A core genome approach that enables prospective and dynamic monitoring of infectious outbreaks

Helen van Aggelen, Raivo Kolde, Hareesh Chamarthi, Joshua Loving, Yu Fan, John T. Fallon, Weihua Huang, Guiqing Wang, Mary M. Fortunato-Habib, Juan J. Carmona, Brian D. Gross

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Whole-genome sequencing is increasingly adopted in clinical settings to identify pathogen transmissions, though largely as a retrospective tool. Prospective monitoring, in which samples are continuously added and compared to previous samples, can generate more actionable information. To enable prospective pathogen comparison, genomic relatedness metrics based on single-nucleotide differences must be consistent across time, efficient to compute and reliable for a large variety of samples. The choice of genomic regions to compare, i.e., the core genome, is critical to obtain a good metric. We propose a novel core genome method that selects conserved sequences in the reference genome by comparing its k-mer content to that of publicly available genome assemblies. The conserved-sequence genome is sample set-independent, which enables prospective pathogen monitoring. Based on clinical data sets of 3436 S. aureus, 1362 K. pneumoniae and 348 E. faecium samples, ROC curves demonstrate that the conserved-sequence genome disambiguates same-patient samples better than a core genome consisting of conserved genes. The conserved-sequence genome confirms outbreak samples with high sensitivity: in a set of 2335 S. aureus samples, it correctly identifies 44 out of 44 known outbreak samples, whereas the conserved-gene method confirms 38 known outbreak samples.

Original languageEnglish
Article number7808
JournalScientific Reports
Issue number1
StatePublished - 1 Dec 2019
Externally publishedYes


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