PubMed

Food Chem (Oxf). 2024 Oct 16;9:100227. doi: 10.1016/j.fochms.2024.100227. eCollection 2024 Dec 30.ABSTRACTTo elucidate the formation of characteristic aroma over enzymatic-catalyzed processes (ECP), GC-MS-based volatile-metabolomic combined with desorption-electrospray-ionization coupled mass-spectrometry-imaging (DESI-MSI) were employed to analyze the changes of volatile organic compounds (VOCs) in Tieguanyin tea. A total of 579 VOCs were obtained, from which 24 components involved in five pathways were identified as biomarkers. Among these, four VOCs including 2-furancarboxylic acid, 4-methylbenzaldehyde, N-benzylformamide, cuminaldehyde, were detected in both DESI-MSI and GC-MS analysis, exhibiting dynamic changes along processing steps. RNA-sequencing analysis indicated the genes referring to stress response were activated during tea processing, facilitating the accumulation of flora-fruity aroma in tea leaf. Metabolic pathways analysis revealed that the increase in floral-fruity related components such as volatile terpenoids, phenylpropanoids/benzenoids, indole, alongside a decrease in green leaf volatiles including (E)-2-Hexenal, (Z)-3-Hexenol, played a crucial role in development of characteristic aroma, which could be a feasible index for evaluating processing techniques or quality of oolong tea.PMID:39497732 | PMC:PMC11533622 | DOI:10.1016/j.fochms.2024.100227

Front Oncol. 2024 Oct 21;14:1424293. doi: 10.3389/fonc.2024.1424293. eCollection 2024.ABSTRACTBladder cancer (BC) is the most common malignancy of the urinary tract. About 75% of all BC patients present with non-muscle-invasive BC (NMIBC), of which up to 70% will recur, and 15% will progress in stage and grade. As the recurrence and progression rates of NMIBC are strongly associated with some clinical and pathological factors, several risk stratification models have been developed to individually predict the short- and long-term risks of disease recurrence and progression. The NMIBC patients are stratified into four risk groups as low-, intermediate-, high-risk, and very high-risk by the European Association of Urology (EAU). Significant heterogeneity in terms of oncological outcomes and prognosis has been observed among NMIBC patients within the same EAU risk group, which has been partly attributed to the intrinsic heterogeneity of BC at the molecular level. Currently, we have a poor understanding of how to distinguish intermediate- and (very-)high-risk NMIBC with poor outcomes from those with a more benign disease course and lack predictive/prognostic tools that can specifically stratify them according to their pathologic and molecular properties. There is an unmet need for developing a more accurate scoring system that considers the treatment they receive after TURBT to enable their better stratification for further follow-up regimens and treatment selection, based also on a better response prediction to the treatment. Based on these facts, by employing a multi-layered -omics (namely, genomics, epigenetics, transcriptomics, proteomics, lipidomics, metabolomics) and immunohistopathology approach, we hypothesize to decipher molecular heterogeneity of intermediate- and (very-)high-risk NMIBC and to better stratify the patients with this disease. A combination of different -omics will provide a more detailed and multi-dimensional characterization of the tumor and represent the broad spectrum of NMIBC phenotypes, which will help to decipher the molecular heterogeneity of intermediate- and (very-)high-risk NMIBC. We think that this combinatorial multi-omics approach has the potential to improve the prediction of recurrence and progression with higher precision and to develop a molecular feature-based algorithm for stratifying the patients properly and guiding their therapeutic interventions in a personalized manner.PMID:39497708 | PMC:PMC11532112 | DOI:10.3389/fonc.2024.1424293

Obesity (Silver Spring). 2024 Nov;32(11):2024-2034. doi: 10.1002/oby.24137.ABSTRACTOBJECTIVE: Individuals living with obesity are differentially susceptible to cardiometabolic diseases. We hypothesized that an integrative multi-omics approach might improve identification of subgroups of individuals with obesity who have distinct cardiometabolic disease patterns.METHODS: We performed machine learning-based, integrative unsupervised clustering to identify proteomics- and metabolomics-defined subpopulations of individuals living with obesity (BMI ≥ 30 kg/m2), leveraging data from 243 individuals in the Multi-Ethnic Study of Atherosclerosis (MESA) cohort. Omics that contributed to the observed clusters were functionally characterized. We performed multivariate regression to assess whether the individuals in each cluster demonstrated differential patterns of cardiometabolic traits.RESULTS: We identified two distinct clusters (iCluster1 and 2). iCluster2 had significantly higher average BMI values, fasting blood glucose, and inflammation. iCluster1 was associated with higher levels of total cholesterol and high-density lipoprotein cholesterol. Pathways mediating cell growth, lipogenesis, and energy expenditures were positively associated with iCluster1. Inflammatory response and insulin resistance pathways were positively associated with iCluster2.CONCLUSIONS: Although the two identified clusters may represent progressive obesity-related pathologic processes measured at different stages, other mechanisms in combination could also underpin the identified clusters given no significant age difference between the comparative groups. For instance, clusters may reflect differences in dietary/behavioral patterns or differential rates of metabolic damage.PMID:39497627 | DOI:10.1002/oby.24137

