Tracking the emergence and global spread of foot-and-mouth disease (FMD)
A Symposium to Mark the 50th Anniversary of the Designation of the Pirbright Laboratory of the Institute for Animal Health as FAO World Reference Laboratory for FMD
9:00-9:10 Wellcome Prof Martin Shirley, IAH Director9:10-9:30 WRLFMD overview Dr David Paton, Head of WRL9:30-10:00 Global diversity of FMDV Mr Nick Knowles, IAH
10:00-10:30 Coffee
10:30-11:00 FMD in Africa Dr Wilna Vosloo, Ondestepoort11:00-11:30 FMD viral evolution Dr Esteban Domingo, Madrid11:30-12:00 Tracing FMDV in UK outbreaks Dr Eleanor Cottam, IAH12:00-12:30 FMD virus structure Prof Dave Stuart, Oxford
12:30-13:30 Lunch
13:30-14:00 Antigenic cartography Dr Derek Smith, Cambridge14:00-14:30 Cross-protection between FMD strains Dr Bernd Haas, Riems14:30-15:00 Virus detection methods Dr Donald King, IAH
15:00-15:30 Tea
15:30-16:00 FMD virus transmission dynamics Prof Mark Woolhouse, Edinburgh16:00-16:20 European collaboration on FMD Dr Kris de Clercq, Brussels16:20-16:40 Future prospects for FMD control Dr Keith Sumption, Rome
17:00 Close
Tracing FMDV in UK outbreaks
The rationale behind using complete genome sequencing of Foot-and-Mouth Disease Virus as an epidemiological modelling tool
9 May 2008
• Rapid replication rate
• Large population sizes
• High error rate of viral polymerase in the order of 10-3 to 10-5 misincorporations per nucleotide copied
FMDV evolution
Fast adaptation and evolution
UK 2001 Outbreak
• 2030 infected premises culled
• 8131 culled as dangerous contacts
• > 6.5 million animals culled
• economic cost exceeding £6 billion
• Pan Asia O serotype• Identified 20th Feb 2001 in
Cheale’s abattoir Essex• Source farm identified as Heddon-
on-the-Wall.• Airborne spread to nearby sheep
farm.• Movement of sheep through
markets one week before disease identified
• Subsequent outbreaks throughout the UK
UK 2001 Outbreak
• The transmission of FMDV is poorly characterised, and information on the direction of farm to farm spread would greatly enhance our understanding and hence control.
• Broad scale genetic tracing of FMDV using VP1 sequences (633nt) between countries
• Attempt in Denmark at intra-epidemic tracing of FMDV using VP1 sequences only*
• Forensic genetic tracing for HIV, Hep C, SARS, Rhinovirus, Norovirus…….
*Christensen, L.S., P. Normann, S. Thykier-Nielsen, J. H. Sorensen, K. de Stricker, and S. Rosenorn. 2005. Analysis of the epidemiological dynamics during the 1982-1983 epidemic of foot-and-mouth disease in Denmark based on molecular high-resolution strain identification. J. Gen. Virol. 86: 2577-2584
Previous work
• Development of method for sequencing complete genome
• Investigation of FMDV evolution during the UK 2001 Outbreak
• Use of complete genome sequence data for forensic genetics of FMDV transmission
Project Introduction
• Direct from epithelium
• RT-PCR– 5 overlapping fragments– 84 sequencing reactions
• Use of QIAGEN robot
• Complete sequence within 3 days
Complete genome sequencing
Cottam et al. 2006 J Virol 80(22), 11274-82
C 7038-2001 FAS
C2 7039-2001 FAS
O 5681-2001
M 9443-2001
D 9161A FAS
D 9161B
B 4141-2001
E 7299-2001 FAS
L 4998-2001
K 4014-2001
F 7675-2001 FAS
