| Literature DB >> 34068782 |
Ehab Mossaad1,2, Alex Gaithuma2, Yassir O Mohamed3, Keisuke Suganuma2,4, Rika Umemiya-Shirafuji2,4, Yuma Ohari5, Bashir Salim6, Mingming Liu2, Xuenan Xuan2,4.
Abstract
Ticks transmit many pathogens with public health and veterinary importance. Despite the wide distribution of tick-borne pathogens in Sudan, the information on the tick-pathogen relationship needs to be updated, particularly using modern molecular techniques. This cross-sectional study, conducted between September and November 2019, used morphology, PCR, and sequencing to confirm the identity of adult cattle ticks (male and female; n = 536) from Khartoum State (n = 417) and East Darfur State (n = 119). Moreover, the presence of Theileria annulata, Babesia bigemina, B. bovis, Anaplasma marginale, and Ehrlichia ruminantium was detected and confirmed in each tick using species-specific PCR or nested PCR and sequencing. The most economically important tick genera, Rhipicephalus, Hyalomma, and Amblyomma, were prevalent in the study area, and 13 different tick species were identified. The most prevalent tick species were Rhipicephalusevertsi evertsi (34.3%) and Hyalomma anatolicum (57.3%) in Khartoum State, and Rhipicephalus annulatus (27%), Rhipicephalus decoloratus (25%), and Hyalomma rufipes (29%) in East Darfur State. We detected all five pathogens in both states. To the best of our knowledge, this is the first study to report the presence of E. ruminantium, its vector Amblyomma variegatum, and B. bovis in Khartoum State. Further, this is the first report on most tick and pathogen species identified in East Darfur State. Our findings indicate the migration of some tick and pathogen species beyond their distribution areas in the country, and this consideration is necessary to develop future control strategies.Entities:
Keywords: East Darfur State; Khartoum State; Sudan; cattle; epidemiology; tick-borne pathogens; ticks
Year: 2021 PMID: 34068782 PMCID: PMC8151415 DOI: 10.3390/pathogens10050580
Source DB: PubMed Journal: Pathogens ISSN: 2076-0817
Prevalence of different tick species in Khartoum State and East Darfur State.
| Tick Species | Khartoum State | East Darfur State | Total |
|---|---|---|---|
|
| 0% (0/417) | 27% (32/119) * | 6% (32/536) |
|
| 0% (0/417) | 25% (30/119) * | 5.6% (30/536) |
|
| 34.3% (143/417) * | 0.84% (1/119) | 27% (144/536) |
|
| 2.6% (11/417) | 0% (0/119) | 2% (11/536) |
|
| 0.5% (2/417) | 0% (0/119) | 0.4% (2/536) |
|
| 1.2% (5/417) | 29% (34/119) * | 7.3% (39/536) |
|
| 57.3% (239/417) * | 0% (0/119) | 44.6% (239/517) |
|
| 2.4% (10/417) | 0% (0/119) | 1.9% (10/536) |
|
| 0% (0/417) | 0.84% (1/119) | 0.2% (1/536) |
|
| 0.24% (1/417) | 7.6% (9/119) * | 1.9% (10/536) |
|
| 0.96% (4/417) | 1.7% (2/119) | 1% (6/536) |
|
| 0% (0/417) | 8.4% (10/119) * | 1.9% (10/536) |
|
| 0.5% (2/417) | 0% (0/119) | 0.4% (2/536) |
| Total | 417 | 119 | 536 |
R.: Rhipicephalus, Am.: Amblyomma, H.: Hyalomma. * p < 0.05 with Chi-Square test or Fisher Exact Probability Test.
Prevalence of different tick-borne pathogens in ticks in Khartoum State and East Darfur State.
| PCR |
|
|
|
|
|
|---|---|---|---|---|---|
| Khartoum State | 42.7% (178/417) * | 15.1% (63/417) | 12.5% (52/417) * | 5.5% (23/417) | 12.2% (51/417) * |
| East Darfur State | 18.5% (22/119) | 31.1% (37/119) * | 4.2% (5/119) | 5.8% (7/119) | 2.5% (3/119) |
| Total | 37.3% (200/536) | 18.7% (100/536) | 10.6% (57/536) | 5.6% (30/536) | 10.07% (54/536) |
* p < 0.05 with Chi-Square test and Fisher Exact Probability Test for the prevalence of E. ruminantium.