J Anim Sci. 2024 Nov 5:skae339. doi: 10.1093/jas/skae339. Online ahead of print.ABSTRACTThe gastrointestinal microbiota plays a key role in the host physiology and health through a complex host-microbiota co-metabolism. Metabolites produced by microbial metabolism can travel through the bloodstream to reach distal organs and affect their function, ultimately influencing the development of relevant production traits such as meat quality. Meat quality is a complex trait made up of a number of characteristics and intramuscular fat content (IMF) is considered to be one of the most important parameters. In this study, 52 rabbits from two lines divergently selected for IMF (high-IMF (H) and low-IMF (L) lines) were used to perform an untargeted metabolomic analysis of their caecal content, with the aim to obtain information on genetically determined microbial metabolism related to IMF. A large, correlated response to selection was found in their caecal metabolome composition. Partial least squares discriminant analysis was used to identify the pathways differentiating the lines, which showed a classification accuracy of 99%. On the other hand, two linear partial least squares analyses were performed, one for each line, to extract evidence on the specific pathways associated with IMF deposition within each line, which showed predictive abilities (estimated using the Q2) of approximately 60%. The most relevant pathways differentiating the lines were those related to amino acids (aromatic, branched-chain and gamma-glutamyl), secondary bile acids, and purines. The higher content of secondary bile acids in the L-line was related to greater lipid absorption, while the differences found in purines suggested different fermentation activities, which could be related to greater nitrogen utilisation and energy efficiency in the L-line. The linear analyses showed that lipid metabolism had a greater relative importance for IMF deposition in the L-line, whereas a more complex microbial metabolism was associated in the H-line. The lysophospholipids and gamma-glutamyl amino acids were associated with IMF in both lines; the nucleotide and secondary bile acid metabolisms were mostly associated in the H-line; and the long-chain and branched-chain fatty acids were mostly associated in the L-line. A metabolic signature consisting of two secondary bile acids and two protein metabolites was found with 88% classification accuracy, pointing to the interaction between lipid absorption and protein metabolism as a relevant driver of the microbiome activity influencing IMF.PMID:39497598 | DOI:10.1093/jas/skae339

J Alzheimers Dis. 2024 Nov;102(1):237-253. doi: 10.3233/JAD-240280. Epub 2024 Oct 25.ABSTRACTBACKGROUND: Blood metabolites have emerged as promising candidates in the search for biomarkers for Alzheimer's disease (AD), as evidence shows that various metabolic derangements contribute to neurodegeneration in AD.OBJECTIVE: We aim to identify metabolic biomarkers for AD diagnosis.METHODS: We conducted an in-depth analysis of the serum metabolome of AD patients and age, sex-matched cognitively unimpaired older adults using ultra-high-performance liquid chromatography-high resolution mass spectrometry. The biomarkers associated with AD were identified using machine learning algorithms.RESULTS: Using the discovery dataset and support vector machine (SVM) algorithm, we identified a panel of 14 metabolites predicting AD with a 1.00 area under the curve (AUC) of receiver operating characteristic (ROC). The SVM model was tested against the verification dataset using an independent cohort and retained high predictive accuracy with a 0.97 AUC. Using the random forest (RF) algorithm, we identified a panel of 13 metabolites that predicted AD with a 0.96 AUC when tested against the verification dataset.CONCLUSIONS: These findings pave the way for an efficient, blood-based diagnostic test for AD, holding promise for clinical screenings and diagnostic procedures.PMID:39497321 | DOI:10.3233/JAD-240280

