PubMed

Sci Rep. 2023 Jun 28;13(1):10461. doi: 10.1038/s41598-023-36535-0.ABSTRACTRespiratory infections are a leading cause of morbidity and mortality in early life, and recurrent infections increase the risk of developing chronic diseases. The maternal environment during pregnancy can impact offspring health, but the factors leading to increased infection proneness have not been well characterized during this period. Steroids have been implicated in respiratory health outcomes and may similarly influence infection susceptibility. Our objective was to describe relationships between maternal steroid levels and offspring infection proneness. Using adjusted Poisson regression models, we evaluated associations between sixteen androgenic and corticosteroid metabolites during pregnancy and offspring respiratory infection incidence across two pre-birth cohorts (N = 774 in VDAART and N = 729 in COPSAC). Steroid metabolites were measured in plasma samples from pregnant mothers across all trimesters of pregnancy by ultrahigh-performance-liquid-chromatography/mass-spectrometry. We conducted further inquiry into associations of steroids with related respiratory outcomes: asthma and lung function spirometry. Higher plasma corticosteroid levels in the third trimester of pregnancy were associated with lower incidence of offspring respiratory infections (P = 4.45 × 10-7 to 0.002) and improved lung function metrics (P = 0.020-0.036). Elevated maternal androgens were generally associated with increased offspring respiratory infections and worse lung function, with some associations demonstrating nominal significance at P < 0.05, but these trends were inconsistent across individual androgens. Increased maternal plasma corticosteroid levels in the late second and third trimesters were associated with lower infections and better lung function in offspring, which may represent a potential avenue for intervention through corticosteroid supplementation in late pregnancy to reduce offspring respiratory infection susceptibility in early life.Clinical Trial Registry information: VDAART and COPSAC were originally conducted as clinical trials; VDAART: ClinicalTrials.gov identifier NCT00920621; COPSAC: ClinicalTrials.gov identifier NCT00798226.PMID:37380711 | DOI:10.1038/s41598-023-36535-0

Nat Commun. 2023 Jun 28;14(1):3823. doi: 10.1038/s41467-023-38921-8.ABSTRACTPancreatic Ductal Adenocarcinoma (PDAC) is highly resistant to chemotherapy. Effective alternative therapies have yet to emerge, as chemotherapy remains the best available systemic treatment. However, the discovery of safe and available adjuncts to enhance chemotherapeutic efficacy can still improve survival outcomes. We show that a hyperglycemic state substantially enhances the efficacy of conventional single- and multi-agent chemotherapy regimens against PDAC. Molecular analyses of tumors exposed to high glucose levels reveal that the expression of GCLC (glutamate-cysteine ligase catalytic subunit), a key component of glutathione biosynthesis, is diminished, which in turn augments oxidative anti-tumor damage by chemotherapy. Inhibition of GCLC phenocopies the suppressive effect of forced hyperglycemia in mouse models of PDAC, while rescuing this pathway mitigates anti-tumor effects observed with chemotherapy and high glucose.PMID:37380658 | DOI:10.1038/s41467-023-38921-8

