Molecular characterisation of selected enteric pathogens and antimicrobial resistance
of Salmonella in rangeland goats in Western
Australia
Thesis presented by
Khalid Rasheed Saif Al-Habsi BSc, MScAnSc
for the degree of
Doctor of Philosophy
School of Veterinary and Life Sciences
Murdoch University
2017 Declaration
I declare that this thesis is my own account of my research and contains as its main content work, which has not been previously submitted for a degree at any tertiary education institution. The methods and results described in this thesis reflect the work performed and are supported with records in the lab books.
Khalid Rasheed Saif Al-Habsi
December 2017
i Statement of Contribution
The five experimental chapters presented in this thesis have been either published as peer reviewed articles (Chapters 3-6) or submitted (Chapter 9) with multiple co- authors. Khalid Rasheed Saif Al-Habsi was the first author on these publications, primarily involved in conceiving ideas and project design, laboratory work, data analysis, interpretation of results and preparation of manuscripts.
All publication co-authors have consented to their work being included in this thesis and have accepted this statement of contribution.
Chapter Title Contribution 3 Zoonotic Cryptosporidium and Giardia K Al-Habsi: 80 % shedding by captured rangeland goats C Jacobson: 8 % U Ryan: 5 % R Yang: 3 % D Miller: 3% A Williams: 1% 4 Morphological and molecular K Al-Habsi: 76 % characterization of three Eimeria species C Jacobson: 11% from captured rangeland goats in western U Ryan: 9 % Australia R Yang: 3 % D Miller: 1% 5 Morphological and molecular K Al-Habsi: 78 % characterization of an uninucleated cyst- U Ryan: 16 % producing Entamoeba spp. in captured R Yang: 3 % rangeland goats in western Australia D Miller 2% C Jacobson: 1 % 6 Molecular characterisation of Salmonella K Al-Habsi: 71 % enterica serovar Typhimurium and C Jacobson: 16 % Campylobacter jejuni faecal carriage by U Ryan: 6 % captured rangeland goats S Abraham: 2% R Yang: 3% D Miller: 2% 9 Salmonella enterica isolates from K Al-Habsi: 83 % Western Australian rangeland goats D Jordan: 5% remain susceptible to critically important S Abraham: 3% antimicrobials A Harb: 2% T Laird: 2% R Yang: 2% C Jacobson: 1% U Ryan: 1% D Miller: 1%
ii Abstract
The Australian goat meat industry is largely supported by the sale of captured feral goats derived from rangeland production systems. Diarrhoea and ill-thrift following capture is a major issue for the industry, yet relatively little is known about the role of infectious disease and the public health significance of gastrointestinal infections. The aim of this thesis was to characterise faecal carriage of selected enteric pathogens by rangeland goats using molecular tools, and to determine potential impacts for goat productivity and public health. A longitudinal study conducted using qPCR and sequencing to screen faecal samples revealed that faecal carriage (prevalence) and shedding intensity of enteric pathogens were generally highest on arrival at the goat depot (feedlot), immediately after capture and transport. Three Cryptosporidium species (C. xiaoi, C. ubiquitum and C. parvum), Giardia duodenalis Assemblage E, three Eimeria species (E. ahsata, E. crandallis and E. arloingi), E. bovis-like Entamoeba sp., Salmonella enterica serovar
Typhimurium, Campylobacter jejuni, Haemonchus contortus and Trichostrongylus spp. were identified in faecal samples from the rangeland goats using molecular tools. Of these, C. ubiquitum subtype XIIa, C. parvum subtypes IIaA17G2R1 and IIaA17G4R1, G. duodenalis Assemblage E, S. enterica serovar Typhimurium and C. jejuni are considered zoonotic or emerging zoonotic pathogens. These studies provided the first description of caprine Eimeria cytochrome c oxidase subunit I (COI) and Entamoeba bovis-like actin sequences, and successfully produced a longer (1,229 bp) 18S rRNA sequence of E. arloingi. Of the pathogens identified in faecal samples, only Cryptosporidium was associated with an increased risk of scouring (diarrhoea) and reduced growth in the following one-month period. Giardia faecal carriage and higher Eimeria oocyst counts were associated with looser faecal consistency, but not to the point where scouring risk was increased.
iii A subsequent investigation of rangeland goats consigned from four locations identified high rates (23-30%) Salmonella faecal carriage, with three serovars identified
(S. Typhimurium, S. Chester and S. Saintpaul) at slaughter, indicating the potential for downstream carcass contamination and food safety concerns. A high percentage of
Salmonella isolates (84.0%) remained entirely susceptible to all antimicrobials tested, which is encouraging, with low rates (4/106) of multi-drug resistance (resistant to three of more classes of antimicrobials) and no resistance to critically important antimicrobials
(fluoroquinolones and third generation cephalosporins) was observed.
The findings of the present study have important implications for management and animal welfare of captured rangeland goats starting from capture yards and feedlots through to slaughter to reduce public health risks.
iv Table of Contents
Declaration ...... i
Statement of Contribution ...... ii
Abstract ...... iii
List of Figures ...... xiv
List of Tables ...... xvi
Acknowledgements ...... xix
Publications arising from this thesis ...... xxii
Poster presentations of work contained within this thesis ...... xxiv
Symbols and Abbreviations ...... xxv
CHAPTER 1. LITERATURE REVIEW ...... 29
1.1. Introduction ...... 29
1.2. Cryptosporidium...... 29
1.2.1. Taxonomy of Cryptosporidium ...... 30
1.2.2. Life cycle of Cryptosporidium ...... 33
1.2.3. Prevalence of Cryptosporidium in goats ...... 35
1.2.4. Host immune response to Cryptosporidium ...... 36
1.2.5. Pathogenesis of Cryptosporidium ...... 36
1.2.6. Diagnosis of Cryptosporidium ...... 37
1.2.7. Treatment of Cryptosporidiosis ...... 37
1.3. Giardia ...... 38
1.3.1. Life cycle of Giardia ...... 42
1.3.2. Prevalence of Giardia in livestock and goats...... 43
1.3.3. Pathogenesis of Giardia ...... 44
1.3.4. Host immune response to Giardia ...... 44
1.3.5. Diagnosis of Giardia ...... 44
1.3.6. Treatment of Giardia ...... 45
v 1.4. Eimeria ...... 45
1.4.1. Taxonomy of Eimeria ...... 46
1.4.2. Life cycle of Eimeria...... 48
1.4.3. Prevalence of Eimeria in goats...... 50
1.4.4. Pathogenesis of Eimeria in goats ...... 50
1.4.5. Host immune response to Eimeria ...... 51
1.4.6. Diagnosis of coccidiosis ...... 51
1.4.7. Treatment of Eimeria ...... 51
1.5. Entamoeba ...... 52
1.5.1. Prevalence of Entamoeba ...... 52
1.5.2. Pathogenesis and host immune response to Entamoeba ...... 53
1.5.3. Diagnosis of Entamoeba ...... 53
1.5.4. Treatment of Entamoeba ...... 54
1.6. Gastrointestinal nematodes (GIN) ...... 54
1.6.1. Life cycle ...... 54
1.6.2. Prevalence of GIN’s in goats ...... 56
1.6.3. Pathogenesis and immune response ...... 56
1.6.4. Diagnosis of GINs ...... 57
1.6.5. Treatment of GINs ...... 58
1.7. Salmonella and Campylobacter ...... 58
1.7.1. Prevalence of Salmonella and Campylobacter sp. and serotypes ...... 59
1.7.2. Immune response of caprine hosts to Salmonella and Campylobacter ...... 60
1.7.3. Pathogenesis of Salmonella and Campylobacter ...... 60
1.7.4. Diagnosis of Salmonella...... 61
1.7.5. Prevention and Treatment of Salmonella and Campylobacter...... 61
1.7.6. Antimicrobial resistance ...... 62
1.8. Aims and Objectives ...... 64
CHAPTER 2. MATERIALS AND METHODS ...... 66
vi 2.1. Animal ethics...... 66
2.2. Animals and faecal samples collection at feedlot (depot) ...... 66
2.3. Diarrhoea and Production Measurements ...... 67
2.3.1. Breech faecal score (dag score) ...... 67
2.3.2. Faecal consistency score ...... 68
2.3.3. Live weight and body condition score ...... 69
2.4. Anthelmintic treatment ...... 69
2.5. Faecal worm egg counts ...... 69
2.6. DNA isolation from faecal samples ...... 70
2.7. Molecular detection and quantification of selected enteric pathogens by quantitative PCR (qPCR) ...... 72
2.7.1. Molecular detection and quantification of Cryptosporidium by qPCR...... 73
2.7.2. Molecular detection and quantification of Giardia by qPCR ...... 73
2.7.3. Molecular detection and quantification of Eimeria by qPCR ...... 73
2.7.4. Molecular detection and quantification of Salmonella and Campylobacter by qPCR and specificity, sensitivity and efficiency for qPCR ...... 73
2.7.5. Molecular detection and quantification of strongylid by qPCR ...... 74
2.8. PCR amplification and sequencing ...... 76
2.8.1. Amplification of Cryptosporidium at the 18S rRNA gene ...... 76
2.8.2. Subtyping of C. parvum at the 60 kDa glycoprotein (gp60) ...... 76
2.8.3. Subtyping of C. ubiquitum at the 60 kDa glycoprotein (gp60) locus ...... 77
2.8.4. Amplification of Giardia spp. at the glutamate dehydrogenase (gdh) locus 78
2.8.5. Amplification of Giardia spp. at the β-giardin (bg) locus ...... 79
2.8.6. Amplification of Giardia spp. at the triose phosphate isomerase (tpi) locus ……………………………………………………………………………..79
2.8.7. Amplification of Entamoeba at the 18S rRNA locus ...... 81
2.8.8. Amplification of Entamoeba at the Actin locus ...... 81
2.8.9. Amplification of Salmonella at the outer membrane porin ompF locus ...... 82
2.8.10. Amplification of Salmonella at the invasion A (invA) locus ...... 82
vii 2.8.11. Amplification of Salmonella at the serovar Typhimurium specific gene loci, STM2755 and STM4497 ...... 83
2.8.12. Amplification of Campylobacter at the 16S rRNA locus ...... 83
2.8.13. Amplification of Campylobacter at the hippuricase (hipO) locus ...... 84
2.8.14. Amplification of Eimeria at the 18S rRNA locus ...... 85
2.8.15. Amplification of Eimeria at the cytochrome c oxidase subunit I (COI) locus ...... 86
2.9. Agarose gel electrophoresis ...... 87
2.10. Sanger sequencing ...... 87
2.11. Sequence and phylogenetic analysis ...... 88
2.12. Microscopy ...... 88
2.12.1. Morphometric assessments of Entamoeba cysts and trophozoites ...... 88
2.12.2. Morphometric assessments of Eimeria spp. oocysts ...... 89
2.12.3. Isolation and analysis of single Eimeria oocysts using a micromanipulator 90
2.13. Additional sampling of rangeland goats at Beaufort River Meats abattoir .. 91
2.14. Salmonella isolation and MALDI–TOF analysis ...... 93
2.15. DNA Extraction...... 94
2.16. PCR amplification and sequencing ...... 94
2.17. Salmonella antimicrobial susceptibility testing and interpretation ...... 95
2.18. Statistical analysis ...... 97
2.19 Conflict of interest statement ...... 98
CHAPTER 3. ZOONOTIC CRYPTOSPORIDIUM AND GIARDIA SHEDDING BY CAPTURED RANGELAND GOATS ...... 99
3.1. Introduction ...... 100
3.2. Materials and methods ...... 102
3.2.1. Animals and sample collection ...... 102
3.2.2. DNA isolation ...... 102
3.2.3. PCR screening, amplification and sequencing ...... 102
3.2.4. Statistical analysis ...... 103
viii 3.3. Results ...... 104
3.3.1. Cryptosporidium and Giardia prevalence ...... 104
3.3.2. Cryptosporidium species and subtypes ...... 104
3.3.3. Giardia assemblages ...... 105
3.3.4. Cryptosporidium and Giardia faecal shedding intensity ...... 105
3.4. Discussion ...... 107
3.5. Conclusion ...... 109
CHAPTER 4. MORPHOLOGICAL AND MOLECULAR CHARACTERISATION OF THREE EIMERIA SPECIES FROM CAPTURED RANGELAND GOATS IN WESTERN AUSTRALIA ...... 110
4.1. Introduction ...... 112
4.2. Materials and methods ...... 113
4.2.1. Animals and faecal sample collection ...... 113
4.2.2. Treatments ...... 114
4.2.3. DNA isolation ...... 114
4.2.4. qPCR screening and quantification ...... 115
4.2.5. PCR amplification and sequencing at the 18S rRNA locus ...... 115
4.2.6. Isolation of morphologically similar Eimeria spp. oocysts using a micromanipulator ...... 115
4.2.7. DNA extraction from isolated oocysts ...... 116
4.2.8. PCR amplification and sequencing of isolated oocysts at the 18S and COI loci ……………………………………………………………………………116
4.2.9. Phylogenetic analysis of Eimeria spp...... 117
4.2.10. Speciation based on morphological characteristics ...... 117
4.2.11. Statistical analyses...... 118
4.3. Results ...... 118
4.3.1. Observed prevalence and shedding intensity of Eimeria spp. using qPCR and genotyping at 18S rRNA locus ...... 118
4.3.2. Phylogenetic analysis of three Eimeria spp. at the 18S rRNA locus ...... 122
ix 4.3.3. Phylogenetic analysis of the three Eimeria spp. at the COI locus ...... 124
4.3.4. Morphology of three Eimeria spp. by microscopy ...... 126
4.4. Discussion ...... 130
4.5. Conclusion ...... 134
Chapter 5. MORPHOLOGICAL AND MOLECULAR CHARACTERIsATION OF AN UNINUCLEATED CYST-PRODUCING ENTAMOEBA SPP. IN CAPTURED RANGELAND GOATS IN WESTERN AUSTRALIA ...... 136
5.1. Introduction ...... 137
5.2. Materials and methods ...... 139
5.2.1. Sampling, morphological and molecular analyses...... 139
5.3. Results ...... 141
5.4. Discussion ...... 148
5.5. Conclusion ...... 149
CHAPTER 6. MOLECULAR CHARACTERISATION OF SALMONELLA ENTERICA SEROVAR TYPHIMURIUM AND CAMPYLOBACTER JEJUNI FAECAL CARRIAGE BY CAPTURED RANGELAND GOATS ...... 150
6.1. Introduction ...... 152
6.2. Materials and Methods ...... 153
6.2.1. Animals and faecal sample collection ...... 153
6.2.2. DNA isolation ...... 154
6.2.3. PCR amplification, quantification and sequencing ...... 154
6.2.4. Specificity and sensitivity of qPCR ...... 155
6.2.5. Inhibition and efficiency analysis of qPCR ...... 156
6.2.6. Molecular characterisation of S. enterica and Campylobacter spp...... 156
6.2.7. Statistical analyses...... 157
6.3. Results ...... 157
6.3.1. Specificity, sensitivity and efficiency for qPCR ...... 157
6.3.2. Faecal carriage and intensity for Salmonella enterica and Campylobacter spp...... 158
x 6.3.3. Salmonella enterica and Campylobacter spp. molecular typing...... 159
6.4. Discussion ...... 159
6.5. Conclusion ...... 164
CHAPTER 7. TRICHOSTRONGYLID NEMATODES IN CAPTURED RANGELAND GOATS ...... 165
7.1. Introduction ...... 166
7.2. Materials and methods ...... 167
7.2.1. Animals and sample collection ...... 167
7.2.2. Treatments ...... 167
7.2.3. Faecal worm egg counts ...... 167
7.2.4. DNA extraction and qPCR ...... 167
7.2.5. Statistical analyses...... 167
7.3. Results ...... 168
7.4. Discussion ...... 170
7.5. Conclusion ...... 173
CHAPTER 8. ASSOCIATIONS FOR ENTERIC PATHOGENS FAECAL CARRIAGE WITH GROWTH AND DIARRHOEA IN CAPTURED RANGELAND GOATS IN WESTERN AUSTRALIA ...... 174
8.1. Introduction ...... 175
8.2. Materials and methods ...... 175
8.2.1. Animals and sample collection ...... 175
8.2.2. Treatments ...... 175
8.2.3. Measurements...... 176
8.2.4. DNA extraction, detection and quantification for enteric pathogens ...... 176
8.2.5. Statistical analyses...... 176
8.3. Results ...... 178
8.3.1. Pathogens prevalence and faecal shedding ...... 178
8.3.2. Associations for enteric pathogens with live weight and BCS ...... 180
xi 8.3.3. Associations between enteric pathogens and growth ...... 181
8.3.4. Associations for enteric pathogens with faecal consistency and scouring . 185
8.4. Discussion ...... 191
8.5. Conclusion ...... 194
CHAPTER 9. SALMONELLA ENTERICA ISOLATES FROM WESTERN AUSTRALIAN RANGELAND GOATS REMAIN SUSCEPTIBLE TO CRITICALLY IMPORTANT ANTIMICROBIALS ...... 195
9.1. Introduction ...... 196
9.2. Materials and methods ...... 198
9.2.1. Study design and sample collection ...... 198
9.2.2. Salmonella isolation and identification ...... 199
9.2.3. DNA Extraction...... 200
9.2.4. PCR amplification and sequencing ...... 201
9.2.5. Salmonella antimicrobial susceptibility testing and interpretation ...... 201
9.2.6. Statistical analyses...... 202
9.3. Results ...... 202
9.3.1. Prevalence of Salmonella ...... 202
9.3.2. Salmonella enterica molecular typing...... 203
9.3.3. Antimicrobial resistance testing ...... 204
9.4. Discussion ...... 208
9.5. Conclusion ...... 210
CHAPTER 10. GENERAL DISCUSSION ...... 212
10.1. Utility of molecular tools to determine pathogen faecal carriage ...... 212
10.2. Associations between pathogen faecal carriage with diarrhoea and illthrift in captured rangelend goats ...... 215
10.3. Public health significance of pathogen faecal carriage by captured rangeland goats ...... 217
10.4. Implications of observations for the goat meat industry ...... 219
xii 10.5. Future directions ...... 223
10.6. Conclusions ...... 228
CHAPTER 11 . REFERENCES...... 229
CHAPTER 12 . APPENDICES ...... 288
APPENDIX 1. Prevalence of Cryptosporidium species and glycoprotein 60 (gp60) subtypes in goats and any associated outbreaks...... 290
APPENDIX 2. Prevalence of G. duodenalis assemblages in goats...... 298
APPENDIX 3. DNA isolation from faecal samples...... 302
APPENDIX 4. The 18S rDNA sequences utilised in Eimeria phylogenetic analyses...... 303
APPENDIX 5. The cytochrome c oxidase subunit I (COI) sequences utilised in Eimeria phylogenetic analyses...... 305
APPENDIX 6. The 18S rDNA sequences utilised in Entamoeba phylogenetic analyses...... 307
APPENDIX 7. The actin sequences utilised in Entamoeba phylogenetic analyses. 308
APPENDIX 8. Zoonotic Cryptosporidium and Giardia shedding by captured rangeland goats...... 309
APPENDIX 9. Morphological and molecular characterization of three Eimeria species from captured rangeland goats in Western Australia...... 310
APPENDIX 10. Morphological and molecular characterization of an uninucleated cyst-producing Entamoeba spp. in captured rangeland goats in Western Australia…………… ...... 311
APPENDIX 11. Molecular characterisation of Salmonella enterica serovar Typhimurium and Campylobacter jejuni faecal carriage by captured rangeland goats...... 312
xiii List of Figures
Figure 1.1. Diagrammatic representation of the Cryptosporidium life cycle...... 35
Figure 1.2. The life cycle of G. duodenalis...... 42
Figure 1.3. Life cycle of Eimeria species. (1) Schematic representation of the life cycle of Eimeria in an infected mammal. (2) Illustration of a fully-formed (sporulated) oocyst..
...... 49
Figure 1.4. Generalised life cycle of GIN’s...... 55
Figure 2.1. Captured and transported rangeland goats at the commercial feedlot (depot) near Geraldton, Western Australia...... 67
Figure 2.2. Graphical representation of the breech fleece faecal soiling scale...... 68
Figure 2.3. Faecal worm egg counts at 40x magnification...... 70
Figure 2.4. Captured and transported rangeland goats arriving at Beaufort River Meats abattoir, Western Australia...... 92
Figure 2.5. Removal of digestive tracts from rangeland goats after evisceration at
Beaufort River Meats abattoir, Western Australia...... 93
Figure 4.1 (a) and (b). Evolutionary relationships of Eimeria spp. inferred by distance analysis of using 18S rRNA gene...... 124
Figure 4.2. Evolutionary relationships of Eimeria spp. inferred by distance analysis of the cytochrome c oxidase subunit I (COI) gene...... 126
Figure 4.3. Nomarski interference-contrast photomicrographs of the Eimeria oocysts from rangeland goats; E. arloingi (A), E. christenseni (B) and E. hirci (C) showing oocyst wall (OW), micropolar cap (MC), sporozoites (SP), and sporocyst residuum (SR).. ... 127
Figure 5.1. Nomarski interference-contrast photomicrographs of Entamoeba cysts isolated from rangeland goats showing centrally located karyosome; 5.1a: cyst stained with iodine, 5.1b: cyst in saline mount...... 145
xiv Figure 5.2. Nomarski interference-contrast photomicrographs of Entamoeba trophozoites isolated from rangeland goats showing centrally located karyosome and diffused glycogen, 5.2a: trophozoite stained with iodine, 5.2b: trophozoite in saline mount...... 145
Figure 5.3. Evolutionary relationships of Entamoeba spp. inferred by distance analysis of using 18S rRNA gene sequences.)...... 146
Figure 5.4. Evolutionary relationships of Entamoeba spp. inferred by distance analysis of using partial actin gene sequences...... 147
Figure 12.1. Graphical representation of the Power Soil DNA Isolation Kit methodology...... 302
xv List of Tables
Table 1.1. Valid Cryptosporidium species confirmed by molecular analysis...... 31
Table 1.2. Giardia duodenalis assemblages...... 40
Table 1.3. Eimeria species reported in goats...... 47
Table 2.1. Criteria used in assessment of faecal consistency score (FCS)...... 68
Table 2.2. Target genes and primers used for amplification and sequencing of Salmonella and Campylobacter isolates in rangeland goats...... 85
Table 2.3. Susceptible Clinical and Laboratory Standards Institute clinical breakpoints and cut-off values (ECOFFs) of Salmonella isolates used for MIC interpretation...... 97
Table 3.1. Cryptosporidium and Giardia prevalence and shedding intensity for 125 goats sampled on four occasions (S1-S4)...... 106
Table 4.1. Eimeria spp. prevalence and shedding intensity observed for captured rangeland goats (n=125) sampled on 4 occasions (S1-S4)...... 120
Table 4.2. Frequency of detection of Eimeria spp. shedding in 125 rangeland goats… ...... 122
Table 4.3. Oocyst morphological features for Eimeria spp. from rangeland goats compared with previous reports...... 128
Table 4.4. Sporocyst morphological features for Eimeria spp. from rangeland goats compared with previous reports...... 129
Table 5.1. Morphometric characteristics of uninucleated cyst-producing Entamoeba spp. reported from livestock compared with the Entamoeba cysts isolated from rangeland goats in Western Australia in the present study...... 143
Table 6.1. Specificity and sensitivity analysis for qPCR...... 158
xvi Table 6.2. Frequency of detection and faecal carriage intensity for S. enterica serovar Typhimurium (S. Typhimurium) and C. jejuni in faecal samples collected from 125 rangeland goats on four occasions (S1-S4)...... 159
Table 7.1. Prevalence of Trichostrongylid nematodes as determined by qPCR, in 125 rangeland goats over 4 monthly sampling occasions (S1-S4)...... 169
Table 7.2. Worm egg counts (WEC) determined by MacMaster and qPCR for 125 rangeland goats over 4 sampling occasions (S1-S4) approximately one month apart...... 169
Table 7.3. Agreement between qPCR and McMaster for detection of Trichostrongylid nematodes in goat faecal samples (n=500)...... 170
Table 8.1. Mean (± standard error) and range for worm egg count (WEC) (determined by microscopy) and Eimeria oocyst count (determined by qPCR) for 125 goats sampled on 4 occasions (S1-S4)...... 178
Table 8.2. Enteric pathogen prevalence (% with 95% confidence interval in parentheses) for 125 goats sampled on 4 occasions (S1-S4)...... 179
Table 8.3. Association of pathogen faecal shedding category with live weight and body condition score (BCS) determined using linear mixed effects models, with least square means ± standard error (LSM ± SE), F-value and P-value for pathogen main effect...... …180
Table 8.4. Live weight and body condition score (BCS) for goats at four sampling occasions (S1-S4) and bivariate correlations (Pearson co-efficient) with McMaster worm egg count (WEC) and qPCR Eimeria oocyst count (OPG)...... 181
Table 8.5. Growth for rangeland goats at four sampling occasions (S1-S4)...... 182
Table 8.6. Association of pathogen faecal shedding category with weight change for one month previous to sampling (past growth) and one month after sampling (future growth) determined using linear mixed effects models, with least square means ± standard error (LSM ± SE), F-value and P-value for pathogen main effect...... 183
Table 8.7. Association between faecal carriage for Cryptosporidium species and future growth determined using linear mixed effects models, with least square means ± standard
xvii error (LSM ± SE), F-value and P-value for pathogen (Cryptosporidium species) main effect...... 184
Table 8.8. Bivariate correlations (Pearson co-efficient) between growth for past (preceding month) or future (following month) growth with McMaster worm egg count (WEC) and qPCR Eimeria oocyst count (OPG)...... 185
Table 8.9. Association of pathogen faecal shedding category with faecal consistency score (FCS) determined using linear mixed effects models, with least square means ± standard error (LSM ± SE), F-value and P-value for pathogen main effect...... 186
Table 8.10. Association for faecal shedding of different Cryptosporidium species with faecal consistency score (FCS) determined using linear mixed effects models with least square means ± standard error (LSM ± SE), and proportion of samples (%) categorised as scouring in each category with Chi-square Fishers’ 2-sided exact test for significance...... 187
Table 8.11. Comparison of scouring prevalence (% faecal samples with FCS > 3) for samples with and without pathogen faecal carriage detected with 2-sided Fishers’ exact test for significance...... 189
Table 8.12. Mean faecal consistency score (FCS) ± standard error (SE) for goats sampled at four sampling occasions (S1-S4) and bivariate correlations (Pearson co-efficient) with McMaster worm egg count (WEC) and qPCR Eimeria oocyst count (OPG)...... 190
Table 9.1. Percent of rangeland goats (n=400) with Salmonella enterica detected in faeces at slaughter in Western Australia showing breakdown by origin of consignment and serovar detected...... 203
Table 9.2. Distribution of MICs and resistance among Salmonella isolates (n=106) from faecal samples collected from rangeland goats at slaughter in Western Australia...... 205
xviii Acknowledgements
At the end of a long incubation period, this thesis has finally seen the light of day.
It would have remained forever dormant if it had not been for the help and encouragement of a great many people. I am gratefully indebted to my supervisors Professor Una Ryan,
Dr Caroline Jacobson, Dr Rongchang Yang, Dr Sam Abraham and Associate Professor
David Miller for their instruction, guidance and mentoring and for sharing their experience and the time they dedicated to my work. In particular, Professor Una, I believe that your philosophy and patience bring out the best in me and made a deep and lasting impression on my life. Many thanks for your continuous support and hosting me in your research group the past years. I would also like to thank Dr Caroline Jacobson for her brilliant comments and suggestions throughout the entire course. Caroline thanks for sharing your expertise and statistical advices at times of critical need. My heartfelt gratitude to Dr Rongchang Yang for training me in molecular techniques and for his constant support. Thanks Rongchang for teaching me to overcome difficulties and focus on the target, in order to be successful. Similarly, profound gratitude goes to Dr Sam
Abraham, who has introduced me to the exciting world of microbial resistance and who has been a truly dedicated mentor. I cannot forget the valuable help and motivation of
Associate Professor David Miller. I salute you, David for your help and support throughout the project, for the several hours of driving to Geraldton for sampling and for keeping an open door during the difficult times in my research. I will remain forever grateful.
I gratefully acknowledge the funding received towards my PhD project concerning the molecular characterisation of the selected enteric pathogens in the rangeland goats from the Meat and Livestock Australia and Livecorp. My sincere thanks also goes to the School of Veterinary and Life Sciences, Murdoch University for providing a small grant to fund the study concern the investigation of the prevalence of
xix Salmonella carriage and antimicrobial resistance among Salmonella isolates from the slaughtered rangeland goats.
I extend particular thanks to Keros and Preston Keynes for providing access to their facilities near Geraldton and assistance with sampling of the rangeland goats
(Chapters 3–8).
I am obliged to Andrew Williams, Murdoch University for his invaluable direction and help with the statistical analysis of the linear mixed effects models of
Chapters (7–8).
I would also like to acknowledge the assistance of Laurence Macri, the plant manager of Beaufort River Meats, Western Australia and his team for their arrangements with sampling of slaughtered rangeland goats (Chapter 9).
Thanks to my friends and colleagues in the Vector and Waterborne Pathogen
Research Group, and the many people in the State Agricultural and Biotechnology Centre
(SABC) for their help, companionship, support and assistance during the time spent there.
I appreciate the great companionship of the officemates; Amanda Barbosa, Cindy
Palermo and Diana Prada and Kamil Ali Braima. Thanks to Elvina Lee for her assistance in the use of the micromanipulator for single Eimeria oocysts isolation (Chapter 4) and
Tanya Laird and Ali Harb for all the help during the work on the antimicrobial resistance
(Chapter 9).
I am grateful to my friends and family for supporting me throughout these years.
I look forward to finally have more time to spend with you all. Especially thanks to my mother for always having the time to listen, regardless of the years of her sickness while
I was abroad and for sharing her wisdom and for helping me to always find the open door.
Thanks to my father for the years of sacrifice and who have offered me unlimited encouragement and have been an enthusiastic sounding board regardless of the topic.
xx Thanks to my sisters; Kawther, Zamzam and QatruAlnada, brothers; Ali and Sultan for their support and advice. Thanks for the laughs you shared on skype and the good times.
There are more times to come!
Thanks to my incredibly patient wife Samiya, for all her efforts throughout my lengthy working sessions over the last years, running the house and taking care of our two precious daughters; Toleen and Leen, during which, she was doing her own degree. That was incredible work and unbelievable support Samiya. A special thanks to dear Toleen and Leen, for always making me smile, and for entertaining and distracting me. Thank you, pretty girls, for motivating me to keep reaching for excellence. Thank you for everything that you are, and everything you will become.
xxi Publications arising from this thesis
Al-Habsi, K., Yang, R., Williams, A., Miller, D., Ryan, U., Jacobson, C., 2017. Zoonotic
Cryptosporidium and Giardia shedding by captured rangeland goats. Veterinary
Parasitology: Regional Studies and Reports. 7, 32–35.
Al-Habsi, K., Yang, R., Ryan, U., Miller, D., Jacobson, C., 2017. Morphological and
molecular characterization of three Eimeria species from captured rangeland goats
in Western Australia. Veterinary Parasitology: Regional Studies and Reports. 9,
75–83.
Al-Habsi K., Yang, R., Ryan, U., Jacobson, C., Miller, D.W., 2017. Morphological and
molecular characterization of an uninucleated cyst-producing Entamoeba spp. in
captured Rangeland goats in Western Australia. Veterinary Parasitology. 235,
41–46.
Al-Habsi, K., Yang, R., Abraham, S., Miller, D., Ryan, U., Jacobson, C., 2017. Molecular
characterisation of Salmonella enterica serovar Typhimurium and Campylobacter
jejuni faecal carriage by captured rangeland goats. Small Ruminant Research. 158,
48–53.
Al-Habsi, K., Jordan, D., Harb, A., Laird, T., Yang, R., O'Dea, M., Jacobson, C., Miller,
D.W., Ryan, U., Abraham, S., 2017. Salmonella enterica isolates from Western
Australian rangeland goats remain susceptible to critically important
antimicrobials. Submitted: Scientific Reports.
xxii xxiii Poster presentations of work contained within this thesis
Al-Habsi, K., Yang, R., Williams, A., Miller, D., Ryan, U., Jacobson. Molecular
characterisation of enteric pathogens in captured rangeland goats. Poster Day
at Murdoch University, 31 October 2014, Murdoch, Western Australia.
Al-Habsi, K., Yang, R., Williams, A., Miller, D., Ryan, U., Jacobson. Morphological
and molecular characterization of an uninucleated cyst-producing Entamoeba
spp. in captured Rangeland goats in Western Australia. 27th Annual Combined
Biological Sciences Meeting. 25th August 2017. University of Western
Australia, Perth, Western Australia, Australia.
Al-Habsi, K., Yang, R., Williams, A., Miller, D., Ryan, U., Jacobson. Morphological and
molecular characterization of an uninucleated cyst-producing Entamoeba spp. in
captured rangeland goats in Western Australia. Australian Society for
Parasitology Conference, 26–29 June 2017. Leura, New South Wales, Australia.
Al-Habsi, K., Yang, R., Williams, A., Miller, D., Ryan, U., Jacobson. Molecular
characterisation of selected protozoal pathogens in rangeland goats in Western
Australia. First Australia-China Conference on Science, Technology and
Innovation (ACCSTI2017), 2–6 February 2017. University of Western Australia,
Perth, Western Australia, Australia.
xxiv Symbols and Abbreviations
Symbols
~ approximately = equals > greater than < less than
- negative + positive % percent x times
Abbreviations
µg microgram µL microlitre AMC amoxicillin-clavulanate acid AMP ampicillin AMR antimicrobial resistance APVMA Australian Pesticides and Veterinary Medicines Authority AZI azithromycin bg β-giardin BHI brain heart infusion BPW buffered peptone water BRM Beaufort River Meats bp base pair C° Celcius centigrade CDC Centers for Disease Control and Prevention CEF cefoxitin CFT ceftiofur CHL chloramphenicol
xxv CI confidence interval CIP ciprofloxacin CLSI Clinical and Laboratory Standards Institute COI mitochondrial cytochrome oxidase I CTX ceftriaxone dH2O distilled water DFA direct fluorescent antibody DNA deoxyribonucleic acid dNTP deoxynucleoside triphosphate ECOFFs epidemiological cutoff values EDTA ethylenediamine-tetraacetic acid, tri potassium salt e.g. exempli gratia – for example ELISA enzyme-linked immunosorbent assay et al and others EUCAST European Committee on Antimicrobial Susceptibility Testing FAMACHA FAffa Malan CHArt g unit of gravitational field g gram gdh glutamate dehydrogenase GEN gentamicin GIN gastrointestinal nematodes gp60 60 kDa glycoprotein h hour hipO hippuricase gene IFA indirect fluorescent-antibody IFAT immunofluorescence antibody test IMS immuno-magnetic separation invA invasion A gene
K2Cr2O7 potassium dichromate KCI potassium chloride kg kilogram km kilometer LOG logarithm
xxvi M molar concentration MALDI-TOF matrix assisted laser desorption/ionization time- of-flight MDR multidrug resistance mg milligram
MgCl2 magnesium chloride MIC minimum inhibitory concentration min minute ML maximum likelihood mL millilitre MLA Meat & Livestock Australia MLG multilocus genotype mM milli molar mm millimetre MP maximum parsimony ompF outer membrane protein n number N/A not available NaCl sodium chloride NAL nalidixic acid ng nanograms NJ neighbor joining nM nano molar NO nitric oxidase OR odds ratio PBS phosphate-buffered-saline PCR polymerase chain reaction pH negative logarithm of the hydrogen ion concentration pM pico molar qPCR quantitative polymerase chain reaction RAPD random amplified polymorphic DNA rDNA ribosomal deoxyribonucleic acid RFLP PCR-restriction fragment length polymorphism RNA ribonucleic acid
xxvii rRNA ribosomal ribonucleic acid RV rappaport-vassiliadis S1-S4 four sampling occasions SABC State Agricultural Biotechnology Centre SD standard deviation SDS sodium dodecyl sulfate SE standard error sp. unknown species sp. n novel species spp. several species SPSS Statistics Package for Social Studies STR streptomycin Syn. synonym Taq Thermus aquaticus deoxyribonucleic acid polymerase TE Tris & EDTA TET tetracycline Tm melting temperature tpi triose phosphate isomerase TRI trimethoprim-sulfamethoxazole U/µL universal units per microlitre v/v conentration: volume/volume % WA Western Australia WEC worm egg count WGS whole genome sequencing WHO World Health Organisation w/v weight per volume χ2 Pearson’s chi-square XLD xylose lysine deoxycholate
xxviii CHAPTER 1. LITERATURE REVIEW
1.1. Introduction
The Australian goat meat industry has experienced strong growth over the past 20 years and this growth has been largely supported by the sale of captured goats derived from rangeland or extensive production systems. Of the 2.13 million goats slaughtered in
2014, approximately 90% were rangeland goats, which were worth $241.8 million (Meat and Livestock Australia, 2015). Rangeland goats are a composite and feral breed of goat which has become naturalised throughout Australia’s rangelands. They are opportunistically captured and relocated to goat depots for partial domestication, for the domestic and export meat markets. Scouring (diarrhoea) and ill-thrift are major issues in rangeland goats when they are captured and kept in intensive conditions prior to slaughter
(Meat and Livestock Australia, 2016), yet relatively little is known about the cause.
Currently there is very little information on the diversity of enteric pathogens in rangeland goats. This literature review describes and discusses the main enteric pathogens that are possible causative agents for scouring and ill-thrift in Australian rangeland goats, along with current methods of diagnosis and control.
1.2. Cryptosporidium
Cryptosporidium spp. belonging to the genus Cryptosporidium are enteric protozoan parasites that cause diarrhoeal illness in humans and animals worldwide (Xiao,
2010). Clinical effects of Cryptosporidium infection, which include diarrhoea, weight loss and often death in lambs and goat kids, may negatively impact livestock productivity
(Casemore et al., 1997; Fayer et al., 1997; de Graaf et al., 1999). However, there is little evidence demonstrating severe impacts on livestock in Australia.
29 Infection with Cryptosporidium is initiated when the cyst is ingested with contaminated water or feed, and transmission is usually via the direct faecal-oral route.
Cryptosporidium oocysts excreted in the faeces are fully sporulated and infectious, and it is thought that transmission to goat kids occurs via infected maternal faeces (Vieira et al.,
1997; Johnson et al., 1999; Weese et al., 2000; Sevinç et al., 2005). In sheep, it has been shown that periparturient shedding of oocysts due to the stress of lambing is the mechanism for the initiation of Cryptosporidium infection in lambs (Ye et al., 2013).
1.2.1. Taxonomy of Cryptosporidium
Cryptosporidium is part of the phylum Apicomplexa and, until recently, belonged to the family Cryptosporidiidae, suborder Eimeriorina and order Eucoccidiorida (which includes Toxoplasma, Cyclospora, Isospora and Sarcocystis) (Levine, 1984; Carey et al.,
2004; Smith et al., 2005). However, molecular and biological studies have shown that
Cryptosporidium is more closely related to a primitive apicomplexan group of parasites known as the gregarines, rather than to coccidians (Carreno et al., 1999; Hijjawi et al.,
2002; Leander et al., 2003; Rosales et al., 2005; Smith et al., 2005; Barta and Thompson,
2006; Ryan et al., 2016a). Molecular studies looking at the 18S rRNA and β-tubulin loci have shown that Cryptosporidium and gregarines form a distinct clade separate from other apicomplexan groups, including coccidians (Morrison and Ellis, 1997; Carreno et al.,
1998; Leander et al., 2003). Evidence of extracellular gregarine-like gamont stages in the lifecycle of Cryptosporidium, and the ability of the parasite to complete its life cycle in host cell-free media also support the theory that Cryptosporidium is related to gregarines
(Hijjawi et al., 2002; Rosales et al., 2005; Hijjawi, 2010). More recently Cryptosporidium has been formally transferred from the Coccidia, to a new subclass, Cryptogregaria, with gregarine parasites (Cavalier-Smith, 2014).
30 To date a total of 34 species of Cryptosporidium have been identified (Table 1.1), of which eight species (C. xiaoi, C. parvum, C. ubiquitum, C. andersoni, C. hominis, C. bovis, C. suis, and C. scrofarum) have been reported in ruminants with six species (C. hominis, C. xiaoi, C. parvum C. ubiquitum and C. andersoni and C. bovis like genotypes) reported in goats. World-wide, C. hominis and C. parvum are responsible for the majority of clinical infections in humans (Xiao, 2010). There are also over 40 Cryptosporidium genotypes, with a high probability that many of these will eventually be given species status with increased molecular characterisation.
Table 1.1. Valid Cryptosporidium species confirmed by molecular analysis.
Species name Major host(s) Reported Reported in Reference(s) in goats Australia C. xiaoi Sheep & goats Yes Yes Fayer and Santin (2009); Zahedi et al. (2017a) C. parvum Ruminants Yes Yes Tyzzer (1912)
C. ubiquitum Ruminants, Yes Yes Fayer et al. (2010) rodents, primates C. andersoni Cattle Yes Yes Lindsay et al. (2000)
C. bovis Cattle Yes* Yes Fayer et al. (2005)
C. ryanae Cattle No Fayer et al. (2008) C. hominis Humans Yes Yes Morgan-Ryan et al. (2002) C. meleagridis Birds & Yes Yes Slavin (1955) humans C. viatorum Humans No No Elwin et al. (2012)
C. scrofarum Pigs No Yes Kváč et al. (2013)
C. suis Pigs No Yes Ryan et al. (2004)
C. canis Dogs No Yes Fayer et al. (2001)
31 Species name Major host(s) Reported Reported in Reference(s) in goats Australia C. felis Cats No Yes Iseki et al. (1989)
C. erinacei Hedgehogs, No No Kváč et al. (2014) horses C. muris Rodents No Yes Tyzzer, (1907); Tyzzer (1910) C. proliferans Rodents No No Kváč et al. (2016)
C. tyzzeri Rodents No Yes Tyzzer (1912); Ren et al. (2012) C. homai Guinea pigs No Yes Zahedi et al. (2017a)
C. wrairi Guinea pigs No Yes Vetterling et al. (1971)
C. cuniculus Rabbits No Yes Robinson et al. (2010)
C. rubeyi Squirrels No No Li et al. (2015)
C. fayeri Marsupials No Yes Ryan et al. (2008)
C. macropodum Marsupials No Yes Power and Ryan (2008) C. avium Birds No No Holubova et al. (2016)
C. baileyi Birds No Yes Current et al. (1986)
C. galli Birds No Yes Pavlásek (1999); Ryan et al. (2003) C. fragile Toads No No Jirků et al. (2008)
C. varanii Lizards No No Pavlasek et al. (1995)
C. serpentis Snakes & No Yes Levine (1980) lizards C. ducismarci Tortoises No No Traversa (2010); Jezkova et al. (2016) C. testudinis Tortoises No No Jezkova et al. (2016)
C. huwi Fish No Yes Ryan et al. (2015); Holubova et al. (2016)
32 Species name Major host(s) Reported Reported in Reference(s) in goats Australia C. molnari Fish No Yes Alvarez-Pellitero and Sitja-Bobadilla (2002); Kvac et al. (2016) C. scophthalmi Turbot No No Alvarez-Pellitero et al. (2004); Costa et al. (2016); Li et al. (2015) *Cryptosporidium bovis like genotype has been reported in goats (Karanis et al., 2007).
Understanding the transmission dynamics of Cryptosporidium has traditionally been difficult because most species of Cryptosporidium are morphologically identical
(Fall et al., 2003). Therefore, molecular characterisation tools such as the polymerase chain reaction (PCR) and DNA-sequence analysis are required to reliably differentiate/ identify species and genotypes of Cryptosporidium. To date, C. parvum, C. hominis, C. meleagridis and C. xiaoi have been identified in goats using molecular tools (Giles et al.,
2009; Robertson 2009; Díaz et al., 2010; Fayer et al., 2010; Silverlås et al., 2012; Koinari et al., 2014; Peng et al., 2016). Except for one study that identified C. parvum in a goat kid in Australia (Morgan et al., 1998), no other studies have utilised molecular tools to identify species/genotypes of Cryptosporidium infecting Australian goats.
1.2.2. Life cycle of Cryptosporidium
The life cycle of Cryptosporidium consists of three alternating phases of development: merogony (asexual), gametogony (sexual), and sporogony (asexual)
(Leander et al., 2003; Leander, 2007) resulting in infective sporulated oocysts, which are excreted from the body of an infected host in the faeces (Harris and Petry, 1999; Fayer et al., 2000) (Fig. 1.1). Infection begins with the ingestion of oocysts and once inside the body, the oocysts excyst, releasing infective sporozoites which attach to the epithelial cells of the small intestine and mature into trophozoites (Current and Reese, 1986; Tzipori
33 and Widmer, 2000). Trophozoites then undergo asexual proliferation by merogony into two types of meronts; type I meronts which form 8 merozoites and type II meronts which form 4 merozoites, which produce sexual reproductive stages (called gamonts) (Barta and
Thompson, 2006). Type I merozoites can cause autoinfection by attaching to epithelial cells or can develop into a type II meront, which initiates sexual multiplication (Chen et al., 2002). Type II merozoites attach to the epithelial cells, where they become either macrogamonts or microgamonts (Chen et al., 2002). Microgamonts develop into microgametocytes which produce up to 16 non-flagellated microgametes, while macrogamonts develop into uninucleate macrogametocytes which are fertilized by mature microgametes (sexual reproduction) (Hijjawi et al., 2004; Barta and Thompson,
2006). The resultant zygotes undergo further asexual development (sporogony) leading to the production of sporulated oocysts containing 4 oocysts (Barta and Thompson, 2006).
While most oocysts are thick-walled and are excreted in the faecal material, some are thin-walled and have been reported to encyst within the same host animal. These auto- infective oocysts and recycling type I meronts are believed to be the means by which persistent chronic infections may develop in hosts without further exposure to exogenous oocysts (Barta and Thompson, 2006). The entire life cycle may be completed in 2 days in many hosts and infections may be short-lived or may persist for several months
(O'Donoghue, 1995). The prepatent period (time between infection and oocyst excretion) ranges from 2 to 14 days.
34
Figure 1.1. Diagrammatic representation of the Cryptosporidium life cycle (taken from Barta and Thompson, 2006).
