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Record W4407165004 · doi:10.1016/j.crmicr.2025.100358

Multi-omics unveils strain-specific neuroactive metabolite production linked to inflammation modulation by Bacteroides and their extracellular vesicles

2025· article· en· W4407165004 on OpenAlexafffund
Basit Yousuf, Walid Mottawea, Galal Ali Esmail, Nazila Nazemof, Nour Elhouda Bouhlel, Emmanuel Njoku, Yingxi Li, Xu Zhang, Zoran Minić, Riadh Hammami

Bibliographic record

VenueCurrent Research in Microbial Sciences · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsHealth CanadaUniversity of Ottawa
FundersShenzhen Institutes of Advanced Technology, Chinese Academy of SciencesChinese Academy of SciencesNatural Sciences and Engineering Research Council of CanadaShenzhen Institute of Synthetic BiologyUniversity of Ottawa
KeywordsExtracellular vesiclesMetaboliteInflammationBacteroidesExtracellularModulation (music)Strain (injury)ChemistryBiologyMicrobiologyCell biologyBiochemistryBacteriaImmunologyGeneticsPhysics

Abstract

fetched live from OpenAlex

• Bacteroides species produce a myriad of neurotransmitter-related metabolites. • Bacteroides signaling via EVs may modulate the gut-brain axis and immune responses. • B. finegoldii shows anti-inflammatory characteristics via GABA and EV production. • Bacteroides and their EVs hold great promise as next-generation psychobiotics. Bacteroides species are key members of the human gut microbiome and play crucial roles in gut ecology, metabolism, and host-microbe interactions. This study investigated the strain-specific production of neuroactive metabolites by 18 Bacteroidetes (12 Bacteroides , 4 Phocaeicola , and 2 Parabacteroides ) using multi-omics approaches. Genomic analysis revealed a significant potential for producing GABA, tryptophan, tyrosine, and histidine metabolism-linked neuroactive compounds. Using untargeted and targeted metabolomics, we identified key neurotransmitter-related or precursor metabolites, including GABA, l -tryptophan, 5-HTP, normelatonin, kynurenic acid, l -tyrosine, and norepinephrine, in a strain- and media-specific manner, with GABA (1–2 mM) being the most abundant. Additionally, extracellular vesicles (EVs) produced by Bacteroides harbor multiple neuroactive metabolites, mainly GABA, and related key enzymes. We used CRISPR/Cas12a-based gene engineering to create a knockout mutant lacking the glutamate decarboxylase gene ( gadB ) to demonstrate the specific contribution of Bacteroides finegoldii -derived GABA in modulating intestinal homeostasis. Cell-free supernatants from wild-type (WT, GABA+) and Δ gadB (GABA-) provided GABA-independent reinforcement of epithelial membrane integrity in LPS-treated Caco-2/HT29-MTX co-cultures. EVs from WT and Δ gadB attenuated inflammatory immune response of LPS-treated RAW264.7 macrophages, with reduced pro-inflammatory cytokines (IL-1β and IL-6), downregulation of TNF-α, and upregulation of IL-10 and TGF-β. GABA production by B. finegoldii had a limited impact on gut barrier integrity but a significant role in modulating inflammation. This study is the first to demonstrate the presence of a myriad of neuroactive metabolites produced by Bacteroides species in a strain- and media-specific manner in supernatant and EVs, with GABA being the most dominant metabolite and influencing immune responses.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.451

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.083
GPT teacher head0.380
Teacher spread0.297 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2025
Admission routes2
Has abstractyes

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