G 9327-2001 FAS
I 9788-2001 FAS
J 9964-2001 FAS
Darlington Cluster
9011-2001 FAC
14476-2001 FASWest Yorkshire
Cumbria14391-2001 FAS
14603-2001 FAS
15101-2001 FAS
14524-2001 FAS
Northumberland
Powys14339-2001 FAS
Staffordshire621-2001 FAS
Northampton220-2001 FAS
Northumberland4569-2001 FAS
Devon173-2001 FAS
Ireland438-2001 FAS
Devon11676-2001 FAS
A 3952-2001 FAS
N 5470-2001 Darlington 2Cheales Abbattoir11-2201 FAS
Ponteland150-2001 FAS
126-2001 FAS
127-2001 FAS
128-2001 FASHeddon on the Wall
100
100
100
92
99
91
99
99
99
98
92
66
89
72
86
64
83
87
87
61 Genetic relationship of34 virus sequences
Maximum likelihood phylogenetic tree10,000 Bootstrap
• 52 nucleotide substitutions between source and final case– 8 were amino acid changes
• 83 variant nucleotides between Wales and Northumberland
Observed Variation
Cottam et al 2006 J Virol 80(22), 11274-82
Molecular clock
Nucleotide changes accrue linearly with time and are inherited
2.26 x 10-5 / site / day
0
10
20
30
40
50
60
0 50 100 150 200 250Day of Outbreak
Nuc
leot
ide
subs
titut
ions
from
inde
x ca
se x
Cottam et al 2006 J Virol 80(22), 11274-82
7088
7109
8091
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7088
7109
4382
5277
8107
3428
4808
Farm 426/02/01
7088
7109
4382
5277
8107
3428
4808
4553
4982
5303
Farm 501/03/01
Farm 324/02/01
7088
7109
4382
5277
8107
2420
25/02/01 28/02/0127/02/01
7088
Farm 122/02/01
time
Known chain of events
4 5
2
3
1
1
Cottam et al 2006 J Virol 80(22), 11274-82
0 9 184.5 Kilometers
Pos + sequenced
Pos not sequenced
Negative
No samples submitted for diagnosis
A
N
O
F
GI
P
ECB
L
DM
J
K
Durham cluster of Infected Premises
Cottam et al. 2008 Proc Biol Sci. 22;275(1637):887-95.
45
2
3
C1
C2
D
F
G
I
JE
B
A1b1a
k
L
M
N
O
P
Difficult to determine transmission tree –839808 different trees consistent with genetic data
Statistical parsimony analysis of sequence data from IPs by TCS
Cottam et al. 2008 Proc Biol Sci. 22;275(1637):887-95.
0 10 20 30 40 50 60 70 80 90 100 110
Day of outbreak
A
B
C
D
M
E
N
G I J
F
K
L
1
2
3
54 O
P
• Restricted by date of cull
• Individual farm infection profiles?
• Statistical weighting for transmission tree – how confident are we?
Cottam et al. 2008 Proc Biol Sci. 22;275(1637):887-95.
Start of outbreak
*Most likely infection date
(mode)
2 dIi(t) probability that i th farm was infected at time t (discrete beta-distribution)
Day of cull
*date of confirmation minus oldest lesion minus 5d incubation
∑ ∑=
−
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iC
j
jt
kii kLjItF
0 1)()()(
Probability that the ith farm is a source of infection at time t :
5d
L(k) probability of incubation for K days prior to becoming infectious, gamma-distribution, 95% probability between 2 and 12 days
2d 12d
Cottam et al. 2008 Proc Biol Sci. 22;275(1637):887-95.
Start of outbreak
*Most likely infection date
(mode)
2 dIi(t) probability that ith farm infected at time t (discrete beta-distribution)
Fi(t) probability that the ith farm is a source of infection at time t
Day of cull
AB
C
D
E
F
KLNO
GMIJ
AB
C
D
E
F
KLNO
GMIJ
TIME
Likelihood of infection
Likelihood of being infectious
Infection profiles of farms
Cottam et al. 2008 Proc Biol Sci. 22;275(1637):887-95.
