PubMed

Chem Biodivers. 2023 Jul 28:e202300346. doi: 10.1002/cbdv.202300346. Online ahead of print.ABSTRACTPleurotus ostreatus is an edible fungus with high nutritional value that uses industrial and agricultural lignocellulosic residues as substrates for growth and reproduction. Understanding their growth metabolic dynamics on agro-industrial wastes would help to develop economically viable and eco-friendly biotechnological strategies for food production. Thus, we used UHPLC-MS/MS and GNPS as an innovative approach to investigate the chemical composition of two strains of P. ostreatus, coded as BH (Black Hirataki) and WH (White Hirataki), grown on sisal waste mixture (SW) supplemented with 20% cocoa almond tegument (CAT) or 20% of wheat bran (WB). Metabolite dereplication allowed the identification of 53 metabolites, which included glycerophospholipids, fatty acids, monoacylglycerols, steroids, carbohydrates, amino acids, and flavonoids. This is the first report of the identification of these compounds in P. ostreatus, except for the steroid ergosterol. Most of the metabolites described in this work possess potential biological activities, which support the nutraceutical properties of P. ostreatus. Thus, the results of this study provide essential leads to the understanding of white-rot fungi chemical plasticity aiming at developing alternative biotechnologies strategies for waste recycling.PMID:37503864 | DOI:10.1002/cbdv.202300346

Front Immunol. 2023 Jul 12;14:1193235. doi: 10.3389/fimmu.2023.1193235. eCollection 2023.ABSTRACTTumor-associated macrophages (TAMs) represent one of the main tumor-infiltrating immune cell types and are generally categorized into either of two functionally contrasting subtypes, namely classical activated M1 macrophages and alternatively activated M2 macrophages. TAMs showed different activation states that can be represent by the two extremes of the complex profile of macrophages biology, the M1-like phenotype (pro-inflammatory activity) and the M2-like phenotype (anti-inflammatory activity). Based on the tumor type, and grades, TAMs can acquire different functions and properties; usually, the M1-like phenotype is typical of early tumor stages and is associated to an anti-tumor activity, while M2-like phenotype has a pro-inflammatory activity and is related to a poor patients' prognosis. The classification of macrophages into M1/M2 groups based on well-defined stimuli does not model the infinitely more complex tissue milieu where macrophages (potentially of different origin) would be exposed to multiple signals in different sequential order. This review aims to summarize the recent mass spectrometry-based (MS-based) metabolomics findings about the modifications of metabolism in TAMs polarization in different tumors. The published data shows that MS-based metabolomics is a promising tool to help better understanding TAMs metabolic phenotypes, although it is still poorly applied for TAMs metabolism. The knowledge of key metabolic alterations in TAMs is an essential step for discovering TAMs polarization novel biomarkers and developing novel therapeutic approaches targeting TAM metabolism to repolarize TAMs towards their anti-tumor phenotype.PMID:37503340 | PMC:PMC10368868 | DOI:10.3389/fimmu.2023.1193235

bioRxiv. 2023 Jul 17:2023.07.14.548964. doi: 10.1101/2023.07.14.548964. Preprint.ABSTRACTMetabolomics is a powerful tool for uncovering biochemical diversity in a wide range of organisms, and metabolic network modeling is commonly used to frame results in the context of a broader homeostatic system. However, network modeling of poorly characterized, non-model organisms remains challenging due to gene homology mismatches. To address this challenge, we developed Metabolic Interactive Nodular Network for Omics (MINNO), a web-based mapping tool that takes in empirical metabolomics data to refine metabolic networks for both model and unusual organisms. MINNO allows users to create and modify interactive metabolic pathway visualizations for thousands of organisms, in both individual and multi-species contexts. Herein, we demonstrate an important application of MINNO in elucidating the metabolic networks of understudied species, such as those of the Borrelia genus, which cause Lyme disease and relapsing fever. Using a hybrid genomics-metabolomics modeling approach, we constructed species-specific metabolic networks for three Borrelia species. Using these empirically refined networks, we were able to metabolically differentiate these genetically similar species via their nucleotide and nicotinate metabolic pathways that cannot be predicted from genomic networks. These examples illustrate the use of metabolomics for the empirical refining of genetically constructed networks and show how MINNO can be used to study non-model organisms.PMID:37503268 | PMC:PMC10370097 | DOI:10.1101/2023.07.14.548964

