PubMed

J Chromatogr A. 2024 Jun 8;1730:465060. doi: 10.1016/j.chroma.2024.465060. Online ahead of print.ABSTRACTHydrophilic interaction (liquid) chromatography (HILIC) has become the first choice LC mode for the separation of hydrophilic analytes. Numerous studies reported the poor retention time repeatability of HILIC. The problem was often ascribed to slow equilibration and insufficient re-equilibration time to establish the sensitive semi-immobilized water layer at the interface of the polar stationary phase and the bulk mobile phase. In this study, we compare retention time repeatability in HILIC for borosilicate glass and PFA (co-polymer of tetrafluoroethylene and perfluoroalkoxyethylene) solvent bottles. During this study, we observed peak patterns shifting towards higher retention times (for metabolites and peptides) and lower retention times (oligonucleotide sample) with ongoing analysis time when standard borosilicate glass bottles were used as solvent reservoirs. It was hypothesized that release of ions (sodium, potassium, borate, etc.) from the borosilicate glass bottles leads to alterations (thickness and electrostatic screening effects) in the semi-immobilized water layer which is adsorbed to the polar stationary phase surface under acetonitrile-rich eluents in HILIC with concomitant shifts in retention. When PFA solvent bottles were employed instead of borosilicate glass, retention time repeatability was greatly improved and changed from average 8.4 % RSD for the tested metabolites with borosilicate glass bottles to 0.14 % RSD for the PFA solvent bottles (30 injections over 12 h). Similar improvements were observed for peptides and oligonucleotides. This simple solution to the retention time repeatability problem in HILIC might contribute to a better acceptance of HILIC, especially in fields like targeted and untargeted metabolomics, peptide and oligonucleotide analysis.PMID:38861823 | DOI:10.1016/j.chroma.2024.465060

Lung. 2024 Jun 11. doi: 10.1007/s00408-024-00712-3. Online ahead of print.ABSTRACTBACKGROUND: Fibrotic interstitial lung disease is often identified late due to non-specific symptoms, inadequate access to specialist care, and clinical unawareness precluding proper and timely treatment. Biopsy histological analysis is definitive but rarely performed due to its invasiveness. Diagnosis typically relies on high-resolution computed tomography, while disease progression is evaluated via frequent pulmonary function testing. This study tested the hypothesis that pulmonary fibrosis diagnosis and progression could be non-invasively and accurately evaluated from the hair metabolome, with the longer-term goal to minimize patient discomfort.METHODS: Hair specimens collected from pulmonary fibrosis patients (n = 56) and healthy subjects (n = 14) were processed for metabolite extraction using 2DLC/MS-MS, and data were analyzed via machine learning. Metabolomic data were used to train machine learning classification models tuned via a rigorous combination of cross validation, feature selection, and testing with a hold-out dataset to evaluate classifications of diseased vs. healthy subjects and stable vs. progressed disease.RESULTS: Prediction of pulmonary fibrosis vs. healthy achieved AUROCTRAIN = 0.888 (0.794-0.982) and AUROCTEST = 0.908, while prediction of stable vs. progressed disease achieved AUROCTRAIN = 0.833 (0.784 - 0.882) and AUROCTEST = 0. 799. Top metabolites for diagnosis included ornithine, 4-(methylnitrosamino)-1-3-pyridyl-N-oxide-1-butanol, Thr-Phe, desthiobiotin, and proline. Top metabolites for progression included azelaic acid, Thr-Phe, Ala-Tyr, indoleacetyl glutamic acid, and cytidine.CONCLUSION: This study provides novel evidence that pulmonary fibrosis diagnosis and progression may in principle be evaluated from the hair metabolome. Longer term, this approach may facilitate non-invasive and accurate detection and monitoring of fibrotic lung diseases.PMID:38861171 | DOI:10.1007/s00408-024-00712-3

Methods Mol Biol. 2024;2792:223-240. doi: 10.1007/978-1-0716-3802-6_18.ABSTRACTPlant science has become more and more complex. With the introduction of new experimental techniques and technologies, it is now possible to explore the fine details of plant metabolism. Besides steady-state measurements often applied in gas-exchange or metabolomic analyses, new approaches, e.g., based on 13C labeling, are now available to understand the changes in metabolic concentrations under fluctuating environmental conditions in the field or laboratory. To explore those transient phenomena of metabolite concentrations, kinetic models are a valuable tool. In this chapter, we describe ways to implement and build kinetic models of plant metabolism with the Python software package modelbase. As an example, we use a part of the photorespiratory pathway. Moreover, we show additional functionalities of modelbase that help to explore kinetic models and thus can reveal information about a biological system that is not easily accessible to experiments. In addition, we will point to extra information on the mathematical background of kinetic models to give an impetus for further self-study.PMID:38861091 | DOI:10.1007/978-1-0716-3802-6_18

