How to catch hantas and other  rainbos: aims and methods +  boreal PUUV ecology Heikki Henttonen

How to catch hantas and other rainbos: aims and methods + boreal PUUV ecology
Heikki Henttonen
Finnish Forest Research Institute
Rodent‐borne viruses: hanta, arena, cowpox RoBo viruses
Rodent‐ and insectivore‐borne viruses Rainbo viruses!!!
Thanks to Mike!
Methodology for monitoring
• What are your aims?
• Whar are your resources?
• What do you need to know (in minimum)? – Rough feeling of rodent species, density, seroprevalence, viruses present, or
– Detailed, longitudinal, frequent, individual‐based monitoring on transmission dynamics
• Do not copy your design from elsewhere, but optimize according to your aims, resources and local conditions
• In population studies, you can compromise almost in everything else but not in replicates (in a way or another)
Do not use laborous/expensive methods if it is not necessary
• ”Are there hantaviruses in UK”
– Catch quickly and efficiently many locations and big samples Æ snap trapping, freezing animals in field, lab work later using e.g. hearts in PBS. Material OK for blotting and PCR.
– Quick dissection in field, blood on paper strips or in PBS, tissues and rest frozen.
– And if you find something, then go there to collect fresh materials for cell cultures and other fine tuned operations, e.g. if fresh blood is needed Do not make it too difficult
Monitoring approaches
Special plague lab in E Kazakstan
• Go and hit safaris
• Regular, but only once, twice... a year
• Intensive longitudinal monitoring of transmission dynamics
• Methodology in field, from field to lab, and in lab.... • Scale ‐‐ methods
• What is the aim ‐‐
improvise, optimise
Somewhere in Siberia
We need long‐term monitoring
• Can be done in many ways depending on aims and resources
• BUT DO IT
• Even a simple monitoring once a year is much better than nothing.
• Only long‐term monitoring will tell what happens out there
• Important events can be rare
• You do not see what you are not looking for
Landscape structure in boreal zone Line trapping at each site
‐5 forest age classes
‐10 replicate sampling areas in each age class
‐ 6 small quadrats at each site
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Non-infected
Infected
40
20
0
clearcut
3 to 4
9 to 11
24 to 26
Years since clearcut
> 100
PUUV prevalence + 95%CI (%)
N of bank voles / 100 trap nights
200 km
km
200
Long term live trappings and experiments
Lake Pallasjärvi
Small quadrat snap trappings in spring and autumn
How to replicate? ‐ Study design in a Finnish study
“Core” area
• 5.8ha • ~250 trap stations
• Monthly live‐trapping for 7 years, CMR
• Onset of infection can be determined
H
P
N
G
F
"Satellite" areas • 14 sites, landscape level
• 0.2ha, 9 trap stations each • Sampled 3 times / year (May, July, October) • Animals removed
Minimum distance between
areas = 750 metres
O
E
M
C
B
D
K
A
I
Design problems – trapping frequency
• Delayed density dependence in PUUV ‐ bank vole systems in Europe
– time lag from rodent increase to virus spread
– suggestions: 6 mo, 3 mo, 1‐2 mo
– the solution:
– trapping intervals: 6 mo, 3 mo, 1‐2 mo
Design your work well to get good results!!
(or those you want), or
be aware of the limitations of your data
Seroprevalence or density...
• Depending on biome, PUUV seroprevalence can be seasonal, not density dependent, or vice versa….
• Considering risk for humans, the density of infectious animals is the important parameter and is often density dependent (delayed or direct), but remember limited shedding period Sampling strategies
• If the old breeding animals, esp. males, are commonly most infected, should the sampling (trap spacing) concentrate on catching these functional groups?
– yes if the target is new parasites/pathogens/biodiv
– no if the target is population level analyses etc • Seasonality and infection dynamics
– when is the right moment to catch
– how does the breeding occur? ‐‐> impact of host population sructure on the infection dynamics Rodent sample flow chart
1. Lung
2.Kidney
+ Spleen
3. Heart/
blood
1) Freeze in liquid nitrogen or
dry ice --> transport frozen to -70°C
-Piece in LSB
-Piece in TriPure/RNAlater
- virus isolation
- (retreiving antibodies)
2) Piece in RNAlater (or TriPure)
Detect/screen RNA/DNA
3) Piece in Laemmli Sample Buffer (LSB)
Screen antigen
by WB
Screen antibody
1) Heart with blood in separate tube
Snap -trapped animals: add 100 ul PBS
• IFA, EIA
- freeze/ store -20°C or -70°C
•microarrays
-or let clot/centrifuge--> serum
Soak in PBS to elute ab
Live animal Cardiac puncture/
saphenous/supraorbital vein)
2) Soak filter paper strip (e.g. 3M,
Whatman) in blood, let dry, can be
sent via mail (see next slide)
1) Soak a piece of filter paper (3M Whatman,
Tervakoski) in blood
Out in the field
2)
Let dry
3) Store the dried filter paper in e.g.
