The aim of the study was to survey the bacterial populations in the blood of domestic dogs and cattle in order to understand the role they play as reservoirs of zoonotic tick-borne pathogens in the Mnisi community area. Barcoded sample-specific primers were used to amplify the 16S ribosomal RNA gene from genomic DNA from 10 domestic dogs and nine cattle. Sequence analysis revealed the detection of Anaplasma, Ehrlichia, Bartonella and Mycoplasma species.

1. Characterization of the bacterial blood microbiome of
dogs and cattle in the Mnisi community, Mpumalanga,
South Africa
• Click on icon to
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Agatha O Kolo, Kelly A Brayton, Nicola E Collins,
Marinda C Oosthuizen

2. Introduction
• In the Mnisi community, dogs are owned by households and
free roaming; cattle rearing is the main agricultural activity
• Mnisi is a rural community at the human/livestock/wildlife
interface

3. • Because of the close interactions shared with people in the
community, dogs and cattle can serve as conduits of infection
to humans
• There is paucity of information on the use of Next Generation
Sequencing (NGS) technology to describe the bacterial
composition of the circulating blood in dogs and cattle
The aim of this study was to provide a comprehensive insight
into bacterial pathogens in the blood of dogs and cattle using
Circular Consensus Sequencing (CCS) on the Pacific
Biosciences platform to understand the role these domestic
animals play as sources of zoonotic and other important
pathogen infections in the Mnisi community

4. Sample set for sequencing
• 9 blood samples collected from dogs in Hluvukani
• 10 cattle blood samples collected at dip tanks in Seville A, Seville B,
Hlalakahle, Tlhavekisa and Gottenburg

5. DNA extraction
16S rRNA gene amplification using barcoded
primers
Circular consensus sequencing (CCS) on the Pacific Biosciences
(PacBio) platform at Washington State University
Binning, trimming and filtering of sequence data using CLC Genomics
Workbench, Ribosomal Database Project (RDP) 16S classifier, NCBI BLASTn &
Microsoft Excel
Methods
Alpha diversity
calculated and
plotted using
vegan in R
Principal Component
Analysis (PCA) to
quantify compositional
similarity/dissimilarity of
bacterial population in
canine and bovine blood
using FactoMineR in R
9 blood samples from dogs
10 blood samples from cattle
Statistically significant
differences in bacterial
composition using
Analysis of Variance
(ANOVA) and Kruskal-
Wallis rank sum test
Sequences
blasted against
local
Anaplasma spp.
database

6. Sequence and statistical analysis in dogs
• 30,340 bacterial sequences generated
• Mean number of reads = 3,034 = sufficient to satisfy a rarefaction curve indicating that
majority of OTUs were captured. OTUs that were less than 1% of the total number of
sequences were grouped as ‘rare’
Mean species diversity of bacterial populations detected in the dogs plotted using a
rarefaction curve plateaued early in the sampling indicating that the majority of
bacterial communities were well represented

7. Relative abundance of major taxa
of bacteria in dogs

8. • Dogs (D2), (D21) and (D26) were linked to the variables E. canis and Ehrlichia spp.
as main positive contributors
• Dogs (D6), (D13), (D14) and (D24) were linked to variables A. xylosoxidans
• Dogs (D25) and (D36) were linked to variables Anaplasma spp.
• Dog (D28) was linked to the rare group
PCA plot of individuals factor map
vs variables factor map

9. • 34,559 bacterial sequences generated
• Mean number of reads = 3,839
• Blood microbiome dominated by Anaplasma spp.
• One sequence each of Brucella sp., Rickettsia sp. and Borrelia sp.
• Others = Bartonella bovis (~0.4%), E. minasensis (~0.02%)
Sequence and statistical analysis in cattle

10. Relative abundance of major taxa of
bacteria in cattle

11. • C17 was linked to the variables Anaplasma sp. Dedessa and A.
centrale as main positive contributors
• Cattle (C5), (C13) and (C47) were linked to the variable A. marginale
• Cattle (C10) and (C38) and (C96) were linked to the variables
Anaplasma sp. Mymensingh and Anaplasma spp. C91 was linked to
Anaplasma sp. Hadesa
PCA plot of individuals factor map
vs variables factor map

12. Discussion
• Anaplasma spp. approx. 36% of all sequences in canine blood
• Dogs in the Mnisi community had co-infections of Anaplasma sp.
ZAM dog and zoonotic A. platys and A. phagocytophilum
• Negative correlation of infection observed between Anaplasma spp.
and E. canis infection in the dogs
• First report of A. xylosoxidans and hemotropic M. haemocanis in
dogs in SA

13. • Anaplasma spp. comprised 96.8% of sequences in cattle blood
• First report of novel Anaplasma sp. Mymensingh, Anaplasma sp.
Dedessa, Anaplasma sp. Hadesa & Anaplasma sp. Saso in cattle in
SA
• Negative correlation of infection observed between A. marginale,
Anaplasma sp. Mymensingh and Anaplasma sp. Dedessa infections
• Detection of Bartonella bovis, Ehrlichia minacensis, Brucella
melitensis and Borrelia sp. in very small fraction in cattle blood

14. • This study demonstrated a highly diverse blood microbiome of
domestic dogs and cattle in the Mnisi community
• It reports on the detection of recently described novel species in
dogs and cattle
• It confirms that dogs and cattle are reservoirs of Anaplasma
species and other infectious pathogens in the community and
highlights the zoonotic risks posed to human health
Conclusion

15. Acknowledgements
• Research funding agencies = UP,
NRF and ITM/DGCD
• My PhD Supervisors
• Prof Eric Etter
• Derek Pouchnik & Mark Wildung @
WSU
• Jeanette Wentzel @ HH
• Environmental monitors of Mnisi
community programme
• DVTD Staff and Students

16. “If you don’t like bacteria
you are on the wrong
planet”……Stewart Brand

17. THANK YOU