bioRxiv. 2023 Jul 13:2023.07.09.548232. doi: 10.1101/2023.07.09.548232. Preprint.ABSTRACTDietary restriction (DR) is the most robust means to extend lifespan and healthspan across species, but factors such as genetic variation affect how an individual will respond to DR. Additionally, it is unclear how cumulative variations in metabolism and the metabolome influence longevity and health. We utilized metabolomic, phenotypic, and genome-wide data from Drosophila Genetic Reference Panel strains raised under ad libitum and DR conditions to identify factors which influence longevity and health in response to dietary modulation. We found multiple intra-dataset correlations (e.g., metabolites with metabolites) but few inter-dataset correlations (e.g., metabolites with health-related phenotypes). Through random forest modeling across all traits and Mendelian Randomization, we found key translatable traits that influence lifespan or healthspan determination and validated the role of multiple metabolites in regulating lifespan. Through these approaches, we utilized data from flies and humans to elucidate potential therapeutic pathways and metabolomic targets for diet response, lifespan, and healthspan.PMID:37503266 | PMC:PMC10369897 | DOI:10.1101/2023.07.09.548232

bioRxiv. 2023 Jul 19:2023.07.19.549370. doi: 10.1101/2023.07.19.549370. Preprint.ABSTRACTHuman cytomegalovirus (CMV) is a highly prevalent herpesvirus that is often transmitted to the neonate via breast milk. Postnatal CMV transmission can have negative health consequences for preterm and immunocompromised infants, but any effects on healthy term infants are thought to be benign. Furthermore, the impact of CMV on the composition of the hundreds of bioactive factors in human milk has not been tested. Here, we utilize a cohort of exclusively breastfeeding full term mother-infant pairs to test for differences in the milk transcriptome and metabolome associated with CMV, and the impact of CMV in breast milk on the infant gut microbiome and infant growth. We find upregulation of the indoleamine 2,3-dioxygenase (IDO) tryptophan-to-kynurenine metabolic pathway in CMV+ milk samples, and that CMV+ milk is associated with decreased Bifidobacterium in the infant gut. Our data indicate a complex relationship between milk CMV, milk kynurenine, and infant growth; with kynurenine positively correlated, and CMV viral load negatively correlated, with infant weight-for-length at 1 month of age. These results suggest CMV transmission, CMV-related changes in milk composition, or both may be modulators of full term infant development.PMID:37503212 | PMC:PMC10370112 | DOI:10.1101/2023.07.19.549370

Res Sq. 2023 Jul 21:rs.3.rs-3171622. doi: 10.21203/rs.3.rs-3171622/v1. Preprint.ABSTRACTSleep-disordered breathing (SDB) is a prevalent disorder characterized by recurrent episodic upper airway obstruction. In a dataset from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), we applied principal component analysis (PCA) on seven measures characterizing SDB-associated respiratory events. We estimated the association of the top two SDB PCs with serum levels of 617 metabolites, in both single-metabolite analysis, and a joint, penalized regression analysis using the least absolute shrinkage and selection operator (LASSO). Discovery analysis included n = 3,299 HCHS/SOL individuals; associations were validated in a separate dataset of n = 1,522 HCHS/SOL individuals. Seven metabolite associations with SDB PCs were discovered and replicated. Metabolite risk scores (MRSs) developed based on LASSO association results and representing metabolite signatures associated with the two SDB PCs were associated with 6-year incident hypertension and incident diabetes. MRSs have the potential to serve as biomarkers for SDB, guiding risk stratification and treatment decisions.PMID:37503089 | PMC:PMC10371150 | DOI:10.21203/rs.3.rs-3171622/v1

