and sole ulcers, referred to as sole lesions, are important causes of lameness in dairy cattle. We aimed to compare the serum metabolome of dairy cows that developed sole lesions in early lactation with that of cows that remained unaffected. We prospectively enrolled a cohort of 1,169 Holstein dairy cows from a single dairy herd and assessed animals at 4 time points: before calving, immediately after calving, early lactation, and late lactation. Sole lesions were recorded by veterinary surgeons at each time point, and serum samples were collected at the first 3 time points. Cases were defined by the presence of sole lesions in early lactation and further subdivided by whether sole lesions had been previously recorded; unaffected controls were randomly selected to match cases. Serum samples from a case-control subset of 228 animals were analyzed with proton nuclear magnetic resonance spectroscopy. Spectral signals, corresponding to 34 provisionally annotated metabolites and 51 unlabeled metabolites, were analyzed in subsets relating to time point, parity cohort, and sole lesion outcome. We used 3 analytic methods (partial least squares discriminant analysis, least absolute shrinkage and selection operator regression, and random forest) to determine the predictive capacity of the serum metabolome and identify informative metabolites. We applied bootstrapped selection stability, triangulation, and permutation to support the inference of variable selection. The average balanced accuracy of class prediction ranged from 50 to 62% depending on the subset. Across all 17 subsets, 20 variables had a high probability of being informative; those with the strongest evidence of being associated with sole lesions corresponded to phenylalanine and 4 unlabeled metabolites. We conclude that the serum metabolome, as characterized by proton nuclear magnetic resonance spectroscopy, does not appear able to predict sole lesion presence or future development of lesions. A small number of metabolites may be associated with sole lesions although, given the poor prediction accuracies, these metabolites are likely to explain only a small proportion of the differences between affected and unaffected animals. Future metabolomic studies may reveal underlying metabolic mechanisms of sole lesion etiopathogenesis in dairy cows; however, the experimental design and analysis need to effectively control for interanimal and extraneous sources of spectral variation.PMID:36870845 | DOI:10.3168/jds.2022-22681

Int J Biol Macromol. 2023 Mar 2:123863. doi: 10.1016/j.ijbiomac.2023.123863. Online ahead of print.ABSTRACTSynthetic biology is an eco-friendly and sustainable approach for the production of compounds, particularly used when the production processes involve toxic reagents. In this study, we used the silk gland of silkworm to produce indigoidine, a valuable natural blue pigment that cannot be synthesized naturally in animals. We genetically engineered these silkworms by integrating the indigoidine synthetase (idgS) gene from S. lavendulae and the PPTase (Sfp) gene from B. subtilis into the silkworm genome. In the resulting Blue silkworm, indigoidine was detected at a high level in the posterior silk gland (PSG), spanning all developmental stages from larvae to adults, without affecting silkworm growth or development. This synthesized indigoidine was secreted from the silk gland and subsequently stored in the fat body, with only a small fraction being excreted by the Malpighian tubule. Metabolomic analysis revealed that Blue silkworm efficiently synthesized indigoidine by upregulating l-glutamine, the precursor of indigoidine, and succinate, which is related to energy metabolism in the PSG. This study represents the first synthesis of indigoidine in an animal and therefore opens a new avenue for the biosynthesis of natural blue pigments and other valuable small molecules.PMID:36870637 | DOI:10.1016/j.ijbiomac.2023.123863

Environ Pollut. 2023 Mar 2:121349. doi: 10.1016/j.envpol.2023.121349. Online ahead of print.ABSTRACTSerum uric acid elevation has been found in long-term nickel (Ni) exposure occupational workers, but the mechanism is unclear. In this study, the relationship between Ni exposure and uric acid elevation was explored in a cohort of 109 participants composed of a Ni-exposed workers group and a control group. The results showed that Ni concentration (5.70 ± 3.21 μg/L) and uric acid level (355.95 ± 67.87 μmol/L) in the serum were increased in the exposure group with a significant positive correlation (r = 0.413, p < 0.0001). The composition of gut microbiota and metabolome revealed that the abundance of uric acid-lowering bacteria, such as Lactobacillus, Lachnospiraceae_Unclassfied and Blautia were reduced while pathogenic bacteria including Parabacteriadies and Escherichia-Shigella were enriched in Ni group, accompanied by impaired intestinal degradation of purines and upregulated biosynthesis of primary bile acids. Consistent with human results, the mice experiments showed that Ni treatment significantly promotes uric acid elevation and systemic inflammation. Lactobacillus and Blautia in gut microbiota were reduced and inflammation-related taxa Alistipes and Mycoplasma were enriched in the Ni treatment. In addition, LC-MS/MS metabolomic analysis indicated that purine nucleosides were accumulated in mice feces, which increased purine absorption and uric acid elevation in the serum. In summary, this study provides evidence that UA elevation was correlated with heavy metals exposure and highlighted the role of gut microbiota in intestinal purine catabolism and in the pathogenesis of heavy metal-induced hyperuricemia.PMID:36870597 | DOI:10.1016/j.envpol.2023.121349