Evaluation of the Most Probable Number associated with Loop-mediated Isothermal Amplification (MPN - LAMP) techinique and Digital PCR for detecting and quantifying Salmonella in natural contaminated poultry samples

• Grant number: 23/01288-0
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: July 01, 2023
• End date: December 31, 2023
• Field of knowledge: Agronomical Sciences - Veterinary Medicine - Products of Animal Origin Inspection
• Principal Investigator: Fábio Sossai Possebon
• Grantee: Vitória Meneghetti Minatel
• Host Institution: Instituto de Biotecnologia (IBTEC). Universidade Estadual Paulista (UNESP). Campus de Botucatu. Botucatu , SP, Brazil

Abstract

Brazil plays an important role in the poultry sector, being the largest exporter of chicken meat in the world. Chicken farming is a highly significant economic and social activity in the country. In this scenario, institutions and industries seek to establish guidelines to control potential diseases transmitted by these products. Salmonella is a pathogen that causes high concern in all sectors of the poultry production chain, being important both in the zootechnical and sanitary aspect and as a major agent of foodborne diseases, causing numerous outbreaks and hospitalizations around the world. The prevalence of this microorganism varies between 36.3% and 86.7% in poultry products. In Brazil, from 2012 to 2021, there were 6,347 outbreaks of foodborne illness, resulting in more than 100,000 sick people and more than 10,000 hospitalized, many of them associated with the consumption of products from the poultry chain and caused by Salmonella. Currently, the isolation and quantification of this pathogen are performed by conventional microbiology techniques, which require a lot of resources, qualified labor, and a long time to obtain results. However, through isolation and quantification, it is possible to guarantee public health protection, identifying critical points and risk factors, determining the quality and safety of food. In view of this, the present project aims to quantify Salmonella in chicken samples by combining Most Probable Number and LAMP techniques, validating the results through absolute quantification by digital PCR.