MetaboLights

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le26_SPF_Steadystate_Colon_P1-C2_C18Msneg_20260127.cefftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS7382/FILES/RAW_FILES/DS0021_Sample73_SPF_Steadystate_Serum_P2-B11_C18Msneg_20260127.d.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS7382/FILES/RAW_FILES/DS0021_Sample76_SPF_Steadystate_Serum_P2-C2_C18Msneg_20260127.d.zipftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS7382/FILES/DERIVED_FILES/DS0021_Sample72_SPF_Steadystate_Serum_P2-B10_C18Msneg_20260127.cefftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS7382/FILES/DERIVED_FILES/DS0021_Sample41_SPF_Steadystate_Colon_P1-D5_C18Msneg_20260127.cefftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS7382/FILES/RAW_FILES/DS0021_Sample37_OMM11_Steadystate_Colon_P1-D1_C18Msneg_20260127.d.zipprimaryOK200ftp://ftp.ebi.ac.uk/pub/databases/metabolights/studies/public/MTBLS7382Peak integration was performed using MassHunter Quantitative Analysis (Agilent, v7.0) based on the accurate high-resolution mass and RT of the reference analytes and the following parameters: signal threshold of 30,000; mass tolerances of 0.002 amu or 20 ppm; retention time tolerance of 0.2 min. Lastly, all metabolites annotated in this manuscript were assigned a Level 1 annotation according to the Metabolomics Standards Initiative (MSI) classification system. This includes a match in retention time using the same chromatographic system, accurate mass, and MS/MS fragmentation pattern, ensuring unequivocal identification of the compounds. MetaboLightsPublicLiquid Chromatography MS - negative - reverse-phaseLiquid chromatography-mass spec analysis was performed as previously described (Zimmermann et al., 2019). Briefly, metabolites were analyzed by reversed-phase chromatography using a 1200 Infinity UHPLC system (Agilent) with an InfinityLab Poroshell HPH-C18 column (2.1 × 100 mm, 1.9 µm) operated at 45°C and mobile phases A (water, 0.1% formic acid (%v/v)) and B (methanol, 0.1% formic acid(%v/v)). Five microliters of the sample were injected with a gradient from 5% to 95% B over 6.5 minutes.Microbial metabolites calibrate innate immunity upon systemic viral infection.Denise SelegatoEMBL Heidelbegblank samplebloodsample preparation blankfecesreference compound mixmass spectrometry assayTo prepare samples for liquid chromatography mass spectrometry (LC-MS) analysis, ~50 mg luminal contents were weighed into a 2 mL tube and 200 mg of zirconia/silica beads (0.1 mm) and 500 μL of organic solvent (acetonitrile:methanol:ddH2O (ratio 2:2:1)) with an internal standard mixture was added. Samples were homogenized for 2 min with a bead beater at maximum speed at RT. For serum, 20 µl were plated into a 96-well plate. Then 105 μL solvent (acetonitrile:methanol (ratio 1:1)) with an internal standard mixture (see above) was added. The internal standard mixture contained phenylalanine-d5, tryptophan-d5, ibuprofen-d4, tolfenamic acid-d4, estriol-d3, diclofenac-d4, warfarin-d5, oxfendazole-d3, chloramphenicol-d5, nafcillin-d5, and caffeine-d9, each at 80 nM final concentration. All samples were incubated at -20°C overnight, followed by centrifugation for 15 min, 3220 x g, 4°C. Fecal supernatants were collected and diluted with ddH2O (dilution 1:3) into a LC-MS 96-well plate, while serum was diluted with ddH2O (dilution 1:2). A pool of all diluted samples was prepared for fecal and seral extractions, respectively in a separate vial.Mus musculusblank samplesample preparation blankreference compound mixhttps://www.ebi.ac.uk/metabolights/MTBLS7382Arisha Patt. Helmholtz Zentrum München. Ingolstädter Landstraße 1 · D-85764 Neuherberg. arisha.patt@helmholtz-munich.de.Denise Selegato. denise.selegato@embl.de.Michael Zimmermann. European Molecular Biology Laboratory, Meyerhofstraße 1 69117 Heidelberg Germany. michael.zimmermann@embl.de.Raw data were centroided using Agilent DAReprocessor, aligned and processed with Mass Profiler Professional (Agilent, v15.1), and features were annotated against the METLIN database (v1233[AP1] ). Human Metabolome Database (HMDB) identifiers were derived from METLIN and compound classes were assigned based on HMDB (v5.0) (Wishart et al., 2022). The resulting feature table was further processed in R (v4.4.2) applying an adapted protocol for feature filtering (retaining features detected in ≥75% of samples in at least one condition), intensity correction based on fecal weight, blank removal, imputation, quantile