bioRxiv. 2023 Jul 11:2023.07.11.548601. doi: 10.1101/2023.07.11.548601. Preprint.ABSTRACTHigh energy-demanding tissues, such as skeletal muscle, require mitochondrial proteostasis to function properly. Two quality-control mechanisms, the ubiquitin proteasome system (UPS) and the release of mitochondria-derived vesicles, safeguard mitochondrial proteostasis. However, whether these processes interact is unknown. Here we show that the E3 ligase CRL5 Ozz , a member of the UPS, and its substrate Alix control the mitochondrial concentration of Slc25A4, a solute carrier that is essential for ATP production. The mitochondria in Ozz -/- or Alix -/- skeletal muscle share overt morphologic alterations (they are supernumerary, swollen, and dysmorphic) and have abnormal metabolomic profiles. We found that CRL5 Ozz ubiquitinates Slc25A4 and promotes its proteasomal degradation, while Alix facilitates SLC25A4 loading into exosomes destined for lysosomal destruction. The loss of Ozz or Alix offsets steady-state levels of Slc25A4, which disturbs mitochondrial metabolism and alters muscle fiber composition. These findings reveal hitherto unknown regulatory functions of Ozz and Alix in mitochondrial proteostasis.PMID:37503076 | PMC:PMC10369959 | DOI:10.1101/2023.07.11.548601

bioRxiv. 2023 Jul 10:2023.07.10.548411. doi: 10.1101/2023.07.10.548411. Preprint.ABSTRACTTryptophan is an essential amino acid that is extensively characterized as a regulator of cellular function through its metabolism by indoleamine 2,3-deoxygenase (IDO) into the kynurenine pathway. However, despite decades of research on tryptophan metabolism, the metabolic regulatory roles of it and its metabolites are not well understood. To address this, we performed an activity metabolomics screen of tryptophan and most of its known metabolites in cell culture. We discovered that treatment of human colon cancer cells (HCT116) with 3-hydroxykynurenine (3-HK), a metabolite of kynurenine, potently disrupted TCA cycle function. Citrate and aconitate levels were increased, while isocitrate and all downstream TCA metabolites were decreased, suggesting decreased aconitase function. We hypothesized that 3HK or one of its metabolites increased reactive oxygen species (ROS) and inhibited aconitase activity. Accordingly, we observed almost complete depletion of reduced glutathione and a decrease in total glutathione levels. We observed a dose-dependent decrease in cell viability after 48 hours of 3HK treatment. These data suggest that raising the intracellular levels of 3HK could be sufficient to induce ROS-mediated apoptosis. We modulated the intracellular levels of 3HK by combined induction of IDO and knockdown of kynureninase (KYNU) in HCT116 cells. Cell viability decreased significantly after 48 hours of KYNU knockdown compared to controls, which was accompanied by increased ROS production and Annexin V staining revealing apoptosis. Finally, we identify xanthommatin production from 3-HK as a candidate radical-producing, cytotoxic mechanism. Our work indicates that KYNU may be a target for disrupting tryptophan metabolism. Interestingly, many cancers exhibit overexpression of IDO, providing a cancer-specific metabolic vulnerability that could be exploited by KYNU inhibition.PMID:37502990 | PMC:PMC10369892 | DOI:10.1101/2023.07.10.548411

Front Endocrinol (Lausanne). 2023 Jul 12;14:1205703. doi: 10.3389/fendo.2023.1205703. eCollection 2023.ABSTRACTINTRODUCTION: Non-alcoholic fatty liver disease (NAFLD) can progress to more severe stages, such as steatohepatitis and fibrosis. Thermoneutral housing together with high-fat diet promoted NAFLD progression in C57BL/6J mice. Due to possible differences in steatohepatitis development between different C57BL/6 substrains, we examined how thermoneutrality affects NAFLD progression in C57BL/6N mice.METHODS: Male mice were fed standard or high-fat diet for 24 weeks and housed under standard (22°C) or thermoneutral (30°C) conditions.RESULTS: High-fat feeding promoted weight gain and hepatic steatosis, but the effect of thermoneutral environment was not evident. Liver expression of inflammatory markers was increased, with a modest and inconsistent effect of thermoneutral housing; however, histological scores of inflammation and fibrosis were generally low (<1.0), regardless of ambient temperature. In standard diet-fed mice, thermoneutrality increased weight gain, adiposity, and hepatic steatosis, accompanied by elevated de novo lipogenesis and changes in liver metabolome characterized by complex decreases in phospholipids and metabolites involved in urea cycle and oxidative stress defense.CONCLUSION: Thermoneutrality appears to promote NAFLD-associated phenotypes depending on the C57BL/6 substrain and/or the amount of dietary fat.PMID:37501785 | PMC:PMC10369058 | DOI:10.3389/fendo.2023.1205703