1.2.3. Prevalence of Cryptosporidium in goats
Cryptosporidium has a worldwide distribution. Much of the research on the prevalence of Cryptosporidium infections in farm animals has been conducted in cattle and sheep and there is relatively little information on the occurrence of cryptosporidiosis in goats. In Australia, cryptosporidiosis was confirmed by histological examination as the cause of death in an Angoran kid goat (Mason et al., 1981) and two cases of human outbreaks with C. parvum due to consumption of unpasteurised goats milk have been reported (Australian Food Industries Science Centre, 1998). An outbreak of diarrhoea in
1 to 2-week-old goats prompted the first characterisation of C. parvum in Australian goats
(Morgan et al., 1998). Studies which have reported the prevalence and/or outbreaks of cryptosporidiosis in goats are described in Appendix 1.
35 1.2.4. Host immune response to Cryptosporidium
Infection of ruminants with Cryptosporidium generally occurs very early in life, at a time when it is difficult for the newborn animals to eliminate the infection, due to immunological immaturity. Both complex innate and adaptive immune response mechanisms are involved in clearing Cryptosporidium infections (Petry et al., 2010).
CD4+ T lymphocytes and Th-1 immune responses play a key role in acquired immunity against cryptosporidiosis, but CD8+ T lymphocytes and dendritic cells contribute to the clearance of the parasite from the intestine (Pantenburg et al., 2008; Ryan et al., 2016b).
Very little is known about the immune response of goats to Cryptosporidium infection but protection of goat kids against C. parvum infection after immunization of dams with a 15 kDa surface sporozoite protein of C. parvum has been reported (Sagodira et al.,
1999).
1.2.5. Pathogenesis of Cryptosporidium
Disease resulting from infection with Cryptosporidium is believed to be associated with destruction of the epithelial layer (Pantenburg et al., 2008), causing inflammation and loss of fluid and increasing susceptibility to other enteric pathogens (de
Graaf et al., 1999; Lefay et al., 2001). Severe intestinal lesions, villous atrophy, fusion, blunting and inflammatory infiltrations in the lamina propria have been reported in infected goat kids (Koudela and Jirí, 1997; Johnson et al., 2000).
The main reported clinical sign of cryptosporidiosis in goats is diarrhoea accompanied by the shedding of a large number of oocysts (de Graaf et al., 1999). High morbidity and mortality have been reported in goat kids and lambs, especially neonates
(Fayer and Ungar, 1986; de Graaf et al., 1999). In sheep, Cryptosporidium has been associated reduced liveweight and reduced carcass weight, and reduced carcass dressing percentage at slaughter (Jacobson et al., 2016).
36 1.2.6. Diagnosis of Cryptosporidium
A variety of laboratory tests have been developed for the diagnosis of cryptosporidiosis. These include microscopic and immunologic (enzyme-linked immunosorbent assay (ELISA) detection of the parasite in the faeces. However, these methods lack sensitivity and specificity (Smith, 2008; Khurana et al., 2012).
The use of molecular techniques including nested PCR and quantitative PCR
(qPCR) for identification of Cryptosporidium species/genotypes offers advantages over
ELISA and conventional flotation methods for sensitivity and specificity. qPCR assays have been developed for enumeration and detection of Cryptosporidium in faeces and water and have been shown to have greater specificity, sensitivity and reproducibility than traditional diagnostic methods (Yang et al., 2013). The 18S ribosomal RNA (rRNA) gene and the hypervariable 60-kDa glycoprotein (gp60) gene have been widely used as targets to identify species and track transmission respectively (Xiao, 2010).
1.2.7. Treatment of Cryptosporidiosis
Only one drug, nitazoxanide (NTZ, Alinia; Romark Laboratories, Tampa, Florida,
United States), has been approved by the United States (US) Food and Drug
Administration (FDA) for treatment of Cryptosporidium in humans. This drug, however, exhibits only moderate clinical efficacy in malnourished children and immunocompetent people, and none in immunocompromised individuals like people with HIV (Ryan et al.,
2016b). In cattle, a drug combination of metronidazole and furazolidone were reported to have some success against cryptosporidiosis (Randhawa et al., 2012). Azithromycin, halofugione, decoquinate and paromomycin have been used to treat calves and neonatal goats, experimentally, or naturally infected with C. parvum under field conditions, with varying success (Naciri and Yvoré, 1989; Redman and Fox, 1993; Chartier et al., 1996;
Mancassola et al., 1997; Johnson et al., 2000; Trotz-Williams et al., 2011; Nasir et al.,
37 2013; Petermann et al., 2014). A product containing activated charcoal and wood vinegar liquid (Obionekk®) has been reported to reduce oocyst excretion and clinical signs of scouring in neonatal goat kids under field conditions (Paraud et al., 2011) and in experimentally infected calves (Watarai et al., 2008).
Due to the lack of effective treatments, strict sanitation and quarantine of sick animals is essential for the control of cryptosporidiosis in farm animals. Supportive care, primarily hydration is also important (Aurich et al., 1990; Hunt et al., 2002).
1.3. Giardia
Giardiasis is the infection caused by the binucleated flagellated protozoan parasite, Giardia, which inhabits the mucosal surface of the small intestine of its hosts.
Currently, seven Giardia spp. are accepted by most researchers on the basis of the morphology of trophozoites and/or cysts and genetic characterisation; Giardia agilis in amphibians, Giardia ardeae and Giardia psittaci in birds, Giardia microti and Giardia muris in rodents, G. peramelis in Australian bandicoots (Isoodon obesulus) and G. duodenalis in mammals (Ryan and Cacciò, 2013; Hillman et al., 2016).
Clinical manifestations of giardiasis are quite variable and range from the absence of symptoms to acute or chronic diarrhoea, malabsorption, weight loss, nausea, vomiting and occasionally death of affected hosts (Olson et al., 1995a; Olson et al., 2004; Ryan et al., 2005). It has also been associated with reduced weight gain, impaired feed efficiency and reduced carcass weight and carcass dressing percentage in domestic ruminants (Olson et al., 1995b; Jacobson et al., 2016). Infection, in goats, can lead to severe diarrhoeal illness and losses in neonatal kids with occasional mortalities (Castro-Hermida et al.,
2005). However, infected animals are more commonly asymptomatic (Xiao, 1994;
O'Handley et al., 1999).
38 Giardia duodenalis (syn. G. intestinalis, G. lamblia), the only species found in mammals is composed of at least eight distinct genetic assemblages (A to H) (Ryan and
Cacciò, 2013; Table 1.2). Of these, assemblage E, which mainly infects ruminants, assemblages A and B and assemblage C have been reported in goats (see Table 1.2; section 1.3.2; Appendix 2). Assemblages A and B are the predominant assemblages in humans and exhibit a broad host range including cattle, sheep, pigs, horses, non-human primates, dogs, cats and fish (Feng and Xiao, 2011; Ryan and Cacciò, 2013; Yang et al.,
2010a; Ghoneim et al., 2012; Durigan et al., 2014).
39 Table 1.2. Giardia duodenalis assemblages.
Assemblage Host Range Reported Reported References in goats in Australia Assemblage A Humans, nonhuman primates, domestic Yes Yes Thompson and Monis (2004); Dixon et al. (2008); and wild ruminants, alpacas, pigs, horses, Lasek-Nesselquist et al. (2008); Thompson et al. domestic & wild canines, cats, ferrets, (2008); Monis et al. (2009); Yang et al. (2010a); rodents, marsupials, seals, fish Ghoneim et al. (2012); Durigan et al. (2014) Assemblage B Humans, nonhuman primates, cattle, Yes Yes Thompson and Monis (2004); Thompson et al. dogs, horses, rabbits, beavers, muskrats, (2008); Monis et al. (2009); Yang et al. (2010b) fish Assemblage C Domestic and wild canines, goats, Yes Yes Thompson and Monis (2004); Thompson et al. humans (2008); Monis et al. (2009), Ng et al. (2011); Liu et al. (2014); Minetti et al. (2014); Štrkolcová et al. (2015) Assemblage D Domestic & wild canines, humans No Yes Thompson and Monis (2004); Thompson et al. (2008); Monis et al. (2009; Broglia et al. (2013)
40 Assemblage Host Range Reported Reported References in goats in Australia Assemblage E Domestic ruminants, pigs, humans Yes Yes Thompson and Monis (2004); Foronda et al. (2008); Thompson et al. (2008); Monis et al. (2009); Helmy et al. (2014); Abdel-Moein and Saeed (2016); Fantinatti et al. (2016); Peng et al. (2016); Scalia et al. (2016); Zahedi et al. (2017b) Assemblage F Cats, humans No Yes Thompson and Monis, 2004; Gelanew et al. (2007); Thompson et al. (2008); Monis et al. (2009) Assemblage G Mice, rats No No Thompson and Monis (2004); Thompson et al. (2008); Monis et al. (2009) Assemblage H Seals No No Lasek-Nesselquist et al. (2010)
41 1.3.1. Life cycle of Giardia
The life cycle of G. duodenalis is characterised as simple and direct and involves just two major stages; the relatively fragile motile feeding trophozoite stage and the environmentally resistant, infective cyst stage (Fig. 1.2) (Kirkpatrick and Farrell, 1982;
Ortega and Adam, 1997). Infection is initiated either by consumption of contaminated food or water or by the faecal-oral route via person-to-person or animal-to-animal contact.
Exposure to the acidic environment of the stomach provides the necessary stimuli for the excystation of the trophozoite from the cyst in the duodenum of the small intestine
(Gardner and Hill, 2001). Trophozoites undergo repeated mitotic division and encystation, which is the process of forming environmentally resistant cysts, that is triggered in response to the bile conditions of the small intestine. Cysts are immediately infectious when excreted in faeces, and are remarkably stable and can survive for weeks to months in the environment (Ryan and Cacciò, 2013).
Figure 1.2. The life cycle of G. duodenalis (taken from Ankarklev et al., 2010).
42 1.3.2. Prevalence of Giardia in livestock and goats
Animals can harbour both zoonotic and host-specific G. duodenalis assemblages that are morphologically identical. Therefore, sensitive typing tools are required to track transmission (Feng and Xiao, 2011). Most livestock are infected with the largely host- specific assemblage E (livestock genotype), but assemblage A is increasingly being reported (Ryan and Cacciò, 2013). Young ruminants have a higher incidence of giardiasis compared to adults, and the intensity of cyst shedding was reported to be higher in young calves, lambs and kids (Xaio et al., 1994; Mockber, 1995; Saeed, 1998; Geurden et al.,
2008a; Ruiz et al., 2008). A recent multicentre trial, which examined Giardia in cattle in
Germany, UK, France and Italy, identified an overall prevalence of 45.4% (942/2072), of which 43% was identified as assemblage A (Geurden et al., 2012). In Western Australian dairy calves, a prevalence of 58% was reported (O'Handley et al., 1999) and an overall prevalence of 11.1% was reported in pre-weaned sheep in Western Australia (Yang et al.,
2009).
Little is known of the prevalence and assemblages of Giardia in goats, with prevelances varying considerably due to the animal’s age, breed and the diagnostic methods used. As discussed above, assemblage E is most common in goats but assembalges A and B (Geurden et al., 2008b; Berrilli et al., 2012; Zhang et al., 2012; Lim et al., 2013; Di Cristanziano et al., 2014; Tzanidakis et al., 2014; Appendix 2) and assemblage C (Ng et al., 2011; Minetti et al., 2014) have been reported.
Assemblage E was thought to be non-zoonotic, however it has recently been found in humans, including Australian humans and therefore it is now considered to be potentially zoonotic (Foronda et al., 2008; Abdel-Moein and Saeed, 2016; Fantinatti et al., 2016; Scalia et al., 2016; Zahedi et al., 2017b). Nothing is known about the prevalence and economic effects of giardiasis in rangeland goats in Australia.
43 1.3.3. Pathogenesis of Giardia
Attachment of Giardia trophozoites to enterocytes triggers a poorly understood intracellular cascade, resulting in osmotic changes, diarrhoea, and other clinical signs of giardiasis (Esch and Petersen, 2013). In goats experimentally infected with Giardia cysts, severe lesions were seen in the duodenum and proximal jejunum consisting of moderate villus atrophy, villus blunting, crypt hyperplasia and inflammatory infiltration in the lamina propria (Koudela and Vítovec, 1998).
1.3.4. Host immune response to Giardia
The actual host defense mechanisms responsible for controlling Giardia infections are poorly understood but are thought to involve both adaptive immune responses as well as innate mechanisms (Solaymani-Mohammadi and Singer, 2010).
Effector mechanisms for killing the parasite include phagocytosis by macrophages, secretion of defensins, nitric oxide (NO) and mucins by epithelial cells as well as the recruitment and activation of mucosal mast cells have been proposed (Eckmann, 2003).
1.3.5. Diagnosis of Giardia
Giardiasis can be diagnosed by microscopy, ELISA and immunochromatographic tests, however these methodologies lack sensitivity and specificity (Monis et al., 2005;
Haque et al., 2007; Payne and Artzer, 2009; Stark et al., 2011). Molecular methods for identifying Giardia assemblages from faecal and water samples have been developed, which are more sensitive and specific, and provide information about the possible sources of infection (Cacciò and Ryan, 2008; Yang et al., 2009; Yang et al., 2010a; 2010b;
Thompson and Monis, 2012; Ryan and Cacciò, 2013; Lim et al., 2013). The most widely used loci include the 18S ribosomal RNA (rRNA), the glutamate dehydrogenase (gdh) and triose-phosphate isomerase (tpi) loci (Monis et al., 1999), or genes uniquely associated with the parasite such as ß-giardin (Lalle et al., 2005a; 2005b).
44 1.3.6. Treatment of Giardia
In humans, there are several anti-giardial drugs, of which the most used are 5- nitroimidazole compounds such as metronidazole. No drug is currently licensed for treating giardiasis in ruminants, but the benzimidazoles, fenbendazole and albendazole, have significant efficacy against giardiasis in calves (O'Handley et al., 1997; 2001; 2006).
Unfortunately, treatment alone is insufficient for controlling G. duodenalis infections in ruminants because reinfection occurs rapidly (O'Handley et al., 1997; 2001; 2006;
Escobedo and Cimerman, 2007). Continual daily administration of a drug is likely to be required to keep ruminants free of the parasite, but such a treatment regimen is not practical (O'Handley et al., 1997; 2001; 2006; Escobedo and Cimerman, 2007). Limiting environmental contamination (water and soil) with the cysts from infected hosts is important for reducing infection rates in livestock (Olson and Buret, 2001; Geurden et al., 2006; Maddox-Hyttel et al., 2006; Uehlinger et al., 2006).
A Giardia vaccine is commercially available for the prevention of clinical signs of giardiasis and reduction of cyst shedding in dogs and cats (GiardiaVax™, Fort Dodge
Animal Health, Overland Park, Kansas, USA). As the vaccine is a mixture of lyophilized trophozoites of assemblages A and B, but not F, C, D and E, variation in protection have been widely reported (Olson et al., 1996; Olson et al., 1997; Olson and Buret, 2001; Stein et al., 2003; Anderson et al., 2004; Uehlinger et al., 2007). A vaccine for livestock is not available.
1.4. Eimeria
Coccidiosis of goats is a widespread infection caused by the protozoan parasite,
Eimeria, which develops in the small and the large intestine and affects young animals in particular (Chartier and Paraud, 2012). Although often asymptomatic in goats, coccidiosis can be a serious economic enteric disease, resulting in diarrhoea, poor weight gain, and
45 occasional death (Chartier and Paraud, 2012; Sharif et al., 2015), particularly in young or stressed goats under poor management conditions (Craig, 1986; Jalila et al., 1998; Georgi and Georgi, 1990; Smith and Sherman, 1994; Gül, 2007).
1.4.1. Taxonomy of Eimeria
Historically, Eimeria have been classified based on their phenotypic characteristics, such as morphology, ultrastructure, life cycle and host specificity (Smith and Sherman, 1994; Duszynski et al., 2000). However, the morphological similarity of oocysts, the broad host specificity of some Eimeria spp., and the diversity of Eimeria spp. within one host, complicate species delimitation (Tenter et al., 2002; Haug et al., 2007).
Molecular data are therefore essential to accurately delimit species. A total of 17 Eimeria species have been described worldwide in goats (Table 1.3), amongst which E. ninakohlyakimovae and E. arloingi are considered the most pathogenic species (Levine
1985; Alyousif et al., 1992; Gül, 2007; Wang et al., 2010; Cavalcante et al., 2012;
Chartier and Paraud, 2012). Sheep and goats harbour their own species of Eimeria and to date cross-infections have not been reported (McDougald, 1979; Bakunzi et al., 2010).
46 Table 1.3. Eimeria species reported in goats worldwide.
Eimeria species Oocyst Site of Pathogenicity References size infection (µm) E. alijevi* 17 x 15 small & large low Shah and Joshi intestines (1963) E. aspheronica* 31 x 23 unknown low Lima (1980) E. arloingi* 28 x 19 small & large high Chevalier (1966) intestines E. caprina* 34 x 23 small & large moderate Lima (1979) intestines E. caprovina* 30 x 24 unknown low Lima (1980) E. christenseni* 38 x 25 small high Levine et al. (1962) intestine E. hirci* 21 x 16 unknown moderate Chevalier (1966) E. jolchijevi* 31 x 22 unknown low Lima (1980) E. 21 x 15 small & large high Yakimoff and ninakohlyakimovae* intestines Rastegaieff (1930) E. kocharli 45 x 37 unknown moderate Vercruysse (1982) E. marisca 19 x 13 unknown moderate Soe and Pomroy (1992) E. masseyensis 22 x 17 unknown unknown Soe and Pomroy (1992) E. minasensis 35 x unknown unkown Silva and Lima 4.5 (1998) E. palitda* 16 x 12 unknown unknown Shah and Joshi (1963) E. punctata 26 x 20 unknown unknown Chevalier (1966) E. sundarbanensis 28 x 20 unknown unknown Bandyopadhyay (2004) E. tunisiensis 33 x 22 unknown unknown Chevalier (1966) *Eimeria species reported in domestic and wild goats in Australia.
47 1.4.2. Life cycle of Eimeria
The life cycle of Eimeria species is homoxenous requiring only one host (Fig.
1.3). It includes an exogenous phase of maturation of the oocyst (sporogony), which occurs outside the host, and a parasitic endogenous phase within the host with an asexual followed by a sexual multiplication (McQueary et al., 1977; Mesfin et al., 1978; Lal et al., 2009). The oocysts passed with the faeces are not sporulated. Sporulated oocysts are formed after 2–7 days according to the species of Eimeria and the environmental conditions; moisture, oxygen and temperature are particularly important.
48
Figure 1.3. Life cycle of Eimeria species. (1) Schematic representation of the life cycle of Eimeria in an infected mammal. (2) Illustration of a fully-formed (sporulated) oocyst. (adapted from Sam-Yellowe, 1996; Lindsay and Tood, 1993; Entzeroth et al., 1998).
49 1.4.3. Prevalence of Eimeria in goats
Reported prevalences for Eimeria in goats vary widely across countries with prevalences ranging from 38% to 100% (Lima, 1980), and significantly higher prevalences in goat kids compared to adult goats (Taylor and Catchpole, 1994; Woji et al., 1994; Koudela and Boková 1998; Wang et al., 2010).
Ten Eimeria species have been reported from domestic and wild goats in
Australia, based on microscopic examination of faeces; E. ninakohlyakimovae, E. arloingi (considered homologous with ovine E. bakuensis), E. hirci (considered homologous with ovine E. crandallis), E. christenseni (considered homologous with ovine E. ahsata), E. alijevi, E. caprina, E. caprovina, E. jolchijevi, E. apsheronica and E. paltida (Kanyari, 1988; O'Callaghan, 1989).
1.4.4. Pathogenesis of Eimeria in goats
Clinical caprine coccidiosis is usually seen in goats aged between three weeks to five months of age (Smith and Sherman, 1994). However, cases of clinical infection have been reported in adult goats (Georgi and Georgi, 1990; Jalila et al., 1998). Clinical signs include profuse watery diarrhoea, weight loss and dehydration (Foreyt et al., 1986; Woji et al., 1994; Cox, 1998; Markovics et al., 2012). Severe bloody diarrhoea has also been reported in young goats with heavy Eimeria infections (Abo-Shehada and Abo-Farieha,
2003).
Relatively little is known about histopathological lesions resulting from Eimeria infections in goats. Gross lesions in the jejunum and ileum, thickening of the jejunal mucosa and hyperplasia of the villi and crypt epithelial cells have been reported in goats
(Kanyari, 1990; Dai et al., 1991; Mahmoud et al., 1994; Nourani et al., 2006; Oruc, 2007;
Hashemnia et al., 2011; Hashemnia et al., 2012).
50 1.4.5. Host immune response to Eimeria
Relatively little is known about the immune response to Eimeria in goats. Studies conducted in cattle indicate that mainly T-cell responses are involved (Yun et al., 2000;
Ruiz et al., 2013). Goat kids immunised with live attenuated E. ninakohlyakimovae oocysts were shown to excrete significantly less oocysts in the faeces (95.3% reduction) and experienced ameliorated clinical coccidiosis, compared to control kids infected with non-attenuated oocysts (Ruiz et al., 2013).
1.4.6. Diagnosis of coccidiosis
Traditionally, identification of Eimeria species is made on the basis of the morphological characterisation of the oocysts. Commerical immuno-diagnostic kits are also available; however, both methods (microscopy and immuno-assays) are time consuming and exhibit less specificity and sensitivity than molecular methods (Barta et al., 1997; Faber et al., 2002; Carvalho et al., 2011a; Gibson-Kueh et al., 2011). The development of DNA-based molecular methods has allowed sensitive and accurate species differentiation of Eimeria (Barta et al., 1997; Kaya et al., 2007; Carvalho et al.,
2011a; Carvalho et al., 2011b; Khodakaram-Tafti et al., 2013).
1.4.7. Treatment of Eimeria
Control of caprine coccidiosis is currently based on management practices combined with specific anticoccidial drugs including Toltrazuril, Clindamycine,
Quinolone, Decoquinate, Amprolium, Diclazuril and Artemisia absinthium (Foreyt et al.,
1986; Tauseef et al., 2011; Temizel et al., 2011; Ruiz et al., 2012; Iqbal et al., 2013; Ruiz et al., 2013). However, the extensive use of drugs has caused the emergence of new drug- resistant Eimeria spp. strains worldwide (Peek and Landman, 2005). These drugs are not licenced for goats in Australia.
51 1.5. Entamoeba
Eukaryotic organisms of the genus Entamoeba have adapted to live as parasites or commensals in the digestive tract of humans and other mammals, amphibians, fish, reptiles, and some invertebrates (Clark, 1995; Stensvold et al., 2010; Hooshyar et al.,
2015). Species within the genus are assigned to either non, uni, quadri or octo-nucleated cyst-producing morphological groups (Stensvold et al., 2010): 1) species without cysts
(E. gingivalis-like group), 2) species with uninucleated cysts (E. bovis-like group), 3) species with quadrinucleated cysts (E. histolytica-like group) and 4) octonucleated cysts
(E. coli- like group). Several species of Entamoeba are found in humans and animals, with the quadrinucleate E. histolytica of medical importance and responsible for invasive
'amoebiasis' (which includes amoebic dysentery, colitis, severe ulceration and amoebic liver abscesses) and diarrhoea in humans worldwide (WHO, 1997; Haque et al., 2003;
Zhang et al., 2015).
Uninucleated cyst-producing Entamoeba have been isolated from a range of hosts including humans, non-human primates and other mammals (monogastrics and birds)
(Noble and Noble, 1952; Das and Ray, 1968; Wittnich, 1976; Shimada et al., 1992;
Pakandl, 1994; Verweij et al., 2001; Stedman et al., 2003; Adejinmi and Osayomi, 2010).
Ruminants such as cattle, buffaloes and sheep are common hosts of uninucleate cyst- producing Entamoeba (Noble and Noble, 1952; Jacob et al., 1990; el-Refaii, 1993;
Skirnisson and Hansson, 2006; Kanyari et al., 2009; Stensvold et al., 2010; Stensvold et al., 2011, Jacob et al., 2016).
1.5.1. Prevalence of Entamoeba
Little is known about the prevalence of Entamoeba in goats, but Entamoeba species (mostly unidentified) have been reported in goats in Kenya (87%) (Kanyari et al.,
2009), Thailand (71.23%) (Sangvaranond et al., 2010), Egypt (71.5%) (Omar, 1979),
52 Tanzania (3.2%) (Mhoma et al., 2011), Cameroon (13.7%) (Ntonifor et al., 2013) and
Brazil (1.8%) (Radavelli et al., 2014). Nothing is known about the prevalence of
Entamoeba in rangeland goats in Australia.
1.5.2. Pathogenesis and host immune response to Entamoeba
The majority of research conducted to date has been on E. histolytica. In most cases, the parasite colonises the colon by high affinity binding to MUC2 mucin without disease symptoms, whereas in some cases the parasite triggers an aggressive inflammatory response upon invasion of the colonic mucosa. The specific host-parasite factors critical for disease pathogenesis are still not well characterised (Begum et al.,
2015). The host mounts an ineffective and excessive host pro-inflammatory response following contact with host cells, that causes tissue damage and participates in disease pathogenesis. Entamoeba can modulate or destroy effector immune cells by inducing neutrophil apoptosis and suppressing nitric oxide (NO) production from macrophages.
Entamoeba adherence to the host cells also induces multiple cytotoxic effects, that can promote cell death through phagocytosis, apoptosis or by trogocytosis (ingestion of living cells) that might play critical roles in immune evasion (Begum et al., 2015). No vaccine is commercially available. The pathogenesis and immune response of Entamoeba infection in farm animals, including goats, is poorly understood.
1.5.3. Diagnosis of Entamoeba
Until recently, the detection, identification and assignment of Entamoeba organisms to species relied mainly on morphology and the host in which parasites were identified (Stensvold et al., 2010; Stensvold et al., 2011). However, morphology is not a reliable tool for delimiting Entamoeba species as cyst morphology varies substantially within as well as between uninucleated cyst-producing species from different ruminant hosts (Noble and Noble, 1952; Pillai and Kain, 1999; Stensvold et al., 2010). The use of
53 molecular tools has dramatically improved the identification, taxonomy, epidemiology and clinical significance of Entamoeba species without reliance on parasite cultures or experimental infections (Stensvold et al., 2011; Jacob et al., 2016).
1.5.4. Treatment of Entamoeba
Drug therapies such as metronidazole and other nitroimidazole-derived compounds have been reported to be effective in treating Entamoeba invasive species in a human study (Quach et al., 2014), and in a calf with clinical infection caused by E. bovis
(Jacob et al., 1990). However, these drugs display unfavourable side effects in humans
(Löfmark al., 2010). Control strategies for Entamoeba infection in goats requires an understanding of the epidemiology and transmission dynamics.
1.6. Gastrointestinal nematodes (GIN)
Due to their ubiquitous distribution and high prevalence, infections with gastrointestinal nematodes (GIN) are of major economic importance in goat farming
(Hoste et al., 2010; Zanzani et al., 2014). The GIN with greatest economic impacts worldwide include the Barber’s Pole worm (Haemonchus contortus) and Teladorsagia circumcincta (formerly Ostertagia circumcincta), which are parasites of the abomasum, and Trichostrongylus spp. in the small intestine. The major clinical signs associated with
GIN in goats include anaemia, diarrhoea, poor growth rates, poor reproductive performance and deaths, with specific impacts dependent on the type of infection
(species) and infection intensity (Rahman and Collins, 1990; Kaplan et al., 2004; Zajac,
2006; Zanzani et al., 2014).
1.6.1. Life cycle
The same life cycle generally applies to all of the economically important trichostrongylid parasites of goats and sheep (Fig. 1.4). In this simple cycle, adult females
54 in the abomasum or intestines produce eggs that are passed in the faeces (dung stage).
Development occurs within the faecal mass, which provides some protection from environmental conditions. A first-stage larva is formed that hatches out of the egg. After hatching, larvae feed on bacteria and undergo two moults to reach the infective third larval stage (L3) (pasture stage). Third-stage larvae make their way out of the faecal material and onto the forage where they can be ingested by the host animal (host stage).
Figure 1.4. Generalised life cycle of GIN’s (adapted from Sheep CRC, 2017; Available: http://www.wormboss.com.au/worms/roundworms/roundworm-life-cycle.php; Last Accessed 12 September 2017).
55 1.6.2. Prevalence of GIN’s in goats
Limited work has been carried out to elucidate the epidemiology of gastrointestinal nematodes in Australian goats, however McGregor et al. (2014) reported
Trichostrongylus spp. and Nematodirus in Angora goats grazed with Merion sheep in southern Australia. The most common species reported for goats in the arid and semi-arid regions of Australia were Haemonchous contortus, and Trichostrongylus spp. (Beveridge et al., 1987). The intensity of infection in sheep and goats is more related to the rainfall in these regions and to the time of year with T. colubriformis, T. vitrinus, T. rugatus and
T. axei as the dominant Trichostrongylus spp. (Beveridge and Ford 1982; Beveridge et al., 1987). In sheep and goats, T. colubriformis, T. vitrines and T. rugatus are small intestinal nematodes; however, T. axei remain in the abomasum (Tongson et al., 1981;
Akkaya 1998). Both Haemonchus contortus and Trichostrongylus spp. have been previously reported in rangeland goats in arid regions of Australia (Beveridge et al.,
1987), and are considered important nematodes in livestock (Cole, 1986).
In Austalian regions with substantial winter rainfall, Teladorsagia circumcincta is one of the most common strongylid worm species affecting sheep (Besier and Love,
2003; Woodgate and Besier, 2010), however this my not be the case with rangeland goats, which are sourced from remote arid and semi-arid regions where conditions are generally not conducive to survival of this parasite.
1.6.3. Pathogenesis and immune response
The most specific indication of haemonchosis is anaemia, seen as pallour of the mucous membranes, especially easily seen in the conjunctivae, and varying from the normal, red-pink colour to extreme white in terminal situations. Affected animals become progressively weaker with increasing blood loss and are less inclined to move and may spend more time lying down than usual (Besier et al., 2016). Diarrhoea is not usual,
56 although haemonchosis can occur concurrently with infections with other nematodes that cause the clinical signs.
The primary consequences of Trichostrongylus spp. and T. circumcincta infections are severe small intestine lesions, villous atrophy and epithelial erosion, which impaires the digestion and absorption of nutrients, causing diarrhoea and significant loss in performance (Roy et al., 1996; Roy et al., 2004; Cardia et al., 2011).
Several studies have illustrated that both the acquisition and the expression of immune responses against nematode species are less efficient in goats than in sheep
(review: Hoste et al., 2010). For example, the acquisition of a fully expressed immune response appears delayed in goats (i.e. 12 months compared with 6 months in sheep). In addition, when grazing, a strong regulation of egg excretion has been described in flocks of adult sheep. Conversely, in goats, a trend for the accumulation of parasites, correlated with higher and constantly increasing egg excretion has generally been found over the whole grazing period. Finally, the ability of goats to control challenge infections is much lower than that of sheep, and that the ‘immune memory’ after drug treatment does not last as long (review: Hoste et al., 2010).
1.6.4. Diagnosis of GINs
Traditional methods for enumeration and identification of GIN’s are based on worm egg counts (WEC) (Whitlock, 1948). Identification to genus or species however requires larval culture, because most species of strongylid nematodes are morphologically indistinguishable at a low magnification (review: Gasser et al., 2008). Larval culture assays can suffer from a lack of reliability, reproducibility and sensitivity, and identification and results can vary considerably depending on the culture conditions
(temperature and relative humidity), leading to a bias when apportioning numbers of eggs or larvae to nematode species or genera (Lichtenfels et al., 1997; Taylor et al., 2002).
57 More recently, PCR methods have been developed which have improved the detection and identification of GIN’s, even when present at low levels (Gasser, 2006;
Yong et al., 2007; Bott et al., 2009; Learmount et al., 2009; Beech et al., 2011; Sweeny et al., 2012a; McNally et al., 2013; Bisset et al., 2014; Önder et al., 2016).
1.6.5. Treatment of GINs
The widespread use of anthelmintics and consequent development of anthelmintic resistance has negatively impacted on the control of GINs in grazing/browsing sheep and goats (Elliot, 1987; Hernández-Villegas et al., 2012), despite the development of a new drug, monepantel (Kaminsky et al., 2008). The successful management of GIN infections relies on the early recognition of risk situations, the periodic monitoring of worm burdens, and preventative programmes which include grazing management and nonchemical measures, in addition to anthelmintic treatments (Besier et al., 2016).
The use of bioactive plants with anthelmintic properties, especially tannin-rich plants, has been proposed as an alternative and/or complement to the control of GINs in sheep and goats to avoid or delay the development of anthelmintic-resistant nematode strains, thereby reducing the dependence on chemical anthelmintic treatments (Min et al.,
2003; Waller and Thamsborg, 2004; Hoste et al., 2006). Recently, a number of reports have been published on the anthelmintic effects of tannin-rich plants and forages in small ruminants (Osoro et al., 2009; Terrill et al., 2009; Celaya et al., 2010; Landau et al.,
2010), with reduced establishment of L3 larvae or worm fertility and egg output in goats
(Min et al., 2005; Hoste et al., 2006; Paolini et al., 2005; Moreno-Gonzalo et al., 2013).
1.7. Salmonella and Campylobacter
Salmonella enterica and Campylobacter spp. occur naturally in the gut of sheep and goats as commensals, and are often asymptomatic in carrier animals (Duffy et al.,
58 2009). However, S. enterica and Campylobacter spp. (C. jejuni and C. coli) can cause acute gastroenteritis, characterised by diarrhoea and weight loss in goats and sheep, particularly when they are subjected to sustained periods of stress (McOrist and Miller
1981).
As Salmonella and Campylobacter are also human pathogens, there are also public health risks associated with faecal carriage and subsequent contamination of carcasses at abattoirs (Duffy et al., 2009; Woldemariam et al., 2009) and through contamination of milk and surface waters (Davies et al., 2004; Garcia et al., 2010).
There are more than 2,500 serovars of S. enterica (Grimont and Weill, 2007), all of which are potentially pathogenic for humans (Bopp et al., 1999) and each with a different host range and disease manifestation (Coburn et al., 2007). Salmonella enterica serotype Typhimurium (S. Typhimurium) is a typical broad-host-range pathogen, which is among the serotypes most frequently associated with disease in humans as well as cattle, pigs, horses, poultry, rodents, and sheep (Sojka et al., 1983; Coburn et al., 2007).
Salmonella in cattle and sheep has been intensively studied, however there is little published information on Salmonella in goats. In an Australian outbreak of acute diarrhoea and deaths due to salmonellosis in a group of 1,016 feral goats of varying ages, four serovars were isolated; S. Adelaide, S. Typhimurium, S. Muenchen and S. Singapore
(McOrist and Miller, 1981).
1.7.1. Prevalence of Salmonella and Campylobacter sp. and serotypes
Contamination with Salmonella and Campylobacter at abattoirs occurs when hygienic standards are not maintained. For example, Salmonella and Campylobacter were recovered from 29% and 7%, respectively, of goat carcasses at abattoirs suggesting possible carcass contamination during processing (Duffy et al., 2009; Woldemariam et al., 2009). In the Australian study by Duffy et al. (2009), Salmonella was also identified
59 in 46% (n=56) of faecal samples and 46% (n=55) of rumen samples. The dominant serotypes isolated were Salmonella Saintpaul (31%), Salmonella Typhimurium (13%) and Salmonella Chester (11%) (Duffy et al., 2009). Other Australian studies have reported that 6% of Australian sheep carcasses and frozen sheep meat were positive for
Salmonella (Adams et al., 1997; Vanderlinde et al., 1999).
1.7.2. Immune response of caprine hosts to Salmonella and Campylobacter
The basis for immunity against Salmonella and Campylobacter infection in small ruminants is not fully understood, particularly in caprine species, but research indicates that the immune response of neonatal goats is not adapted to cope with the bacterial infection during the first few weeks of age (Johnson et al., 2010).
In ovine species, both humoral and cellular immunity play an important role in protection against Salmonella infection (Mastroeni et al, 1993). Humoral IgM, IgG1 antibodies and traces of IgG2 were detected in ovine species under in vitro conditions
(Berthon et al., 1994). For Campylobacter, the involvement of IgG antibodies in host defense in experimentally challenged sheep with C. fetus has been demonstrated
(Grogono-Thomas et al., 2003) and increased interleukin IL-6 and IL-15 were reported in ewes with C. jejuni-induced abortion (Sanad et al., 2014).
1.7.3. Pathogenesis of Salmonella and Campylobacter
Little research has been conducted in this area concerning goats. Otesile et al.
(1990) reported pyrexia, diarrhoea (khaki-coloured, containing mucus or blood flecks) and neutrophilia in goats experimentally infected with Salmonella Typhimurium. The significant pathophysiological consequences of Campylobacter infections include decreased absorption in the colon resulting from a disruption to the microvilli, and exudative superficial erosive colitis. The mechanism by which Campylobacter causes this
60 is by attachment to the wall of the gastrointestinal tract and subsequent release of toxins
(enterotoxins and/or cytotoxins) (Glastonbury, 1990; Olson et al., 2008).
1.7.4. Diagnosis of Salmonella
Salmonella and Campylobacter can be detected using microscopy, culture and immunoassays; however, these methods can lack specificity and are time-consuming
(Pawlowski et al., 2009). Conventional methods are also problematic due to fastidious growth requirements, and the fact that selective enrichment stages are necessary to detect low levels of these organisms by culture methods, and this prevents the original bacterial count in the samples from being estimated (Maciel et al., 2011). Additionally, both
Salmonella and Campylobacter may enter into a viable but non-culturable state (VBNC)
(Alexandrino et al., 2004; Murphy et al., 2006; Panutdaporn et al., 2006; Passerat et al.,
2009; Kusumoto et al., 2013).
More recently, PCR assays have been developed which have demonstrated enhanced detection of Salmonella and Campylobacter (Abubakar et al., 2007; Al Amri et al., 2007; Postollec et al., 2011; Barbau-Piednoir et al., 2013). Molecular methods have yet to be routinely applied to the detection and characterisation of Salmonella and
Campylobacter in goats.
1.7.5. Prevention and Treatment of Salmonella and Campylobacter
To reduce the spread of Salmonella and Campylobacter infection, affected animals are usually isolated from the rest of the flock to stop the spread of infection to other animals (Bulgin and Anderson, 1981). However, frequently by the time salmonellosis is detected, it has often already spread widely throughout the flock.
Treatment of animals with clinical symptoms associated with Salmonella infection usually consists of antibiotic and fluid therapy and other various treatments aimed at alleviating the symptoms associated with gastroenteritis and septicemia caused by the
61 bacterium. Abdulgafar et al. (2011) reported the effectiveness of ceftriaxone (a third- generation cephalosporin) in treating goats with S. typhimurium infection by inhibiting the bacterial cell wall synthesis. Traditionally, antibiotics such as erythromycin have been the drug of choice for treating C. jejuni enteritis (Nachamkin et al., 2002) with oral replacement of fluids and electrolytes (Skirrow and Blaster, 2000). However, Sahin et al.
(2008) reported tetracycline-resistant C. jejuni in sheep. A commercial vaccine for
Salmonella and Campylobacter infection is not available.
1.7.6. Antimicrobial resistance
Antibiotic resistance is a global threat. All antimicrobial use creates selection pressure on microorganisms whether provided to humans, animals, or the environment.
Controversy continues concerning antimicrobial use in food animals and its relationship to drug-resistant infections in humans (McCrackin et al., 2016; Helke et al., 2017). Drug resistance in S. enterica and Campylobacter spp. is mediated by numerous mechanisms.
They may become resistant to antimicrobials by modifying or inactivating the antimicrobial agent, modifying the antimicrobial target, the action of the efflux pumps, or cell membrane permeability (McCrackin et al., 2016; Helke et al., 2017). Laboratory- based surveillance for antimicrobial resistance (AMR) is essential to generate reliable data on the occurrence of AMR in different geographical regions and provide a platform for future interventions.
Laboratory-confirmed Campylobacter isolates exhibiting 42% resistance to tetracyclines, 22% to quinolones and 2% to macrolides have been reported (CDC, 2015).
These drug classes have been in past or current use in food animal production in United
States for one or more of the following purposes: growth promotion, disease prevention, treatment or control. Quinolones and macrolides are categorized by the World Health
Organization as critically important antimicrobials for use in human medicine (CDC,
62 2015), so there is concern about the resistance of Campylobacter to these drug classes and whether their use in food animal production may contribute to resistance. By contrast, fluoroquinolones were never approved for use in Australian food animals.
The emergence of multidrug-resistant (MDR) forms of S. enterica in food- producing animals is a substantial threat to human and animal health, especially when it involves serovars with a propensity to cause severe clinical disease in humans (Abraham et al., 2014). Examples of MDR S. enterica serovars with elevated virulence for humans that have recently emerged in animals include: serovar Newport in the USA; serovar
Heidelberg in Canada; and serovar Kentucky in Egypt and Africa (Le Hello et al., 2013;
Abraham et al., 2014; Tadesse et al., 2016). Treatement of MDR S. enterica serovars is particularly problematic when they posess AmpC and/or extended-spectrum β-lactamase- producing genes and concurrent fluoroquinolone resistance (Abraham et al., 2014).
Australia's unique geography, quarantine restrictions and predominance of extensive livestock systems, act to prevent the entry of exotic MDR S. enterica serovars and subsequent colonisation of food animals. In addition, Australia is the only country never to have permitted the use of fluoroquinolones and gentamicin in food-producing animals (Cheng et al., 2012). Very little is known about MDR S. enterica serovars in livestock in Australia and nothing is known about goats. A recent study of S. enterica (n
=165) isolated from livestock in New South Wales, Australia reported that most isolates
(66%) remained susceptible to all antimicrobials tested (n=18), but 8% of the isolates were resistant to four or more antimicrobials. Antimicrobials with the highest prevalence of resistance were sulfafurazole (28%), ampicillin (17%), tetracycline (16%) and trimethoprim (8%). There was no resistance to fluoroquinolones or third-generation cephalosporins (Abraham et al., 2014). This contrasts with international studies where the prevalence of resistance to these drugs has steadily risen in S. enterica serovars isolated from food animals, in some cases to >25% of isolates from a particular host
63 species (Hur et al., 2012). As rangeland goatmeat accounts for approximately 90% of all exported Australian goatmeat, determining the extent of MDR S. enterica serovars in rangeland goats going through Australian abattoirs is a pressing need.
1.8. Aims and Objectives
This literature review highlighted that knowledge gaps exist for the causes of diarrhoea and ill thrift in captured rangeland goats, and that a number of enteric pathogens could be responsible that also have public health significance. Molecular tools may offer some advantages in the characterising faecal shedding of pathogens by goats. With this in mind, the aims of this project are to:
1. Establish whether molecular tools have utility for diagnosis of Cryptosporidium,
Giardia, Eimeria, Entamoeba, trichostrongylid worms, Salmonella and
Campylobacter faecal carriage in goat faecal samples.
2. Determine whether enteric pathogens are associated with diarrhoea or reduced
growth rate in captured rangeland goats.
3. Determine the public health risks associated with faecal carriage of bacteria and
protozoan parasites by rangeland goats following capture and at slaughter.
The general hypothesis for this thesis is that molecular tools will demonstrate faecal carriage of enteric pathogens associated with diarrhoea and reduced growth in captured rangeland goats, and with zoonotic potential. This project will, for the first time, provide information on the occurance of selected enteric pathogens in captured rangeland goats using molecular tools and provide evidence on the prevalence of Salmonella antimicrobial resistance in rangeland goatmeat, which is essential information for formulating appropriate recommendations for management of rangeland goats for meat production.
64
65 CHAPTER 2. MATERIALS AND METHODS
2.1. Animal ethics
All sample collection methods used were approved by the Murdoch University
Animal Ethics Committee (approval number R2617/13). All goats were managed according to the Code of Practice for Goats in Western Australia (Department of Local
Government and Regional Development Western Australia, 2003).
2.2. Animals and faecal samples collection at feedlot (depot)
The rangeland goats (n=125) were captured from a sheep and cattle extensive rangeland grazing property (North Wooramel station), located 78 km east of Denham and
113 km south east of Carnarvon in the Gascoyne region of Western Australia. Goats were transported by road to a commercial goat depot near Geraldton, Western Australia.
On arrival at the goat depot, the goats weighed on average 30.7 ± 0.3 kg (±SEM).
The estimated age of the goats, based on dentition, was between 9 – 12 months. All goats were male. Goats were housed outdoors in four group pens (30-33 goats per pen) for the duration of the study. Commercial grain-based pellets, hay and water were supplied ad libitum. Straw-bedding was provided with bare dirt covering the majority of available pen space. No pasture was available for the duration of the study.
Faecal samples were collected once monthly for four months (S1 to S4) by rectal palpation. The first faecal sample collection occurred on arrival at the goat depot. Faecal samples were immediately placed on ice until transported to the lab and then stored at
4°C until DNA extraction was performed.
66
Figure 2.1. Captured and transported rangeland goats at the commercial feedlot (depot) near Geraldton, Western Australia. Photo provided by David W. Miller, Murdoch University.
2.3. Diarrhoea and Production Measurements
Breech faecal score (dag score), faecal consistency score (FCS), live weight, body condition score (BCS) and other related clinical signs for each animal were recorded at each sampling occasion (S1-S4).
2.3.1. Breech faecal score (dag score)
Breech faecal soiling score was measured at each sampling occasion (S1-S4) using a scale of 1 (no evidence of breech fleece faecal soiling) to 5 (very severe breech faecal soiling extending down the hind legs to, or below the hocks) as used for sheep as shown in Fig. 2.2 (Australian Wool Innovation, 2007).
67
Figure 2.2. Graphical representation of the breech fleece faecal soiling scale (Australian Wool Innovation et al., 2007).
2.3.2. Faecal consistency score
Faecal consistency score was measured at each sampling occasion (S1-S4) using a scale of 1 (hard, dry pellet) to 5 (liquid/fluid diarrhoea) previously described (Greeff and Karlsson, 1997; Table 2.1).
Table 2.1. Criteria used in assessment of faecal consistency score (FCS).
