Reputation at Risk: How Animal Welfare, Antimicrobial Resistance and Social Responsibility Are Shaping Consumer Perceptiono MARIE MOLDE, DATASSENTIAL
ARLIN WASSERMAN, CHANGING TASTES
o ELIZABETH WELLINGTON, UNIVERSITY OF WARWICK
o CONSTANZA ALVIAL, PRO BONO NETWORK
ElizabethWellingtonLiz is a professor at the University of Warwick’s School of Life
Sciences. She is involved in the study of bacteria in soil and
survival of pathogenic bacteria in the environment. Her
expertise is in the detection, quantification and analysis of
soil microbial communities, including the identification of
pathogen reservoirs outside of their hosts. She earned her
Ph.D. from the University of Liverpool.
PROFESSOR UNIVERSITY OFWARWICK
Antimicrobial resistance and aquacultureElizabeth Wellington
University of Warwick, UKProfessor E M H Wellington
School of Life SciencesThe University of Warwick
Coventry CV4 7ALUnited Kingdom
Tel: 00442476 523184Fax: 00442476 523701
Email: [email protected] http://www2.warwick.ac.uk/fac/sci/lifesci/people/ewellington/
http://www2.warwick.ac.uk/fac/cross_fac/wesic/people/
WHO2017
AMR is a global issue
One health perspective
Harbarth et al., 2015 AMR & InfectControl
• Aquaculture systems are complex and dynamic, with many factors driving the (mis)use of antibiotics
• ABU in aquaculture is different to that in humans and livestock, since it is administered directly in to the aquatic environment usually through medicated feed
• Antibiotics and feed are often supplied separately in aquaculture. Thismeans that farmers have to mix the antibiotics with the feed, resultingin a high risk of occupational exposure
• Fish do not metabolise antibiotics effectively, and it has been estimated that 75% of the antibiotics fed to fish will be excreted back in their active form in to the aquatic environment through faeces
• Aquaculture systems are often linked to the natural waterenvironment,facilitating contamination of the environment and waterways, and havingthe potential to lead to the emergence and dissemination of ABR furtherthan terrestrial livestock systems
Characteristics of antibiotic use (ABU) in aquaculture
Henriksson etal., 2017 Sustain Sci.
Growth of food animal production > thirty years from 1980 and aquaculture sector in 2014
Antibiotic use in Atlantic salmon farming- major producersSignificantly higher frequencies of AMR genes in urinary
Escherichia coli isolates from Chileans living in aquaculture regions compared to isolates from non-aquaculture localities,
suggesting thatAM use in the Chilean salmon industry may be contributing to increased risks of AMR genes in humans
(Tomova et al. 2015 )
Tomova et al. 2015
Marathe et al. J. Biosci. 41(3), September 2016, 341–346 Indian Academy of Sciences 341
Elevated AMR in bacteria from farmed fish
ARG biomarkers farming
Pearl river delta, South ChinaHuang et al., Chemosphere 2018
Rivers and lakes in Pune,India
Report for Defra UK Gov
James et al., 2018 draft report commissioned by Defra UKGov
-DNA was purified from triplicate samples and qPCR was used to determine resistance loads at each site.-16s rDNA amplicon sequencing on all sites-Metagenomes on 20 core sites
Thames Investigation
Routinely monitored by CEH Extra sites chosen for study
Gene Target Resistance to/Marker16S rDNAIntI1 QacE TetM RuBac HuBacQnrS ErmFCTX-M (Group 1)E. coli
bacterial marker class 1 integronquaternary ammonium compounds TetracyclineRuminant assoc. BacteroidesHuman assoc. Bacteroidesfluoroquinolones erythromycin (macrolide)CTX-M-1 and 15 (beta lactams) faecal contamination
Enterococci faecal contamination
-69 sites located along the Thames catchment were chosen forsampling.-Sampling begins at the source of each tributary and continues along the tributary where potential sources of AMR (eg. WWTPs and fish farms) are located.