Front Immunol. 2023 Jul 11;14:1156774. doi: 10.3389/fimmu.2023.1156774. eCollection 2023.ABSTRACTBACKGROUND: Primary Sjogren's syndrome (pSS) is a prototypical systemic autoimmune disease characterised by lymphocyte infiltration and immune-complex deposition in multiple organs. The specific distribution of immune cell populations and their relationship with mitochondria remain unknown.METHODS: Histological analysis was performed to assess the specific distribution of innate and adaptive immune cell populations in labial salivary gland (LSG) samples from 30 patients with pSS and 13 patients with non-pSS. The ultrastructural morphometric features of mitochondria within immune cells were observed under the transmission electron microscope (TEM). RNA sequencing was performed on LSG samples from 40 patients with pSS and 7 non-pSS patients. The Single-sample Gene Set Enrichment Analysis (ssGSEA), ESTIMATE, and CIBERSORT algorithms and Pearson correlation coefficients were used to examine the relationship between mitochondria-related genes and immune infiltration. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify the mitochondria-specific genes and the related pathways based on the immune cell types.RESULTS: HE staining revealed a massive infiltration of plasma cells with abundant immunoglobulin protein distributed around phenotypically normal-appearing acinar and ductal tissues of patients with pSS. Immunohistochemical analyses revealed that innate immune cells (macrophages, eosinophils and NK cells) were distributed throughout the glandular tissue. Dominant adaptive immune cell infiltration composed of B cells, CD4+T cells and CD8+ T cells or ectopic lymphoid follicle-like structures were observed in the LSGs of patients with pSS. TEM validated the swelling of mitochondria with disorganised cristae in some lymphocytes that had invaded the glandular tissue. Subsequently, bioinformatic analysis revealed that innate and adaptive immune cells were associated with different mitochondrial metabolism pathways. Mitochondrial electron transport and respiratory chain complexes in the glandular microenvironment were positively correlated with innate immune cells, whereas amino acid and nucleic acid metabolism were negatively correlated with adaptive immune cells. In addition, mitochondrial biogenesis and mitochondrial apoptosis in the glandular microenvironment were closely associated with adaptive immune cells.CONCLUSION: Innate and adaptive immune cells have distinct distribution profiles in the salivary gland tissues of patients with pSS and are associated with different mitochondrial metabolic pathways, which may contribute to disease progression.PMID:37497211 | PMC:PMC10366690 | DOI:10.3389/fimmu.2023.1156774

BMC Med. 2023 Jul 27;21(1):275. doi: 10.1186/s12916-023-02967-8.ABSTRACTBACKGROUND: Homozygous familial hypercholesterolemia (HoFH) is an orphan metabolic disease characterized by extremely elevated low-density lipoprotein cholesterol (LDL-C), xanthomas, aortic stenosis, and premature atherosclerotic cardiovascular disease (ASCVD). In addition to LDL-C, studies in experimental models and small clinical populations have suggested that other types of metabolic molecules might also be risk factors responsible for cardiovascular complications in HoFH, but definitive evidence from large-scale human studies is still lacking. Herein, we aimed to comprehensively characterize the metabolic features and risk factors of human HoFH by using metabolic systems strategies.METHODS: Two independent multi-center cohorts with a total of 868 individuals were included in the cross-sectional study. First, comprehensive serum metabolome/lipidome-wide analyses were employed to identify the metabolomic patterns for differentiating HoFH patients (n = 184) from heterozygous FH (HeFH, n = 376) and non-FH (n = 100) subjects in the discovery cohort. Then, the metabolomic patterns were verified in the validation cohort with 48 HoFH patients, 110 HeFH patients, and 50 non-FH individuals. Subsequently, correlation/regression analyses were performed to investigate the associations of clinical/metabolic alterations with typical phenotypes of HoFH. In the prospective study, a total of 84 HoFH patients with available follow-up were enrolled from the discovery cohort. Targeted metabolomics, deep proteomics, and random forest approaches were performed to investigate the ASCVD-associated biomarkers in HoFH patients.RESULTS: Beyond LDL-C, various bioactive metabolites in multiple pathways were discovered and validated for differentiating HoFH from HoFH and non-FH. Our results demonstrated that the inflammation and oxidative stress-related metabolites in the pathways of arachidonic acid and lipoprotein(a) metabolism were independently associated with the prevalence of corneal arcus, xanthomas, and supravalvular/valvular aortic stenosis in HoFH patients. Our results also identified a small marker panel consisting of high-density lipoprotein cholesterol, lipoprotein(a), apolipoprotein A1, and eight proinflammatory and proatherogenic metabolites in the pathways of arachidonic acid, phospholipid, carnitine, and sphingolipid metabolism that exhibited significant performances on predicting first ASCVD events in HoFH patients.CONCLUSIONS: Our findings demonstrate that human HoFH is associated with a variety of metabolic abnormalities and is more complex than previously known. Furthermore, this study provides additional metabolic alterations that hold promise as residual risk factors in HoFH population.PMID:37501168 | DOI:10.1186/s12916-023-02967-8