Microbiol Spectr. 2024 Jun 11:e0352423. doi: 10.1128/spectrum.03524-23. Online ahead of print.ABSTRACTGluten possesses unique properties that render it only partially digestible. Consequently, it exerts detrimental effects on a part of the worldwide population who are afflicted with celiac disease (1%) or related disorders (5%), particularly due to the potential for cross-contamination even when adhering to a gluten-free diet (GFD). Finding solutions to break down gluten during digestion has a high nutritional and social impact. Here, a randomized double-blind placebo-controlled in vivo challenge investigated the gluten-degrading activity of a novel probiotic preparation comprising lactobacilli and their cytoplasmic extracts, Bacillus sp., and bacterial protease. In our clinical trial, we collected feces from 70 healthy volunteers at specific time intervals. Probiotic/placebo administration lasted 32 days, followed by 10 days of wash-out. After preliminary GFD to eliminate residual gluten from feces, increasing amounts of gluten (50 mg-10 g) were administered, each one for 4 consecutive days. Compared to placebo, the feces of volunteers fed with probiotics showed much lower amounts of residual gluten, mainly with increased intakes. Probiotics also regulate the intestinal microbial communities, improving the abundance of genera pivotal to maintaining homeostasis. Quantitative PCR confirmed that all probiotics persisted during the intervention, some also during wash-out. Probiotics promoted a fecal metabolome with potential immunomodulating activity, mainly related to derivatives of branched-chain amino acids and short-chain fatty acids.IMPORTANCE: The untapped potential of gluten-degrading bacteria and their application in addressing the recognized limitations of gluten-related disorder management and the ongoing risk of cross-contamination even when people follow a gluten-free diet (GFD) emphasizes the significance of the work. Because gluten, a common protein found in many cereals, must be strictly avoided to stop autoimmune reactions and related health problems, celiac disease and gluten sensitivity present difficult hurdles. However, because of the hidden presence of gluten in many food products and the constant danger of cross-contamination during food preparation and processing, total avoidance is frequently challenging. Our study presents a novel probiotic preparation suitable for people suffering from gluten-related disorders during GFD and for healthy individuals because it enhances gluten digestion and promotes gut microbiota functionality.PMID:38860826 | DOI:10.1128/spectrum.03524-23

J Cardiovasc Surg (Torino). 2024 Jun 11. doi: 10.23736/S0021-9509.24.13062-5. Online ahead of print.ABSTRACTINTRODUCTION: This systematic review aimed to discuss the current knowledge of possibly useful circulatory biomarkers (other than D-dimers) in the diagnosis of patients with an acute aortic dissection (AAD), to distinguish these patients from patients with Acute Myocardial Infarction (AMI).EVIDENCE ACQUISITION: This study followed the PRISMA guidelines. The databases PubMed, EMBASE and Scopus were systematically searched from inception to May 2023. Studies were included if they presented measurements of biomarker(s) in the blood/plasma/serum samples from adult patients with AAD versus AMI. Articles were excluded if aortic dissection was subacute or chronic (>14 days), if they lack a control group (AMI), or if they were animal studies, revisions, or editorials. The main outcome was the identification of biomarkers that exhibited diagnostic potential to differentiate patients with AAD versus AMI.EVIDENCE SYNTHESIS: The research query resulted in 1342 articles after the removal of duplicates, from which seven were included in the systematic review. The biomarkers identified included general blood assessment, metabolomics, products of the degradation of fibrin, extracellular matrix markers and an ischemia-associated molecule. Most studies lack diagnostic validity such as sensitivity and specificity. In six studies, the concentration of a total of six biomarkers showed significative differences between AAD and AMI group.CONCLUSIONS: A great heterogeneity of molecules has been studied as putative diagnostic markers of AAD versus AMI. Studies of better quality are needed, presenting the diagnostic validity of the molecules under analysis and the putative synergic diagnostic value of the molecules identified so far.PMID:38860700 | DOI:10.23736/S0021-9509.24.13062-5

