Genomic Characterization Helps Dissecting an Outbreak of Listeriosis in Northern Italy

• Published in: PLoS currents 2017-07, Vol.9
• Main Authors: Comandatore, Francesco, Corbella, Marta, Andreoli, Giuseppina, Scaltriti, Erika, Aguzzi, Massimo, Gaiarsa, Stefano, Mariani, Bianca, Morganti, Marina, Bandi, Claudio, Fabbi, Massimo, Marone, Piero, Pongolini, Stefano, Sassera, Davide
• Format: Article
• Language: English
• ISSN: 2157-3999; 2157-3999
• DOI: 10.1371/currents.outbreaks.633fd8994e9f06f31b3494567c7e504c

Listeria monocytogenes (Lm) is a bacterium widely distributed in nature and able to contaminate food processing environments, including those of dairy products. Lm is a primary public health issue, due to the very low infectious dose and the ability to produce severe outcomes, in particular in elderly, newborns, pregnant women and immunocompromised patients. In the period between April and July 2015, an increased number of cases of listeriosis was observed in the area of Pavia, Northern Italy. An epidemiological investigation identified a cheesemaking small organic farm as the possible origin of the outbreak. In this work we present the results of the retrospective epidemiological study that we performed using molecular biology and genomic epidemiology methods. The strains sampled from patients and those from the target farm's cheese were analyzed using PFGE and whole genome sequencing (WGS) based methods. The performed WGS based analyses included: a) in-silico MLST typing; b) SNPs calling and genetic distance evaluation; c) determination of the resistance and virulence genes profiles; d) SNPs based phylogenetic reconstruction. Three of the patient strains and all the cheese strains resulted to belong to the same phylogenetic cluster, in Sequence Type 29. A further accurate SNPs analysis revealed that two of the three patient strains and all the cheese strains were highly similar (0.8 SNPs of average distance) and exhibited a higer distance from the third patient isolate (9.4 SNPs of average distance). Despite the global agreement among the results of the PFGE and WGS epidemiological studies, the latter approach agree with epidemiological data in indicating that one the patient strains could have originated from a different source. This result highlights that WGS methods can allow to better.