The Ins and Outs of DNA Fingerprinting the Infectious Fungi

Abstract

SUMMARY DNA fingerprinting methods have evolved as major tools in fungal epidemiology. However, no single method has emerged as the method of choice, and some methods perform better than others at different levels of resolution. In this review, requirements for an effective DNA fingerprinting method are proposed and procedures are described for testing the efficacy of a method. In light of the proposed requirements, the most common methods now being used to DNA fingerprint the infectious fungi are described and assessed. These methods include restriction fragment length polymorphisms (RFLP), RFLP with hybridization probes, randomly amplified polymorphic DNA and other PCR-based methods, electrophoretic karyotyping, and sequencing-based methods. Procedures for computing similarity coefficients, generating phylogenetic trees, and testing the stability of clusters are then described. To facilitate the analysis of DNA fingerprinting data, computer-assisted methods are described. Finally, the problems inherent in the collection of test and control isolates are considered, and DNA fingerprinting studies of strain maintenance during persistent or recurrent infections, microevolution in infecting strains, and the origin of nosocomial infections are assessed in light of the preceding discussion of the ins and outs of DNA fingerprinting. The intent of this review is to generate an awareness of the need to verify the efficacy of each DNA fingerprinting method for the level of genetic relatedness necessary to answer the epidemiological question posed, to use quantitative methods to analyze DNA fingerprint data, to use computer-assisted DNA fingerprint analysis systems to analyze data, and to file data in a form that can be used in the future for retrospective and comparative studies.

Genetic diversity and dynamics of bacterial and yeast strains associated to Spanish-style green table-olive fermentations in large manufacturing companies

“…The quality of the cluster analysis was verified by calculating the cophenetic correlation value (in percentage) for each dendrogram, using the BioNumerics 7.0 software. Interpretation of values obtained for the similarity coefficients was as follows: 1.0, genetically indistinguishable isolated; 0.99 to 0.80, closely related isolates that are highly similar but not identical, which could be considered the same strain; 0.79 to 0.50, related isolates; b 0.50, unrelated isolates (Tenover et al, 1995;Soll, 2000).…”

Sudden increase of vancomycin-resistant enterococcal infections in a Korean tertiary care hospital: possible consequences of increased use of oral vancomycin

“…The dendrogram was generated from the matrix of similarity coefficients (Dice) which were calculated by the unweighted pair-group method. 15 Plasmids were isolated by the alkaline lysis method and the patterns were compared after electrophoresis and staining. 16 …”

Usefulness of McRAPD for typing and importance of biofilm production in a case of nosocomial ventriculoperitoneal shunt infection caused by Candida lusitaniae

“…No marked differences were observed in either RAPD fingerprints or McRAPD profiles between the isolates showing different positions in some chromosomes after PFGE, confirming that the isolates recovered from our patient should belong to the same strain. Thus, small differences in their karyotypes should indicate microevolution possibly due to slight chromosome translocation which has been already reported, particularly in C. albicans (Iwaguchi et al 2001;Soll 2000).…”