An efficient strategy of screening for pathogens in wild-caught ticks and mosquitoes by reusing small RNA deep sequencing data.

Published

Journal Article

This paper explored our hypothesis that sRNA (18 ∼ 30 bp) deep sequencing technique can be used as an efficient strategy to identify microorganisms other than viruses, such as prokaryotic and eukaryotic pathogens. In the study, the clean reads derived from the sRNA deep sequencing data of wild-caught ticks and mosquitoes were compared against the NCBI nucleotide collection (non-redundant nt database) using Blastn. The blast results were then analyzed with in-house Python scripts. An empirical formula was proposed to identify the putative pathogens. Results showed that not only viruses but also prokaryotic and eukaryotic species of interest can be screened out and were subsequently confirmed with experiments. Specially, a novel Rickettsia spp. was indicated to exist in Haemaphysalis longicornis ticks collected in Beijing. Our study demonstrated the reuse of sRNA deep sequencing data would have the potential to trace the origin of pathogens or discover novel agents of emerging/re-emerging infectious diseases.

Full Text

Duke Authors

Cited Authors

  • Zhuang, L; Zhang, Z; An, X; Fan, H; Ma, M; Anderson, BD; Jiang, J; Liu, W; Cao, W; Tong, Y

Published Date

  • January 2014

Published In

Volume / Issue

  • 9 / 3

Start / End Page

  • e90831 -

PubMed ID

  • 24618575

Pubmed Central ID

  • 24618575

Electronic International Standard Serial Number (EISSN)

  • 1932-6203

International Standard Serial Number (ISSN)

  • 1932-6203

Digital Object Identifier (DOI)

  • 10.1371/journal.pone.0090831

Language

  • eng