J Agric Food Chem. 2024 Nov 4. doi: 10.1021/acs.jafc.4c07416. Online ahead of print.ABSTRACTChrysoeriol, a natural flavonoid, has shown potential in inhibiting melanoma. However, the detailed molecular mechanisms of its action still need to be clarified. In this study, chrysoeriol showed significant suppressive effects on melanoma progression in a mouse model. The integrative gut microbiota and metabolomic analyses revealed that chrysoeriol modulates multiple pathways associated with apoptosis, necroptosis, pyroptosis, and ferroptosis. Morphological changes in chrysoeriol-treated melanoma cells showed PANoptosis- and ferroptosis-related characteristics. Additionally, chrysoeriol induced apoptosis, altered mitochondrial membrane potential, increased ROS production, promoted necroptosis, and also upregulated molecules linked to pyroptosis and ferroptosis. Molecular-level experiments confirmed that chrysoeriol promoted the upregulation of crucial proteins associated with the PANoptosis and ferroptosis pathways. Inhibition of PANoptosis and ferroptosis pathways by inhibitors or gene knockdown significantly attenuated the inhibitory effects of chrysoeriol on melanoma cell viability. This study provides robust evidence that chrysoeriol triggers both PANoptosis and ferroptosis in melanoma cells, underscoring its promise as a treatment option for melanoma.PMID:39497239 | DOI:10.1021/acs.jafc.4c07416

Lipids Health Dis. 2024 Nov 4;23(1):359. doi: 10.1186/s12944-024-02337-0.ABSTRACTBACKGROUND: Metabolic disruptions were observed in patients with optic neurodegenerative diseases (OND). However, evidence for the causal association between metabolites and OND is limited.METHODS: Two-sample Mendelian randomization (MR). Summary data for 128 blood metabolites was selected from three genome-wide association study (GWASs) involving 147,827 participants of European descent. GWASs Data for glaucoma (20906 cases and 391275 controls) and age-related macular degeneration (AMD, 9721 cases and 381339 controls) came from FinnGen consortium. A bi-directional MR was conducted to assess causality, and a Mediation MR was further applied to explore the indirect effect, a phenome-wide MR analysis was then performed to identify possible side-effects of the therapies.RESULTS: All the results underwent correction for multiple testing and rigorous sensitivity analyses. We identified N-acetyl glycine, serine, uridine were linked to an elevated risk of glaucoma. 1-arachidonic-glycerol-phosphate-ethanolamine, 4-acetamido butanoate, o-methylascorbate, saturated fatty acids, monounsaturated fatty acids, VLDL cholesterol, serum total cholesterol, X-11,529 were linked to reduced risk of glaucoma. There were 4 metabolites linked to a reduced risk of AMD, including tryptophan betaine, 4-androsten-3beta-17beta-diol disulfate, apolipoprotein B, VLDL cholesterol. We discovered IOP, AS, T2D as glaucoma risk factors, while BMI, AS, GCIPL as AMD factors. And 6 metabolites showed associations with risk factors in the same direction as their associations with glaucoma/AMD. Phenome-wide MR indicated that selected metabolites had protective/adverse effects on other diseases.CONCLUSIONS: By integrating genomics and metabolomics, this study supports new insights into the intricate mechanisms, and helps prevent and screen glaucoma and AMD.PMID:39497194 | DOI:10.1186/s12944-024-02337-0

Funct Integr Genomics. 2024 Nov 4;24(6):207. doi: 10.1007/s10142-024-01486-w.ABSTRACTPlants acts as living chemical factories that may create a large variety of secondary metabolites, most of which are used in pharmaceutical products. The production of these secondary metabolites is often much lower. Moreover, the primary constraint after discovering potential metabolites is the capacity to manufacture sufficiently for use in industrial and therapeutic contexts. The development of omics technology has brought revolutionary discoveries in various scientific fields, including transcriptomics, metabolomics, and genome sequencing. The metabolic pathways leading to the utilization of new secondary metabolites in the pharmaceutical industry can be identified with the use of these technologies. Genome editing (GEd) is a versatile technology primarily used for site-directed DNA insertions, deletions, replacements, base editing, and activation/repression at the targeted locus. Utilizing GEd techniques such as clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 (CRISPR-associated protein 9), metabolic pathways engineered to synthesize bioactive metabolites optimally. This article will briefly discuss omics and CRISPR/Cas9-based methods to improve secondary metabolite production in medicinal plants.PMID:39496976 | DOI:10.1007/s10142-024-01486-w

