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Identification of the Major Molecular Types of Cryptococcus neoformans and C. gattii by Hyperbranched Rolling Circle Amplification

Overview of attention for article published in PLOS ONE, April 2014
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Title
Identification of the Major Molecular Types of Cryptococcus neoformans and C. gattii by Hyperbranched Rolling Circle Amplification
Published in
PLOS ONE, April 2014
DOI 10.1371/journal.pone.0094648
Pubmed ID
Authors

Luciana Trilles, Bin Wang, Carolina Firacative, Márcia dos Santos Lazéra, Bodo Wanke, Wieland Meyer

Abstract

The agents of cryptococcosis C. neoformans and C. gattii are important agents of meningoencephalitis in immunocompromised and immunocompetent hosts, respectively. They are grouped into eight major molecular types, VNI-VNIV for C. neoformans and VGI-VGIV for C. gattii. These major molecular types differ in their host range, epidemiology, antifungal susceptibility and geographic distribution. To enable a rapid identification of the major molecular types and potential hybrids within the two species specific probes based on the PLB1 gene in combination with hyperbranched rolling circle amplification (HRCA) were developed. HRCA was applied to 76 cryptococcal strains, 10 strains each representing the 7 haploid major molecular types, 4 VNIII hybrid strains and 2 inter-species hybrid strains. All strains were correctly identified to the major molecular type and or hybrid type using HRCA alone. To increase the sensitivity a semi-nested PCR step was developed, which will enable the identification of the molecular types/hybrids directly from clinical samples, harboring a low copy number of DNA (40 copies). Thus, HRCA based on the PLB1 locus alone and in combination with a semi-nested PCR showed to be a specific and sensitive methodology, with a great potential to be used on clinical specimens for the direct diagnosis of the agents of cryptococcosis, including hybrid strains, enabling a rapid and patient tailored treatment choice of this disease.

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Geographical breakdown

Country Count As %
Mexico 1 2%
Unknown 64 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 13 20%
Researcher 9 14%
Student > Ph. D. Student 8 12%
Student > Bachelor 6 9%
Professor 4 6%
Other 12 18%
Unknown 13 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 22%
Biochemistry, Genetics and Molecular Biology 10 15%
Medicine and Dentistry 10 15%
Immunology and Microbiology 9 14%
Environmental Science 1 2%
Other 4 6%
Unknown 17 26%