eppendorf tube or in a plastic bag (RT, +4°C or ‐20°C)
Back in the
laboratory
1) Take a piece (1x1cm) of the dried blood‐
containing filter and cut it further to smaller pieces
2) Soak the filter pieces in 1 ml PBS at a shaker for
appr. 2 hours
3) Transfer the diluted blood (now appr. 1:10) into a new tube
4) The sample is now ready for use in e.g. IFA
Finnish factory line (Vaheri et al. 2008)
Comparison of methods for screening for viral infections
in wildlife: A case study on Puumala virus and bank voles
H Henttonen, L Voutilainen, M Razzauti, A Plyusnina, ER
Kallio, J Laakkonen, J Niemimaa, T Mappes, E Koskela,
A Vaheri, O Vapalahti and A Plyusnin
Blood on paper strips
Tested
Positive
Prevalence %
(95% CI)
115
54
47.0 (38.1–56.0)
99
50
50.5 (40.8–60.2)
115
55
47.8 (38.9–56.9)
EIA (Ab)
97
48
49.5 (39.8–59.3)
WB (N-protein)
115
58
50.4 (41.4–59.4)
RT-PCR (RNA)
115
72
62.6 (53.5–70.9)
128
26
20.3 (14.2–28.2)
100
21
21.0 (14.1–30.1)
EIA (Ab)
93
17
18.3 (11.6–27.4)
WB (N-protein)
128
28
21.9 (15.5–29.8)
RT-PCR (RNA)
100
40
40.0 (30.9–49.8)
Method
May
IFAT whole
blood
IFAT dried
blood
IFAT heart +
PBS
October
IFAT whole
blood
IFAT dried
blood
Evaluated
method
May
Paper strip
IFAT
Heart + PBS
IFAT
EIA
Gold standard
Whole blood
IFAT
Whole blood
IFAT
Whole blood
IFAT
Whole blood
RT-PCR
IFAT
Immunoblottin
RT-PCR
g
October
Paper strip
IFAT
EIA
Whole blood
IFAT
Whole blood
IFAT
Whole blood
RT-PCR
IFAT
Immunoblottin
RT-PCR
g
No.
samples
compared
Positive predictive
valuea % (95% CI)
Negative predictive
valueb % (95% CI)
99
98.0 (94.1–100.0)
100.0 (100.0–100.0)
106
100.0 (100.0–100.0)
100.0 (100.0–100.0)
97
95.7 (90.0–100.0)
96.0 (90.6–100.0)
106
100.0 (100.0–100.0)
71.9 (60.3–83.6)
115
100.0 (100.0–100.0)
75.4 (64.3–86.6)
100
95.2 (86.1–100.0)
100.0 (100.0–100.0)
93
88.2 (72.9–100.0)
94.7 (89.7–99.8)
100
100.0 (100.0–100.0)
75.0 (65.5–84.5)
100
100.0 (100.0–100.0)
76.9 (67.6–86.3)
a number of true positives / (number of true positives + number of false positives). (sensitivity)
b number of true negatives / (number of true negatives + number of false negatives). (specificity)
Typical positive and negative human result in POC Puumala IgM rapid test
1. IgM‐positive serum
2. IgM‐negative serum
3. IgM‐positive fingertip blood
4. IgM‐negative fingertip blood
The test functions well if the sample has not been frozen
ReaScan system
ReaScan Reader
Reader open
Ready for use
Result
Cross reactivity
• Serotests tell that hanta is around, but because of cross reactivity, serotests do not tell the specific hanta strain. Several ag's can react in a serotest ‐‐> cross neutr., PCR/sequencing • In humans, antibodies in the acute phase of disease are not specific, only convalescence sera should be used for cross neutralization to identiy the specific strain. Contamination
• Contamination in PCR happens easily, especially if several strains are analysed in the same lab at the same time
Spill over (in robo world)
• Infection to secondary hosts (e.g. PUUV carried by My. glareolus to sympatric Mi. agrestis, M
arvalis, A. sylvaticus), or TULV from M arv. to M
agr., or SAAV/DOBV in Apodemus mice
• Can secondary host spread the virus?
– In sec. host, viremia very short and weak – Induction of antibodies, but no virus found
– Virus found but….
