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Record W4407137266 · doi:10.1128/aem.02265-24

The impact of wild-boar-derived microbiota transplantation on piglet microbiota, metabolite profile, and gut proinflammatory cytokine production differs from sow-derived microbiota

2025· article· en· W4407137266 on OpenAlexafffund
Rajibur Rahman, Janelle M. Fouhse, Tingting Ju, Yi Fan, Tulika Bhardwaj, Ryan K. Brook, Roman Nosach, John J. Harding, Benjamin P. Willing

Bibliographic record

VenueApplied and Environmental Microbiology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsUniversity of SaskatchewanUniversity of CalgaryUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAnimal and Plant Health Inspection ServiceAlberta Livestock and Meat AgencyUniversity of Saskatchewan
KeywordsBiologyLactobacillusMicrobiologyGut floraFecesImmune systemColonisation resistanceMetaboliteTransplantationColonizationImmunologyFood scienceFermentationInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

ABSTRACT Colonization of co-evolved, species-specific microbes in early life plays a crucial role in gastrointestinal development and immune function. This study hypothesized that modern pig production practices have resulted in the loss of co-evolved species and critical symbiotic host-microbe interactions. To test this, we reintroduced microbes from wild boars (WB) into conventional piglets to explore their colonization dynamics and effects on gut microbial communities, metabolite profiles, and immune responses. At postnatal day (PND) 21, 48 piglets were assigned to four treatment groups: (i) WB-derived mixed microbial community (MMC), (ii) sow-derived MMC, (iii) a combination of WB and sow MMC (Mix), or (iv) Control (PBS). Post-transplantation analyses at PND 48 revealed distinct microbial communities in WB-inoculated piglets compared with Controls, with trends toward differentiation from Sow but not Mix groups. WB-derived microbes were more successful in colonizing piglets, particularly in the Mix group, where they competed with Sow-derived microbes. WB group cecal digesta enriched with Lactobacillus helveticus , Lactobacillus mucosae , and Lactobacillus pontis . Cecal metabolite analysis showed that WB piglets were enriched in histamine, acetyl-ornithine, ornithine, citrulline, and other metabolites, with higher histamine levels linked to Lactobacillus abundance. WB piglets exhibited lower cecal IL-1β and IL-6 levels compared with Control and Sow groups, whereas the Mix group showed reduced IFN-γ, IL-2, and IL-6 compared with the Sow group. No differences in weight gain, fecal scores, or plasma cytokines were observed, indicating no adverse effects. These findings support that missing WB microbes effectively colonize domestic piglets and may positively impact metabolite production and immune responses. IMPORTANCE This study addresses the growing concern over losing co-evolved, species-specific microbes in modern agricultural practices, particularly in pig production. The implementation of strict biosecurity measures and widespread antibiotic use in conventional farming systems may disrupt crucial host-microbe interactions that are essential for gastrointestinal development and immune function. Our research demonstrates that by reintroducing wild boar-derived microbes into domestic piglets, these microbes can successfully colonize the gut, influence microbial community composition, and alter metabolite profiles and immune responses without causing adverse effects. These findings also suggest that these native microbes can fill an intestinal niche, positively impacting immune activation. This research lays the groundwork for future strategies to enhance livestock health and performance by restoring natural microbial populations that produce immune-modulating metabolites.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.003
GPT teacher head0.204
Teacher spread0.201 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2025
Admission routes2
Has abstractyes

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