Environ Sci Technol. 2024 Jun 11. doi: 10.1021/acs.est.4c01328. Online ahead of print.ABSTRACTMicrobial organic matter turnover is an important contributor to the terrestrial carbon dioxide (CO2) budget. Partitioning of organic carbons into biomass relative to CO2 efflux, termed carbon-use efficiency (CUE), is widely used to characterize organic carbon cycling by soil microorganisms. Recent studies challenge proposals of CUE dependence on the oxidation state of the substrate carbon and implicate instead metabolic strategies. Still unknown are the metabolic mechanisms underlying variability in CUE. We performed a multiomics investigation of these mechanisms in Pseudomonas putida, a versatile soil bacterium of the Gammaproteobacteria, processing a mixture of plant matter derivatives. Our 13C-metabolomics data captured substrate carbons into different metabolic pathways: cellulose-derived sugar carbons in glycolytic and pentose-phosphate pathways; lignin-related aromatic carbons in the tricarboxylic acid cycle. Subsequent 13C-metabolic flux analysis revealed a 3-fold lower investment of sugar carbons in CO2 efflux compared to aromatic carbons, in agreement with reported substrate-dependent CUE. Proteomics analysis revealed enzyme-level regulation only for substrate uptake and initial catabolism, which dictated downstream fluxes through CO2-producing versus biomass-synthesizing reactions. Metabolic partitioning as shown here explained the substrate-dependent CUE calculated from reported metabolic flux analyses of other bacteria, further supporting a metabolism-guided perspective for predicting the microbial conversion of accessible organic matter to CO2 efflux.PMID:38860668 | DOI:10.1021/acs.est.4c01328

Mol Genet Genomic Med. 2024 Jun;12(6):e2472. doi: 10.1002/mgg3.2472.ABSTRACTBACKGROUND: Serine residues in the protein backbone of heavily glycosylated proteoglycans are bound to glycosaminoglycans through a tetrasaccharide linker. UXS1 encodes UDP-glucuronate decarboxylase 1, which catalyzes synthesis of UDP-xylose, the donor of the first building block in the linker. Defects in other enzymes involved in formation of the tetrasaccharide linker cause so-called linkeropathies, characterized by short stature, radio-ulnar synostosis, decreased bone density, congenital contractures, dislocations, and more.METHODS: Whole exome sequencing was performed in a father and son who presented with a mild skeletal dysplasia, as well as the father's unaffected parents. Wild-type and mutant UXS1 were recombinantly expressed in Escherichia coli and purified. Enzyme activity was evaluated by LC-MS/MS. In vivo effects were studied using HeparinRed assay and metabolomics.RESULTS: The son had short long bones, normal epiphysis, and subtle metaphyseal changes especially in his legs. The likely pathogenic heterozygous variant NM_001253875.1(UXS1):c.557T>A p.(Ile186Asn) detected in the son was de novo in the father. Purified Ile186Asn-UXS1, in contrast to the wild-type, was not able to convert UDP-glucuronic acid to UDP-xylose. Plasma glycosaminoglycan levels were decreased in both son and father.CONCLUSION: This is the first report linking UXS1 to short-limbed short stature in humans.PMID:38860481 | DOI:10.1002/mgg3.2472

Front Microbiol. 2024 May 27;15:1391059. doi: 10.3389/fmicb.2024.1391059. eCollection 2024.ABSTRACTPlant-microbe interactions are pivotal for ecosystem dynamics and sustainable agriculture, and are influenced by various factors, such as host characteristics, environmental conditions, and human activities. Omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, have revolutionized our understanding of these interactions. Genomics elucidates key genes, transcriptomics reveals gene expression dynamics, proteomics identifies essential proteins, and metabolomics profiles small molecules, thereby offering a holistic perspective. This review synthesizes diverse microbial-plant interactions, showcasing the application of omics in understanding mechanisms, such as nitrogen fixation, systemic resistance induction, mycorrhizal association, and pathogen-host interactions. Despite the challenges of data integration and ethical considerations, omics approaches promise advancements in precision intervention and resilient agricultural practices. Future research should address data integration challenges, enhance omics technology resolution, explore epigenomics, and understand plant-microbe dynamics under diverse conditions. In conclusion, omics technologies hold immense promise for optimizing agricultural strategies and fortifying resilient plant-microbe alliances, paving the way for sustainable agriculture and environmental stewardship.PMID:38860224 | PMC:PMC11163067 | DOI:10.3389/fmicb.2024.1391059