BMC Plant Biol. 2023 Jul 28;23(1):373. doi: 10.1186/s12870-023-04381-x.ABSTRACTBACKGROUND: Buckwheat (Fagopyrum spp.), belonging to the Polygonaceae family, is an ancient pseudo-cereal with high nutritional and nutraceutical properties. Buckwheat proteins are gluten-free and show balanced amino acid and micronutrient profiles, with higher content of health-promoting bioactive flavonoids that make it a golden crop of the future. Plant metabolome is increasingly gaining importance as a crucial component to understand the connection between plant physiology and environment and as a potential link between the genome and phenome. However, the genetic architecture governing the metabolome and thus, the phenome is not well understood. Here, we aim to obtain a deeper insight into the genetic architecture of seed metabolome in buckwheat by integrating high throughput metabolomics and genotyping-by-sequencing applying an array of bioinformatics tools for data analysis.RESULTS: High throughput metabolomic analysis identified 24 metabolites in seed endosperm of 130 diverse buckwheat genotypes. The genotyping-by-sequencing (GBS) of these genotypes revealed 3,728,028 SNPs. The Genome Association and Prediction Integrated Tool (GAPIT) assisted in the identification of 27 SNPs/QTLs linked to 18 metabolites. Candidate genes were identified near 100 Kb of QTLs, providing insights into several metabolic and biosynthetic pathways.CONCLUSIONS: We established the metabolome inventory of 130 germplasm lines of buckwheat, identified QTLs through marker trait association and positions of potential candidate genes. This will pave the way for future dissection of complex economic traits in buckwheat.PMID:37501129 | DOI:10.1186/s12870-023-04381-x

Transl Neurodegener. 2023 Jul 28;12(1):38. doi: 10.1186/s40035-023-00370-0.ABSTRACTMultiple system atrophy (MSA) is a fatal progressive neurodegenerative disease. Biomarkers are urgently required for MSA to improve the diagnostic and prognostic accuracy in clinic and facilitate the development and monitoring of disease-modifying therapies. In recent years, significant research efforts have been made in exploring multidimensional biomarkers for MSA. However, currently few biomarkers are available in clinic. In this review, we systematically summarize the latest advances in multidimensional biomarkers for MSA, including biomarkers in fluids, tissues and gut microbiota as well as imaging biomarkers. Future directions for exploration of novel biomarkers and promotion of implementation in clinic are also discussed.PMID:37501056 | DOI:10.1186/s40035-023-00370-0

Nat Commun. 2023 Jul 27;14(1):4518. doi: 10.1038/s41467-023-40245-6.ABSTRACTGlobally, the lifespan of populations increases but the healthspan is lagging behind. Previous research showed that survival into extreme ages (longevity) clusters in families as illustrated by the increasing lifespan of study participants with each additional long-lived family member. Here we investigate whether the healthspan in such families follows a similar quantitative pattern using three-generational data from two databases, LLS (Netherlands), and SEDD (Sweden). We study healthspan in 2143 families containing index persons with 26 follow-up years and two ancestral generations, comprising 17,539 persons. Our results provide strong evidence that an increasing number of long-lived ancestors associates with up to a decade of healthspan extension. Further evidence indicates that members of long-lived families have a delayed onset of medication use, multimorbidity and, in mid-life, healthier metabolomic profiles than their partners. We conclude that both lifespan and healthspan are quantitatively linked to ancestral longevity, making family data invaluable to identify protective mechanisms of multimorbidity.PMID:37500622 | DOI:10.1038/s41467-023-40245-6

