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Record W4417276958 · doi:10.1093/jambio/lxaf303

The influence of short-chain fatty acids on the survival and virulence of <i>Arcobacter butzleri</i>

2025· article· en· W4417276958 on OpenAlexaff
Inês M Fonseca, Cristiana Mateus, Alexandre C.C. Vieira, Fernanda Domingues, Vera Manageiro, Mónica Oleastro, Susana Ferreira

Bibliographic record

VenueJournal of Applied Microbiology · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsAgriculture and Agri-Food Canada
FundersMinistério da Ciência, Tecnologia e Ensino Superior
KeywordsVirulencePathogenBacteriaFatty acidEnterobacteriaceaeVirulence factor

Abstract

fetched live from OpenAlex

AIMS: Arcobacter butzleri, a widespread bacterium linked to gastrointestinal disease, can bypass host colonization resistance mechanisms; however, its response to short-chain fatty acids (SCFAs) remains poorly understood. This study investigated the impact of SCFAs on A. butzleri's survival and virulence. METHODS AND RESULTS: Eight A. butzleri isolates were assessed under varying concentrations of individual SCFAs and mixtures (m-SCFAs). Higher SCFAs concentrations inhibited bacterial growth in a strain-dependent manner. Transcript analysis of putative virulence genes revealed upregulation of ciaB and flaA across most m-SCFAs concentrations, while luxS expression increased at 90 mM. SCFAs generally reduced bacterial motility, with sodium propionate reducing motility but enhancing biofilm-forming ability in the model strain. Additionally, SCFAs exposure decreased the ability of A. butzleri to adhere to and invade the Caco-2 intestinal epithelial cell line. Whole-genome sequencing of the eight A. butzleri isolates revealed extensive genetic diversity, particularly in virulence- and stress-associated genes, although consistent genotype/phenotype correlations were not observed. CONCLUSIONS: Altogether, these findings demonstrate that SCFAs modulate A. butzleri survival and virulence, providing novel insights into their significance in shaping pathogen behaviour and host-pathogen interactions.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.758
Threshold uncertainty score0.209

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.013
GPT teacher head0.223
Teacher spread0.211 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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