Multidrug-resistant bacteria - why bother typing them ? - Professor Neil Woodford Antimicrobial Resistance & Healthcare Associated Infections ...
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Multidrug-resistant bacteria - why bother typing them ?
Professor Neil Woodford
Antimicrobial Resistance & Healthcare
Associated Infections (AMRHAI) Reference Unit
© Crown copyrightInternational Consensus: AMR is a
Critical Public Health Threat
2 Oslo, 5th October 2014 © Crown CopyrightResistance threatens healthcare …every day
Colonized residents Hospital treatment or
or visitors travel overseas
Non-human
Inter-hospital
reservoirs: foodstuffs
transfers
(domestic or imported)
Non-human Victims from
reservoirs: animals conflict zones
and environment
• Multiple risks to be assessed to minimize damage
• Requires the detail to be understood
3 Oslo, 5th October 2014 © Crown CopyrightNational & international capacity building
• Without lab testing we’re blind to (the extent of) the problem
• Improve lab access; aim for a reference lab in every country
• Each serving as the hub of a national network
• Each acting as a spoke in an international network
• Performing essential techniques, proficient to international standards
• Sharing data / experience
4 Oslo, 5th October 2014 © Crown CopyrightAMRHAI’s Agenda
Setting England’s AMR and HCAI Problems into National and
Global Context
• Outbreak strains
• Resistance elements
• Population biology, ecology and biogeography
• Transmission pathways
• Reasons for success
• Better diagnostics, therapies and rational interventions
5 Oslo, 5th October 2014 © Crown CopyrightSurveillance of resistance
Informs on prevalence and changes in antibiotic resistance
– Guides empirical prescribing & control strategies
– Assess if control is working
Surveillance Shortfalls
– Lack of clinical denominators
– Need more community based surveillance
– Need to link antibiotic consumption to resistance
Underpinned by good microbiology (not just number crunching)
6 Oslo, 5th October 2014 © Crown Copyright3rd-gen cephalosporin resistance, EARS-Net, 2012
E. coli K. pneumoniae
• Requires AST data and species ID only
• No detail; no explanation
7 Oslo, 5th October 2014 © Crown CopyrightThe molecular microbiology of resistance
a) Resistance genes move between
plasmids +
b) The plasmids move between
strains, species and genera +
c) The bacteria move between
hosts and settings
Stokes & Gillings, FEMS Microbiol Rev, 2011
8 Oslo, 5th October 2014 © Crown CopyrightThe forensics of AMR
Genes
• Resistance involves
– emergence of mutations Gene carriers
– spread of resistance genes
– spread of resistant strains IS, In, Tn, plasmids
Host species
• Tracking and characterizing
– the resistant strains Strains, clones, phylogenetic
– their resistance genes groups, virulence traits, co-resistance
Patients
Hospital / community setting; risk factors
9 Oslo, 5th October 2014 © Crown CopyrightThe resistance ratchet keeps turning
Pathogen Established problems Emerging threats
E. faecium VRE, HLGR, Amp-R Lin-R, Dap-R, Tig-R
S. aureus MRSA (ha/ca) Van-R, Lin-R, Dap-R
Klebsiella ESBLs Carbapenemases, Col-R
Acinetobacter MDR, Carbapenemases Tig-R, Col-R
Pseudomonas MDR, except Col Carbapenemases, Col-R
Enterobacter AmpC, ESBLs Carba-R, Carbapenemases
E. coli Cip-R, ESBLs Carbapenemases
• 5 of 7 ESKAPEEs are Gram-negative
• The resistance issue for the next 5-10 years
10 Oslo, 5th October 2014 © Crown CopyrightThe molecular epidemiology of resistance
• The resistant isolates
– molecular methods define strains
– relevant to hospital epidemiology
– inter-patient or inter-hospital spread of strains
– identifying new strains with the same resistance
– on a national & global scale, the strains are highly
diverse
• Their resistance genes / elements
– horizontal transfer of transposons or plasmids
– fundamental units of resistance
– characterization needed for “the bigger picture”
– origins and evolution of resistance
11 Oslo, 5th October 2014 © Crown CopyrightPFGE analysis: a “gold standard” past its prime
≤3 band differences; same
4-6 band differences; related
>6 band differences; unrelated
• May gives too much discrimination
• Unsuitable for epidemiologically -
unrelated isolates
• Hides ancestral relationships
12 Oslo, 5th October 2014 © Crown CopyrightST131 dominates among ESBL-positive E. coli 13 Oslo, 5th October 2014 © Crown Copyright