EBioMedicine. 2023 Jun 26;93:104684. doi: 10.1016/j.ebiom.2023.104684. Online ahead of print.ABSTRACTBACKGROUND: Combined glucose-dependent insulinotropic polypeptide receptor (GIPR) and glucagon-like peptide-1 receptor (GLP1R) agonism is superior to single GLP1R agonism with respect to glycemic control and weight loss in obese patients with or without type 2 diabetes. As insulin resistance and obesity are strong risk factors for nonalcoholic fatty liver disease (NAFLD), in the current study we investigated the effects of combined GIPR/GLP1R agonism on NAFLD development.METHODS: Male APOE∗3-Leiden.CETP mice, a humanized model for diabetic dyslipidemia and NAFLD when fed a high-fat high-cholesterol diet, received subcutaneous injections with either vehicle, a GIPR agonist, a GLP1R agonist, or both agonists combined every other day.FINDINGS: GIPR and GLP1R agonism reduced body weight and additively lowered fasting plasma levels of glucose, triglycerides and total cholesterol. Strikingly, we report an additive reduction in hepatic steatosis as evidenced by lower hepatic lipid content and NAFLD scores. Underlying the lipid-lowering effects were a reduced food intake and intestinal lipid absorption and an increased uptake of glucose and triglyceride-derived fatty acids by energy-combusting brown adipose tissue. Combined GIPR/GLP1R agonism also attenuated hepatic inflammation as evidenced by a decreased number of monocyte-derived Kupffer cells and a reduced expression of inflammatory markers. Together, the reduced hepatic steatosis and inflammation coincided with lowered markers of liver injury.INTERPRETATION: We interpretate that GIPR and GLP1R agonism additively attenuate hepatic steatosis, lower hepatic inflammation, ameliorate liver injury, together preventing NAFLD development in humanized APOE∗3-Leiden.CETP mice. We anticipate that combined GIPR/GLP1R agonism is a promising strategy to attenuate NAFLD progression in humans.FUNDING: This work was supported by a grant from the Netherlands CardioVascular Research Initiative: the Dutch Heart Foundation, Dutch Federation of University Medical Centers, the Netherlands Organization for Health Research and Development, and the Royal Netherlands Academy of Sciences [CVON-GENIUS-II] to P.C.N.R., a Lilly Research Award Program [LRAP] Award to P.C.N.R. and S.K., a Dutch Heart Foundation [2017T016] grant to S.K., and an NWO-VENI grant [09150161910073] to M.R.B.; J.F.D.B. is supported by the Nutrition and Health initiative of the University of Groningen; Z.Y. is supported by a full-time PhD scholarship from the China Scholarship Council (201806850094 to Z.Y.).PMID:37379656 | DOI:10.1016/j.ebiom.2023.104684

Reproduction. 2022 Jan 28;163(4):183-198. doi: 10.1530/REP-21-0351. eCollection 2022 Apr 1.ABSTRACTDietary supplementation is the most feasible method to improve oocyte function and developmental potential in vivo. During three experiments, oocytes were collected from maturing, dominant follicles of older mares to determine whether short-term dietary supplements can alter oocyte metabolic function, lipid composition, and developmental potential. Over approximately 8 weeks, control mares were fed hay (CON) or hay and grain products (COB). Treated mares received supplements designed for equine wellness and gastrointestinal health, flaxseed oil, and a proprietary blend of fatty acid and antioxidant support (reproductive support supplement (RSS)) intended to increase antioxidant activity and lipid oxidation. RSS was modified for individual experiments with additional antioxidants or altered concentrations of n-3 to n-6 fatty acids. Oocytes from mares supplemented with RSS when compared to COB had higher basal oxygen consumption, indicative of higher aerobic metabolism, and proportionately more aerobic to anaerobic metabolism. In the second experiment, oocytes collected from the same mares prior to (CON) and after approximately 8 weeks of RSS supplementation had significantly reduced oocyte lipid abundance. In the final experiment, COB was compared to RSS supplementation, including RSS modified to proportionately reduce n-3 fatty acids and increase n-6 fatty acids. The ability of sperm-injected oocytes to develop into blastocysts was higher for RSS, regardless of fatty acid content, than for COB. We demonstrated that short-term diet supplementation can directly affect oocyte function in older mares, resulting in oocytes with increased metabolic activity, reduced lipid content, and increased developmental potential.PMID:37379450 | PMC:PMC8942336 | DOI:10.1530/REP-21-0351

Eur J Immunol. 2023 Jun 28:e2250071. doi: 10.1002/eji.202250071. Online ahead of print.ABSTRACTDisulfide bond A oxidoreductase-like protein (DsbA-L) drives acute kidney injury (AKI) by directly upregulating the expression of voltage-dependent anion-selective channels in proximal tubular cells. However, the role of DsbA-L in immune cells remains unclear. In this study, we used an LPS-induced AKI mouse model to assess the hypothesis that DsbA-L deletion attenuates LPS-induced AKI and explore the potential mechanism of DsbA-L action. After 24 hours of LPS exposure, the DsbA-L knockout group exhibited lower serum creatinine levels compared to the wild-type (WT) group. Furthermore, peripheral levels of the inflammatory cytokine interleukin-6 (IL-6) were decreased. Transcriptomic data analysis revealed a significant down-regulation in the IL-17 and tumor necrosis factor pathways in DsbA-L knockout mice following LPS induction. Metabolomic analysis suggested that arginine metabolism was significantly different between the WT and DsbA-L knockout groups after LPS treatment. Notably, the M1 polarization of macrophages in the kidneys of DsbA-L knockout AKI mice was significantly reduced. Expression of the transcription factors nuclear factor kappa B (NF-κB) and activator protein 1 (AP-1) was downregulated after DsbA-L knockout. Our results suggest that DsbA-L regulates LPS-mediated oxidative stress, promotes M1 polarization of macrophages and induces expression of inflammatory factors via the NF-κB/AP-1 pathway. This article is protected by copyright. All rights reserved.PMID:37379419 | DOI:10.1002/eji.202250071