Front Microbiol. 2024 May 27;15:1416235. doi: 10.3389/fmicb.2024.1416235. eCollection 2024.ABSTRACTOur previous studies have revealed that L. acidophilus possesses inhibitory effects on PCV2 proliferation in vivo, although the underlying mechanisms remain elusive. Probiotics like L. acidophilus are known to exert antiviral through their metabolites. Therefore, in this study, non-targeted metabolomics was used to detect the changes in metabolites of L. acidophilus after 24 h of proliferation. Subsequently, high-throughput molecular docking was utilized to analyze the docking scores of these metabolites with PCV2 Cap and Rep, aiming to identify compounds with potential anti-PCV2 effects. The results demonstrated that 128 compounds such as Dl-lactate were significantly increased. The results of high-throughput molecular docking indicated that compounds such as ergocristine, and telmisartan formed complexes with Cap and Rep, suggesting their potential anti-PCV2 properties. Furthermore, compounds like vitamin C, exhibit pharmacological effects consistent with L. acidophilus adding credence to the idea that L. acidophilus may exert pharmacological effects through its metabolites. These results will provide a foundation for the study of L. acidophilus.PMID:38860222 | PMC:PMC11163031 | DOI:10.3389/fmicb.2024.1416235

Front Pharmacol. 2024 May 27;15:1284752. doi: 10.3389/fphar.2024.1284752. eCollection 2024.ABSTRACTBACKGROUND: Both Sophora flavescens (SF) and Astragalus mongholicus (AM) are known for their anti-inflammatory, antifibrotic, and anticancer activities. However, the efficacy, multi-target mechanisms, and therapeutic substances of SF-AM herb pair on the progression of hepatitis-cirrhosis-hepatocellular carcinoma hepatocellular carcinoma (HCC) remain unclear.PURPOSE: To investigate the efficacy, mechanisms, and potential therapeutic substances of SF-AM herb pair in the progression of hepatitis-cirrhosis-HCC.METHODS: Firstly, diethylnitrosamine was used to establish the hepatitis-cirrhosis-HCC model. HE staining and non-targeted metabolomics were used to evaluate the efficacy of SF-AM herb pair. Subsequently, the absorbed components of SF-AM herb pair in the plasma of rats were determined through HPLC-Q-TOF-MS/MS analysis. Flow cytometry, Western blot, and qRT-PCR were then employed to assess CD4+ and CD8+ T lymphocytes, PI3K/Akt signaling pathway-related proteins, and their corresponding mRNAs. Simultaneously, the efficacy and mechanism of SF-AM herb pair on HCC were confirmed by in vitro experiments. Finally, Pearson correlation analysis was performed between pharmacodynamic indicators and in vivo components to identify the potential therapeutic substances of SF-AM herb pair.RESULTS: SF-AM herb pair can alleviate the pathological damage and reverse metabolic abnormalities in hepatitis, cirrhosis, and HCC rats, particularly during the hepatitis and cirrhosis stages. Pharmacological researches have demonstrated that SF-AM herb pair can increase the proportion of CD8+ T lymphocytes, inhibit the expression of PI3K, Akt, p-Akt, NF-κB p65, NF-κB pp65, and Bcl-2, as well as increase the expression of IκBα, Bax, and cleaved caspase-3. These findings suggest that SF-AM herb pair has the ability to enhance immunity, anti-inflammation and promote apoptosis. Cell experiments have shown that SF-AM herb pair can inhibit the proliferation of HepG2 cell and regulate the PI3K/Akt signaling pathway. Moreover, 23 absorbed prototypical components and 53 metabolites of SF-AM herb pair were identified at different stages of HCC rats. Pearson correlation analysis revealed that matrine, cytisine, wogonoside, and isoastragaloside are potential therapeutic substances in SF-AM herb pair for the prevention and treatment of hepatitis, cirrhosis, and HCC.CONCLUSION: In summary, this study revealed the efficacy, mechanisms, and potential therapeutic substances of SF-AM herb pair in the hepatitis-cirrhosis-HCC axis and provided a reference for its clinical application.PMID:38860166 | PMC:PMC11163057 | DOI:10.3389/fphar.2024.1284752