normalization (normalize.quantiles function from the preprocessCore package (v1.64.0) (Bolstad, 2023) and log-transformation (Dricot et al., 2025). For multivariate analyses, data were additionally mean-centered and unit variance scaled (z-scored). [AP1]Doi 10.1007/978-1-0716-0239-3_9 InfectionCommunitydenise.selegato@embl.deColonic content and serum were collected from germ-free and mice colonized with OMM12 and SPF, separately. Metabolomicsultra-performance liquid chromatography-mass spectrometryMetabolomicsMus musculusuntargeted analysisPooled Samplesample preparation blankbloodmicrobiomereference compound mixexperimental sampleuntargeted metabolite profilingAgilent 6550 iFunnel Q-TOFblank sampleAgilent 1220 Infinity LCfecesultra-performance liquid chromatography-mass spectrometryMetabolomicsMus musculusuntargeted analysisPooled Samplesample preparation blankbloodmicrobiomereference compound mixexperimental sampleuntargeted metabolite profilingAgilent 6550 iFunnel Q-TOFblank sampleAgilent 1220 Infinity LCfecesThe qTOF (Agilent 6550) was operated in scanning mode (50–1700 m/z) at the following source parameters: VCap: 3500 V, nozzle voltage: 2000 V, gas temp: 225 °C; drying gas 13 L/min; nebulizer: 20 psig; sheath gas temp 225 °C; sheath gas flow 12 L/min. Online mass calibration was used throughout the run in a second ionization source and a constant flow of reference ion solution (112.9857 and 1033.9881 m/z). LC–MS/MS was performed to confirm metabolite identities, using the same methods as described above and the targeted-MS/MS mode of the instrument with a preferred inclusion list for parent ion with 20 ppm tolerance, Iso width set to ‘narrow width’ and collision energy set to either 10, 20, or 40 eV.Taurine5-methoxytryptamineNaringeninOleic Acid13-methyltetradecanoic acidGuanosineDocosahexanoic acidObeticholic AcidXanthurenic acid12-ketolithocholic acidDocosatetraenoic acidLithocholic acidIndole-3-acrylic acidUrsodeoxycholic acidDocosapentaenoic acid3,5-Dihydroxybenzoic acidEstriolIndole-3-carboxaldehydeKynurenic acidOxindole-3-acetic acid7,12-diketolithocholic acidIndoline-2-carboxylic acidPhenylalanineIndoxyl sulfateCholesterol-3-sulfateTryptophanMaltotrioseRiboflavineIndole-3-pyruvic acidCitric acidDeoxycholic acidMuricholic acid16-DehydroprogesteroneIndole-3-lactic acid2-Hydroxystearic acidIndole-3-propionic acidChenodeoxycholic acidfalseMicrobial metabolites calibrate innate immunity upon systemic viral infectionGut microbiome dysbiosis is often associated with immune-mediated diseases. Here, we used germ-free (GF) mice, the synthetic minimal consortium OMM12, and specific pathogen-free (SPF) mice to dissect the causal influence of the microbiome on anti-viral immunity. The lack of microbial diversity affected innate immune cells in their responsiveness upon Lymphocytic choriomeningitis virus (LCMV) infection. Single-cell RNA sequencing of myeloid cells from the small intestinal lamina propria revealed a strong impact of the microbial composition on activation of monocytes and other myeloid cell populations defined by an elevated response signature to type 1 interferons in GF and OMM12 mice. To link compositional changes in microbes to the divergent immune regulation upon LCMV infection, metabolomics analysis of the gut luminal content and serum at steady state and after infection was performed and revealed differences in the abundance of bile acids and tryptophan derivatives. LCMV infection itself only impacted on the intestinal metabolic composition of OMM12 and germfree mice, whereas SPF mice were largely resilient to infection-induced metabolic alterations. The metabolic composition of gnotobiotic mice leads to a reduced capacity of AhR activation. Among those alterations, tryptophan derivatives like indoline-2-carboxylic acid, indol-3-carbinol, 1,3-dihydro-(2H)-indol-2-one, indoxyl sulfate, indole-3-acrylic acid, and 5-methoxytryptamine are potential candidates with immunomodulatory capacities through AhR activation. Collectively, this study reveals a major impact of microbiota-induced, altered metabolism on innate immunity of myeloid cells after viral infection. Thereby, myeloid cell functionality can be dramatically shaped by the gut microbial composition and availability of certain metabolites, especially AhR ligands, which is of high relevance to further understand the host-microbiota interactions and to sharpen immune-modulating therapeutic strategies.2026-08-012026-08-01MTBLS7382