Pediatr Res. 2024 Nov 4. doi: 10.1038/s41390-024-03690-7. Online ahead of print.ABSTRACTBACKGROUND: Extrauterine growth restriction (EUGR) affects a substantial proportion of preterm infants and may influence both short-term complications and long-term sequelae. While many preterm infants with EUGR are secondary to small for gestational age (SGA) or very low birth weight (VLBW), a subset of EUGR infants do not exhibit these conditions. The purpose of this study is to investigate the metabolic profiles and biomarkers of EUGR infants in the absence of SGA and VLBW.METHODS: A total of 100 feces (n = 50) and plasma samples (n = 50) were collected from participants categorized as either EUGR (EUGR group) or non-EUGR (NonEUGR group) in the absence of SGA and VLBW. Metabolites were characterized via UPLC-MS/MS using the Discovery HD4® platform. Data normalization, partial least squares discriminant analysis (PLSDA), and KEGG enrichment analysis of metabolite profiles were performed using the MetaboAnalyst 6.0.RESULTS: The clinical characteristics of preterm infants differed significantly between the EUGR and NonEUGR groups at discharge, including length of stay, weight Z-score, weight, height Z-score, height, head circumference, and fat-free mass. The PLSDA model exhibited clustering within groups and separation between groups. A total of 58 and 71 differential metabolites were identified in feces and plasma samples, respectively. They were involved in pathways such as caffeine, galactose, glutathione, cysteine, and methionine metabolisms. In the feces sample, 1-palmitoyl-galactosylglycerol exhibited a significant negative correlation with the growth characteristics of preterm infants, while 1-palmitoyl-2-palmitoleoyl-GPC displayed the opposite pattern. In plasma samples, androsterone glucuronide displayed a significant positive correlation with the growth characteristics of preterm infants, whereas 2-methoxyhydroquinone sulfate generated an opposite pattern. Moreover, 2-oleoylglycerol and sphinganine-1-phosphate exhibited the highest area under the curve in feces and plasma samples, respectively, according to diagnostic ROC curves.CONCLUSION: Preterm infants with EUGR, in the absence of SGA and VLBW, exhibit specific clinical characteristics and metabolomic profiles. Sphinganine-1-phosphate and 2-oleoylglycerol may hold promise as diagnostic markers for EUGR in the absence of SGA and VLBW.IMPACT: The objective of this study is to identify the differential metabolites in preterm infants with extrauterine growth restriction (EUGR) in the absence of small for gestational age (SGA) or very low birth weight (VLBW). Preterm infants with EUGR without SGA and VLBW exhibit specific clinical characteristics and metabolomic profiles. Sphinganine-1-phosphate and 2-oleoylglycerol emerged as potential diagnostic biomarkers for EUGR. This study enhances our understanding of the metabolomic profile in preterm infants with EUGR without SGA or VLBW. Our findings will offer valuable evidence for improving nutritional management and shedding light on the associated pathophysiological mechanisms of EUGR.PMID:39496876 | DOI:10.1038/s41390-024-03690-7

Arch Gynecol Obstet. 2024 Nov 4. doi: 10.1007/s00404-024-07796-5. Online ahead of print.ABSTRACTBACKGROUND: Endometriosis affects the quality of life in women during their reproductive years, causing immense pain and can result in infertility. It is characterized by inflammation and the growth of the endometrium outside the uterine cavity. Metabolomics has the potential to resolve the major bottleneck of endometriosis which is delay in diagnosis due to the invasive diagnostic approach.In this review, the author has summarized the identified biomarkers of endometriosis from different bodily fluids. Metabolomics promises a non-invasive diagnostic approach for endometriosis that could aid in earlier diagnosis and prognosis.METHODS: Patients with endometriosis keywords were searched in correspondence with the assigned keywords, including metabolomics from PubMed, from its inception to Dec 2023. The relevant studies from this search were extracted and included in the study.RESULTS: This article provides information regarding metabolomics studies in endometrisis.CONCLUSIONS: We demonstrated that metabolomics is about to change the world of endometriosis by analyzing and detecting the diagnosis, prognosis, mortality and treatment response biomarkers.PMID:39496808 | DOI:10.1007/s00404-024-07796-5

