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Table_2_Microevolution and Gain or Loss of Mobile Genetic Elements of Outbreak-Related Listeria monocytogenes in Food Processing Environments Identifi.XLSX (85.95 kB)

Table_2_Microevolution and Gain or Loss of Mobile Genetic Elements of Outbreak-Related Listeria monocytogenes in Food Processing Environments Identified by Whole Genome Sequencing Analysis.XLSX

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posted on 2020-05-29, 04:05 authored by Helen Yang, Maria Hoffmann, Marc W. Allard, Eric W. Brown, Yi Chen

Whole genome sequencing (WGS) analyses have been instrumental in traceback investigations of Listeria monocytogenes (Lm). To demonstrate how long-read sequencing analysis can capture and describe relationships among isolates from clinical, food, and environmental sources, we analyzed 366 long-read- and shotgun-sequenced isolates from 16 Lm outbreak strains associated with cantaloupe, leafy green, stone fruit, caramel apple, mung bean sprout, multiple cheese products, multiple ice cream products, and their production environments. The analyses demonstrated that outbreak strains could be distributed in different areas and zones of food production environments through persistent or repeated contamination. Multi-strain and multi-clone contamination were common. Further, WGS could differentiate among isolates collected at different time points or from different production lines in the same facility, revealing microevolution events in processing environments. Our comparison between complete and shotgun genomes showed that isolates of the same outbreak strain diversified mostly by gain/loss of plasmids and chromosome-borne prophages that constitute 2 to 5% of the chromosome. In contrast, other genes missing in the shotgun genomes were randomly scattered, constituting ~0.5% of the chromosome. Among different outbreak strains of the same CC, most gene-scale differences were due to gain/loss of mobile genetic elements, such as plasmids, chromosome-borne prophages, a Tn916 like transposon, and Listeria Genomic Island 2. The nucleotide variations in the same prophage and the same plasmid shared among isolates of the same outbreak strain were limited, which enabled different WGS tools to unambiguously cluster isolates of the same outbreak strain. In some outbreak strains, correlation between prophage gain/loss and single nucleotide polymorphism (SNP) accumulations in the genome backbone were observed.

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