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DOI 10.1186/s12917-025-05278-7

Медицинская библиотека · BMC veterinary research · 2026

A rapid and field-deployable RAA-CRISPR/Cas12a platform for detection of Mycoplasma gallisepticum in poultry.

Hu Qiao, Zhang Rongrong, Liu Jiaying, Zhang Wenting, Liao Xia, Guo Yunqing, Lu Qin, Yang Bokai, Zhang Tengfei, Zhai Xinguo, Luo Qingping

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Аннотация

BACKGROUND

Mycoplasma gallisepticum (MG) is a major pathogen that causes respiratory diseases 14in poultry, resulting in reduced production and severe economic losses. Current MG detection methods are time-consuming, labor-intensive, and expensive. Hence, the rapid and accurate detection of MG is critical for effective disease control. Therefore, this study aimed to develop a dual-mode diagnostic assay for sensitive and specific detection of MG by combining recombinase-aided amplification (RAA) with CRISPR/Cas12a technology. Conserved regions of the mgc2 gene were used for primer and CRISPR RNA design, and the reaction conditions were optimized to maximize detection efficiency.

RESULTS

The assay achieved a detection limit of 2 copies/µL and demonstrated high specificity against seven other common avian pathogens. Detection was visualized within 1 h using either fluorescence or lateral flow dipstick. Moreover, clinical validation of chicken samples showed complete concordance with quantitative real-time polymerase chain reaction results. Furthermore, an epidemiological investigation revealed that chickens had the highest positivity rate for MG among chickens, ducks, and pigeons in Hubei Province.

CONCLUSIONS

This simple, rapid, field-deployable method is valuable for timely MG surveillance and effective disease management in poultry production.

Для цитирования: Hu Qiao, Zhang Rongrong, Liu Jiaying, Zhang Wenting, Liao Xia, Guo Yunqing, Lu Qin, Yang Bokai, Zhang Tengfei, Zhai Xinguo, Luo Qingping. A rapid and field-deployable RAA-CRISPR/Cas12a platform for detection of Mycoplasma gallisepticum in poultry.. BMC veterinary research. 2026. DOI: 10.1186/s12917-025-05278-7.

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