Evolutionary Relationships of Outbreak-associated Listeria monocytogenes Strains of Serotypes 1/2a and 1/2b Determined by Whole Genome Sequencing.

Bergholz TM1, den Bakker HC2, Katz LS3, Silk BJ3, Jackson KA3, Kucerova Z3, Joseph LA3, Turnsek M3, Gladney LM3, Halpin JL3, Xavier K4, Gossack J4,Ward TJ5, Frace M3, Tarr CL6.

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Abstract

We used whole genome sequencing to determine evolutionary relationships among 20 outbreak-associated clinical isolates of Listeria monocytogenes serotypes 1/2a and 1/2b. Isolates from six of eleven outbreaks fell outside of the clonal groups or 'epidemic clones' that have been previously associated with outbreaks, suggesting that epidemic potential may be widespread in L. monocytogenes and is not limited to the recognized epidemic clones. Pairwise comparisons between epidemiologically-related isolates within clonal complexes showed that genome-level variation differed by two orders of magnitude between different comparisons, and the distribution of point mutations (core versus accessory genome) also varied. In addition, genetic divergence between one closely related pair of isolates from a single outbreak was driven primarily by changes in phage regions. The evolutionary analysis showed the changes could be attributed to horizontal gene transfer; members of the diverse bacterial community found in the production facility could have served as the source of novel genetic material at some point in the production chain. The results raise the question of how to best utilize information contained within the accessory genome in outbreak investigations. The full magnitude and complexity of genetic changes revealed by genome sequencing could not be discerned from traditional subtyping methods and the results demonstrate the challenges of interpreting genetic variation among isolates recovered from a single outbreak. Epidemiological information remains critical for proper interpretation of nucleotide and structural diversity among isolates recovered during outbreaks, and will remain so until we understand more about how various population histories influence genetic variation.