∑∑∑≠= ==
⋅⋅=n
ikk
k
C
tij
C
tiij tFtItFtI
kj
1 00)()()()(l
Likelihood that farm i infected farm j :
From these infection profiles we can calculate a likelihood for each hypothesised transmission event
It is now possible to determine the transmission tree with the highest likelihood from all the trees consistent with the genetic data
Cottam et al. 2008 Proc Biol Sci. 22;275(1637):887-95.
Num
ber o
f con
secu
tive
farm
infe
ctio
ns
0
1
2
3
4
5
1 2 3 4 5 6 7 8 9 10
Number of variant nucleotides between consecutive farm infections
Mean 4.2 (SD 2.1) nucleotide changes per transmssion event
Thus if the number of changes seen is outside this distribution, a missing intermediate farm would be suspected
Distribution of the number of changes that occur upon transmission of virus between farms (n=16)
Cottam et al. 2008 Proc Biol Sci. 22;275(1637):887-95.
0 10 20 30 40 50 60 70 80 90 100 110
Day of outbreak
A
B
C
D
M
E
N
G I J
F
K
L1
2
3
54 O
P (IP1515)
IP14
Rate of nucleotide change seems to vary…….
2.26 x 10-5 / site / day
0
10
20
30
40
50
60
0 50 100 150 200 250
Day of Outbreak
Nuc
leot
ide
subs
titut
ions
from
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se x
• Previously linked mutation rate with time
• Was the rate of genetic evolution of FMDV in the epidemic due in part to the rate of transmission and spread of the virus?
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Genetic evolution of FMDV
2007 UK FMDV Outbreaks
IAH2
IAH1
AY593815
IP2b
IP2c
IP1b(1)
IP1b(2)MAH
Synonymous substitution
Non-synonymous substitution
Non-synonymous substitution important in cell culture adaptation
August
Cottam et al. 2008 PLoS Pathogens 4(4): e1000050
IAH2
IAH1
AY593815
IP2b
IP2c
IP3bIP1b(1)
IP1b(2)MAH
SeptemberAugust
Cottam et al. 2008 PLoS Pathogens 4(4): e1000050
9 substitutions
Date
IP2b
IP2c
IP3b
IP1b(2)
IP1b(1)
29-J
ul-0
7
19-A
ug-0
7
12-A
ug-0
7
05-A
ug-0
7
26-A
ug-0
7
02-S
ep-0
7
09-S
ep-0
7
16-S
ep-0
7
23-S
ep-0
7
22-J
ul-0
7
15-J
ul-0
7
Lesionspresent
Infection window
IAH2
IAH1
AY593815
IP2bIP2c
IP3c
IP4b
IP3b
IP5
IP6b
IP1b(1)
IP1b(2)
IP7
MAHIP8
29-J
ul-0
7
19-A
ug-0
7
12-A
ug-0
7
05-A
ug-0
7
26-A
ug-0
7
02-S
ep-0
7
09-S
ep-0
7
16-S
ep-0
7
23-S
ep-0
7
Date
IP2b
IP2c
IP3c
IP4b
IP3b
IP5
IP1b(2)IP1b(1)
IP6b
IP7
22-J
ul-0
7
15-J
ul-0
7
30-S
ep-0
7
IP8
Cottam et al. 2008 PLoS Pathogens 4(4): e1000050
Summary• Complete genome sequencing data can assist in
our understanding of the spread of FMDV
• Combining genetic and epidemiological data gives greater resolution.
• More research is needed to help refine the use of these data in real time.
Don KingDavid PatonNick KnowlesNigel FerrisGeoff HutchingsAndrew ShawJemma WadsworthJohn Gloster
Thank you
Dan HaydonGael Thébaud
John Wilesmith
Sam Mansley