Front Physiol. 2024 May 27;15:1396212. doi: 10.3389/fphys.2024.1396212. eCollection 2024.ABSTRACTIntroduction: European mistletoe (Viscum album L.) has been gaining increasing interest in the field of oncology as a clinically relevant adjunctive treatment in many forms of cancer. In the field of phytopharmacology, harvesting time is pivotal. In the last century, a form of metabolomic fingerprinting based on pattern formation was proposed as a way to determine optimal harvesting times to ensure high quality of mistletoe as raw material for pharmaceutical use. In order to further evaluate the information obtained with this metabolomic fingerprinting method, we analysed a large time series of previously undigitised daily mistletoe chromatograms dating back to the 1950s. Methods: These chromatograms were scanned and evaluated using computerized image analysis, resulting in 12 descriptors for each individual chromatogram. We performed a statistical analysis of the data obtained, investigating statistical distributions, cross-correlations and time self-correlations. Results: The analysed dataset spanning about 27 years, contains 19,037 evaluable chromatograms in daily resolution. Based on the distribution and cross-correlation analyses, the 12 descriptors could be clustered into six independent groups describing different aspects of the chromatograms. One descriptor was found to mirror the annual rhythm being well correlated with temperature and a phase shift of 10 days. The time self-correlation analysis showed that most other descriptors had a characteristic self-correlation of ∼50 days, which points to further infradian rhythms (i.e., more than 24 h). Discussion: To our knowledge, this dataset is the largest of its type. The combination of this form of metabolomic fingerprinting with the proposed computer analysis seems to be a promising tool to characterise biological variations of mistletoe. Additional research is underway to further analyse the different rhythms present in this dataset.PMID:38860114 | PMC:PMC11163206 | DOI:10.3389/fphys.2024.1396212

Clin Kidney J. 2024 Apr 24;17(6):sfae108. doi: 10.1093/ckj/sfae108. eCollection 2024 Jun.ABSTRACTBACKGROUND: There is interest in identifying novel filtration markers that lead to more accurate GFR estimates than current markers (creatinine and cystatin C) and are more consistent across demographic groups. We hypothesize that large-scale metabolomics can identify serum metabolites that are strongly influenced by glomerular filtration rate (GFR) and are more consistent across demographic variables than creatinine, which would be promising filtration markers for future investigation.METHODS: We evaluated the consistency of associations between measured GFR (mGFR) and 887 common, known metabolites quantified by an untargeted chromatography- and spectroscopy-based metabolomics platform (Metabolon) performed on frozen blood samples from 580 participants in Chronic Kidney Disease in Children (CKiD), 674 participants in Modification of Diet in Renal Disease (MDRD) Study and 962 participants in African American Study of Kidney Disease and Hypertension (AASK). We evaluated metabolite-mGFR correlation association with metabolite class, molecular weight, assay platform and measurement coefficient of variation (CV). Among metabolites with strong negative correlations with mGFR (r < -0.5), we assessed additional variation by age (height in children), sex, race and body mass index (BMI).RESULTS: A total of 561 metabolites (63%) were negatively correlated with mGFR. Correlations with mGFR were highly consistent across study, sex, race and BMI categories (correlation of metabolite-mGFR correlations between 0.88 and 0.95). Amino acids, carbohydrates and nucleotides were more often negatively correlated with mGFR compared with lipids, but there was no association with metabolite molecular weight, liquid chromatography/mass spectrometry platform and measurement CV. Among 114 metabolites with strong negative associations with mGFR (r < -0.5), 27 were consistently not associated with age (height in children), sex or race.CONCLUSIONS: The majority of metabolite-mGFR correlations were negative and consistent across sex, race, BMI and study. Metabolites with consistent strong negative correlations with mGFR and non-association with demographic variables may represent candidate markers to improve estimation of GFR.PMID:38859934 | PMC:PMC11163224 | DOI:10.1093/ckj/sfae108

Int J Biol Markers. 2024 Jun 11:3936155241258780. doi: 10.1177/03936155241258780. Online ahead of print.ABSTRACTBACKGROUND: Early identification and therapy can significantly improve the outcome for gastric cancer. However, there is still no perfect biomarker available for the detection of early gastric cancer. This study aimed to investigate the alterations in the plasma metabolites of early gastric cancer using metabolomics and lipidomics based on high-performance liquid chromatography-mass spectrometry (HPLC-MS), which detected potential biomarkers that could be used for clinical diagnosis.METHODS: To investigate the changes in metabolomics and lipidomics, a total of 30 plasma samples were collected, consisting of 15 patients with early gastric cancer and 15 healthy controls. Extensive HPLC-MS-based untargeted metabolomic and lipidomic investigations were conducted. Differential metabolites and metabolic pathways were uncovered through the utilization of statistical analysis and bioinformatics analysis. Candidate biomarker screening was performed using support vector machine-based multivariate receiver operating characteristic analysis.RESULTS: A disturbance was observed in a combined total of 19 metabolites and 67 lipids of the early gastric cancer patients. The analysis of KEGG pathways showed that the early gastric cancer patients experienced disruptions in the arginine biosynthesis pathway, the pathway for alanine, aspartate, and glutamate metabolism, as well as the pathway for glyoxylate and dicarboxylate metabolism. Plasma metabolomics and lipidomics have identified multiple biomarker panels that can effectively differentiate early gastric cancer patients from healthy controls, exhibiting an area under the curve exceeding 0.9.CONCLUSION: These metabolites and lipids could potentially serve as biomarkers for the screening of early gastric cancer, thereby optimizing the strategy for the detection of early gastric cancer. The disrupted pathways implicated in early gastric cancer provide new clues for additional understanding of gastric cancer's pathogenesis. Nonetheless, large-scale clinical data are required to prove our findings.PMID:38859802 | DOI:10.1177/03936155241258780