qPCRTargets
Location of fish farms and wastewater treatment plants
Sampling Planktonic and Benthic Phases
100%90%80%70%60%50%40%30%20%10%
0%water
Abun
danc
e
sediment
Sample type
(a)Verrucomicrobia
Unassigned;Other
TM7
Spirochaetes
Proteobacteria
Planctomycetes
OD1
Nitrospirae
Gemmatimonadetes
Firmicutes
Cyanobacteria
Chloroflexi
Chlorobi
Bacteroidetes
Actinobacteria
Acidobacteria
Gemma Hill
Red=sediment; blue= water
Verrucomicrobia
Unassigned;Other
TM7
Spirochaetes
Proteobacteria
Planctomycetes
OD1
Nitrospirae
Gemmatimonadetes
Firmicutes
Cyanobacteria
Chloroflexi
Chlorobi
Bacteroidetes
Actinobacteria
Acidobacteria
-Planktonic and benthic phases differed significantly in phyla abundance.-Benthic phases displayed higher bacterial diversity compared to planktonic phase
Benthic phase contains higher bacterial loads
1
10
100
1000
0000
00000
00000
00000
00
three five seven eight two seven eight eleven
kennet
Gen
e co
pies
per
gra
m w
etw
eigt
(a)
qnrS ermF tetM E_coli inti1 qacE ctx-m
102
10
1
1000000
100
10
1
1
10
104
3
105
qnrS
108
107
106
thame
ermF tetM E.coli intI1 blactx-m-1qacE
1
10
100
1000
10000
three five seven eight two seven eight eleven
kennet
Gen
e co
pies
per
ml
qnrS ermF
tetM E_coli inti1 qacE ctx-m
1
intI1 blactx-m-1qacE
thame
qnrS ermF tetM E.coli
102
10
1
103
104
Gemma Hill
BenthicTotal bacterial load: 10^8cells/gram
PlanktonicTotal bacterial load: 10^4cells/ml
Benthic phase constitutes a greater reservoir for ARGs than planktonic phase
Approach
1400
1200
1000
800
600
400
200
0
Cher
wel
lC
ole
1co
le2
Co
le4
Co
ln1
COLN
3CO
LN4
COLN
5 cut2
Cu
t3 c
ut4
cu
t6
Enbo
rne
Ev
enlo
deKe
nnet
10
Kenn
et11
Ke
nnet
12
Kenn
et13
c
Kenn
et14
Ke
nnet
2a
Kenn
et2
Ke
nnet
3d
Kenn
et4a
Ke
nnet
4a
Kenn
et6
Ke
nnet
7a
Kenn
et8
Ke
nnet
9
Lam
1 L
am3
Lam
4 L
am5
Le
ach2
Lo
ddon
O
CK
TC
11
Ray_
TC2
Ray1
Ra
y2 R
ay4
Ra
y5 R
ay6
Ra
y8ke
y2
Ray9
key3
RTha
mes
1
RTha
mes
3
RTha
mes
4
RTha
mes
5
RTha
mes
6
Tham
e1b
Th
ame2
Th
ames
3
Tham
e3b
Th
ame4
a
Tham
e5b
Th
ame5
d
Tham
e6c
Th
ame7
c
Tham
e8c
Wye
Organic PollutantAnalytes
River CutRiverRay
RiverThame
Summary of abundance of organic pollutant analytes Three seasons
tetM Summer
CTX-M-1 Summer
Prevalence of CTX-M-1 (Group1) / tetM
ch
cole
coln cut
enb
evnld
key
knt
lam
leach
lodden ock
pang ray
ray_tc2
rtham
es
tham
e
wye
−5
−4
−3
−2
−1
LogPrevalence
CTX−M−1 S16
●
●
●
●
●● ●
● ●
●
●
●
51.4
51.5
51.6
51.7
51.8
51.9
−1.6 −0.8−1.2longitude
latitu
de
2.5
0.0
−2.5
−5.0
map1[, i]
ecoli_log
●
●
●
●
●●
●
● ●
●
●
51.4
51.5
51.6
51.7
51.8
51.9
−1.6 −0.8−1.2longitude
latitu
de