Faecal consistency score Faecal consistency description
1 Hard, dry pellet, cracks when placed under firm pressure between finger and thumb 2 Soft, moist pellet, less tendency to crack when placed under firm pressure between finger and thumb 3 Soft faecal mass, loss of pellet structure 4 Soft paste, pasty diarrhoea 5 Liquid/fluid
68 2.3.3. Live weight and body condition score
Rangeland goats were weighed at each sampling occasion, live weight was recorded to the nearest 100 g and body condition score was measured by manual palpitation of the lumber region using a scale that ranged from 1 (very thin, emaciated) to 5 (very fat) (Sutherland et al., 2010).
2.4. Anthelmintic treatment
All goats were treated with an anthelmintic, 0.4 mg/kg moxidectin (Cydectin oral plus selenium®, Virbac Australia), and an anti-coccidial treatment (20 mg/kg toltrazuril,
Baycox®, Bayer Australia) immediately after the first (S1) and second (S2) sampling as part of the standard management practice for goats being introduced to the feedlot.
2.5. Faecal worm egg counts
All faecal worm egg counts were performed in the State Agriculture
Biotechnology Centre (SABC), Murdoch University, using a modified McMaster technique as reported in the Australian Standard Diagnostic Techniques for Animal
Diseases Manual (Whitlock, 1948; Lyndal-Murphy, 1993). For this technique, approximately, 2 g of faeces were weighed and placed in a 60 mL mixing jar and 2.5 mL of tap water was added to soften the faecal pellets. The faeces were mashed up using a pair of forceps and allowed to soak for more than 1 h. A flotation salt solution (saturated sodium chloride solution with specific gravity 1.20 – 1.25) was added to the sample to make a final volume of 50 mL solution. The faecal suspension was mixed vigorously using a tongue depressor until a homogenous solution was obtained. Using a pipette, 0.6 mL of solution was drawn out from the center of the mixed faecal suspension and added to the counting chamber of a Whitlock Paracytometer slide. The eggs were allowed 10 minutes (maximum time) to float up under the glass before counting at 40x magnification
69 using a light microscope (Olympus BH-2) as shown in Figure 2.3. All visible eggs within the double line boundaries of the Whitlock Paracytometer counting chamber were counted.
Figure 2.3. Faecal worm egg counts at 40x magnification.
2.6. DNA isolation from faecal samples
Genomic DNA was extracted directly from faeces using a PowerSoil® DNA isolation kit (MO BIO laboratories, Carlsbad, California, USA) according to the manufacturer’s protocol. The kit is designed to remove faecal PCR inhibitors, which potentially increases the DNA quality. Approximately, 0.2 grams of each faecal sample were placed in a Powerbead tube and then mixed by vortexing. To ensure complete lysis of any pathogen that may have been present, five freeze thaw cycles were conducted, which consisted of dipping the sample into liquid nitrogen for approximately 10 seconds until frozen and then incubating at 95 °C until thawed. Sixty microliters of solution C1 were then added to the Powerbead tubes containing the sample and the mixture was again mixed by vortexing. The Powerbead tube was secured horizontally onto a flat-bed vortex pad with tape and vortexed at maximum speed for 10 minutes and then centrifuged at
70 10,000 x g for 30 seconds at room temperature. The supernatant was then transferred to a clean 2 mL collection tube. To this, 250 μL of solution C2 were added and the contents were mixed by vortexing for 5 seconds and incubated at 4 °C for 5 minutes. After incubation, the tube was centrifuged at room temperature for 1 minute at 10,000 x g and approximately 600 μL of supernatant was transferred to a clean 2 mL collection tube and
200 μL of solution C3 were added to it. The tubes were vortexed briefly and incubated at
4 °C for 5 minutes. Following incubation, the tubes were centrifuged at room temperature for 1 minute at 10,000 x g. Up to 750 μL of supernatant were collected into a clean 2 mL collection tube and 1,200 μL of solution C4 were added to the supernatant. The solutions were mixed by vortexing for 5 seconds.
Approximately, 675 μL of the supernatant mixture were loaded onto a spin filter, which captures the DNA. The tube was centrifuged at 10,000 x g for 1 minute at room temperature. The flow-through was discarded. An additional 675 μL of supernatant mixture was loaded onto the spin filter and the process was repeated until all the remaining supernatant was loaded onto the spin filter and centrifuged. This was followed by the addition of 500 μL of solution C5 (ethanol wash solution) to rinse the captured
DNA by centrifugation at room temperature for 30 seconds at 10, 000 x g. The flow- through was discarded. The spin filter tubes were centrifuged again and the spin filter was placed in a clean 2 mL collection tube. To concentrate the DNA, 50 μL of solution C6
(sterile DNA elution buffer) (instead of the recommended 100 μL) was then added to the centre of the white filter membrane of the spin filter, and the tube was centrifuged at room temperature for 30 seconds at 10, 000 x g to elute the DNA. The spin filter was discarded and the tube containing the DNA was stored at -20 °C. Graphical representation of the
Power Soil DNA isolation kit methodology is illustrated in Appendix 3.
71 2.7. Molecular detection and quantification of selected enteric pathogens by quantitative PCR (qPCR)
Previously developed quantitative PCR (qPCR) assays were conducted on a
Rotor-Gene6000 Cycler (Qiagen, Hilden, Germany) following protocols previously described (Harmon et al., 2007; 2014a; 2014b, 2014c; 2014d; Ryan, 2016). Primers and probes for Cryptosporidium, Giardia, Eimeria, Salmonella, Campylobacter,
Haemonchus and Trichostrongylus using a quantitative PCR (qPCR) were used (see sections from 2.7.1 to 2.7.5). The specificity and sensitivities of these assays have been previously reported (Harmon et al., 2007; Yang et al., 2014a; 2014b; 2014c; 2014d; Ryan,
2016).
The following qPCR protocol and thermocycling conditions were used for all assays. The total reaction volume in these assays was 15 μL. The reaction mixture contained 5 mM MgCl2, 1 mM deoxynucleotide triphosphates (dNTP’s), 1x PCR buffer,
1.0 U Kapa DNA polymerase (Kapa Biosystems, Cape Town, South Africa). 0.2 μM each of forward and reverse primers, 0.2 μM each of forward and reverse internal amplification control (IAC) primers, 50 nM of the probe, 50 nM of internal amplification control (IAC) probe, 10 copies of IAC template and 1 μL of sample DNA (Yang et al., 2014d). The IAC consisted of a fragment of a coding region from Jembrana Disease Virus (JDV) cloned into a pGEM-T vector (Promega, USA) as previously described (Yang et al., 2013). The
IAC primers were JDVF (5′-GGT AGT GCT GAA AGA CAT T) and JDVR (5′-ATG
TAG CTT GAC CGG AAG T) and the probe was 5′-(Cy5) TGC CCG CTG CCT CAG
TAG TGC (BHQ2). The PCR cycling conditions consisted of a pre-melt at 95 °C for 3 minutes and then 45 cycles of 95 °C for 30 seconds, and a combined annealing and extension step of 60 °C for 45 seconds.
72 2.7.1. Molecular detection and quantification of Cryptosporidium by qPCR
Primers and probes for Cryptosporidium at the actin locus were used as previously described by Yang et al. (2014a). Briefly the forward primer, Allactin F1 5′-
ATCGTGAAAGAATGACWCAAATTATGTT-3′, the reverse primer Allactin R1 5′-
ACCTTCATAAATTGGAACGGTGTG-3′ and the probe 5′-(FAM)-
CCAGCAATGTATGTTAATA BHQ1-3′ which produces a 161 bp product were used.
2.7.2. Molecular detection and quantification of Giardia by qPCR
Primers and probes for Giardia at the glutamate dehydrogenase (gdh) were used as previously described by Yang et al. (2014b), using the forward primer, gdhF1 F1 5’–
GGGCAAGTCCGACAACGA–3’, the reverse primer gdhR1 5’–
GCACATCTCCTCCAGGAAGTAGAC–3’ and the probe 5’–(JOE 670) -
TCATGCGCTTCTGCCAG BHQ2–3’ which produces a 261 bp product.
2.7.3. Molecular detection and quantification of Eimeria by qPCR
Primers and probes for Eimeria at the 18S rRNA locus were used as previously described by Yang et al. (2014c), using the forward primer, Eim F1 5′–
CGAATGGCTCATTAAAACAGTTATAGTT–3′, the reverse primer Eim R1 5′–
CGCATGTATTAGCCATAGAATTACCA–3′ and the probe 5′– (JOE)-
ATGGTCTCTTCCTACATGGA BHQ1–3′ which produces an 85 bp product.
2.7.4. Molecular detection and quantification of Salmonella and Campylobacter by qPCR and specificity, sensitivity and efficiency for qPCR
Primers and probes for Salmonella were used as previously described by Yang et al. (2014c). A 96 bp product was amplified from the S. enterica outer membrane protein
(ompF) using the forward primer ompF1 5′-TCGCCGGTCGTTGTCCAT-3′, the reverse
73 primer ompR1 5′-AACCGCAAACGCAGCAGAA-3′ and the probe 5′-2′7, ′-dimeth-oxy-
4′5, ′-dichloro-6-carboxyfluorescein (JOE)-ACGTGACGACCCACGGCTTTAC-3′.
Primers and probes for Campylobacter spp. were used as previously described by
Yang et al. (2014c). A 121-base pair (bp) product was amplified from the Campylobacter spp. purine biosynthesis gene (purA) using the forward primer PurAF1 5′-
CGCCCTTATCCTCAGTAGGAAA-3′, the reverse primer purAR1 5′-
TCAGCAGGCGCTTTAACAG-3′ and the probe 5′-6-carboxyfluorescein (FAM)-
AGCTCCATTTCCCACACGCGTTGC-3′. Specificity and sensitivity analysis for qPCR for both Salmonella and Campylobacter were adapted from Yang et al., 2014d.
Evaluation demonstrated no cross-reactions with other genera; the qPCR only amplified the relevant bacterial species (Table 6.1, appendix 11).
2.7.5. Molecular detection and quantification of strongylid by qPCR
Faecal samples (n=500) were screened for Haemonchus, Teladorsagia and
Trichostrongylus and using methods previously described by Ryan (2016). The primers and probe for Haemonchus were modified from Harmon et al. (2007). The forward primer
HC-ITS F1 (5’–CATATACATGCAACGTGATGTTATGAA–3’), the reverse primer
HC-ITS R1 (5’–GCTCAGGTTGCATTATACAAATGATAAA–3’) and the probe (5’–
FAM- ATGGCGACGATGTTC-BHQ1–3’) were used to amplify 92 bp fragment of rRNA ITS1 region. To enhance base pairing and duplex stability, the oligonucleotide duplexes C-5 propynyl-dC (pdC) and C-5 propynyl-dU (pdU) were replaced by dC and dT respectively when probe was prepared. A 143 bp fragment of the Teladorsagia ITS2 region was amplified using the primers TC-ITS2 F1 (5’–
TCTGGTTCAGGGTTGTTAATGAAACTA–3’) and TC-ITS2R1 (5’–
CCGTCGTACGTCATGTTGCAT–3’) and the probe (5’– CAL Fluor Orange 560 –
TGTGGCTAACATATAACACTGTTTGTCGA- BHQ1–3’).
74
A 114 bp fragment of Trichostrongylus ITS1 region was amplified using TS ITS1
F1 (5’–AGTGGCGCCTGTGATTGTTC–3’), TS ITS1 R1 (5’–
TGCGTACTCAACCACCACTA–3’) and the probe (5’–CAL Fluor Red 610–
TGCGAAGTTCCCATCTATGATGGTTGA-BHQ2–3’).
As previously described by Yang et al. (2013a), the internal amplification control
(IAC) consisted of a fragment of a coding region from Jembrana Disease Virus (JDV) cloned into a pGEM-T vector (Promega, Madison, WI, USA). The IAC primers were
JDVF (5’–GGTAGTGCTGAAAGACATT-3’) and JDVR (5’–
ATGTAGCTTGACCGGAAGT–3’) and the probe was 5’–Cy5-
TGCCCGCTGCCTCAGTAGTGC-BHQ2–3’ (Yang et al., 2013a). Presence of PCR inhibitors were examined by adding an internal amplification control (IAC) to all extracted faecal DNA samples.
The qPCR protocol and thermocycling conditions for strongylid qPCR assays were performed as previously described (see section 2.7).
Previous specificity testing revealed no cross-reactions with other genera and only the relevant strongyle species were amplified (Ryan, 2016). Sensitivity testing demonstrated mean minimum detection for all three genera was 0.04 eggs per µL of faecal
DNA extract, equating to a minimum detection of 10 epg (Ryan, 2016). The mean amplification efficiency for the qPCR of H. contortus, Tel. circumcincta and
Trichostrongylus spp. was 107.3%, 94% and 100.5% respectively (Ryan, 2016).
75 2.8. PCR amplification and sequencing
2.8.1. Amplification of Cryptosporidium at the 18S rRNA gene
A two-step nested PCR was used to amplify the 18S rRNA gene for
Cryptosporidium, with the primary amplified product of ~763 base pairs (bp) using the forward primer 18SiCF2 (5’ – GAC ATA TCA TTC AAG TTT CTG ACC – 3’) and the reverse primer 18SiCR2 (5’ – CTG AAG GAG TAA GGA ACA ACC – 3’) (Ryan et al.,
2003). The PCR mixture consisted of 400 mM of each dNTP (Fisher Biotech, Perth,
Australia), 1 x kapa Taq DNA polymerase buffer (Kapa Biosystems, Cape Town, South
Africa), 2.5 mM MgCl2 (Fisher Biotech), 0.05U/μL of kapa Taq DNA Polymerase (Kapa
Biosystems, Cape Town, South Africa) and 0.80 μM of forward and reverse primers. PCR reactions containing 1 μL of DNA were amplified in a total volume of 25 μL. Following a 5-min preliminary heating at 95oC for 5 mins, 50 PCR cycles (95oC for 30 s, 58oC for
30 s, and 72oC for 60 s) were carried out on an Applied Biosystems Gene Amp PCR
System 2700 thermocycler, with a final 7-min extension at 72oC. A positive control (C. hominis) and a negative control (no DNA added) were included in all reactions.
For the secondary PCR, a product of ~580bp was amplified using 1μL of primary
PCR product and nested forward 18SiCF1 (5’ – CCT ATC AGC TTT AGA CGG TAG
G – 3’) and reverse 18SiCR1 (5’ – TCT AAG AAT TTC ACC TCT GAC TG – 3’) primers (Ryan et al., 2003). The conditions for the secondary PCR were identical to the primary. Positive secondary PCR products were sequenced directly in both directions.
2.8.2. Subtyping of C. parvum at the 60 kDa glycoprotein (gp60)
All C. parvum positive samples were subtyped by a nested PCR amplification at the 60 kDA glycoprotein (gp60) locus as previously described (Strong et al., 2000; Peng et al., 2003a; Ng et al., 2008). A primary PCR product of ~1000bp was amplified using the forward gp60 F1 (5’ – ATA GTC TCC GCT GTA TTC– 3’) and the reverse primer
76 gp60 R1 (5’ – TCC GCT GTA TTC TCA GCC– 3’) in the primary PCR. The PCR mixture consisted of 400mM of each dNTP (Fisher Biotech, Perth, Australia), 1 x DNA polymerase buffer (Fisher Biotech, Perth, Australia), 3mM MgCl2 (Fisher Biotech, Perth,
Australia), 0.05U/μL of Tth+ Taq DNA Polymerase (Fisher Biotech, Perth, Australia) and 0.80 μM of forward and reverse primers. PCR reactions containing 1 μL of DNA were amplified in a total volume of 25μL. Following a 5-min preliminary heating at 95oC for 5 mins, 35 PCR cycles (95oC for 45 s, 58oC for 45 s, 72oC for 60 s) were carried out on an Applied Biosystems Gene Amp PCR System 2700 thermocycler, with a 10-min final extension at 72oC. A positive control (C. hominis) and negative control (no DNA added) were included for all sets of reactions.
In the secondary PCR, a fragment of ~850bp was amplified using 2 μL of primary
PCR product and forward gp60 F2 (5’ – GGA AGG AAC GAT GTA TCT – 3’) and reverse gp60 R2 (5’ – GCA GAG GAA CCA GCA TC – 3’) primers. The conditions for the secondary PCR were identical to the primary PCR. Positive secondary PCR products were sequenced directly in both directions.
2.8.3. Subtyping of C. ubiquitum at the 60 kDa glycoprotein (gp60) locus
Subtyping of C. ubiquitum was performed using a two-step nested PCR to amplify a ~ 948 bp fragment of the gp60 gene as described (Li et al., 2014). The sequences of primers used in primary and secondary PCR were 5′–
TTTACCCACACATCTGTAGCGTCG–3′ (Ubi-18S-F1) and 5′–
ACGGACGGAATGATGTATCTGA–3′ (Ubi-18S-R1), and 5′–
ATAGGTGATAATTAGTCAGTCTTTAAT–3′ (Ubi-18S-F2) and 5′–
TCCAAAAGCGGCTGAGTCAGCATC–3′ (Ubi-18S-R2), which amplified an expected
PCR product of 1,044 and 948 bp, respectively. The partial C. ubiquitum gp60 gene was amplified by nested PCR in a total volume of 50 μL, containing 1 μL of DNA (primary
77 PCR) or 2 μL of the primary PCR product (secondary PCR), primers at a concentration of 0.25 µM (Ubi-18S-F1 and Ubi-18S-R1) or 0.5 µM (Ubi-18S-F2 and Ubi-18S-R2), 0.2
µM dNTP mix (Promega, Madison, WI, USA), 3 µM MgCl2 (Promega), 1 × GeneAmp
PCR buffer (Applied Biosystems, Foster City, CA, USA), and 1.25 U of Taq DNA polymerase (Promega). The primary PCR reactions also contained 400 ng/μL non- acetylated bovine serum albumin (Sigma, St. Louis, MO, USA) to reduce PCR inhibition.
PCR amplification consisted of an initial denaturation at 94°C for 5 min; 35 cycles at
94°C for 45 s, 45 s at 58°C (primary PCR) or at 55°C (secondary PCR), 1 min at 72°C; and a final extension for 7 min at 72°C. A positive control and negative control (no DNA added) were included for all sets of reactions.
2.8.4. Amplification of Giardia spp. at the glutamate dehydrogenase (gdh) locus
A semi-nested PCR was used to screen for Giardia at the gdh gene, which amplified a product of ~480bp, using the external forward primer GDHeF (5’ – TCA
ACG TYA AYC GYG GYT TCC GT – 3’), internal forward primer GDHiF (5’ – CAG
TAC AAC TCY GCT CTC GG – 3’) and the reverse primer GDHiR (5’ – GTT RTC
CTT GCA CAT CTC C – 3’) (Read et al., 2004). Primers contained degenerate bases
(“Y”) to enable amplification of isolates across all assemblages. The total reaction volume for this assay was 25 μL, which contained 1 μL of genomic DNA, 1.5 mM MgCl2, 200
μM of each dNTP, 12.5 pmol each of forward and reverse primers, 1 x Kapa Taq buffer and 0.05 U/μL of Kapa Taq DNA polymerase (Kapa Biosystems, Cape Town, South
Africa). Following a 5-min preliminary heating at 95oC for 5 mins, 50 PCR cycles (95oC for 30 s, 56oC for 30 s, 72oC for 50 s) were carried out on an Applied Biosystems Gene
Amp PCR System 2700 thermocycler, with a final 7-min extension at 72oC. A positive control (G. duodenalis assemblage A) and a negative control (no DNA added) was included in all reactions.
78 2.8.5. Amplification of Giardia spp. at the β-giardin (bg) locus
A semi-nested PCR was used to type Giardia gdh positives at the β–giardin (bg) locus, which produced a primary amplified product of ~753bp using the forward G7 (5’
– AAG CCC GAC GAC CTC ACC CGC AGT GC – 3’) and reverse G759 (5’ – GAG
GCC GCC CTG GAT CTT CGA GAC GAC – 3’) primers (Cacciò et al., 2002; Lalle et al., 2005). The PCR mixture consisted of 400mM of each dNTP (Fisher Biotech, Perth,
Australia), 1 x Kapa Taq DNA polymerase buffer (Kapa Biosystems, Cape Town, South
Africa), 2.5 mM MgCl2 (Fisher Biotech, Perth, Australia), 0.05U/μL of kapa Taq DNA
Polymerase (Kapa Biosystems, Cape Town, South Africa) and 0.80 μM of both forward and reverse primers. PCR reactions containing 1 μL of DNA were amplified in a total volume of 25 μL. Following a 5-min preliminary heating at 95oC for 5 mins, 50 PCR cycles (95oC for 30 s, 65oC for 30 s, 72oC for 60 s) were carried out on an Applied
Biosystems Gene Amp PCR System 2700 thermocycler, with a final 7-min extension at
72oC. A positive control (G. duodenalis assemblage A) and a negative control (no DNA added) were included in all reactions.
In the secondary PCR, a fragment of ~384bp was amplified using 1 μL of primary
PCR product and forward G376 (5’ – GGA AGG AAC GAT GTA TCT – 3’) and reverse
G759 (Cacciò et al., 2002; Lalle et al., 2005). The conditions for the secondary PCR were identical to those of the primary PCR, except that an annealing temperature of 55oC was used, instead of 65oC. Positive secondary PCR products were sequenced directly in the reverse direction.
2.8.6. Amplification of Giardia spp. at the triose phosphate isomerase (tpi) locus
All Giardia isolates positive at the gdh locus were typed using an assemblage specific amplification nested PCR of the triosephosphate isomerise (tpi) gene. The primary PCR amplified a PCR product of ~605bp, using the external forward primer
79 AL3543 (5’ – AAA TIA TGC CTG CTC GTC G – 3’) and the reverse primer AL3546
(5’ – GTT RTC CTT GCA CAT CTC C – 3’) (Geurden et al., 2008a). The PCR mixture consisted of 400 mM of each dNTP (Fisher Biotech, Perth, Australia), 1 x DNA polymerase buffer (Fisher Biotech, Perth, Australia), 2.5 mM MgCl2 (Fisher Biotech,
Perth, Australia), 0.05U/μL of Tth+ Taq DNA Polymerase (Fisher Biotech, Perth,
Australia) and 0.80 μM of forward and reverse primers. PCR reactions containing 2.5 μL of DNA were amplified in a total volume of 25 μL. Following a 5-min preliminary heating at 94oC, 40 PCR cycles (94oC for 45 s, 56oC for 45 s, 72oC for 60 s) were carried out on an Applied Biosystems Gene Amp PCR System 2700 thermocycler, with a final 10-min extension at 72oC.
Each Giardia positive, was screened with two assemblage specific secondary
PCRs, using a 1 in 10 dilutions of the first round PCR as a template. The first PCR assay was for assemblage A, with assemblage A specific forward primer Af (5’ – CGC CGT
ACA CCT GTC A – 3’) and reverse primer (5’ – AGC AAT GAC AAC CTC CTT CC –
3’) amplifying ~332bp PCR product (Geurden et al., 2008a; Geurden et al., 2009). The second assemblage E-specific PCR used the specific forward primer Ef (5’ – CCC CTT
CTG CCG TAC ATT TAT – 3’) and the reverse primer Er (5’ – GGC TCG TAA GCA
ATA ACG ACT T – 3’) amplifying a ~388bp PCR product (Geurden et al., 2008a;
Geurden et al., 2009). The reaction mixture for the secondary assemblage-specific tpi
PCR consisted of 400 mM of each dNTP (Fisher Biotech, Perth, Australia), BSA at a final concentration of 0.1 μg/μL 1 x DNA polymerase buffer (Fisher Biotech, Perth, Australia),
2.5 mM MgCl2 (Fisher Biotech, Perth, Australia), 0.05U/μL of Tth+ Taq DNA
Polymerase (Fisher Biotech, Perth, Australia) and 0.80 μM of forward and reverse primers. PCR reactions containing 2.5μL of diluted template DNA were amplified in a total volume of 25 μL. Following a 10-min preliminary heating at 94oC, 40 PCR cycles
(94oC for 45 s, 64oC for 45 s for assemblage A specific primers or 67oC for assemblage
80 E specific primers, 72oC for 60 s) were carried out on an Applied Biosystems Gene Amp
PCR System 2700 thermocycler, with a final 10-min extension at 72oC. A positive control
(G. duodenalis assemblage A) and a negative control (no DNA added) were included in all reactions.
2.8.7. Amplification of Entamoeba at the 18S rRNA locus
Samples that were positive for Entamoeba by microscopy were examined by PCR using the eukaryotic 18S primers RD5 (5–ATCTGGTTGATCCTGCCAGT–3) and RD3
(5– ATCCTTCCGCAGGTTCACCTAC–3) as previously described (Clark et al., 2006).
An approx. 1,950 bp PCR product was amplified, which was initially sequenced with the
RD5 or RD3 primers in both directions. Based on the partial sequences obtained, a set of new Entamoeba specific primers ENF2 (5–AAGCATGGGACAATATCGAGG) and
ENR2 (5– GTCCCTTTAAGAAGTGATGC) were designed to conduct sequence walking to obtain the full-length sequence of the 1,950 bp PCR product. The primers were designed using Primer3 (http://bioinfo.ut.ee/primer3-0.4.0/primer3/).
2.8.8. Amplification of Entamoeba at the Actin locus
All microscopy positives were also analysed at the actin locus (~1,100 bp amplicon) as described by Sulaiman et al. (2002). For the primary PCR, a PCR product of 1,095 bp was amplified using forward (5'–ATG(A/G)G(A/
T)GAAGAAG(A/T)A(A/G)(C/T)(A/T)CAAGC–3') and reverse (5'–
AGAA(G/A)CA(C/T)TTTCTGTG(T/G)ACAAT–3') primers. The PCR reaction consisted of 50 ng DNA, 200 pM of each dNTP, 1 x PCR buffer (Fisher Biotech, Perth,
Australia), 3.0 mM MgCl2, 5.0 U of Taq polymerase (Fisher Biotech, Perth, Australia), and 200 nM of each primer in a total of 100 μL reaction. The reactions were performed for 35 cycles (each cycle is 94oC for 45 s, 50oC for 45 s, and 72oC for 60 s) on a Perkin
Elmer GeneAmp PCR 9700 thermocycler, with an initial hot start (94 C for 5 min) and a
81 final extension (72oC for 10 min). For the secondary PCR, a fragment of 1,066 bp was amplified using 2.5 μL of primary PCR reaction and forward (5'–
CAAGC(A/T)TT(G/A)GTTGTTGA(T/C)AA–3') and reverse (5'–
TTTCTGTG(T/G)ACAAT(A/T)(G/C)(A/T)TGG–3') primers using a lower annealing temperature (45oC). A positive control (E. histolytica) was used and a negative control
(no DNA added) was included in all reactions. Positive secondary PCR products were sequenced directly in both directions.
2.8.9. Amplification of Salmonella at the outer membrane porin ompF locus
All Salmonella samples that were positive by qPCR were re-screened at the outer membrane porins (ompF) locus with a single step PCR, using the ompF forward primer:
5’–CCTGGCAGCGGTGATCC–3’ and ompF reverse primer: 5’–
AAATTTCTGCTGCGTTTGCG–3’, as previously described by Tatavarthy and Cannons
(2010), which produced a product of ~578bp (Table 2.2). Briefly, The following PCR mixture (50 μl) was used: 10× PCR buffer, 0.2 mM dNTPs (Fisher Biotech, Perth,
Australia), 0.2 μM of each primer, 0.4 U of DNA polymerase, and 3 mM MgCl2 (Fisher
Biotech, Perth, Australia) and 1.0 μl of target DNA solution. The thermocycling program comprised an initial denaturation (94°C, 2 min) followed by 35 cycles of denaturation at
(94°C, 1 min), annealing (55°C, 1 min), and extension at (72°C, 1 min). A positive and a negative control (no DNA added) were included for all sets of reactions.
2.8.10. Amplification of Salmonella at the invasion A (invA) locus
All Salmonella positives were also typed at the invasion A (invA) locus using a single step PCR with the invA forward primer: 5’–TTGTTACGGCTATTTTGACCA–3’ and invA reverse primer: 5’–CTGACTGCTACCTTGCTGATG–3’ as previously described by Swamy et al. (1996), producing a product of ~521bp (Table 2.2). Briefly, the following PCR mixture (50 μl) was used: 10× PCR buffer, 0.2 mM dNTPs (Fisher
82 Biotech, Perth, Australia), 0.2 μM of each primer, 0.4 U of DNA polymerase and 3 mM
MgCl2 (Fisher Biotech, Perth, Australia), and 1.0 μl of target DNA solution. The thermocycling program comprised an initial denaturation (94°C, 2 min) followed by 30 cycles of denaturation at (94°C, 1 min), annealing (42°C, 1 min), and extension at (72°C,
2 min). A positive (S. enterica serovar Hadar) and a negative control (no DNA added) were included in all reactions.
2.8.11. Amplification of Salmonella at the serovar Typhimurium specific gene loci, STM2755 and STM4497
All Salmonella positives were typed at the STM2755 and STM4497 genes using a single step PCR with the STM2755 forward primer: 5’–
AGCTTGCCCTGGACGAGTT–3’ and STM2755 reverse primer: 5’–
TGGTCGGTGCCTGTGTGTA–3’ and STM4497 forward primer: 5’–
GGAATCAATGCCCGCCAATG–3’ and STM4497 reverse primer: 5’–
CGTGCTTGAATACCGCCTGTC–3’ as previously described by Shanmugasundaram et al. (2009), producing products of 406 and 523 bp respectively (Table 2.2). Briefly, the following PCR mixture (50 μl) was used: 10× PCR buffer, 0.2 mM dNTPs (Fisher
Biotech, Perth, Australia), 0.2 μM of each primer, 0.4 U of DNA polymerase, and 3 mM
MgCl2 (Fisher Biotech, Perth, Australia), and 1.0 μl of target DNA solution. The thermocycling program comprised an initial denaturation (94°C, 2 min) followed by 35 cycles of denaturation at (94°C, 1 min), annealing (66°C, 1 min), and extension at (72°C,
1 min). A positive (S. enterica serovar Typhimurium) and a negative control (no DNA added) were included in all reactions.
2.8.12. Amplification of Campylobacter at the 16S rRNA locus
All samples positive for Campylobacter by qPCR were typed at the 16S rRNA locus using single step PCR with the primers OT1559 5′-
83 CTGCTTAACACAAGTTGAGTAGG and 18-1rev 5′-
TTCTGACGGTACCTAAGGAA-3' as previously described by Lubeck et al. (2003), producing a product of ~287bp (Table 2.2). The following PCR mixture (50 μl) was used:
10× PCR buffer, 0.2 mM dNTPs (Fisher Biotech, Perth, Australia), 0.2 μM of each primer, 0.4 U of DNA polymerase, and 3 mM MgCl2 (Applied Biosystems, Denmark), and 1.0 μl of target DNA solution. The thermocycling program comprised an initial denaturation (94°C, 2 min) followed by 35 cycles of denaturation at (94°C, 1 min), annealing (55°C, 1 min), and extension at (72°C, 1 min). A positive (C. jejuni) and a negative control (no DNA added) were included in all reactions.
2.8.13. Amplification of Campylobacter at the hippuricase (hipO) locus
A one-step PCR of the hippuricase gene (hipO) (344 bp amplicon) was conducted using the primers hipO-F 5′–GACTTCGTGCAGATATGGATGCTT–3' and hipO-R 5′–
GCTATAACTATCCGAAGAAGCCATCA–3' and PCR conditions described by
Persson and Olsen, (2005) (Table 2.2). The PCR reaction consisted of 1 µL of DNA (~50 ng), 200 pM of each dNTP, 1 x PCR buffer (Fisher Biotech, Perth, Australia), 3.0 mM
MgCl2, 5.0 U of Taq polymerase (Fisher Biotech, Perth, Australia), and 200 nM of each primer in a total of 100 μL reaction. Thermocycler conditions were 94 °C for 6 min, followed by 35 cycles of 94°C for 50 s, 57°C for 40 s and 72°C for 50 s, and finally 72°C for 3 min. A positive (C. jejuni) and a negative control (no DNA added) were included in all reactions.
84 Table 2.2. Target genes and primers used for amplification and sequencing of Salmonella and Campylobacter isolates in rangeland goats.
Target/ Primer Nucleotide sequence (5′–3′) PCR Product Reference size (bp) Salmonella spp. ompF/ ompF1 TCGCCGGTCGTTGTCCAT qPCR 96 Yang et al. (2014d) ompF/ ompR1 AACCGCAAACGCAGCAGAA ompF/ ompF1 CCTGGCAGCGGTGATCC one-step 578 Tatavarthy and PCR Cannons (2010) ompF/ ompF- TGGTGTAACCTACGCCATC seqR invA/ invA-F TTGTTACGGCTATTTTGACCA one-step 521 Swamy et al. (1996) PCR invA/ invA-R CTGACTGCTACCTTGCTGATG STM2755/ AGCTTGCCCTGGACGAGTT one-step 406 Shanmugasundaram STM2755-F PCR et al. (2009) STM2755/ TGGTCGGTGCCTGTGTGTA STM2755-R STM4497/ GGAATCAATGCCCGCCAATG one-step 523 Shanmugasundaram STM4497-F PCR et al. (2009) STM4497/ CGTGCTTGAATACCGCCTGTC STM4497-R Campylobacter spp.
purA/ purAF1 CGCCCTTATCCTCAGTAGGAAA qPCR 121 Yang et al. (2014d)
purA/ purAR1 TCAGCAGGCGCTTTAACAG
16S rRNA/ CTGCTTAACACAAGTTGAGTAGG one-step 287 Lubeck et al. (2003) OT1559 PCR 16S rRNA/ 18-1 TTCCTTAGGTACCGTCAGAA hipO/ hipO-F GACTTCGTGCAGATATGGATGCTT one-step 344 Persson and Olsen PCR (2005) hipO/ hipO-R GCTATAACTATCCGAAGAAGCCAT CA
2.8.14. Amplification of Eimeria at the 18S rRNA locus
Amplification of Eimeria-qPCR positives at the 18S locus was conducted using a two-step PCR with the primers EiGTF1- 5'– TTC ACT GGT CCC TCC GAT C–3' and
85 EIGTR1- 5'– AAC CAT GGT AAT TCT ATG G–3' (Yang et al., 2016) for the primary reaction. The primers EiGTF2- 5'– TTA CGC CTA CTA GGC ATT CC–3' and EiGTR2-
5'– TGA CCT ATC AGC TTT CGA CG–3' (Yang et al., 2015) were used for the secondary reaction. The PCR reaction contained 2.5 µL of 10 × Kapa PCR buffer, 2 µL of 25 mM MgCl2, 1.5 µL of 10 nM dNTPs, 10 pM of each primer, 1 unit of KapaTaq
(Geneworks, Adelaide, SA), 1 µL of DNA (about 50 ng) and 15.9 µL of H2O. PCR cycling conditions for the external PCR were 1 cycle of 94°C for 3 min, followed by 35 cycles of 94°C for 30 s, 58°C for 30 s and 72°C for 2 min and a final extension of 72°C for 5 min. The conditions for the secondary PCR were the same except for 45 cycles instead of 35. The expected PCR product was ∼1,510 bp. However, this process yielded mixed chromatograms for some samples (n=100) which required further isolation of morphologically similar Eimeria oocysts using a micromanipulator (see section 2.12.3).
2.8.15. Amplification of Eimeria at the cytochrome c oxidase subunit I (COI) locus
A partial COI gene fragment (723 bp) was amplified using a nested PCR with the following primers COIF1 5'–GGTTCAGGTGTTGGTTGGAC–3 (Ogedengbe et al.,
2011) and COXR1 5'–CCA AGA GAT AAT AC (AG) AA (AG) TGG AA–3' (Dolnik et al., 2009) for the external reaction and COIF2 5'–TAA GTA CAT CCC TAA TGT C–3'
(Yang et al., 2013b) and COXR2 5'–ATA GTA TGT ATC ATG TA (AG)(AT)GC AA–
3' (Dolnik et al., 2009) for the internal reaction. The PCR reaction contained 2.5 µL of
10 × Kapa PCR buffer, 2 µL of 25 mM MgCl2, 1.5 µL of 10 nM dNTPs, 10 pM of each primer, 1 unit of KapaTaq (Geneworks, Adelaide, SA), 1 µL of DNA (~50 ng) and
15.9 µL of H2O. PCR cycling conditions for the external PCR were 1 cycle of 94 °C for
3 min, followed by 35 cycles of 94 °C for 30 s, 58 °C for 30 s and 72 °C for 2 min and a final extension of 72 °C for 5 min. The conditions for the secondary PCR were the same except for 45 cycles instead of 35.
86 2.9. Agarose gel electrophoresis
Horizontal electrophoresis was performed using 1.0% agarose gels (Promega,
Madison, USA) in 1x TAE buffer (40 mM Tris-HCL; 20 mM acetate; 2mM EDTA pH adjusted to 8.0) stained with 0.025μL/mL SYBER® safe DNA gel stain (Invotrgoen,
Carlsbad, USA). Post electrophoresis PCR product visualisation was performed by UV transillumination using a BIO Rad Gel Doc 1000 transilluminator.
2.10. Sanger sequencing
All secondary PCR positive products were gel purified using an in-house filter tip method as previously described (Yang et al., 2013) and sequenced using an ABI PrismTM
Terminator Cycle Sequencing Kit (Applied Biosystems, Foster City, California, USA) on an Applied Biosystem 3730 DNA Analyzer.
Purified secondary PCR products were sequenced using a Big Dye version 3.1
Terminator Cycle Sequencing Kit (Applied Biosystems, Foster City, California) according to the manufacturer’s instructions. One eighth reactions were performed with the reaction mixture containing 1 μL of 5x sequencing buffer (Applied Biosystems), 6.25 pmoles primer and 20 ng DNA template for Cryptosporidium, Giardia, Eimeria,
Entamoeba, Salmonella and Campylobacter purified PCR product made up to a final volume of 10 μL with PCR grade water (Fisher Biotech). Thermal cycling conditions for the sequence reaction included an initial hold on 96oC for 2 mins, followed by 35 cycles of 96oC for 10 s, 58oC for 5 s and 60oC for 4 mins. Following completion of the sequence reaction, the full 10 μL sequencing reaction was added to a 0.5 mL Eppendorf tube containing 1 μL of 125 mM disodium salt (EDTA), 1 μL of 3M sodium acetate pH and
25 μL of 100% ethanol. The contents of the Eppendorf tube were mixed by pipetting and then left to stand at room temperature for 20 mins. Samples were then centrifuged at
20,000 x g for 30 mins and the supernatant discarded. The DNA pellet was then washed
87 with 125 μL 70% ethanol, and centrifuged at 20,000 x g for 5 mins and the supernatant discarded. The pellet was then subjected to a final wash in 25 μL 70% ethanol and centrifuged at 20,000 x g for 5 mins.
2.11. Sequence and phylogenetic analysis
Sequence searches of positive isolates for Cryptosporidium, Giardia, Eimeria,
Entamoeba, Salmonella and Campylobacter were conducted using BLAST
(http://blast.ncbi.nlm.nih.gov/Blast.cgi) and nucleotide sequences were analysed using
Chromas Lite version 2.0 (http://www.technelysium.com.au) and aligned with reference genotypes from GenBank using Clustal W (http://www.clustalw.genome.jp).
Phylogenetic trees were constructed for Entamoeba spp. at 18S rRNA and actin loci and Eimeria spp. at the 18S rRNA and COI loci with additional isolates from
GenBank. Parsimony, Maximum likelihood (ML) and Neighbor-joining (NJ) analyses were conducted using MEGA 6 (Tamura et al., 2013). ML and NJ analyses were conducted using Tamura-Nei based on the most appropriate model selection using
ModelTest in MEGA 6. Bootstrap analyses were conducted using 1000 replicates to assess the reliability of inferred tree topologies.
2.12. Microscopy
2.12.1. Morphometric assessments of Entamoeba cysts and trophozoites
Direct microscopic examination of faecal suspensions in saline and wet mounted with 0.9% saline and Lugol's iodine was conducted. Approximately 2 mg of stool sample was picked up using a wooden stick and mixed with a drop of normal saline (0.9%) on a glass slide with applicator stick. The preparation was covered with a cover slip and observed under the microscope. For iodine wet mount preparation, approximately 2 mg of faecal sample was picked up using a wooden stick and mixed with a drop of dilute
88 Lugol’s iodine. It was covered with a coverslip and observed under the microscope for the presence of cysts and trophozoites. Entamoeba cysts were also concentrated using zinc-sulfate gradient floatation (Faust’s method) (Ramos et al., 2005). In this assay, a fine faecal suspension was made by mixing 1 g of faecal sample and 10 mL of lukewarm distilled water. The coarse particles were removed by straining through a wire gauge. The filtrate was collected in a tube and centrifuged for 1 min at 1,455 × g. The supernatant fluid was poured off and distilled water was added to the sediment. It was shaken well and centrifuged and the procedure was repeated two to three times until the supernatant fluid became clear, which was then poured off. 3-4 mL of a 33% zinc sulphate was added to the sediment. The sediment was then stirred and more zinc sulphate solution was added to fill the tube up to the top and centrifuged again for at least 1 min at 1455 × g. The surface film was then removed by a loop on to a glass slide, covered with a cover slip, and observed under Nomarski contrast with a 100× oil immersion objective lens in combination with an ocular micrometer, on an Olympus DP71 digital micro-imaging camera. The diameters of cysts (n=35) and trophozoites (n=15) were measured and averages and ranges were calculated.
2.12.2. Morphometric assessments of Eimeria spp. oocysts
Morphological characteristics for sporulated oocysts were determined for faecal samples that were qPCR positive (section 2.6.3.). Approximately 2g faeces were placed in 2% (w/v) potassium dichromate solution (K2Cr2O7), mixed well and poured into petri dishes to a depth of less than 1 cm and kept under close observation at room temperature in the dark to facilitate sporulation. Faecal flotation was conducted using a saturated sodium chloride and 50% sucrose (w/v) solution as previously described (Soulsby, 1982).
In this protocol, flotation solutions, NaCl (360 g liter−1; specific gravity, 1.21) and sucrose solution (500 g of sucrose and 6.5 g of phenol in 320 mL of water) were prepared and faecal samples were emulsified with 45-mL portions of the flotation solutions and
89 centrifuged at 500 × g for 10 min. The upper 5 mL of each supernatant was transferred to a 50-mL tube. A sample from the supernatant layer was transferred to a slide covered by a cover slip, and observed under the microscope and observed under Nomarski contrast with a 100× oil immersion objective.
Sporulated oocysts were observed using an Olympus DP71 digital micro-imaging camera and images were taken using Nomarski contrast imaging system with a 100× oil immersion objective lens in combination with an ocular micrometre on an Olympus DP71 digital micro-imaging camera. Morphological features were recorded and measurements were performed on oocysts (n=35) of each identified Eimeria species. All measurements were given in micrometres (μm) as the mean followed by the range in parentheses. Minor shape variations were observed. The number of oocyst cell wall layers was confirmed by crushing individual oocysts with gentle coverslip pressure. Species were differentiated by reference to the descriptions given by Honess (1942), Levine et al., (1962a) and Shah and
Joshi (1963).
2.12.3. Isolation and analysis of single Eimeria oocysts using a micromanipulator
A 3-axis hydraulic micromanipulator (MO-102, Nirashige, Japan) was used to select four morphologically similar Eimeria spp. oocysts from each faecal sample. Where multiple morphotypes were observed (i.e. mixed infections), four oocysts of each morphotype were selected and transferred to separate slides.
The morphologically similar oocysts (n=4 per morphotype) isolated from each qPCR positive faecal sample were transferred to a new slide, examined and photographed using microscopy (Olympus DP71 digital micro-imaging camera) to confirm morphological similarity. Measurements were recorded for species identification based on morphological characteristics. These were then transferred into a PCR tube containing
90 10 µL of lysis buffer (0.005% SDS in TE solution) by washing the coverslip with 100 µL saline. After a brief centrifugation, the tube was frozen in liquid nitrogen and thawed in a 95 °C water bath for four rounds to disrupt the oocyst walls. After the addition of 0.5 µL proteinase K (20 mM), the tube was incubated at 56 °C for 2 h and then at 95 °C for
15 min. The entire lysate of the morphologically similar oocysts was used for two separate
PCRs (18S rRNA and COI) as previously described in sections 2.7.14 and 2.7.15).
2.13. Additional sampling of rangeland goats at Beaufort River Meats abattoir
In order to conduct further microbial analysis on rangeland goats faecal samples during the slaughter process, additional goat faecal samples (n=400) were sampled at
Beaufort River Meats abattoir, that processes goats, sheep and occasionally deer and is located 60 km east of Katanning and 254 km south of Perth in the Woodanilling region of Western Australia. The goats included in the present study originated from four consignments; Meedo Station in the Carnarvon region, Tamala Station in the Shark Bay region, Wagga Wagga Station in the Yalgoo region and Wooramel Station in the
Wooramel region, which arrived at the abattoir between November and December 2016 as shown in Fig. 2.4. As part of the standard management practice, goats were trapped in yards and supplied with oaten hay and water ad libitum. Goats were loaded in the morning
(05:30) and transported in open trailers for approximately 12 hours. On arrival at the abattoir (lairage), goats were kept in a shaded pen with access to water. Slaughter commenced at 10.00 am on the day following transport. Slaughter of goats from different consignments was occurred on different days.
After evisceration, goats’ digestive tracts proceeded to the offal room where the sampling was carried out.
91
Figure 2.4. Captured and transported rangeland goats arriving at Beaufort River Meats abattoir, Western Australia. Photo provided by Laurence Macri, BRM.
From each of the four consignments, 100 goats were sampled with specimens collected at regular time intervals (approximately two to four minutes) as the consignment was processed, so as to spread the sampling across the entire consignment. After evisceration, goats’ digestive tracts were separated from carcasses for collection of offal.
For each sample, approximately 25 g of faecal content was obtained by making a transverse incision of the large intestine, 10 to 20 cm proximal to the anus, using a sterile scalpel blade and then using a sterile-gloved hand to express faecal matter into a sterile polypropylene container. Samples were then immediately labelled, stored on ice or in a refrigerator (4.0°C), while being transported to the laboratory for isolation of Salmonella later that day.
92
Figure 2.5. Removal of digestive tracts from rangeland goats after evisceration at Beaufort River Meats abattoir, Western Australia. Photo provided by Laurence Macri, BRM.
