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Published on: February 4, 2018
Droplet digital PCR-based pathogen monitoring system improves identifying Haemaphysalis longicornis infected with
Yujin Baek1,2, Jae-Hun Jeong1,3, Da-Eun Jeong4
1Division of Biomedical Metrology, Korea Research Institute of Standards and Science, Daejeon, Republic of Korea.
Background:
Asian long-horned ticks, Haemaphysalis longicornis, vector viruses, bacteria and parasites that cause major zoonotic diseases in human. In order to prevent and manage the spread of tick-borne zoonosis, it is important to monitor pathogen prevalence in wild tick populations using molecular diagnostics with high detection performance. In this study, we introduce a novel droplet digital PCR (ddPCR)-based pathogen monitoring system to identify Haemaphysalis longicornis ticks infected with Bandavirus dabieense and other zoonotic pathogens at low concentrations with higher sensitivity and accuracy from existing molecular detection methods.
Methods:
Using metrologically certified B. dabieense RNA reference materials, we directly compared the detection limits between ddPCR and quantitative PCR (qPCR). Then, among 502 individual H. longicornis adult ticks collected from fields, we determined the detection rate of ticks infected with B. dabieense. We also investigated tick innate immune system, JAK/STAT, for its relevance in identifying ticks infected with low concentrations of B. dabieense. From B. dabieense-infected ticks, we examined for other tick-borne pathogens and nucleic acid concentrations of identified pathogens using ddPCR.
Results:
Our ddPCR-based method showed high sensitivity by 20 times lower detection limits than that of qPCR. Detection rate of ticks infected with B. dabieense from fields was 35.9%. Among ticks infected with low B. dabieense virus concentrations, defined by the B. dabieense RNA copy numbers in bottom 25% quartiles observed from infected ticks, STAT expression level was significantly higher compared to laboratory strains and uninfected field populations. Lastly, multiplexed ddPCR results indicated that individual ticks can harbor up to four different pathogens concurrently.
Conclusions:
Our newly developed ddPCR-based pathogen monitoring system improves the identification of H. longicornis infected with B. dabieense and other tick-borne pathogens at low nucleic acid concentrations compared with qPCR. In addition, our results suggest that STAT expression may provide exploratory and complementary insight into tick innate immune activation in low-copy B. dabieense infections, and that ddPCR-based multiplexing can detect co-infections with multiple tick-borne pathogens in individual ticks. These findings highlight the potential of ddPCR as a sensitive and practical tool for surveillance and management of tick-borne zoonotic pathogens in vector populations.
