Assessing mutation accumulation in DNA repair-deficient Listeria monocytogenes: implications for cgMLST cluster thresholds in outbreak analysis.

Abstract

Background: Listeria (L.) monocytogenes is primarily transmitted via contaminated food and can cause listeriosis, an infection often associated with sepsis and meningitis in at-risk individuals. Accurate outbreak detection relies on whole genome sequencing (WGS) and core genome multilocus sequence typing (cgMLST), which use allele thresholds to identify related strains.

Methods: This study investigated mutation rates in L. monocytogenes, focusing on isolates with DNA repair deficiencies. Serial subcultivations were performed, comparing a repair-deficient isolate with a wild-type control. Genetic variability was assessed using WGS and cgMLST.

Results: Mutation rates were significantly higher in repair-deficient isolates, exceeding typical cgMLST thresholds currently used in Listeria outbreak investigations, leading to a misclassification of related isolates as unrelated. An additional analysis of the Austrian Listeria database revealed that such deficiencies are rare among isolates.

Conclusions: The standard 7-allele cgMLST threshold effectively identifies related strains in most cases, but may require adjustments for hypermutator strains. Incorporating DNA repair data could improve the accuracy of outbreak investigations, ensuring reliable public health responses.