Whole genome sequencing (WGS)
in clinical practice
Derrick Crook
Public Health England
Oxford University Hospitals FT Trust
University of Oxford
Are we ready to implement WGS?
• In one step it will provide:
- Species identification
- Resistance prediction
- Nearest genomic matches to identify and track outbreaks
Lancet Respir Med. 2016 Jan
Pilot study of an app for processing WGS
• 331 samples processed
• Data Transferred via the cloud to
Oxford
• Analysed and generated reports
recording:
1. Species
2. Resistance prediction
3. Nearest genomics match
(against 4000 WGS TB in
database)
Summary – Species ID
Concordant
M. tuberculosis complex
WGS only
Routine only
157
1
M. tuberculosis complex (BCG)
8
M. tuberculosis complex (africanum)
2
M. tuberculosis complex & M. avium complex
1
5
3
M. avium complex
71
1
1
M. abscessus complex
39
1
M. gordonae
18
M. xenopi
11
M. kansasii
6
M. malmoense
3
M. fortuitum
2
M. szulgae
2
M. celatum
1
M. lentiflavum
1
M. avium complex & M. malmoense
1
M. scrofulaceum
Failed to identify species
Total
1
1
1
9
10
2
331 (96%)
18 (5%)
10 (3%)
For MTBC: Sensitivity 95.4%
Specificity 98.1%
Based on single sequencing event (no repeating of tests)
Summary – Resistance prediction
A draft system – restricted by limited catalogue
Resistant DST
Sensitive DST
DST not attempted
DST failed
WGS
WGS
WGS
WGS
R
S
M
F
R
S
M
F
R
S
M
F
R
S
M
F
Isoniazid
13
2
1
0
0
143
0
7
0
0
0
0
0
1
0
1
First-line
Rifampicin
5
1
0
0
0
148
4
9
0
0
0
0
0
0
0
1
drugs
Ethambutol
5
1
0
0
1
153
0
7
0
0
0
0
0
0
0
1
Pyrazinamide
8
1
0
0
0
149
1
8
0
0
0
0
0
0
0
1
Streptomycin
5
1
0
0
0
14
0
0
2
138
0
8
0
0
0
0
line
Fluoroquinolones
3
1
0
0
0
6
0
0
2
148
0
8
0
0
0
0
drugs
Aminoglycosides
1
0
0
0
0
5
0
0
2
141
7
12
0
0
0
0
TOTAL
40
7
1
0
1
618
5
31
6
427
7
28
0
1
0
4
Second-
WGS resistance predictions for MTB isolates compared to phenotypic DST. R = Resistant, S =
Sensitive, M = Mixed (resistant and sensitive), F = failed WGS prediction
Report automatically generated from pipeline
Speed – Analysis & reporting
WGS faster
WGS slower
Cost
Process
Throughput
*
(2014)
Total per
sample in 2014
(GBP)
10% fewer
samples per
year (GBP)
10% more
samples per year
(GBP)
15265
52·39
52·90
51·97
WGS and routine
clinical workflows
MGIT culture
Cepheid Xpert MTB/RIF
617
99·66
102·35
97·44
WGS workflow only
Routine clinical
workflows only
WGS
2207
118·55
120·16
117·26
Identification assays
Hain MTBC
Hain CM/AS
2207
866
1341
55·05
55·28
54·87
MIRU-VNTR
866
107·75
110·89
105·18
First-line DST
866
135·47
137·12
134·13
Limited second-line DSTǂ
62
93·01
93·24
92·83
62
101·27
104·24
173·06
310·18
507·66
108·18
356·19
553·69
486·01
545.37
524·00
98·86
169·23
303·36
495·05
106·84
346·15
537·84
476·75
534.73
513·64
ǂǂ
Second-line DST
WGS workflow
scenarios
Routine clinical
workflow scenarios
Total workflow costs
MGIT culture + WGS
MGIT culture + WGS + first-line DST
MGIT culture + WGS + first-line DST + full second-line DST
Culture + identification assays
Culture + identification assays + MIRU-VNTR + first-line DST
Culture + identification assays + MIRU-VNTR + first-line DST + full second-line DST
WGS-based diagnostics
WGS-based diagnostics + first- and full second-line DST
Routine clinical workflow based diagnostics
170·94
306··41
500·68
107·44
350·66
544·93
480·91
539.53
518·31
Birmingham pilot – TB WGS lab workflow and parallel
evaluation
•
Study design includes:
•
Using prospective
samples for WGS
Real-time comparison
to current routine tests
•
Larger study
•
1,700 isolates (900-TB)
to be sequenced
•
Birmingham
sequenced 2,000
(850-TB) to date
•
Full analysis to follow
•
Aim to show
equivalence to current
routine tests
10
0.5 mL
for routine
+ve
Mycobacterial
culture
•
Data
input
TBWGS
db
Data
input
LabKey
Local
LIMS
Extract
DNA
1.7 mL
for WGS
Data
input
TBWGS
db
DNA
quantify
and
normalise
Library
prep
Data
input
TBWGS
db
Parameters checked at end of run:
Size data created (Gb)
Reads identified per sample (%)
Cluster density (k/mm 2)
Q-score (%)
Clusters passing filter (%)
Centralised
information
processing
DNA
quantify,
normalise
and pool
Run
samples
on
MiSeq
Data
input
TBWGS
db
Data
uploaded
to Base
Space
Prospects of rapid diagnostic WGS
Zamin Iqbal
and Mikrobe
Can sequence an isolate is 6 hours and possibly 1 hour
All results in one day within 2 years
Price? ($10/genome)
Rapid diagnostic for TB requires:
1.
2.
3.
4.
5.
6.
Direct from sputum
Portable, cheap, manufacturable.
Results within hours
Genotype->resistance
Integration with epidemiology
Data sharing
Rapid diagnostic for TB requires:
1.
2.
3.
4.
5.
Direct from sputum Achieved
Portable, cheap, manufacturable. ONT
Results within hours ONT
Genotype->resistance CRyPTIC + Mykrobe predictor
Integration with epidemiology and global data sharing Mykrobe
Atlas, ReSeqTB
Acknowledgements
•
Sarah Walker
•
Rosalind Harding
Oxford High Throughput Sequencing Hub team
•
Tim Peto
People participating in the studies
•
Mark Wilcox – Leeds
Informatics
•
Grace Smith – Birmingham
•
David Wyllie
•
Philip Monk - Leicester
•
John Finney
•
John Paul – Brighton
•
Milind Achyria
•
Martin Llewellyn – Brighton
•
Laura Madrid
•
Research Fellows (6)
•
Infections in Oxfordshire Research Database Team
•
Julian Parkhill
Bioinformatics and Population Biology
•
Amy Mathers - Uva, USA
•
Danny Wilson
Microbiology, DNA preparation
•
Carlos del Ojo Elias
•
Dai Griffiths
•
Saheer Gharbia
•
Kate Dingle
•
Tanya Golubchik
•
Nicole Stoesser
•
Anna Sheppard
•
Alison Vaughan
•
Dilrini de Silva
•
Bernadette Young
•
Xavier Didelot
•
Claire Gordon
•
Jess Hedge
•
Vasiliki Kostiou
International
•
Stefan Niemann Tom Rogers
•
Adam Geiss
•
Nazir Ismail
•
Tonya Votintseva
•
Jennifer Gardy
•
Luke Anson
•
Teresa Street
Philip Supply