J Dairy Sci. 2023 Jul 25:S0022-0302(23)00428-9. doi: 10.3168/jds.2023-23259. Online ahead of print.ABSTRACTRecent studies have suggested that dietary rumen-protected choline (RPC) supplementation can modulate immune function, attenuate inflammation, and improve performance in periparturient dairy cattle; however, this has yet to be evaluated during a mastitis challenge. Therefore, the objective of this study was to examine the effects of supplementation and dose of RPC on metabolism, inflammation, and performance during an intramammary lipopolysaccharide (LPS) challenge. Parous Holstein cows (parity, mean ± SD, 1.9 ± 1.1 at enrollment) were blocked by calving month and randomly assigned within block to receive either 45 g/d of RPC (20.4 g/d of choline ions; CHOL45, n = 18), 30 g/d of RPC (13.6 g/d of choline ions; CHOL30, n = 21), or no RPC (CON, n = 19) as a top-dress starting 24 d before expected calving until 21 d postpartum. Cows were alternately assigned within treatment group to either receive an intramammary LPS challenge (200 μg in each rear quarter; Escherichia coli O111:B4) or not at 17 DIM. Before the challenge, CHOL45 and CHOL30 cows produced 3.4 and 3.8 (±1.2 SED) kg/d more milk than CON, respectively. Dietary RPC supplementation did not mitigate the milk loss associated with the intramammary LPS challenge; however, CHOL45 and CHOL30 cows produced 3.1 and 3.5 (±1.4 SED) kg/d more milk than CON, respectively in the carryover period (22 to 84 DIM). Dietary RPC supplementation enhanced plasma β-hydroxybutyrate (BHB) concentrations before the LPS challenge, and increased plasma nonesterified fatty acids (NEFA) and acetylcarnitine concentrations during the LPS challenge, potentially reflecting greater adipose tissue mobilization, fatty acid transport and oxidation. Aside from trimethylamine N-oxide and sarcosine, which were increased in CHOL45-LPS as compared with CON-LPS, most other choline metabolite concentrations in plasma were unaffected by treatment, likely because more choline was being secreted in milk. Plasma lactic acid concentrations were decreased in CHOL45-LPS and CHOL30-LPS as compared with CON-LPS, suggesting a reduction in glycolysis or an enhancement in the flux through the lactic acid cycle to support gluconeogenesis. Plasma concentrations of fumaric acid, a byproduct of AA catabolism and the urea cycle, were increased in both choline groups as compared with CON-LPS during the LPS challenge. Cows in the CHOL45 group had greater plasma antioxidant potential before the LPS challenge and reduced plasma methionine sulfoxide concentrations during the LPS challenge compared with CON-LPS, suggesting an improvement in oxidant status. Nevertheless, concentrations of inflammatory markers such as haptoglobin and tumor necrosis factor α (TNFα) were not affected by treatment. Taken together, our data suggest that the effects of dietary RPC supplementation on milk yield could be mediated through metabolic pathways and are unlikely to be related to the resolution of inflammation in periparturient dairy cattle. Lastly, dose responses to dietary RPC supplementation were not found for various economically important outcomes including milk yield, limiting the justification for feeding a greater dietary RPC dose in industry.PMID:37500444 | DOI:10.3168/jds.2023-23259

