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Cited by 377

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Application of DNA typing methods to epidemiology and taxonomy of Candida species

Open access
Scherer, S, Stevens, D A·1987·Journal of Clinical Microbiology

Abstract

Methods are described for extraction of DNA from the yeast form of Candida spp., followed by digestion and electrophoresis of DNA fragments. The resulting gel patterns (greater than 100 bands) were used to type Candida isolates. Four intense bands identified, three of which are present in each isolate (6 to 7, 3.7 or 4.2, and 2.5 to 3 kilobases), appear to be DNA encoding the rRNA. The methods proved to be both simple and reproducible. The patterns were shown to be stable through several hundred doublings from multiple single colonies. A survey of isolates showed that, on the basis of similarity of gel patterns, several Candida species could be sorted into mutually exclusive groups, and subgroups could be created. Analyses of this survey suggested the possible epidemiologic and taxonomic applications of these methods. DNA typing methods appear to offer important potential advantages over phenotyping methods. The methods provide a base for further epidemiologic studies and for further development of techniques, such as the use of cloned probes for studies of DNA homology.

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Metadata

Authors
Scherer, S., & Stevens, D. A.
Venue
Journal of Clinical Microbiology
Published
1987-04
Volume
25
Issue
4
Pages
675-679
ISSN
  • 0095-1137 (ISSN-L)
  • 1098-660X
OpenAlex
W2149223090
Cited by
377
References
0
FWCI
7.00
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Application of DNA typing methods to epidemiology and taxonomy of Candida species. https://app.cochat.ai/papers/10.1128/jcm.25.4.675-679.1987
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Scherer, S., & Stevens, D. A. (1987). Application of DNA typing methods to epidemiology and taxonomy of Candida species. Journal of Clinical Microbiology. https://doi.org/10.1128/jcm.25.4.675-679.1987

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.