Integrative Molecular Phenotyping
INTEGRATIVE MOLECULAR
PHENOTYPING
WHEELOCK LABORATORY
DEPARTMENT OF MEDICAL
BIOCHEMISTRY AND BIOPHYSICS
WHEELOCK LABORATORY
DEPARTMENT OF MEDICAL
BIOCHEMISTRY AND BIOPHYSICS
WHEELOCK LABORATORY
DEPARTMENT OF MEDICAL
BIOCHEMISTRY AND BIOPHYSICS
WHEELOCK LABORATORY
DEPARTMENT OF MEDICAL
BIOCHEMISTRY AND BIOPHYSICS
WHEELOCK LABORATORY
DEPARTMENT OF MEDICAL
BIOCHEMISTRY AND BIOPHYSICS
WHEELOCK LABORATORY

PubMed

Computational tools and algorithms for ion mobility spectrometry-mass spectrometry

Mon, 04/03/2024 - 12:00
Proteomics. 2024 Mar 4:e2200436. doi: 10.1002/pmic.202200436. Online ahead of print.ABSTRACTIon mobility spectrometry-mass spectrometry (IMS-MS or IM-MS) is a powerful analytical technique that combines the gas-phase separation capabilities of IM with the identification and quantification capabilities of MS. IM-MS can differentiate molecules with indistinguishable masses but different structures (e.g., isomers, isobars, molecular classes, and contaminant ions). The importance of this analytical technique is reflected by a staged increase in the number of applications for molecular characterization across a variety of fields, from different MS-based omics (proteomics, metabolomics, lipidomics, etc.) to the structural characterization of glycans, organic matter, proteins, and macromolecular complexes. With the increasing application of IM-MS there is a pressing need for effective and accessible computational tools. This article presents an overview of the most recent free and open-source software tools specifically tailored for the analysis and interpretation of data derived from IM-MS instrumentation. This review enumerates these tools and outlines their main algorithmic approaches, while highlighting representative applications across different fields. Finally, a discussion of current limitations and expectable improvements is presented.PMID:38438732 | DOI:10.1002/pmic.202200436

Pathogenicity of monokaryotic and dikaryotic mycelia of Ganoderma boninense revealed via LC-MS-based metabolomics

Mon, 04/03/2024 - 12:00
Sci Rep. 2024 Mar 4;14(1):5330. doi: 10.1038/s41598-024-56129-8.ABSTRACTThis study compared the pathogenicity of monokaryotic (monokaryon) and dikaryotic (dikaryon) mycelia of the oil palm pathogen Ganoderma boninense via metabolomics approach. Ethyl acetate crude extracts of monokaryon and dikaryon were analysed by liquid chromatography quadrupole/time-of-flight-mass spectrometry (LC-Q/TOF-MS) coupled with multivariate data analysis using MetaboAnalyst. The mummichog algorithm was also used to identify the functional activities of monokaryon and dikaryon without a priori identification of all their secondary metabolites. Results revealed that monokaryon produced lesser fungal metabolites than dikaryon, suggesting that monokaryon had a lower possibility of inducing plant infection. These findings were further supported by the identified functional activities. Monokaryon exhibits tyrosine, phenylalanine, and tryptophan metabolism, which are important for fungal growth and development and to produce toxin precursors. In contrast, dikaryon exhibits the metabolism of cysteine and methionine, arginine and proline, and phenylalanine, which are important for fungal growth, development, virulence, and pathogenicity. As such, monokaryon is rendered non-pathogenic as it produces growth metabolites and toxin precursors, whereas dikaryon is pathogenic as it produces metabolites that are involved in fungal growth and pathogenicity. The LC-MS-based metabolomics approach contributes significantly to our understanding of the pathogenesis of Ganoderma boninense, which is essential for disease management in oil palm plantations.PMID:38438519 | DOI:10.1038/s41598-024-56129-8

A comprehensive UHPLC-MS/MS method for metabolomics profiling of signaling lipids: Markers of oxidative stress, immunity and inflammation