2.14. Salmonella isolation and MALDI–TOF analysis
Samples for isolation of Salmonella were prepared as described by Garcia et al.
(2010). Briefly, 10 g of each faecal sample were transferred aseptically to each of 7 mL of 0.1% Buffered Peptone Water (BPW) and 7mL Rappaport–Vassiliadis (RV) broth, mixed, allowed to settle and incubated for 18–24 h at 37 °C and 42 °C, respectively. After incubation, a loopful of each enrichment broth was inoculated onto Xylose Lysine
Deoxycholate (XLD) (Oxoid CM0469, Basingstoke, England) agar and Brilliance
Salmonella (BS) (Thermofisher Scientific, Australia) and each were incubated at 37°C for 24 hrs. Typical Salmonella colonies identified by colony morphology (e.g. black and pink colonies on XLD and BS agars respectively) were further cultured into Colombia sheep blood agar (ThermoFisher Scientific, Australia) and incubated at 37 °C for 24 h.
From each plate 10–25 colonies were harvested, deposited in Brain Heart Infusion (BHI) broth containing glycerol (20% v/v) and stored frozen at − 80 °C until further use.
Identification of organisms as Salmonella was achieved using Matrix Assisted
Laser Deionised Time of Flight (MALDI–TOF) analysis as follows. All samples of
93 presumptively positive colonies were inoculated onto Colombia sheep blood agar
(ThermoFisher Scientific, Australia), incubated at 37 °C for 24 h and then transferred to a target plate (96 MSP, Bruker® – Billerica, USA). A minimum amount of colonies were carefully transferred to the centre of each well of the microplate to avoid cross contamination. Control wells (without bacteria) were also used on each target plate. The bacterial spot was covered with a lysis solution (70% formic acid; Sigma–Aldrich®) and then a 1 μL aliquot of matrix solution (alpha-ciano-4-hidroxi-cinamic acid diluted in 50% acetonitrile and 2.5% trifluoroacetic acid, Sigma–Aldrich®) was added. The spectra of each sample were collected in a mass range between 2000 and 20,000 m/s, and then were analyzed by the MALDI Biotyper 2.0 (Bruker®) program, using the standard configuration for bacteria identification, which compared the spectrum of the samples with the references in the database. The results vary on a 0–3 scale, where the highest value means a more precise match and reliable identification. In the current study, the values accepted for matching were greater than or equal to 2.
2.15. DNA Extraction
All the Salmonella isolates were sub-cultured on Coloumbia Sheep Blood Agar
(ThermoFisher Scientific, Australia) and incubated overnight at 37 °C. The genomic
DNA was isolated from a single colony of the overnight cultures using the DNeasy®
Blood & Tissue Kit (Qiagen, Hilden, Germany) following the manufacturer’s recommendations and stored at −20°C until use. A negative control (no faecal sample) was used in each extraction group.
2.16. PCR amplification and sequencing
All the MALDI-TOF positive isolates were subjected to one-step PCR using serovar Typhimurium specific primers to the putative hexulose-6-phosphate synthase
94 gene (STM2755; 406 bp amplicon) and cytoplasmic proteins STM4497; 523 bp amplicon) using PCR conditions described by Shanmugasundaram et al., (2009) and detailed in section 2.8.11. S. enterica serovar Typhimurium isolate (Abraham et al., 2016) was used as a positive control. Non-amplified isolates at the STM2755 and STM4497 loci were further subjected to a one-step PCR for the S. enterica ompF (578 bp amplicon) and invA (521 bp amplicon) genes as described by Tatavarthy and Cannons (2010) and
Swamy et al., (1996) respectively and detailed in section 2.8.10. S. enterica serovars
(Dublin, Enteritidis and Hadar, Hato) (Harb et al., 2017) were used as positive controls
(SFI4-7). PCR products were separated by gel electrophoresis and purified using an in- house filter tip method previously described (Yang et al., 2013). Purified PCR products were sequenced using an ABI Prism Dye Terminator Cycle Sequencing kit (Applied
Biosystems) using an annealing temperature of 58 °C. Nucleotide sequences were analysed using Chromas lite version 2.0 (http://www.technelysium.com.au) and aligned with reference sequences from GenBank using Clustal W
(http://www.clustalw.genome.jp).
2.17. Salmonella antimicrobial susceptibility testing and interpretation
Each isolate was subjected to broth microdilution assays (Sensititre; Thermo
Fisher Scientific, Waltham, MA) to determine the minimum inhibitory concentrations
(MICs) of 13 antimicrobial agents: cefoxitin (CEF), azithromycin (AZI), chloramphenicol (CHL), tetracycline (TET), ceftriaxone (CTX), amoxicillin-clavulanic acid (AMC), ciprofloxacin (CIP), gentamicin (GEN), ceftiofur (CFT), trimethoprim- sulfamethoxazole (TRI), ampicillin (AMP), nalidixic acid (NAL) and streptomycin
(STR) against Salmonella. MIC results were interpreted as resistant (R), susceptible (S) and intermediate, according to veterinary-specific and human approved interpretative criteria as per the Clinical and Laboratory Standards Institute (CLSI) VET01S guidelines
95 (CLSI, 2015). When clinical breakpoints were not available in CLSI, MICs were interpreted based on epidemiological cut-off values (ECOFFs) for non-wild type (non-
WT) organisms derived from assessment of the MIC distribution using ECOFFinder
(Turnidge et al., 2006; CLSI, 2016) and/or as published by the European Committee on
Antimicrobial Susceptibility Testing (EUCAST) (EUCAST, 2016) as presented in Table
2.3. For phenotypic analysis, if ECOFF was not present, the clinical break points were used. Staphylococcus aureus ATCC 25923 and ATCC 29213 and Escherichia coli ATCC
25922 were used as control strains. Salmonella isolates showing clinical resistance to three or more classes of antimicrobial agents were classified as multi-drug resistant
(MDR).
96 Table 2.3. Susceptible Clinical and Laboratory Standards Institute clinical breakpoints and cut-off values (ECOFFs) of Salmonella isolates used for MIC interpretation.
MIC (μg/mL) Antimicrobial CLSI susceptible: EUCAST ECOFF: treatment success likely wild type Cefoxitin (FOX) ≤8 ≤8 Azithromycin (AZI) None None Chloramphenicol (CHL) ≤8 ≤16 Tetracycline (TET) ≤4 ≤4 Ceftriaxone (AXO) ≤1 None Amoxicillin-clavulanic acid (AUG) ≤8 None Ciprofloxacin (CIP) ≤0.6 ≤0.6 Gentamicin (GEN) ≤4 ≤1 Nalidixic acid (NAL) ≤16 None Ceftiofur (XNL) ≤2 ≤2 Trimethoprim-sulfamethoxazole ≤1 ≤1 (SXT) Ampicillin (AMP) ≤8 ≤4 Streptomycin (STR) ≤32 ≤32
2.18. Statistical analysis
Methods for statistical analyses are described in each experimental chapter.
Analyses were performed using SAS (Version 9.2, SAS Institute) for linear mixed effect models and IBM SPSS statistics (version 24, IBM Corporation) for other analyses except where specified. The experimental unit for analyses was individual goats.
Pathogen faecal carriage detection for each pathogen (Cryptospordium, Giardia,
Salmonella, Campylobacter, Haemonchus and Trichostrongylus) for each goat at each timepoint was categorised as detected (pathogen detected by qPCR) or absent (not detected). McMaster WEC and qPCR Eimeria OPG were log-transformed for analyses using Log10 (x + 25) where x = trichostrongylid eggs or Eimeria oocysts per gram of faeces.
97 Point prevalence for pathogen genera were determined by the proportion of goats pathogen-positive by PCR for each sample occasion. Longitudinal prevalence was calculated as the proportion of goats pathogen-positive on at least one occasion. The 95% confidence intervals for prevalence were calculated using Jeffrey's interval method
(Brown et al., 2001).
Two-tailed Chi-square tests (Pearson Chi-square or Fisher’s exact test) were used to compare frequency of faecal carriage detection between sampling occasions.
Monthly growth rate was determined by calculating weight change for the one- month period following faecal sample collection (future growth) for sampling occasions
1-3, and the one-month period before faecal sample collection (past growth) for sampling occasions 2-4.
Faecal samples were categorised as scouring (FCS 4 or higher) or not scouring
(FCS 1-2). There were no faecal samples with FCS=3. Prevalence for scouring (% samples categorised as scouring) were determined for faecal samples with and without faecal carriage detected for each pathogen. Scouring prevalence for faecal samples with or without enteric pathogens detected were compared using the Chi-squared test with
Fishers exact 2-sided test for independence. Odds ratios were used to calculate relative risk for scouring for pathogen detection categories.
2.19 Conflict of interest statement
The researcher and supervisory team had no financial or personal relationships with other people or organisations that could inappropriately influence or bias the content of this research in this thesis.
98 CHAPTER 3. ZOONOTIC CRYPTOSPORIDIUM AND GIARDIA SHEDDING BY CAPTURED RANGELAND GOATS
The contents of this chapter have been published in Veterinary Parasitology:
Regional Studies and Reports. The article can be found in Appendix 8.
This chapter describes the longitiudinal prevalence and molecular characterisation of protozoal agents; Cryptosporidium and Giardia spp. from captured rangeland goats.
Two molecular methods were used: (1) qPCR to determine the longituidinal prevalence of both potozoal agents and (2) nested PCR for molecular characterisation of species and genotyping of subspecies of both Cryptosporidium and Giardia in captured rangeland goats.
Research highlights:
First report for Cryptosporidium and Giardia in captured rangeland goats.
Shedding of zoonotic C. parvum and C. ubiquitum.
First report of zoonotic Cryptosporidium parvum subtype IIaA17G4R1 in goats.
Giardia duodenalis Assemblage E identified – considered potentially zoonotic.
Findings have implications for management of captured rangeland goats and
effluent.
99 Abstract: Faecal shedding of Cryptosporidium and Giardia by captured rangeland
goats was investigated using a longitudinal study with four faecal samples collected
from 125 male goats once monthly for four months, commencing immediately after
capture and transport to a commercial goat depot (feedlot). Goats were composite
breed and aged approximately 9–12 months on arrival. Faecal samples were screened
for Cryptosporidium and Giardia presence and concentration using quantitative PCR
and sequencing at the 18S ribosomal RNA locus (Cryptosporidium), and glutamate
dehydrogenase and β-giardin loci (Giardia). Longitudinal prevalence for
Cryptosporidium was 27.2% (point prevalence range 3–14%) with 3 species
identified: C. xiaoi (longitudinal prevalence 13.6%), C. ubiquitum (6.4%) and C.
parvum (3.2%). Sub-typing at the gp60 locus identified C. ubiquitum XIIa, C. parvum
IIaA17G2R1 and C. parvum IIaA17G4R1. This is the first report of the zoonotic C.
parvum subtype IIaA17G4R1 in goats. The pattern of genotypes shed in faeces
changed over the duration of study with C. ubiquitum identified only at the first and
second samplings, and C. parvum identified only at the fourth sampling. Longitudinal
prevalence for Giardia duodenalis was 29.6% (point prevalence range 4–12%) with
all positives sub-typed as assemblage E. Only 2/125 goats were identified to be
shedding Cryptosporidium or Giardia on more than one occasion. This is the first
report of Cryptosporidium and Giardia genotypes in captured rangeland goats. Faecal
shedding of zoonotic Cryptosporidium spp. and potentially zoonotic G. duodenalis
has implications for food safety and effluent management.
3.1. Introduction
Strong growth in the Australian goat meat industry has been largely supported by goats derived from rangeland (extensive) production systems. Rangeland goats are a composite breed naturalised throughout Australian rangelands, typically unmanaged
100 (undomesticated) and opportunistically captured and utilised for meat production.
Diarrhoea and ill-thrift are cited as important issues for rangeland goats following capture, particularly under intensive management conditions in feedlots prior to slaughter (Meat and Livestock Australia, 2016). Causes of diarrhoea and ill thrift in captured rangeland goats are not well described, although it is suggested that stress associated with capture, transport and domestication of wild goats, and high stocking densities in feedlots increase shedding and transmission of disease agents with veterinary and public health importance, e.g. Eimeria and Salmonella (Meat and Livestock Australia, 2016). Reviews of available evidence have concluded that Cryptosporidium spp. and Giardia duodenalis may cause diarrhoea, weight loss and mortalities in goat kids, although evidence of disease in goats postweaning age is less clear (de Graaf et al., 1999; O'Handley and Olsen 2006; Geurden et al., 2010; Santin, 2013). Six Cryptosporidium species and genotypes have been reported in goats; C. parvum, C. hominis, C. xiaoi, C. ubiquitum, C. andersoni and rat genotype II (Robertson, 2009; Koinari et al., 2014; Ryan et al., 2014; Peng et al., 2016).
Giardia duodenalis assemblages A, B and E have been identified in goats (Robertson,
2009; Zhang et al., 2012; Peng et al., 2016; Table 1.3). Importantly, some
Cryptosporidium and G. duodenalis genotypes reported in goats have public health significance, having zoonotic potential and the capacity for contamination of water supplies (Robertson, 2009; Ryan et al., 2014).
The epidemiology of Cryptosporidium and Giardia in rangeland goats in
Australia is not described, and may have implications for management of goats pre- slaughter. The work presented in this chapter was therefore conducted to investigate the faecal shedding of Cryptosporidium and Giardia species by captured rangeland goats using molecular tools.
101 3.2. Materials and methods
3.2.1. Animals and sample collection
Sampling occurred once monthly for four months (S1 to S4) from 125 male rangeland goats (composite breed) following capture and beginning immediately after arrival at a commercial goat depot (feedlot) near Geraldton, Western Australia in
February 2014. On arrival (S1), goats weighed 30.7 ± 0.3 kg (mean ± SEM) with estimated age 9–12 months based on dentition. Goats were housed in four group pens
(approximately 30 goats per pen). Grain-based pellets, hay and water were supplied ad libitum. Goats were consigned for slaughter after conclusion of the experiment when they reached acceptable slaughter weight. Faecal samples were collected directly from the rectum and stored on ice or a refrigerator (4.0 °C) until DNA extraction was performed.
Sample collection methods were approved by Murdoch University Animal Ethics
Committee (approval number R2617/13).
3.2.2 DNA isolation
Four freeze–thaw cycles were employed followed by genomic DNA extraction from 200 mg of each faecal sample using a Power Soil DNA Kit (MolBio, Carlsbad,
California), which includes a mechanical bead disruption step using glass beads to increase the efficiency of DNA extraction. A negative control (no faecal sample) was used in each extraction group.
3.2.3. PCR screening, amplification and sequencing
Faecal samples were screened for the presence of Cryptosporidium and Giardia spp. using quantitative PCR (qPCR) as previously described (Yang et al., 2014a; Yang et al., 2014b). Analytical specificity and sensitivity testing of the qPCR assays was previously described (Yang et al., 2014a; Yang et al., 2014b), with no cross-reactions
102 with other genera and detection of all Cryptosporidium and Giardia isolates tested. The assays detected 2 Cryptosporidium oocysts and 1 Giardia cyst per μl of faecal DNA extract. Mean RSQ and % RDS were 0.99 and 1.5% for Cryptosporidium, and 0.98 and
5.5% for Giardia respectively. The number of oocyst equivalents per gram of faeces was calculated on the premise that one oocyst contains 40 fg of genomic DNA (Guy et al.,
2003). Cryptosporidium qPCR positives were amplified at the 18S rRNA locus using a nested PCR as previously described (Morgan et al., 1997). Subtyping at the gp60 locus was conducted for C. parvum (Ng et al., 2008) and C. ubiquitum (Li et al., 2014). Giardia positive isolates were amplified at the glutamate dehydrogenase (gdh) and β-giardin (bg) loci (Read et al., 2004; Lalle et al., 2005). Triose-phosphate isomerase (tpi) assemblage
E-specific primers (Geurden et al., 2008) were used to confirm the assemblages typed at the gdh and bg loci. Purified PCR products were sequenced using an ABI Prism™ Dye
Terminator Cycle Sequencing kit (Applied Biosystems, California). Nucleotide sequences were analyzed using Chromas lite version 2.0
(http://www.technelysium.com.au) and aligned with reference sequences from GenBank using Clustal W (http://www.clustalw.genome.jp).
3.2.4. Statistical analysis
Statistical analyses were performed using IBM SPSS Statistics Version 21 for
Mac. Goats were classified as positive (parasite DNA detected) or negative (no parasite
DNA detected) for Cryptosporidium and Giardia. Point prevalence was determined by proportion of positive goats for each sample occasion. Two-tailed Chi-square tests were used to compare point prevalence between sampling occasions. Longitudinal prevalence was calculated as the proportion of goats with parasite DNA detected on at least one occasion. Prevalence 95% confidence intervals were calculated using Jeffrey’s interval method (Brown et al., 2001). Differences in shedding intensity for Cryptosporidium and
Giardia between time points were assessed using univariate general linear model with
103 timepoint included as a fixed factor and least squares difference post hoc test. Levene’s test was used to determine for equality of variance (P>0.05). P-values of 0.05 were used to declare statistical significance.
3.3. Results
3.3.1. Cryptosporidium and Giardia prevalence
A total of 36/500 faecal samples were qPCR-positive for Cryptosporidium and
38/500 were PCR-positive for Giardia. Point prevalences and longitudinal prevalences are shown in Table 3.1. Point prevalence fell between the first and second sampling for both Cryptosporidium and Giardia. By S4, point prevalence for both Cryptosporidium and Giardia were not different to S1.
Two goats were Cryptosporidium-positive on two occasions (S1 and S3; S3 and
S4) and one goat was Giardia-positive on two occasions (S1 and S4). No goats were
Cryptosporidium or Giardia-positive on more than two occasions. Concurrent
Cryptosporidium and Giardia infections were identified at each sampling occasion (Table
3.1).
3.3.2. Cryptosporidium species and subtypes
Overall 29/36 qPCR Cryptosporidium-positive samples were successfully sequenced at the 18S locus and three Cryptosporidium species were detected; C. xiaoi
(n=17), C. ubiquitum (n=8) and C. parvum (n=4). Sub-typing at the gp60 locus identified all eight C. ubiquitum positives as XIIa, while C. parvum positives were subtyped as
IIaA17G2R1 (n=1) and IIaA17G4R1 (n=3). Point prevalence and longitudinal prevalence for each species identified by sequencing are shown in Table 3.1.
Cryptosporidium xiaoi was identified at all four sampling occasions. Cryptosporidium ubiquitum was not identified after S2. Cryptosporidium parvum was identified at S4 only.
104 No mixed genotype Cryptosporidium infections were identified in any goats at a single sampling occasion. For the two goats that were Cryptosporidium-positive on two occasions, one goat was positive for C. ubiquitum (S3) and C. parvum IIaA17G4R1 (S4), and the other goat was positive for C. ubiquitum (S1) with the second isolate (S4) not successfully sequenced. Representative sequences were submitted to GenBank under the accession numbers: KX813706, KX813707, KX813708 and KX813709.
3.3.3. Giardia assemblages
Overall, 26/38 Giardia qPCR positives were successfully typed at the gdh and bg loci and all were identified as Giardia duodenalis assemblage E. This observation was confirmed using assemblage E-specific tpi primers. No positive samples from S4 were sequenced. Representative sequences were submitted to GenBank under the accession numbers: KX813710 and KX813711.
3.3.4. Cryptosporidium and Giardia faecal shedding intensity
Faecal shedding intensity (concentration) in positive samples are shown in Table
3.1. There was no effect of sampling occasion on shedding intensity in positive goats for either Cryptosporidium (P=0.374) or Giardia (P=0.400).
105 Table 3.1. Cryptosporidium and Giardia prevalence and shedding intensity for 125 goats sampled on four occasions (S1-S4).
Sampling occasion Longitudinal prevalence S1 S2 S3 S4 Prevalence (% (95% confidence interval)) Cryptosporidium spp. 14.4 (9.1, 21.3)a 4.0 (1.5, 8.5)b 3.2 (1.1, 7.4)b 7.2 (3.6, 12.7)ab 27.2 (20, 35.5) C. xiaoi 8.8 (4.8, 14.7)a 2.4 (0.7, 6.3)b 0.8 (0.1, 3.7)b 1.6 (0.3, 5.0)b 13.6 (8.4, 20.4) C. ubiquitum 5.6 (2.5, 10.7)a 0.8 (0.1, 3.7)b 0 (0, 2.0)b 0 (0, 2.0)b 6.4 (3.1, 11.7) C. parvum 0 (0, 2.0)a 0 (0, 2.0)a 0 (0, 2.0)a 3.2 (1.1, 7.4)b 3.2 (1.1, 7.4) Not sequenced* 0 0.8 2.4 2.4 - Giardia spp. 12.0 (7.2, 18.5)a 4.0 (1.5, 8.5)b 7.2 (3.6, 12.7)ab 7.2 (3.6, 12.7)ab 29.6 (22.1, 38.0) G. duodenalis assemblage E 12.0 (7.2, 18.5)a 4.0 (1.5, 8.5)b 5.6 (2.5, 10.7)b - - Not sequenced* 0 0 1.6 7.2 - Concurrent Cryptosporidium & Giardia 7.2 (3.6, 12.7)a 0.8 (0.1, 3.7)b 0.8 (0.1, 3.7)b 4.0 (1.5, 8.5)ab 12.8 (7.8, 19.5) Faecal shedding intensity in positive samples (oocysts per gram faeces) Cryptosporidium spp. Mean ± standard error 27 182 ± 13 462 48 732 ± 31 060 7325±8445 4841±1704 Range 216 – 238 325 1047 – 169 020 84-16 518 67-14 650 Giardia spp. Mean ± standard error 10 043±6441 485±200 354±370 2443±1130 Range 551-92 357 168-1247 36-988 36-9883 abc Point prevalence values in rows with different superscripts are significantly different (P<0.05). *Samples qPCR positive but not successfully sequenced.
106 3.4. Discussion
This is the first report of Cryptosporidium and Giardia genotypes from Australian rangeland goats. The key finding in the present study was that the pattern of
Cryptosporidium genotypes shed in faeces of rangeland goats changed over time following capture, transport and housing in a feedlot. The change in zoonotic genotypes identified occurred between arrival at the feedlot (C. ubiquitum) and after 3 months in the feedlot (C. parvum). This is also the first report of the zoonotic C. parvum IIaA17G4R1 genotype in goats. Giardia duodenalis assemblage E was also identified, and is potentially zoonotic. Faecal shedding of zoonotic Cryptosporidium and potentially zoonotic G. duodenalis has impacts for food safety and management of effluent to manage risk of contamination of water supplies (Robertson, 2009).
The impacts of Cryptosporidium and Giardia on goat meat productivity in goats postweaning age are not well described (O'Handley and Olsen 2006; Geurden et al.,
2010), but have been associated with reduced growth, carcase weight and carcase dressing efficiency in Australian sheep (Sweeny et al., 2012b; Jacobson et al., 2016). Both organisms are considered a primary pathogen associated with outbreaks of diarrhoea and deaths in goat kids, but asymptomatic infections are common in older animals (Koudela and Votovec 1998; de Graaf et al., 1999; O'Handley and Olsen 2006; Geurden et al.,
2010; Santin, 2013).
This is the first report for molecular characterisation of Cryptosporidium and
Giardia from goats in Australia. Two of the three Cryptosporidium species identified in this study, C. parvum and C. ubiquitum, are considered zoonotic and of public health importance. Cryptosporidium xiaoi has only been reported in two HIV-positive individuals in Ethiopia and is not considered a major zoonotic species (Adamu et al.,
2013). Cryptosporidium ubiquitum is an emerging zoonotic pathogen and has been
107 identified in human cases of cryptosporidiosis overseas (Li et al., 2014), but has not been identified in the limited typing of Australian human Cryptosporidium isolates reported to date. Subtyping at the gp60 locus identified C. ubiquitum subtype XIIa, which has been previously reported in goats (Li et al., 2014; Mi et al., 2014; Wang et al., 2014) and humans (Li et al., 2014), therefore is considered is a potentially zoonotic subtype.
The C. parvum subtype IIaA17G2R1 identified in the present study, has been previously reported in goats from China (Mi et al., 2014) and is a common subtype identified in humans in Australia (Waldron et al., 2011). The C. parvum IIaA17G4R1 subtype has not been previously reported in goats.
Giardia duodenalis assemblage E was the only assemblage identified at three loci in this study. Assemblage E has not been reported to date in Australian humans and was previously thought to be non-zoonotic, but has recently been found in humans, including
Australian humans (Foronda et al., 2008; Abdel-Moein and Saeed, 2016; Fantinatti et al.,
2016; Scalia et al., 2016; Zahedi et al., 2017b) and in one study in Egypt was detected in
62.5% of human samples (Abdel-Moein and Saeed, 2016) and therefore should be considered potentially zoonotic.
Shedding prevalence was highest at the first sampling occasion that occurred immediately after arrival at the feedlot. The peak in prevalence could be attributable to stress associated with trapping of the wild goats, mixing of unfamiliar animals, food deprivation, transport, mixing, or contaminated feed/water. Repeated shedding by individual goats was not common (2/125 goats), suggesting new infections were occurring in goats whilst housed in the feedlot. Furthermore, the longer goats were in the feedlot, the shedding of zoonotic C. parvum was more likely. Recommendations for management of goats in feedlots should emphasise design of water and feed troughs to minimise faecal contamination of feed and water to limit the spread of both protozoan parasites and bacteria of veterinary and zoonotic importance (More, 2002). Furthermore,
108 management of goat manure and effluent should also consider public health risks associated with Giardia and Cryptosporidium (Robertson, 2009).
3.5. Conclusion
Two zoonotic Cryptosporidium genotypes (C. ubiquitum and C. parvum) and the potentially zoonotic G. duodenalis assemblage E were identified in faeces from Western
Australian rangeland goats. Point prevalence for zoonotic C. ubiquitum was highest at the first sample collection following capture and transport to the feedlot, whereas point prevalence for zoonotic C. parvum was highest after goats had been housed in the feedlot for 3 months. New infections occurred in goats housed in the feedlot. The zoonotic C. parvum subtype IIaA17G4R1 was identified for the first time in goats. Faecal shedding of zoonotic Cryptosporidium and potentially zoonotic G. duodenalis has implications for food safety and effluent management.
109 CHAPTER 4. MORPHOLOGICAL AND MOLECULAR CHARACTERISATION OF THREE EIMERIA SPECIES FROM CAPTURED RANGELAND GOATS IN WESTERN AUSTRALIA
The contents of this chapter have been published in Veterinary Parasitology:
Regional Studies and Reports. The article can be found in Appendix 9.
This chapter describes the longitudinal prevelance and molecular characterisation of three identified Eimeira spp. from captured rangeland goats. Two molecular methods were used: (1) qPCR to determine the longitudinal prevalence of caprine Eimeria spp. and (2) nested PCR for molecular characterisation of Eimeria species using a combination of 18S rRNA and COI loci. It also provided morphomometric assessments of the species identified as a confirmation of the molecular methods utilised.
Research highlights:
First study to produce a longer (1,229 bp) 18S rRNA sequence of E. arloingi.
First study to produce COI caprine sequences.
First report for molecular characteristics of caprine-derived Eimeria spp. using a
combination of 18S rRNA and COI.
Molecular techniques offer some advantages over microscopy for identification
of Eimeria species, particularly with respect to precision.
Findings have implications for management of captured rangeland goats and
effluent.
110 Abstact: Faecal shedding of Eimeria by captured rangeland goats (Capra hircus) was investigated using a longitudinal observational study. Faecal samples were collected from
125 male goats on four occasions. The first sampling occurred following capture and transport, immediately after arrival at a commercial goat depot (feedlot) in Western
Australia, with subsequent 3 sample collections occurring at one month intervals thereafter. Goats were composite breed and aged approximately 9–12 months on arrival at the feedlot. Prevalence and shedding intensity (faecal oocyst concentration) for Eimeria were determined using qPCR. Species were identified from individual oocysts (isolated using micromanipulation) using molecular analysis at two loci, specifically 18S rRNA and mitochondrial cytochrome oxidase gene (COI), and confirmed by microscopy.
Longitudinal prevalence (animals positive at least once) for Eimeria spp. by qPCR was
90.4%, with 60% goats shedding Eimeria spp. on more than one occasion. Point prevalence (prevalence at a single sampling occasion) ranged from 2.4% (fourth sampling) to 70.4% (second sampling). Three species were identified at the 18S rRNA locus and confirmed by microscopy: E. christenseni (longitudinal prevalence for single infection 34.4%), E. hirci (17.6%) and E. arloingi (8.8%) over the four sample collections. Mixed infections were identified in 56.8% goats (longitudinal prevalence).
18S rRNA sequences from E. christenseni and E. hirci were 100% homologous with ovine E. ahsata and E. crandallis respectively, and E. arloingi was 100% similar to caprine E. arloingi. At the COI locus, E. christenseni, E. hirci and E. arloingi grouped separately, and were closely related to ovine E. ahsata, with genetic similarities of 96.5%,
92.6% and 91.4% respectively. This is the first report for molecular characteristics of caprine-derived Eimeria spp. using a combination of 18S rRNA and COI. Molecular techniques can be used to identify Eimeria spp. in goat faecal samples, specifically through characterization at 18S locus and other gene loci when used in parallel. Molecular
111 techniques offer some advantages over microscopy for identification of Eimeria species, particularly with respect to precision.
4.1. Introduction
Strong growth in the Australian goat meat industry has been largely based on rangeland goats (Meat and Livestock Australia, 2015). Rangeland goats are trapped, transported and may be managed under intensive management in feedlots (goat depots) for variable periods prior to slaughter. Diarrhoea and ill-thrift are cited as major issues in captured rangeland goats (Meat and Livestock Australia, 2016), yet relatively little is known about the underlying causes. Coccidiosis caused by Eimeria spp. and associated with stress of capture, transport, overcrowding and domestication of rangeland goats has been suggested as a cause of diarrhoea and ill thrift in captured goats (Meat and Livestock
Australia, 2016), but the epidemiology of Eimeria spp. in rangeland goats is not well described. Ten Eimeria species have been reported from domestic and wild goats in
Australia, based on microscopic examination of faeces; E. ninakohlyakimovae, E. arloingi (considered homologous with ovine E. bakuensis), E. hirci (considered homologous with ovine E. crandallis), E. christenseni (considered homologous with ovine E. ahsata), E. alijevi, E. caprina, E. caprovina, E. jolchijevi, E. apsheronica and E. paltida have been identified (Kanyari, 1988; O'Callaghan, 1989). Many Eimeria infections in goats are asymptomatic; however, some species have been associated with diarrhoea and stunted growth (Chartier and Paraud, 2012; Ruiz et al., 2012). Of the 16
Eimeria species described in goats worldwide, E. ninakohlyakimovae and E. arloingi are considered the most pathogenic (Koudela and Boková, 1998; Cavalcante et al., 2012;
Chartier and Paraud, 2012; Khodakaram-Tafti et al., 2013). Identification of Eimeria spp. has traditionally been made on the basis of the morphological characteristics of the sporulated oocysts and host specificity. However, morphological techniques have been
112 described as having relatively low sensitivity, and practical limitations associated with the time (Carvalho et al., 2011a, 2011b), labor, and training required for microscopy
(Khodakaram-Tafti et al., 2013). Furthermore, the morphological similarity of oocysts of some Eimeria spp. is a limitation in supporting (or refuting) identification based on microscopy alone (Tenter et al., 2002; Haug et al., 2007; Kawahara et al., 2010; Hatam-
Nahavandi et al., 2016). For example, Eimeria spp. from goats and sheep may be morphologically identical, but cross infection studies (demonstrating patent infections in naïve animals following infection) are required to confirm host specificity. Molecular tools can address limitations with respect to sensitivity and unambiguous identification of Eimeria spp., and have been used to describe the epidemiology of Eimeria spp. in
Australian sheep (Yang et al., 2014). The 18S rRNA locus has been used extensively as a molecular marker in phylogenetic analysis. As it is a conservative gene, the 18S may not be the most suitable gene for differentiating closely related Eimeria species and therefore this locus should be used in parallel with other gene loci for characterization of
Eimeria spp. (Ogedengbe et al., 2011).
The aim of the present study was to describe the species of Eimeria from captured rangeland goats managed under typical conditions for meat production in Western
Australia using molecular and morphological tools. The hypothesis tested was that molecular techniques can be used to identify Eimeria spp. in goat faecal samples.
4.2. Materials and methods
4.2.1. Animals and faecal sample collection
This was a longitudinal observational study with 125 male rangeland goats
(composite breed) sampled once monthly for four months (S1 to S4) commencing
February 2014. Goats were captured from a sheep and cattle extensive rangeland grazing property, North Wooramel station, located 78 km east of Denham and 113 km south east
113 of Carnarvon in the Gascoyne region of Western Australia. The first sample collection
(S1) occurred immediately after transport and arrival at a commercial goat depot (feedlot) near Geraldton, Western Australia, where goats were housed for the duration of the study.
On arrival at the feedlot (S1), goats weighed 30.7 ± 0.3 kg (mean ± standard error) with an estimated age of 9–12 months based on dentition. Goats were housed in four group pens (approximately 30 goats per pen). Grainbased pellets, hay and water were supplied ad libitum. Straw-bedding was provided with bare dirt covering the majority of available pen space. No pasture was available for the duration of the study. Goats were consigned for slaughter after conclusion of the experiment when they reached acceptable slaughter weight. Faecal samples were collected directly from the rectum and stored on ice or in a refrigerator (4.0 °C) until DNA extraction or sporulation for microscopy were performed.
Sample collection methods were approved by Murdoch University Animal Ethics
Committee (approval number R2617/13).
4.2.2. Treatments
All goats were treated with an anthelmintic, 0.4 mg/kg moxidectin (Cydectin oral plus selenium®, Virbac Australia), and an anti-coccidial treatment (20 mg/kg toltrazuril,
Baycox®, Bayer Australia) immediately after the first (S1) and second (S2) sampling as part of the standard management practice for goats being introduced to the feedlot.
4.2.3. DNA isolation
For each faecal sample (n=500), four freeze–thaw cycles were employed followed by genomic DNA extraction for 200 mg faeces from each faecal sample (n=500).
Extractions were performed using a Power Soil DNA Kit (MolBio, Carlsbad, California), which included a mechanical bead disruption step using glass beads to increase the efficiency of DNA extraction. A negative control (no faecal sample) was used in each extraction group.
114 4.2.4. qPCR screening and quantification
All faecal samples (n=500) were screened by qPCR at the 18S ribosomal RNA
(rRNA) locus (section 2.7.3), and oocyst concentrations in faecal samples (oocyst per gram of faeces) were determined by qPCR as previously described (Yang et al., 2014c).
4.2.5. PCR amplification and sequencing at the 18S rRNA locus
All qPCR Eimeria positive samples (n=210) were subjected to a two-step PCR at the 18S locus which was used for the molecular genotyping of Eimeria species using the primers EiGTF1 and EiGTR1 (Yang et al., 2016) for the external PCR and the primers
EiGTF2 and EiGTR2 (Yang et al., 2015) for the internal reaction (section 2.8.14). The expected PCR product was ∼1510 bp. However, this process yielded mixed chromatograms for some samples (n=100).
4.2.6. Isolation of morphologically similar Eimeria spp. oocysts using a micromanipulator
Morphologically identical sporulated Eimeria oocysts were isolated from all qPCR positive faecal samples, including single infections (n=110) and samples that produced mixed chromatograms (n=100) via sequencing of nested 18S PCR amplicons as described above. The process used for sporulation is described in more detail below
(Section 4.2.9). Sporulated oocysts were examined by microscopy, and a 3 axis hydraulic micromanipulator (MO-102, Nirashige, Japan) was used to select four morphologically similar Eimeria spp. oocysts from each faecal sample. Where multiple morphotypes were observed (i.e. mixed infections), four oocysts of each morphotype were selected and transferred to separate slides as described above. The morphologically similar oocysts
(n=4 per morphotype) isolated from each qPCR positive faecal sample were transferred to a new slide, examined and photographed using microscopy (Olympus DP71 digital
115 micro-imaging camera) to confirm morphological similarity. Measurements were recorded for species identification based on morphological characteristics (Section 4.2.9).
4.2.7. DNA extraction from isolated oocysts
Morphologically similar Eimeria spp. oocysts (n = 4 oocysts per morphotype), isolated from each qPCR positive faecal sample were transferred into a PCR tube containing 10 μl of lysis buffer (0.005% SDS in TE solution) by washing the coverslip with 100 μl saline. After a brief centrifugation, the tube was frozen in liquid nitrogen and thawed in a 95 °C water bath for four rounds to disrupt the oocyst walls. After the addition of 0.5μl proteinase K (20mM), the tube was incubated at 56 °C for 2 h and then at 95 °C for 15min. The entire lysate of the morphologically similar oocysts was used for two separate PCRs (18S rRNA and COI) as described below (Section 4.2.8).
4.2.8. PCR amplification and sequencing of isolated oocysts at the 18S and COI loci
PCR amplification at the 18S rRNA locus was conducted as previously described
(Section 4.2.5) on the DNA extracted from the morphologically similar Eimeria spp. isolated oocysts (Section 4.2.6) of the faecal samples initially screened positive by qPCR.
A partial mitochondrial cytochrome oxidase gene (COI) gene sequence (723 bp) was amplified using a nested PCR with the following primers COIF1 (Ogedengbe et al., 2011) and COXR1 (Dolnik et al., 2009) for the external reaction and COIF2 (Yang et al., 2013b) and COXR2 (Dolnik et al., 2009), for the internal reaction.
The amplified DNA fragments from the secondary 18S rRNA and COI PCR products were separated by gel electrophoresis and purified using an in-house filter tip method and used for sequencing without any further purification as previously described
(Yang et al., 2013a). The results of the sequence reactions were analysed and edited using
FinchTV (Version 1.4), compared to existing Eimeria spp. 18S and COI sequences on
116 GenBank using BLAST searches and aligned with reference genotypes from GenBank using ClustalW in BioEdit (V7.2.5) (www.mbio.ncsu.edu/bioedit/).
4.2.9. Phylogenetic analysis of Eimeria spp.
Phylogenetic trees were constructed for Eimeria spp. at the 18S rRNA and COI loci with additional isolates from GenBank. Distance estimation was conducted using
TREECON (Van de Peer and De Wachter, 1994), based on evolutionary distances calculated with the Tamura–Nei model. Parsimony and Maximum Likelihood (ML) analyses were conducted using Molecular Evolutionary Genetics Analysis software
(MEGA version 6) (Tamura et al., 2013). Bootstrap analyses were conducted using 1000 replicates to assess the reliability of inferred tree topologies.
4.2.10. Speciation based on morphological characteristics
Morphological characteristics for sporulated oocysts were determined for faecal samples that were qPCR positive (Section 4.2.4). Approximately 2 g faeces were placed in 2% (w/v) potassium dichromate solution (K2Cr2O7), mixed well and poured into petri dishes to a depth of < 1 cm and kept under close observation at room temperature in the dark to facilitate sporulation. Faecal flotation was conducted using a saturated sodium chloride and 50% sucrose (w/v) solution (Soulsby, 1982). A sample from the supernatant layer was transferred to a slide. Sporulated oocysts were observed using an Olympus
DP71 digital micro-imaging camera and images were taken using Nomarski contrast imaging system with a 100× oil immersion objective. Morphological features were recorded and measurements were performed on oocysts (n=35) of each identified Eimeria species based on morphological similarity. All measurements are given in micrometres
(μm) as the mean followed by the range in parentheses. Minor shape variations were observed. The number of oocyst cell wall layers was confirmed by crushing individual
117 oocysts with gentle coverslip pressure. Species were differentiated by reference to the descriptions given by Honess (1942), Levine et al. (1962a) and Shah and Joshi (1963).
4.2.11. Statistical analyses
Goats were classified as positive (parasite DNA detected) or negative (no parasite
DNA detected) separately for Eimeria (all species), E. arloingi, E. christenseni, E. hirci or mixed infection (more than one Eimeria spp.). Point prevalence was determined by proportion of positive goats for each sample occasion. Longitudinal prevalence was calculated as the proportion of goats with Eimeria DNA detected on at least one occasion.
Prevalence 95% confidence intervals were calculated using Jeffrey's interval method
(Brown et al., 2001). Goats were categorised for frequency of Eimeria detection across the four sampling occasions (i.e. positive on 0, 1, 2, 3 or 4 occasions). Two-tailed Z tests
(Sergeant, 2016) were used to compare point prevalence between sampling occasions, and proportion of goats for each frequency of Eimeria detection across the four sampling occasions (i.e. positive on 0, 1, 2, 3 or 4 occasions). P-values of 0.05 were used to declare statistical significance. Faecal shedding intensity was log transformed for analysis using
LOG10 (OPG + 1). Differences in Eimeria spp. shedding intensity between time points were assessed using a univariate general linear model (SPSS Statistics for Mac version
21, IBM) with timepoint included as a fixed factor and least squares difference post hoc test. P-values of 0.05 were used to declare statistical significance.
4.3. Results
4.3.1. Observed prevalence and shedding intensity of Eimeria spp. using qPCR and genotyping at 18S rRNA locus
Overall, 210/500 faecal samples were qPCR positive for Eimeria spp., and
191/210 qPCR positive samples were successfully sequenced. Single infections with three Eimeria species were identified in samples successfully sequenced at 18S rRNA
118 locus; E. christenseni (53/191), E. hirci (23/191) and E. arloingi (15/191). Infections with mixed Eimeria spp. were identified in 100/191 successfully sequenced samples at 18S rRNA locus. The prevalence and shedding intensity for single and mixed Eimeria spp. infections are shown in Table 4.1.
119 Table 4.1. Eimeria spp. prevalence and shedding intensity observed for captured rangeland goats (n=125) sampled on 4 occasions (S1-S4).
Sampling occasion Longitudinal S1 S2 S3 S4 prevalence Prevalence (% (95% confidence interval)) Eimeria spp. # 50.4 (41.7, 59.1)a 70.4 (62.0, 77.9)b 44.8 (36.3, 53.6)a 2.4 (0.7, 6.3)c 90.4 (84.3, 94.6) Single infections## 20.8 (14.4, 28.5)a 34.4 (26.5, 43.0)b 16.8 (11.0, 24.1)a 0.8 (0.1, 3.7)c 54.4 (45.7, 62.9) E. christenseni 12.0 (7.2, 18.5)a 19.2 (13.0, 26.8)b 11.2 (6.6, 17.6)a 0 (0, 2.0)c 34.4 (26.5, 43.0) E. hirci 6.4 (3.1, 11.7)a 8.8 (4.8, 14.7)a 2.4 (0.7, 6.3)ac 0.8 (0.1, 3.7)c 17.6 (11.7, 25.0) E. arloingi 2.4 (0.7, 6.3)ac 6.4 (3.1, 11.7)a 3.2 (1.1, 7.4)a 0 (0, 2.0)c 8.8 (4.8, 14.7) Mixed infections## 24.0 (17.2, 32.0)a 30.4 (22.9, 38.8)a 24.0 (17.2, 32.0)a 1.6 (0.3, 5.0)b 56.8 (48.0, 65.2) E. christenseni + E. hirci 3.2 (1.1, 7.4)a 6.4 (3.1, 11.7)a 1.6 (0.3, 5.0)ab 0 (0, 2.0)b 10.4 (5.96, 16.6) E. christenseni + E. arloingi 2.4 (0.7, 6.3)a 1.6 (0.3, 5.0)a 2.4 (0.7, 6.3)a 0.8 (0.1, 3.7)a 7.2 (3.6, 12.7) E. hirci + E. arloingi 3.2 (1.1, 7.4)a 0.8 (0.1, 3.7)ab 0.8 (0.1, 3.7)ab 0 (0, 2.0)b 3.2 (1.1, 7.4) E. christenseni + E. hirci + E. arloingi 15.2 (9.7, 22.3)a 21.6 (15.1, 29.4)a 19.2 (13.0, 26.8)a 0.8 (0.1, 3.7)b 44.0 (35.5, 52.8) Species prevalence (single + mixed infections) E. christenseni 32.8 (25.0, 41.4)a 48.8 (40.1, 57.5)b 34.4 (26.5, 43.0)a 1.6 (0.3, 5.0)c 74.4 (66.3, 81.4) E. hirci 28.0 (20.7, 36.3)ab 37.6 (29.5, 46.3)a 24.0 (17.2, 32.0)b 1.6 (0.3, 5.0)c 63.2 (54.5, 71.3) E. arloingi 23.2 (16.5, 31.2)a 30.4 (22.9, 38.8)a 25.6 (18.6, 33.7)a 1.6 (0.3, 5.0)b 54.4 (45.7, 62.9) Not sequenced* 5.6 5.6 4.0 0 – Faecal shedding intensity (oocysts per gram) All samples (mean ± SE) 530±183a 10525±2496b 350±88a 1±1c Positive samples only (mean ± SE) 1051±352a 15,851±3627b 841±193a 31±21a All samples (range) 0–15,908 0–191,821 0–5375 0–73
120 abc Point prevalence (z test) and mean shedding intensity (LSD post hoc test, faecal oocyst count log transformed for analysis) values in rows with different superscripts are significantly different (P<0.05). # Eimeria DNA identified using qPCR. ## Based on sequencing at 18S rRNA locus. *Samples qPCR positive but not successfully sequenced at 18S rRNA locus. SE: standard error.
121 Frequencies of Eimeria detection over the four sampling occasions are shown in
Table 4.2. Over the four sample collections, 60% (75/125) of goats were shedding
Eimeria spp. on more than one occasion. More goats were shedding on two of the four sampling occasions (53/125) than either one occasion (38/125) or three occasions
(22/125; Table 4.2). No goats were identified as shedding Eimeria spp. on more than three occasions. Mixed Eimeria spp. infections, single E. christenseni infections, single E. hirci infections were all more commonly identified on one occasion compared with two or three occasions.
Table 4.2. Frequency of detection of Eimeria spp. shedding in 125 rangeland goats.
Frequency of detection of Eimeria (n) 0 1 2 3 4 Eimeria spp. 12a 38b 53c 22a 0d Single infections
E. christenseni 82a 35b 6c 2cd 0d E. hirci 103a 21b 1c 0c 0c E. arloingi 114a 8b 2bc 1c 0c Mixed infections 54a 46a 21b 4c 0d abc Frequency values in rows with different superscripts are significantly different (two tailed, P<0.05).