Biochem J. 2023 Jun 28;480(12):891-908. doi: 10.1042/BCJ20210534.ABSTRACTMetabolomics is a powerful research discovery tool with the potential to measure hundreds to low thousands of metabolites. In this review, we discuss the application of GC-MS and LC-MS in discovery-based metabolomics research, we define metabolomics workflows and we highlight considerations that need to be addressed in order to generate robust and reproducible data. We stress that metabolomics is now routinely applied across the biological sciences to study microbiomes from relatively simple microbial systems to their complex interactions within consortia in the host and the environment and highlight this in a range of biological species and mammalian systems including humans. However, challenges do still exist that need to be overcome to maximise the potential for metabolomics to help us understanding biological systems. To demonstrate the potential of the approach we discuss the application of metabolomics in two broad research areas: (1) synthetic biology to increase the production of high-value fine chemicals and reduction in secondary by-products and (2) gut microbial interaction with the human host. While burgeoning in importance, the latter is still in its infancy and will benefit from the development of tools to detangle host-gut-microbial interactions and their impact on human health and diseases.PMID:37378961 | DOI:10.1042/BCJ20210534

Adv Exp Med Biol. 2023;1412:491-509. doi: 10.1007/978-3-031-28012-2_27.ABSTRACTThis chapter describes the application of genomic, transcriptomic, proteomic, and metabolomic methods in the study of SARS-CoV-2 variants of concern. We also describe the important role of machine learning tools to identify the most significant biomarker signatures and discuss the latest point-of-care devices that can be used to translate these findings to the physician's office or to bedside care. The main emphasis is placed on increasing our diagnostic capacity and predictability of disease outcomes to guide the most appropriate treatment strategies.PMID:37378785 | DOI:10.1007/978-3-031-28012-2_27

Adv Exp Med Biol. 2023;1412:311-335. doi: 10.1007/978-3-031-28012-2_17.ABSTRACTCurrently, methods in machine learning have opened a significant number of applications to construct classifiers with capacities to recognize, identify, and interpret patterns hidden in massive amounts of data. This technology has been used to solve a variety of social and health issues against coronavirus disease 2019 (COVID-19). In this chapter, we present some supervised and unsupervised machine learning techniques that have contributed in three aspects to supplying information to health authorities and diminishing the deadly effects of the current worldwide outbreak on the population. First is the identification and construction of powerful classifiers capable of predicting severe, moderate, or asymptomatic responses in COVID-19 patients starting from clinical or high-throughput technologies. Second is the identification of groups of patients with similar physiological responses to improve the triage classification and inform treatments. The final aspect is the combination of machine learning methods and schemes from systems biology to link associative studies with mechanistic frameworks. This chapter aims to discuss some practical applications in the use of machine learning techniques to handle data coming from social behavior and high-throughput technologies, associated with COVID-19 evolution.PMID:37378775 | DOI:10.1007/978-3-031-28012-2_17