Mon, 04/03/2024 - 12:00
Anal Chim Acta. 2024 Apr 8;1297:342348. doi: 10.1016/j.aca.2024.342348. Epub 2024 Feb 10.ABSTRACTSignaling lipids (SLs) play a crucial role in various signaling pathways, featuring diverse lipid backbone structures. Emerging evidence showing the biological significance and biomedical values of SLs has strongly spurred the advancement of analytical approaches aimed at profiling SLs. Nevertheless, the dramatic differences in endogenous abundances across lipid classes as well as multiple isomers within the same lipid class makes the development of a generic analytical method challenging. A better analytical method that combines comprehensive coverage and high sensitivity is needed to enable us to gain a deeper understanding of the biochemistry of these molecules in health and disease. In this study, we developed a fast and comprehensive targeted ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method for profiling SLs. The platform enables analyses of 260 metabolites covering oxylipins (isoprostanes, prostaglandins and other oxidized lipids), free fatty acids, lysophospholipids, sphingoid bases (C16, C18), platelet activating factors (C16, C18), endocannabinoids and bile acids. Various validation parameters including linearity, limit of detection, limit of quantification, extraction recovery, matrix effect, intra-day and inter-day precision were used to characterize this method. Metabolite quantitation was successfully achieved in both NIST Standard Reference Material for human plasma (NIST SRM 1950) and pooled human plasma, with 109 and 144 metabolites quantitated. The quantitation results in NIST SRM 1950 plasma demonstrated good correlations with certified or previously reported values in published literature. This study introduced quantitative data for 37 SLs for the first time. Metabolite concentrations measured in NIST SRM 1950 will serve as essential reference data for facilitating interlaboratory comparisons. The methodology established here will be the cornerstone for in-depth profiling of signaling lipids across diverse biological samples and contexts.PMID:38438234 | DOI:10.1016/j.aca.2024.342348

Tetrad stage transient cold stress skews auxin-mediated energy metabolism balance in Chinese cabbage pollen

Mon, 04/03/2024 - 12:00
Plant Physiol. 2024 Mar 4:kiae123. doi: 10.1093/plphys/kiae123. Online ahead of print.ABSTRACTChanging ambient temperature often impairs plant development and sexual reproduction, particularly pollen ontogenesis. However, mechanisms underlying cold stress-induced male sterility are not well understood. Here, we exposed Chinese cabbage (Brassica campestris) to different cold conditions during flowering and demonstrated that the tetrad stage was the most sensitive. After completion of pollen development at optimal conditions, transient cold stress at the tetrad stage still impacted auxin levels, starch and lipid accumulation, and pollen germination, ultimately resulting in partial male sterility. Transcriptome and metabolome analyses and histochemical staining indicated that the reduced pollen germination rate was due to the imbalance of energy metabolism during pollen maturation. The investigation of β-glucuronidase (GUS)-overexpressing transgenic plants driven by the promoter of DR5 (DR5::GUS report system) combined with cell tissue staining and metabolome analysis further validated that cold stress during the tetrad stage reduced auxin levels in mature pollen grains. Low-concentration auxin treatment on floral buds at the tetrad stage before cold exposure improved the cold tolerance of mature pollen grains. Artificially changing the content of endogenous auxin during pollen maturation by spraying chemical reagents and loss-of-function investigation of the auxin biosynthesis gene YUCCA6 by artificial microRNA technology showed that starch overaccumulation severely reduced the pollen germination rate. In summary, we revealed that transient cold stress at the tetrad stage of pollen development in Chinese cabbage causes auxin-mediated starch-related energy metabolism imbalance that contributes to the decline in pollen germination rate and ultimately seed set.PMID:38438131 | DOI:10.1093/plphys/kiae123

Metabolomics profile and machine learning prediction of treatment responses in immune thrombocytopenia: A prospective cohort study

Mon, 04/03/2024 - 12:00
Br J Haematol. 2024 Mar 4. doi: 10.1111/bjh.19391. Online ahead of print.ABSTRACTImmune thrombocytopenia (ITP) is an autoimmune disease characterized by antibody-mediated platelet destruction and impaired platelet production. The mechanisms underlying ITP and biomarkers predicting the response of drug treatments are elusive. We performed a metabolomic profiling of bone marrow biopsy samples collected from ITP patients admission in a prospective study of the National Longitudinal Cohort of Hematological Diseases. Machine learning algorithms were conducted to discover novel biomarkers to predict ITP patient treatment responses. From the bone marrow biopsies of 91 ITP patients, we quantified a total of 4494 metabolites, including 1456 metabolites in the positive mode and 3038 metabolites in the negative mode. Metabolic patterns varied significantly between groups of newly diagnosed and chronic ITP, with a total of 876 differential metabolites involved in 181 unique metabolic pathways. Enrichment factors and p-values revealed the top metabolically enriched pathways to be sphingolipid metabolism, the sphingolipid signalling pathway, ubiquinone and other terpenoid-quinone biosynthesis, thiamine metabolism, tryptophan metabolism and cofactors biosynthesis, the phospholipase D signalling pathway and the phosphatidylinositol signalling system. Based on patient responses to five treatment options, we screened several metabolites using the Boruta algorithm and ranked their importance using the random forest algorithm. Lipids and their metabolism, including long-chain fatty acids, oxidized lipids, glycerophospholipids, phosphatidylcholine and phosphatidylethanolamine biosynthesis, helped differentiate drug treatment responses. In conclusion, this study revealed metabolic alterations associated with ITP in bone marrow supernatants and a potential biomarker predicting the response to ITP.PMID:38438130 | DOI:10.1111/bjh.19391

