Journal: Journal of Advanced Research

Article Title: Integrative multi-omics analysis of autism spectrum disorder reveals unique microbial macromolecules interactions

doi: 10.1016/j.jare.2025.01.036

Figure Lengend Snippet: Metabolic profiling of gut microbial communities in autism. A ) Principal component analysis (PCA) between ASD and control metabolic profile. B) Heatmap showing the abundance of significant metabolites identified in both groups with associated clinical data (age, residence, mode of delivery, GSI score, sex, socioeconomic state, and CARS score). C) Box plots showing the significant metabolite abundance between both groups. Bars under each box plot refer to parameters for each significant metabolite including; expression [Exp] (red; up-regulated in ASD, blue; down-regulated in ASD), role in Autism [Role] (red; have a role in autism, blue; have no role or unknown), origin (red; human, blue; diet, grey; bacteria), role in neurodegenerative diseases (red; yes, blue; no) and pass Blood-brain-barrier [BBB] (red; yes, blue; no), the last line shows the class of each metabolite. D) Metabolite–metabolite interaction network analysis of annotated significantly differentially accumulated metabolites. Line thickness indicates the strength and confidence of data support. e) Pathway enrichment analysis of the significant and unique metabolites using q -value (<0·05). The bubble chart shows the enrichment of differential metabolites in each pathway. The size of the bubble represents the ratio of identified metabolites to total within the pathway. Color represents the nine main pathway groups.

Article Snippet: A High-resolution Human Metabolome database (feces metabolites database-version 4.0) was used as a search space ( https://hmdb.ca ) .

Techniques: Control, Expressing, Bacteria

Journal: Scientific reports

Article Title: Untargeted metabolomic profiling for identifying systemic signatures of helicobacter pylori infection in a guinea pig model.

doi: 10.1038/s41598-025-98016-w

Figure Lengend Snippet: Fig. 4. Classical univariate receiver operating characteristic curves generated from the spectral data to identify serum metabolomic biomarkers indicating H. pylori infection. Box plots representing the distribution of the normalized signal intensities come from: (a) 20-dihydroxyleukotriene B4 (HMDB0012635); (b) PGD2 ethanolamide (HMDB0013629); (c) L.L-Cyclo(leucylprolyl) (HMDB0034276); (d) LysoPC(P-16:0/0:0) (HMDB0010407); (e) PS(18:2(9Z.12Z)/18:2(9Z.12Z)) (HMDB0012402); (f) PG(18:2(9Z.12Z)/22:4(7Z. 10Z.13Z.16Z)) (HMDB0010656); (g) N-Lactoylleucine (HMDB0062176); (h) Isoleucyl-Phenylalanine (HMDB0028914); (i) 5-Methoxytryptophol (HMDB0001896); (j) Deoxycholic acid 3-glucuronide (HMDB0002596);) (k) PC(16:1(9Z)/14:1(9Z)) (HMDB0007999); (l) gamma-Aminobutyric acid (HMDB0000112). The boxes represent the interquartile range (difference between the upper 75% and lower quartile 25%), the thick black lines, and the median. A horizontal line is in red, indicating the optimal cutoff. Abbreviations: 0—H. pylori-negative; 1 – H. pylori positive.

Article Snippet: In serum samples from patients infected with influenza virus Banoei et al., using 1H-NMR, detected citrate; fumarate; 3-Methyl,2-Isovalerate; alanine; tyrosine; methionine; histidine; 4-hydroxybutyrate44, while in patients infected with COVID-19 LC–MS analysis showed the presence of bile acids, bilirubin, diacylglycerols, free fatty acid, glucose, glucuronate, glycerol 3-phosphate, kynurenine, lysophosphotidylcholines, malic acid, monosialodihexosylganglioside, phosphatidylcholines, sphingomyelin, Lp log2(FC) FC m/z RT (min) p-Value Name (ID in HMDB) Cellular locations Biological process 1 1.2063 2.31 368.2231 2.4 0.015061 20-dihydroxy leukotriene B4 HMDB0012635 Extracellular membrane Lipid peroxidation Fatty acids metabolism Cell signaling Lipid metabolism pathway https://hmdb.ca/metabolites/ 2 0.5568 1.94 394.2702 2.65 0.000024 PGD2 Dihomo-gammalinolenoylethanolamide (DGLEA) HMDB0013629 Cytoplasm membrane Lipid peroxidation Fatty acids metabolism Cell signaling Lipid metabolism pathway Inflammatory response https://hmdb.ca/metabolites/ 3 0.7517 1.68 211.1444 2.2 0.001232 L,L-Cyclo(leucylprolyl) HMDB0034276 Extracellular cytoplasm Tyrosine metabolism Alkaloid biosynthesis https://hmdb.ca/metabolites/ 4 0.6172 1.50 765.5122 7.02 2.11E-23 (PC) Phosphatidylcholine HMDB0007999 Extracellular membrane PC shows anti-inflammatory effects 31.

Techniques: Generated, Infection

Journal: Cell Death and Differentiation

Article Title: A novel role of exostosin glycosyltransferase 2 (EXT2) in glioblastoma cell metabolism, radiosensitivity and ferroptosis

doi: 10.1038/s41418-025-01503-w

Figure Lengend Snippet: A Workflow of untargeted metabolomics upon EXT2 knockdown in irradiated DD-T4 and U-251MG cells. B Differential impact of the treatment groups on the metabolome of DD-T4 and U-251MG GBM models determined by Partial Least-Squares Discriminant Analysis (PLSDA) using MetaboAnalyst.ca web tool. C Filtration of LC-MS/MS analytical features for metabolite identification using Human Metabolome Data Base (HMDB) web tool. D Categorization of metabolite content by HMDB and determination of changes in metabolite abundance upon EXT2 depletion and irradiation. Numbers in column graph indicate significantly altered metabolites in the respective color-coded metabolite category. Data are visualized as mean ( n = 4) of the fold change (relative to siC/IR). Significant alterations were determined by t -test with p < 0.05. E Identified deregulated metabolic pathways upon EXT2 knockdown and irradiation obtained from KEGG and Small Molecule Pathway Database (SMPDB) database analyses. The impact is quantified as a percentage of significant up- and down-regulated metabolites. F Overlap of significantly altered metabolites, shown in D in DD-T4 and U-251MG models. G SAM metabolite abundance in unirradiated and irradiated EXT2-depleted cell cultures. H Mapping of metabolites involved in SAM metabolism altered upon EXT2 knockdown identified from untargeted metabolomics. Color code: red, upregulated; blue, down-regulated; green, not changed; black, metabolite not found. Metabolite abundance indicates peak intensity value ( n = 4; one-way ANOVA; ** p < 0.01; *** p < 0.005).

Article Snippet: C Filtration of LC-MS/MS analytical features for metabolite identification using Human Metabolome Data Base (HMDB) web tool.

Techniques: Knockdown, Irradiation, Filtration, Liquid Chromatography with Mass Spectroscopy