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Development, validation, and application of SYBR green-based qPCR assays for detection and quantification of tetA, tetB, and tetO genes in poultry and associated environments
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Development, validation, and application of SYBR green-based qPCR assays for detection and quantification of tetA, tetB, and tetO genes in poultry and associated environments
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Development, validation, and application of SYBR green-based qPCR assays for detection and quantification of tetA, tetB, and tetO genes in poultry and associated environments
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Journal Article
Development, validation, and application of SYBR green-based qPCR assays for detection and quantification of tetA, tetB, and tetO genes in poultry and associated environments
2026
Overview
Tetracycline resistance genes (
genes) are among the most prevalent antimicrobial resistance determinants in poultry, raising concerns about their dissemination across animal, human, and environmental interfaces. This study aimed to develop and validate rapid, sensitive, and cost-effective SYBR Green-based quantitative PCR (qPCR) assays for the detection and quantification of
, and
genes in bacterial isolates and complex matrices.
Following
and end-point PCR screening of ten published primer pairs, the most specific combinations were optimized for annealing temperature and primer concentration, and their analytical and diagnostic performances were evaluated.
The assays exhibited efficiencies of 80.7-93.6%, strong linearity (
> 0.99), and high repeatability (CV < 5%). Diagnostic sensitivity and specificity ranged from 92.11-100% and 91.38-100%, respectively. Application of the assays to fecal, cecal, and drinking water samples collected from free-range and short-chain poultry farms revealed that all but one samples were positive for at least one of the investigated
genes, with prevalence ranging from 65.79% (
) to 93.33% (
).
These SYBR Green-based qPCR assays provide a robust, quantitative, and affordable tool for monitoring
genes dissemination in poultry and associated environments. Their simplicity and reproducibility make them particularly suitable for large-scale surveillance programs and for use in settings where resources or access to probe-based platforms are limited.
