Talk at ASMicrobe-2022 in Washington DC.

1. Ben Pascoe
b.pascoe@bath.ac.uk | Twitter @benizao
Attributing the source of clinical
campylobacteriosis cases in the
United States

2. Campylobacter: Human infection predominantly from eating undercooked
contaminated poultry products
 Contaminated chicken products
 More often in young people,
 More severe in older people;
 Seasonal differences
Nichols et al 2012: BMJ Open e001179.
2019 FoodNet estimates
 9,731 infections
 1,988 hospitalizations
 26 deaths
 19.5 cases per 100,000
 13% increase from baseline period
Tack, D. M., et al. (2020): MMWR Morb Mortal Wkly Rep 68(16): 369-373

3. A year in Campylobacter research
Neglected lineages and new species
o Campylobacter bilis sp. nov., isolated from chickens with spotty liver disease | Phung et
al (2022): doi.org/10.1099/ijsem.0.005314
o Characterization of Campylobacter jejuni Adapted to the Guinea Pig (novel sub-
species?) | Parker et al (2021): doi.org/10.3389/fcimb.2021.607747
o Quantifying bacterial evolution in the wild |Calland et al (2021):
doi.org/10.1371/journal.pgen.1009829
Global perspectives on Campy infections
o Local accessory genome sharing in Egypt | Mouftah et al (2022):
doi.org/10.1099/mgen.0.000834
o Genomic epidemiology of Campylobacter from Chile | Bravo et al (2021):
10.1371/journal.pntd.0009207
o Genomic Analysis and AMR of Campy in Peru | Quino et al (2022):
doi.org/10.3389/fmicb.2021.802404
Interactions with other species
o Interspecies recombination in bacteria of the genus Campylobacter | Mourkas et al
(2022): doi.org/10.7554/eLife.73552

4. A year in Campylobacter research
Antimicrobial resistance
o 18 years of Campy AMR | Van Vliet et al (2022): doi.org/10.1128/aac.01687-21
o In public repositories | Cobo-Diaz et al (2021): doi.org/10.3389/fmicb.2021.662144
Source attribution
o Host-Segregating SNPs C. coli | Jehanne et al (2020): doi.org/10.1128/AEM.01787-20
o ML to predict the source of campylobacteriosis| Arning et al (2022):
doi.org/10.1371/journal.pgen.1009436
Surveillance
o New Hampshire | Park et al (2020): doi: 10.1128/JCM.02070-19
o Tennessee | Kelley et al (2021): doi.org/10.3389/fmicb.2020.571064
o High-risk lineages | Peters et al (2021): doi.org/10.1038/s42003-021-02554-8
@benizao

5. Several potential sources.
Sheppard et al. (2009) Campylobacter Genotyping to Determine the Source of Human Infection. Clinical Infectious Diseases 48:1072–1078
Sheppard et al. (2010) Host Association of Campylobacter Genotypes Transcends Geographic Variation. Applied Environmental
Microbiology 76, 5269-5277
952
22
42
45
177
682
48
1275
661
692
61
206
354
257
1034
574
21
Different hosts have different Campylobacter
types so disease can be attributed.
Several potential sources of disease

6. 1
0.5
0
` 1000 2000 3000 4000
1
0.5
0
1
0.5
0
500
0
0
A
B
Source
probability
Human cases
1 1
0
0.2
0.4
0.6
0.8
1
0
0.2
0.4
0.6
0.8
1
Proportion
of
human
cases,
STRUCTURE
A B
C D
C. jejuni C. coli Chicken is a major source of
human infection
Sheppard et al. (2009) Clinical Infectious Diseases 48:1072–1078
Clinical isolates can be assigned to different hosts based on MLST genes

7. Greater proportion of French isolates attributed to
ruminant sources
60 – 80 % attributed to chicken
40 – 60 % to ruminant
4 – 10 % to wild birds & environment
(Sheppard et al., 2009, Kittl et al., 2013, Boysen et al., 2014, Mossong et al., 2016)
Differences in attribution between countries

8. Pascoe B et al. (2016) Local genes for local bacteria: evidence of allopatry in the genomes of transatlantic
Campylobacter populations. Molecular ecology 26 (17), 4497-4508
Highly recombining genes can be used to attribute isolates by geography

9. Gaps in attribution ability when the test population is too
different from the putative reservoir collection
Effective source attribution relies on
composition of your comparison dataset:
-> rare STs/CCs poorly attributed
-> under sampled sources?
Pascoe et al (2020) Genomic epidemiology of Campylobacter jejuni associated with asymptomatic
pediatric infection in the Peruvian Amazon PloS NTD 14(8):e0008533; doi:
10.1371/journal.pntd.0008533

10. Sample dataset: ~25,000 genomes
Peter Evans
FSIS

11. Clustering by source reservoir

12. C. jejuni C. coli
Host-restricted and generalist lineages cause clinical disease

13. Random forest selection of host segregating markers
Machine learning to predict the
source of campylobacteriosis
using whole genome data
Arning et al (2021): PLoS
Genetics
doi.org/10.1371/journal.pgen.1
009436
Present in source #1, but
absent in source #2.
2,000 markers per source
selected for further
analysis.

14. Markers scored and mapped back to pangenome

15. Self test accuracy of selected markers when used in iSource
attribution model
Review | Cody et al (2019): Eurosurveillance 10.2807/1560-7917.ES.2019.24.43.1800696
Overall self-test accuracy: 82%

16. Poultry is the major source of campylobacteriosis: C. jejuni

17. Poultry is the major source of campylobacteriosis: C. coli

18. 1-Rising incidence (FoodNet)
2-Rising % attributed to chicken
3-Increasing FQ resistance?

19. Increase in MDR by HSS region
(2009 vs 2018)

20. FSIS: Peter Evans, Mustafa Simmonds, Neal
Golden, Glenn Tillman
CDC: Beau Bruce, Lavin Joseph, Charlotte Lane
FSA: Michael Williams
pubMLST: Keith Jolley, Martin Maiden
University of Oslo: Johan Panesar, Jukka
Corander
Pathogen Genomics & Evolution Group,
University of Bath (Prof. Samuel Sheppard)
Special thanks to Grant Futcher
L>R: (me!), William Monteith, Sarah Bennett, Sam
Sheppard, Jessica Calland & Evangelos Mourkas
Joining the University of Oxford later in 2022
THANKS!