The molecular epidemiology of resistance
• The resistant isolates
– molecular methods define strains
– relevant to hospital epidemiology
1. inter-patient or inter-hospital spread of strains
2. identifying new strains with the same resistance
3. on a national & global scale, the strains are highly
diverse
• Their resistance genes / elements
– horizontal transfer of transposons or plasmids
– fundamental units of resistance
– characterization needed for “the bigger picture”
– origins and evolution of resistance
14 Oslo, 5th October 2014 © Crown CopyrightCTX-M ESBLs are global
15 Oslo, 5th October 2014 © Crown Copyright
Hawkey and Jones. JAC 2009; 64 (Suppl. 1), i3-i10Travel destination influences risk and type of
resistance
16 Oslo, 5th October 2014 © Crown Copyright
Ostholm-Balkhed et al. JAC 2013; 68: 2144-53Neat packages of multi-resistance
Antibiotic
Genes Mechanism
classes
aac6’-Ib-cr
Aminoglycosides Modify drug
aadA5
blaCTX-M-15
β-lactams blaOXA-1 Destroy drug
blaTEM-1
Chloramphenicol catB4 Modify drug
Macrolides mph(A) Efflux
Fluoroquinolones aac6’-Ib-cr Modify drug
Sulfonamides sulI By-pass
Trimethoprim dhfrXVII By-pass
Tetracycline tet(A) Efflux
17 Oslo, 5th October 2014 © Crown Copyright
Woodford, Carattoli et al. AACKPC: Dominated by K. pneumoniae ST258 18 Oslo, 5th October 2014 © Crown Copyright Munoz-Price et al. Lancet Infect Dis 2013;13:785-96
A KPC cluster: spread of strains and plasmids
Isolate Patient Bacterial ID VNTR profile KPC Plasmid
n=6 A, B, C, K. pneumoniae
6, 4, 2, 0, -, 2, 2, 3, 1 pKpQIL-D2
D, E, H
3 C E. cloacae n.a. pKpQIL-D2
7 F Klebsiella oxytoca n.a. pKpQIL-D2
8 G Citrobacter freundii n.a. Not pKpQIL-like*
9 G K. pneumoniae 1, -, 4, 1, -, 1, 3, 5, 1 Not pKpQIL-like*
• Patients A, B, C, D, E & H – spread of the same K. pneumoniae strain
• Patients C and F – spread of pKpQIL plasmid into two other species
• Patient G – Separate introduction (distinct strains and plasmids)
19 Oslo, 5th October 2014 © Crown CopyrightWhole genome sequencing (WGS): a fuller
picture for the future ?
• Ideally analyse all outbreak isolates, but
realistically only a few
• Take one isolate per patient, analyse and
make a story...
• Degree of diversity within the patient ?
• In the host strain
• In the resistance plasmid
• Prepare for more complexity ...and a need
for new interpretive criteria
20 Oslo, 5th October 2014 © Crown Copyright
20The Challenge Many publications attesting to utility of NGS • Evolution, resistance prediction, investigating outbreaks etc Public Health England has invested in NGS Fully validated, accredited end-to-end service • Support clinical and public health interventions • Automated (where possible) Role in National Reference Service provision? 21 Oslo, 5th October 2014 © Crown Copyright
WGS for outbreaks: NIH KPC cluster • 18 cases of KPC+ K. pneumoniae • Colistin-resistance in isolates from patients 2 and 8. • Extensive overlap of patients within wards supported numerous transmission pathways. 22 Oslo, 5th October 2014 © Crown Copyright
WGS for outbreaks: NIH KPC cluster
• 18 cases of KPC+ K.
pneumoniae
• Colistin-resistance in isolates
from patients 2 and 8.
Not even WGS
• Extensive overlap of patients was definitive
within wards supported
numerous transmission
pathways.
• Mutational colistin resistance
emerged twice
23 Oslo, 5th October 2014 © Crown CopyrightResistance prediction • Need a catalogue of all resistance determinants – By species? • Need an algorithm for fast processing • Will need to achieve low levels of very major errors and major errors (i.e. high sensitivity and specificity respectively) • Will need to be validated to be equivalent or superior to routine susceptibility testing
Sensitivity and specificity of genotypic resistance predictions
versus gold standard “reference” phenotype results for 74
Escherichia coli bloodstream isolates
J. Antimicrob. Chemother. (2013)Goals for the future
• Better capture of patient-level meta-
data, linked with lab data
• Routine deployment of WGS for
typing and resistance analysis
• evaluate accuracy of resistance
/ susceptibility prediction
• discover novel mechanisms
Outbreaks • Robust (sensitive and specific)
contained rapid diagnostics
• New treatment options
Effective IPC
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