Distribution of tick-borne pathogens within different tick species.
| Tick Species |
|
|
|
|
|
|---|---|---|---|---|---|
|
| 0% (0/200) | 11% (11/100) | 3.3% (1/30) | 1.8% (1/57) | 0% (0/54) |
|
| 0% (0/200) | 18% (18/100) | 0% (0/30) | 5.3% (3/57) | 0% (0/54) |
|
| 27.5% (55/200) | 15% (15/100) | 23.3% (7/30) | 35.1% (20/57) | 24.1% (13/54) |
|
| 2% (4/200) | 1% (1/100) | 3.3% (1/30) | 1.8% (1/57) | 5.6% (3/54) |
| 0% (0/200) | 0% (0/100) | 0% (0/30) | 0% (0/57) | 0% (0/54) | |
|
| 3.5% (7/200) | 2% (2/100) | 10% (3/30) | 1.8% (1/57) | 5.6% (3/54) |
|
| 56.5% (113/200) | 44% (44/100) | 43.3% (13/30) | 49.1% (28/57) | 55.5% (30/54) |
|
| 4% (4/200) | 4% (4/100) | 0% (0/30) | 0% (0/57) | 5.5% (3/54) |
| 0% (0/200) | 0% (0/100) | 0% (0/30) | 0% (0/57) | 0% (0/54) | |
|
| 3% (6/200) | 2% (2/100) | 10% (3/30) | 0% (0/57) | 0% (0/54) |
|
| 1.5% (3/200) | 1% (1/100) | 6.6% (2/30) | 3.5% (2/57) | 1.9% (1/54) |
|
| 4% (8/200) | 2% (2/100) | 0% (0/30) | 0% (0/57) | 1.9% (1/54) |
|
| 0% (0/200) | 0% (0/100) | 0% (0/30) | 1.8% (1/57) | 0% (0/54) |
|
| 200 | 100 | 30 | 57 | 54 |
R.: Rhipicephalus, Am.: Amblyomma, H.: Hyalomma. * No tick-borne pathogen detected.
Figure 1Phylogenetic analysis of Theileria annulata identified in this study based on Tams-1 gene sequences using the maximum likelihood method. The number at the nodes represents the percentage occurrence of clade in a 1000 bootstrap replication of data. The best model was Tamura-Nei Model 92 with Gamma distribution. Sequences from this study are shown in bold font. The tree was constructed using the MEGA version X software program.
Figure 2Phylogenetic analysis of Babesia bigemina identified in this study based on ama1 gene sequences using the maximum likelihood method. The number at the nodes represents the percentage occurrence of clade in a 1000 bootstrap replication of data. The best model was the Kimura 2-parameter model. Sequences from this study are shown in bold font. The tree was constructed using the MEGA version X software program.
Figure 3Phylogenetic analysis of Babesia bovis identified in this study based on spb4 gene sequences using the maximum likelihood method. The number at the nodes represents the percentage occurrence of clade in a 1000 bootstrap replication of data. The best model was the Kimura 2-parameter model with invariant sites. Sequences from this study are shown in bold font. The tree was constructed using the MEGA version X software program.
Figure 4Phylogenetic analysis of Anaplasma marginale identified in this study based on msp4 gene sequences using the maximum likelihood method. The number at the nodes represents the percentage occurrence of clade in a 1000 bootstrap replication of data. The best model was the Tamura 2-parameter model with invariant sites. Sequences from this study are shown in bold font. The tree was constructed using the MEGA version X software program.
Figure 5Phylogenetic analysis of Ehrlichia ruminantium identified in this study based on pCS20 gene sequences using the maximum likelihood method. The number at the nodes represents the percentage occurrence of clade in 1000 a bootstrap replication of data. The best model was Tamura-Nei Model 92. Sequences from this study are shown in bold font. The tree was constructed using the MEGA version X software program.
Figure 6A map of Sudan. Map created using the ArcMap 10.1 software program (Esri, Redlands, CA, USA).
Primer sequences used in this study.
| Pathogen Target Gene | Assays | Oligonucleotide Sequences (5′→3′) | Annealing Temperature | Product Size (bp) | References |
|---|---|---|---|---|---|
|
| PCR | ATGCTGCAAATGAGGAT | 56 °C | 768 | [ |
| GGACTGATGAGAAGACGATGAG | |||||
|
| PCR | TACTGTGACGAGGACGGATC | 62 °C | 211 | [ |
| CCTCAAAAGCAGATTCGAGT | |||||
|
| PCR | AGTTGTTGGAGGAGGCTAAT | 58 °C | 907 | [ |
| TCCTTCTCGGCGTCCTTTTC | |||||
| nPCR | GAAATCCCTGTTCCAGAG | 58 °C | 503 | [ | |
| TCGTTGATAACACTGCAA | |||||
|
| PCR | CTGAAGGGGGAGTAATGGG | 60 °C | 344 | [ |
| GGTAATAGCTGCCAGAGATTCC | |||||
|
| PCR | CTTGATGGAGGATTAAAAGCA | 60 °C | 279 | [ |
| GTAATGTTTCATGTGAATTGATCC |