Multi-platform omics sequencing dissects the atlas of plasma-derived exosomes in rats with or without depression-like behavior after traumatic spinal cord injury

Mon, 04/03/2024 - 12:00
Prog Neuropsychopharmacol Biol Psychiatry. 2024 Mar 2:110987. doi: 10.1016/j.pnpbp.2024.110987. Online ahead of print.ABSTRACTBACKGROUND: Exosomes can penetrate the blood-brain barrier for material exchange between the peripheral and central nervous systems. Differences in exosome contents could explain the susceptibility of different individuals to depression-like behavior after traumatic spinal cord injury (TSCI).METHODS: Hierarchical clustering was used to integrate multiple depression-related behavioral outcomes in sham and TSCI rats and ultimately identify non-depressed and depressed rats. The difference in plasma exosome contents between non-depressed and depressed rats after TSCI was assessed in 15 random subjects by performing plasma exosome transcriptomics, mass spectroscope-based proteomics, and non-targeted metabolomics analyses.RESULTS: The results revealed that about 27.6% of the rats developed depression-like behavior after TSCI. Totally, 10 differential metabolites, 81 differentially expressed proteins (DEPs), 373 differentially expressed genes (DEGs), and 55 differentially expressed miRNAs (DEmiRNAs) were identified between non-depressed TSCI and sham rats. Meanwhile, 37 differential metabolites, 499 DEPs, 1361 DEGs, and 89 DEmiRNAs were identified between depressed and non-depressed TSCI rats. Enrichment analysis showed that the progression of depression-like behavior after TSCI may be related to amino acid metabolism disorder and dysfunction of multiple signaling pathways, including endocytosis, lipid and atherosclerosis, toll-like receptor, TNF, and PI3K-Akt pathway.CONCLUSION: Overall, our study systematically revealed for the first time the differences in plasma exosome contents between non-depressed and depressed rats after TSCI, which will help broaden our understanding of the complex molecular mechanisms involved in brain functional recombination after TSCI.PMID:38438071 | DOI:10.1016/j.pnpbp.2024.110987

Machine learning reveals serum myristic acid, palmitic acid and heptanoylcarnitine as biomarkers of coronary artery disease risk in patients with type 2 diabetes mellitus

Mon, 04/03/2024 - 12:00
Clin Chim Acta. 2024 Mar 2:117852. doi: 10.1016/j.cca.2024.117852. Online ahead of print.ABSTRACTBACKGROUND: Coronary heart disease (CHD) is the most important complication of type 2 diabetes mellitus (T2DM) and the leading cause of death. Identifying the risk of CHD in T2DM patients is important for early clinical intervention.METHODS: A total of 213 participants, including 81 healthy controls (HCs), 69 T2DM patients and 63 T2DM patients complicated with CHD were recruited in this study. Serum metabolomics were conducted by using ultra-high performance liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS). Demographic information and clinical laboratory test results were also collected.RESULTS: Metabolic phenotypes were significantly altered among HC, T2DM and T2DM-CHD. Acylcarnitines were the most disturbed metabolites between T2DM patients and HCs. Lower levels of bile acids and higher levels of fatty acids in serum were closely associated with CHD risk in T2DM patients. Artificial neural network model was constructed for the discrimination of T2DM and T2DM complicated with CHD based on myristic acid, palmitic acid and heptanoylcarnitine, with accuracy larger than 0.95 in both training set and testing set.CONCLUSION: Altogether, these findings suggest that myristic acid, palmitic acid and heptanoylcarnitine have a good prospect for the warning of CHD complications in T2DM patients, and are superior to traditional lipid, blood glucose and blood pressure indicators.PMID:38438006 | DOI:10.1016/j.cca.2024.117852

Temporal Effects of Safflower Oil Diet-Based Linoleic Acid Supplementation on Barth Syndrome Cardiomyopathy

Mon, 04/03/2024 - 12:00
Circulation. 2024 Mar 5;149(10):790-793. doi: 10.1161/CIRCULATIONAHA.123.065414. Epub 2024 Mar 4.NO ABSTRACTPMID:38437482 | DOI:10.1161/CIRCULATIONAHA.123.065414

AI-organoid integrated systems for biomedical studies and applications

Mon, 04/03/2024 - 12:00
Bioeng Transl Med. 2024 Jan 20;9(2):e10641. doi: 10.1002/btm2.10641. eCollection 2024 Mar.ABSTRACTIn this review, we explore the growing role of artificial intelligence (AI) in advancing the biomedical applications of human pluripotent stem cell (hPSC)-derived organoids. Stem cell-derived organoids, these miniature organ replicas, have become essential tools for disease modeling, drug discovery, and regenerative medicine. However, analyzing the vast and intricate datasets generated from these organoids can be inefficient and error-prone. AI techniques offer a promising solution to efficiently extract insights and make predictions from diverse data types generated from microscopy images, transcriptomics, metabolomics, and proteomics. This review offers a brief overview of organoid characterization and fundamental concepts in AI while focusing on a comprehensive exploration of AI applications in organoid-based disease modeling and drug evaluation. It provides insights into the future possibilities of AI in enhancing the quality control of organoid fabrication, label-free organoid recognition, and three-dimensional image reconstruction of complex organoid structures. This review presents the challenges and potential solutions in AI-organoid integration, focusing on the establishment of reliable AI model decision-making processes and the standardization of organoid research.PMID:38435826 | PMC:PMC10905559 | DOI:10.1002/btm2.10641

