Comprehensive assessment of four different molecular genotyping panels to characterize avian pathogenic <i>E. coli</i> (APEC) for epidemiological studies

Avian pathogenic Escherichia coli (APEC) is a leading cause of colibacillosis in poultry worldwide. Molecular genotyping using polymerase chain reaction is a rapid and effective way to separate APEC from commensal E. coli in poultry. This study assessed the accuracy of four different molecular genotyping panels in a head-to-head comparison, using 250 APEC isolates from diseased birds and 106 fecal E. coli (AFEC) isolates from healthy birds. The cut-off value of all four panels was observed and optimal cut-off values with sensitivity and specificity were suggested in this study. The results found that the APECtyper panel had the highest sensitivity (81.2%) being significantly different to the other three panels, while the 9-gene panel demonstrated the highest specificity (89.6%). The cut-off of the 13-gene panel was optimized with a predicted probability of 12%, balancing sensitivity (57.2%) and specificity (75.5%), which was used in this study. Overall, three of the four panels except the 13-gene panel showed good performance with distinct strengths. This research provides valuable insights, but further studies are needed to confirm the reliability and reproducibility of these assays across different geographical regions, various poultry populations, and diverse field conditions.

Authors

Institutions

Publication Details

Journal
Letters in Applied Microbiology
Published
2025-11-28
DOI
https://doi.org/10.1093/lambio/ovaf134
Primary Topic
Escherichia coli research studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comprehensive assessment of four different molecular genotyping panels to characterize avian pathogenic E. coli (APEC) for epidemiological studies

Catherine M. Logue, Roy D. Berghaus, Karen L. Jones, Klao Runcharoon et al.
Letters in Applied Microbiology
Escherichia coli research studies
article

Comprehensive assessment of four different molecular genotyping panels to characterize avian pathogenic E. coli (APEC) for epidemiological studies

Catherine M. Logue, Roy D. Berghaus, Karen L. Jones, Klao Runcharoon, Margaret E Favro
article en

Abstract

Avian pathogenic Escherichia coli (APEC) is a leading cause of colibacillosis in poultry worldwide. Molecular genotyping using polymerase chain reaction is a rapid and effective way to separate APEC from commensal E. coli in poultry. This study assessed the accuracy of four different molecular genotyping panels in a head-to-head comparison, using 250 APEC isolates from diseased birds and 106 fecal E. coli (AFEC) isolates from healthy birds. The cut-off value of all four panels was observed and optimal cut-off values with sensitivity and specificity were suggested in this study. The results found that the APECtyper panel had the highest sensitivity (81.2%) being significantly different to the other three panels, while the 9-gene panel demonstrated the highest specificity (89.6%). The cut-off of the 13-gene panel was optimized with a predicted probability of 12%, balancing sensitivity (57.2%) and specificity (75.5%), which was used in this study. Overall, three of the four panels except the 13-gene panel showed good performance with distinct strengths. This research provides valuable insights, but further studies are needed to confirm the reliability and reproducibility of these assays across different geographical regions, various poultry populations, and diverse field conditions.

Letters in Applied MicrobiologyVol. 78(12)
University of Georgia (US)
Openalex Percentile: Top 68%
Escherichia coli research studies
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.