Keynote at CVASU’s 16th International Scientific Conference by Professor Damer Blake of the Royal Veterinary College (RVC), London. October 2019.

1. Enteric parasites and microbiomes of poultry:
interactions with relevance to veterinary and
public health
David Ferguson, University of Oxford
Damer Blake and the Eimeria FADH consortium

2. Chicken production is booming…
• > 66 billion broilers produced in 2017 (FAO)
…and so are Eimeria

3. The problem: coccidiosis
Eimeria spp.

4. Eimeria spp.
• Necrotic enteritis
• Well established link with Clostridium perfringens
• Salmonella enterica Typhimurium
(e.g. Baba et al., 1982 Res. Vet. Sci. 33:95-8)
Coccidiosis + dysbiosis
• Campylobacter jejuni? A notable public health risk…

5. E. tenella impact on the caecal microbiome
• E. tenella is widespread and pathogenic
• Replicates within the chicken caeca
• Site of digestion, fermentation, nutrient absorption
• Numerous microbial community
• Contributes to pathogen defence
• E. tenella impact on dysbiosis?

6. 0 (Normal) 1 2 3 4
E. tenella impact on the caecal microbiome
• E. tenella = caecal lesions, 0-4 Johnson and Reid, 1970
Uninfected
• 8-10 / lesion score category
• Caecal lumen contents - genomic DNA
• Illumina NGS microbiome
• Disease severity: infected 21 days old, lesion score 108 hrs

7. Microbiome sequencing
• Microbiome sequencing is well established for
bacterial communities
• Commonly targets the 16S ribosomal DNA
• Highly conserved
• Several variable regions
• PCR using DNA from bacterial populations
• ‘Deep’ sequence – operational taxonomic units (OTUs)

8. OTUs: alpha diversity
Occurrence of taxa not affected by E. tenella
infection

9. OTUs: beta diversity (PCoA)
Uninf:LS4
LS0:LS3 LS0:LS4
Proportions of taxa affected by E. tenella infection

10. Log2 fold change
Significant genus changes:
all infected compared to uninfected (reference)
5 0 -5-2.5 -7.52.5
Staphylococcus
Brachybacterium
Brevibacterium
Jeotgalicoccus
Corynebacterium
Anaerotruncus
Lactobacillus
Bifidobacterium
Clostridium
Propionibacterium
Strenotrophomonas
NA

11. Log2 fold change
Significant genus changes: LS4 compared to LS0
5 0 -5
Lactobacillus
Bifidobacterium
Clostridium
NA
Pediococcus
SMB53
Candidatus arthromitus
Streptococcus
Ruminococcus
Anaerotruncus
Ruminococcus
Strenotrophomonas
Bacteroides

12. Number of significantly different species
LS 0 LS 1 LS 2 LS 3 LS 4
Uninfected 26 23 16 31 41
1 3 29 35
0 1 10
0 1
0
Differentially abundant species
10
20
30
40
Number
different
OTUs vs
Uninfected

13. Number of significantly different species
LS 0 LS 1 LS 2 LS 3 LS 4
Uninfected 26 23 16 31 41
1 3 29 35
0 1 10
0 1
0
Differentially abundant species
10
20
30
40
Number
different
OTUs vs
Uninfected
• Uninfected vs infected
•  E. coli / Shigella in infected chickens
•  Streptococcus / Staphylococcus… + unidentified OTUs
• Lactobacillus  L. johnsonii (LS 0)
 L. reuteri, L. pontis (LS 3/4)

14. Number of significantly different species
LS 0 LS 1 LS 2 LS 3 LS 4
Uninfected 26 23 16 31 41
1 3 29 35
0 1 10
0 1
0
Differentially abundant species
10
20
30
40
Number
different
OTUs vs
Uninfected
• Lesion scores 0 vs 3/4
•  facultative anaerobes in LS 3/4 – many
Enterobacteriaceae
• Bacteroides almost disappear in LS 0
• Lactobacillus  L. johnsonii (LS 0) – probiotic?
 L. reuteri, L. pontis (LS 3/4)

15. Host genetics: influence of chicken breed
• Comparison between ‘global’ commercial and
indigenous chicken microbiomes
• Sampled the caeca
• Two locations in India: Tamil Nadu + Anand
• Single and co-reared chickens