Identification of inhibitors from a functional food-based plant Perillae Folium against hyperuricemia via metabolomics profiling, network pharmacology and all-atom molecular dynamics simulations

Mon, 04/03/2024 - 12:00
Front Endocrinol (Lausanne). 2024 Feb 16;15:1320092. doi: 10.3389/fendo.2024.1320092. eCollection 2024.ABSTRACTINTRODUCTION: Hyperuricemia (HUA) is a metabolic disorder caused by purine metabolism dysfunction in which the increasing purine levels can be partially attributed to seafood consumption. Perillae Folium (PF), a widely used plant in functional food, has been historically used to mitigate seafood-induced diseases. However, its efficacy against HUA and the underlying mechanism remain unclear.METHODS: A network pharmacology analysis was performed to identify candidate targets and potential mechanisms involved in PF treating HUA. The candidate targets were determined based on TCMSP, SwissTargetPrediction, Open Targets Platform, GeneCards, Comparative Toxicogenomics Database, and DrugBank. The potential mechanisms were predicted via Gene Ontology (GO) and Kyoto Gene and Genome Encyclopedia (KEGG) analyses. Molecular docking in AutoDock Vina and PyRx were performed to predict the binding affinity and pose between herbal compounds and HUA-related targets. A chemical structure analysis of PF compounds was performed using OSIRIS DataWarrior and ClassyFire. We then conducted virtual pharmacokinetic and toxicity screening to filter potential inhibitors. We further performed verifications of these inhibitors' roles in HUA through molecular dynamics (MD) simulations, text-mining, and untargeted metabolomics analysis.RESULTS: We obtained 8200 predicted binding results between 328 herbal compounds and 25 potential targets, and xanthine dehydrogenase (XDH) exhibited the highest average binding affinity. We screened out five promising ligands (scutellarein, benzyl alpha-D-mannopyranoside, elemol, diisobutyl phthalate, and (3R)-hydroxy-beta-ionone) and performed MD simulations up to 50 ns for XDH complexed to them. The scutellarein-XDH complex exhibited the most satisfactory stability. Furthermore, the text-mining study provided laboratory evidence of scutellarein's function. The metabolomics approach identified 543 compounds and confirmed the presence of scutellarein. Extending MD simulations to 200 ns further indicated the sustained impact of scutellarein on XDH structure.CONCLUSION: Our study provides a computational and biomedical basis for PF treating HUA and fully elucidates scutellarein's great potential as an XDH inhibitor at the molecular level, holding promise for future drug design and development.PMID:38435751 | PMC:PMC10905266 | DOI:10.3389/fendo.2024.1320092

Taurine as a biomarker for aging: A new avenue for translational research

Mon, 04/03/2024 - 12:00
Adv Biomark Sci Technol. 2023;5:86-88. doi: 10.1016/j.abst.2023.10.002.ABSTRACTThe physiologic and irreversible process of ageing is accompanied by a wide range of structural and functional shifts at multiple different levels. It is also suggested that variations in the blood concentrations of metabolites, hormones, and micronutrients may play a role in the ageing process. Recently, Singh et al. 1,2 investigated a study on Taurine shortage as a driver and biomarker of ageing and its impact on a healthy lifespan.2 They further proposed that functional abnormalities in numerous organs associated with age-related illnesses have been linked to early-life Taurine insufficiency. Taurine deficiency in the elderly and the possible benefits of Taurine supplements One of the reasons for decreasing Taurine concentration is the loss of endogenous synthesis, which may contribute to the decrease in Taurine levels seen in the elderly. While it was previously believed that the liver was responsible for most Taurine synthesis in humans, new research suggests that other organs or common intermediates may play a larger role. The authors experimented with and analysed a life-span examination of various organisms, for example, mice to assess the impacts of Taurine supplementation. They also analysed after the administration of oral Taurine supplementation in conjunction with other interventions using multi-omics data sets (RNA sequencing, metabolomics etc.) across different species.PMID:38435677 | PMC:PMC10901744 | DOI:10.1016/j.abst.2023.10.002

Alpha-Linolenic Acid Ameliorates Cognitive Impairment and Liver Damage Caused by Obesity