Anal Bioanal Chem. 2024 Nov 4. doi: 10.1007/s00216-024-05622-0. Online ahead of print.ABSTRACTThe study of the dialogue between microorganisms at the molecular level is becoming essential to understand their relationship (antagonist, neutral, or beneficial interactions) and its impact on the organization of the microbial community. Mass spectrometry imaging (MSI) with matrix-assisted laser desorption/ionization (MALDI) is a technique that reveals the spatial distribution of molecules on a sample surface that may be involved in interactions between organisms. An experimental limitation to perform MALDI MSI is a flat sample surface, which in many cases could not be achieved for bacterial colonies such as filamentous bacteria (e.g., Streptomyces). In addition, sample heterogeneity affects sample dryness and MALDI matrix deposition prior to MSI. To avoid such problems, we introduce an additional step in the sample preparation. A polymeric membrane is interposed between the microorganisms and the agar-based culture medium, allowing the removal of bacterial colonies prior to MSI of the homogeneous culture medium. A proof of concept was evaluated on Streptomyces ambofaciens (a soil bacterium) cultures on solid media. As the mycelium was removed at the same time as the polymeric membrane, the metabolites released into the medium were spatially resolved by MALDI MSI. In addition, extraction of the recovered mycelium from the membrane confirmed the identification of the metabolites by ESI MS/MS analysis. This approach allows both the spatial distribution of metabolites produced by microorganisms in an agar medium to be studied under well-controlled sample preparation and their structure to be elucidated. This capability is illustrated using desferrioxamine E, a siderophore produced by S. ambofaciens.PMID:39496785 | DOI:10.1007/s00216-024-05622-0

Sci Rep. 2024 Nov 4;14(1):26705. doi: 10.1038/s41598-024-77494-4.ABSTRACTClinical proteomics analysis is of great significance for analyzing pathological mechanisms and discovering disease-related biomarkers. Using computational methods to accurately predict disease types can effectively improve patient disease diagnosis and prognosis. However, how to eliminate the errors introduced by peptide precursor identification and protein identification for pathological diagnosis remains a major unresolved issue. Here, we develop a powerful end-to-end deep learning model, termed "MS1Former", that is able to classify hepatocellular carcinoma tumors and adjacent non-tumor (normal) tissues directly using raw MS1 spectra without peptide precursor identification. Our model provides accurate discrimination of subtle m/z differences in MS1 between tumor and adjacent non-tumor tissue, as well as more general performance predictions for data-dependent acquisition, data-independent acquisition, and full-scan data. Our model achieves the best performance on multiple external validation datasets. Additionally, we perform a detailed exploration of the model's interpretability. Prospectively, we expect that the advanced end-to-end framework will be more applicable to the classification of other tumors.PMID:39496730 | DOI:10.1038/s41598-024-77494-4

Sci Rep. 2024 Nov 4;14(1):26635. doi: 10.1038/s41598-024-75627-3.ABSTRACTIdentifying biomarkers able to discriminate individuals on different health trajectories is crucial to understand the molecular basis of age-related morbidity. We investigated multi-omics signatures of general health and organ-specific morbidity, as well as their interconnectivity. We examined cross-sectional metabolome and proteome data from 3,142 adults of the Cooperative Health Research in South Tyrol (CHRIS) study, an Alpine population study designed to investigate how human biology, environment, and lifestyle factors contribute to people's health over time. We had 174 metabolites and 148 proteins quantified from fasting serum and plasma samples. We used the Cumulative Illness Rating Scale (CIRS) Comorbidity Index (CMI), which considers morbidity in 14 organ systems, to assess health status (any morbidity vs. healthy). Omics-signatures for health status were identified using random forest (RF) classifiers. Linear regression models were fitted to assess directionality of omics markers and health status associations, as well as to identify omics markers related to organ-specific morbidity. Next to age, we identified 21 metabolites and 10 proteins as relevant predictors of health status and results confirmed associations for serotonin and glutamate to be age-independent. Considering organ-specific morbidity, several metabolites and proteins were jointly related to endocrine, cardiovascular, and renal morbidity. To conclude, circulating serotonin was identified as a potential novel predictor for overall morbidity.PMID:39496618 | DOI:10.1038/s41598-024-75627-3

