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PXD070601

PXD070601 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleIntegration of human microbiota (SIHUMIx) and zebrafish models reveals microbiome-mediated host responses to azoxystrobin
DescriptionThe gut microbiome is essential for neurodevelopment via bidirectional gut-brain axis signaling, yet environmental chemicals can potentially disrupt this communication by altering community structure and xenobiotic metabolism. In this study, we investigated whether the fungicide azoxystrobin, a known metabolic disruptor, modulates microbiome composition and function to influence neurobehavior. We integrated a simplified human gut microbiota model (SIHUMIx) with a vertebrate host model (larval zebrafish), to elucidate microbiome-mediated mechanisms of xenobiotic neurotoxicity. SIHUMIx was exposed to azoxystrobin for 7 days at 10% of the acceptable daily intake, followed by recovery. Integrated metaproteomic and metabolomic analyses revealed functional reprogramming of the microbiota, characterized by upregulation of vitamin and cofactor biosynthesis, nutrient acquisition, and detoxification pathways, and decreased carbohydrate fermentation and amino acid turnover, consistent with reduced short-chain fatty acid levels. Microbiome-depleted and SIHUMIx-colonized larvae were exposed to azoxystrobin at 4 days post fertilization and neurobehavioral outcomes were assessed after 24 h using the Visual and Acoustic Motor Response assay. Azoxystrobin exposure disrupted non-associative habituation learning independent of microbiome status but induced dark phase-hyperactivity only in colonized larvae, indicating a microbiome-dependent phenotype. Targeted metabolomics revealed lower serotonin levels in microbiome-depleted larvae relative to colonized controls, and that azoxystrobin exposure reduced serotonin in colonized larvae toward depleted levels. These results suggest that microbiota-dependent serotonergic signaling may modulate host responses to azoxystrobin. This integrated ex vivo-in vivo approach supports the concept that the microbiome is a key determinant of neurotoxic responses and underscores the importance of incorporating microbiome-mediated effects into chemical risk assessment frameworks.
HostingRepositoryPRIDE
AnnounceDate2026-04-27
AnnouncementXMLSubmission_2026-04-26_19:48:56.667.xml
DigitalObjectIdentifier
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportUnsupported dataset by repository
PrimarySubmitterNico Jehmlich
SpeciesList scientific name: Escherichia coli (strain K12); NCBI TaxID: NEWT:83333; scientific name: Lactobacillus plantarum subsp. plantarum; NCBI TaxID: NEWT:337330; scientific name: Thomasclavelia ramosa; NCBI TaxID: NEWT:1547; scientific name: Bacteroides thetaiotaomicron; NCBI TaxID: NEWT:818; scientific name: Clostridium butyricum DSM 10702; NCBI TaxID: NEWT:1316931; scientific name: Anaerostipes caccae; NCBI TaxID: NEWT:105841; scientific name: Bifidobacterium longum NCC2705; NCBI TaxID: NEWT:206672; scientific name: Blautia producta ATCC 27340 = DSM 2950; NCBI TaxID: NEWT:1121114;
ModificationListmonohydroxylated residue; iodoacetamide derivatized residue
InstrumentQ Exactive HF
Dataset History
RevisionDatetimeStatusChangeLog Entry
02025-11-11 14:06:29ID requested
12026-04-26 19:48:57announced
Publication List
Wray C, Casta, ñ, eda-Monsalve V, Engelmann B, Rolle-Kampczyk UE, Schweiger N, Gutsfeld S, Ghosh D, Kader S, Tyler CR, Jehmlich N, Tal T, Integration of human microbiota (SIHUMIx) and zebrafish models reveals microbiome-mediated host responses to azoxystrobin. Toxicol Sci, 209(4):(2026) [pubmed]
10.1093/toxsci/kfag022;
Keyword List
submitter keyword: Metabolomics, SIHUMIx, Zebrafish, Azoxystrobin,Microbiome
Contact List
Nico Jehmlich
contact affiliationHelmholtz Centre for Environmental Research GmbH - UFZ Department of Molecular Toxicology Permoserstraße 15, 04318 Leipzig, Germany
contact emailnico.jehmlich@ufz.de
lab head
Nico Jehmlich
contact affiliationHelmholtz-Centre for Environmental Research - UFZ
contact emailnico.jehmlich@ufz.de
dataset submitter
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