Mon, 04/03/2024 - 12:00
Diabetes Metab Syndr Obes. 2024 Feb 28;17:981-995. doi: 10.2147/DMSO.S434671. eCollection 2024.ABSTRACTBACKGROUND: Obesity is a growing global problem that causes various complications such as diabetes, cognitive dysfunction, cardiovascular diseases, and hepatobiliary disease. Alpha-linolenic acid (ALA) has been reported to exhibit multiple pharmaceutical effects. This study aimed to explore the effects of ALA on obesity-induced adipose tissue accumulation, cognitive impairment, inflammation, and colonic mucosal barrier integrity.METHODS: Mice were fed with high-fat diet (HFD) and were treated with ALA (60 or 100 mg/kg). Body weight, adipose tissue, serum glucose and lipid levels, glucose resistance, and insulin resistance were measured. Cognitive ability was analyzed using the behavior tests. PTP1B and IRS/p-AKT/p-GSK3β/p-Tau signaling were examined to evaluate inflammation and synaptogenesis. Colon mucosal barrier integrity was examined by Alcian blue staining and expression of the tight junction proteins. The production of pro-inflammatory cytokines and liver damages were evaluated. 3T3-L1 cells were used for in vitro experiments. Cell viability, migration and invasion were detected. The levels of ROS, iron, and ferrous ions were measured to assess ferroptosis. Metabolomic analysis of adipose tissues was performed.RESULTS: ALA treatment prevented HFD-induced adipose tissue accumulation, improved glucose and lipid homeostasis and metabolism. Administration of ALA repressed the HFD-induced increase in insulin levels and insulin resistance index. Serum and colon levels of pro-inflammatory cytokines were decreased after ALA treatment. ALA elevated mitochondrial content in brown adipose tissues. ALA ameliorated obesity-induced cognitive impairment and hippocampal inflammation, enhanced colon mucosa integrity. ALA treatment ameliorated HFD-induced liver damage and lipid accumulation and inhibited differentiation of preadipocyte 3T3-L1 cells into mature adipocytes and induces ferroptosis. Metabolomic analysis suggested that ALA may target the glycerolipid metabolism pathway to ameliorate obesity. Knockdown of AGPAT2 abolished the protective effects of ALA.CONCLUSION: ALA treatment suppressed adipose accumulation in adipocytes, improved cognitive ability and colon integrity, and alleviated liver damage by modulating the 1-acylglycerol-3-phosphate O-acyltransferase 2 (AGPAT2).PMID:38435630 | PMC:PMC10909331 | DOI:10.2147/DMSO.S434671

Mechanistic insights into inositol-mediated rumen function promotion and metabolic alteration using <em>in vitro</em> and <em>in vivo</em> models

Mon, 04/03/2024 - 12:00
Front Vet Sci. 2024 Feb 16;11:1359234. doi: 10.3389/fvets.2024.1359234. eCollection 2024.ABSTRACTInositol is a bioactive factor that is widely found in nature; however, there are few studies on its use in ruminant nutrition. This study investigated the effects of different inositol doses and fermentation times on rumen fermentation and microbial diversity, as well as the levels of rumen and blood metabolites in sheep. Rumen fermentation parameters, microbial diversity, and metabolites after different inositol doses were determined in vitro. According to the in vitro results, six small-tailed Han sheep fitted with permanent rumen fistulas were used in a 3 × 3 Latin square feeding experiment where inositol was injected into the rumen twice a day and rumen fluid and blood samples were collected. The in vitro results showed that inositol could increase in vitro dry matter digestibility, in vitro crude protein digestibility, NH3-N, acetic acid, propionic acid, and rumen microbial diversity and affect rumen metabolic pathways (p < 0.05). The feeding experiment results showed that inositol increased the blood concentration of high-density lipoprotein and IgG, IgM, and IL-4 levels. The rumen microbial composition was significantly affected (p < 0.05). Differential metabolites in the rumen were mainly involved in ABC transporters, biotin metabolism, and phenylalanine metabolism, whereas those in the blood were mainly involved in arginine biosynthesis and glutathione and tyrosine metabolism. In conclusion, inositol improves rumen function, affects rumen microorganisms and rumen and blood metabolites and may reduce inflammation, improving animal health.PMID:38435365 | PMC:PMC10904589 | DOI:10.3389/fvets.2024.1359234

Untargeted metabolomics unveiled the role of butanoate metabolism in the development of Pseudomonas aeruginosa hypoxic biofilm