5.0
2.5
0.0
−2.5
−5.0
map1[, i]
ecoli_log
●● ●●
●●
●● ●● ● ●● ●
● ●
●
●
●
●
●
51.4
51.5
51.6
51.7
51.8
51.9
−1.6 −0.8−1.2longitude
latitu
de
−6
−3
0
3
map1[, i]
ecoli_log
K1 ●●
K3K2 K4
K6
K5 K7
Lam1● Lam2
●Lam3/4
●Lam5
● K14 K15Enb
Pang
RT4
Leach1●
● ●Cole3●
Cole1
Cole2
RT2
Ock ●
Evnld●
●
RT3
Cherwell●
●
RayTC2
Thame6●
Thame8
Thame1●
Thame2Thame3●
●
Thame4/5
Wye●
RT6●
Cut6●
Cut5●
Lodden● ●
● RT5
● Cn4●Cn5 ● Leach2
Cn3●
Cn1●
● Cn2
Ray2Ray1 ● ●Ray4
●●Ray3
Key1 Ray6 RT1Key2 ●●Key3 Ray5
Cut2Cut3 Cut1
Cut4K8
K9 ●●● K11
K10 K12
K3K2 K4 ● ●
K1 ●●●●K6K5 K7
Lam1● Lam2
●Lam3/4
●
Lam5●
● K14K15
●
● Enb
Pang
RT4
Leach1●
● Cole3●
Cole1
Cole2
RT2 ●
Ock ●
Evnld●
●
RT3
Cherwell●
●
RayTC2
Thame6●
Thame8
Thame1●
●Thame2Thame3
●
●
Thame4/5
Wye●
RT6●
Cut6Cut5 ●
●
Lodden●RT5 ●
● Cn4● Cn5 ● Leach2
Cn3● Cn2
Cn1
Ray2Ray1 ● ● Ray4
●● Ray3
●
Key1 Ray6 RT1Key2 ●
Key3 ● Ray5
Cut2Cut3 ●● ●Cut1
Cut4K8
K9 ● ●●
● K11
K10 K12
K3K1 ●●●●K6
K2 K4 K5 K7
Lam1● Lam2
●Lam3/4
●
Lam5●
● K14K15●
● Enb
Pang
●RT4
● ●Cole3
RT2
Ock ●
Evnld●
●
RT3
Cherwell●
●
RayTC2
Thame6●
Thame8
Thame1●
●Thame2Thame3
●
●
Thame4/5
Wye●
RT6●
Cut6●
Cut5Lodden● ●
● RT5
● Cn2 Leach1●
Cn3●
● Cn4● Cn5 ● Leach2
Cn1
●●Ray3 Cole1Ray2
Ray1 ● ●Ray4
Key1 Ray6 RT1Key2 ● Cole2Key3 ● Ray5
Cut3 ●● ●Cut1 Cut2
Cut4K8
K9 ● ●●
● K11●
K10 K12
E.coli Log(cells/gram)
S15
W16
S16
E.coli Log(cells/gram)
E.coli Log(cells/gram)5.0
E. coli : (uidA gene) Faecal Contamination IndicatorEcoli Log cells/gram W16
S15
W16
S16
Ray6 Ray4 Cut2 Ray_TC2 Cut6 Cut1 Ray5 Cut5 Cole1 Coln4RThames3 Coln5Wye Enbourne RThames2 Thame6 Lodden Evenload Ockkey1 Leach1 Coln1 Pang Leach2 RThames6 Cut3 Cole2 Cole3 Ray2 Coln2 Ray1K3K5K6Cut4Ray3K2RThames1 Coln3 RThames5 K12Cherwell K1Thame8 Thame4 key2 Thame5 RThames4 Thame7 K14K15key3 K8Lam3 K11Thame1 K13K9 K7Lam2 Thame3 K10K4Lam1 Lam5 Lam4 Thame2
−6
−4
−2
0
2
4
RuBac Log Abundance
S15
W16
S16
Cut5 Cut3 Cut6 Cut4 Cut1 Cut2 Lam1 K6 K7Lam2 K13 K15 K5Coln1 Lam5 Coln2 Ray2 Lodden Thame1 Wye Pang OckRThames5 Coln3 Thame6 Lam3 RThames6 K4Leach2 Coln4 K9 K10Ray1 Thame4 K12Enbourne Thame5 Thame3 Lam4 Thame2 Thame7 Thame8 K3key1 Cole2 key3 RThames1 RThames3 K1K14Leach1 K2K8Cole3 Cherwell Ray3 Coln5 K11RThames4 Cole1 Ray5 RThames2 key2Ray4 Ray6 Evenload Ray_TC2
0
1
2
3
4HuBac Log Abundance
S15
W16
S16
Ray3 K12 K6key3 K7Cut4 Cut6 Cut5 Ray6 Coln4 Ray4 Cut2 K3key2 Enbourne WyeCut3 Cut1 Cole1 Evenload Thame2 Lam4RThames5 Thame5 RThames4 RThames6 K5K1Ock Coln5RThames2 Coln2 Coln3 Cherwell Coln1K11 K2Lam5 Thame3 K13Lam2 K8 K9 K14Lodden K10RThames1 Lam1 Ray1 Pang Thame6 Lam3 RThames3 Thame7 Thame1 Leach1 Thame4 Cole2 Cole3 Ray_TC2 Ray5 Ray2 Leach2 key1 Thame8 K15K4