Brief Bioinform. 2024 May 23;25(4):bbae264. doi: 10.1093/bib/bbae264.ABSTRACTHow to resolve the metabolic dark matter of microorganisms has long been a challenging problem in discovering active molecules. Diverse omics tools have been developed to guide the discovery and characterization of various microbial metabolites, which make it gradually possible to predict the overall metabolites for individual strains. The combinations of multi-omic analysis tools effectively compensates for the shortcomings of current studies that focus only on single omics or a broad class of metabolites. In this review, we systematically update, categorize and sort out different analysis tools for microbial metabolites prediction in the last five years to appeal for the multi-omic combination on the understanding of the metabolic nature of microbes. First, we provide the general survey on different updated prediction databases, webservers, or software that based on genomics, transcriptomics, proteomics, and metabolomics, respectively. Then, we discuss the essentiality on the integration of multi-omics data to predict metabolites of different microbial strains and communities, as well as stressing the combination of other techniques, such as systems biology methods and data-driven algorithms. Finally, we identify key challenges and trends in developing multi-omic analysis tools for more comprehensive prediction on diverse microbial metabolites that contribute to human health and disease treatment.PMID:38859767 | DOI:10.1093/bib/bbae264

Mol Med. 2024 Jun 10;30(1):80. doi: 10.1186/s10020-024-00850-7.ABSTRACTBACKGROUND: Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease that commonly results from a high-calorie diet and sedentary lifestyle, leading to insulin resistance and glucose homeostasis perturbation. Physical activity is recommended as one first-line treatment in T2DM, but it leads to contrasted results. We hypothesized that, instead of applying standard exercise protocols, the prescription of personalized exercise programs specifically designed to reverse the potential metabolic alterations in skeletal muscle could result in better results.METHODS: To test this hypothesis, we drew the metabolic signature of the fast-twitch quadriceps muscle, based on a combined unbiased NMR spectroscopy and RT-qPCR study, in several T2DM mouse models of different genetic background (129S1/SvImJ, C57Bl/6J), sex and aetiology (high-fat diet (HFD) or HFD/Streptozotocin (STZ) induction or transgenic MKR (FVB-Tg Ckm-IGF1R*K1003R)1Dlr/J) mice. Three selected mouse models with unique muscular metabolic signatures were submitted to three different swimming-based programs, designed to address each metabolic specificity.RESULTS: We found that depending on the genetic background, the sex, and the mode of T2DM induction, specific muscular adaptations occurred, including depressed glycolysis associated with elevated PDK4 expression, shift to β-oxidation, or deregulation of amino-acid homeostasis. Interestingly, dedicated swimming-based exercises designed to restore specific metabolic alterations in muscle were found optimal in improving systemic T2DM hallmarks, including a significant reduction in insulin resistance, the improvement of glucose homeostasis, and a delay in sensorimotor function alterations.CONCLUSION: The muscle metabolism constitutes an important clue for the design of precision exercises with potential clinical implications for T2DM patients.PMID:38858657 | DOI:10.1186/s10020-024-00850-7

Biomark Res. 2024 Jun 10;12(1):60. doi: 10.1186/s40364-024-00600-1.ABSTRACTAcute myeloid leukemia (AML) is the most frequent leukemia in adults with a high mortality rate. Current diagnostic criteria and selections of therapeutic strategies are generally based on gene mutations and cytogenetic abnormalities. Chemotherapy, targeted therapies, and hematopoietic stem cell transplantation (HSCT) are the major therapeutic strategies for AML. Two dilemmas in the clinical management of AML are related to its poor prognosis. One is the inaccurate risk stratification at diagnosis, leading to incorrect treatment selections. The other is the frequent resistance to chemotherapy and/or targeted therapies. Genomic features have been the focus of AML studies. However, the DNA-level aberrations do not always predict the expression levels of genes and proteins and the latter is more closely linked to disease phenotypes. With the development of high-throughput sequencing and mass spectrometry technologies, studying downstream effectors including RNA, proteins, and metabolites becomes possible. Transcriptomics can reveal gene expression and regulatory networks, proteomics can discover protein expression and signaling pathways intimately associated with the disease, and metabolomics can reflect precise changes in metabolites during disease progression. Moreover, omics profiling at the single-cell level enables studying cellular components and hierarchies of the AML microenvironment. The abundance of data from different omics layers enables the better risk stratification of AML by identifying prognosis-related biomarkers, and has the prospective application in identifying drug targets, therefore potentially discovering solutions to the two dilemmas. In this review, we summarize the existing AML studies using omics methods, both separately and combined, covering research fields of disease diagnosis, risk stratification, prognosis prediction, chemotherapy, as well as targeted therapy. Finally, we discuss the directions and challenges in the application of multi-omics in precision medicine of AML. Our review may inspire both omics researchers and clinical physicians to study AML from a different angle.PMID:38858750 | DOI:10.1186/s40364-024-00600-1

