| Literature DB >> 25685835 |
Sonjoy Kumar Borthakur1, Dilip Kumar Deka2, Saidul Islam2, Dilip Kumar Sarma3, Prabhat Chandra Sarmah2.
Abstract
The aim of the present study was to determine the prevalence of Dirofilaria immitis in stray, pet, and working dogs (n = 413, 266, and 103, resp.) from Guwahati (Assam) and Aizawl (Mizoram), areas located in two Northeastern States of India. Diagnostic methods applied were microscopy (wet film and Knott's concentration technique), immunological test (Ag ELISA by SNAP 4Dx ELISA kit), and molecular tools (polymerase chain reaction and sequencing), which evidenced 11.38, 18.03, and 13.93% of positive animals, respectively. No significant differences were observed by area (18.23% versus 17.68%) nor by sex (18.1% versus 17.9%), whereas stray dogs proved more infected than other groups (P < 0.05). ELISA test evidenced an overall 22.69% of occult infections, mainly in working dogs (60%), and molecular techniques detected Dirofilaria (Nochtiella) repens in 4 stray dogs from Guwahati. Characterization of D. immitis isolates for ITS-2 region showed close identity with South Asian isolates.Entities:
Mesh:
Year: 2015 PMID: 25685835 PMCID: PMC4320797 DOI: 10.1155/2015/265385
Source DB: PubMed Journal: ScientificWorldJournal ISSN: 1537-744X
Figure 1Map showing the study areas.
Prevalence of Dirofilaria immitis by category of dogs and area of study on the basis of Ag ELISA test.
| Dog category | Guwahati | Aizawl | Overall | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Numbers | Positive | Chi value | Numbers | Positive | Chi value | Numbers | Positive | Chi value | |
| Stray dogs | 223 | 63 (28.25) | 27.6139 | 190 | 44 (23.15) | 11.0458 | 413 | 107 (25.90) | 36.7706 |
| Pet dogs | 174 | 17 (9.77) | 92 | 7 (7.60) | 266 | 24 (9.02) | |||
| Working dogs | 91 | 9 (9.89) | 12 | 1 (8.33) | 103 | 10 (9.70) | |||
|
| |||||||||
| Total | 488 | 89 (18.23) | 294 | 52 (17.68) | 782 | 141 ( | |||
Comparative efficacy percentage of microscopy, Ag ELISA, and PCR in detecting Dirofilaria immitis infection in dogs.
| Detection methods | |||||
|---|---|---|---|---|---|
| Dog category | Number of blood samples tested | Microscopy (Knott's technique) | Ag ELISA | PCR | |
| Numbers of positive (%) | Numbers of positive (%) | Specific primer for | Panfilarial primers (%) | ||
| Stray | 413 | 69 (16.70%) | 107 (25.90%) | 88 (21.30%) | 92 (88 + 4*) |
| Pet | 266 | 16 (6.01%) | 24 (9.02%) | 17 (6.39%) | 17 (6.39%) |
| Working | 103 | 4 (3.88%) | 10 (9.70%) | 4 (3.88%) | 4 (3.88%) |
|
| |||||
| Grand total | 782 | 89 (11.38%) | 141 (18.03%) | 109 (13.93%) | 113 (14.45%) |
* Dirofilaria repens.
Figure 2(a) Gel picture showing amplification of D. immitis (specific primers). Lane A: 100 bp ladder. Lane B: negative. Lane C: PCR product of ITS-2. (b) Gel picture showing amplification of D. immitis and D. repens (panfilarial primers). Lane A: 100 bp ladder. Lanes B and C: amplification for D. immitis. Lanes D and E: amplification for D. repens.
Figure 3Phylogenetic tree constructed for Dirofilaria immitis from the ITS-2 region using Clustal W of DNASTAR.
ITS-2 sequence pair distance analysis of Dirofilaria immitis isolates compared with homologous isolates (slow/accurate, IUB).
| Percent identity | |||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| ||||
| Divergence |
| 99.8 | 94.1 | 91.0 | 90.2 | 90.2 | 84.7 | 93.4 | 95.5 | 95.7 | 95.9 | 95.4 | 94.5 | 98.9 |
|
| |
|
| 0.2 | 94.1 | 91.0 | 90.2 | 90.2 | 84.7 | 93.4 | 95.5 | 95.4 | 95.7 | 95.2 | 94.3 | 98.6 |
|
| ||
|
| 5.1 | 5.1 | 95.7 | 94.9 | 94.1 | 91.4 | 93.3 | 93.7 | 95.7 | 88.6 | 93.7 | 86.3 | 93.7 |
| FJ2634568 Brazil | ||
|
| 8.7 | 8.7 | 4.6 | 97.6 | 93.7 | 89.0 | 90.2 | 90.6 | 92.2 | 85.5 | 90.6 | 83.1 | 90.6 |
| FJ263462 Brazil | ||
|
| 9.6 | 9.6 | 5.5 | 2.5 | 95.3 | 88.3 | 90.2 | 89.8 | 91.4 | 84.8 | 89.8 | 82.4 | 89.8 |
| FJ263464 Brazil | ||
|
| 9.6 | 9.6 | 6.3 | 6.8 | 5.0 | 87.9 | 89.8 | 89.5 | 91.4 | 84.8 | 89.5 | 83.2 | 89.8 |
| HM126607 Turkey | ||
|
| 13.6 | 13.6 | 6.1 | 8.9 | 9.3 | 9.8 | 88.5 | 88.5 | 86.8 | 80.0 | 88.1 | 78.6 | 84.4 |
| JN084168 Iran | ||
|
| 4.1 | 4.1 | 4.3 | 7.9 | 7.4 | 7.9 | 12.8 | 97.4 | 95.4 | 89.3 | 97.1 | 87.6 | 93.4 |
| JN084166 Iran | ||
|
| 1.8 | 1.8 | 3.8 | 7.4 | 7.9 | 8.4 | 12.7 | 2.8 | 98.0 | 91.6 | 99.2 | 89.9 | 95.5 |
| JX889634 Iran | ||
|
| 0.5 | 0.7 | 2.9 | 6.9 | 7.3 | 7.3 | 13.6 | 4.1 | 1.2 | 92.0 | 97.0 | 90.7 | 95.0 |
| EU087699 Mizoram | ||
|
| 0.0 | 0.2 | 5.4 | 9.3 | 10.2 | 10.2 | 14.4 | 4.3 | 1.9 | 0.5 | 93.2 | 95.4 | 94.8 |
| EU182329 China | ||
|
| 1.2 | 1.5 | 3.8 | 7.4 | 7.9 | 8.4 | 13.2 | 3.1 | 0.9 | 0.7 | 1.3 | 91.8 | 94.8 |
| EU182331 China | ||
|
| 0.7 | 1.0 | 6.7 | 10.5 | 11.4 | 10.4 | 15.5 | 5.2 | 2.8 | 1.3 | 0.7 | 2.0 | 93.4 |
| EU182330 China | ||
|
| 0.0 | 0.2 | 5.1 | 8.7 | 9.6 | 9.6 | 13.7 | 4.1 | 1.8 | 0.5 | 0.0 | 1.2 | 0.7 |
| AF217800 Taiwan | ||
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| ||||