Evidence map›Paper›PMID 39948046›Full record

ArticleAnimal models and experimental medicine2025

Quorum quenching enzymes disrupt bacterial communication in a sex- and dose-dependent manner.

Aneesh Syal, Maria Martell, Rakesh Sikdar, Matthew Dietz, Zachary Ziegert, Cyrus Jahansouz, Mikael H Elias, Christopher Staley

Abstract read
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Article in Animal models and experimental medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Aneesh SyalDivision of Basic and Translational Research, Department of Surgery, University of Minnesota, Minneapolis, Minnesota, USA.
Maria MartellDivision of Basic and Translational Research, Department of Surgery, University of Minnesota, Minneapolis, Minnesota, USA.
Rakesh SikdarBioTechnology Institute, University of Minnesota, St. Paul, Minnesota, USA.
Matthew DietzDivision of Basic and Translational Research, Department of Surgery, University of Minnesota, Minneapolis, Minnesota, USA.
Zachary ZiegertDivision of Basic and Translational Research, Department of Surgery, University of Minnesota, Minneapolis, Minnesota, USA.
Cyrus JahansouzDivision of Colon and Rectal Surgery, Department of Surgery, University of Minnesota, Minneapolis, Minnesota, USA.
Mikael H EliasBioTechnology Institute, University of Minnesota, St. Paul, Minnesota, USA.
Christopher StaleyDivision of Basic and Translational Research, Department of Surgery, University of Minnesota, Minneapolis, Minnesota, USA.ORCID 0000-0002-2309-0083

Funding

Biotechnology Institute and the MnDrive initiative (to MHE)
6 · The paper itself

Abstract

backgroundOver the past 50 years, the incidence of obesity has gradually increased, necessitating investigation into the multifactorial contributors to this disease, including the gut microbiota. Bacteria within the human gut microbiome communicate using a density-dependent process known as quorum sensing (QS), in which autoinducer (AI) molecules (e.g., N-acyl-homoserine lactones [AHLs]) are produced to enable bacterial interactions and regulate gene expression.

methodsWe aimed to disrupt QS using quorum quenching (QQ) lactonases GcL and SsoPox, which cleave AHL signaling molecules in a taxa-specific manner based on differing enzyme affinities for different substrates. We hypothesized that QQ hinders signals from obesity-associated pathobionts, thereby slowing or preventing obesity.

resultsIn a murine model of diet-induced obesity, we observed GcL and SsoPox treatments have separate sex-dependent and dose-dependent effects on intestinal community composition and diversity. Notably, male mice given 2 mg/mL SsoPox exhibited significant changes in the relative abundances of gram-negative taxa, including Porphyromonadaceae, Akkermansiaceae, Muribaculaceae, and Bacteroidales (Kruskal-Wallis p < 0.001). Additionally, we used covariance matrix network analysis to model bacterial taxa co-occurrence due to QQ enzyme administration. There were more associations among taxa in control mice, particularly among gram-negative bacteria, whereas mice receiving SsoPox had the fewest associations.

conclusionsOverall, our study establishes proof of concept that QQ is a targetable strategy for microbial control in vivo. Further characterization and dosage optimization of QQ enzymes are necessary to harness their therapeutic capability for the treatment of chronic microbial-associated diseases.

Indexed as

Carboxylic Ester HydrolasesGastrointestinal MicrobiomeQuorum SensingAnimalsFemaleMaleMiceMice, Inbred C57BLObesitySex FactorsCarboxylic Ester Hydrolasesmicrobiomemicrobiota therapeuticsobesityquorum sensing

Identifiers

PMID39948046
PMCPMC11904096

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.