Molecular Identification of Salmonella Strains Isolated from Livestock in Alborz Province and Their Serotyping

Abstract

Background and Aim: Salmonellosis is an important infectious zoonotic disease that makes it even more significant to identify and control the causative strains. Molecular methods, especially polymerase chain reaction (PCR), for virulence genes can help to quickly and accurately identify Salmonella strains. Accordingly, the purpose of this study was molecular identification based on sivH, hilA and sefA genes and serotyping of Salmonella strains isolated from livestock in Alborz province, Iran. Materials and Methods:The present study was conducted on 30 Salmonella strains isolated from livestock in Alborz province. Salmonella strains were isolated using morphological identification and differential and selective culture media. DNA was then extracted by boiling, and PCR was performed to detect the virulence genes of hilA, sivH, and sefA. The sensitivity and specificity of the primers used were determined using PCR. Results:The PCR findings showed that 27 (90%) isolates had the hilA gene, 10 (33.3%) isolates had the sefA gene, and 24 (80%) isolates had the sivH gene. Moreover, the highest frequency among serotypes was related to Salmonella typhimurium (10%). The sensitivity of ST11-ST15, hilA, sefA, and sivH primers were estimated at 0.0001, 1, 0.1, and 0.001 ng/mol, respectively. The specificity of primers for Salmonella strains was also confirmed. Conclusion:Identifying livestock with salmonellosis and isolating pathogenic strains from other livestock are of the most important methods capable of reducing the prevalence of foodborne infection in consumers. This can be achieved by the PCR technique for virulence genes, especially hilA, which is more prevalent among Salmonella strains.

Molecular Identification and Characterization of Salmonella Sp. In Raw and Heat-Treated Milks from Local Market

“…The important conventional techniques used for detection of microbes in milk are generally laboratorybased, consumed time, and labor intensive (Dawood Saleem et al, 2022;Moghadam et al, 2022) (Hameed et al, 2018).…”