Research Note: Real-time fluorescence-based recombinase-aided amplification for rapid detection of Mycoplasma synoviae.

Mycoplasma synoviae rapid visual detection real-time recombinase-aided amplification

Journal

Poultry science
ISSN: 1525-3171
Titre abrégé: Poult Sci
Pays: England
ID NLM: 0401150

Informations de publication

Date de publication:
22 Jun 2024
Historique:
received: 02 04 2024
revised: 11 06 2024
accepted: 19 06 2024
medline: 13 7 2024
pubmed: 13 7 2024
entrez: 12 7 2024
Statut: aheadofprint

Résumé

Mycoplasma synoviae (MS) is an essential pathogenic mycoplasma in poultry worldwide, posing a serious threat to the poultry industry's health. Timely detection is imperative for early diagnosis, prevention, and control of MS infection. Current laboratory methods for MS detection are generally complicated, time-consuming, and require sophisticated equipment. Therefore, a simple and rapid method is urgently needed. This study developed a novel real-time fluorescence-based recombinase-aided amplification (RF-RAA) technique for detecting MS nucleic acids, enabling target gene amplification within 20 min at 39°C. The RF-RAA outcomes are interpretable in 2 modalities: real-time fluorescence monitoring employing a temperature-controlled fluorescence detector or direct visual inspection facilitated by a portable blue light transilluminator. This method exhibits robust specificity, demonstrating no cross-reactivity with various common poultry pathogens, and achieves high sensitivity, detecting as low as 10 copies/μL for the standard plasmid. Seventy-one clinical samples of chicken throat swabs were detected by RF-RAA and real-time fluorescence quantitative polymerase chain reaction (qPCR) methods. The diagnostic coincidence rates of qPCR with RF-RAA (fluorescence monitoring) and RF-RAA (visual observation) were determined to be 100% and 97.2% (69/71), respectively. In conclusion, the RF-RAA method developed in this study provides a rapid and visually observable approach for MS detection, offering a novel technique to diagnosing MS infection, especially in resource-limited settings.

Identifiants

pubmed: 38996740
pii: S0032-5791(24)00574-1
doi: 10.1016/j.psj.2024.103995
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

103995

Informations de copyright

Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

DISCLOSURES The authors declare no conflicts of interest.

Auteurs

Wenlong Xia (W)

Yancheng Engineering Research Center of Animal Biologics, School of Marine and Biological Engineering, Yancheng Teachers University, Yancheng 224007, China.

Shupei Yu (S)

Yancheng Animal Husbandry and Veterinary Station, Yancheng 224001, China.

Jing Huang (J)

Yancheng Engineering Research Center of Animal Biologics, School of Marine and Biological Engineering, Yancheng Teachers University, Yancheng 224007, China.

Yanan Li (Y)

Yancheng Engineering Research Center of Animal Biologics, School of Marine and Biological Engineering, Yancheng Teachers University, Yancheng 224007, China.

Pei Wang (P)

Yancheng Engineering Research Center of Animal Biologics, School of Marine and Biological Engineering, Yancheng Teachers University, Yancheng 224007, China.

Shujun Shen (S)

Yancheng Engineering Research Center of Animal Biologics, School of Marine and Biological Engineering, Yancheng Teachers University, Yancheng 224007, China.

Minsheng Feng (M)

Yancheng Engineering Research Center of Animal Biologics, School of Marine and Biological Engineering, Yancheng Teachers University, Yancheng 224007, China.

Pengcheng Fu (P)

Yancheng Engineering Research Center of Animal Biologics, School of Marine and Biological Engineering, Yancheng Teachers University, Yancheng 224007, China.

Huilin Guan (H)

Yancheng Engineering Research Center of Animal Biologics, School of Marine and Biological Engineering, Yancheng Teachers University, Yancheng 224007, China.

Zhongjun Fan (Z)

Yancheng Engineering Research Center of Animal Biologics, School of Marine and Biological Engineering, Yancheng Teachers University, Yancheng 224007, China. Electronic address: fzj811@126.com.

Classifications MeSH