J Dairy Sci. 2023 Jul 25:S0022-0302(23)00412-5. doi: 10.3168/jds.2022-22890. Online ahead of print.ABSTRACTHeat stress (HS) impairs productivity, health, and welfare in dairy cows, and additionally causes metabolic changes. Hence, specific metabolites could be used as HS biomarkers. Consequently, the aim of the present study was to compare blood metabolite concentrations of German Holstein dairy cows and of their female calves suffering from high temperature-humidity index (THI) during late gestation (cows) or during their first week of life (calves) or not. According to the mean daily THI (mTHI) at the day before blood sampling, animals were classified into 2 groups: high mTHI ≥60 (hmTHI) and low mTHI <60 (lmTHI). To perform a standard cross-sectional 2-group study, cow groups (n = 48) and calf groups (n = 47) were compared separately. Differences in metabolite concentrations between hmTHI and lmTHI animals were inferred based on a targeted metabolomics approach. In the first step, processed metabolomics data were evaluated by multivariate data analysis techniques, and were visualized using the web-based platform MetaboAnalyst V5.0. The most important metabolites with pronounced differences between groups were further analyzed in a second step using linear mixed models. We identified 9 thermally sensitive metabolites for the cows [dodecanedioic acid; 3-indolepropionic acid; sarcosine; triglycerides (14:0_34:0), (16:0_38:7), (18:0_32:1), and (18:0_36:2); phosphatidylcholine aa C38:1; and lysophosphatidylcholine a C20:3] and for the calves [phosphatidylcholines aa C38:1, ae C38:3, ae C36:0, and ae C36:2; cholesteryl esters (17:1) and (20:3); sphingomyelins C18:0 and C18:1; and p-cresol sulfate], most of them related to lipid metabolism. Apart from 2 metabolites (3-indolepropionic acid and sarcosine) in cows, the metabolite plasma concentrations were lower in hmTHI than in lmTHI groups. In our heat-stressed dry cows, results indicate an altered lipid metabolism compared with lactating heat-stressed cows, due to the missing antilipolytic effect of HS. The results also indicate alterations in lipid metabolism of calves due to high mTHI in the first week of life. From a cross-generation perspective, high mTHI directly before calving seems to reduce colostrum quality, with detrimental effects on metabolite concentrations in offspring.PMID:37500442 | DOI:10.3168/jds.2022-22890

J Dairy Sci. 2023 Jul 25:S0022-0302(23)00423-X. doi: 10.3168/jds.2022-23118. Online ahead of print.ABSTRACTLameness in dairy cattle is a highly prevalent condition that impacts on the health and welfare of dairy cows. Prompt detection and implementation of effective treatment is important for managing lameness. However, major limitations are associated with visual assessment of lameness, which is the most commonly used method to detect lameness. The aims of this study were to investigate the use of metabolomics and machine learning to develop novel methods to detect lameness. Untargeted metabolomics using liquid chromatography-mass spectrometry (LC-MS) alongside machine learning models and a stability selection method were utilized to evaluate the predictive accuracy of differences in the metabolomics profile of first-lactation dairy cows before (during the transition period) and at the time of lameness (based on visual assessment using the 0-3 scale of the Agriculture and Horticulture Development Board). Urine samples were collected from 2 cohorts of dairy heifers and stored at -86°C before analysis using LC-MS. Cohort 1 (n = 90) cows were recruited as current first-lactation cows with weekly mobility scores recorded over a 4-mo timeframe, from which newly lame and nonlame cows were identified. Cohort 2 (n = 30) cows were recruited within 3 wk before calving, and lameness events (based on mobility score) were recorded through lactation until a minimum of 70 d in milk (DIM). All cows were matched paired by DIM ± 14 d. The median DIM at lameness identification was 187.5 and 28.5 for cohort 1 and 2, respectively. The best performing machine learning models predicted lameness at the time of lameness with an accuracy of between 81 and 82%. Using stability selection, the prediction accuracy at the time of lameness was 80 to 81%. For samples collected before and after calving, the best performing machine learning model predicted lameness with an accuracy of 71 and 75%, respectively. The findings from this study demonstrate that untargeted LC-MS profiling combined with machine learning methods can be used to predict lameness as early as before calving and before observable changes in gait in first-lactation dairy cows. The methods also provide accuracies for detecting lameness at the time of observable changes in gait of up to 82%. The findings demonstrate that these methods could provide substantial advancements in the early prediction and prevention of lameness risk. Further external validation work is required to confirm these findings are generalizable; however, this study provides the basis from which future work can be conducted.PMID:37500436 | DOI:10.3168/jds.2022-23118