4.3.2. Phylogenetic analysis of three Eimeria spp. at the 18S rRNA locus
A 1229 bp PCR product of E. christenseni and E. hirci and E. arloingi, was successfully amplified and sequenced. Phylogenetic analyses of these species at the 18S locus using Distance, Parsimony and ML analyses produced similar results (Fig. 4.1a, distance tree shown). Eimeria christenseni from rangeland goats grouped in a clade with
E. ahsata (AF338350) with 100% homology, and E. hirci from rangeland goats grouped in a clade with E. crandallis (AF336339) with 100% homology (Fig. 4.1a), both of which were from domestic sheep (Ovis aries) in Turkey (Kaya et al., 2007). The single available
122 goat-derived E. arloingi 18S sequence on GenBank (KC507792) was only 637 bp in length and therefore an insert tree (Fig. 4.1b) was generated to compare the 18S rRNA sequences from E. arloingi, E. hirci and E. christenseni. This analysis revealed that E. arloingi from rangeland goats in the present study was 100% identical to E. arloingi
(KC507792) from Iranian native goat kids (Capra hircus) (Khodakaram-Tafti et al.,
2013).
123
E. adenoeides KC305182 89, 82, 76 E. adenoeides KC305185 84, 90, _ A E. meleagridis HG793040 62, 68, 65 E. sp. meleagris gallopavo HM117011 53, 57, 54 E. tenella EU025113 E. pavonina JN596589 76, 69, 74 E. acervulina U67115 74, 80, _ E. sp. alectoris graeca HM070378 92, 81, 90 E. sp. ex numida meleagris KJ547707 E. sp. ex phasianus colchicus KJ547706 82, 75, 88E. dispersa HG793041 64, 86, _ E. purpureicephali KU140597 E. innocua HG793045 74, 84, 82 E. sp. ex apodemus agrarius JQ993655 E. myoxi JF304148 84, 88, 81E. brasiliensis KU351728 91, 94, _ E. alabamensis AB769556 E. bukidnonensis AB769601 92, 95, 97E. bukidnonensis AB769599 E. bukidnonensis AB769595 83, 80, 89E. auburnensis AB769571 81, 80, 86E. pellita KU351731 B 85, 84, 90 E. wyomingensis AB769654 E. canadensis AB769610 81, 86, 86 E. cylindrica AB769616 E. christenseni rangeland goat KX84568 E. faurei AF345998 63, _, _ E. ahsata AF338350 74, 77, 83 E. hirci rangeland goats KX845685 E. crandallis AF336339 E. arloingirangeland goats KX845686 72, 79, 80 E. weybridgensis AY028972 E. arloingi KC507792 94, 97, 85 E. christenseni rangeland goats KX845684 E. ahsata AF338350 95, _, 97E. hirci rangeland goats KX845685 E. arloingirangeland goats KX845686 E. crandallis AF336339 E. zuernii KT184356 66, _, _ 83, 86, 88 E. zuernii KU351737 Toxoplasma gondii L24381 E. illinoisensis KU351730 E. bovis KT184336 99, 100, 82E. ovinoidalis AF345997 0.02 E. ellipsoidalis AB769634 Toxoplasma gondii L24381
0.01
Figure 4.1 (a) and (b). Evolutionary relationships of Eimeria spp. inferred by distance analysis of using 18S rRNA gene. Accession numbers of samples follow the species name. Percentage support (> 50%) from 1000 pseudoreplicates from distance, ML and parsimony analysis, respectively, is indicated at the left of the support node (dash (−) = value was < 50%).
The 18S rRNA nucleotide sequences of the three Eimeria spp. from the rangeland goats in the present study were deposited in GenBank under the accession numbers
KX845684 (E. christenseni), KX845685 (E. hirci) and KX845686 (E. arloingi).
4.3.3. Phylogenetic analysis of the three Eimeria spp. at the COI locus
Phylogenetic analysis of the 670 bp COI sequence placed E. christenseni from rangeland goats in the same clade with ovine E. ahsata (KT184373) from Canada
124 (Ogedengbe et al., 2016) (Fig. 4.2). Eimeria christenseni, E. hirci and E. arloingi from rangeland goats exhibited 96.5%, 92.6% and 91.4% genetic similarity respectively with ovine E. ahsata (KT184373). The partial COI nucleotide sequences from these three
Eimeria spp. from rangeland goats were deposited in GenBank under the accession numbers KX857468 (E. christenseni), KX857469 (E. hirci) and KX857470 (E. arloingi).
125
(93,_,98) E. falciformis HM771682 50,_68 Ei. sp. ex apodemus agrarius JQ993702 63,_,72 E. sp. ex apodemus sylvaticus JQ993707 99,_99 E. sp. ex apodemus agrarius JQ993700 95,55,95 E. nafuko JQ993708 100,_100 E. burdai JQ993709 88,62,90 E. lancasterensis KT361039 75,54,73 E. tamiasciuri KT184375 Isospora manorinae KT224377 98_99 E. magna KF419217 95,61,96 94,65,96 E. intestinalis JQ993693 95,56,99 E. irresidua JQ993694 98,50,71 E. piriformis JQ993698 72_,71) E. exigua JQ993691 E. sp. alectoris graeca HM117020 E. cahirinensis JQ993686 _63,_ E. macusaniensis KU215889 E. arloingi rangeland goats KX857470 _,60,_ E. hirci rangeland goats KX857469 98,_100 89,_,98 E. christenseni rangeland goats KX857468 88,_93 E. ahsata KT184373 88,_97 E. bovis KT184372 100_,100 E. zuernii HM771687 E. sp. RY-2016a KT305929 E. innocua HG793049 90,59,_ 95,53,100 E. purpureicephali KU140598 E. dispersa KJ608416 85,52,98E. dispersa HG793048 99,_100 E. acervulina EF158855 E. acervulina FJ236420 E. acervulina FJ236428 E. brunetti HM771675 E. mitis FR796699 Toxoplasma gondii KM657810 0.2
Figure 4.2. Evolutionary relationships of Eimeria spp. inferred by distance analysis of the cytochrome c oxidase subunit I (COI) gene. Accession numbers of samples follow the species name. Percentage support (> 50%) from 1000 pseudoreplicates from distance, ML and parsimony analysis, respectively, is indicated at the left of the support node (dash (−) = value was < 50%).
4.3.4. Morphology of three Eimeria spp. by microscopy
Morphological characteristics of oocysts and sporocysts are shown in Tables 4.3 and 4.4. Oocyst sporulation was achieved within 48–72 h at room temperature. Except for the absence of the polar granules in the examined sporulated oocysts, the morphological features (shape and size) of the oocysts and sporocysts from the three identified Eimeria spp. were consistent with ranges previously reported for the respective
126 species (Tables 4.3 and 4.4), and morphological species identification was consistent with the species identification by sequencing. All Eimeria oocysts examined in the present study had bi-layered oocyst walls and possessed micropolar caps, which were more prominent in E. arloingi compared with those of E. christenseni and E. hirci (Fig. 4.3a).
No polar granules (Table 4.3) or Stieda bodies (Table 4.4) were observed. A sporocyst residuum was present in all three species (Table 4.4), with more obvious shattered granules for E. arloingi and E. christenseni (Fig. 4.3, a and b). Minor shape variations were observed.
Figure 4.3. Nomarski interference-contrast photomicrographs of the Eimeria oocysts from rangeland goats; E. arloingi (A), E. christenseni (B) and E. hirci (C) showing oocyst wall (OW), micropolar cap (MC), sporozoites (SP), and sporocyst residuum (SR). Scale bar= 20 μm.
127 Table 4.3. Oocyst morphological features for Eimeria spp. from rangeland goats compared with previous reports.
Oocyst Size
mean (range) μm Species (synonymous Shape index Host Shape Height Width Wall Micropolar cap Polar granule Reference names) mean (range) E. christenseni a ellipsoid– 34.5 23.3 1.5 Observed Goat bi-layered present absent ovoid* (28.9–35.8) (16.4-25.8) (1.2–1.8) 33.4 22.6 1.48 Previously reported Sheep ellipsoid bi-layered N/A present Honess (1942) (29–37) (17-28) (1.2–1.8) E. hirci b ellipsoid– 20.7 18.2 1.14 Observed Goat bi-layered present absent ovoid* (17.4–23.4) (16.8-22.2) (1.04–1.2) broadly 21.9 19.4 1.11 Previously reported Sheep ellipsoid– bi-layered present N/A Honess (1942) (17–23) (17-22) (1.00–1.35) ovoid E. arloingi c ellipsoid– 28.3 20.1 1.41 Observed Goat bi-layered prominent absent ovoid* (23.4–29.2) (18.4–21.2) (1.23–1.59) ellipsoid– 28 20 1.4 Previously reported Goat slightly bi-layered present present Levine et al. (1962a) (22–31) (17-22) (1.3–1.6) ovoid ellipsoid– 28 21 1.4 Goat bi-layered present present Shah and Joshi (1963) ovoid (22–35) (18-26) (1.3–1.6) aE. ahsata has been considered synonymous with E. christenseni and has been redescribed in domestic sheep with slightly larger measurements (Levine et al., 1962b). b E. crandallis has been considered synonymous with E. hirci (Chevalier, 1966). cE. bakuensis has been considered synonymous with E. arloingi (Chevalier, 1966). *although majority of E. arloingi were ellipsoid and E. christenseni and E. hirci were ovoid, minor shape variation occurred within species.
128 Table 4.4. Sporocyst morphological features for Eimeria spp. from rangeland goats compared with previous reports. Sporocysts
Size mean (range) μm Species (synonymous Host Shape Height Width Stieda body Residuum Reference names) E. christenseni a Observed Goat broadly elongate– 15.4 8.6 absent present** ovoid (13.9–17.7) (8.1-10.5) Previously reported Sheep elongate– ovoid 15.4 7.81 N/A present Honess (1942) (n/a) (n/a) E. hirci b Observed Goat slightly ovoid-round 9.2 6.6 absent present*** (8.1–10.8) (5.9-8.3) Previously reported Sheep ovoid 9. 5 6.4 N/A N/A Honess (1942) (8–11) (5-8) E. arloingi c Observed Goat elongate ovoid 13.8 8.2 absent present** (11.7–15.7) (7.0–9.8) Previously reported Goat elongate ovoid 14 8 (6-8) absent present Levine et al. (1962a) (12–16) Goat elongate ovoid 13 8 (6-10) absent present Shah and Joshi (1963) (11–17) aE. ahsata has been considered synonymous with E. christenseni and has been redescribed in domestic sheep with slightly larger measurements (Levine et al., 1962b). b E. crandallis has been considered synonymous with E. hirci (Chevalier, 1966). cE. bakuensis has been considered synonymous with E. arloingi (Chevalier, 1966). **numerous granules in a spherical mass. ***few granules in a spherical mass.
129 4.4. Discussion
This study is the first to describe a combination of morphological and molecular characteristics for Eimeria species from Australian rangeland goats. Three Eimeria spp. were identified at the 18S and COI loci (E. christenseni, E. hirci and E. arloingi).
Morphological characteristics of oocysts were consistent with previous reports, and confirmed sequencing results. Observations supported the hypothesis tested that molecular techniques can be used to identify Eimeria spp. in goat faecal samples, specifically, through characterisation at 18S locus and other gene loci when used in parallel. Molecular techniques offer some advantages over microscopy for identification of Eimeria species, particularly with respect to precision for species identification. The molecular techniques confirmed that Eimeria shedding was common in the captured goats, with over 90% of goats at the feedlot shedding Eimeria spp. on at least one sampling occasion. Mixed infections were identified in 57% of goats.
The three Eimeria spp. identified in this study have all been previously reported in Australian rangeland goats (O'Callaghan, 1989). All three Eimeria spp. are considered pathogenic in goats (Andrews, 2013), although to a lesser extent compared to E. ninakohlyakimovae, which was not identified in the present study. Eimeria christenseni has been associated with severe diarrhoea, anorexia, polydipsia, poor hair coat, and extreme weakness in neonatal goat kids (Lima, 1981). Eimeria hirci (ovine homologous
E. crandallis) is considered pathogenic in goats, but the lesions and pathology caused have not been completely delineated (Taylor et al., 2016). Eimeria crandallis (caprine homologous E. hirci) resulted in loss of surface epithelial cells, villous atrophy, crypt destruction and severe diarrhoea when experimentally inoculated into lambs up to 3 months of age (Gregory and Catchpole, 1990; Taylor et al., 2003). Eimeria arloingi has
130 been associated with both subclinical and clinical coccidiosis and subsequent production losses (Jalila et al., 1998; Koudela and Boková, 1998).
Mixed Eimeria spp. infections were commonly identified at the first three sampling occasions. The pathogenicity of mixed infection in rangeland goats has yet to be tested, but previous studies in sheep have shown that mixed Eimeria infections extend patency and increase oocyst production, which may aggravate the overall effect of infection (Catchpole et al., 1976). Similarly, co-infections with other parasites and bacteria may exacerbate clinical outcome of infection in sheep and goats (Foreyt, 1990;
Glastonbury, 1990; Rahman, 1994; Navarre and Pugh, 2002; Andrews, 2013), therefore the role of Eimeria spp. in conjunction with other infectious agents on diarrhoea and ill thrift in captured rangeland goats should be addressed in future studies.
Eimeria prevalence and shedding intensity determined by qPCR were highest at the second sampling occasion, approximately one month after capture, transport and arrival at the feedlot. It was not possible to determine specific factors that contributed to the rise in prevalence and shedding intensity observed between arrival (S1) and S2, but stress associated with transport, mixing of animals and confinement of undomesticated goats are possible causes (Main and Creeper, 1998). This observational study likely failed to identify peak shedding intensity for Eimeria as a consequence of the one-month interval between S1 (immediately after capture and transport) and S2. Kommuru et al.
(2014) reported increased oocyst counts in goat kids (16 weeks of age) one week after weaning, transport and change of housing from pasture to pens, but oocyst counts then steadily decreased for the following four weeks (Kommuru et al., 2014). Severe (often fatal) coccidiosis following mustering and transport has been reported in Western
Australian rangeland goats, with onset of clinical signs 5–7 days after entering feedlot
(Main and Creeper, 1998).
131 It is possible that the two anti-coccidial treatments given immediately after the first (S1) and second (S2) sampling impacted the prevalence and shedding intensity of
Eimeria spp., particularly for those species with longer pre-patent period. These treatments were given as part of the normal husbandry at the feedlot. Despite treatment, both prevalence and intensity of Eimeria shedding increased between S1 and S2 (i.e. one month after the first treatment) and declined between S2 and S3 (i.e. one month after the second treatment). Coccidiosis in goats is generally self-limiting. Given the increase in prevalence and shedding intensity of Eimeria observed at S2 (one month after the first toltrazuril treatment), the fall in prevalence and shedding intensity of Eimeria observed between S2 and S3 (i.e. one month after the second treatment) was more likely attributable to goats acquiring immunity following exposure to infection, than to any effect of treatment. Variable effects of toltrazuril on Eimeria shedding by goats have been reported. For example, Iqbal et al. (2013) reported 100% reduction in oocyst shedding 28 days following a single toltrazuril treatment (20 mg/kg) in 1–3-month-old goats housed in group pens, whereas Chartier et al. (1992) reported a reduction in faecal oocyst counts for only 14 days following single treatment (20 mg/kg) in 4–6-month-old goats housed in group pens. Further investigation into whether toltrazuril is effective in reducing
Eimeria shedding, the duration of response to treatment, and whether treatment is effective in reducing clinical coccidiosis is warranted before recommendations can be made with respect to use of toltrazuril in captured rangeland goats. The further reduction in oocyst counts is likely due to acquisition of immunity (Ruiz et al., 2013).
Except for the absence of the polar granules in the examined sporulated oocysts from rangeland goats, the other morphological characteristics of oocysts and sporocysts of the identified species were consistent with previous reports. Polar granules were reported in E. christensni (syn. E. ahsata) (Honess, 1942) and E. arloingi (syn. E. bakuensis) (Levine et al., 1962a; Shah and Joshi, 1963), however none of the authors
132 reported whether their observations of the polar granules were made on fully sporulated oocycts or not. Levine and Ivens (1981) reported the disappearance of polar granules of some Eimeria spp. after sporulation.
Identification of Eimeria species based on morphological characteristics was consistent with identification by sequencing. The combined use of morphological and molecular tools offers advantages in confirming Eimeria spp. identification (Kawahara et al., 2010; Hatam-Nahavandi et al., 2016), particularly with respect to speciation for morphologically similar Eimeria spp. oocysts in faecal samples. For example, E. crandallis (described in goats) and E. weybridgensis (described in sheep) share similar morphological characteristics, with only minor differences evident following sporulation.
Molecular tools can be used to confirm identification of morphologically similar oocysts from different hosts (for example sheep and goats) to determine if they are genetically identical (same species), or different species that are morphologically similar, without the need for cross infection studies.
This is the first study to report characterisation of Eimeria spp. from goats using both 18S and COI loci. Using the 18S locus and other gene loci in parallel improves precision for molecular characterisation. The 18S locus has been extensively used as a molecular marker in a plethora of phylogenetic analysis; however, as the 18S gene is highly conserved, the COI locus was also included as it has been shown to have higher resolving power for Eimeria spp., especially with respect to recent speciation events
(Ogedengbe et al., 2011).
The phylogenetic analysis at the 18S locus revealed that E. christenseni and E. hirci from rangeland goats were identical to ovine homologous E. ahsata (AF336339) and E. crandallis (AF338350) from domestic sheep in Turkey (Kaya et al., 2007), and clustered together on a single clade. This was consistent with reports that some Eimeria species, including E. ahsata and E. crandallis, may infect both goats and sheep
133 (Vercruysse, 1982; More et al., 2015). Both E. ahsata and E. crandallis have been reported in Australian sheep using molecular identification (Yang et al., 2014).
The present study is the first to produce a longer (1229 bp) 18S rRNA sequence of E. arloingi. Sequence comparison of this species was not possible due to the non- availability of longer 18S sequences in GeneBank. Therefore, only 673 bp of common sequence overlap was used to conduct the comparison with E. arloingi (KC507792). The sequence for E. arloingi from rangeland goats in the present study was identical to an 18S sequence from E. arloingi reported in goats in Iran (Khodakaram-Tafti et al., 2013).
Goat-derived sequences were not available in GenBank at the COI locus except for one E. ahsata sequence from domestic sheep. Sequences from E. christenseni, E. hirci and E. arloingi exhibited 96.5%, 92.6% and 91.4% genetic similarities respectively with ovine E. ahsata (KT184373), which is within the range of accepted species and suggests that the COI gene is a suitable locus for differentiating closely Eimeria related species in small ruminants. As more sequences from small ruminants become available in GenBank, phylogenetic analysis of the COI locus will be able to provide more meaningful information on relationships between caprine and ovine Eimeria species. Analyzing the isolates at multiple loci will provide a more in-depth analysis of the evolution of caprine- derived Eimeria spp.
4.5. Conclusion
In conclusion, three Eimeria spp. (E. christenseni, E. hirci and E. arloingi) were identified from captured rangeland goats at the 18S and COI loci, and this was confirmed with morphological characteristics of oocysts. To our knowledge the present study reports the first combination of 18S and COI genes for molecular characterisation of Eimeria species in goats. Molecular methods offer improved precision for species identification for oocysts, and may be used to determine whether morphologically identical Eimeria
134 spp. from different hosts are genetically similar (same species) or different species with similar morphological characteristics, without the need for cross infection studies.
Molecular tools have application in investigations to improve understanding of coccidiosis epidemiology, treatment and control studies, and diagnostic investigations of outbreaks. In the present study, Eimeria spp. shedding was common in captured rangeland goats under typical feedlot management conditions, with 90% of goats shedding at least once over the four sampling occasions. Mixed infections were identified in 57% of goats.
The impact of time on the acquisition of immunity was not established by this observational study, consequently further work is required to determine the impact of coccidial immunity acquisition on health and production for captured goats in confined feeding facilities. Additionally, this study serves as a prelude for future epidemiological studies pertaining to the clinical relevancy of coccidiosis in goats with respect to their age, and interventions that may ameliorate the impact of coccidiosis for captured rangeland goats and small ruminants more generally.
135 CHAPTER 5. MORPHOLOGICAL AND MOLECULAR CHARACTERISATION OF AN UNINUCLEATED CYST- PRODUCING ENTAMOEBA SPP. IN CAPTURED RANGELAND GOATS IN WESTERN AUSTRALIA
The contents of this chapter have been published in Veterinary Parasitology. The article can be found in Appendix 10.
This chapter describes the analyses of faecal samples from captured rangeland goats for Entamoeba spp. Two methods were used: (1) faecal flotation and microscopic analysis and (2) nested PCR detection and molecular characterisation at two loci for
Entamoeba spp. in captured rangeland goats.
Research highlights:
First report of Entamoeba from wild rangeland goats in Western Australia.
Molecular characteristation at two loci.
Genetically closest to an E. bovis isolate from a sheep from Sweden.
First study to produce actin sequences from E. bovis-like Entamoeba sp.
136 Abstract: Uninucleated Entamoeba cysts measuring 7.3 × 7.7 m were detected in faecal samples collected from wild rangeland goats (Capra hircus) after arrival at a commercial goat depot near Geraldton, Western Australia at a prevalence of 6.4% (8/125). Sequences were obtained at the 18S rRNA (n=8) and actin (n=5) loci following PCR amplification.
At the 18S locus, phylogenetic analysis grouped the isolates closest with an E. bovis isolate (FN666250) from a sheep from Sweden with 99% similarity. At the actin locus, no E. bovis sequences were available, and the isolates shared 94.0% genetic similarity with E. suis from a pig in Western Japan. This is the first report to describe the morphology and molecular characterisation of Entamoeba from Rangeland goats in
Western Australia and the first study to produce actin sequences from E. bovis-like
Entamoeba sp.
5.1. Introduction
Organisms of the genus Entamoeba have adapted to live as parasites or commensals in the digestive tract of humans and other mammals, birds, amphibians, fish and reptiles (Skirnisson and Hansson, 2006; Stensvold et al., 2010). Species within the genus can all be assigned to either uni-, quadri- or octo-nucleated and noncyst-producing morphological groups (Stensvold et al., 2010): 1) species without cysts (E. gingivalis- like group), 2) species with uninucleated cysts (E. bovis-like group), 3) species with quadrinucleated cysts (E. histolytica-like group, 4) octonucleated cysts (E. coli- like group). Several species are found in humans and animals with the quadrinucleate E. histolytica responsible for invasive ‘amoebiasis’ (which includes amoebic dysentery and amoebic liver abscesses) in humans. Uninucleated cyst-producing Entamoebae have been isolated from a range of hosts including humans, non-human primates, other mammals and birds (Noble and Noble, 1952; Skirnisson and Hansson, 2006; Stensvold et al., 2010).
Ruminants such as cattle and sheep are common hosts of uninucleate cyst-producing
137 Entamoebae (Noble and Noble, 1952; Jacob et al., 1990; Hampton et al., 2006; Skirnisson and Hansson, 2006; Kanyari et al., 2009; Stensvold et al., 2010; Stensvold et al., 2011) and unidentified Entamoeba species have been reported in goats in Kenya (Kanyari et al.,
2009), Thailand (Sangvaranond et al., 2010), Tanzania (Mhoma et al., 2011), Cameroon
(Ntonifor et al., 2013) and Brazil (Radavelli et al., 2014). Until recently, the detection, identification and assignment of Entamoeba organisms to species relied mainly on morphology and the host in which parasites were identified (Stensvold et al., 2010;
Stensvold et al., 2011). However, morphology is not a reliable tool for delimiting
Entamoeba species as cyst morphology varies substantially within as well as between uninucleated cyst-producing species fromdifferent ruminanthosts (Noble and Noble,
1952; Pillai and Kain, 1999; Stensvold et al., 2010). The use of molecular tools is therefore essential to resolve the identification, taxonomy, epidemiology and clinical significance of Entamoeba species without reliance on parasite cultures or experimental infections (Stensvold et al., 2011; Jacob et al., 2016). Rangeland goats are an introduced animal species in Australia. They can be legally trapped and reared by licensed operators
(goat depots) for the domestic and export meat markets, which was worth approximately
$AUS242 million in 2014 (Meat and Livestock Australia, 2015). Few studies have conducted genetic characterisation of Entamoeba species from ruminants (Stensvold et al., 2010; Jacob et al., 2016), which is important for understanding their evolutionary and taxonomic relationships. In the present study, uninucleate Entamoeba cysts were identified in the faeces of Rangeland goats in Western Australia by microscopy and were characterised at the 18S ribosomal RNA (rRNA) and actin loci.
138 5.2. Materials and methods
5.2.1. Sampling, morphological and molecular analyses.
Faecal samples were collected by rectal palpation from 125 male Australian
Rangeland goats (Capra hircus) on arrival at a commercial goat depot near Geraldton,
Western Australia, after capture and transport from a sheep and cattle extensive rangeland grazing property, North Wooramel station, located 78 km east of Denham and 113 kmsoutheast of Carnarvoninthe Gascoyne region of Western Australia. On arrival, the goats weighed on average 30.7 ± 0.3 kg (±SEM), and the estimated age of the goats, based on dentition, was between 9 and 12 months. Faecal samples were immediately placed on ice until transported to the lab, where microscopy work was performed on the same day of collection and then stored in the refrigerator (4.0 ◦C) until DNA extraction was performed. All sample collection methods used were approved by the Murdoch
University Animal Ethics Committee (approval number R2617/13). Direct microscopic examination of faecal suspensions in saline and wet mounted with 0.9% saline and
Lugol’s iodine was conducted. Entamoeba cysts were concentrated using zinc-sulfate gradient floatation (Faust’s method) (Ramos et al., 2005) and observed under Nomarski contrast with a 100 × oil immersion objective lens in combination with an ocular micrometre on an Olympus DP71 digital micro-imaging camera. The diameters of cysts
(n=35) (isolated from the eight positive samples) and trophozoites (n=15) (isolated from two positive samples) were measured and averages and ranges were calculated. Genomic
DNA was extracted from 200 mg of each faecal sample using a Power Soil DNA Kit
(MolBio, Carlsbad, California) with some modifications. Briefly, samples were subjected to four cycles of freeze/thaw by liquid nitrogen and boiling water to ensure efficient lysis of cysts before being processed using the manufacturer’s protocol. A negative control (no faecal sample) was used in each extraction group. Samples that were positive for
Entamoeba by microscopy were examined by PCR using the eukaryotic primers RD5 (5’
139 –ATCTGGTTGATCCTGCCAGT–3’) and RD3 (5’ –
ATCCTTCCGCAGGTTCACCTAC–3’) as previously described (Clark et al., 2006). An approx. 1950 bp PCR product was amplified, which was initially sequenced with the RD5 or RD3 primers in both directions. Based on the partial sequences obtained, a set of new
Entamoeba specific primers ENF2 (5’ –AAGCATGGGACAATATCGAGG) and ENR2
(5’ – GTCCCTTTAAGAAGTGATGC) were designed to conduct sequence walking to obtain the full length sequence of the 1950 bp PCR product. The primers were designed using Primer3 (http://bioinfo.ut.ee/primer3-0.4.0/primer3/). All microscopy positives were also analysed at the actin locus (∼1100 bp amplicon) as described by Sulaiman et al. (2002), as although these primers were originally designed for Cryptosporidium, they also amplify Entamoeba (Matsubayashi et al., 2014). The amplified DNA fragments from the PCR products were gel purified using an in-house filter tip method as previously described (Yang et al., 2013) and sequenced using forward and reverse primers in duplicate using amplicons from different PCR runs. AnABI PrismTM Dye Terminator
Cycle Sequencing kit (Applied Biosystems, Foster City, California) was used for Sanger sequencing according to the manufacturer’s instructions. The results of the sequencing reactions were analysed and edited using FinchTV (Version 1.4), compared to existing
Entamoeba spp. 18S rRNA and actin sequences on GenBank using BLAST searches and aligned with reference sequences from GenBank using Clustal W in BioEdit (V7.2.5).
Phylogenetic trees were constructed for the 18S and actin sequences obtained and including additional sequences available in GenBank. Parsimony, Maximum likelihood
(ML) and Neighborjoining (NJ) analyses were conducted using MEGA 6 (Tamura et al.,
2013). ML and NJ analyses were conducted using Tamura-Nei based on the most appropriate model selection using ModelTest in MEGA 6. Bootstrap analyses were conducted using 1000 replicates to assess the reliability of inferred tree topologies.
140 5.3. Results
Entamobea was identified by microscopy in eight faecal samples at a prevalence of 6.4% (8/125) (2.1-10.7 95 CI). Cysts (n=35) were uninucleate and spherical with a single-layered cyst wall and within the nucleus, a centrally located karyosome (condensed zone of chromatin filaments) was seen (Table 5.1, Fig. 5.1, a and b). Glycogen was diffuse and vacuoles were noted in most examined cysts which measured 7.3 (6.5-11.4) x 7.7
(6.6-12.3) μm with a width to length ratio of 1.05 (1.01-1.11). The diameter of the single nucleus averaged 1.7 μm (1.3-2.9) (Table 5.1). Trophozoites were identified in two faecal samples and measured 15.8 μm (14.2-18.2 μm) in diameter and and within the nucleus, a centrally located and irregular 7 shaped karyosome was seen (Fig. 5.2, a and b).
18S sequences (1,800 bp) were obtained from all eight microscopy positives.
Phylogenetic analyses using Parsimony, NJ and ML analyses produced similar results
(Fig. 5.3- NJ tree shown) and grouped the 18S Entamoeba sequences from rangeland goats in a clade with Entamoeba bovis and were most closely related (99% similarity) to an E. bovis isolate (FN666250) from a sheep (Ovis aries) isolate from Sweden (Fig. 5.3).
Amongst all E. bovis isolates, the genetic similarity ranged from 96% to 99%.
At the actin locus, a 1,066 bp PCR product was successfully amplified from 5 isolates. Some sequence variation was observed in the actin sequences with 1-6 single nucleotide polymorphisms (SNP’s) observed between sequences. There were fewer
Entamoeba spp. actin sequences available in the GenBank database compared to the 18S
140 rRNA locus and E. bovis sequences were not available. Phylogenetic analysis of available sequences grouped the Entamoeba actin sequences from rangeland goats in a separate clade with the highest similarity (94%) with Entamoeba suis from pigs (Sus scrofa domesticus) from Western Japan (AB914739) (Fig. 5.4). Representative 18S and actin sequences have been deposited in GenBank under accession numbers KY012746,
KY012747, KY012748 and KX363870.
141
142 Table 5.1. Morphometric characteristics of uninucleated cyst-producing Entamoeba spp. reported from livestock compared with the Entamoeba cysts isolated from rangeland goats in Western Australia in the present study.
Species a Host Cyst diagnostic characters Reference Cyst shape Cyst size Nucleus Karyosome Glycogen Vacuoles (mean) (mean) Entamoeba bovis Cattle 4–15μm 1.5–5.5μm N/A N/A present in Noble and Noble (1952) (Bos taurus) N/A (8.8μm) (3.0μm) various sizes White-tailed deer N/A 6–11 μm N/A N/A N/A N/A Kingston and Stabler (Odocoileus (8.2 μm) (1978) virginianus) Gnu (Connochaetes N/A 6–13 μm N/A N/A N/A N/A Mackinnon and Dibb taurinus) (9.0 μm) (1938) Bay Duiker N/A N/A N/A N/A N/A N/A Bray (1964) (Cephalophus dorsalis) Cattle (Bos taurus) N/A 3.9–14.4μm N/A N/A N/A N/A Stensvold et al. (2010) (6.6μm) N/A Sheep (Ovis aries) N/A 5.4–13.8μm N/A N/A N/A N/A Stensvold et al. (2010) (7.2μm) Entamoeba ovis b Sheep (Ovis aries) N/A 4–13 μm N/A N/A N/A N/A Noble and Noble (1952) (7.2 μm) N/A Entamoeba debliecki Goat (Capra hircus) round/ oval 4–12 μm N/A N/A present present Nieschulz (1923); (6.42 μm) (2.4μm) Noble and Noble (1952) Goat (Capra hircus) spherical/ 4.75–13.3 1.9-4.2μm large central/ N/A present Hoare (1940) ovoid/ 6.65μm c N/A eccentric (off ellipsoid to the side) Entamoeba dilimanib Goat (Capra hircus) N/A 5–16μm N/A N/A N/A N/A Noble (1954) (9.7μm) N/A Entamoeba suis b Pig (Sus domesticus) N/A 9.5–15.5μm N/A N/A N/A N/A Clark et al. (2006) (12.85μm) N/A
143 Species a Host Cyst diagnostic characters Reference Cyst shape Cyst size Nucleus Karyosome Glycogen Vacuoles (mean) (mean) Entamoeba polecki b Pig (Sus domesticus) N/A 4–17μm (8.09 large N/A N/A N/A Noble and Noble (1952) μm) (2.22μm) Entamoeba from Goat (Capra hircus) spherical 6.5–12.3 μm (1.3-2.9) central diffuse present Present study rangeland goats 7.3x7.7μm 1.7 μm aThe non-cyst species E. caprae, has been reported in a goat (Fantham, 1923), however as only trophozoite and its nucleus measurements were given, this species was not included. bEntamoeba ovis, E. suis, E. polecki and E. dilimani are considered synonymous with E. debliecki (Levine, 1985; Clark and Diamond, 1997; Clark et al., 2006). cThis is the median of 800 cysts measured in English goats and believed to be E. debliecki (Hoare, 1940).
144
Figure 5.1. Nomarski interference-contrast photomicrographs of Entamoeba cysts isolated from rangeland goats showing centrally located karyosome; 5.1a: cyst stained with iodine, 5.1b: cyst in saline mount. Scale bar = 10 μm.
Figure 5.2. Nomarski interference-contrast photomicrographs of Entamoeba trophozoites isolated from rangeland goats showing centrally located karyosome and diffused glycogen, 5.2a: trophozoite stained with iodine, 5.2b: trophozoite in saline mount. Scale bar = 20 μm.
145
95, 99, 100 Entamoeba sp. (Rangeland goats), isolate codes C1-1, C1-52, C1-116 KY012746 95, 100, 95 Entamoeba sp. (Rangeland goats), isolate codes C1-70, C1-72 KY012747 94, 100, 99 Entamoeba sp. (Rangeland goats), isolate codes C1-14, C1-27, C1-49 KY012748 93, 98, 98 E. bovis (Sheep) FN666250 92, 88, 100 E. bovis (Cattle) FN666249 89, 100, 94 E. bovis (Cattle) FN666248 1 nucleus per cyst 92, 100, 100 E. bovis (Reindeer) FN666252 93, 98, 98 E. bovis (Sheep) FN666251 85, 100, 100 Entamoeba sp. RL8 KR025406 82, 74, 76 Entamoeba sp. RL3 FR686359 89, 100, 100 Entamoeba sp. RL3 FR686358 88, 92, 91 Entamoeba sp. RL2 FR686363 93, 97, 96 95, 100, 100 Entamoeba sp. RL2 FR686362 4 nuclei per cyst
93, 89, 90 Entamoeba sp. CS-2010 FN666253 1 nucleus per cyst Entamoeba sp. RL4 FR686361 Cyst data n/a 81, 84, 82 E. moshkovskii AF149906 82, 74, 100 85, 100, 100 E. ecuadoriensis DQ286373 82, 99, 99 E. dispar Z49256 4 nuclei per cyst 81, 100, 100 E.histolytica X64142 75, 69, 84 80, 81, 94 E. nuttalli FR686356 E. equi DQ286371 84, 86, 80 Cyst data n/a 87, 76, 84 E. insolita AF149909 Entamoeba sp. RL6 AF149911 89, 95, 82 85, 94, 77 Entamoeba sp. RL5 FR686365 E. terrapinae AF149910.1 4 nuclei per cyst 96, 100, 100 E. hartmanni AF149907 E. ranarum AF149908 E. invadens AF149905
E. gingivalis D28490 No cyst 96, 100, 100 E. suis DQ286372 1 nucleus per cyst E. poleckii AF149913
96, 100, 100 E. coli AF149914 8 nuclei per cyst
0.1
Figure 5.3. Evolutionary relationships of Entamoeba spp. inferred by distance analysis of using 18S rRNA gene sequences. Percentage support (>50%) from 1000 pseudoreplicates from distance, ML and parsimony analysis, respectively, is indicated at the left of the support node (- = value was <50%).
146
E. invadens AK423143 E. invadens AK423812 E. invadens AK423715 95, 92, 85 E. invadens AK423421 E. invadens AK421778 E. invadens AK422641 E. invadens AK423483 E. invadens AK421769 E. invadens AB522086 E. invadens AK422259 E. invadens AK424086 99, 88, 86 E. invadens XM 004184261 E. invadens AK422955 E. invadens AK424152 E. invadens AK423830 99, 87, 83 E. invadens AK423417 98, 81, 95 E. invadens AK423753 E. invadens AK422264 100, 83, 97E. suis AB914739 E. suis AB914740 100, 88, 99 E. suis AB914741 Entamoeba sp. (Rangeland goats), isolate code C1-70 KX363870 100, 90, 86 Entamoeba sp. (Rangeland goats), isolate code C1-27 KX363870 98, 89, 81 Entamoeba sp. (Rangeland goats), isolate code C1-1 KX363870 Entamoeba sp. (Rangeland goats), isolate code C1-52 KX363870
87, 82, 84 Entamoeba sp. (Rangeland goats), isolate code C1-72 KX363870 E. moshkovskii EMO 002120-1 E. dispar EDI 004490A 83, 81, 83 E. histolytica AK420640 73, 71, 72 E. histolytica AK420864 E. histolytica AK419281 75, 69, 70 E. histolytica AK419281
84, 77, 81E. histolytica AK419296 E. histolytica AK420713 Rhizomastix bicoronata KP343638 0.02
Figure 5.4. Evolutionary relationships of Entamoeba spp. inferred by distance analysis of using partial actin gene sequences. Percentage support (>50%) from 1000 pseudoreplicates from distance, ML and parsimony analysis, respectively, is indicated at the left of the support node (- = value was <50%).
147 5.4. Discussion
In the present study, uninucleate Entamoeba cysts identified in the faeces of rangeland goats in Western Australia were analysed morphologically and molecularly. It is difficult to compare the Entamoeba detected in the present study with Entamoeba species identified in goats and other ruminants in previous studies, as few microscopic studies are available and no molecular characterisation has been conducted on Entamoeba from goats. A non-encysting species, E. caprae has been described in goats (Fantham,
1923) and within the 8 uninucleate E. bovis-like group, E. dilimani and E. debliecki (syn.
E. ovis) has been described in goats (Noble and Noble, 1952; Noble, 1954). The size of the cysts (7.3 x 7.7 μm) in the present study were smaller than those of E. bovis from cattle (diameter of 8.8 μm) previously reported (Noble and Noble, 1952) and slightly bigger than the average cyst diameters reported in sheep (7.2 μm) (5.4-13.8 μm) and cattle
(6.6 μm) (3.9-14.4 μm) in Sweden (Stensvold et al., 2010). The Entamoeba cysts analysed in the present study also differed from Entamoeba cysts isolated from an English goat, believed to be E. debliecki, 6.6μm (4.7 161 to 13.3 μm) and also differed in karyosome location, which was centrally located in the present study and eccentric (off centre) in the cysts from an English goat (Hoare, 1940). The cysts in rangeland goats also differed from the round/oval cysts 6.4 (4-12) μm thought to be E. debliecki (Noble and Noble, 1952).
Cysts of E. dilimani were reported to be 9.7 (5-16) μm in diameter (Noble, 1954). Further research is required to clarify the taxonomy of caprine Entamoeba sp.
Sequence comparison and phylogenetic analysis at the 18S locus revealed that the
Entamoeba isolated from rangeland goats in the present study shared 99% similarity with
E. bovis (FN666250) from a sheep in Sweden. Amongst the five identified E. bovis 18S sequences available in GenBank, the genetic similarity ranged between 96-99% and therefore the Entamoeba sequences detected in rangeland goats are within this range. At the actin locus, unfortunately no actin sequences were available from E. bovis in GenBank
148 and the Entamoeba sp. from rangeland goats grouped (94% similarity) with E. suis from a pig in Western Japan (AB914740), the only other actin sequence available from a uninucleate Entamoeba sp. The actin gene is a conserved locus but with sufficient single nucleotide polymorphisms (SNPs) to delimit species in a genus and therefore is a common locus for taxonomic studies of microorganisms (Reisler and Egelman 2007;
Lahr et al., 2011). Similar to the 18S rRNA PCR, no mixed chromatograms were detected, suggesting that only one Entamoeba sp. was present in the rangeland goats.
5.5. Conclusion
In conclusion, an uninucleated E. bovis-like Entamoeba spp. was identified from rangeland goats, which we believe is a genotype of E. bovis. In addition, for the first time an E. bovis-like actin sequence was produced, which will facilitate future phylogenetic analysis of Entamoeba in ruminants and other ungulates. The clinical impact of the E. bovis isolate in rangeland goats is unknown, but given the economic importance of rangeland goat meat, further studies should be conducted to examine the prevalence and clinical impact (if any) on rangeland goats.
149 CHAPTER 6. MOLECULAR CHARACTERISATION OF SALMONELLA ENTERICA SEROVAR TYPHIMURIUM AND CAMPYLOBACTER JEJUNI FAECAL CARRIAGE BY CAPTURED RANGELAND GOATS
The contents of this chapter have been published as an original research article in
Small Ruminant Research. The article can be found in Appendix 11.
This chapter describes the longitiudinal prevelanace and molecular characterisation of bacterial agents; Salmonella enterica and Campylobacter spp. from captured rangeland goats. Two molecular methods were used: (1) qPCR to determine the longituidinal prevelance of both bacterial agents and (2) PCR at multiple loci for molecular characterisation of species and serovars of Salmonella and Campylobacter in captured rangeland goats.
Research highlights:
Zoonotic S. enterica serovar Typhimurium and C. jejuni faecal carriage by goats
identified using qPCR.
High frequency for S. enterica serovar Typhimurium faecal carriage immediately
after capture and transport.
Low frequency of faecal carriage detection one to three months after arrival at the
feedlot.
Repeated S. enterica serovar Typhimurium faecal carriage detection not common.
Meat hygiene and effluent management implications for goats following capture
and transport.
150
Abstract: Western Australian rangeland goats were surveyed for faecal carriage of
Salmonella enterica and Campylobacter spp. Faecal samples were collected from 125 goats on four occasions. The first sample was collected immediately upon arrival at a commercial goat depot (feedlot). Subsequent samples were collected at one month intervals thereafter. Frequency of detection and faecal carriage intensity were determined using qPCR targeting the S. enterica outer membrane protein (ompF) and Campylobacter spp. purine biosynthesis gene (purA). Salmonella enterica were identified in 40/500 of faecal samples, with S. enterica faecal carriage detected in 30% (38/125) goats over the duration of the study. Campylobacter spp. were identified in 12/500 of samples, with
Campylobacter spp. detected in 10% (12/125) goats over duration of the study. Frequency of detection was highest at the first sample collection for both S. enterica (26%) and
Campylobacter spp. (8%). Repeat detection of Salmonella was observed for only a single goat (0.8%). Salmonella qPCR positive samples were characterised at ompF and invA genes as S. enterica. Further characterisation at STM2755 and STM4497 genes confirmed the isolates were S. enterica serovar Typhimurium. Characterization at the 16S rRNA and hippuricase (hipO) genes revealed all Campylobacter spp. positive samples were C. jejuni. This study demonstrates that qPCR can be used for rapid identification of faecal carriage in goat faecal samples and showed evidence of carriage of zoonotic S. enterica serovar Typhimurium and C. jejuni by captured rangeland goats. The findings have implications for management of goats at abattoirs and in confined feeding facilities.
151 6.1. Introduction
Undomesticated rangeland goats are naturalised throughout Australian rangelands and opportunistically captured and utilised for meat production (Meat and Livestock
Australia, 2015). Following capture, rangeland goats may be managed in goat depots
(feedlots) for variable periods prior to slaughter. Diarrhoea and ill-thrift (weight loss or poor growth rates) are cited as important issues for captured rangeland goats under intensive management conditions in goat depots (Meat and Livestock Australia, 2016).
The causes of diarrhoea and ill-thrift are not well described. It has been suggested that stress associated with capture, transport and domestication, as well as high stocking densities in feedlots, may contribute to increased shedding and transmission of disease agents with veterinary and public health importance, such as Salmonella (Meat and
Livestock Australia, 2016).
Salmonella and Campylobacter occur naturally in the gut as commensals, and infections are often asymptomatic (Kusiluka et al., 1996; Duffy et al., 2009; Markey et al., 2013). However, Salmonella (S.) enterica and Campylobacter spp. (C. jejuni and C. coli) have been associated with diarrhoea, weight loss, lethargy and inappetance in goats, with sustained periods of stress identified as a risk factor for manifestation of disease in both goats and sheep (Bulgin and Anderson, 1981; McOrist and Miller, 1981; Richards et al., 1989; Sharma et al., 2001; Markey et al., 2013). Outbreaks of acute diarrhoea due to S. enterica (S. Adelaide, S. Typhimurium, S. Muenchen and S. Singapore) with 38% mortality rate have been reported in Australian rangeland goats (McOrist and Miller,
1981), but the epidemiology of Salmonella and Campylobacter infections and specific risk factors for faecal carriage in rangeland goats are not well described.
Apart from impacts on goat health and production, there are important implications for faecal carriage of S. enterica and Campylobacter spp. along the entire goat meat supply chain. Salmonella enterica and some Campylobacter spp. have zoonotic
152 potential, therefore faecal carriage is associated with public health risks via contamination of carcases and water sources (Davies et al., 2004; Garcia et al., 2010). There are also important economic consequences for processors, with many meat export markets having zero tolerance for contamination of meat products.
Molecular methods including quantitative PCR (qPCR) for detection of
Salmonella and Campylobacter in faeces and food can offer some advantages over culture, including speed, and greater specificity, sensitivity and reproducibility (Maciel et al., 2011; Singh et al., 2011; Zhang et al., 2011; Whiley et al., 2016). Molecular tools based on qPCR have been used to characterise faecal carriage of S. enterica and
Campylobacter spp. for sheep (Yang et al., 2014d; Yang et al., 2017). The aim of the present study was to determine faecal carriage of S. enterica and Campylobacter spp. in captured rangeland goats in Western Australia using molecular tools.
