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Journal of Clinical Microbiology, October 2004, p. 4503-4511, Vol. 42, No. 10
0095-1137/04/$08.00+0     DOI: 10.1128/JCM.42.10.4503-4511.2004
Copyright © 2004, American Society for Microbiology. All Rights Reserved.

Multiple-Locus Variable-Number Tandem Repeat Analysis, a Novel Typing Scheme To Study the Genetic Relatedness and Epidemiology of Enterococcus faecium Isolates

Eijkman-Winkler Institute for Microbiology, Infectious Diseases and Inflammation,¹ Department of Internal Medicine, Division of Acute Internal Medicine and Infectious Diseases, University Medical Center Utrecht, Utrecht,² Laboratory for Vaccine-Preventable Diseases, National Institute for Public Health and the Environment, Bilthoven, The Netherlands³

Received 14 April 2004/ Returned for modification 28 May 2004/ Accepted 9 June 2004

Multiresistant Enterococcus faecium is a major cause of hospital acquired infections and outbreaks. Here, we describe the development of multiple-locus variable-number tandem repeat (VNTR) analysis (MLVA) as a novel typing method to assess the genetic relatedness of E. faecium isolates. Six VNTR loci were used to genotype 392 isolates recovered from different animals and human community, hospital survey, and clinical isolates. From 3 to 13 alleles were found per locus, resulting in 127 different MLVA profiles. Clustering of MLVA profiles confirmed the host-specific genogroups found by multilocus sequence typing (MLST) and showed the grouping of clinical and epidemic isolates that belonged to the MLST-C1 cluster in a distinct MLVA-C1 cluster (sensitivity of 97% and specificity of 90%). Furthermore, the discriminatory power of MLVA is comparable to MLST. MLVA profiles appeared to be relatively stable, since isolates from a single outbreak shared the same MLVA profile, which is a prerequisite when MLVA is used to study hospital outbreaks. Our data show that MLVA is a highly reproducible and portable typing method; in contrast to MLST, it is fast, relatively cheap, and easy to perform. Furthermore, it has the abilities of MLST to recognize genetically related and potential epidemic isolates. Submission of MLVA profiles is possible via a Web-based database for international comparison.

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