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个人信息Personal Information
副教授
博士生导师
硕士生导师
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:生物工程学院
联系方式:13342277088
电子邮箱:biolwl@dlut.edu.cn
Nested PCR detection of malaria directly using blood filter paper samples from epidemiological surveys
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论文类型:期刊论文
发表时间:2014-05-08
发表刊物:MALARIA JOURNAL
收录刊物:SCIE、Scopus
卷号:13
期号:1
ISSN号:1475-2875
关键字:Malaria; PCR detection; Blood filter paper; Epidemiology; Sensitivity; Accuracy
摘要:Background: Nested PCR is considered a sensitive and specific method for detecting malaria parasites and is especially useful in epidemiological surveys. However, the preparation of DNA templates for PCR is often time-consuming and costly.
Methods: A simplified PCR method was developed to directly use a small blood filter paper square (2 x 2 mm) as the DNA template after treatment with saponin. This filter paper-based nested PCR method (FP-PCR) was compared to microscopy and standard nested PCR with DNA extracted by using a Qiagen DNA mini kit from filter paper blood spots of 204 febrile cases. The FP-PCR technique was further applied to evaluate malaria infections in 1,708 participants from cross-sectional epidemiological surveys conducted in Myanmar and Thailand.
Results: The FP-PCR method had a detection limit of similar to 0.2 parasites/mu L blood, estimated using cultured Plasmodium falciparum parasites. With 204 field samples, the sensitivity of the FP-PCR method was comparable to that of the standard nested PCR method, which was significantly higher than that of microscopy. Application of the FP PCR method in large cross-sectional studies conducted in Myanmar and Thailand detected 1.9% (12/638) and 6.2% (66/1,070) asymptomatic Plasmodium infections, respectively, as compared to the detection rates of 1.3% (8/638) and 0.04% (4/1,070) by microscopy.
Conclusion: This FP-PCR method was much more sensitive than microscopy in detecting Plasmodium infections. It drastically increased the detection sensitivity of asymptomatic infections in cross-sectional surveys conducted in Thailand and Myanmar, suggesting that this FP-PCR method has a potential for future applications in malaria epidemiology studies.