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Use of a bioinformatic-assisted primer design strategy to establish a new nested PCR-based method for Cryptosporidium

Overview of attention for article published in Parasites & Vectors, October 2017
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Title
Use of a bioinformatic-assisted primer design strategy to establish a new nested PCR-based method for Cryptosporidium
Published in
Parasites & Vectors, October 2017
DOI 10.1186/s13071-017-2462-4
Pubmed ID
Authors

Anson V. Koehler, Pasi K. Korhonen, Ross S. Hall, Neil D. Young, Tao Wang, Shane R. Haydon, Robin B. Gasser

Abstract

The accurate tracking of Cryptosporidium in faecal, water and/or soil samples in water catchment areas is central to developing strategies to manage the potential risk of cryptosporidiosis transmission to humans. Various PCR assays are used for this purpose. Although some assays achieve specific amplification from Cryptosporidium DNA in animal faecal samples, some do not. Indeed, we have observed non-specificity of some oligonucleotide primers in the small subunit of nuclear ribosomal RNA gene (SSU), which has presented an obstacle to the identification and classification of Cryptosporidium species and genotypes (taxa) from faecal samples. Using a novel bioinformatic approach, we explored all available Cryptosporidium genome sequences for new and diagnostically-informative, multi-copy regions to specifically design oligonucleotide primers in the large subunit of nuclear ribosomal RNA gene (LSU) as a basis for an effective nested PCR-based sequencing method for the identification and/or classification of Cryptosporidium taxa. This newly established PCR, which has high analytical specificity and sensitivity, is now in routine use in our laboratory, together with other assays developed by various colleagues. Although the present bioinformatic workflow used here was for the specific design of primers in nuclear DNA of Cryptosporidium, this approach should be broadly applicable to many other microorganisms.

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Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 13%
Student > Bachelor 6 13%
Student > Ph. D. Student 5 10%
Researcher 4 8%
Professor > Associate Professor 4 8%
Other 9 19%
Unknown 14 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 21%
Immunology and Microbiology 6 13%
Agricultural and Biological Sciences 5 10%
Medicine and Dentistry 3 6%
Computer Science 2 4%
Other 7 15%
Unknown 15 31%