6.2. Materials and Methods
6.2.1. Animals and faecal sample collection
Rangeland goats (n=125) were captured from a sheep and cattle rangeland grazing property, North Wooramel station, located 78 km east of Denham and 113 km south east of Carnarvon in the Gascoyne region of Western Australia. Goats were transported by road to a commercial goat depot (feedlot) near Geraldton, Western Australia. On arrival at the feedlot (S1), goats weighed 30.7 ± 0.3 kg (mean ± standard error) with an estimated age of 9–12 months based on dentition. Only male goats were included in the study.
Faecal samples were collected from each goat on four occasions (S1- S4). The first sample collection (S1) occurred immediately after arrival at the feedlot. Subsequent sampling (S2-S4) occurred monthly thereafter. Faecal samples were collected directly from the rectum and stored on ice or in a refrigerator (4.0 °C) until DNA extraction. Goats were housed in four group pens (30–33 goats per pen) for the duration of the study. Grain-
153 based pellets, hay and water were supplied ad libitum. Straw-bedding was provided with bare dirt covering the majority of available pen space. No pasture was available for the duration of the study. Goats were consigned for slaughter after the conclusion of the experiment when they reached acceptable slaughter weight. All procedures were approved and monitored by the Murdoch University Animal Ethics Committee (approval number R2617/13).
6.2.2. DNA isolation
Genomic DNA was extracted from 200 mg of each faecal sample using a Power
Soil DNA Kit (MolBio, Carlsbad, California). A negative control (no faecal sample) was used in each extraction group.
6.2.3. PCR amplification, quantification and sequencing
All samples were screened for the presence of S. enterica and Campylobacter spp. using a quantitative PCR (qPCR) at the outer membrane protein (ompF) and purine biosynthesis gene (purA) respectively as described by Yang et al. (2014). Briefly, a 96 base pair (bp) product was amplified from the S. enterica ompF using the forward primer ompF1 5′-TCGCCGGTCGTTGTCCAT-3′, the reverse primer ompR1 5′-
AACCGCAAACGCAGCAGAA-3′ and the probe 5′–2′7,′-dimethoxy-4′5,′-dichloro-6- carboxyfluorescein (JOE)-ACGTGACGACCCACGG CTTTAC–3′. A 121 bp product was amplified from the Campylobacter spp. purA using the forward primer purAF1 5′–
CGCCCTTATCCTCAGT AGGAAA–3′, the reverse primer purAR1 5′–
TCAGCAGGCGCTTTAA CAG–3′ and the probe 5′–6-carboxyfluorescein (FAM)-
AGCTCCATTTCC CACACGCGTTGC–3′. An internal amplification control (IAC) consisting of a fragment of a coding region from Jembrana disease virus (JDV) cloned into a pGEM-T vector (Promega) and IAC primers were used as described previously
(Yang et al., 2013). Each 15 μL PCR mixture contained 1 × PCR buffer (10 mM Tris–
154 HCl, 50 mM KCI), 4 mM MgCl2, 1 mM deoxynucleotide triphosphates, 1.0 U KAPA
DNA polymerase (MolBio), 0.2 μM each forward and reverse primer, 0.2 μM each forward and reverse IAC primers, 50 nM probe, 50 nM IAC probe, 10 copies IAC template and 1 μL sample DNA. The PCR cycling conditions consisted of 95°C for 3 min, then 45 cycles of 95°C for 20 s and 60°C for 45 s.
6.2.4. Specificity and sensitivity of qPCR
The analytical specificities of the multiplex qPCR assays were assessed by testing
DNA from S. enterica (S. enterica serovar Typhimurium, S. Wandsbek II 21:z10:z6, S.
Bredeney, S. Muenchen, S. Adelaide, S. Waycross, S. Infantis), C. jejuni, C. coli,
Chlamydia pecorum, Chlamydia abortus, Yersinia enterocolitica, Streptococcus bovis
(ATCC33317), Enterococcus durans (ATCC 11576), Escherichia coli (ATCC 25922),
Bacillus subtilis (ATCC 6633), Serratia marcescens (ATCC 14756 pigmented),
Citrobacter freundii (NCTC 9750), Enterobacter cloacae (ATCC 13047), Coxiella burnetii, Giardia duodenalis assemblages A and E from sheep, Cryptosporidium spp.
(n=5), Isospora sp., Tenebrio sp., Cyclospora sp., Toxoplasma gondii, Trichostrongylus colubriformis, Teladorsagia circumcincta, Haemonchus contortus and Eimeria sp., as well as human, sheep and cattle genomic DNA (Yang et al., 2014d). To determine the sensitivity of the assay, 10-fold serial dilutions of plasmids containing the cloned PCR products amplified from each of the two bacteria (S. enterica and Campylobacter spp.) were prepared from 1 × 106 copies to 10 copies. These were then ‘spiked’ into faecal samples and the DNA was extracted and amplified as described above. Mean detection limits, the coefficient of determination R-squared values and % relative standard deviation were calculated. Template copy numbers were converted to numbers of organisms present on the basis that ompF (S. enterica) and purA (Campylobacter spp.) are single copy genes (Pearson et al., 2007; Tatavarthy and Cannons, 2010; GenBank
155 CP000814) and bacterial genomes are haploid. Therefore the detected plasmid numbers were equivalent to the numbers of S. enterica and Campylobacter spp.
6.2.5. Inhibition and efficiency analysis of qPCR
Equal amounts of the IAC template (10 copies) were added to all faecal DNA samples to detect any PCR inhibitors present in the extracted DNA. If inhibition was evident, then the sample was diluted and reamplified (Yang et al., 2014d). Amplification efficiency (E, a measure of inhibition), was estimated by using the slope of the standard curve and the formula E = −1 + 10(−1/slope) (Nybo, 2011). To estimate amplification efficiency on faecal samples, serial dilutions of five individual DNA samples (neat, 1:10,
1:100) were performed and multiple qPCR reactions were conducted on each dilution.
The Ct values were then plotted vs. the log 10 of the dilution and a linear regression was performed using the Rotor-Gene 6.0 software.
6.2.6. Molecular characterisation of S. enterica and Campylobacter spp.
Initially qPCR-positive Salmonella samples were subjected to onestep PCR for the S. enterica gene ompF (578 bp amplicon) and invA (521 bp amplicon) gene as described by Tatavarthy and Cannons (2010) and Swamy et al. (1996) respectively.
Positive S. enterica isolates were further investigated using serovar specific STM2755
(406 bp amplicon) and STM4497 (523 bp amplicon) primers and PCR conditions described by Shanmugasundaram et al. (2009). The primers’ specificity were assessed by testing DNA from an isolate of S. enterica serovar Typhimurium (Abraham et al., 2016) as a positive control and four isolates of S. Anatum, S. Dublin, S. Enteritidis and S. Hadar as negative controls. Samples that were qPCR-positive for Campylobacter spp. were subjected to PCR for the Campylobacter spp. 16S rRNA gene (287 bp amplicon) using primers and PCR conditions described by Lubeck et al. (2003). Positive Campylobacter spp. isolates were further confirmed by species specific PCR at the hippuricase (hipO)
156 (344 bp amplicon) gene previously described by Persson and Olsen (2005). PCR products were separated by gel electrophoresis and purified using an in-house filter tip method
(Yang et al., 2013). Purified PCR products were sequenced using an ABI Prism Dye
Terminator Cycle Sequencing kit (Applied Biosystems) using an annealing temperature of 58 °C. Nucleotide sequences were analysed using Chromas lite version 2.0
(http://www.technelysium.com.au) and aligned with reference sequences from GenBank using Clustal W (http://www.clustalw.genome.jp). The target genes and primers used for the amplification and sequencing of S. enterica and Campylobacter spp. isolates and their length are given (Table 2.2).
6.2.7. Statistical analyses
Goats were classified as positive (DNA detected) or negative (no DNA detected) for S. enterica and Campylobacter spp. Frequency of faecal carriage detection was determined by proportion of positive goats for each sample occasion. Statistical analyses were performed using IBM SPSS Statistics for Mac (version 24). Two-tailed Chi-square tests (Pearson Chi-square or Fisher’s exact test) were used to compare frequency of faecal carriage detection between sampling occasions and different pens at the goat depot.
Prevalence confidence intervals (95%) were calculated using Jeffrey's interval method
(Brown et al., 2001).
6.3. Results
6.3.1. Specificity, sensitivity and efficiency for qPCR
Specificity and sensitivity of the multiplex bacterial qPCR are shown in Table 6.1
(adapted from Yang et al., 2014d). Evaluation demonstrated no cross-reactions with other genera; the qPCR only amplified the relevant bacterial species.
157 Table 6.1. Specificity and sensitivity analysis for qPCR (adapted from Yang et al.,
2014d).
S. enterica C. jejuni Specificity Cross-reactions with other genera nil nil Sensitivity Mean minimum detection (organisms/g faeces) ~1,250 ~1,250 R-squared value 0.99 0.99 % relative standard deviation 4.5 3.5 Frequency PCR inhibition (%) ~2 ~2 Mean efficiency (%) 97.4 103.8
6.3.2. Faecal carriage and intensity for Salmonella enterica and Campylobacter spp.
A total of 40/500 faecal samples were qPCR-positive for Salmonella and 12/500 were PCR-positive for Campylobacter spp. over the four sampling occasions.
Frequencies of detection faecal carriage are shown in Table 6.2. Faecal carriage for both
S. enterica and Campylobacter spp. were highest at S1 (immediately after capture and transport) and decreased (P<0.05) at subsequent samplings (Table 6.2). Neither S. enterica nor Campylobacter spp. were identified at S4 (Table 6.2). Concurrent (mixed)
S. enterica and Campylobacter spp. faecal carriage was identified in 4% (5/125) of the goats at S1 only. Faecal carriage was detected in 0.8% (1/125) goats on three sampling occasions (S1-S3). Faecal carriage was not identified on two sampling occasions in any goats. Frequency of faecal carriage detection was higher (P=0.033) for pen 3 (4/31) compared to pen 2 (0/33) or pen 4 (0/31) at S2, but otherwise there was no difference in faecal carriage frequency between pens (P>0.05).
158 Table 6.2. Frequency of detection and faecal carriage intensity for S. enterica serovar Typhimurium (S. Typhimurium) and C. jejuni in faecal samples collected from 125 rangeland goats on four occasions (S1-S4).
Frequency of faecal carriage
detection (%) Sampling occasion S. Typhimurium C. jejuni February (S1) 25.6 a 8 a March (S2) 4.8 b 0.8 b April (S3) 1.6 b 0.8 b May (S4) 0 b 0 b
Longitudinal frequency of detection# (95% CI) 30.4 (22.8, 38.8) 9.6 (5.4, 15.7) abcFaecal carriage frequency (%) values for sampling occasions (in columns) with different superscripts are significantly different (P<0.05). #Goats with faecal carriage detected on at least one sampling occasion. CI: confidence interval.
6.3.3. Salmonella enterica and Campylobacter spp. molecular typing
All Salmonella-positive sequences (n=40) were confirmed as S. enterica at the ompF and invA loci (98–99% homology to GenBank isolates CP014979 and CP014971 respectively). Further amplification and sequencing using serovar specific primers
(STM2755 and STM4497) confirmed all S. enterica-positive isolates as S. enterica serovar Typhimurium by (100% homology to GenBank isolate CP013720).
All Campylobacter-positive samples (n=12) were identified C. jejuni based on amplicon sequencing of both the 16S rRNA and hipO loci (99% homology to GenBank isolates CP001876 and KJ659824 respectively).
6.4. Discussion
This study identified faecal carriage of two important caprine pathogens with zoonotic potential by captured rangeland goats, namely S. enterica serovar Typhimurium
159 and C. jejuni. The temporal pattern of faecal carriage observed has important implications for the goat meat industry, with the highest frequency of detection for both S. enterica serovar Typhimurium and C. jejuni identified on arrival at the feedlot, immediately following capture and road transport. This is an important observation because the first sampling occasion reflected levels of faecal carriage likely to be observed at abattoirs for goats consigned directly to slaughter following capture and transport by road from rangeland properties to processing facilities, and this is common practice. The high frequency of S. enterica serovar Typhimurium faecal carriage observed at the first sampling occasion (26%) indicates further investigation of the factors that impact shedding by goats in lairage, including the impact of pre-slaughter management practices, are warranted because high frequency of faecal carriage has important implications for meat hygiene and abattoir effluent management.
The other key observation was the decline in faecal carriage detection one month subsequent to capture and transport. Persistent faecal carriage detection over more than one sample occasion (monthly intervals) was not common (0.8% goats) for rangeland goats housed in the goat depot. The decline in faecal carriage frequency suggests investigations based on faecal samples from goats that are habituated to their surroundings are likely to underestimate faecal carriage potential following a period of stress. Comparison of frequency of faecal carriage of S. enterica serovar Typhimurium and C. jejuni between studies is problematic because factors apart from geographic location, including diagnostic techniques, husbandry and management practices, herd size and season will impact detection.
Risk factors for S. enterica serovar Typhimurium and C. jejuni faecal carriage were not tested in the present observational study, but the higher frequency of faecal carriage identified at the first sample collection was likely attributable to stress associated with trapping and transport of the wild goats, including mixing of unfamiliar animals,
160 increased stock density, food deprivation, or contaminated feed/water during the trapping period. Transportation stress in goats has been associated with increased plasma cortisol levels (Kannan et al., 2003; Al-Kindi et al., 2005), and this has been shown to play a major role in the recrudescence of Salmonella resulting in increased shedding
(Verbrugghe et al., 2011). Transportation stress in goats (domestic and feral) has been associated with lowered immunity (Kannan et al. 2000; Kannan et al., 2002), elevated plasma glucose concentration (Sanhouri et al., 1992; New et al., 1996; Rajion et al.,
2001), and clinical salmonellosis (McOrist and Miller 1981).
Concurrent faecal carriage with both S. enterica serovar Typhimurium and
Camplyobacter spp. was not commonly observed (4% goats) in the present study and the highest point prevalence for S. enterica serovar Typhimurium and C. jejuni at the first sampling occasion supports the suggestion that stress related to capture and transport increases faecal pathogen shedding by rangeland goats.
Both S. enterica serovar Typhimurium and C. jejuni observed in the present study have zoonotic potential. Salmonella enterica serovar Typhimurium is a typical broad- host-range pathogen, which is among the serotypes most frequently associated with disease in humans (Coburn et al., 2007), including Australia where S. enterica serovar
Typhimurium was reported as the most frequently reported serovar in all states and territories, and associated with 43.9% of the 127,195 cases of human salmonellosis reported between 2000 and 2013 (Ford et al., 2016). Likewise, outbreaks of C. jejuni have been widely reported in Australia (Hundy and Raupach, 2003; Parry et al., 2012; Moffatt et al., 2016), with campylobacteriosis also a major cause of foodborne outbreaks
(Unicomb et al., 2009). Reports of Salmonella recovery from 28.9% goat carcasses in
Australia (Duffy et al., 2009) and 51.2% goat carcasses in Saudi Arabia (Bosilevac et al.,
2015) demonstrate carcass contamination during processing. Salmonellosis has been associated with consumption of raw or improperly cooked goat meat in Japan (Kadaka et
161 al., 2000). Similarly, Campylobacter recovery from goat carcases has been widely reported in Ethiopian, Ghanaian and Grecian abattoirs (Woldemariam et al., 2009; Lazou et al., 2014; Karikari et al., 2017), raw retail goatmeats respectively in Ethiopia and Iran
(Dadi and Asrat, 2008; Rahimi et al., 2010), and goat meat has been reported to act as major source of human and environmental contamination by Campylobacter spp. in
Congo (a Mpalang et al., 2014).
This study is the first molecular description of S. enterica and Camplobacter spp. reported for Australian rangeland goats. Molecular methods including qPCR offer some advantages for enumeration and detection of Salmonella and Campylobacter in faeces and food, including greater specificity, sensitivity and reproducibility than conventional diagnostic methods (Maciel et al., 2011; Singh et al., 2011; Zhang et al., 2011; Whiley et al., 2016). The present study demonstrated rapid detection of S. enterica and
Campylobacter spp. in faecal samples of captured rangeland goats through qPCR, and offered high specificity to detect S. enterica in faecal samples of rangeland goats when specific primer pairs that target a putative hexulose-6-phosphate synthase (STM2755) and cytoplasmic proteins (STM4497) are utilised. These genes are present in serovar
Typhimurium but not in any other S. enterica serovars (Chan et al., 2003;
Shanmugasundaram et al., 2009; Park et al., 2009; Park and Ricke, 2015; Ogunremi et al., 2017). The qPCR method offers some potential advantages as a diagnostic test in that it can be used for rapid detection of pathogens in faecal samples, and can be run as multiplex PCR for a range of other pathogens (for example, Cryptosporidium, Giardia,
Eimeria and helminths) during outbreak investigations and routine surveillance. The high minimum detection limit of the qPCR assay (~1,250 organisms/g faeces) meant that the rate of detection of faecal carriage may have under-estimated the proportion of samples that would have been positive by culture using methods that include selective enrichment.
Unfortunately, it was not within the scope of the study to validate the agreement for
162 detection and quantitation of the qPCR with culture methods. Inhibitors in faecal samples can hinder PCR amplification (Wilson, 1997), but for the present study inhibition determined by IAC amplification was only ~2% samples. It is likely the sensitivity of the assay could be increased with inclusion of a pre-enrichment step. Further validation of the qPCR for quantification of bacterial shedding intensity with culture methods is warranted.
There were some weaknesses of the present study that should be addressed in future investigations. The observational study design and small number of facilities included in the study meant that risk factors for faecal carriage were not determined. Only male goats were included in the study. Male goats are preferentially managed in
Australian goat depots for several reasons. Following capture, producers may choose to retain female goats to maintain goat populations, and consign males to goat depots or slaughter. Live export markets have preference for entire male goats, therefore goat depots preferentially source males because these can be marketed into export or domestic meat markets, or for live export. Finally, wild male goats are not castrated when captured, therefore males and females need to be housed and managed separately in the depot.
Including both males and females in the study would confound the effect of pen on pathogen shedding, growth and diarrhoea.
Another weakness of this study is that faecal carriage of wild goats prior to capture, between capture and transport, and at slaughter were not determined. Developing methods for collection of fresh faecal samples from wild goats prior to capture is challenging, but as animals need to be trapped and transported in order to enter goat depots or slaughter facilities, post-capture sampling is appropriate to characterise animal health and public health risks associated with pathogen faecal carriage. Follow up studies could include faecal sample collection for animals in trap yards (soon after capture) if suitable handling facilities to restrain wild goats are available. The findings of the present
163 study prompted a follow-up experiment of rangeland goats at slaughter that were sourced from a wider geographical area.
As described above, the high minimum detection limit of the qPCR assay meant that the rate of detection of faecal carriage may have under-estimated the proportion of samples that would have been positive using methods (including culture) that include selective enrichment. A further limitation was lack of isolation (by culture) limited the ability for evaluating the genotypic characteristic of the isolate and downstream public health impact including antimicrobial resistance (AMR). Notwithstanding these limitations, the observations demonstrate clearly that faecal carriage of S. enterica serovar
Typhimurium and C. jejuni in rangeland goats in the period immediately following capture and transport are sufficiently high to warrant further investigation into the risk factors for shedding and how these can be managed to reduce impacts on abattoir and meat hygiene, and the health and productivity of goats in confined feeding facilities.
6.5. Conclusion
The present study demonstrates that rangeland goats may act as reservoirs for S. enterica serovar Typhimurium and C. jejuni, and utilisation of qPCR has identified high frequency of detection of faecal carriage of S. enterica serovar Typhimurium in goats immediately following capture and transport. The qPCR method for detection may have underestimated the rate of faecal carriage that would be detected using culture methods that include selective enrichment. Further studies are warranted to determine the animal production and public health impacts of S. enterica serovar Typhimurium and C. jejuni in rangeland goats, and the impact of pre-slaughter management on faecal carriage.
164 CHAPTER 7. TRICHOSTRONGYLID NEMATODES IN CAPTURED RANGELAND GOATS
This chapter describes the pattern of Trichostrongylid nematode egg excretion determined by McMaster WEC flotation and molecular qPCR for captured rangeland goats at a commercial depot (feedlot).
Research highlights:
qPCR identified Haemonchus contortus and Trichostrongylus spp. in samples
collected on arrival at the goat depot, but not at subsequent sampling occasions.
Teladorsagia circumcincta was not detected on any sampling occasion.
McMaster WEC were below levels suggestive of clinical haemonchosis.
The qPCR egg count results were very high and not correlated with McMaster
WEC, thus qPCR was not quantitative for Trichostrongylid nematode screening.
165 7.1. Introduction
Trichostrongylid nematodes may cause scouring and ill thrift in goats (Hoste et al., 2008; Torres-Acosta and Hoste, 2008; Calvete et al., 2014). The most common species reported for goats in the arid and semi-arid regions of Australia are H. contortus, and Trichostrongylus spp. (Beveridge et al., 1987). The dominant Trichostrongylus spp. reported in Australian goats are T. vitrinus, T. axei, T. colubriformis and T. rugatus
(Beveridge et al., 1987). Nematode species and intensity of infection in sheep and goats is related to the rainfall in these regions (Beveridge and Ford 1982; Beveridge et al.,
1987). Infection may be associated with inappetence, weight loss and scouring, and may worsen if accompanied by low plain of nutrition (Gordon, 1948; Love and Hutchinson,
2003).
Worm egg counts (WEC) are commonly determined by microscopy using modified McMaster methods. A molecular technique based on quantitative PCR (qPCR) for the species-specific diagnosis of Trichostrongylid carriage/infections was successfully used by Harmon et al. (2007) and Ryan, 2016) to detect Trichstrongylid nematode eggs in faeces. Although qPCR has been used to confirm the presence of individual Trichstrongylid species in genomic DNA extracted from faecal samples and has the potential to quantify faecal carriage, the technique has, to the author’s knowledge, not been validated for goats, not confirmed to be quantitative, and has only been tested on DNA extracted from eggs purified from human and sheep faeces by either sodium nitrate flotation or column-purification methods (Bott et al., 2009; Hunt, 2011; Roeber et al., 2011).
The aim of this chapter was to determine whether quantitative PCR (qPCR) has utility in screening goat faecal samples for Trichstrongylid parasites (Haemonchus,
Teladorsagia and Trichostrongylus).
166 7.2. Materials and methods
7.2.1. Animals and sample collection
The sampling method is described in detail in Chapter 2, section 2.2.
7.2.2. Treatments
All goats were treated with an anthelmintic, 0.4 mg/kg moxidectin (Cydectin oral plus selenium®, Virbac Australia), and an anti-coccidial treatment (20 mg/kg toltrazuril,
Baycox®, Bayer Australia) immediately after the first (S1) and second (S2) sampling as part of the standard management practice for goats being introduced to the feedlot
(Section 2.4).
7.2.3. Faecal worm egg counts
Worm egg count was determined using a modified McMaster technique described in more detail in Chapter 2, section 2.5. Larval cultures were not performed.
7.2.4. DNA extraction and qPCR
DNA extraction and qPCR of Haemonchus, Teladorsagia and Trichostrongylus are described in detail in Chapter 2, sections 2.6 and 2.7.5. Briefly, faecal samples were screened and quantified for the presence of the Trichostrongylid nematodes using quantitative PCR (qPCR) as previously described by Harmon et al. (2007) and Ryan
(2016) (see section 2.7.5).
7.2.5. Statistical analyses
Prevalences with 95% intervals were calculated as proportion of goats that were
Trichostrongylid nematode-positive on at least one occasion. Quantitative PCR total
WEC was calculated by the sum total of egg counts calculated for Haemonchus,
Teladorsagia and Trichostrongylus. Faecal samples were categorised for
167 Trichostrongylid detection category as detected (McMaster WEC ≥50 epg or qPCR total
WEC ≥1 epg) or not detected (WEC less than 50 epg and qPCR 0) each for McMaster and total qPCR.
Analyses were performed using IBM SPSS statistics (version 24, IBM
Corporation). Nematode species prevalences were compared using Chi-square test with
Fishers exact test for significance. The WEC for each time point were compared using a general linear model with time point included as a fixed factor and post-hoc test to compare differences. Associations between McMaster WEC and total qPCR were determined using bivariate correlations with Pearson co-efficient. Agreement between methods for detection were evaluated using kappa statistic.
7.3. Results
The prevalence of Trichostrongylid nematodes is shown in Table 7.1.
Teladorsagia was not detected in any of the samples. Haemonchus and Trichostrongylus were detected at S1 by qPCR, but not at the subsequent sampling occasions (Table 7.1).
168 Table 7.1. Prevalence of Trichostrongylid nematodes as determined by qPCR, in 125 rangeland goats over 4 monthly sampling occasions (S1-S4).
Sampling occasion
S1 S2 S3 S4
H. contortus 24 (17.2, 32.0) a 0 (0, 2) b 0 (0, 2) b 0 (0, 2) b
T. circumcincta 0 (0, 2) 0 (0, 2) 0 (0, 2) 0 (0, 2)
Trichostrongylus spp. 26.4 (19.3, 34.6) a 0 (0, 2) b 0 (0, 2) b 0 (0, 2) b ab Point prevalence values in rows with different superscripts are significantly different (P<0.05).
McMaster WEC and qPCR WEC are shown in Table 7.2. The McMaster WEC were highest at S1. The McMaster WEC were below levels where clinical haemonchosis was likely. The qPCR WEC were very high, and the levels observed were not biologically plausible for WEC in otherwise healthy goats, especially considering the McMaster WEC
(Table 7.2). For example, 39/52 positive samples had qPCR WEC >10 000 epg, and 29/52 were >100 000 epg.
Table 7.2. Worm egg counts (WEC) determined by MacMaster and qPCR for 125 rangeland goats over 4 sampling occasions (S1-S4) approximately one month apart.
S1 S2 S3 S4 McMaster WEC (eggs per gram) Mean SE 450 ± 59 a 250± 37 b 150± 29 bc 100±27 c Range 0–1850 0–1350 0–1100 0–1600
qPCR WEC (eggs per gram)* Mean SE 1.47x109 ± 9.0x108 0 0 0 Range 0–8.4x1010 - - -
* All three nematode genera combined.
169 No correlation (Pearson correlation co-efficient -0.077; P=0.393) between
McMaster WEC and qPCR WEC were identified at S1, the only sampling occasions at which qPCR-positive samples were identified.
Agreement between qPCR and McMaster for detection of Trichostrongylid are shown in Table 7.3. Agreement between the methods for detection was very poor (kappa
0.056; P=0.160). Overall, 7.2% of samples were qPCR-positive/McMaster-negative and
19.8% of samples were McMaster-positive/qPCR negative.
Table 7.3. Agreement between qPCR and McMaster for detection of Trichostrongylid nematodes in goat faecal samples (n=500).
qPCR
Not detected Detected Total McMaster < 50 (not detected) 349 36 385 > 50 (detected) 99 16 115 Total 448 52 500
7.4. Discussion
Haemonchus contortus and Trichostrongylus spp. were identified in captured rangeland goats using qPCR. Both species have been previously reported in rangeland goats in arid regions of Australia (Beveridge et al., 1987), and are considered important nematodes in livestock (Cole, 1986). It was not surprising that Tel. circumcincta was not identified in faecal samples. The goats were sourced from remote arid and semi-arid regions where conditions are generally not conducive to survival of this parasite.
Quantitation for WEC with qPCR was not achieved in this study and the accuracy of qPCR for qualitative identification of Trichostronglid nematode species could not be validated because larval cultures were not performed to confirm species present. By the
170 time poor agreement between the methods was recognised, samples had been frozen and were not suitable for larval cultures. As such, only McMaster WEC are included as co- variates for analyses in Chapter 8 (conducted to determine relationships for pathogen detection with weight, growth, faecal consistency and scouring in goats), and analyses for associations between nematode species identification and production parameters should be interpreted with caution.
There was no correlation between WEC determined by McMaster and qPCR, and similarly the level of agreement for detection was very poor. Other studies have reported challenges in achieving precise quantitation with qPCR (Harmon et al., 2007). In the present study, WEC quantitation with qPCR greatly overestimated WEC relative to
McMaster method at S1, and the values observed at this time point were so high as to not be plausible. The reason for this was not determined, but it is possible that eggs in faecal samples had embryonated in the period between sample collection and DNA extraction.
Larval development would increase the amount of parasite DNA present relative to unembryonated Trichostrongylid eggs. It was also possible that Trichostrongylid genera not included in qPCR assay were present, and contributed to McMaster WEC. For example, Cooperia, Chabertia, Oesphagostamum have been reported in Australian goats
(Edgar, 1936; Beveridge et al., 1987). The presence of other genera would also explain the observation that 20% of samples were McMaster-positive/qPCR negative. Larval cultures that would have confirmed the presence of other genera were not performed.
The observation that 7.2% of samples were qPCR-positive/McMaster-negative could be explained by a number of factors. It is possible that the qPCR assay was detecting nematode DNA in small numbers of eggs in faeces (below normal detection limit for
McMaster WEC). The assay was performed using faecal extraction, not purified eggs, and it is possible faecal material contained nematode DNA not derived from eggs (for example, DNA in digesta derived from nematode larvae or adults).
171 Mean McMaster WEC were 100 epg at S2, S3 and S4, despite moxidectin treatment immediately after S1 and S2. It was not clear whether this represents reinfection, treatment failure or anthelmintic resistance. Treatment of goats with moxidectin is an off-label usage in Australia. The moxidectin dose (0.4 mg/kg) was consistent with recommendations by Kaplan (2014). The pre-patent period for H. contortus and Trichostrongylus spp. are 18–21 and 15-23 days respectively. Goats did not have access to pasture, so substantial reinfection was unlikely (Besier et al., 2016), but it is possible that some faecal contamination of feed and straw bedding had occurred.
Moxidectin does have label claim in sheep for 91 days protection for H. contortus and 49 days Trichostrongylus spp. (Vibrac Australia, 2011). Assuming this applies to goats, a fully effective dose at S1 and S2 would have been expected to have reduced re-infection.
Moxidectin resistance has not been reported in Trichostrongylus spp. for goats, but H. contortus resistance has been widely reported in Australia for sheep (Besier and Love,
2003; Le Jambre et al., 2005; Woodgate and Besier, 2010). However, these goats were wild prior to capture, and the goat parasite population is unlikely to have been exposed to moxidectin treatment, making resistance less likely to be present at meaningful levels.
The results suggest that any off-label use of moxidectin without WEC monitoring to determine efficacy should be discouraged in goat depots. Furthermore, as rangeland goats are wild and not habituated to close handling, oral dosing may render both goats and operator at risk of injury (Lyndal-Murphy et al., 2007). The use of non-chemical alternative management methods that include grazing rotations, nutritional supplements and bioactive tanniferous forages to control nematodes in Australian goats have been suggested.
172 7.5. Conclusion
The present study identified Haemonchus and Trichostrongylus spp. druing the first sampling following capture and transport of rangeland goats with no detection of
Teladorsagia using qPCR assays. Conventional McMaster technique was also carried out. However, as no larval culture were conducted, quantitation for WEC with qPCR was not achieved. Therefore, further qPCR analyses based on larval culture are required to obtain more comparable data to WEC. Further studies are also required to determine the extent of production loss associated with strongyle faecal carriages in rangeland goats.
173 CHAPTER 8. ASSOCIATIONS FOR ENTERIC PATHOGENS FAECAL CARRIAGE WITH GROWTH AND DIARRHOEA IN CAPTURED RANGELAND GOATS IN WESTERN AUSTRALIA
This chapter investigated possible associations between selected enteric pathogens (Cryptosporidium, Giardia, Eimeria, Entamoeba, Salmonella,
Campylobacter, Haemonchus and Trichostrongylus) with live weight, growth rate and body condition score (BCS) in captured rangeland goats at a commercial depot (feedlot) in Western Australia.
Research highlights:
Cryptosporidium faecal carriage was associated with lower growth, looser faeces
and higher scouring risk.
Cryptosporidium parvum and C. ubiquitum faecal carriage was associated with
scouring.
Giardia faecal carriage was associated with looser faeces, but no increase in
scouring risk.
Higher Eimeria shedding (oocysts per gram) was associated with looser faeces
immediately after capture and arrival at goat depot.
174 8.1. Introduction
Diarrhoea and ill-thrift (weight loss or poor growth rates) are cited as important issues for captured rangeland goats under intensive management conditions in goat depots
(Meat and Livestock Australia, 2016). The causes of diarrhoea and ill-thrift are not well described. Faecal carriage for Cryptosporidium and Giardia (Chapter 3), Eimeria
(Chapter 4), Entamoeba (Chapter 5), Salmonella and Campylobacter (Chapter 6),
Haemonchus and Trichostrongylus (Chapter 7) were identified in rangeland goats in a
Western Australian goat depot.
The aim of this chapter was to determine any association between faecal carriage for these pathogens with live weight, reduced growth or scouring.
8.2. Materials and methods
8.2.1. Animals and sample collection
The sampling is described in detail in section 2.2. Briefly, faecal samples, body weight and body condition assessments were collected from 125 male goats on four occasions (S1-S4) at approximately one-month intervals, with the first sample (S1) collected immediately after arrival at the depot.
8.2.2. Treatments
All goats were treated with an anthelmintic, 0.4 mg/kg moxidectin (Cydectin oral plus selenium®, Virbac Australia), and an anti-coccidial treatment (20 mg/kg toltrazuril,
Baycox®, Bayer Australia) immediately after the first (S1) and second (S2) sampling as part of the standard management practice for goats being introduced to the feedlot
(Section 2.4).
175 8.2.3. Measurements
Live weight was measured on each sampling occasions using electronic scales.
Body condition score (BCS) was measured by manual palpation using a scale of 1 (very thin) to 5 (very fat) as previously described (Sutherland et al., 2010). Faecal consistency score (FCS) was measured using a scale of 1 (hard dry pellet) to 5 (watery diarrhoea) as previously described (Greeff and Karlsson, 1997).
8.2.4. DNA extraction, detection and quantification for enteric pathogens
The DNA extraction and qPCR of Cryptosporidium, Giardia, Eimeria,
Salmonella, Campylobacter, Haemonchus and Trichostrongylus are described in detail in
Chapter 2. Faecal samples were screened and quantified for the presence of the selected enteric pathogens using quantitative PCR (qPCR) as described (section 2.7.1-2.7.5).
Entamoeba cysts in faecal samples were detected by microscopy and confirmed by nested
PCR as described in sections 2.8.7, 2.8.8 and 2.12.1. Faecal worm egg counts (WEC) were determined using a modified McMaster technique described in more detail in section
2.5.
8.2.5. Statistical analyses
The experimental unit for analyses was individual goats. Analyses were performed using SAS (Version 9.2, SAS Institute) for linear mixed effect models and
IBM SPSS statistics (version 24, IBM Corporation) for all other analyses.
Pathogen faecal carriage detection for each pathogen (Cryptospordium, Giardia,
Salmonella, Campylobacter, Haemonchus and Trichostrongylus) for each goat at each timepoint was categorised as detected (pathogen detected by qPCR) or absent (not detected). Pathogen faecal carriage for Cryptosporidium were categorised for species detection (e.g. C. xiaoi detected, C. ubiquitum detected, C. parvum detected,
176 Cryptosporidium spp. detected but not sequenced, no Cryptosporidium detected).
McMaster WEC and qPCR Eimeria OPG were log-transformed for analyses using Log10
(x + 25) where x = trichostrongylid eggs or Eimeria oocysts per gram of faeces. Monthly growth rate was determined by calculating weight change for the one-month period following faecal sample collection (future growth) for sampling occasions 1-3, and the one-month period before faecal sample collection (past growth) for sampling occasions
2-4.
Faecal samples were categorised as scouring (FCS 4 or higher) or not scouring
(FCS 1-2). There were no faecal samples with FCS=3. Prevalence for scouring (% samples categorised as scouring) were determined for faecal samples with and without faecal carriage detected for each pathogen. Scouring prevalence for faecal samples with or without enteric pathogens detected were compared using the Chi-squared test with
Fishers exact 2-sided test for independence. Odds ratios were used to calculate relative risk for scouring for pathogen detection categories.
Associations between oocyst counts (McMaster trichostrongylid WEC and qPCR
Eimeria OPG) and live weight, past growth, future growth, BCS and FCS were determined using bivariate correlations with Pearson co-efficient. Correlations were determined both separately for each time point and for all time points combined.
Live weight, future growth, past growth and FCS were analysed using linear mixed effects models. Initially base models were constructed for each dependent variable, with pen number (1-4) and sampling occasion (S1, S2, S3 or S4) included as fixed effects, and log transformed WEC and OPG included as covariates. To account for repeat sampling of individuals across the four time-points, animal identification code was included as a random term. Within these base models, pathogen detection (detected or absent) was included as a fixed effect, giving a total of 6 models (one per pathogen) for each dependent variable (live weight, past growth, future growth and FCS). Interactions
177 between the pathogen term and other factors in the base model were tested, and non- significant terms (P>0.05) were removed in a step-wise manner. Least square means were generated for significant pathogen main effects.
8.3. Results
8.3.1. Pathogens prevalence and faecal shedding
The prevalence and faecal carriage (shedding) intensity for faecal pathogens are summarised in Table 8.1 (WEC and Eimeria counts) and Table 8.2 (pathogen prevalence), and are described in detail in Chapter 3 (Cryptosporidium and Giardia),
Chapter 4 (Eimeria), Chapter 5 (Entamoeba), Chapter 6 (Salmonella and
Campylobacter), Chapter 7 (Trichostrongylid nematodes). With the exception of
Eimeria, prevalence and shedding intensity for the pathogens identified in this study were highest at S1, immediately following arrival at the goat depot. Eimeria prevalence (Table
8.2) and shedding intensity (Table 8.1) were highest at S2, approximately one month after arrival at the goat depot.
Table 8.1. Mean (± standard error) and range for worm egg count (WEC) (determined by microscopy) and Eimeria oocyst count (determined by qPCR) for 125 goats sampled on 4 occasions (S1-S4).
WEC (eggs per g faeces) Eimeria (oocysts per g faeces) Sampling occasion Mean ± SE Range Mean ± SE Range
S1 450 ± 59 a 0–1850 530 ± 183 a 0-15 908 S2# 250 ± 37 b 0–1350 10 525 ± 2496 b 0-191 821 S3# 150 ± 29 bc 0–1100 350 ± 88 a 0-5375 S4# 100 ± 27 c 0–1600 1 ± 1 c 0-73 abc Values in columns with different superscripts are significantly different (Peason or Fishers 2-sided exact test P<0.05). #Goats were treated with moxidectin and toltrazuril after S1 and S2.
178 Table 8.2. Enteric pathogen prevalence (% with 95% confidence interval in parentheses) for 125 goats sampled on 4 occasions (S1-S4).
Sampling occasion
S1 S2 S3 S4 Screening method (reported prevalence)
Cryptosporidium spp. 14.4 (9.1, 21.3) a 4.0 (1.5, 8.5) b 3.2 (1.1, 7.4) b 7.2 (3.6, 12.7) ab qPCR (Chapter 3) a b b b C. xiaoi 8.8 (4.8, 14.7) 2.4 (0.7, 6.3) 0.8 (0.1, 3.7) 1.6 (0.3, 5.0) qPCR & sequencing (Chapter 3) a b b b C. unbiquitum 5.6 (2.5, 10.7) 0.8 (0.1, 3.7) 0 (0, 2.0) 0 (0, 2.0) qPCR & sequencing (Chapter 3)
a a a b C. parvum 0 (0, 2.0) 0 (0, 2.0) 0 (0, 2.0) 3.2 (1.1, 7.4) qPCR & sequencing (Chapter 3)
Giardia duodenalis Assemblage E 12.0 (7.2, 18.5) a 4.0 (1.5, 8.5) b 7.2 (3.6, 12.7) ab 7.2 (3.6, 12.7) ab qPCR (Chapter 3)
Eimeria* 50.4 (41.7, 59.1) a 70.4 (62.0, 77.9) b 44.8 (36.3, 53.6) a 2.4 (0.7, 6.3) c qPCR (Chapter 4)
Entamoeba# 6.4 (3.1, 11.7) - - - Microscopy & nested PCR (Chapter 5)
Salmonella enterica serovar Typhimurium 25.6 (18.6, 33.8) a 4.8 (2.0, 9.6) b 1.6 (0.3, 5.0) b 0 (0, 2) b qPCR & sequencing (Chapter 6)
Campylobacter jejuni 8 (4.2, 13.7) a 0.8 (0, 3.7) b 0.8 (0, 3.7) b 0 (0, 2) b qPCR & sequencing (Chapter 6)
b b b Haemonchus contortus* 24.0 (17.2, 32.0) a 0 (0, 2) 0 (0, 2) 0 (0, 2) qPCR (Chapter 7)
Teladorsagia circumcincta* 0 (0, 2) 0 (0, 2) 0 (0, 2) 0 (0, 2) qPCR (Chapter 7)
b b b Trichostrongylus* 26.4 (19.3, 34.6) a 0 (0, 2) 0 (0, 2) 0 (0, 2) qPCR (Chapter 7)
*Goats were treated with moxidectin and toltrazuril after S1 and S2. # Determined for S1 only. abc Point prevalence values in rows with different superscripts are significantly different (P<0.05).
179 8.3.2. Associations for enteric pathogens with live weight and BCS
Associations for detection of faecal carriage with live weight and body condition
(BCS) are shown in Table 8.3. There was no association between live weight and faecal carriage for any of the identified pathogens.
Associations for live weight and BCS with WEC and OPG are shown in Table
8.4. Weak but significant negative correlations over the entire sampling period were identified for Eimeria with live weight, and for both WEC and Eimeria with BCS (Table
8.4).
Table 8.3. Association of pathogen faecal shedding category with live weight and body condition score determined using linear mixed effects models, with least square means ± standard error (LSM ± SE), F-value and P-value for pathogen main effect.
Live weight and BCS for faecal Main effect carriage categories (LSM ± SE) Pathogen Not detected F-value P-value detected Liveweight (kg) Cryptosporidium 34.34 ± 0.68 34.13 ± 0.42 0.13 0.717 Giardia 34.29 ± 0.66 34.13 ± 0.42 0.08 0.779 Entamoeba# 32.14 ± 2.37 31.34 ± 0.52 0.11 0.74 Salmonella 33.18 ± 0.69 34.23 ± 0.42 3.07 0.081 Campylobacter 33.21 ± 1.10 34.17 ± 0.41 0.85 0.359 Haemonchus 33.75 ± 0.78 34.17 ± 0.42 0.36 0.548 Trichostrongylus 34.44 ± 0.74 34.12 ± 0.42 0.23 0.633
Body condition score Cryptosporidium 2.07 ± 0.06 2.06 ± 0.02 0.00 0.977 Giardia 2.14 ± 0.06 2.06 ± 0.02 2.12 0.146 Entamoeba# 1.86 ± 0.17 1.76 ± 0.04 0.32 0.575 Salmonella 2.07 ± 0.06 2.06 ± 0.02 0.00 0.952 Campylobacter 2.17 ± 0.10 2.06 ± 0.02 1.16 0.282 Haemonchus 2.14 ± 0.07 2.06 ± 0.02 1.37 0.242 Trichostrongylus 2.05 ± 0.07 2.06 ± 0.02 0.02 0.875 #Determined at S1 only.
180 Table 8.4. Live weight and body condition score (BCS) for goats at four sampling occasions (S1-S4) and bivariate correlations (Pearson co-efficient) with McMaster worm egg count (WEC) and qPCR Eimeria oocyst count (OPG). Significant correlations (P<0.05) are shown in bold.
Correlations for live weight or BCS WEC OPG Sample occasion n Mean ± SE Range Pearson P-value Pearson P-value Liveweight (kg) S1 125 31.42 ± 0.49 17.0 – 49.0 0.033 0.713 -0.019 0.829 S2* 125 32.81 ± 0.50 21.0 – 51.0 0.141 0.117 -0.093 0.304 S3* 125 34.69 ± 0.45 21.5 – 50.5 0.048 0.596 0.062 0.496 S4* 125 37.70 ± 0.44 23.5 – 53.5 0.012 0.894 -0.021 0.820 Total 500 34.16 ± 0.26 17.0 – 53.5 -0.036 0.422 -0.143 0.001 Body condition score S1 125 1.76 ± 0.04 1 – 3 0.032 0.727 -0.008 0.931 S2* 125 2.02 ± 0.03 1 – 3 0.010 0.916 -0.098 0.278 S3* 125 2.23 ± 0.03 1 – 3 0.046 0.613 -0.026 0.772 S4* 125 2.24 ± 0.03 1 – 3 0.015 0.869 -0.115 0.201 Total 500 2.06 ± 0.02 1 – 3 -0.096 0.031 -0.096 0.032
SE: standard error. *Goats were treated with moxidectin and toltrazuril after S1 and S2.
8.3.3. Associations between enteric pathogens and growth
Growth for goats over sampling period (S1-S4) are shown in Table 8.5. The mean live weight change ranged 1.4–3.0 kg per month, but at each sampling occasion subsequent to arrival at the feedlot, the range of growth rates observed included goats that had lost weight relative to previous sampling.
181 Table 8.5. Growth for rangeland goats at four sampling occasions (S1-S4).
Growth (kg)
Sampling period Mean ± SE Range
S1-S2 1.39 ± 0.39 -9.0 – 13.5 S2-S3 1.88 ± 0.32 -6.0 – 12.5 S3-S4 3.02 ± 0.18 -0.5 – 15.0 Overall growth (S1-S4) 6.28 ± 0.46 -6.0 – 26.0
Associations for detection of faecal carriage with growth are shown in Table 8.6.
Cryptosporidium faecal carriage was associated with 1.48 kg lower growth for the one- month period after sampling (P=0.041; Table 8.6). No other associations were reported for faecal carriage with any pathogens tested with past growth or future growth.
182 Table 8.6. Association of pathogen faecal shedding category with weight change for one month previous to sampling (past growth) and one month after sampling (future growth) determined using linear mixed effects models, with least square means ± standard error
(LSM ± SE), F-value and P-value for pathogen main effect. Significant main effects
(P<0.05) are shown in bold.
