Research

Resolve the epidemiology behind the genome.

Chromosomes, plasmids and phylogenies answer different questions. I combine them to distinguish clonal transmission from mobile resistance and keep uncertainty explicit.

01 · Transmission

Genomic surveillance

Sequence data can confirm a suspected outbreak, show that cases are unrelated, or reveal an environmental reservoir. My work links local nanopore sequencing with reference-laboratory context and clinical or infection-prevention interpretation.

<48 hinitial genomic result during a K. variicola neonatal-unit investigation

121 genomesprospective K. pneumoniae hospital surveillance

75 STsdiverse population; no patient-to-patient transmission detected

K. variicola neonatal outbreak · K. pneumoniae prospective surveillance · MRSA NICU investigation

02 · AMR

Mobile resistance

A resistance phenotype can spread with a bacterial clone, with a plasmid, or with a smaller mobile element. Chromosomal relatedness alone cannot distinguish those processes.

1,543mcr-bearing plasmids placed in global context

112 / 119plasmids circularised among nanopore-sequenced New Zealand mcr-positive isolates

14plasmid lineages resolved by pangenome clustering

mcr plasmid genomics · OXA-48 / ST131 · hospital plasmid reservoirs

03 · Evolution

Phylogenomics

Phylogenies become more informative when branch structure is connected to the mutations, mobile elements, geography and sampling history behind it.

397AK3 MRSA genomes

~20 yearsof lineage evolution reconstructed

ST131geographical structure resolved within a pandemic E. coli lineage

AK3 MRSA · E. coli ST131 · C. psittaci

04 · Methods

Reproducible inference

Matrix filtering, branch definition and ancestral-state reconstruction are small steps with large downstream consequences. I build focused tools when those steps need explicit validation, deterministic output and machine-readable provenance.

Research software and validation →