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WGS as a starting point to understand AMR Jennifer Gardy, Canada Research Chair in Public Health Genomics, University of British Columbia & BC Centre for Disease Control @jennifergardy
with Laura Piddock, Professor of Microbiology, University of Birmingham @LauraPiddock
1995-20042005 2014
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There are over 70,000 prokaryotic genomes in NCBI
We sequenced 36 TB genomes!
We sequenced 1400 TB genomes!
Clinicians want to know what a bug is and what
to treat it with. Fast.
Is WGS faster than NAATs or LPAs for
diagnosis/speciation? Not really.
1. WGS will impact AMR diagnostics by offering new insights and new targets
PMC3989053
• 2007 S. aureus isolate, phenotypically MRSA but no mecA • WGS at Sanger revealed mecA homolog with 69% identity - named mecC • mecC detected all over the place after its discovery • Diagnostic PCRs and Vitek protocols changed to capture this new gene
2. WGS couples diagnosis and resistance prediction
PMC4703848 http://www.mykrobe.com
3. WGS identifies and queries a larger set of resistance determinants
Walker et al, Lancet ID, PMC4579482
3651 Mtb isolates sequenced, 232 resistance determinants found
PMID 15591164 (OA)
Sequenced 3 isolates after BDQ tx
4. WGS enables the discovery of new antimicrobial mechanisms of action
PMC4556809
PMC4587932
5. WGS reveals the drivers and
evolution of within-host and population-level
evolution of resistance.
DIAGN
OSIS
1. Sensitivity in sequencing from a clinical sample
2. Clinical metagenomics - who’s the pathogen, who’s a commensal, who’s a contaminant?
RESIS
TANC
E PRE
DICTIO
N 1. What’s a resistance-determining mutation versus a compensatory or other mutation?
2. What is the effect of rare variants on resistance phenotype?
3. What’s in the databases? Who is maintaining the databases?
4. How the @#$% are we supposed to identify resistance associated with different modes, levels of gene expression?
5. Are people releasing enough well-annotated genomes to enable comparative genomics efforts?
EPIDE
MIOL
OGY
1. How can we infer transmission from genomic data alone?
2. How can we infer transmission when it’s not just a strain but an MGE that’s moving?
3. Do we have enough spatial and temporal coverage of annotated genomes to make useful inferences about population dynamics?