Mon, 04/03/2024 - 12:00
Front Cell Infect Microbiol. 2024 Feb 16;14:1346813. doi: 10.3389/fcimb.2024.1346813. eCollection 2024.ABSTRACTPseudomonas aeruginosa is a versatile opportunistic pathogen which causes a variety of acute and chronic human infections, some of which are associated with the biofilm phenotype of the pathogen. We hypothesize that defining the intracellular metabolome of biofilm cells, compared to that of planktonic cells, will elucidate the metabolic pathways and biomarkers indicative of biofilm inception. Disc-shaped stainless-steel coupons (12.7 mm diameter) were employed as a surface for static biofilm establishment. Each disc was immersed in a well, of a 24-well microtiter plate, containing a 1-mL Lysogeny broth (LB) suspension of P. aeruginosa ATCC 9027, a strain known for its biofilm prolificacy. This setup underwent oxygen-depleted incubation at 37°C for 24 hours to yield hypoxic biofilms and the co-existing static planktonic cells. In parallel, another planktonic phenotype of ATCC 9027 was produced in LB under shaking (200 rpm) incubation at 37°C for 24 hours. Planktonic and biofilm cells were harvested, and the intracellular metabolites were subjected to global untargeted metabolomic analysis using LC-MS technology, where small metabolites (below 1.5 kDa) were selected. Data analysis showed the presence of 324 metabolites that differed (p < 0.05) in abundance between planktonic and biofilm cells, whereas 70 metabolites did not vary between these phenotypes (p > 0.05). Correlation, principal components, and partial least square discriminant analyses proved that the biofilm metabolome is distinctly clustered away from that of the two planktonic phenotypes. Based on the functional enrichment analysis, arginine and proline metabolism were enriched in planktonic cells, but butanoate metabolism was enriched in biofilm cells. Key differential metabolites within the butanoate pathway included acetoacetate, 2,3-butandiol, diacetyl, and acetoin, which were highly upregulated in the biofilm compared to the planktonic cells. Exogenous supplementation of acetoin (2 mM), a critical metabolite in butanoate metabolism, augmented biofilm mass, increased the structural integrity and thickness of the biofilm, and maintained the intracellular redox potential by balancing NADH/NAD+ ratio. In conclusion, P. aeruginosa hypoxic biofilm has a specialized metabolic landscape, and butanoate pathway is a metabolic preference and possibly required for promoting planktonic cells to the biofilm state. The butanoate pathway metabolites, particularly acetoin, could serve as markers for biofilm development.PMID:38435305 | PMC:PMC10904581 | DOI:10.3389/fcimb.2024.1346813

Integrative Omics Analysis Reveals Metabolic Features of Ground-Glass Opacity-Associated Lung Cancer

Mon, 04/03/2024 - 12:00
J Cancer. 2024 Feb 4;15(7):1848-1862. doi: 10.7150/jca.92437. eCollection 2024.ABSTRACTBackground: Ground-glass opacity (GGO)-associated cancers are increasingly prevalent, exhibiting unique clinical and molecular features that suggest the need for a distinct treatment strategy. However, the metabolic characteristics and vulnerabilities of GGO-associated lung cancers remain unexplored. Methods: We conducted metabolomic and transcriptomic analyses on 40 pairs of GGO-associated lung cancer tissues and adjacent normal tissues. By integrating data from TCGA database and single-cell RNA sequencing, we aimed to identify aberrant metabolic pathways, establish a metabolite-associated gene signature, and pinpoint key metabolic genes. The physiological effect of key genes was detected in vitro and vivo assays. Results: We identified a 30-gene metabolite-associated signature and discovered aberrant metabolic pathways for GGO-associated lung cancer at both metabolic and transcriptional levels. Patients with this signature displayed specific prognostic and molecular features. Cox regression analysis, based on the Cancer Genome Atlas Program (TCGA) data, further narrowed down the metabolite-related gene signature, resulting in a 5-gene signature. Confirmed by single-cell RNA sequencing (GSE203360), the 5-gene signature was mainly expressed in cancer cells of GGO tissue. Real-time quantitative PCR (RT-qPCR) further validated the differential expression of these genes between GGO and adjacent normal tissue obtained from pulmonary surgery. Finally, our integrative analysis unveiled aberrant histidine metabolism at both the multi-omics and single-cell levels. Moreover, we identified MAOB as a key metabolic gene, demonstrating its ability to suppress cell proliferation, migration, and invasion in LUAD cell lines, both in vitro and in vivo. Conclusions: We identified a specific metabolite-associated gene signature and identified aberrant histidine metabolism in GGO-associated lung cancer from multiple perspectives. Notably, MAOB, a crucial component in histidine metabolism, demonstrated a significant inhibitory effect on the proliferation and metastasis of LUAD, indicating its potential significance in pathogenesis and therapeutic interventions.PMID:38434969 | PMC:PMC10905408 | DOI:10.7150/jca.92437

Chinese herbal decoction, Yi-Qi-Jian-Pi formula exerts anti-hepatic fibrosis effects in mouse models of CCl<sub>4</sub>-induced liver fibrosis

