A Lincomycin-Specific Antibody Was Developed Using Hapten Prediction, and an Immunoassay Was Established to Detect Lincomycin in Pork and Milk.

ELISA lincomycin milk monoclonal antibody pork

Journal

Foods (Basel, Switzerland)
ISSN: 2304-8158
Titre abrégé: Foods
Pays: Switzerland
ID NLM: 101670569

Informations de publication

Date de publication:
29 Sep 2024
Historique:
received: 24 07 2024
revised: 02 09 2024
accepted: 18 09 2024
medline: 16 10 2024
pubmed: 16 10 2024
entrez: 16 10 2024
Statut: epublish

Résumé

Prolonged consumption of animal-derived foods containing high levels of lincomycin (LIN) residues can adversely impact human health. Therefore, it is essential to develop specific antibodies and immunoassay methods for LIN. This study utilized computational chemistry to predict the efficacy of LIN haptens prior to chemical synthesis, with subsequent confirmation obtained through an immunization experiment. A hybridoma cell line named LIN/1B11 was established, which is specific to LIN. The optimized indirect competitive enzyme-linked immunosorbent assay (ic-ELISA) method exhibited high specificity for detecting LIN residues, with an IC50 value of 0.57 ± 0.03 µg/kg. The method effectively detected LIN residues in pork and milk samples, achieving a limit of detection (LOD) ranging from 0.81 to 1.20 µg/kg and a limit of quantification (LOQ) ranging from 2.09 to 2.29 µg/kg, with recovery rates between 81.9% and 108.8%. This study offers a valuable tool for identifying LIN residues in animal-derived food products. Furthermore, the efficient hapten prediction method presented herein improves antibody preparation efficiency and provides a simple method for researchers in screening haptens.

Identifiants

pubmed: 39410153
pii: foods13193118
doi: 10.3390/foods13193118
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : This work was supported by 2019 National Risk Assessment of Quality and Safety of Agricultural Product
ID : GJFP2019027

Auteurs

Yuhan Shang (Y)

National Reference Laboratory of Veterinary Drug Residues (HZAU), Huazhong Agricultural University, Wuhan 430070, China.
National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya 572024, China.

Dandan Zhang (D)

National Reference Laboratory of Veterinary Drug Residues (HZAU), Huazhong Agricultural University, Wuhan 430070, China.

Yun Shen (Y)

National Reference Laboratory of Veterinary Drug Residues (HZAU), Huazhong Agricultural University, Wuhan 430070, China.

Yuanhu Pan (Y)

National Reference Laboratory of Veterinary Drug Residues (HZAU), Huazhong Agricultural University, Wuhan 430070, China.

Jing Wang (J)

National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya 572024, China.
Institute of Quality Standard and Testing Technology for Agro, Products, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-Product Quality and Safety, Ministry of Agriculture Beijing, Beijing 100081, China.

Yulian Wang (Y)

National Reference Laboratory of Veterinary Drug Residues (HZAU), Huazhong Agricultural University, Wuhan 430070, China.

Classifications MeSH