New Insights into Listeria monocytogenes Antimicrobial Resistance, Virulence Attributes and Their Prospective Correlation

Antibiotics (Basel). 2022 Oct 21;11(10):1447. doi: 10.3390/antibiotics11101447.

Abstract

Listeriosis is one of the most common foodborne diseases caused by Listeria monocytogenes (L. monocytogenes). A poor prognosis has been recorded for the invasive listeriosis, especially neurolisteriosis. In several countries throughout the world, foodborne infections with L. monocytogenes exceeded the legal safety limits in animal sourced foods. Therefore, we decided to investigate the variability, virulence and antimicrobial resistance profiles of this pathogen. Both phenotypic and genotypic methods were used for identifying L. monocytogenes isolates and confirming their virulence profiles. The antimicrobial resistances and their correlation analysis with the existence of virulence genes were detected. Additionally, sequencing and phylogenetic analysis based on L. monocytogenes inlA and inlB genes were undertaken. The prevalence rate (11.9%) and the resistance profiles of L. monocytogenes were shocking. The multi-drug resistance (MDR) phenotypes were common among our isolates (64.9%). Fortunately, the resistance phenotypes were always associated with low virulence arrays and the MDR strains possessed low virulence fitness. Herein, the high genotypic and phenotypic diversity of L. monocytogenes isolates and their weak clonality and adaptability highlighted the difficulty in controlling and managing this pathogen. Therefore, it is important to add more restriction guidelines from national authorities on the consumption of ready to eat foods.

Keywords: MDR; diversity; foodborne; listeriosis; virulence.

Grants and funding

This work was funded by Zagazig, Suez Canal and Port Said Universities and Princess Nourah Bint Abdulrahman University Researchers supporting project number (PNURSP2022R155) Princess Nourah Bint Abdurahman University, Rihadh, Saudi Arabia. The APC and molecular studies were funded by Taif University Researchers Supporting Project number (TURSP 2020/257).