BMC Plant Biol. 2024 Jun 11;24(1):526. doi: 10.1186/s12870-024-05217-y.ABSTRACTLight intensity is a key factor affecting the synthesis of secondary metabolites in plants. However, the response mechanisms of metabolites and genes in Gentiana macrophylla under different light intensities have not been determined. In the present study, G. macrophylla seedlings were treated with LED light intensities of 15 µmol/m2/s (low light, LL), 90 µmol/m2/s (medium light, ML), and 200 µmol/m2/s (high light, HL), and leaves were collected on the 5th day for further investigation. A total of 2162 metabolites were detected, in which, the most abundant metabolites were identified as flavonoids, carbohydrates, terpenoids and amino acids. A total of 3313 and 613 differentially expressed genes (DEGs) were identified in the LL and HL groups compared with the ML group, respectively, mainly enriched in KEGG pathways such as carotenoid biosynthesis, carbon metabolism, glycolysis/gluconeogenesis, amino acids biosynthesis, plant MAPK pathway and plant hormone signaling. Besides, the transcription factors of GmMYB5 and GmbHLH20 were determined to be significantly correlated with loganic acid biosynthesis; the expression of photosystem-related enzyme genes was altered under different light intensities, regulating the expression of enzyme genes involved in the carotenoid, chlorophyll, glycolysis and amino acids pathway, then affecting their metabolic biosynthesis. As a result, low light inhibited photosynthesis, delayed glycolysis, thus, increased certain amino acids and decreased loganic acid production, while high light got an opposite trend. Our research contributed significantly to understand the molecular mechanism of light intensity in controlling metabolic accumulation in G. macrophylla.PMID:38858643 | DOI:10.1186/s12870-024-05217-y

J Transl Med. 2024 Jun 10;22(1):555. doi: 10.1186/s12967-024-05355-9.ABSTRACTBACKGROUND: Astragaloside IV (AST-IV), as an effective active ingredient of Astragalus membranaceus (Fisch.) Bunge. It has been found that AST-IV inhibits the replication of dengue virus, hepatitis B virus, adenovirus, and coxsackievirus B3. Enterovirus 71 (EV71) serves as the main pathogen in severe hand-foot-mouth disease (HFMD), but there are no specific drugs available. In this study, we focus on investigating whether AST-IV can inhibit EV71 replication and explore the potential underlying mechanisms.METHODS: The GES-1 or RD cells were infected with EV71, treated with AST-IV, or co-treated with both EV71 and AST-IV. The EV71 structural protein VP1 levels, the viral titers in the supernatant were measured using western blot and 50% tissue culture infective dose (TCID50), respectively. Network pharmacology was used to predict possible pathways and targets for AST-IV to inhibit EV71 replication. Additionally, ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) was used to investigate the potential targeted metabolites of AST-IV. Associations between metabolites and apparent indicators were performed via Spearman's algorithm.RESULTS: This study illustrated that AST-IV effectively inhibited EV71 replication. Network pharmacology suggested that AST-IV inhibits EV71 replication by targeting PI3K-AKT. Metabolomics results showed that AST-IV achieved these effects by elevating the levels of hypoxanthine, 2-ketobutyric acid, adenine, nicotinic acid mononucleotide, prostaglandin H2, 6-hydroxy-1 H-indole-3- acetamide, oxypurinol, while reducing the levels of PC (14:0/15:0). Furthermore, AST-IV also mitigated EV71-induced oxidative stress by reducing the levels of MDA, ROS, while increasing the activity of T-AOC, CAT, GSH-Px. The inhibition of EV71 replication was also observed when using the ROS inhibitor N-Acetylcysteine (NAC). Additionally, AST-IV exhibited the ability to activate the PI3K-AKT signaling pathway and suppress EV71-induced apoptosis.CONCLUSION: This study suggests that AST-IV may activate the cAMP and the antioxidant stress response by targeting eight key metabolites, including hypoxanthine, 2-ketobutyric acid, adenine, nicotinic acid mononucleotide, prostaglandin H2, 6-Hydroxy-1 H-indole-3-acetamide, oxypurinol and PC (14:0/15:0). This activation can further stimulate the PI3K-AKT signaling to inhibit EV71-induced apoptosis and EV71 replication.PMID:38858642 | DOI:10.1186/s12967-024-05355-9