16. Host genetics: influence of location
• Strong geographic effect on 16S microbiome:
incorporates husbandry, climate, diet, management…

17. • …sub-divided by breed
Host genetics: influence of chicken breed
A: Aseel, C: Cobb400,
K: Kadaknath, R: Ross 308
-A: Anand, -T: Tamil Nadu

18. • LEfSe analysis: differentially abundant genera as
biomarkers of host breed
Host genetics: influence of chicken breed
• Eimeria co-infection
(qPCR, 18S rDNA NGS)

19. Coccidial metagenomics: broilers
● Ruminants, other hosts
● Cryptosporidium, other coccidians
%sequencerepresentation

20. Coordinate2
Coordinate 1
E. tenella
E. necatrix
E. mitis
E. acervulina
Coccidial metagenomics: Eimeria 18S rDNA

21. 16S rDNA : 18S rDNA
• Microbiome:
• E. tenella/E. necatrix and 16S coordinates 1 and 2
• Specific bacteria:
• E. tenella and selected Lactobacillus spp.
• E. tenella and Campylobacter jejuni

22. Campylobacter colonisation: caeca
a
b
c
0
2
4
6
8
10
0 1 2 3 4 5 6
Log10 CFU
Av
Caecal
C. jejuni
Log10 cfu/g
Eimeria WT Attn - WT Attn -
C. jejuni + + + - - -
• C. jejuni colonisation associated with E. tenella severity
d21 Limit
detn

23. Liver
C. jejuni
Log10 cfu/g
a a
b
0
1
2
3
4
5
0 1 2 3 4 5 6
Log10 cfu
Av
Limit
detn
Campylobacter colonisation: liver
Eimeria WT Attn - WT Attn -
C. jejuni + + + - - -
• Unexpectedly, E. tenella infection associated with reduced
C. jejuni liver load

24. a
a
b
0
1
2
3
4
5
0 1 2 3 4 5 6
Log10 cfu
Av
Campylobacter colonisation: spleen
Spleen
C. jejuni
Log10 cfu/g
Limit
detn
Eimeria WT Attn - WT Attn -
C. jejuni + + + - - -
• Consistently, E. tenella also associated with reduced C.
jejuni spleen load

25. Eimeria WT Attn - WT Attn
C. jejuni + + + - -
IL-1β
IL-6
IFN-γ
IL-2
IL-10
iNOS
IL-13
↑↑a ↑↑a ↑↑a ↑↑a ↑↑a
↑↑a ↑↑a ↑b ↑↑a ↑↑a
↑↑↑a ↑↑↑a ↑b ↑↑↑a ↑↑↑a
↑↑a ↑↑a ↑b ↑↑a ↑↑a
↑↑a ↑↑a ↑b ↑↑a ↑↑a
↑↑a ↑↑a ↑b ↑↑a ↑↑a
↓↓a ↓↓a ↑b ↓↓a ↓↓a
Co-infection impact on immune response (caeca)
Reference transcripts: GAPDH, TATA-BP and 28S rDNA
Bystander
effect?

26. Eimeria WT Attn - WT Attn
C. jejuni + + + - -
muc5ac
muc2
muc13
↑↑a ↑↑a -b ↑↑a ↑↑a
↑↑a ↑↑a -b ↑↑a ↑↑a
↑↑a ↑↑a -b ↑↑a ↑↑a
Co-infection impact on mucosal response
Reference transcripts: GAPDH, TATA-BP and 28S rDNA

27. Mucus layer
Glycocalyx
EpitheliumImmunity?
Working model…
Th1
Heterophil influx
Immunity?

28. Summary
• Enteric microbiota is a complex and dynamic environment
• Bacteria, host, immunity, environment…
• Viruses, fungi, parasites such as Eimeria
• Specific bacteria – food safety/security vs probiotics
• Consequences for AMR, chicken productivity and welfare
• Tools are evolving rapidly, costs are decreasing
• Future: population structure and dynamics…

30. https://www.onehealthpoultry.org/

31. Sarah Williams-Macdonald
Matt Nolan
Virginia Marugán-Hernández
Androniki Psifidi
Fiona Tomley
Acknowledgements
Richard StablerAnkit Hinsu
Jalpa Thakkar
Prakash Koringa
Subhash Jakhesara
D. N. Rank
Chaitanya G. Joshi
Muthusamy Raman