0
1
2
3
4
Entero Log Abundance
S15
W16
S16
K11Thame5RThames4Thame3 LoddenRThames5RThames2RThames3K13 K14Lam3 key2EvenloadLam5 Thame7 K15RThames1Thame2 Thame1 Coln5 Thame4 Cut5 Ray5 Ray6 Cut4 Ray4 Wye Cut2Enbourne Ray_TC2Ray3 K2 K3Coln3 Cut3 K6 K4 K5 K9Ock Cole2 Leach2 Thame6 Cole1 Coln1 Lam4 Leach1 Ray1 K10PangRay2K12Thame8 Cut6 Cut1 Lam1 Coln4 key3K7Lam2 Cole3RThames6Cherwell K8Coln2 K1key1
1
2
3
4
5
HuBaC and RuBac: Seeing differences between abundance of each within various tributaries
Human or animal origins?
Previous model work on the Environmental Resistome: Thames Catchment
The Thames catchment consists of ~66500 miles of sewer and 350 WWTPs that treat 4.2 billion litres of sewage everyday.
Amos et al., 2015. The ISME Journal, 9, 1467–1476
-2.0 0.5-1.5 -1.0 -0.5 0.0Predicted log integron prevalence (%)
Obs
erve
d lo
gin
tegr
on
prev
alen
ce(%
)
adj-R2= 0.83
-1.5
-2.0
-1.0
-0.5
0.0
0.5
-1.5
-1.0
-0.5
0.0
0.5
Actu
al lo
g in
tegr
onpr
eval
ence
WWTP only
-2.0
0.0 0.5 1.0 1.5 2.0 2.5
Predicted log integron prevalenceAll metadata
Explained 49 % of variance:R2 adjustedà
(0.49) P < 0.01
Explained 82. 9% of variance : R2 adj (0.83) P < 0.01
Alternatives to ABU
Vaccines* Probiotics*Improved microbiomes Animal husbandry Improved sanitationIdentification of drivers of AMR
*Shrimp farming, viral diseases white spot syndrome virus (WSSV) use GMO Bacillus subtilis spores that display the VP28 capsid protein of WSSV and when administered in feed appears to protect against white spot disease. Protective mechanism unclear; shrimp are not thought to produce antibodies, but presentation of the viral antigens does produce some level of specific immunity. Hoelzer et al., Vet Research 2018
In conclusion
Improving the natural defences :
initiate innate and subsequent adaptive immune responses, e.g. triggering the host’s pattern recognitionreceptors
De Bruijn et al., FEMS Microbiol Ecol.2018
University of Warwick Professor Liz Wellington Dr Chris QuinceDr Jennie HoldenDr Seb RaguideauDr Hayley KingDr Gemma Hill Séverine Rangama
University of ExeterDr Will GazeDr Lihong Zhang Konrad Paszkkiewicz Suzanne Kay
Thames WaterHoward Brett
Rothamsted ResearchDr Andrew Mead
Hong Kong UniversityDr Tong Zhang
University of BirminghamProfessor Peter Hawkey
CEH, Wallingford Dr Andrew Singer Dr Mike Bowes Holly Tipper
Using next generation sequencing to reveal human impact on aquatic reservoirs of antibiotic resistant bacteria at the catchment scale
RESERVOIRS
