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other·infectious disease, epidemiology, public health, research methods·PMC10282972

Challenges Associated with Investigating Salmonella Enteritidis with Low Genomic Diversity in New York State: The Impact of Adjusting Analytical Methods and Correlation with Epidemiological Data

Foodborne Pathogens and Disease · 8 authors, 2 centres

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TL;DR

This study examined a large, genetically similar cluster of Salmonella Enteritidis from human cases and found that lowering the genomic allele threshold for clustering, followed by more advanced genomic analysis, effectively subdivided the cluster into smaller, epidemiologically linked groups.

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A large cluster of 265 isolates was identified using an initial core genome multilocus sequence typing (cgMLST) threshold, which exhibited chaining and a broad allele range (0-14). To resolve this, researchers applied a stricter 0-allele cgMLST threshold, subdividing the large cluster into 34 smaller subclusters. Further analysis using whole genome multilocus sequence typing (wgMLST) and high-quality single-nucleotide polymorphism (hqSNP) analysis increased resolution. Limitations included incomplete epidemiological data for 31% of subclusters due to resource diversion during the COVID-19 pandemic.

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other

SPECIALTY

infectious disease

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AI pipeline

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ORIGINAL PAPER

PMC10282972

Challenges Associated with Investigating Salmonella Enteritidis with Low Genomic Diversity in New York State: The Impact of Adjusting Analytical Methods and Correlation with Epidemiological Data

Foodborne Pathogens and Disease

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ABSTRACT

Defining investigation-worthy genomic clusters among strains of Salmonella Enteritidis is challenging because of their highly clonal nature. We investigated a cluster identified by core genome multilocus sequence typing (cgMLST) consisting of 265 isolates with isolation dates spanning two and a half years. This cluster experienced chaining, growing to a range of 14 alleles. The volume of isolates and broad allele range of this cluster made it difficult to ascertain whether it represented a common-source outbreak. We explored laboratory-based methods to subdivide and refine this cluster. These methods included using cgMLST with a narrower allele range, whole genome multilocus sequence typing (wgMLST) and high-quality single-nucleotide polymorphism (hqSNP) analysis. At each analysis level, epidemiologists retroactively reviewed exposures, geography, and temporality for potential commonalities. Lowering the threshold to 0 alleles using cgMLST proved an effective method to refine this analysis, resulting in this large cluster being subdivided into 34 smaller clusters. Additional analysis by wgMLST and hqSNP provided enhanced cluster resolution, with the majority of clusters being further refined. These analysis methods combined with more stringent allele thresholds and layering of epidemiologic data proved useful in helping to subdivide this large cluster into actionable subclusters.

CITATION EXPORT

Deborah J. Baker, Amy Robbins, Jennifer Newman et al.. Challenges Associated with Investigating Salmonella Enteritidis with Low Genomic Diversity in New York State: The Impact of Adjusting Analytical Methods and Correlation with Epidemiological Data. Foodborne Pathogens and Disease. (2023). https://doi.org/10.1089/fpd.2022.0068

AUTHORS

8 · 2 CENTRES

Deborah J. Baker, Amy Robbins, Jennifer Newman, Madhu Anand, William J. Wolfgang, Damaris V. Mendez-Vallellanes, Samantha E. Wirth, Lisa A. Mingle

1New York State Department of Health, Wadsworth Center, Albany, New York, USA.
2New York State Department of Health, Bureau of Communicable Disease Control, Albany, New York, USA.