Neurochem Int. 2023 Jul 25:105588. doi: 10.1016/j.neuint.2023.105588. Online ahead of print.ABSTRACTBACKGROUND: Stroke is a significant health issue in the United States, and identifying biomarkers for the prevention and functional recovery after an acute stroke remains the highest priority. This study aims to identify circulating metabolite signatures that may be associated with stroke pathophysiology by performing discovery and validation studies.METHODS: We performed targeted metabolomics profiling of 420 participants of the discovery dataset of Metabolome in an Ischemic Stroke Study (MISS) using high-throughput nuclear magnetic resonance (NMR) spectroscopy. A validation study of significantly altered metabolites was conducted using an independent cohort of 117,988 participants from the UK Biobank, whose metabolomics profiles were generated using the same NMR technology.RESULTS AND CONCLUSION: Our study identified 16 metabolites to be significantly perturbed during acute stroke. Amino acid phenylalanine was significantly increased, while glutamine and histidine were significantly lowered in stroke. Serum levels of apolipoprotein A-1, HDL particles, small HDL particles, essential fatty acids, and phosphatidylcholine were reduced, while ketone bodies like 3-hydroxybutyrate and acetoacetate were markedly increased in stroke. Based on the robust validation in a large independent UK Biobank dataset, some of these analytes may become clinically meaningful biomarkers to predict or prevent stroke in humans.PMID:37499945 | DOI:10.1016/j.neuint.2023.105588

J Sci Food Agric. 2023 Jul 27. doi: 10.1002/jsfa.12885. Online ahead of print.ABSTRACTBACKGROUND: Mandarin wine has high added value which can effectively extend the industry chain of mandarin and bring excellent economic performance. However, innovative fermentation methods are urgently needed to improve the typical taste and flavor characteristics of mandarin wine. In this study, the effect and underlying mechanism of co-fermentation with Saccharomyces cerevisiae and Schizosaccharomyces pombe on the characteristics of mandarin wine was investigated based on an integrated metabolomic and transcriptomic analyses.RESULTS: Compared to fermentation with only S. cerevisiae, the mandarin wine of co-fermentation with S. cerevisiae and Sc. pombe had a higher pH value, lower content of malic acid, and more abundant free amino acids, resulting in better sensory evaluation scores. The introduction of Sc. pombe extended the stage of alcoholic fermentation and enhanced the richness and diversity of volatile compounds, especially the floral and fruity aroma compounds, including ethyl hexanoate, ethyl caprylate, ethyl enanthate, 1-heptanol, and phenylethyl alcohol. Moreover, the significantly differential metabolites and varying genes were mainly found in pathways of glycolysis, pyruvate metabolism, citrate cycle, and amino acids metabolism.CONCLUSION: Co-fermentation with S. cerevisiae and Sc. pombe showed more advantages in producing distinctive taste and flavor of mandarin wine compared to fermentation with only S. cerevisiae. This study can spark new strategies of co-fermentation to improve the sensory quality of mandarin wine. This article is protected by copyright. All rights reserved.PMID:37499161 | DOI:10.1002/jsfa.12885

J Agric Food Chem. 2023 Jul 27. doi: 10.1021/acs.jafc.3c01913. Online ahead of print.ABSTRACTCyanobacterial fructose-1,6-/sedoheptulose-1,7-bisphosphatase (Cy-FBP/SBPase) was an important regulatory enzyme in cyanobacterial photosynthesis and was a potential target enzyme for screening to obtain novel inhibitors against cyanobacterial blooms. In this study, we developed a novel pharmacophore screening model based on the catalytic mechanism and substrate structure of Cy-FBP/SBPase and screened 26 S series compounds with different structures and pharmacophore characteristics from the Specs database by computer-assisted drug screening. These compounds exhibited moderate inhibitory activity against Cy-FBP/SBPase, with 9 compounds inhibiting >50% at 100 μM. Among them, compound S5 showed excellent inhibitory activity against both Cy-FBP/SBPase and Synechocystis sp. PCC6803 (IC50 = 6.7 ± 0.7 μM and EC50 = 7.7 ± 1.4 μM). The binding mode of compound S5 to Cy-FBP/SBPase was predicted using the molecular docking theory and validated by sentinel mutation and enzyme activity analysis. Physiochemical, gene transcription level, and metabolomic analyses showed that compound S5 significantly reduced the quantum yield of photosystem II and the maximum electron transfer rate, downregulated transcript levels of related genes encoding the Calvin cycle and photosystem, reduced the photosynthetic efficiency of cyanobacteria, thus inhibited metabolic pathways, such as the Calvin cycle and tricarboxylic acid cycle, and eventually achieved an efficient algicide. In addition, compound S5 had a high safety profile for human-derived cells and zebrafish. In summary, the novel pharmacophore screening model obtained from the current work provides an effective solution to the cyanobacterial bloom problem.PMID:37498729 | DOI:10.1021/acs.jafc.3c01913