BMC Genomics. 2024 Jun 10;25(1):580. doi: 10.1186/s12864-024-10325-y.ABSTRACTBACKGROUND: Understanding growth regulatory pathways is important in aquaculture, fisheries, and vertebrate physiology generally. Machine learning pattern recognition and sensitivity analysis were employed to examine metabolomic small molecule profiles and transcriptomic gene expression data generated from liver and white skeletal muscle of hybrid striped bass (white bass Morone chrysops x striped bass M. saxatilis) representative of the top and bottom 10 % by body size of a production cohort.RESULTS: Larger fish (good-growth) had significantly greater weight, total length, hepatosomatic index, and specific growth rate compared to smaller fish (poor-growth) and also had significantly more muscle fibers of smaller diameter (≤ 20 µm diameter), indicating active hyperplasia. Differences in metabolomic pathways included enhanced energetics (glycolysis, citric acid cycle) and amino acid metabolism in good-growth fish, and enhanced stress, muscle inflammation (cortisol, eicosanoids) and dysfunctional liver cholesterol metabolism in poor-growth fish. The majority of gene transcripts identified as differentially expressed between groups were down-regulated in good-growth fish. Several molecules associated with important growth-regulatory pathways were up-regulated in muscle of fish that grew poorly: growth factors including agt and agtr2 (angiotensins), nicotinic acid (which stimulates growth hormone production), gadd45b, rgl1, zfp36, cebpb, and hmgb1; insulin-like growth factor signaling (igfbp1 and igf1); cytokine signaling (socs3, cxcr4); cell signaling (rgs13, rundc3a), and differentiation (rhou, mmp17, cd22, msi1); mitochondrial uncoupling proteins (ucp3, ucp2); and regulators of lipid metabolism (apoa1, ldlr). Growth factors pttg1, egfr, myc, notch1, and sirt1 were notably up-regulated in muscle of good-growing fish.CONCLUSION: A combinatorial pathway analysis using metabolomic and transcriptomic data collectively suggested promotion of cell signaling, proliferation, and differentiation in muscle of good-growth fish, whereas muscle inflammation and apoptosis was observed in poor-growth fish, along with elevated cortisol (an anti-inflammatory hormone), perhaps related to muscle wasting, hypertrophy, and inferior growth. These findings provide important biomarkers and mechanisms by which growth is regulated in fishes and other vertebrates as well.PMID:38858615 | DOI:10.1186/s12864-024-10325-y

Nat Microbiol. 2024 Jun 10. doi: 10.1038/s41564-024-01698-7. Online ahead of print.ABSTRACTDietary intake of phytate has various reported health benefits. Previous work showed that the gut microbiota can convert phytate to short-chain fatty acids (SCFAs), but the microbial species and metabolic pathway are unclear. Here we identified Mitsuokella jalaludinii as an efficient phytate degrader, which works synergistically with Anaerostipes rhamnosivorans to produce the SCFA propionate. Analysis of published human gut taxonomic profiles revealed that Mitsuokella spp., in particular M. jalaludinii, are prevalent in human gut microbiomes. NMR spectroscopy using 13C-isotope labelling, metabolomic and transcriptomic analyses identified a complete phytate degradation pathway in M. jalaludinii, including production of the intermediate Ins(2)P/myo-inositol. The major end product, 3-hydroxypropionate, was converted into propionate via a synergistic interaction with Anaerostipes rhamnosivorans both in vitro and in mice. Upon [13C6]phytate administration, various 13C-labelled components were detected in mouse caecum in contrast with the absence of [13C6] InsPs or [13C6]myo-inositol in plasma. Caco-2 cells incubated with co-culture supernatants exhibited improved intestinal barrier integrity. These results suggest that the microbiome plays a major role in the metabolism of this phytochemical and that its fermentation to propionate by M. jalaludinii and A. rhamnosivorans may contribute to phytate-driven health benefits.PMID:38858593 | DOI:10.1038/s41564-024-01698-7