Nat Commun. 2024 Nov 4;15(1):9522. doi: 10.1038/s41467-024-53733-0.ABSTRACTFat accumulation, de novo lipogenesis, and glycolysis are key drivers of hepatocyte reprogramming and the consequent metabolic dysfunction-associated steatotic liver disease (MASLD). Here we report that obesity leads to dysregulated expression of hepatic protein-tyrosine phosphatases (PTPs). PTPRK was found to be increased in steatotic hepatocytes in both humans and mice, and correlates positively with PPARγ-induced lipogenic signaling. High-fat-fed PTPRK knockout male and female mice have lower weight gain and reduced hepatic fat accumulation. Phosphoproteomic analysis in primary hepatocytes and hepatic metabolomics identified fructose-1,6-bisphosphatase 1 and glycolysis as PTPRK targets in metabolic reprogramming. Mechanistically, PTPRK-induced glycolysis enhances PPARγ and lipogenesis in hepatocytes. Silencing PTPRK in liver cancer cell lines reduces colony-forming capacity and high-fat-fed PTPRK knockout mice exposed to a hepatic carcinogen develop smaller tumours. Our study defines the role of PTPRK in the regulation of hepatic glycolysis, lipid metabolism, and tumour development in obesity.PMID:39496584 | DOI:10.1038/s41467-024-53733-0

CNS Neurosci Ther. 2024 Nov;30(11):e70094. doi: 10.1111/cns.70094.ABSTRACTThis case report provides the first evidence that coenzyme Q10 may improve muscle weakness in patients with 22q11.2DS. The patient's genetic copy number deletion mutation region mainly contains COMT, PRODH functional genes related with mitochondria dynamics. The level of L-arginine was significantly increased after treatment by coenzyme Q10 in serum.PMID:39496467 | DOI:10.1111/cns.70094

Exp Anim. 2024 Nov 5. doi: 10.1538/expanim.24-0080. Online ahead of print.ABSTRACTTo investigate the pathogenesis of hyperlipidemia in Wistar-SD Hypercholesterolemia (WSHc) rats and clarify the genetic and biological characteristics. Six 7-8-week-old WSHc rats were fed a high-fat diet (HFD), and another six were fed ordinary feed, with age-matched Wistar rats as the control group under the same treatment. After 16 weeks, serum lipid levels were measured. A transcriptomic analysis of the differences in gene expression of the liver related to cholesterol metabolism was conducted, and 119 differentially expressed genes were discovered through bioinformatics analysis and molecular biology verification. UHPLC-Q-TOF/MS was applied for lipidomic analysis of serum samples from each group. WSHc rats developed dyslipidemia after a high-fat diet was induced. Investigation of the gene profiles using the protein-protein interaction network and one-cluster clustering analysis identified SREBF1 as a HUB gene and NR1d1 as an independent key gene. SREBF1 and NR1d1 were further validated in molecular biology experiments, which was consistent with the transcriptomic results. Lipid metabolomics analysis identified seven lipid subclasses and 84 lipid molecules. The metabolic profiles of serum lipid media of the WSHc + HFD and WSHc + SC groups were significantly different compared to that of the control group by 62 and 70 lipid molecules, respectively. Differential metabolites were produced via sphingolipid and glycerophospholipid metabolism. A stable model of hypercholesterolemia in WSHc rats can be generated by feeding on a high-fat diet, and the pathogenesis mainly involves two key genes, SREBF1 and NR1d1, and the sphingolipid and glycerophospholipid metabolism pathways.PMID:39496388 | DOI:10.1538/expanim.24-0080

J Agric Food Chem. 2024 Nov 4. doi: 10.1021/acs.jafc.4c06490. Online ahead of print.ABSTRACTDysregulated muscle glycogen metabolism preslaughter contributes to aberrant postmortem muscle pH (>5.8) in dark-cutting beef phenotypes. However, the underlying mechanisms have remained elusive. Herein, we examine the glycogen dependent regulation of postmortem muscle pH decline and darkening in beef. We show that supplementation of glycogen in vitro restores postmortem pH decline in dark-cutting beef by reverting the metabolome toward a typical postmortem muscle state characterized by increased activities of enzymes glycogen phosphorylase and lactate dehydrogenase (p < 0.05) coupled with a pronounced abundance of glycolytic metabolites and reduced abundance of tricarboxylic acid cycle and amino acid metabolites. Furthermore, concurrent inhibition of mitochondrial respiration at complexes I, IV, and V with glycogen supplementation stimulates greater pH decline. Together, our findings show that supplementing glycogen at low concentrations (10 mM) can reprogram the dark-cutting beef muscle's metabolome toward typical postmortem state and promote muscle acidification. Thus, enhancing glycogen levels could represent a promising strategy for mitigating dark-cutting beef phenotypes and improving meat quality.PMID:39496138 | DOI:10.1021/acs.jafc.4c06490

