Genome characteristics of clinical Salmonella enterica population from a state public health laboratory, New Hampshire, USA, 2017-2020.

Background: The implementation of whole genome sequencing (WGS) by PulseNet, the molecular subtyping network for foodborne diseases, has transformed surveillance, outbreak detection, and public health laboratory practices in the United States. In 2017, the New Hampshire Public Health Laboratories, a member of PulseNet, commenced the use of WGS in tracking foodborne pathogens across the state. We present some of the initial results of New Hampshire's initiative to transition to WGS in tracking Salmonella enterica, a bacterial pathogen that is responsible for non-typhoidal foodborne infections and enteric fever. We characterize the population structure and evolutionary history of 394 genomes of isolates recovered from human clinical cases in New Hampshire from 2017 to 2020.

Results: The New Hampshire S. enterica population is phylogenetically diverse, consisting of 78 sequence types (ST) and 67 serotypes. Six lineages dominate the population: ST 11 serotype Enteritidis, ST 19 Typhimurium, ST 32 Infantis, ST 118 Newport, ST 22 Braenderup, and ST 26 Thompson. Each lineage is derived from long ancestral branches in the phylogeny, suggesting their extended presence in the region and recent clonal expansion. We detected 61 genes associated with resistance to 14 antimicrobial classes. Of these, unique genes of five antimicrobial classes (aminocoumarins, aminoglycosides, fluoroquinolones, nitroimidazoles, and peptides) were detected in all genomes. Rather than a single clone carrying multiple resistance genes expanding in the state, we found multiple lineages carrying different combinations of independently acquired resistance determinants. We estimate the time to the most recent common ancestor of the predominant lineage ST 11 serotype Enteritidis (126 genomes) to be 1965 (95% highest posterior density intervals: 1927-1982). Its population size expanded until 1978, followed by a population decline until 1990. This lineage has been expanding since then. Comparison with genomes from other states reveal lack of geographical clustering indicative of long-distance dissemination.

Conclusions: WGS studies of standing pathogen diversity provide critical insights into the population and evolutionary dynamics of lineages and antimicrobial resistance, which can be translated to effective public health action and decision-making. We highlight the need to strengthen efforts to implement WGS-based surveillance and genomic data analyses in state public health laboratories.