Weight change for faecal carriage Main effect categories (LSM ± SE) Pathogen detected Not detected F-value P-value Past growth (kg/month) Cryptosporidium 2.08 ± 0.83 2.09 ± 0.19 0.00 0.995 Giardia 2.76 ± 0.74 2.04 ± 0.19 0.88 0.350 Entamoeba# - - - - Salmonella 2.36 ± 1.28 2.08 ± 0.18 0.05 0.827 Campylobacter 3.78 ± 2.55 2.08 ± 0.18 0.45 0.504 Haemonchus - - - - Trichostrongylus -0.16 ± 3.56 2.09 ± 0.18 0.40 0.529 Future growth (kg/month) Cryptosporidium 0.71 ± 0.69 2.19 ± 0.19 4.23 0.041 Giardia 1.22 ± 0.69 2.16 ± 0.19 1.87 0.173 Entamoeba# 2.67 ± 1.88 1.38 ± 0.41 0.45 0.505 Salmonella 3.05 ± 0.59 1.97 ± 0.19 2.94 0.088 Campylobacter 3.41 ± 1.10 2.05 ± 0.18 1.49 0.223 Haemonchus 3.38 ± 0.71 1.98 ± 0.19 3.60 0.059 Trichostrongylus 1.38 ± 0.69 2.16 ± 0.19 1.11 0.292
#Determined at S1 only.
Association between faecal carriage for the Cryptosporidium identified and growth are shown in Table 8.7. Compared to samples without Cryptosporidium detected,
C. xiaoi faecal carriage was associated with 1.95 kg lower growth in the following month
(P=0.047). There was no statistically significant difference in future growth associated
183 with faecal carriage for C. ubiquitum (P=0.105). The mean lower growth value of 2.1 kg for C. ubiquitum, however, significance is likely constrained by sample size.
Table 8.7. Association between faecal carriage for Cryptosporidium species and future growth determined using linear mixed effects models, with least square means ± standard error (LSM ± SE), F-value and P-value for pathogen (Cryptosporidium species) main effect.
Cryptosporidium- Future growth (kg/month) positive samples (n) LSM ± SE Not detected 467 2.19 ± 0.19 a C. xiaoi 16 0.25 ± 0.95 b
C. parvum 4 N/A C. ubiquitum 8 0.09 ± 1.27 ab Not sequenced 5 5.16 ± 2.49 ab
F-value 2.5 P-value 0.06 ab values in column with different superscripts are significantly different (P<0.05). N/A – all positive samples were at S4 so future growth not determined.
184 Association between WEC and Eimeria OPG with past and future growth are shown in Table 8.8, with no significant association between WEC or OPG with past or future growth identified.
Table 8.8. Bivariate correlations (Pearson co-efficient) between growth for past (preceding month) or future (following month) growth with McMaster worm egg count (WEC) and qPCR Eimeria oocyst count (OPG).
Association with WEC Correlation with OPG
Sampling Pearson P-value Pearson P-value periods coefficient coefficient Past growth (kg/month) S1 - - - - S2* 0.121 0.181 0.006 0.945 S3* -0.032 0.725 0.119 0.187
S4* -0.131 0.146 -0.130 0.150 Future growth (kg per month) S1 0.096 0.286 0.061 0.498 S2* -0.142 0.114 0.155 0.084
S3* -0.054 0.559 0.084 0.350 S4* - - - -
*Goats were treated with 0.4 mg/kg moxidectin after S1 and S2.
8.3.4. Associations for enteric pathogens with faecal consistency and scouring
Associations for detection of faecal carriage are shown in Table 8.9 (all pathogens) and Table 8.10 (Cryptosporidium). Cryptosporidium (all species) faecal carriage was associated with 0.92 higher FCS, and Giardia faecal carriage was associated with 0.4 higher FCS relative to samples without these pathogens detected (Table 8.9).
Faecal carriage for C. xiaoi (0.5 higher FCS; P=0.030), C. ubiquitum (1.45 higher FCS;
P<0.001) and C. parvum (1.55 higher FCS; P<0.001) were each associated with higher
185 FCS compared to Cryptosporidium-negative samples (Table 8.10). No other associations were noted for FCS for any of the other pathogens identified.
Table 8.9. Association of pathogen faecal shedding category with faecal consistency score (FCS) determined using linear mixed effects models, with least square means ± standard error (LSM ± SE), F-value and P-value for pathogen main effect. Significant main effects (P<0.05) are shown in bold.
FCS for faecal carriage categories Main effect
(LSM ± SE) Detected Not detected F-value P-value
Cryptosporidium 2.34 ± 0.15 1.42 ± 0.05 36.49 <0.001
Giardia 1.86 ± 0.15 1.46 ± 0.05 7.10 0.008
Entamoeba# 1.35 ± 0. .33 1.34 ± .07 0.01 0.977
Salmonella 1.30 ± 0.16 1.50 ± 0.05 1.52 0.219
Campylobacter 1.19 ± 0.28 1.49 ± 0.05 1.13 0.288
Haemonchus 1.82 ± 0.18 1.47 ± 0.05 3.54 0.061
Trichostrongylus 1.51 ± 0.18 1.49 ± 0.05 0.02 0.883
#Determined at S1 only.
186 Table 8.10. Association for faecal shedding of different Cryptosporidium species with faecal consistency score (FCS) determined using linear mixed effects models with least square means ± standard error (LSM ± SE), and proportion of samples (%) categorised as scouring in each category with Chi-square Fishers’ 2-sided exact test for significance.
Category Samples (n) FCS % Scouring
(LSM ± SE) No Cryptosporidium detected 467 1.43 ± 0.05 a 9.2% a C. xiaoi 16 1.92 ± 0.22 b 12.5% ab C. parvum 4 2.98 ± 0.44 c 50.0% bc C. ubiquitum 8 2.88 ± 0.31 c 62.5% c Cryptosporidium-positive but not 5 1.96 ± 0.39 abc 20.0% abc sequenced
Cryptosporidium species detection main effect F-value 9.63 - P-value <0.001 - abc Values in columns with different superscripts are significantly different (P<0.05).
The prevalence for scouring in samples with and without pathogen faecal carriage detected are shown in Table 8.10 (Cryptosporidium species only) and Table 8.11 (all pathogens tested). The prevalence for diarrhoea was 21.1% higher for Cryptosporidium- positive samples (prevelance 30.3%) compared with Cryptosporidium-negative samples
(prevelance 9.2%, P<0.001) (Table 8.11), and Cryptosporidium-positive samples were
4.3 (95% confidence interval 1.9, 9.6; P<0.001) times more likely to be classified as scouring compared with Cryptosporidium-negative samples. Compared to
Cryptosporidium-negative samples, C. parvum-positive samples were 9.9 (95% CI 1.4,
71.7; P=0.047) times more likely to be classified as scouring, and C. ubiquitum-positive samples were 16.4 (95% CI 3.8, 71.1; P<0.001) were more likely to be classified as
187 scouring. Associations between scouring prevalence and pathogen faecal carriage for pathogens other than Cryptosporidium spp. were not identified.
188 Table 8.11. Comparison of scouring prevalence (% faecal samples with FCS > 3) for samples with and without pathogen faecal carriage detected with 2-sided Fishers’ exact test for significance. Significant effects (P<0.05) are shown in bold.
Scouring prevalence (%) Pathogen detected Not detected P-value Cryptosporidium 33.3 9.2 <0.001 Giardia 18.4 10.0 0.105 Entamoeba# 0.0 6.8 1.000 Salmonella 5.0 11.1 0.294 Campylobacter 0 10.8 0.616 Haemonchus 10.0 10.6 1.000 Trichostrongylus 5.9 10.9 0.563
#Determined at S1 only.
Correlations for WEC and Eimeria OPG with FCS are shown in Table 8.12.
Positive correlations between Eimeria OPG and FCS were noted at S1 and for overall sampling period. No correlations between WEC and FCS were noted.
189 Table 8.12. Mean faecal consistency score (FCS) ± standard error (SE) for goats sampled at four sampling occasions (S1-S4) and bivariate correlations (Pearson co-efficient) with McMaster worm egg count (WEC) and qPCR Eimeria oocyst count (OPG). Significant correlations (P<0.05) are shown in bold.
Faecal consistency score (FCS)
Correlations for FCS Sample occasion Association with WEC Association with OPG
Mean ± SE Range Pearson P-value Pearson P-value n S1 125 1.33 ± 0.07 1 - 5 -0.127 0.159 0.558 <0.001 S2 125 2.16 ± 0.12 1 - 5 -0.113 0.211 -0.110 0.221 S3 125 1.26 ± 0.06 1 - 5 -0.032 0.724 0.040 0.656 S4 125 1.20 ± 0.06 1 - 4 -0.034 0.706 -0.047 0.604 Total 500 1.49 ± 0.04 1 - 5 -0.047 0.292 0.231 <0.001
190 8.4. Discussion
The major findings in this chapter were that Cryptosporidium, and specifically C. xiaoi, was the only pathogen associated with lower growth of captured rangeland goats.
Cryptosporidium faecal carriage, and specifically C. parvum and C. ubiquitum were associated with looser faeces and increased risk of scouring. Giardia faecal carriage was associated with looser faeces (higher FCS), but no increase in scouring. Higher Eimeria oocyst counts were associated with looser faeces at the first sampling occasion, immediately after capture and transport to the goat depot. Pathogen faecal carriage was generally low after the first sample occasion, and results should be interpreted with this in mind. It is likely that different impacts would be identified in the event of outbreaks of clinical disease (e.g. salmonellosis or coccidiosis).
Cryptosporidium faecal carriage was associated with 1.5 kg lower growth in the subsequent one-month period. More specifically, C. xiaoi was associated with 2.3 kg lower growth in following month. This is the first report for reductions in growth associated with C. xiaoi in Australian goats or sheep. There was no association with live weight, suggesting that a bias to faecal carriage by smaller goats or goats in poor body condition could confound growth. The rate of faecal carriage detection for C. parvum and
C. ubiquitum were low (point prevalences <6%), and C. parvum was only detected at the last timepoint, so the absence of a statistical difference in growth or live weight for these species was not unexpected. Jacobson et al (2016) observed 2.3-4.5 kg lower live weight with C. parvum faecal carriage in Australian lambs, but found no association between
Cryptosporidium (all species) or Giardia and weight which was in agreement to the present study. A previous study identified C. xiaoi in diarrhoeic goat kids in Spain (Díaz et al., 2010), providing further support that this parasite species may be involved in the aetiology of caprine diarrhoea.
191 Carcass weight was not measured in the present study. Use of liveweight change or other measures based on live weight (such as feed conversion efficiency) may underestimate the impact of nematodes (Liu et al., 2005; Jacobson et al., 2009) and protozoans (Sweeny, 2012a; Sweeny et al., 2012b; Jacobson et al., 2016) and may underestimate carcass productivity losses associated with parasitism in sheep and goats.
Therefore, measurement of carcass weight and/or lean meat yield may better reflect the true economic effect of parasitism in meat production systems (Jacobson et al., 2009;
Sweeny, 2012a; Jacobson et al., 2016). Body condition may be a more appropriate measure of impact on body tissues than weight because it is not biased by weight of gastrointestinal organs, overall size, pregnancy, fleece and so on. However, BCS by manual palpation is typically not sensitive enough to detect small changes in fat and muscle deposition.
Cryptosporidium and Giardia faecal carriage, and higher Eimeria oocyst count at
S1 were associated with softer, looser faeces (higher FCS). Higher Eimeria oocyst counts were associated with softer, looser faeces (higher FCS) at S1, immediately after arrival at the depot. The risk of faecal soiling of the breech and haircoat increased when faeces were no longer in a pelleted form (FCS≥3). Faecal carriage of Cryptosporidium, and specifically C. parvuum and C. ubiquitum were associated with a greater than 5-fold increase in risk of scouring relative to absence of Cryptosporidium faecal carriage and an increased risk of goats producing non-pelleted faeces. This was in agreement with
Sweeny et al., (2011a) who reported that Cryptosporidium and Giardia faecal carriage detected by qPCR were associated with an increased risk of liquid faeces (FCS≥3.0). This association for scouring with C. parvum and C. ubiquitum faecal carriage has important implications post-farm as scouring may increase risk of carcass contamination, and both are considered zoonotic (Chapter 3). More generally, Cryptosporidium in Australian
192 goats is not well described, and the association with reduced growth confirms the need for better epidemiological studies to determine impacts for the goat meat industry.
Weak but significant negative correlations over the entire sampling period were identified between body condition for WEC, and both weight and body condition (BCS) for Eimeria oocyst count. This suggests that lighter goats had higher Eimeria oocyst shedding concentrations, and animals in poorer body condition had both higher WEC and higher Eimeria oocyst shedding concentration. However, the correlations were weak, suggesting weight and BCS explain only a small proportion (less than 15%) of the variation observed.
There were no associations for S. enterica serovar Typhimurium and C. jejuni faecal carriage with weight or BCS, meaning there was no evidence to suggest faecal carriage was biased towards smaller or thinner goats.
There were a number of limitations for the present study. Sampling occurred at only one depot, and did not capture variation between seasons and years. Hence in future, a similar study needs to be conducted on captured rangeland goat flocks from a wider geographic area to determine pathogen epidemiology, risk factors associated with faecal carriage, and impacts on goat health and production. The qPCR assay for nematodes was not validated using faecal culture, so the observations of no association between detection and weight, growth, or FCS should be interpreted with caution. Goats were treated twice with anthelmintics and anticoccidials, which likely interfered with identifying associations between Eimeria and nematodes with growth and scouring. As mentioned above, measurement of carcase weight would have been a more sensitive measure than live weight for impacts on the goat meat industry. There were a number of factors that impact the reliability of live weight, including goat movement during the weighing process, variable gastrointestinal weight due to differences in contents/fill relating to feed intake time off feed at the time of weighing (Thompson et al., 1987; Warriss et al., 1987).
193 8.5. Conclusion
The experiments described in this thesis demonstrated faecal carriage for a range of bacteria, protozoan and nematode parasites, but only Cryptosporidium was associated with an increased risk of scouring and reduced growth. Giardia faecal carriage and higher
Eimeria oocysts counts were associated with looser faecal consistency, but not to the point where scouring risk was increased. Further studies are warranted to determine the production impacts associated with Cryptosporidium for goats.
194 CHAPTER 9. SALMONELLA ENTERICA ISOLATES FROM WESTERN AUSTRALIAN RANGELAND GOATS REMAIN SUSCEPTIBLE TO CRITICALLY IMPORTANT ANTIMICROBIALS
The contents of this chapter have been submitted for publication at Journal of
Scientific Reports.
This chapter describes the prevelance, molecular characterisation of Salmonella enterica isolates and antimicrobial resistance among Salmonella isolates from rangeland goats in Western Australia. Three methods were used: (1) culture and MALDI-TOF for
Salmonella isolation and identification and (2) one-step PCR at multiple loci for molecular characterisation of Salmonella serovars in slaughtered rangeland goats and (3) minimum inhibitory concentrations (MICs) were determined using the broth microdilution assay to determine the MICs of 13 antimicrobial agents tested.
Research highlights:
High carriage of Salmonella among slaughtered rangeland goats may indicate
downstream carcass contamination and food safety concerns.
Faecal carriage of three Salmonella serovars identified using molecular tools, with
S. Typhimurium predominant.
Low antimicrobial resistance rates among the Salmonella isolates from goats are
encouraging.
195 Abstract: This study investigated faecal carriage and antimicrobial resistance (AMR) of
Salmonella enterica recovered from rangeland goats. Faecal samples (n=400) were collected at slaughter from four consignments of goats (n=100 samples per consignment), each from one of four localities in Western Australia. Carriage of Salmonella spp. was detected in 106 samples (26.5%; 95% CI 22.4–31.0%). The rate of faecal carriage for each consignment ranged between 23-30%. PCR assays targeting the STM2755 and
STM4497 genes revealed 84.9% of the isolates were of serovar Typhimurium.
Salmonella Chester (11/106, 10.4%) and S. Saintpaul (5/106, 4.7%) were characterised at invA and ompF genes. Antimicrobial susceptibility testing demonstrated that 84.0% of isolates were susceptible to all tested (n=13) antimicrobials. Resistance was identified to azithromycin (14.2%), tetracycline (10.4%), ampicillin (5.7%), amoxicillin–clavulanate and cefoxitin (3.8%), trimethoprim/sulfamethoxazole (1.9%), gentamicin and streptomycin (0.9%). No isolate was resistant to four or more antimicrobials, or to critically important antimicrobials such as fluoroquinolones and extended spectrum cephalosporins. This is the first study reporting AMR in Salmonella isolates from
Australian rangeland goats. The rate of detection of AMR was very low, some resistance to low-importance drugs was present in the Salmonella population, despite the absence of active selection pressure.
9.1. Introduction
Antimicrobial resistance (AMR) is a human and animal health issue due to the potential for the transmission of antimicrobial resistant bacteria between animals and humans via a number of pathways (Founou et al., 2016). There are widespread concerns that emergence of antimicrobial resistance in animal bacteria to last line or so called
“critically important antimicrobials” (CIAs) can have detrimental impacts on human health (Economou and Gousia, 2015). CIA-resistance in non-typhoidal Salmonella is of
196 special interest because the organism is readily transmitted to humans in under-cooked meat products, via direct contact with animals and via the environment (Mukerji et al.,
2017). Although most such infections are self-limiting, a small proportion can result in serious disease with poor outcomes when the range of therapeutic options is limited due to the pathogen possessing resistance to CIAs (Roca et al., 2015).
Non-typhoidal Salmonella that are resistant to CIAs appear to be very rare in
Australian food-producing animals (Abraham et al., 2014; Barlow et al., 2015). This is attributed to the country’s isolation, quarantine restrictions, extensive livestock systems and strong regulations that virtually exclude the use of CIAs in food- producing animals
(Cheng et al., 2012). Nevertheless, in other parts of the world carbapenemase-producing
Enterobacteriaceae (Escherichia coli) have been detected in livestock (buffalo calves and beef cattle) (Singh et al., 2012), and recently in free-ranging Australian silver gull (E. coli) (Dolejska et al., 2016) and domestic cats (Abraham et al., 2016) (S. enterica serovar
Typhimurium) have been shown to harbour these organisms despite the low likelihood that any animals in these populations have ever received antimicrobials (Sherley et al.,
2000; Dolejska et al., 2016). This raises the possibility that extensively-grazed food- animals in remote areas might also be vulnerable to colonisation with CIA resistant
Salmonella, even though the chance that such animals are exposed to antimicrobials is extremely low due to the low incidence of bacterial disease, lack of opportunity to handle animals and administer treatments if required.
The Australian goat-meat industry is dominated by rangeland goats and is valued at $241.8 million p.a., with approximately 90% of products exported (Meat and Livestock
Australia, 2016). A great deal of effort is expended during processing to minimise the transfer of faecal flora (including Salmonella) onto carcases (Australian Quarantine and
Inspection Service, 2000; Duffy et al., 2009). A number of enteric pathogens, including
S. enterica serovar Typhimurium, have been reported in rangeland goats. Serotyping and
197 phage-typing of rumen, faecal and carcass samples from rangeland goats at slaughter identified that the predominant Salmonella enterica serovars were S. Saintpaul, S.
Typhimurium and S. Chester (Duffy et al., 2009). Knowledge of the occurrence of AMR in rangeland goats is useful for understanding the ecology of AMR in general because these animals have negligible contact with humans, are rarely subject to management interventions (including antimicrobial treatment), and are typically stocked at low density in remote, semi-arid and arid areas of Australia. The aims of the present study were to determine the prevalence and antimicrobial resistance status of non-typhoidal Salmonella in the faeces of Australian rangeland goats presented for slaughter in Western Australia.
9.2. Materials and methods
9.2.1. Study design and sample collection
Rangeland goats (Capra hircus) were sampled at a processing establishment located in the Beaufort River region of Western Australia that processes goats, sheep and occasionally deer. Goats were captured from the arid zones in Western Australia and were originated from four consignments between November and December 2016.
Consignments were sourced from Meedo Station in the Carnarvon region, Tamala Station in the Shark Bay region, Wagga Wagga Station in the Yalgoo region, and Wooramel
Station in the Wooramel region. The stations were approximately 120-650 km apart. As part of the standard management practice, goats were trapped in yards and supplied with oaten hay and water ad libitum. Goats were loaded in the morning (05:30) and transported in open trailers for approximately 12 hours. On arrival at the abattoir (lairage), goats were kept in a shaded pen with access to water. Slaughter commenced at 10:00am on the day following transport. Slaughter of goats from different consignments was occurred on different days.
198 From each of the four consignments, 100 goats were sampled with specimens collected at regular time intervals (approximately two to four minutes) as the consignment was processed so as to spread the sampling across the entire consignment. After evisceration, goats’ digestive tracts were separated from carcasses for collection of offal.
For each sample, approximately 25 g of faecal contents was obtained by making a transverse incision of the large intestine 10 to 20 cm proximal to the anus using a sterile scalpel blade and then using a sterile-gloved hand to express faecal matter into a sterile polypropylene container. Samples were then immediately labelled, stored on ice or in a refrigerator (4.0°C), while being transported to the laboratory for isolation of Salmonella later that day.
Sample collection methods were approved by Murdoch University Animal Ethics
Committee (approval number R2617/13). All methods were carried out in accordance with relevant guidelines and regulations.
9.2.2. Salmonella isolation and identification
Samples for isolation of Salmonella were as described by Garcia (2010). Briefly,
10 g of each faecal sample were transferred aseptically to each of 7 mL of 0.1% Buffered
Peptone Water (BPW) and 7mL Rappaport–Vassiliadis (RV) broth, mixed, allowed to settle and incubated for 18–24 h at 37 °C and 42 °C, respectively. After incubation, a loopful of each enrichment broth was inoculated onto Xylose Lysine Deoxycholate
(XLD) (Oxoid CM0469, Basingstoke, England) agar and Brilliance Salmonella (BS)
(Thermofisher Scientific, Australia) and each were incubated at 37°C for 24 hrs. Typical
Salmonella colonies identified by colony morphology (e.g. black and pink colonies on
XLD and BS agars respectively) were further cultured into Colombia sheep blood agar
(ThermoFisher Scientific, Australia) and incubated at 37 °C for 24 h. From each plate
199 10–25 colonies were harvested, deposited in Brain Heart Infusion (BHI) broth containing glycerol (20% v/v) and stored frozen at − 80 °C until further use.
Identification of organisms as Salmonella was achieved using Matrix Assisted
Laser Deionised Time of Flight (MALDI–TOF) analysis as follows. All samples of presumptively positive colonies were inoculated onto Colombia sheep blood agar
(ThermoFisher Scientific, Australia), incubated at 37 °C for 24 h and then transferred to a target plate (96 MSP, Bruker® – Billerica, USA). A minimum amount of colonies were carefully transferred to the centre of each well of the microplate to avoid cross contamination. Control wells (without bacteria) were also used on each target plate. The bacterial spot was covered with a lysis solution (70% formic acid; Sigma–Aldrich®) followed by 1 μL aliquot of matrix solution (alpha-ciano-4-hidroxi-cinamic acid diluted in 50% acetonitrile and 2.5% trifluoroacetic acid, Sigma–Aldrich®). The spectra of each sample were collected in a mass range between 2000 and 20,000 m/s, and then were analyzed by the MALDI Biotyper 2.0 (Bruker®) program, using the standard configuration for bacteria identification, which compared the spectrum of the samples with the references in the database. The results vary on a 0–3 scale, where the highest value indicates a more precise match and reliable identification. In the current study, the values accepted for matching were greater than or equal to 2.
9.2.3. DNA Extraction
All the Salmonella isolates were sub-cultured on Columbia sheep blood agar
(ThermoFisher Scientific, Australia) and incubated overnight at 37 °C. The genomic
DNA was purified from a single colony from the overnight cultures using the DNeasy®
Blood & Tissue Kit (Qiagen, Hilden, Germany) following the manufacturer’s recommendations and stored at −20°C until use. A negative control (saline) was used in each extraction group.
200 9.2.4. PCR amplification and sequencing
All MALDI-TOF positive isolates were subjected to PCR using serovar
Typhimurium specific primers targeting the putative hexulose-6-phosphate synthase
(STM2755; 406 bp amplicon) and cytoplasmic proteins (STM4497; 523 bp amplicon) and PCR conditions previously described (Shanmugasundaram et al., 2009). A previously characterized S. enterica serovar Typhimurium isolate (Abraham et al., 2016) was used as a positive control. Isolates which returned negative results using the STM2755 and
STM4497 primer sets were further subjected to PCR for the S. enterica ompF (578 bp amplicon) and invA (521 bp amplicon) genes as described (Swamy et al., 1996; Tatavarth and Cannons, 2010). Previously characterized S. enterica serovars Dublin, Enteritidis,
Hadar and Hato (Harb et al., 2017) (SFI-4-7) were used as positive controls. PCR products were separated by gel electrophoresis and purified using an in-house filter tip method previously described (Yang et al., 2013). Purified PCR products were sequenced using an ABI Prism Dye Terminator Cycle Sequencing kit (Applied Biosystems).
Nucleotide sequences were analysed using Chromas lite version 2.0
(http://www.technelysium.com.au) and aligned with reference sequences from GenBank using Clustal W (http://www.clustalw.genome.jp).
9.2.5. Salmonella antimicrobial susceptibility testing and interpretation
Each isolate was subjected to broth microdilution assays (Sensititre; Thermo
Fisher Scientific, Waltham, MA) to determine the minimum inhibitory concentrations
(MICs) of 13 antimicrobial agents: cefoxitin (CEF), azithromycin (AZI), chloramphenicol (CHL), tetracycline (TET), ceftriaxone (CTX), amoxicillin-clavulanic acid (AMC), ciprofloxacin (CIP), gentamicin (GEN), ceftiofur (CFT), trimethoprim- sulfamethoxazole (TRI), ampicillin (AMP), nalidixic acid (NAL) and streptomycin
(STR) against Salmonella. MIC results were interpreted as resistant (R), susceptible (S)
201 and intermediate, according to veterinary specific and human approved interpretative criteria as per the Clinical and Laboratory Standards Institute (CLSI) VET01S guidelines
(CLSI, 2015). When clinical breakpoints were not available in CLSI, MICs were interpreted based on epidemiological cut-off values (ECOFFs) as non-wild type (non-
WT) organisms derived from assessment of the MIC distribution using ECOFFinder
(Turnidge et al., 2006; CLSI, 2016) and/or as published by the European Committee on
Antimicrobial Susceptibility Testing (EUCAST) as presented in Table 2.3. For phenotypic analysis, if ECOFF was not present, the clinical break points were used.
Staphylococcus aureus ATCC 25923 and ATCC 29213 and Escherichia coli ATCC
25922 were used as control strains. Salmonella isolates showing clinical resistance to three or more classes of antimicrobial agents were classified as multi-drug resistant
(MDR).
9.2.6. Statistical analyses
Statistical analyses were performed using Stata/MP 14.0 (Stata Corp., College
Station, TX, USA). Point prevalence was determined by proportion of Salmonella- positive goats for each consignment. Prevalence 95% confidence intervals (CI) were calculated using Jeffrey's interval method (Brown et al., 2011). Two-tailed Chi-square tests were used to compare point prevalence between consignments.
9.3. Results
9.3.1. Prevalence of Salmonella
The overall rate of detection of Salmonella faecal carriage was 106/400 (26.5%), with faecal carriage in the four consignments ranging between 23-30% (Table 9.1). Rate of detection was not significantly different between consignments. When tested by
MALDI-TOF, all Salmonella isolates from rangeland goats returned matches to
Salmonella with values equal or greater than 2, confirming their classification.
202 9.3.2. Salmonella enterica molecular typing
Salmonella enterica serovar Typhimurium was detected in 90/106 (84.9%) isolates by amplification using serovar specific primers; STM2755 and STM4497. Of the
90 S. enterica serovar Typhimurium samples detected, a representative sample subset (32 isolates; 8 isolates per consignment) were sequenced at the STM2755 and STM4497 loci.
Sequencing indicated that S. enterica serovar Typhimurium from rangeland goats shared identical genetic similarity with S. enterica serovar Typhimurium (CP019649) previously obtained from Australian pigs (Dyall-Smith et al., 2017) (Table 9.1). The remaining
16/106 isolates were amplified and sequenced at invA and ompF loci with 11/106 (10.4%) isolates identified as S. Chester (99% homology to GenBank isolate CP019178) and 5/106
(4.7%) isolates identified as S. Saintpaul (99% homology to GenBank isolate CP017727)
(Table 9.1).
Table 9.1. Percent of rangeland goats (n=400) with Salmonella enterica detected in faeces at slaughter in Western Australia showing breakdown by origin of consignment and serovar detected.
Percent of goats with S. enterica detected in faeces (95% CI)
Serovars
Consignment All serovars S. Typhimurium S. Chester S. Saintpaul
Overall 26.5 (22.4–31.0) 22.5 (18.6–26.8) 2.8 (1.5–4.7) 1.25 (0.5–2.7)
Carnarvon (n=100) 28 (19.9–37.3) 24 (16.5–33.0) 2a (0.4–6.3) 2 (0.4–6.3)
Shark Bay (n=100) 30 (21.7–39.5) 23 (15.6–31.9) 5b (1.9–10.6) 2 (0.4–6.3)
Yalgoo (n=100) 23 (15.6–31.9) 21 (13.9–29.7) 2a (0.4–6.3) 0 (0.0–2.5)
Wooramel (n=100) 25 (17.3–34.1) 22 (14.8–30.8) 2a (0.4–6.3) 1 (0.1–4.6) ab Point prevalence (%) for different consignment (in columns) with different superscripts are significantly different (P<0.05).
203 9.3.3. Antimicrobial resistance testing
The majority of isolates (89/106; 84.0%) remained phenotypically susceptible to all 13 antimicrobials in the present study (Table 9.2). Isolates with AMR to one (3/106;
2.9%), two (10/106; 9.4%) and three (4/106; 3.7%) antimicrobials drugs were identified
(Table 9.2), with the four isolates clinically resistant to three classes (β–lactamase,
Macrolides and Tetracylines) of the antimicrobial agents classified as multi-drug resistant
(MDR). No isolates were resistant to four or more antimicrobials, and none were resistant to either ceftiofur, ceftriaxone, chloramphenicol or ciprofloxacin (Table 9.2). However, the data shown in Table 9.2 for amoxicillin-clavulanate, azithromycin and ceftriaxone, represents the percent of non-susceptible isolates due to a lack of breakpoint for wild type.
Resistance was most frequently detected to azithromycin (14.2%), followed by tetracycline (10.5%), ampicillin (5.7%), amoxicillin–clavulanate and cefoxitin (3.8%), trimethoprim/sulfamethoxazole (1.9%), gentamicin (0.9%) and streptomycin (0.9%)
(Table 9.2).
Resistance was not evenly distributed amongst the Salmonella from different consignments of goats. The Salmonella from Carnarvon region goats were susceptible to all tested antimicrobials, unlike the other regions (Table 9.2). The only resistant isolates
(16.0%; 17/106) were S. enterica Typhimurium, when typed using primers to the putative hexulose-6-phosphate synthase (STM2755) and cytoplasmic protein gene (STM4497).
204 Table 9.2. Distribution of MICs and resistance among Salmonella isolates (n=106) from faecal samples collected from rangeland goats at slaughter in Western Australia.
% % Antimicrobial concentration (μg/mL)a Antimicrobial Clinical Class Group b n Resistance agent Resistance (95% CI) 0.016 0.06 0.06 0.13 0.25 0.5 1 2 4 8 16 32 64 128 (95% CI) β–lactams–β– Amoxicillin– A 28 0.0 (0–12.3) 0.0 (0–12.3) 92.9 3.6 3.6 lactamase Clavulanate* inhibitor combinations B 30 0.0 (0–11.6) 0.0 (0–11.6) 96.7 3.3 C 23 17.4 (5– 17.4 (5–38.8) 78.3 4.3 17.4 38.8) D 25 0.0 (0–13.7) 0.0 (0–13.7) 88 4 4 4 Penicillins Ampicillin A 28 0.0 (0–13.7) 0.0 (0–12.3) 92.9 7.1 B 30 0.0 (0–11.6) 0.0 (0–11.6) 83.3 13.3 3.3 C 23 17.4 (5– 17.4 (5–38.8) 82.6 4.3 13 38.8) D 25 8.0 (1–26) 4.0 (0.1–20.4) 72 16 4 4 4 Macrolides Azithromycin^ A 28 NA 0.0 (0–12.3) 64.3 35.7 B 30 NA 10.0 (2.1– 10 43.3 36.7 10 26.5) C 23 NA 30.4 (13.2– 47.8 21.7 30.4 52.9) D 25 NA 20.0 (6.8– 32 48 20 40.7) Cephems– Cefoxitin A 28 0.0 (0–12.3) 0.0 (0–12.3) 53.6 32.1 14.3 second generation B 30 0.0 (0–11.6) 0.0 (0–11.6) 56.7 43.3 C 23 17.4 (5– 13.0 (2.8– 4.3 34.8 43.5 4.3 13 38.8) 33.6) D 25 0.0 (0–13.7) 0.0 (0–13.7) 60 36 4 Cephems– Ceftiofur A 28 0.0 (0–12.3) 0.0 (0–12.3) 14.3 78.6 7.1
205 % % Antimicrobial concentration (μg/mL)a Antimicrobial Clinical Class Group b n Resistance agent Resistance (95% CI) 0.016 0.06 0.06 0.13 0.25 0.5 1 2 4 8 16 32 64 128 (95% CI) third generation B 30 0.0 (0–11.6) 0.0 (0–11.6) 10 86.7 3.3 C 23 0.0 (0–14.8) 0.0 (0–14.8) 91.3 8.7 D 25 0.0 (0–13.7) 0.0 (0–13.7) 12 88 Ceftriaxone* A 28 0.0 (0–11.6) 0.0 (0–11.6) 92.9 7.1 B 30 0.0 (0–14.8) 0.0 (0–14.8) 100 C 23 0.0 (0–13.7) 0.0 (0–13.7) 91.3 8.7 D 25 0.0 (0–11.6) 0.0 (0–11.6) 96 4 Phenicols Chloramphenico A 28 0.0 (0–11.6) 0.0 (0–11.6) 96.4 3.6 l B 30 0.0 (0–14.8) 0.0 (0–14.8) 3.3 93.3 3.3 C 23 0.0 (0–13.7) 0.0 (0–13.7) 8.7 82.6 8.7 D 25 0.0 (0–11.6) 0.0 (0–11.6) 8 80 12 Quinolones Ciprofloxacin A 28 0.0 (0–12.3) 0.0 (0–12.3) 25 75 B 30 0.0 (0–11.6) 0.0 (0–11.6) 30 63.3 6.7 C 23 0.0 (0–14.8) 0.0 (0–14.8) 21.7 73.9 4.3 D 25 0.0 (0–13.7) 0.0 (0–13.7) 12 84 4 Aminoglycosi Gentamicin A 28 0.0 (0–11.6) 0.0 (0–12.3) 10.7 89.3 des B 30 0.0 (0–11.6) 0.0 (0–11.6) 3.3 80 13.3 3.3 C 23 3.3 (0.1– 0.0 (0–14.8) 17.4 65.2 17.4 17.2) D 25 0.0 (0–13.7) 0.0 (0–13.7) 16 64 20 Naladixic Acid # A 28 NA NA 3.6 96.4 B 30 NA NA 3.3 80 16.7 C 23 NA NA 8.7 78.3 13 D 25 NA NA 4 72 16 8 Aminoglycosi Streptomycin A 28 0.0 (0–11.6) 0.0 (0–12.3) 3.6 17.9 39.3 39.3 des B 30 0.0 (0–14.8) 0.0 (0–11.6) 10 56.7 33.3 C 23 0.0 (0–13.7) 0.0 (0–14.8) 17.4 60.9 21.7 D 25 4.0 (0.1– 0.0 (0–13.7) 8 72 16 4 20.4)
206 % % Antimicrobial concentration (μg/mL)a Antimicrobial Clinical Class Group b n Resistance agent Resistance (95% CI) 0.016 0.06 0.06 0.13 0.25 0.5 1 2 4 8 16 32 64 128 (95% CI) Tetracylines Tetracycline A 28 0.0 (0–11.6) 0.0 (0–11.6) 100 B 30 10.0 (2.1– 10.0 (2.1– 90 10 26.5) 26.5) C 23 17.4 (5.0– 17.4 (5.0– 82.6 17.4 38.8) 38.8) D 25 16.0 (4.5– 16.0 (4.5– 84 16 36.1) 36.1) Folate Trimethoprim– A 28 0.0 (0–12.3) 0.0 (0–11.6) 96.4 3.6 pathway Sulfamethoxazo inhibitors le B 30 0.0 (0–11.6) 0.0 (0–14.8) 86.7 10 3.3 C 23 4.3 (0.1– 0.0 (0–13.7) 87 8.7 4.3 21.9) D 25 4.0 (0–20.4) 4.0 (0–20.4) 88 8 4 a Solid vertical lines indicate breakpoints for resistance. The white fields indicate the dilution range tested for each antimicrobial. Values in the shaded area indicate MICs greater than the highest concentration tested. b Groups denoted by letters; A= Carnarvon, B= Shark Bay, C= Yalgoo, D= Wooramel. * Data represents the percent non-susceptible due to a lack of breakpoint for wild type. ^ Data represents the percent clinically resistant due to lack of breakpoints for both wild type and susceptible. # No data presented for this antimicrobial agent due to lack of wild, susceptible and clinical breakpoints.
207 9.4. Discussion
The current study represents the first comprehensive description of AMR from
Australian goats. High rates of detection of Salmonella faecal carriage, but markedly low rates of AMR and MDR were observed in the present study. Overall 84% of Salmonella isolates from rangeland goats were entirely susceptible to all the antimicrobials tested, and no CIA resistance (fluoroquinolones and third generation cephalosporins) was observed. The majority of the AMR observed was for goats from Yalgoo, and further characterisation of Salmonella for this region is warranted. The AMR detection rates for goats were comparable with those reported by Barlow et al. (2015) for Australian beef cattle, where resistance to tetracycline (6.6%), ampicillin (7.5%), trimethoprim/sulfamethoxazole and streptomycin was observed (Barlow et al., 2015).
The present study reported 3.8% cefoxitin-resistance in Salmonella from goats for the first time. Cefoxitin resistance in E. coli has been reported in 14.3% of Australian porcine isolates (Abraham et al., 2014).
There has been a world-wide increase in the reporting of MDR forms of
Salmonella isolates from food-producing animals to the level where it represents a risk to human health (Randall et al., 2004; Hong et al., 2016). In Africa and the Indian sub- continent, goats have been reported to contribute to Salmonella contamination in the food chain, with MDR being present including resistance against CIA’s (Molla et al., 2006;
Singh et al., 2012; Ferede, 2014; Umeh and Enwuru, 2014). In contrast, the results of the present study demonstrate low proportions of Salmonella isolates expressing AMR and
MDR in agreement with studies reported for other Australian livestock (Abraham et al.,
2014; Barlow et al., 2015). Multiple antimicrobial resistance (mainly streptomycin and tetracycline) was reported in Salmonella isolated from Australian dairy cattle (Mackie et al., 1996) although recently resistance to ceftiofur has also been detected (Sparham et al.,
208 2017). Similarly, 0.6%–1.2% of clinical Salmonella isolates from pigs showed resistance to trimethoprim, gentamicin and tetracycline (Abraham et al., 2014).
Published studies generally report high rates of isolation of Salmonella from caprine gut contents and faeces. For example, 46.3% and 45.5% of faecal and rumen samples respectively contained Salmonella, when 121 rangeland goats were sampled at two Queenslander abattoirs (Duffy et al., 2009). Rates of detection for S. enterica from goats at slaughter have also been reported in Nigeria (24.2%) and Ethiopia (3–11.5%)
(Woldemariam et al., 2005; Molla et al., 2006; Teklu and Negussie, 2011; Jajere et al.,
2015; Kuma et al., 2017). Generally high rates of Salmonella detection can be explained by the ruminant digestive tract’s sensitivity to the effects that fasting and ration change have on the presence of Salmonella (Vergara et al., 2017). Thus, factors in the present study such as geographic location of origin, which impacts on the duration of fasting and also the extent of diet change (since animals are from natural pastures), are all likely reasons why a high proportion of goats were positive for faecal carriage of Salmonella.
Agglutination-based serotyping has been the predominant technique for laboratory-based surveillance of Salmonella including typing and serovar discrimination.
However, molecular typing of Salmonella serovars, as demonstrated in this work, can address substantial limitations of the conventional approach with respect to sensitivity and demands on technician time. A further advantage of the molecular approach is that it can identify and differentiate many of those Salmonella serovars that do not express O- antigens and/or both phase 1 and 2 flagellar antigens (Herrera-León et al., 2007; Zhu et al., 2015; Bugarel et al., 2017). Moreover, molecular serotyping methods are much more accessible since they are not reliant on stocks of agglutination sera and thus are now very attractive for use in conjunction with single bacterial colony isolation for better sensitivity and outbreak investigation.
209 The three S. enterica serovars identified in the present study (Typhimurium,
Chester and Saintpaul) have all been previously reported in Australian rangeland goats
(Duffy et al., 2009). The S. enterica serovars identified in the present study have also been reported in Australian feral pigs (Bensink et al., 1991), wildlife (Parsons et al.,
2011), wild birds (Dolejska et al., 2016), and cattle (Barlow et al., 2015) indicating all these species and rangeland goats are likely elements in the ecology of S. enterica that involves multi-directional transmission. A recent study has proposed that water sources contaminated by the faeces of feral pigs could account for the occurrence of Salmonella infection in co-grazing animals in remote arid and semi-arid regions (Ward et al., 2013) although due to the broad host range of some serovars (e.g. Typhimurium), the true picture is perhaps more complex and involving multiple reservoirs. Thus, ecological studies to determine the role of invasive species in livestock and wildlife in Salmonella transmission in rangeland regions are warranted and are now possible with the aforementioned availability of molecular serotyping.
There were some limitations of the present study that should be addressed in future investigations. Future studies will ideally include whole genome sequencing (WGS) of the Salmonella isolates to determine the genotypic characteristics of Salmonella including virulence determinants, carriage of AMR genes and bacterial serotypes. Notwithstanding this, the findings from the present study demonstrate high faecal carriage of Salmonella in slaughtered rangeland goats but with encouragingly low levels of antimicrobial resistance.
9.5. Conclusion
This is the first comprehensive description of antimicrobial resistance in S. enterica in rangeland goats in Australia. The present study demonstrated that goats at slaughter had a high rate of faecal carriage for Salmonella spp., but low rates of AMR
210 and MDR detection. High rates of carriage of Salmonella spp. are associated with risk of the organism entering the food chain. Further studies are needed to elucidate practical and affordable interventions for reducing the faecal carriage of Salmonella at the time feral goats are slaughtered. The work also serves as a prelude for applying whole genome analysis to understand what relationships, if any, exist between caprine-Salmonella and those Salmonella found in other animals and humans.
211 CHAPTER 10. GENERAL DISCUSSION
The aims of this thesis were to establish whether molecular tools have utility for detection of faecal carriage with caprine enteric pathogens, and determine whether there was evidence of associations for diarrhoea, poor growth or public health risks associated with faecal carriage of eneteric pathogens by captured ranglend goats. The experimental observations suppported the general hypothesis for this thesis that molecular tools will demonstrate faecal carriage by captured rangeland goats for enteric pathogens associated with diarrhoea, reduced growth and with potential public health impacts.
The molecular techniques investigated offered some advantages over microscopy for screening goat faecal camples for faecal carriage of some of the pathogens investigated; Cryptosporidium and Giardia (Chapter 3), Eimeria (Chapter 4) and
Entamoeba (Chapter 5). The molecular tools provided a qualitiative, but not quantitative screening tool for Salmonella and Campylobacter (Chapter 6) and nematodes (Chapter
7). Through the use of a combination of molecular tools, microscopy and culture techniques, experiments outlined in this thesis demonstrated that Cryptosporidium faecal carriage was associated with reduced growth and diarrhoea for captured goats (Chapter
8), and identified public health implications associated with faecal carriage of zoonotic
Cryptosporidium, Giardia, Campylobacter and Salmonella by captured ranglend goats at a goat depot (Chapters 3-6) and at an abattoir (Chapter 9). The public health implications for antimicrobial resistance among Salmonella isolates from rangeland goats are described (Chapter 9).
10.1. Utility of molecular tools to determine pathogen faecal carriage
The experiments outlined in this thesis utilised a multiplex qPCR assay in combination with sequencing to determine faecal carriage for enteric pathogens
212 associated with diarrhoea and illthrift in goats. The key advantages of the multiplex qPCR were that it provided the potential for rapid screening for multiple enteric pathogens, and when used in combination with screening, offers high specificity for identification to species and genotype level.
The molecular tools allowed for identification of three Cryptosporidium species
(Chapter 3), one Giardia duodenalis Assemblage (Chapter 3), three Eimeria species
(Chapter 4) and a C. bovis-like Entamoeba spp. (Chapter 5) in captured rangeland goats.
Conventional methods based on morphology lack the ability to differentiate
Cryptospordium species and Giardia assemblages, and frequently lack the ability for reliable species delimitation of Eimeria and Entamoeba due to overlapping morphological characteristics. Indeed, this was true for the three Eimeria species (E. ahsata, E. crandallis and E. arloingi) and E. bovis-like Entamoeba sp. identified in this thesis. Differentiating species and genotypes has implications for investigating disease outbreaks, epidemiological studies, and identifying public health risk associated with faecal carriage of pathogens that have zoonotic potential.
These studies were the first to describe a combination of morphological and molecular characterisation for Eimeria (Chapter 4) and Entamoeba (Chapter 5) from goats. Prior to this study, there was only one 673 bp E. arloingi 18S rRNA sequence available in GenBank and the present study was the first to successfully produce a longer
(1,229 bp) 18S sequence of E. arloingi. In addition, both caprine Eimeria cytochrome c oxidase subunit I (COI) and Entamoeba bovis-like actin sequences were produced for the first time, which will facilitate future phylogenetic analysis of Eimeria and Entamoeba in ruminants and other ungulates. The phylogenetic analysis generated in the present study facilitated a better understanding of the taxonomy of both Eimeria and Entamoeba from goats.
213 Similarly, qPCR and sequencing at multiple gene loci were used to identify faecal carriage for Salmonella and Campylobacter (Chapter 6). The specific primers used identified three Salmonella enterica serovars (S. Typhimurium, S. Chester and S.