Medicine (Baltimore). 2024 Nov 1;103(44):e40161. doi: 10.1097/MD.0000000000040161.ABSTRACTInflammation plays a crucial role in chronic kidney disease (CKD) and pulmonary hypertension (PH). Considering that the neutrophil-to-lymphocyte ratio (NLR) has recently emerged as a powerful predictor of adverse outcomes in many chronic diseases, we aimed to investigate the association between NLR and all-cause mortality in patients with CKD-related PH. A total of 176 hospitalized patients with predialysis CKD-related PH were recruited retrospectively from January 2012 to June 2020 by reviewing electronic medical records. The NLR and clinical characteristics of the patients were included in the current analysis. The Kaplan-Meier method and univariate and multivariate Cox regression analyses were performed to identify the association between NLR and the incidence of all-cause mortality. Baseline NLR values were associated with hemoglobin, estimated glomerular filtration rate and C-reactive protein. During a median follow-up period of 32.5 (11.3-53.0) months, 23 patients died. Regardless of whether the NLR acted as a continuous variable with a hazard ratio of 1.408 (95% confidence interval: 1.124-1.763) or a categorical variable (NLR ≤4.3 vs NLR >4.3) with a hazard ratio of 3.100 (95% confidence interval: 1.299-7.402), an elevated NLR was significantly associated with all-cause mortality in different models. A greater NLR at baseline was remarkably associated with a higher all-cause mortality in hospitalized patients with CKD-related PH.PMID:39496051 | DOI:10.1097/MD.0000000000040161

Proc Natl Acad Sci U S A. 2024 Nov 12;121(46):e2406771121. doi: 10.1073/pnas.2406771121. Epub 2024 Nov 4.ABSTRACTBurkholderia thailandensis has emerged as a nonpathogenic surrogate for Burkholderia pseudomallei, the causative agent of melioidosis, and an important Gram-negative model bacterium for studying the biosynthesis and regulation of secondary metabolism. We recently reported that subinhibitory concentrations of trimethoprim induce vast changes in both the primary and secondary metabolome of B. thailandensis. In the current work, we show that the folate biosynthetic enzyme FolE2 is permissive under standard growth conditions but essential for B. thailandensis in the presence of subinhibitory doses of trimethoprim. Reasoning that FolE2 may serve as an attractive drug target, we screened for and identified ten inhibitors, including dehydrocostus lactone (DHL), parthenolide, and β-lapachone, all of which are innocuous individually but form a chemical-synthetic lethal combination with subinhibitory doses of trimethoprim. We show that DHL is a mechanism-based inhibitor of FolE2 and capture the structure of the covalently inhibited enzyme using X-ray crystallography. In vitro, the combination of subinhibitory trimethoprim and DHL is more potent than Bactrim, the current standard of care against melioidosis. Moreover, unlike Bactrim, this combination does not affect the growth of most commensal and beneficial gut bacteria tested, thereby providing a degree of specificity against B. pseudomallei. Our work provides a path for identifying antimicrobial drug targets and for utilizing binary combinations of molecules that form a toxic cocktail based on metabolic idiosyncrasies of specific pathogens.PMID:39495920 | DOI:10.1073/pnas.2406771121

Pak J Pharm Sci. 2024 Sep;37(5):1135-1150.ABSTRACTPeperomia dindygulensis is used as an anticancer medicinal plant in China and is rich in a series of novel secolignans, including peperomin E (PE). In our prior study, we demonstrated the significant reduction in tumor weight and volume in vivo in a PCa DU145 cell xenograft tumor mouse model following PE treatment. However, the impact of PE on PCa metabolism remains unclear. Therefore, the objective of this investigation is to examine the influence of PE on metabolism regulation within a PCa mouse model. An untargeted UPLC-Q-TOF-MS plasma metabolomics approach was carried out to explore the mechanism of action of PE in a human prostate cancer DU145 cell xenograft tumour mouse model based on principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), identification of potential biomarkers and pathway analysis. A total of 71 potential plasma metabolite biomarkers were identified in the nude mouse model and 36 of which were reversed to different degrees after the treatment with PE. These identified biomarkers primarily relate to amino acid metabolism, fatty acid metabolism and cholic acid metabolism. These findings showed that PE could improve endogenous metabolism in the DU145 cell xenograft tumor mouse model and offered a reliable foundation for the design of new therapeutic drugs for treating PCa.PMID:39495855