Mon, 04/03/2024 - 12:00
Heliyon. 2024 Feb 22;10(5):e26129. doi: 10.1016/j.heliyon.2024.e26129. eCollection 2024 Mar 15.ABSTRACTBACKGROUND: Yi-Qi-Jian-Pi Formula (YQJPF) is a herbal medicine that is used to treat patients with liver failure. However, scientific evidence supporting the treatment of hepatic fibrosis with YQJPF has not been forthcoming. The present study aimed to determine the mechanisms underlying the anti-fibrotic effects of YQJPF in mouse models of hepatic fibrosis.METHODS: Mice were randomly assigned to control, hepatic fibrosis model, silymarin (positive treated), and low-, medium- and high-dose YQJPF (7.5, 15, and 30 g/kg, respectively) groups. Liver function, inflammatory cytokines, and oxygen stress were analyzed using ELISA kits. Sections were histopathologically stained with hematoxylin-eosin, Masson trichrome, and Sirius red. Macrophage polarization was measured by flow cytometry and immunofluorescence. Potential targets of YQJPF against hepatic fibrosis were analyzed by network pharmacology of Chinese herbal compound and the effects of YQJPF on the transforming growth factor-beta (TGF-β)/Suppressor of Mothers against Decapentaplegic family member 3 (Smad3) signaling pathway were assessed using qRT-PCR and immunohistochemical staining. Finally, metagenomics and LC-MS/MS were used to detect the intestinal flora and metabolites of the mice, and an in-depth correlation analysis was performed by spearman correlation analysis. The data were compared by one-way ANOVA and least significant differences (LSDs) or ANOVA-Dunnett's T3 method used when no homogeneity was detected.RESULTS: We induced hepatic fibrosis using CCl4 to establish mouse models and found that YQJPF dose-dependently increased body weight, improved liver function, and reversed hepatic fibrosis. Elevated levels of the pro-inflammatory factors IL-1β, IL-6, and TNF-α in the model mice were substantially decreased by YQJPF, particularly at the highest dose. Levels of serum malondialdehyde and superoxide dismutase (SOD) activity were elevated and reduced, respectively. The malondialdehyde concentration decreased and SOD activity increased in the high-dose group. M1 polarized macrophages (CD86) in the mouse models were significantly decreased and M2 polarization was mildly decreased without significance. However, high-dose YQJPF increased the numbers of M2 macrophages and inhibited TGF-β/Smad3 signaling. Metagenomic and non-targeted metabolomics detection results showed that YQJPF could regulate intestinal homeostasis, and Spearman correlation analysis showed that the abundance of Calditerrivibrio_nitroreducens was significantly negatively correlated with 18β-glycyrrhetinic acid. It is suggested that Calditerrivibrio_nitroreducens may reduce the anti-fibrosis effect of licorice and other Chinese herbs by digesting 18β-glycyrrhetinic acid.CONCLUSIONS: YQJPF can reverse liver fibrosis by inhibiting inflammation, suppressing oxidative stress, regulating the immunological response initiated by macrophages, inhibiting TGF-β/Smad3 signaling and regulating intestinal flora homeostasis. Therefore, YQJPF may be included in clinical regimens to treat hepatic fibrosis.PMID:38434258 | PMC:PMC10907526 | DOI:10.1016/j.heliyon.2024.e26129

Cross-sectional analyses of metabolites across biological samples mediating dietary acid load and chronic kidney disease

Mon, 04/03/2024 - 12:00
iScience. 2024 Feb 5;27(3):109132. doi: 10.1016/j.isci.2024.109132. eCollection 2024 Mar 15.ABSTRACTChronic kidney disease (CKD) is a major public health burden, with dietary acid load (DAL) and gut microbiota playing crucial roles. As DAL can affect the host metabolome, potentially via the gut microbiota, we cross-sectionally investigated the interplay between DAL, host metabolome, gut microbiota, and early-stage CKD (TwinsUK, n = 1,453). DAL was positively associated with CKD stage G1-G2 (Beta (95% confidence interval) = 0.34 (0.007; 0.7), p = 0.046). After adjusting for covariates and multiple testing, we identified 15 serum, 14 urine, 8 stool, and 7 saliva metabolites, primarily lipids and amino acids, associated with both DAL and CKD progression. Of these, 8 serum, 2 urine, and one stool metabolites were found to mediate the DAL-CKD association. Furthermore, the stool metabolite 5-methylhexanoate (i7:0) correlated with 26 gut microbial species. Our findings emphasize the gut microbiota's therapeutic potential in countering DAL's impact on CKD through the host metabolome. Interventional and longitudinal studies are needed to establish causality.PMID:38433906 | PMC:PMC10907771 | DOI:10.1016/j.isci.2024.109132

Blood metabolomic and transcriptomic signatures stratify patient subgroups in multiple sclerosis according to disease severity