Saintpaul) and one Campylobacter species (C. jejuni) (Chapter 9). A key limitation of the project was that the qPCR was not validated against culture methods, and the minimum detection level was relatively high. Whilst the qPCR provides a rapid screening tool for identifying faecal carriage, and in combination with sequencing is highly specific for identification of Salmonella serovars, further work is required to validate the qPCR for quantification. Including selective enrichment steps will aid in increasing Salmonella concentration to levels that exceed the detection limits of the screening test. This is warranted, as qPCR offers the potential to address limitations with respect to sensitivity and labour costs of conventional serotyping (Herrera-León et al., 2007; Zhu et al., 2015;
Bugarel et al., 2017).
The multiplex qPCR for three trichostrongylid nematode genera (Haemonchus,
Trichostrongylus and Teladorsagia) did not correlate with McMaster WEC and was not validated with larval culture (Chapter 7). As such, the multiplex qPCR has limited application for diagnosis of helminthosis without further validation. Even without quantification, rapid determination of whether Haemonchus is present could be useful in informing anthelmintic treatment decisions, but McMaster WEC would still be needed to determine if infection levels meet thresholds whereby treatment would normally be recommended. There were a number of reasons why there was very poor correlation/agreement between WEC and qPCR, including that the qPCR did not include the full range of trichostrongylid nematode species that can contribute to WEC, and larval development between sample collection and DNA extraction can impact the quanity of worm DNA in samples. Other studies have reported good agreement with WEC (Siedek et al., 2006; Sweeny et al., 2001b; Sweeny et al., 2012a, b), so further work is warranted
214 to develop and validate the multiplex qPCR for goat nematodes. In the meantime, the recommendation is that whilst qPCR offers potential for rapid screening to determine if
Haemonchus is present, the screening methodology should include McMaster WEC for quantification of trichostrongylid infections, and especially for monitoring response to treatement where accurate quantitation is desirable. Estimating faecal egg count by conducting faecal egg count reduction test (FECRT) would be an important element in monitoring anthelmintic efficacy against gastrointestinal nematodes in rangeland goats
(Dobson et al., 2012; Love et al., 2017).
10.2. Associations between pathogen faecal carriage with diarrhoea and illthrift in captured rangelend goats
Faecal carriage with a range of enteric pathogens (Cryptosporidium, Giardia,
Eimeria, Entamoeba, Haemonchus, Trichostrongylus, Salmonella and Campylobacter) were demonstrated for rangeland goats in a goat depot (Chapters 3-7). Of these, only
Cryptosporidium faecal carriage was associated with reduced growth and diarrhoea, although Giardia faecal carriage and higher Eimeria oocyst shedding were also associated with looser faeces (Chapter 8). These observations were made in a single cohort of goats at a single goat depot, and therefore further studies are required to determine the extent of economic loss associated with these enteric pathogens in rangeland goats.
The magnitude of reduced weight gain observed in goats shedding
Cryptosporidium (1.48 kg per month), and specifically C. xiaoi (1.95 kg per month), was of a magnitude that has the potential to impact profitability for goat meat production.
Importantly, this level of reduced weight gain was observed in pens of typically healthy goats, and in the absence of an obvious outbreak of clinical cryotosporidiosis that would normally be associated with depression and profuse scouring.
215 Whilst faecal carriage of Cryptosporidium (all species), Cryptosporidium xiaoi,
Cryptosporidium parvum, Cryptosporidium ubiquitum, Giardia and higher shedding of
Eimeria were associated with looser faeces (increased FCS), only Cryptosporidium (all species), Cryptosporidium parvum and Cryptosporidium ubiquitum were associated with an increased risk of scouring (FCS of 3.0 or higher).
Importantly, the observations for reduced weight gain and increased scouring risk associated with Cryptosporidium were made in older goats. Most reports suggest that clinical impacts are most commonly observed in neonatal goats, and the disease has tranditionally been considered as only being an issue in the neonatal period. More recently, associations between Cryptosporidium parvum shedding and weight of sheep at weaning (12 weeks old) and the post weaning (19 weeks) period have been reported, suggesting that impacts on growth are likely to occur beyond the neonatal period for sheep
(Jacobson et al., 2016). This was consistent with the observations in the ranglenad goats in the present project that were estimated to be 9-12 months old (based on dentation) on arrival at the goat depot.
Cryptosporidium infection has been reported to affect sheep production with reduced body weight condition score (Sweeny et al., 2011a; 2012b), reduced growth rate and reduced carcass weight and dressing percentage at slaughter (Sweeny et al., 2011a,
Jacobson et al., 2016). This is the first report of Cryptosporidium association with reduced weight and diarrhoea in rangeland goats. The present study demonstrated that the clinical impacts observed in older goats were caused by enteric pathogens (mainly
Cryptosporidium), and younger goats are expected to have a higher prevalence due to their immunological immaturity, therefore economic burdens are likely to be higher for younger goats (Foreyt, 1990; Giadinis et al., 2015).
216 10.3. Public health significance of pathogen faecal carriage by captured rangeland goats
Faecal carriage with zoonotic C. parvum, C. ubiquitum (Chapter 3), S.
Typhimurium and C. jejuni (Chapter 6) were reported for rangeland goats at the depot.
This prompted an additional study into faecal carriage prevalence and occurrence of antimicrobial resistance for goats at an abattoir, which identified three Salmonella serovars (Salmonella Typhimurium, Salmonella Chester and Salmonella Saintpaul) and confirmed high rates of Salmonella faecal carriage, but low rates of AMR (Chapter 9).
High carriage of Salmonella by goats following capture and transport to a goat depot
(Chapter 6) or abattoir (Chapter 9) indicate downstream concerns for carcass contamination and food safety.
The antimicrobial susceptibility testing (Chapter 9) represents the first published description of antimicrobial resistance of S. enterica from Australian rangeland goats. A key observation was that captured rangeland goats transported to a goat depot or abattoir had a high carriage of Salmonella spp., but low rates of antimicrobial resistance. Most
(84.0%) of the Salmonella isolates from slaughtered rangeland goats were susceptible to all tested antimicrobials. A low proportion (3.7%) of isolates were classified as multi- drug resistant (resistant to 3 classes of antimicrobials) but no isolates were resistant to critically important antimicrobials such as fluoroquinolones and extended spectrum cephalosporins. The low proportions of Salmonella isolates from rangeland goats expressing AMR and MDR was in agreement with studies reported for other Australian livestock (Abraham et al., 2014; Barlow et al., 2015). Antimicrobial resistance to multiple antibiotics (mainly streptomycin and tetracycline) was reported in Salmonella isolated from Australian dairy cattle (Mackie et al., 1996). However, in another study, high levels of AMR that were not critically or highly important to human medicine status of
Enterococcus were reported in Australian cattle production systems (Barlow et al., 2017).
217 The finding of AMR in the present study, was noteworthy as the goats were managed in such a way that they were unlikely to have ever been exposed to antibiotic treatments.
There was variation in AMR between consignments sourced from different regions, suggesting the need for further inestigation of AMR in rangeland goats from different geographical locations.
Faecal carriage with zoonotic Cryptosporidium and Giardia that may contaminate water sources indicates public health implications for management of wastewater at goat depots and abattoirs. Goat depots and livestock truck washdown facilities should be designed in such a manner to reduce faecal contamination of waterways. Whilst faecal carriage for Crypotosporidium and Giardia were highest at the first sample collection
(immediately after arrival at the goat depot), C. parvum was only identified at the sample collection approximately 3 months after arrival at the depot suggesting that a shift towards shedding of zoonotic genotypes may occur even in goats that are habituated to the goat depot environment. Although several studies reported cryptosporidiosis resulting from contact with goats after consumption of their products (Appendix 1), there is only one
Australian study that reported cryptosporidiosis due to consumption of unpasteurised goats milk (Australian Food Industries Science Centre, 1998). This warrants further investigation to determine the public health risk significance of pathogen (mainly
Cryptosporidium) faecal carriage by captured rangeland goats.
The present study has addressed the lack of understanding about the public health significance of protozoan parasites by identifying zoonotic Cryptosporidium genotypes and Giardia assemblage E in captured rangeland goats in confined feeding facilities. It also contributed information about zoonotic S. enterica serovar Typhimurium and C. jejuni faecal carriage by the goats using molecular tools. The present study highlighted the possibility that rangeland goats can serve as carriers of zoonotic enteric pathogens
218 via contamination of carcases and water sources from gastrointestinal contents at slaughter.
10.4. Implications of observations for the goat meat industry
Faecal carriage for enteric pathogens was demonstrated for ranglend goats in a
goat depot (Chapters 3-7) and at an abattoir (Chapter 9).
Faecal carriage detection rates were generally highest when sampled immediately
after goats had been captured and transported to the goat depot.
The exception was Eimeria where prevalence and faecal carriage intensity was
highest one month after arrival at the depot. This was consistent with previous
studies that showed a period of stress associated with transport, mixing of animals
and confinements of undomesticated rangeland goats are likely to exacerbate
faecal carriage (Main and Creeper, 1998; Cavalcante et al., 2012).
This has implications for managing goats in depots or at abattoir lairage, where
high rates of faecal carriage may result in environmental contamination. In the
case of goat depots, this has potential to increase disease transmission and
contribute to disease outbreaks.
For goats consigned directly to slaughter, high rates of pathogen faecal carriage
has implications for abattoir hygiene with the potential to contaminate caracasses
and effluent (waste water) with pathogens that have zoonotic potential.
Further investigation into the risk factors for faecal carriage and management
factors that may reduce faecal carriage for rangeland goats consigned to goat
depots or slaughter are warranted. In general, faecal carriage declined to low
levels at the sampling occasions ocuuring two and three months after arrival at the
depot.
219 Future studies examining pathogens in rangeland goats should include sampling
of goats in the period soon after capture when faecal carriage is most likely to be
detected, and it should be noted that screening samples collected after goats have
habituated to the goat depot environment may underestimate the range of
pathogens present in that population. Utilising molecular tools for screening goat
faecal samples for pathogens revealed that mixed infections were common,
especially in samples collected on arrival at the goat depot when rates of faecal
carriage were highest. This suggests that future studies should consider
monitoring goats for a range of pathogens to determine the impact of co-infections
on goat health and production.
This was the first report of reduced growth and diarrhoea associated with
Cryptosporidium in Australian goats beyond the neonatal period, and
cryptosporidiosis should be considered a differential diagnosis for scouring and
illthrift in goats beyond weaning. Goats at the depot were treated with an
anthelmintic (moxidectin) and anticoccidial drug (toltrazuril) immediately after
the first and second sample collection. This was part of the standard husbandry
procedure at the goat depot with the intent of reducing the impact of nematodes
and coccidiosis. This is an off-label use of both treatments for goats in Australia.
The McMaster WEC suggested that treatment failure occurred, but it was not
possible to determine if this was due to underdosing, anthelmintic resistance or
reinfection, particularly as goats are considered to be metabolically different from
sheep (Lyndal-Murphy et al., 2007). The recommendation based on this is that
moxidectin, and anthelmintics in general, should only be used at goat depots
where there is a clear indication (based on WEC) and where WEC monitoring can
be used to determine treatment efficacy.
220 As previously suggested, the use of non-chemical alternative management
methods including grazing rotations, nutritional supplements and bioactive
tanniferous forages should be considered by the Australian goat industry (Lyndal-
Murphy et al., 2007). It was not clear if toltrazuril treatment was effective in
reducing Eimeria shedding to a level where it was reducing coccidiosis in the
goats at the depot. A rise in Eimeria prevalence and shedding intensity was
observed at the second sample collection, approximtaley one month after the first
toltrazuril treatment. Eimeria shedding intensity declined at the last two sample
occasions (one and two months after the second toltrazuril treatment).
Coccidiosis is generally a self-limiting infection, and the fall in prevalence and
shedding intensity of Eimeria observed at the last two sampling occasions was
more likely attributable to goats acquiring immunity following exposure to
infection, than to any effect of treatment. Other studies have noted variable
responses to treatment (Chartier et al., 1992; Iqbal et al., 2013).
Further investigation into whether toltrazuril is effective in reducing Eimeria
shedding, the duration of response to treatment, and whether treatment is effective
in reducing clinical coccidiosis is warranted before recommendations can be made
with respect to the use of toltrazuril in captured rangeland goats at goat depots.The
associations between selected enteric pathogens (Cryptosporidium, Giardia,
Eimeria, Entamoeba, Salmonella, Campylobacter, Haemonchus and
Trichostrongylus) identified in captured rangeland goats upon their arrival to a
commercial depot (feedlot) with production parameters (live weight, growth rate
and body condition score (BCS) highlighted in this thesis (Chapter 8).
Cryptosporidium, and specifically C. xiaoi, was the only pathogen associated
with lower growth of captured rangeland goats. Cryptosporidium infected
221 animals in the current study gained less weight (1.48 kg) over S1 and S2 compared
to non-infected goats.
There were no significant growth associations identified with other C. parvum and
C. ubiquitum species.
It is very important to investigate the carriage of this protozoal pathogen in
rangeland goats at a larger scale to determine the actual impact on their
productivity. Therefore, determining hot standard carcase weight (HSCW) in
rangeland goats as an indicator of productivity is warranted.
Except for Cryptosporidium, no association with weight gain was reported with
other selected and identified enteric pathogens. In term of scouring, Giardia and
Cryptosporidium faecal carriage, and higher Eimeria oocysts counts (on arrival)
were associated with looser faecal consistency.
Cryptosporidium and Giardia infection in rangeland goats were associated with
higher faecal consistency score (FCS) (more loose faeces) (0.92 and 0.4
respectively) and an increased risk of goats producing non-pelleted faeces.
The present study also demonstrated that goats shedding Cryptosporidium were 5
times more likely to be scouring than goats shedding no Cryptosporidium.
Furthermore, goats shedding C. parvum and C. ubiquitum are 10 and 16 times
respectively more likely to be scouring than goats shedding no Cryptosporidium.
This is a very interesting outcome, as it may increase the risk of carcass
contamination in these goats especially with zoonotic and emerging zoonotic
Cryptosporidium species (C. parvum and C. ubiquitum) (Chapter 3).
Except for the above mentioned protozoal pathogens, no association with scouring
was reported with other selected and identified enteric pathogens.Although, two
222 anti-coccidial treatments given immediately after the first (S1) and second (S2)
sampling, the present study demonstrated weak but significant negative
correlations over the entire sampling period were identified between Eimeria OPG
and liveweight, and for both worm egg counts (WEC) and Eimeria OPG with
body condition score (BCS).
Further investigation is warranted to elucidate the contribution of Eimeria oocyst
output to environmental contamination in the feedlot.
10.5. Future directions
Many questions remain, which require scientific work beyond the framework of this thesis and research opportunities which have arisen due to the accomplished work.
Some of the questions originating from this research include the following:
(1) Assessment of public health risks associated with rangeland goats’
production at the state and probably at the national level?
This would seem a natural precursor to larger studies to evaluate the public health risk associated with current goat production and processing practices, however this will involve extenive funding and additional supporting resources to conduct the assessment.
(2) What is the full range of pathogens in Australian rangeland goats?
Further studies into the epidemiology of both internal and external pathogen species/genotypes, on a broader scale, are required. The present study provided insights into selected gastrointestinal protozoa (Eimeria, Cryptosporidium and Giardia),
Entamoeba, bacteria (Salmonella and Campylobacter) and nematodes (Haemonchus,
Trichostrongylus and Teladorsagia) after rangeland goats have been captured, transported and relocated into commercial goat depot. However, the investigations were performed on goats from a single geographical location, and did not capture variation that
223 may occur across seasons. The qPCR was not validated with nematode larval cultures, and requires refinement for qualitative and quantitative disgnosis of nematode infections.
More information about other enteric pathogens that may be present in Australian rangeland goats is needed including Escherichia coli, Clostridium perfringins, Yersinia spp., pestivirus and rotavirus, as well as those that can cause ill-thrift such as Pasteurella spp., Fasciola hepatica and lentivirus. Infectious causes of abortion such as Chlamydia pecorum, C. psittaci, Toxoplasma gondii, Brucella and Coxiella also have potential to impact profiatability of goat enterprises.
To this end, the high throughput capacity and the superior depth of coverage offered by high throughput amplicon-based Next Generation Sequencing (NGS) will facilitate the large scale molecular epidemiological analyses that are required to better understand the full diversity of pathogens, the extent of mixed infections and the transmission dynamics of pathogens in rangeland goats.
Specifically, a large scale longitudinal research study utilising NGS is required to:
(i) collect data on the epidemiology of a wide range of pathogens in different
geographical areas and feedlots at different time points, in both warm and cool
seasons and at different ecological zones, age groups, sex, and management
systems to determine the distribution of different species/genotypes/ serovars
of internal pathogens (parasites and bacteria) across different geographical
areas, and;
(ii) to determine the full clinical and economic impacts caused by these pathogens.
(iii) to determine the specific factors that contributed to the rise in prevelences and
shedding intensity of enteric pathogens following the capture of rangeland
goats.
224 (3) What are the dynamics of faecal carriage, sources of infection and risk factors for pathogen faecal carriage by captured rangeland goats?
A key limitation of these experiments was the inability to determine the dynamics of faecal carriage between the first sample collection and second sample collection one month later, so it was not clear whether faecal carriage prevalence and intensity increased after arrival before declining to the level observed at the second sampling occasion. More frequent monitoring in subsequent studies could determine the recommended interval for sampling for epidemiological studies and routine screening of goats at depots.
As this was beyond the scope of the current study, faecal carriage of enteric pathogens in wild rangeland goats prior to capture, during trapping (between capture and transport), and at slaughter were not determined. Therefore, future studies should include faecal sample collection for animals in trap yards (soon after capture) to determine how time from capture impacts faecal carriage. Future studies will also need to validate observations using goats of different ages, goats sourced from a wider geographical area and across different seasons. Further research is also required to confirm the effect of management factors factors including duration of trapping, diet and stocking density during both trapping and transportation of rangeland goats on the faecal carriage of pathogens. Blood analyses for hormones such as cortisol could be used to quantify the degree of stress associated with capture and transport, and determine how this impacts pathogen faecal carriage. However, hormone fluctuation during the day should be considered and levels may underestimate the actual degree of stress related to transport as it often involves significant stress at time of sampling (Atkinson, 2000).
The sources of infection for the pathogens in the present study were not determined. Three Salmonella enterica serovars were identified from rangeland goats, specifically S. Typhimurium (Chapters 6 and 9), S. Chester (Chapter 9) and S. Saintpaul
(Chapter 9). These serovars have been already reported in Australian feral pigs (Bensink
225 et al., 1991), wildlife (Parsons et al, 2011) and wild birds (Dolejska et al., 2016), indicating a possible potential epidemiological role of these hosts in contaminating water sources and disseminating S. enterica to rangeland goats.
Understanding the sources of infection and risk factors for faecal carriage will inform recommendations for management practices that can be implemented to reduce transmission, contamination of the environment and expression of clinical disease by goats. Better understanding of the risk factors of Salmonella carriage in rangeland goats at slaughter using both faecal samples and carcass monitoring will inform potential control measures to manage Salmonella contamination in the slaughter chain, starting from capture of rangeland goats, through to transport, lairage, the evisceration process, chilling, cutting and boning.
(4) What is the relationship between nutrition and pathogens in rangeland goats?
In goats experimentally infected with gastrointestinal nematodes, improved nutrition by combining protein and energy has been demonstrated to increase the density of intestinal eosinophils associated with reduced worm establishment, and improved mast cells and globule leucocytes function contributing to reduced egg excretion (Torres-
Acosta et al., 2004; Torres-Acosta et al., 2006). The ruminant digestive tract appears to be particularly sensitive to the effects that fasting and ration change have on the presence of Salmonella (Vergara et al., 2017). The impact of dietary supplementation, fasting and ration change on pathogen faecal carriage and expression of disease by rangeland goats are not described. This broad nutrition-infection topic in rangeland goats should be considered in future research.
(5) What is the pathogenicity of different Eimeria species in rangeland goats?
As one of the Eimeria species identified in the present study; E. arloingi is considered one of the most pathogenic species in goats, further investigation into
226 histopathological changes and impacts on growth and faecal consistency associated with faecal carriage caused by specific Eimeria species are warranted.
(6) What are the risk factors for antimicrobial resistant Salmonella in slaughtered rangeland goats, and what is the practical application of whole genome sequencing
(WGS) for typing resistance in Salmonella?
High levels of Salmonella faecal carriage but low levels of AMR were reported for slaughtered rangeland goats (Chapter 9). The rate of AMR observed, whilst low, was notable in that goats had not been exposed to antimicrobial treatments. Further investigations are warranted to determine the levels of AMR for goats across wider geaographical area, and across seasons.
Affordable WGS technologies are quickly becoming a routine part of laboratory medicine, promising a single workflow to supplant several traditional procedures that require specialized training and reagents (Didelot et al., 2012). Compared to conventional antimicrobial tests, WGS offers more comprehensive information on the genotypic characteristics of Salmonella including identification of antimicrobial analysis, virulence determinants, and serotypes. This includes the full complement of resistance determinants, including resistance to compounds not routinely tested phenotypically. For example, a recent study used WGS to detect antimicrobial resistance genes in S. enterica serovars isolated from dairy cattle and humans in the US and showed that WGS can be used to reliably predict phenotypic resistance across Salmonella isolated from bovine sources (Carroll et al., 2017). WGS needs to be applied to Salmonella isolates from rangeland goats to provide definitive genotype information, identify the full complement of resistance determinants present and determine its practicality and cost-effectiveness.
227 10.6. Conclusions
The results generated in this study validated the general hypothesis that molecular tools would demonstrate faecal carriage of enteric pathogens associated with diarrhoea and reduced growth in captured rangeland goats, and with zoonotic potential. The results have been shared with Meat and Livestock Australia, who can disseminate the information to goat meat producers and processors. Extension programmes should focus on addressing known risk factors for gastrointestinal parasites and bacteria in the management of rangeland goats following capture. Meat and Livestock Australia could assist producers and processors through improved understanding of appropriate control measures for diseases to prevent disease transmission and the impacts of health and productivity for goats. This research has provided new information on the public health risks associated with faecal carriage of bacteria and parasites by rangeland goats following capture and at slaughter.
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287 CHAPTER 12. APPENDICES
The following appendices include journal articles published by the candidate over the course of the candidature. They are submitted as additional evidence for candidature for the degree of Doctor of Philosophy.
Appendix 1. Prevalence of Cryptosporidium species and glycoprotein 60 (gp60) subtypes in goats and any associated outbreaks.
Appendix 2. Prevalence of G. duodenalis assemblages in goats.
Appendix 3. Graphical representation of the Power Soil DNA Isolation Kit methodology described in Chapter 2.
Appendix 4. The 18S rDNA sequences utilised in Eimeria phylogenetic analyses described in Chapter 4.
Appendix 5. The cytochrome c oxidase subunit I (COI) sequences utilised in
Eimeria phylogenetic analyses described in Chapter 4.
288 Appendix 6. The 18S rDNA sequences utilised in Entamoeba phylogenetic analyses described in Chapter 5.
Appendix 7. The actin sequences utilised in Entamoeba phylogenetic analyses described in Chapter 5.
Appendix 8. Al-Habsi, K., Yang, R., Williams, A., Miller, D., Ryan, U.,
Jacobson, C., 2017. Zoonotic Cryptosporidium and Giardia shedding by captured rangeland goats. Veterinary Parasitology: Regional Studies and Reports. 7, 32–35.
Appendix 9. Al-Habsi, K., Yang, R., Ryan, U., Miller, D., Jacobson, C., 2017.
Morphological and molecular characterization of three Eimeria species from captured rangeland goats in Western Australia. Veterinary Parasitology: Regional Studies and
Reports. 7, 32–35.
Appendix 10. Al-Habsi K., Yang, R., Ryan, U., Jacobson, C., Miller, D.W., 2017.
Morphological and molecular characterization of an uninucleated cyst-producing
Entamoeba spp. in captured Rangeland goats in Western Australia. Veterinary
Parasitology. 235, 41–46.
Appendix 11. Al-Habsi, K., Yang, R., Abraham, S., Miller, D., Ryan, U.,
Jacobson, C., 2017. Molecular characterisation of Salmonella enterica serovar
Typhimurium and Campylobacter jejuni faecal carriage by captured rangeland goats.
Small Ruminant Research. Accepted for puplication: 23-Nov.-2017.
289 APPENDIX 1. Prevalence of Cryptosporidium species and glycoprotein 60 (gp60) subtypes in goats and any associated outbreaks.
Country Goat Type/Breed Goat Age Diagnostic method Prevalence*, Reported outbreaks, References used Cryptosporidium/ Species species and gp60 subtypes (n) Algeria N/A N/A PCR N/A, C. xiaoi N/A Li et al. (2014) N/A gp60 subtype XIIa (n=1) Australia N/A 2 weeks microscopy/ electron N/A 1 goat kid died of Mason et al. (1981) Angora microscopy N/A Cryptosporidium Australia N/A N/A PCR N/A 2 human cases Australian Food N/A N/A with C. parvum due Industries Science to consumption of Centre (1998) unpasteurised goats milk Australia N/A 1-2 weeks PCR N/A 1 goat kid with Morgan et al. (1998) C. parvum Bangladesh N/A kids (1–6 microscopy/ PCR 15%- microscopy N/A Siddiki et al. (2015) N/A months) 3%- PCR C. xiaoi (n=3) Belgium N/A kids microscopy/ PCR N/A 9.5% Geurden et al. (2008b) N/A C. parvum; subtypes IIaA15G2R1 (n=3) and IIdA22G1 (n=8) Botswana N/A kids ≤ 3–6 ELISA N/A 10.5% Sharma and Busang N/A months C. parvum (n=15) (2013) Botswana N/A ≤ 4weeks– microscopy/ N/A 12.2% Sharma and Busang N/A adults ELISA NA (2015) Brazil N/A 15 days–8 microscopy N/A 4.8% Bomfim et al. (2005) Saanen/ years NA Mixed (Saanen/Swiss) brown
290 Country Goat Type/Breed Goat Age Diagnostic method Prevalence*, Reported outbreaks, References used Cryptosporidium/ Species species and gp60 subtypes (n) Brazil dairy 1–2 week microscopy 22 goat kids infected N/A Vieira et al. (1997) N/A N/A China N/A kids/ PCR N/A 11.4% Mi et al. (2014) N/A adults C. xiaoi (n=10) C. parvum (n=14); subtype IIdA19G1 (n=8), IIaA14G2R1(n=1), IIaA15G1R1 (n=1), IIaA15G2R1 (n=1), IIaA17G2R1 (n=1), unknown (n=2) C. ubiquitum (n=10); subtype XIIa China N/A kids/ PCR N/A 3.5% Wang et al. (2014) N/A adults C. andersoni (n=16) C. ubiquitum (n=24) C. xiaoi (n=4) China Cashmere/ pre- PCR 16.5% C. parvum (n=8) N/A Peng et al. (2016) Saanen/ weaned/ C. xiaoi (n=94) Boar adults C. ubiquitum (n=2) China N/A N/A IFT/ PCR C.bovis like (n=1) N/A Karan et al., (2007) Chile N/A kids microscopy N/A 10.5% Gorman et al. (1990) N/A ˂1 month NA Cyprus N/A 4–15 days microscopy N/A 89.3% Giadinis et al. (2012) Damascus N/A Czech Republic N/A kids PCR N/A N/A Cacciò et al. (2000) N/A C. parvum (n=1) Czech Republic N/A N/A microscopy/PCR N/A N/A Hajdusek et al. (2004)
291 Country Goat Type/Breed Goat Age Diagnostic method Prevalence*, Reported outbreaks, References used Cryptosporidium/ Species species and gp60 subtypes (n) N/A C. parvum (n=1) Egypt N/A N/A microscopy N/A 13.5% El-Sherbini and N/A N/A Mohammed (2006) Egypt N/A N/A microscopy N/A 25.9% Shoukry et al., 2009 N/A NA Ethiopia N/A adults microscopy N/A 44.3 Ayana et al. (2009) N/A N/A Ethiopia N/A 5 days–6 microscopy N/A 11.5% Ayana and Alemu N/A months N/A (2015) France N/A 5–30 days microscopy N/A 16.2% Delafosse et al. (2006) Saanen and Alpine N/A
France N/A N/A PCR N/A N/A Ngouanesavanh et al. N/A C. parvum (n=7) (2006) France N/A pre- IFT /PCR N/A 68%–93% Rieux et al. (2013) N/A weaned C. xiaoi (n=18) kids C. parvum (n=1) France N/A 1–5 years IFAT/ PCR N/A 88.9% Paraud et al. (2014) Saanen C. ubiquitum (n=16)
Greece N/A kids (4–9 microscopy/ PCR N/A 7.1% Tzanidakis et al. (2014) N/A weeks) C. parvum; subtypes IIdA4G2T14 (n=1) and IIdA4G3T13(n=1) C. ubiquitum (n=5) C. xiaoi (n=7) Greece local dairy kids (4–15 microscopy N/A 76.4% Giadinis et al. (2015) crossbreeds days) N/A
292 Country Goat Type/Breed Goat Age Diagnostic method Prevalence*, Reported outbreaks, References used Cryptosporidium/ Species species and gp60 subtypes (n) Hungary N/A kids microscopy N/A 25% Nagy et al. (1984) N/A N/A India N/A N/A PCR N/A N/A Rajendran et al. (2011) N/A C. xiaoi (n=1) C. parvum; subtype IIdA15G1 (n=1) India N/A N/A IMS/ DFA N/A 20% Daniels et al. (2015) N/A N/A India N/A kids PCR N/A 3.5% Maurya et al. (2013) N/A C. parvum (n=4) Iran N/A 1–6 microscopy N/A 18.9% Khezri and Khezri N/A months N/A (2013) Iran N/A kids/adults microscopy N/A 6.2% Shafieyan et al. (2015) N/A N/A Iraq N/A N/A microscopy N/A 17.7% Mahdi and Ali (2002) N/A N/A Israel N/A kid PCR N/A N/A Tanriverdi et al. (2006) N/A C. parvum (n=1) Italy N/A kids electron microscopy NA 19% Rossanigo et al. (1987) N/A N/A Italy N/A kids PCR N/A N/A Cacciò et al. (2000) N/A C. parvum (n=14) Italy N/A N/A PCR N/A N/A Drumo et al. (2012) N/A C. parvum (n=21) Malawi N/A N/A microscopy N/A 10.2% Banda et al. (2009) N/A N/A Malaysia N/A N/A Microscopy 43.3% N/A Yusof et al. (2017) N/A PCR C. parvum N/A
293 Country Goat Type/Breed Goat Age Diagnostic method Prevalence*, Reported outbreaks, References used Cryptosporidium/ Species species and gp60 subtypes (n) Mexico N/A up to 3 microscopy N/A 72.5% Romero-Salas et al. N/A months N/A (2016) Netherland N/A kids PCR N/A N/A Cacciò et al. (2000) N/A C. parvum (n=6) Nigeria N/A kids/ microscopy N/A 24% Pam et al. (2013) N/A adults N/A Nigeria N/A kids/ ELISA N/A 37.5% Akinkuotu et al. (2015) N/A adults C. parvum (n=81) Norway N/A N/A PCR 40 cases of school children N/A Lange et al. (2014) N/A with C. parvum (subtype N/A IIa A19G1R1) associated with contact with lambs/goat kids Oman N/A neonatal/ microscopy/ electron 283 goats died N/A Johnson et al. (1999) N/A adults microscopy N/A Papua New N/A adults PCR N/A 4.4% Koinari et al. (2014) Guinea N/A C. hominis; subtype IdA15G1 (n=6) C. parvum; subtypes IIaA15G2R1 (n=1) and IIaA19G4R1 (n=1) C. xiao (n=1) Rat genotype II (n=1) Poland Meat crossbreeds 1 day– 9 PCR N/A C. parvum N/A Kaupke et al. (2017) Saanen weeks PCR 48% C. xiaoi Alpine PCR 61.1% C. xiaoi Polish White PCR 50% C. xiaoi Improved PCR 15% C. xiaoi
294 Country Goat Type/Breed Goat Age Diagnostic method Prevalence*, Reported outbreaks, References used Cryptosporidium/ Species species and gp60 subtypes (n) Polish Color PCR Improved 87.5% C. xiaoi Anglo-Nubian Republic of Korea N/A N/A PCR N/A 42.9% Park et al. (2006) N/A C. hominis (n=3) Romania N/A 1 day–6 microscopy N/A 24% Bejan et al. (2009) N/A weeks N/A Spain N/A N/A microscopy N/A 11% Matos-Fernandez et al. N/A N/A (1993) Spain N/A N/A microscopy N/A 42% Munoz-Fernandez et al. N/A N/A (1996) Spain N/A kids/ IFAT N/A 0–50% Castro-Hermida et al., N/A adults C. parvum (n=13) 2005 Spain N/A <1 month– microscopy N/A 9% Castro-Hermida et al. N/A adults N/A (2007) Spain N/A ˂21 days PCR N/A N/A Quílez et al. (2008) N/A C. parvum; subtype IId (n=17) Spain N/A N/A microscopy N/A 19.1% Sanz Ceballos et al. N/A N/A (2009) Spain N/A ˂21 days PCR N/A N/A Díaz et al. (2010) Murciano-Granadina C. xiaoi (n=2) Spain N/A kids/ microscopy/ PCR N/A 62.7 %–microscopy Díaz et al. (2015) N/A adults C. parvum; subtypes IIaA13G1R1 (n=5), IIaA14G2R1 (n=1), IIaA15G2R1 (n=38), IIaA16G3R1 (n=11) and IIdA17G1 (n=3) C. xiaoi (n=5)
295 Country Goat Type/Breed Goat Age Diagnostic method Prevalence*, Reported outbreaks, References used Cryptosporidium/ Species species and gp60 subtypes (n) Sri Lanka N/A <6 microscopy N/A 21.7%–33.6% Noordeen et al. (2000) N/A months– N/A >12 months Sri Lanka N/A 4 days microscopy/ PCR N/A N/A Noordeen et al. (2002) N/A C. parvum (n=1) Switzerland N/A kids/ microscopy N/A 3.5% Marreros et al. (2012) Alpine ibex adults NA Taiwan N/A kids/ microscopy/ IFA N/A 35.8% Watanabe et al., (2005) N/A adults N/A Tanzania N/A N/A PCR N/A 8.9% Parsons et al. (2015) N/A C. xiaoi (n=5) Trinidad N/A ˂3 months microscopy N/A 20% Kaminjolo et al. (1993) and Tobago N/A N/A Turkey N/A 5-15 days microscopy/ ELISA 70 goat kids died N/A Sevinç et al. (2005) N/A C. parvum (n=133) Turkey N/A N/A microscopy/ ELISA N/A 10.71% Ciçek et al. (2008) N/A N/A United Kingdom N/A N/A PCR N/A N/A Giles et al. (2009) Pygmy C. hominis (n=1) United Kingdom N/A N/A microscopy N/A 20% Smith et al. (2010) N/A N/A United States N/A N/A PCR N/A N/A Fayer et al. (2010) Boer C. ubiquitum (n=4) United States dairy N/A IFAT/ PCR 6 human cases with N/A Rosenthal et al. (2014) N/A Cryptosporidium C. parvum; consumed or in contact subtype IIaA16G3R1 (n=6) with goat’s milk Zambia N/A <3 months ELISA N/A 4.8% Goma et al. (2007)
296 Country Goat Type/Breed Goat Age Diagnostic method Prevalence*, Reported outbreaks, References used Cryptosporidium/ Species species and gp60 subtypes (n) N/A C. parvum (n=1) Zambia N/A N/A IFAT N/A 5.9% Siwila et al. (2013) N/A N/A *Prevelance (%) reported have been rounded to the nearest decimal percentage point.
297 APPENDIX 2. Prevalence of G. duodenalis assemblages in goats.
Country Goat Type/Breed Goat Age Diagnostic method Prevalence* Giardia/ Assemblage (n) Reference
Australia N/A N/A PCR N/A Ng et al. (2011) N/A Assemblage C (n=1) Bangladesh N/A kids (1–6 months) PCR 3% Hossain et al. (2014) Black Assemblage E (n=3) Bengal/Jamunapari Belgium N/A kids microscopy/ PCR 35.8% Geurden et al. (2008b) N/A Assemblages E (n=22) and A (n=6) at tpi and Assemblages E (n= 12), A (n=6) and E+A (n=5) at β-giardin Brazil N/A 15 days–8 years microscopy 14.3% Bomfim et al. (2005) Saanen/ N/A Mixed (Saanen/Swiss) brown Brazil dairy kids/ microscopy 22.4% Sudré et al. (2012) N/A adults N/A Brazil N/A mainly adults microscopy 22.6% Radavelli et al. (2014) N/A
298 Country Goat Type/Breed Goat Age Diagnostic method Prevalence* Giardia/ Assemblage (n) Reference
Brazil N/A adults microscopy/ PCR 29.3% Sudré et al. (2014) Saanen Assemblage E (n=8) at β-giardin and Assemblage E (n=4) at tpi China N/A 1 month–4 years PCR 2.9% Zhang et al. (2012) N/A Assemblages E (n=23), A (n=4) and B (n=2) China N/A N/A microscopy/ PCR 6.3% Gu et al. (2014) NA Assemblage E (n=23) at tpi and assemblage E (n=16) at gdh China Cashmere/ Saanen/ preweaned/ PCR 12.7% Peng et al. (2016) Boar adults Assemblage A(n=4) Assemblage E (n=76) Côte dÍvoire N/A N/A PCR N/A Berrilli et al. (2012) N/A Assemblages A+B (n=1) Greece N/A kids (4–9 weeks) microscopy/ PCR 40.40% Tzanidakis et al. (2014) N/A Assemblages E (n=28), A (n=1) at β- giardin, Assemblages E (28), A (n=1) and A+E (n=3) at tpi India N/A N/A IMS/ DFA 15% Daniels et al. (2015)
299 Country Goat Type/Breed Goat Age Diagnostic method Prevalence* Giardia/ Assemblage (n) Reference
N/A N/A
Iran N/A <12 month PCR 15.90% Jafari et al. (2014) N/A Assemblage E (n=15) Malaysia N/A 3 months– 7 years PCR 6.80% Lim et al. (2013) Jamnapuri Assemblages A (n=3), B (n=1) and E (n=12) Netherlands N/A N/A PCR Assemblage E (n=1) van der Giessen et al. (2006) Spain N/A kids/ adults IFAT 0–30% Castro-Hermida et al. N/A N/A (2005) Spain N/A <1 month–adults microscopy 33% Castro-Hermida et al. N/A N/A (2007) Spain N/A 2–6 months PCR 42.20% Ruiz et al. (2008) Majorera Assemblage E (n=17) Tanzania N/A N/A PCR 22% Di Cristanziano et al. N/A Assemblages E (n=6), A (n=1) and B (2014) (n=2) Uganda N/A N/A PCR 12.3% Assemblages E (n=2) at gdh, Johnston et al. (2010) Assemblages E (n=3) at tpi United Kingdom N/A N/A PCR N/A Minetti et al. (2014) N/A Assemblage C (n=1)
300 Country Goat Type/Breed Goat Age Diagnostic method Prevalence* Giardia/ Assemblage (n) Reference
Zambia N/A N/A IFAT 5.90% Siwila et al. (2013) N/A N/A *Prevelance (%) reported have been rounded to the nearest decimal percentage point.
301 APPENDIX 3. DNA isolation from faecal samples.
Figure 12.1. Graphical representation of the Power Soil DNA Isolation Kit methodology. (Available: https://openwetware.org/wiki/BISC209/F13:_Lab5, Last Accessed 4 October 2017).
302 APPENDIX 4. The 18S rDNA sequences utilised in Eimeria phylogenetic analyses.
18S rDNA sequences GenBank Accession No. E. adenoeides KC305182 E. adenoeides KC305185 E. meleagridis HG793040 E. sp. meleagris gallopavo HM117011 E. tenella EU025113 E. pavonina JN596589 E. acervulina U67115 E. sp. alectoris graeca HM070378 E. sp. ex numida meleagris KJ547707 E. sp. ex phasianus colchicus KJ547706 E. dispersa HG793041 E. purpureicephali KU140597 E. innocua HG793045 E. sp. ex apodemus agrarius JQ993655 E. myoxi JF304148 E. brasiliensis KU351728 E. alabamensis AB769556 E. bukidnonensis AB769601 E. bukidnonensis AB769599 E. bukidnonensis AB769595 E. auburnensis AB769571 E. pellita KU351731 E. wyomingensis AB769654 E. canadensis AB769610 E. cylindrica AB769616 E. faurei AF345998 E. hirci rangeland goats KX845685 E. crandallis AF336339 E. weybridgensis AY028972 E. christenseni rangeland goats KX845684 E. ahsata AF338350
303 18S rDNA sequences GenBank Accession No. E. arloingi rangeland goats KX845686 E. zuernii KT184356 E. zuernii KU351737 E. illinoisensis KU351730 E. bovis KT184336 E. ovinoidalis AF345997 E. ellipsoidalis AB769634 E. arloingi KC507792 Toxoplasma gondii L24381
304 APPENDIX 5. The cytochrome c oxidase subunit I (COI) sequences utilised in Eimeria phylogenetic analyses.
COI sequences Genbank Accession No. E. falciformis HM771682 E. sp. ex apodemus agrarius JQ993702 E. sp. ex apodemus sylvaticus JQ993707 E. sp. ex apodemus agrarius JQ993700 E. nafuko JQ993708 E. burdai JQ993709 E. lancasterensis KT361039 E. tamiasciuri KT184375 Isospora manorinae KT224377 E. magna KF419217 E. intestinalis JQ993693 E. irresidua JQ993694 E. piriformis JQ993698 E. exigua JQ993691 E. sp. alectoris graeca HM117020 E. cahirinensis JQ993686 E. macusaniensis KU215889 E. arloingi rangeland goats KX857470 E. hirci rangeland goats KX857469 E. christenseni rangeland goats KX857468 E. ahsata KT184373 E. bovis KT184372 E. zuernii HM771687 E. sp. RY-2016a KT305929 E. innocua HG793049 E. purpureicephali KU140598 E. dispersa KJ608416 E. dispersa HG793048 E. acervulina EF158855 E. acervulina FJ236420 E. acervulina FJ236428
305 COI sequences Genbank Accession No. E. brunetti HM771675 E. mitis FR796699 Toxoplasma gondii KM657810
306 APPENDIX 6. The 18S rDNA sequences utilised in Entamoeba phylogenetic analyses.
18S sequences GenBank Accession no. Entamoeba sp. rangeland goats KY012746 Entamoeba sp. rangeland goats KY012747 Entamoeba sp. rangeland goats KY012748 E. bovis FN666250 E. bovis FN666249 E. bovis FN666248 E. bovis FN666252 E. bovis FN666251 Entamoeba sp. RL8 KR025406 Entamoeba sp. RL3 FR686359 Entamoeba sp. RL3 FR686358 Entamoeba sp. RL2 FR686363 Entamoeba sp. RL2 FR686362 Entamoeba sp. CS-2010 FN666253 Entamoeba sp. RL4 FR686361 E. moshkovskii AF149906 E. ecuadoriensis DQ286373 E. dispar Z49256 E. histolytica X64142 E. nuttalli FR686356 E. equi DQ286371 E. insolita AF149909 Entamoeba sp. RL6 AF149911 Entamoeba sp. RL5 FR686365 E. terrapinae AF149910 E. hartmanni AF149907 E. ranarum AF149908 E. invadens AF149905 E. gingivalis D28490 E. suis DQ286372 E. poleckii AF149913 E. coli AF149914
307 APPENDIX 7. The actin sequences utilised in Entamoeba phylogenetic analyses.
Actin sequences GenBank Accession no. E. invadens AK422641 E. invadens AK421778 E. invadens AK423421 E. invadens AK423715 E. invadens AK423143 E. invadens AK423812 E. invadens AK423483 E. invadens AK421769 E. invadens AB522086 E. invadens AK422259 E. invadens AK424086 E. invadens AK424152 E. invadens AK422955 E. invadens AK423830 E. invadens AK423417 E. invadens AK423753 E. invadens AK422264 E. suis AB914739 E. suis AB914740 E. suis AB914741 Entamoeba sp. rangeland goats KX363870 E. moshkovskii EMO 002120-1 E. dispar EDI 004490A E. histolytica AK420640 E. histolytica AK420864 E. histolytica AK419281 E. histolytica AK419282 E. histolytica AK419296 E. histolytica AK420713 Rhizomastix bicoronata KP343638
308 APPENDIX 8. Zoonotic Cryptosporidium and Giardia shedding by captured rangeland goats.
Al-Habsi, K., Yang, R., Williams, A., Miller, D., Ryan, U., Jacobson, C., 2017. Zoonotic
Cryptosporidium and Giardia shedding by captured rangeland goats. Veterinary
Parasitology: Regional Studies and Reports. 7, 32–35. https://doi.org/10.1016/j.vprsr.2016.11.006.
309 APPENDIX 9. Morphological and molecular characterization of three Eimeria species from captured rangeland goats in Western Australia.
Al-Habsi, K., Yang, R., Ryan, U., Miller, D., Jacobson, C., 2017. Morphological and molecular characterization of three Eimeria species from captured rangeland goats in
Western Australia. Veterinary Parasitology: Regional Studies and Reports. 9, 75–83. https://doi.org/10.1016/j.vprsr.2017.05.001.
310 APPENDIX 10. Morphological and molecular characterization of an uninucleated cyst-producing Entamoeba spp. in captured rangeland goats in Western Australia.
Al-Habsi K., Yang, R., Ryan, U., Jacobson, C., Miller, D.W., 2017. Morphological and molecular characterization of an uninucleated cyst-producing Entamoeba spp. in captured
Rangeland goats in Western Australia. Veterinary Parasitology. 235, 41–46. https://doi.org/10.1016/j.vetpar.2017.01.013.
311 APPENDIX 11. Molecular characterisation of Salmonella enterica serovar Typhimurium and Campylobacter jejuni faecal carriage by captured rangeland goats.
Al-Habsi, K., Yang, R., Abraham, S., Miller, D., Ryan, U., Jacobson, C., 2017. Molecular characterisation of Salmonella enterica serovar Typhimurium and Campylobacter jejuni faecal carriage by captured rangeland goats. Small Ruminant Research. 158, 48–53. https://doi.org/10.1016/j.smallrumres.2017.11.011.
312