Adv Exp Med Biol. 2023;1412:197-209. doi: 10.1007/978-3-031-28012-2_10.ABSTRACTCOVID-19 stands for Corona Virus Disease 2019, which starts as a viral infection that provokes illness with different symptoms and severity. The infected individuals can be asymptomatic or present with mild, moderate, severe, and critical illness with acute respiratory distress syndrome (ARDS), acute cardiac injury, and multiorgan failure. When the virus enters the cells, it replicates and provokes responses. Most diseased individuals resolve the problems in a short time but unfortunately, some may die, and almost 3 years after the first reported cases, COVID-19 still kills thousands per day worldwide. One of the problems in not curing the viral infection is that the virus passes by undetected in cells. This can be caused by the lack of pathogen-associated molecular patterns (PAMPs) that start an orchestrated immune response, such as activation of type 1 interferons (IFNs), inflammatory cytokines, chemokines, and antiviral defenses. Before all of these events can happen, the virus uses the infected cells and numerous small molecules as sources of energy and building blocks for newly synthesized viral nanoparticles that travel to and infect other host cells. Therefore, studying the cell metabolome and metabolomic changes in biofluids might give insights into the state of the viral infection, viral loads, and defense response. NMR-metabolomics can help in solving the real-time host interactions by monitoring concentration changes in metabolites. This chapter addresses the state of the art of COVIDomics by NMR analyses and presents exemplified biomolecules identified in different world regions and gravities of illness as potential biomarkers.PMID:37378768 | DOI:10.1007/978-3-031-28012-2_10

Eur J Nutr. 2023 Jun 28. doi: 10.1007/s00394-023-03186-w. Online ahead of print.ABSTRACTBACKGROUND: Maternal dietary choline has a central role in foetal brain development and may be associated with later cognitive function. However, many countries are reporting lower than recommended intake of choline during pregnancy.METHODS: Dietary choline was estimated using food frequency questionnaires in pregnant women participating in population-derived birth cohort, the Barwon Infant Study (BIS). Dietary choline is reported as the sum of all choline-containing moieties. Serum total choline-containing compounds (choline-c), phosphatidylcholine and sphingomyelin were measured using nuclear magnetic resonance metabolomics in the third trimester. The main form of analysis was multivariable linear regression.RESULTS: The mean daily dietary choline during pregnancy was 372 (standard deviation (SD) 104) mg/day. A total of 236 women (23%) had adequate choline intake (440 mg/day) based on the Australian and New Zealand guidelines, and 27 women (2.6%) took supplemental choline ([Formula: see text] 50 mg/dose) daily during pregnancy. The mean serum choline-c in pregnant women was 3.27 (SD 0.44) mmol/l. Ingested choline and serum choline-c were not correlated (R2) = - 0.005, p = 0.880. Maternal age, maternal weight gain in pregnancy, and a pregnancy with more than one infant were associated with higher serum choline-c, whereas gestational diabetes and environmental tobacco smoke during preconception and pregnancy were associated with lower serum choline-c. Nutrients or dietary patterns were not associated with variation in serum choline-c.CONCLUSION: In this cohort, approximately one-quarter of women met daily choline recommendations during pregnancy. Future studies are needed to understand the potential impact of low dietary choline intake during pregnancy on infant cognition and metabolic intermediaries.PMID:37378694 | DOI:10.1007/s00394-023-03186-w

Metabolomics. 2023 Jun 28;19(7):64. doi: 10.1007/s11306-023-02027-5.ABSTRACTINTRODUCTION: Interpretation and analysis of NMR-based metabolic profiling studies is limited by substantially incomplete commercial and academic databases. Statistical significance tests, including p-values, VIP scores, AUC values and FC values, can be largely inconsistent. Data normalization prior to statistical analysis can cause erroneous outcomes.OBJECTIVES: The objectives were (1) to quantitatively assess consistency among p-values, VIP scores, AUC values and FC values in representative NMR-based metabolic profiling datasets, (2) to assess how data normalization can impact statistical significance outcomes, (3) to determine resonance peak assignment completion potential using commonly used databases and (4) to analyze intersection and uniqueness of metabolite space in these databases.METHODS: P-values, VIP scores, AUC values and FC values, and their dependence on data normalization, were determined in orthotopic mouse model of pancreatic cancer and two human pancreatic cancer cell lines. Completeness of resonance assignments were evaluated using Chenomx, the human metabolite database (HMDB) and the COLMAR database. The intersection and uniqueness of the databases was quantified.RESULTS: P-values and AUC values were strongly correlated compared to VIP or FC values. Distributions of statistically significant bins depended strongly on whether or not datasets were normalized. 40-45% of peaks had either no or ambiguous database matches. 9-22% of metabolites were unique to each database.CONCLUSIONS: Lack of consistency in statistical analyses of metabolomics data can lead to misleading or inconsistent interpretation. Data normalization can have large effects on statistical analysis and should be justified. About 40% of peak assignments remain ambiguous or impossible with current databases. 1D and 2D databases should be made consistent to maximize metabolite assignment confidence and validation.PMID:37378680 | DOI:10.1007/s11306-023-02027-5