Mon, 04/03/2024 - 12:00
iScience. 2024 Feb 15;27(3):109225. doi: 10.1016/j.isci.2024.109225. eCollection 2024 Mar 15.ABSTRACTThere are no blood-based biomarkers distinguishing patients with relapsing-remitting (RRMS) from secondary progressive multiple sclerosis (SPMS) although evidence supports metabolomic changes according to MS disease severity. Here machine learning analysis of serum metabolomic data stratified patients with RRMS from SPMS with high accuracy and a putative score was developed that stratified MS patient subsets. The top differentially expressed metabolites between SPMS versus patients with RRMS included lipids and fatty acids, metabolites enriched in pathways related to cellular respiration, notably, elevated lactate and glutamine (gluconeogenesis-related) and acetoacetate and bOHbutyrate (ketone bodies), and reduced alanine and pyruvate (glycolysis-related). Serum metabolomic changes were recapitulated in the whole blood transcriptome, whereby differentially expressed genes were also enriched in cellular respiration pathways in patients with SPMS. The final gene-metabolite interaction network demonstrated a potential metabolic shift from glycolysis toward increased gluconeogenesis and ketogenesis in SPMS, indicating metabolic stress which may trigger stress response pathways and subsequent neurodegeneration.PMID:38433900 | PMC:PMC10907838 | DOI:10.1016/j.isci.2024.109225

Unlocking protein-based biomarker potential for graft-versus-host disease following allogenic hematopoietic stem cell transplants

Mon, 04/03/2024 - 12:00
Front Immunol. 2024 Feb 16;15:1327035. doi: 10.3389/fimmu.2024.1327035. eCollection 2024.ABSTRACTDespite the numerous advantages of allogeneic hematopoietic stem cell transplants (allo-HSCT), there exists a notable association with risks, particularly during the preconditioning period and predominantly post-intervention, exemplified by the occurrence of graft-versus-host disease (GVHD). Risk stratification prior to symptom manifestation, along with precise diagnosis and prognosis, relies heavily on clinical features. A critical imperative is the development of tools capable of early identification and effective management of patients undergoing allo-HSCT. A promising avenue in this pursuit is the utilization of proteomics-based biomarkers obtained from non-invasive biospecimens. This review comprehensively outlines the application of proteomics and proteomics-based biomarkers in GVHD patients. It delves into both single protein markers and protein panels, offering insights into their relevance in acute and chronic GVHD. Furthermore, the review provides a detailed examination of the site-specific involvement of GVHD. In summary, this article explores the potential of proteomics as a tool for timely and accurate intervention in the context of GVHD following allo-HSCT.PMID:38433830 | PMC:PMC10904603 | DOI:10.3389/fimmu.2024.1327035

TRPV4-dependent Ca<sup>2+</sup> influx determines cholesterol dynamics at the plasma membrane

Mon, 04/03/2024 - 12:00
Biophys J. 2024 Mar 2:S0006-3495(24)00164-4. doi: 10.1016/j.bpj.2024.02.030. Online ahead of print.ABSTRACTThe activities of the transient receptor potential vanilloid 4 (TRPV4), a Ca2+-permeable non-selective cation channel, are controlled by its surrounding membrane lipids (e.g., cholesterol, phosphoinositides). The transmembrane region of TRPV4 contains a cholesterol recognition amino acid consensus (CRAC) motif and its inverted (CARC) motif located in the plasmalemmal cytosolic leaflet. TRPV4 localizes in caveolae, a bulb-shaped cholesterol-rich domain at the plasma membrane. Here, we visualized the spatiotemporal interactions between TRPV4 and cholesterol at the plasma membrane in living cells by dual-color single-molecule imaging using total internal reflection fluorescence microscopy (TIRFM). To this aim, we labelled cholesterol at the cytosolic leaflets of the plasma membrane using a cholesterol biosensor, D4H. Our single-molecule tracking analysis showed that the TRPV4 molecules colocalize with D4H-accessible cholesterol molecules mainly in the low fluidity membrane domains in which both molecules are highly-clustered. Colocalization of TRPV4 and D4H-accessible cholesterol was observed both inside and outside of caveolae. Agonist-evoked TRPV4 activation remarkably decreased colocalization probability and association rate between TRPV4 and D4H-accessible cholesterol molecules. Interestingly, upon TRPV4 activation, the particle density of D4H-accessible cholesterol molecules was decreased and the D4H-accessible cholesterol molecules in the fast-diffusing state were increased at the plasma membrane. The introduction of skeletal dysplasia-associated R616Q mutation into the CRAC/CARC motif of TRPV4, which reduced the interaction with cholesterol clusters, could not alter the D4H-accessible cholesterol dynamics. Mechanistically, TRPV4-mediated Ca2+ influx and the C-terminal calmodulin-binding site of TRPV4 are essential for modulating the plasmalemmal D4H-accessible cholesterol dynamics. We propose that TRPV4 remodels its surrounding plasmalemmal environment by manipulating cholesterol dynamics through Ca2+ influx.PMID:38433447 | DOI:10.1016/j.bpj.2024.02.030

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