SET-M33 peptide as a selective <i>in vitro</i> antimicrobial agent against the porcine respiratory pathogen <i>Glaesserella parasuis</i>

As we face the threat from bacterial pathogens that are resistant to many conventional antibiotics, many current research efforts focus on expanding our arsenal of antimicrobial compounds. However, identifying use cases in which such new antimicrobials can effectively target pathogens while minimizing collateral damage in the commensal microbiota remains a challenge. To tackle this challenge, we focused on one new antimicrobial, the synthetic antimicrobial peptide SET-M33, and examined its ability to target porcine respiratory pathogens and a collection of porcine commensal nasal microbiota members <i>in vitro</i>. Our experiments revealed three key results. First, there were large differences in SET-M33 sensitivity across the tested strains. In particular, pathogenic <i>Glaesserella parasuis</i> was highly sensitive to SET-M33 at concentrations that did not affect the growth of most commensal strains. Second, some of the tested commensal strains (<i>Rothia nasimurium</i> and <i>Staphylococcus aureus</i>) were able to inactivate SET-M33 during <i>in vitro</i> cultivation. Third, despite this potential for SET-M33 inactivation by commensal strains, SET-M33 was still able to selectively eliminate pathogenic <i>G. parasuis</i> from <i>in vitro</i> co-cultures that also contained <i>R. nasimurium</i>. Overall, this study highlights the substantial complexity that emerges from the interplay between antimicrobials, pathogens, and commensals, even within a comparatively simple <i>in vitro</i> system, and provides a template for identifying suitable use cases for newly developed antimicrobials.IMPORTANCEAntimicrobial resistance in pathogenic bacteria is a major global challenge. To tackle it, antimicrobial peptides (AMPs) have emerged as particularly promising candidates, and recent years have seen a rapid expansion of the available AMP arsenal. However, identifying good "use cases" for such AMPs-that is, scenarios in which an AMP not only inhibits a pathogen of interest but also avoids disrupting the commensal microbiota-remains challenging. Here, we aimed to develop an experimental framework that enables the rapid detection of such use cases <i>in vitro</i>. As a test case, we focused on the synthetic AMP SET-M33 and examined its effect on several respiratory porcine pathogens and a collection of commensal nasal microbiota strains. We found that even within such a comparatively simple <i>in vitro</i> model system, there is substantial complexity that emerges from the interplay among AMPs, pathogens, and commensals.

Authors

Institutions

Publication Details

Journal
Microbiology Spectrum
Published
2026-02-18
DOI
https://doi.org/10.1128/spectrum.03918-25
Primary Topic
Antimicrobial Peptides and Activities
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SET-M33 peptide as a selective in vitro antimicrobial agent against the porcine respiratory pathogen Glaesserella parasuis

Karl Kochanowski, Virginia Aragón, Marta Cerdà‐Cuéllar, Ana Laura Pereira Lourenço et al.
Microbiology Spectrum
Antimicrobial Peptides and Activities
article

SET-M33 peptide as a selective in vitro antimicrobial agent against the porcine respiratory pathogen Glaesserella parasuis

Karl Kochanowski, Virginia Aragón, Marta Cerdà‐Cuéllar, Ana Laura Pereira Lourenço, Oussama Rouam el Khatab, Chiara Falciani, Alessandro Pini
article en

Abstract

As we face the threat from bacterial pathogens that are resistant to many conventional antibiotics, many current research efforts focus on expanding our arsenal of antimicrobial compounds. However, identifying use cases in which such new antimicrobials can effectively target pathogens while minimizing collateral damage in the commensal microbiota remains a challenge. To tackle this challenge, we focused on one new antimicrobial, the synthetic antimicrobial peptide SET-M33, and examined its ability to target porcine respiratory pathogens and a collection of porcine commensal nasal microbiota members <i>in vitro</i>. Our experiments revealed three key results. First, there were large differences in SET-M33 sensitivity across the tested strains. In particular, pathogenic <i>Glaesserella parasuis</i> was highly sensitive to SET-M33 at concentrations that did not affect the growth of most commensal strains. Second, some of the tested commensal strains (<i>Rothia nasimurium</i> and <i>Staphylococcus aureus</i>) were able to inactivate SET-M33 during <i>in vitro</i> cultivation. Third, despite this potential for SET-M33 inactivation by commensal strains, SET-M33 was still able to selectively eliminate pathogenic <i>G. parasuis</i> from <i>in vitro</i> co-cultures that also contained <i>R. nasimurium</i>. Overall, this study highlights the substantial complexity that emerges from the interplay between antimicrobials, pathogens, and commensals, even within a comparatively simple <i>in vitro</i> system, and provides a template for identifying suitable use cases for newly developed antimicrobials.IMPORTANCEAntimicrobial resistance in pathogenic bacteria is a major global challenge. To tackle it, antimicrobial peptides (AMPs) have emerged as particularly promising candidates, and recent years have seen a rapid expansion of the available AMP arsenal. However, identifying good "use cases" for such AMPs-that is, scenarios in which an AMP not only inhibits a pathogen of interest but also avoids disrupting the commensal microbiota-remains challenging. Here, we aimed to develop an experimental framework that enables the rapid detection of such use cases <i>in vitro</i>. As a test case, we focused on the synthetic AMP SET-M33 and examined its effect on several respiratory porcine pathogens and a collection of commensal nasal microbiota strains. We found that even within such a comparatively simple <i>in vitro</i> model system, there is substantial complexity that emerges from the interplay among AMPs, pathogens, and commensals.

Microbiology Spectrum
University of Siena (IT), Universitat Autònoma de Barcelona (ES), Centre de Recerca en Sanitat Animal (ES), Lancet Laboratories (ZA), Azienda Ospedaliera Universitaria Senese (IT), National Centre for Clinical Research on Emerging Drugs (AU)
Openalex Percentile: Top 51%
Antimicrobial Peptides and Activities
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.