Mol Carcinog. 2023 Jun 28. doi: 10.1002/mc.23597. Online ahead of print.ABSTRACTMany cancers, including melanoma, have a higher requirement for l-methionine in comparison with noncancerous cells. In this study, we show that administration of an engineered human methionine-γ-lyase (hMGL) significantly reduced the survival of both human and mouse melanoma cells in vitro. A multiomics approach was utilized to identify global changes in gene expression and in metabolite levels with hMGL treatment in melanoma cells. There was considerable overlap in the perturbed pathways identified in the two data sets. Common pathways were flagged for further investigation to understand their mechanistic importance. In this regard, hMGL treatment induced S and G2 phase cell cycle arrest, decreased nucleotide levels, and increased DNA double-strand breaks suggesting an important role for replication stress in the mechanism of hMGL effects on melanoma cells. Further, hMGL treatment resulted in increased cellular reactive oxygen species levels and increased apoptosis as well as uncharged transfer RNA pathway upregulation. Finally, treatment with hMGL significantly inhibited the growth of both mouse and human melanoma cells in orthotopic tumor models in vivo. Overall, the results of this study provide a strong rationale for further mechanistic evaluation and clinical development of hMGL for the treatment of melanoma skin cancer and other cancers.PMID:37378415 | DOI:10.1002/mc.23597

Front Cardiovasc Med. 2023 Jun 12;10:1191303. doi: 10.3389/fcvm.2023.1191303. eCollection 2023.ABSTRACTProprotein convertase subtilisin/kexin type 9 (PCSK9), one of the key regulators of the low-density lipoprotein receptor (LDLR), can play a direct role in atheroma development. Although advances in the understandings of genetic PCSK9 polymorphisms have enabled to reveal the role of PCSK9 in the complex pathophysiology of cardiovascular diseases (CVDs), increasing lines of evidence support non-cholesterol-related processes mediated by PCSK9. Owing to major improvements in mass spectrometry-based technologies, multimarker proteomic and lipidomic panels hold the promise to identify novel lipids and proteins potentially related to PCSK9. Within this context, this narrative review aims to provide an overview of the most significant proteomics and lipidomics studies related to PCSK9 effects beyond cholesterol lowering. These approaches have enabled to unveil non-common targets of PCSK9, potentially leading to the development of novel statistical models for CVD risk prediction. Finally, in the era of precision medicine, we have reported the impact of PCSK9 on extracellular vesicles (EVs) composition, an effect that could contribute to an increased prothrombotic status in CVD patients. The possibility to modulate EVs release and cargo could help counteract the development and progression of the atherosclerotic process.PMID:37378405 | PMC:PMC10291627 | DOI:10.3389/fcvm.2023.1191303

iScience. 2023 May 23;26(6):106960. doi: 10.1016/j.isci.2023.106960. eCollection 2023 Jun 16.ABSTRACTBy a survey of metagenome-wide association studies (MWAS), we found a robust depletion of Bacteroides cellulosilyticus, Faecalibacterium prausnitzii, and Roseburia intestinalis in individuals with atherosclerotic cardiovascular disease (ACVD). From an established collection of bacteria isolated from healthy Chinese individuals, we selected B. cellulosilyticus, R. intestinalis, and Faecalibacterium longum, a bacterium related to F. prausnitzii, and tested the effects of these bacteria in an Apoe/- atherosclerosis mouse model. We show that administration of these three bacterial species to Apoe-/- mice robustly improves cardiac function, reduces plasma lipid levels, and attenuates the formation of atherosclerotic plaques. Comprehensive analysis of gut microbiota, plasma metabolome, and liver transcriptome revealed that the beneficial effects are associated with a modulation of the gut microbiota linked to a 7α-dehydroxylation-lithocholic acid (LCA)-farnesoid X receptor (FXR) pathway. Our study provides insights into transcriptional and metabolic impact whereby specific bacteria may hold promises for prevention/treatment of ACVD.PMID:37378328 | PMC:PMC10291474 | DOI:10.1016/j.isci.2023.106960

