Comparative Analysis of Phenotypic and Genotypic Antibiotic Susceptibility of Pasteurella multocida Isolated from Various Host Species in France and Hungary

<b>Background/Objectives</b>: <i>Pasteurella multocida</i> is responsible for a wide variety of animal diseases worldwide, causing major economic losses. These infections are usually treated with antibiotics; however, the emergence of multidrug-resistant (MDR) strains is increasingly hindering. Understanding antibiotic resistance in <i>P. multocida</i> is important for effective treatment strategies and public health, as it impacts both animal and human welfare. <b>Methods</b>: In this study, the antibiotic susceptibility of 80 <i>P. multocida</i> isolates was evaluated by phenotypic (disk diffusion and broth microdilution) and genotypic analysis via whole-genome sequencing, with particular attention to the occurrence of MDR strains. The strains were tested against antibiotics from nine antimicrobial classes (penicillins, cephalosporins, aminoglycosides, tetracyclines, macrolides, fluoroquinolones, lincosamides, phenicols, and sulfonamides). Antimicrobial resistance gene (ARG) sequences and single-nucleotide polymorphisms (SNPs) were evaluated in paired reads using the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) and the Comprehensive Antibiotic Resistance Database (CARD) via Resistance Gene Identifier (RGI), respectively. <b>Results</b>: Phenotypic results indicated that cephalosporins and phenicols were the most effective drugs against <i>P. multocida</i>; however, the majority of strains were also susceptible to fluoroquinolones and tetracyclines. In contrast, high resistance rates were observed to sulfamethoxazole and clindamycin. The most prevalent resistance genes were <i>str</i>A, <i>sul</i>2, and <i>tet</i>H, while none of the strains harbored the <i>bla</i>-<sub>TEM</sub> or <i>erm</i> (42) genes. <b>Conclusions</b>: Of the two phenotypic methods, MIC values showed a stronger positive correlation with genotypic results, making it a more suitable method for determining antibiotic susceptibility. The phenotypic results for phenicols, tetracyclines, and fluoroquinolones showed a strong correlation with the detected resistance genes. In contrast, resistance to sulfamethoxazole, β-lactams, and macrolides remained genetically unexplained, suggesting the existence of additional resistance mechanisms to be explored.

Authors

Institutions

Publication Details

Journal
Antibiotics
Published
2025-09-08
DOI
https://doi.org/10.3390/antibiotics14090906
Primary Topic
Microbial infections and disease research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comparative Analysis of Phenotypic and Genotypic Antibiotic Susceptibility of Pasteurella multocida Isolated from Various Host Species in France and Hungary

Tibor Magyar, Marianna Domán, Enikő Wehmann, Katalin Pintér et al.
Antibiotics
Microbial infections and disease research
article

Comparative Analysis of Phenotypic and Genotypic Antibiotic Susceptibility of Pasteurella multocida Isolated from Various Host Species in France and Hungary

Tibor Magyar, Marianna Domán, Enikő Wehmann, Katalin Pintér, Hubert Gantelet
article en

Abstract

<b>Background/Objectives</b>: <i>Pasteurella multocida</i> is responsible for a wide variety of animal diseases worldwide, causing major economic losses. These infections are usually treated with antibiotics; however, the emergence of multidrug-resistant (MDR) strains is increasingly hindering. Understanding antibiotic resistance in <i>P. multocida</i> is important for effective treatment strategies and public health, as it impacts both animal and human welfare. <b>Methods</b>: In this study, the antibiotic susceptibility of 80 <i>P. multocida</i> isolates was evaluated by phenotypic (disk diffusion and broth microdilution) and genotypic analysis via whole-genome sequencing, with particular attention to the occurrence of MDR strains. The strains were tested against antibiotics from nine antimicrobial classes (penicillins, cephalosporins, aminoglycosides, tetracyclines, macrolides, fluoroquinolones, lincosamides, phenicols, and sulfonamides). Antimicrobial resistance gene (ARG) sequences and single-nucleotide polymorphisms (SNPs) were evaluated in paired reads using the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) and the Comprehensive Antibiotic Resistance Database (CARD) via Resistance Gene Identifier (RGI), respectively. <b>Results</b>: Phenotypic results indicated that cephalosporins and phenicols were the most effective drugs against <i>P. multocida</i>; however, the majority of strains were also susceptible to fluoroquinolones and tetracyclines. In contrast, high resistance rates were observed to sulfamethoxazole and clindamycin. The most prevalent resistance genes were <i>str</i>A, <i>sul</i>2, and <i>tet</i>H, while none of the strains harbored the <i>bla</i>-<sub>TEM</sub> or <i>erm</i> (42) genes. <b>Conclusions</b>: Of the two phenotypic methods, MIC values showed a stronger positive correlation with genotypic results, making it a more suitable method for determining antibiotic susceptibility. The phenotypic results for phenicols, tetracyclines, and fluoroquinolones showed a strong correlation with the detected resistance genes. In contrast, resistance to sulfamethoxazole, β-lactams, and macrolides remained genetically unexplained, suggesting the existence of additional resistance mechanisms to be explored.

AntibioticsVol. 14(9)
Centre Hospitalier de Beauvais (FR), HUN-REN Veterinary Medical Research Institute (HU), University of Veterinary Medicine (HU)
Openalex Percentile: Top 78%
Microbial infections and disease research
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.