Phylodynamic modelling of bacterial outbreaks using nanopore sequencing

Abstract

Nanopore sequencing and phylodynamic modelling have been used to reconstruct the transmission dynamics of viral epidemics, but their application to bacterial pathogens has remained challenging. Here, we implement Random Forest models for single nucleotide polymorphism (SNP) polishing to estimate divergence and effective reproduction numbers (Re) of two community-associated, methicillin-resistant Staphylococcus aureus (MRSA) outbreaks in remote Far North Queensland and Papua New Guinea (n = 159). Successive bar-coded panels of S. aureus isolates (2 x 12 per MinION) sequenced at low-coverage (> 5x - 10x) provided sufficient data to accurately infer assembly genotypes with high recall when compared with Illumina references. De novo SNP calling with Clair was followed by SNP polishing using intra- and inter-species models trained on Snippy reference calls. Models achieved sufficient resolution on ST93 outbreak sequence types (> 70 - 90% accuracy and precision) for phylodynamic modelling from lineage-wide hybrid alignments and birth-death skyline models in BEAST2. Our method reproduced phylogenetic topology, geographical source of the outbreaks, and indications of sustained transmission (Re > 1). We provide Nextflow pipelines that implement SNP polisher training, evaluation, and outbreak alignments, enabling reconstruction of within-lineage transmission dynamics for infection control of bacterial disease outbreaks using nanopore sequencing.