Front Immunol. 2023 Jun 12;14:1188257. doi: 10.3389/fimmu.2023.1188257. eCollection 2023.ABSTRACTIdiopathic inflammatory myopathy (IIM) is a heterogeneous group of autoimmune diseases with various clinical manifestations, treatment responses, and prognoses. According to the clinical manifestations and presence of different myositis-specific autoantibodies (MSAs), IIM is classified into several major subgroups, including PM, DM, IBM, ASS, IMNM, and CADM. However, the pathogenic mechanisms of these subgroups remain unclear and need to be investigated. Here, we applied MALDI-TOF-MS to examine the serum metabolome of 144 patients with IIM and analyze differentially expressed metabolites among IIM subgroups or MSA groups. The results showed that the DM subgroup had lower activation of the steroid hormone biosynthesis pathway, while the non-MDA5 MSA group had higher activation of the arachidonic acid metabolism pathway. Our study may provide some insights into the heterogeneous mechanisms of IIM subgroups, potential biomarkers, and management of IIM.PMID:37377960 | PMC:PMC10291268 | DOI:10.3389/fimmu.2023.1188257

Front Pharmacol. 2023 Jun 12;14:1228923. doi: 10.3389/fphar.2023.1228923. eCollection 2023.ABSTRACT[This corrects the article DOI: 10.3389/fphar.2023.1021535.].PMID:37377931 | PMC:PMC10292008 | DOI:10.3389/fphar.2023.1228923

Front Pharmacol. 2023 Jun 12;14:1203349. doi: 10.3389/fphar.2023.1203349. eCollection 2023.ABSTRACTBackground: Alzheimer's disease (AD), the most prevalent form of dementia, is a debilitating, progressive neurodegeneration. Amino acids play a wide variety of physiological and pathophysiological roles in the nervous system, and their levels and disorders related to their synthesis have been related to cognitive impairment, the core feature of AD. Our previous multicenter trial showed that hachimijiogan (HJG), a traditional Japanese herbal medicine (Kampo), has an adjuvant effect for Acetylcholine estelase inhibitors (AChEIs) and that it delays the deterioration of the cognitive dysfunction of female patients with mild AD. However, there are aspects of the molecular mechanism(s) by which HJG improves cognitive dysfunction that remain unclear. Objectives: To elucidate through metabolomic analysis the mechanism(s) of HJG for mild AD based on changes in plasma metabolites. Methods: Sixty-seven patients with mild AD were randomly assigned to either an HJG group taking HJG extract 7.5 g/day in addition to AChEI or to a control group treated only with AChEI (HJG:33, Control:34). Blood samples were collected before, 3 months, and 6 months after the first drug administration. Comprehensive metabolomic analyses of plasma samples were done by optimized LC-MS/MS and GC-MS/MS methods. The web-based software MetaboAnalyst 5.0 was used for partial least square-discriminant analysis (PLS-DA) to visualize and compare the dynamics of changes in the concentrations of the identified metabolites. Results: The VIP (Variable Importance in Projection) score of the PLS-DA analysis of female participants revealed a significantly higher increase in plasma metabolite levels after HJG administration for 6 months than was seen in the control group. In univariate analysis, the aspartic acid level of female participants showed a significantly higher increase from baseline after HJG administration for 6 months when compared with the control group. Conclusion: Aspartic acid was a major contributor to the difference between the female HJG and control group participants of this study. Several metabolites were shown to be related to the mechanism of HJG effectiveness for mild AD.PMID:37377927 | PMC:PMC10292017 | DOI:10.3389/fphar.2023.1203349