• Cross neutralization to analyse (if you have a good set of hanta antigens) ‐ quite demanding
• Seropositivity alone can be misleading!! The role of maternal antibodies in hanta dynamics?
(Arikawa et al. 1985, 1985, Zhang et al 1988, 1989, Kallio et al, 2006, 2010)
• Hantaviruses cause a chronic life‐time infection in rodents though neutralizing antibodies are present
• During lactation, the female transfers maternal antibodies to young
• We can detect the mat ab's until 2 months but the true protection is up to 3 (4?) months • But how well do we detect them? Age, avidity test…
• Seasonally, mat ab's can make a considerable proportion of seropositivity
• Transmission processes delayed
• Depending on spring density and prevalence, differences in autumn prevalenve between years and cycles?
Change in the paradigm: Insectivores march in!
(Almost) nothing is known on transmissibility of insectivore hantas humans
Sironen et al, in prep.
Biome specific epidemiologies
Mainly seasonal, but occassional mast driven peaks
Extended cyclic high density period
S and C Finland
30
Mast year
30
25
25
Density index
Density index
20
15
10
5
20
15
10
5
0
0
0
1
2
3
4
5
6
Year
Boreal north
7
8
9
0
1
2
3
4
5
Year
Temperate
6
7
8
9
Geography of rodent cycles and NE in Finland:
rodent surveillance as an early warning system
Spatial pattern of vole cycles
NE cases in whole Finland
Drastic change at the national level in late 1990s due to the change in the geographic synchrony of vole cycles
NE dynamics at local scale
How many infected bank voles in Nov 2008 in Finland?
• Bank vole peak area 100 000 km2
• Exclude lakes and fields Æ 70 000 km2 = 7 000 000 ha of forest.
• Conservative estimate 30 bank voles per ha = 210 000 000 bank voles
• Seroprevalence in November e.g. 40%
• Min 80 000 000 infectious bank voles peeing PUUV in forests of southern Finland Æ
• All time NE record!
Strange things happen in the Finnish night
landscape: 25 km2 study area
Northern pattern
homogenous lanscape, moisture, long winter, no strong dilution by other species
H
P
N
G
F
O
E
M
C
B
D
K
200
180
Maternal antibodies
Susceptible
Fresh infections
Chronic infections
PUUV prevalence
A
I
100
60
120
100
40
80
60
20
40
20
0
2002
0
2003
2004
2005
2006
2007
2008
2009
PUUV prevalence (%)
Number of bank voles
140
N o f P U U V -in fe c te d b a n k v o le s
80
160
60
50
40
30
20
10
0
2 02 3 03 4 04 5 05 6 06 7 07 8
y -0 o v- ay -0 o v- ay -0 o v- ay -0 o v- ay -0 o v- ay -0 o v- ay -0
a
M N M N M N M N M N M N M
Trapping session
Detailed longitudinal surveillance
Infected host in the landscape
P
O
N
M
K
I
H
G
F
E
D
C
B
A
Boreal zone: intensive transmission in nonbreeding subadult bank voles in winter
Maturation in spring
Most of the transmission in autumn and winter among nonbreeding voles. Æ
Season for human epidemiology
The importance of seasonal and cyclic heterogeneities for parasite parameters in rodent populations
• Populations are made of subgroups which differ in age, maturity, behaviour, immunity
• Their proportions change bothseasonally and multiannually
• "Functional groups"
– old breeding 1) males and 2) females
– young breeding 3) males and 4) females
– 5) subadults, not breeding, have dealyed the maturation to the next year
– 6) juveniles, by age
juveniles
< 4‐5 weeks
1. immediate maturation
2. delayed maturation
slow dispersal
subadults, nonbreeding, sexes similar
overwintering
intensive dispersal
dispersal with maturation
young breeding animals, sexes different
regression in winter/ dry season, "subadults"
maturation next spring
old breeding animals, sexes different
Seasonal development of functional groups in a rodent population
Behaviour and immunity are related to functional group, not to absolute age as such
Come on, get my virus!
Immunochromatographic rapid test Sample (5‐10 μl)
Buffer (2 drops)
Sample
pad
Conjugate
pad
Test line
Control line
Hantavirus nucleocapsidprotein (50 ng) in test line
Gold-conjugated rabbit anti-human-IgM antibody or
Gold-conjugated rabbit anti-mouse-IgG antibody
in conjugate pad
Goat anti-rabbit antibody in cntrol line
Hantavirus–specific IgM / IgG antibody in sample
Unspecific IgM / IgG in sample
Mammal species numbers in Europe
Higher diversity to south Æ more dilution impact
IUCN