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[Molecular identification of Anopheles hyrcanus complex by using single enzyme digestion PCR-RFLP method].

[Article in Chinese]

Author information

1
Jiangsu Institute of Parasitic Diseases, Key Laboratory on Technology for Parasitic Disease Prevention and Control, Ministry of Health, Wuxi 214064, China.

Abstract

OBJECTIVE:

To establish a novel molecular identification method for discrimination of members within Anopheles hyrcanus complex.

METHODS:

The sequences of the ribosomal DNA second internal transcribed spacer (rDNA ITS2) region of An. hyrcanus complex, including An. anthropophagus, An. lesteri, An. sinesis and An. yatsushiroensisi were analyzed by using molecular biology software Vector NTI 9.0, and a specificity restriction enzyme was selected based on the restriction fragment length polymorphism. Thus the single enzyme digestion PCR-RFLP method was established for genetic identification of An. hyrcanus complex, and 452 anopheline mosquitoes captured in the field were tested, comparing with the results of the previously established double enzyme digestion PCR-RFLP method and traditional morphological classification.

RESULTS:

The molecular software analysis revealed that the restriction enzyme Dde I could digest rDNA ITS2 region of An. hyrcanus complex into different fragments, thus it could be used for single enzyme PCR-RFLP for An. hyrcanus complex identification, and the result was further confirmed by laboratory experiment. Furthermore, a total of 452 anopheline mosquitoes captured from 4 malaria endemic areas were tested by this single enzyme digestion PCR-RFLP method, and 20 of them were identified as An. anthropophagus, 6 as An. lesteri, 391 as An. sinesis, and 35 as An. yatsushiroensisi. The results were 100% accordant to the double enzyme digestion PCR-RFLP method, and 93.4% accordant to the traditional morphological classification.

CONCLUSIONS:

The newly established single enzyme digestion PCR-RFLP method can be used for An. hyrcanus complex identification, and is more simple and reliable than the traditional morphological classification, and it is a suitable tool for field entomology surveillance.

PMID:
23236792
[Indexed for MEDLINE]
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