Front Mol Biosci. 2023 Jun 12;10:1161036. doi: 10.3389/fmolb.2023.1161036. eCollection 2023.ABSTRACTBackground: Chronic kidney disease (CKD) is characterized by the progressive and irreversible deterioration of kidney function and structure with the appearance of renal fibrosis. A significant decrease in mitochondrial metabolism, specifically a reduction in fatty acid oxidation (FAO) in tubular cells, is observed in tubulointerstitial fibrosis, whereas FAO enhancement provides protection. Untargeted metabolomics offers the potential to provide a comprehensive analysis of the renal metabolome in the context of kidney injury. Methodology: Renal tissue from a carnitine palmitoyl transferase 1a (Cpt1a) overexpressing mouse model, which displays enhanced FAO in the renal tubule, subjected to folic acid nephropathy (FAN) was studied through a multiplatform untargeted metabolomics approach based on LC-MS, CE-MS and GC-MS analysis to achieve the highest coverage of the metabolome and lipidome affected by fibrosis. The expression of genes related to the biochemical routes showing significant changes was also evaluated. Results: By combining different tools for signal processing, statistical analysis and feature annotation, we were able to identify variations in 194 metabolites and lipids involved in many metabolic routes: TCA cycle, polyamines, one-carbon metabolism, amino acid metabolism, purine metabolism, FAO, glycerolipids and glycerophospholipids synthesis and degradation, glycosphingolipids interconversion, and sterol metabolism. We found several metabolites strongly altered by FAN, with no reversion induced by Cpt1a overexpression (v.g. citric acid), whereas other metabolites were influenced by CPT1A-induced FAO (v.g. glycine-betaine). Conclusion: It was implemented a successful multiplatform metabolomics approach for renal tissue analysis. Profound metabolic changes accompany CKD-associated fibrosis, some associated with tubular FAO failure. These results highlight the importance of addressing the crosstalk between metabolism and fibrosis when undertaking studies attempting to elucidate the mechanism of CKD progression.PMID:37377862 | PMC:PMC10291237 | DOI:10.3389/fmolb.2023.1161036

Front Plant Sci. 2023 Jun 12;14:1172028. doi: 10.3389/fpls.2023.1172028. eCollection 2023.ABSTRACTCereal grains have been domesticated largely from food grains to feed and malting grains. Barley (Hordeum vulgare L.) remains unparalleled in its success as a primary brewing grain. However, there is renewed interest in "alternative" grains for brewing (and distilling) due to attention being placed on flavor, quality, and health (i.e., gluten issues) aspects that they may offer. This review covers basic and general information on "alternative grains" for malting and brewing, as well as an in-depth look at several major biochemical aspects of these grains including starch, protein, polyphenols, and lipids. These traits are described in terms of their effects on processing and flavor, as well as the prospects for improvement through breeding. These aspects have been studied extensively in barley, but little is known about the functional properties in other crops for malting and brewing. In addition, the complex nature of malting and brewing produces a large number of brewing targets but requires extensive processing, laboratory analysis, and accompanying sensory analysis. However, if a better understanding of the potential of alternative crops that can be used in malting and brewing is needed, then significantly more research is required.PMID:37377804 | PMC:PMC10291334 | DOI:10.3389/fpls.2023.1172028

Front Plant Sci. 2023 Jun 12;14:1166813. doi: 10.3389/fpls.2023.1166813. eCollection 2023.ABSTRACTStem rust caused by the pathogen Puccinia graminis f. sp. tritici is a destructive fungal disease-causing major grain yield losses in wheat. Therefore, understanding the plant defence regulation and function in response to the pathogen attack is required. As such, an untargeted LC-MS-based metabolomics approach was employed as a tool to dissect and understand the biochemical responses of Koonap (resistant) and Morocco (susceptible) wheat varieties infected with two different races of P. graminis (2SA88 [TTKSF] and 2SA107 [PTKST]). Data was generated from the infected and non-infected control plants harvested at 14- and 21- days post-inoculation (dpi), with 3 biological replicates per sample under a controlled environment. Chemo-metric tools such as principal component analysis (PCA), orthogonal projection to latent structures-discriminant analysis (OPLS-DA) were used to highlight the metabolic changes using LC-MS data of the methanolic extracts generated from the two wheat varieties. Molecular networking in Global Natural Product Social (GNPS) was further used to analyse biological networks between the perturbed metabolites. PCA and OPLS-DA analysis showed cluster separations between the varieties, infection races and the time-points. Distinct biochemical changes were also observed between the races and time-points. Metabolites were identified and classified using base peak intensities (BPI) and single ion extracted chromatograms from samples, and the most affected metabolites included flavonoids, carboxylic acids and alkaloids. Network analysis also showed high expression of metabolites from thiamine and glyoxylate, such as flavonoid glycosides, suggesting multi-faceted defence response strategy by understudied wheat varieties towards P. graminis pathogen infection. Overall, the study provided the insights of the biochemical changes in the expression of wheat metabolites in response to stem rust infection.PMID:37377801 | PMC:PMC10292758 | DOI:10.3389/fpls.2023.1166813