Sequence Analysis of the Variable Number Tandem Repeat in Staphylococcus aureus Protein A Gene - Bacterial Pathogenesis: Methods and Protocols - page 280

discriminating epidemiologically related isolates from those that are unrelated
isolates. Although the discriminatory power of PFGE is most likely higher than
that of spa typing, a number of studies have shown that the Simpson's index of
diversity of the two typing techniques approximate one another (21) . However,
PFGE analysis requires unique and costly equipment, and the method is consid-
erably more time and labor intensive compared to spa typing. Furthermore, as
PFGE produces image-based results, the storage and analysis of fingerprints
require sophisticated software and dedicated personnel to digitize and interpret
the image as well as maintain the database (6,40,41) . In addition, the interpre-
tation is somewhat subjective, and protocol standardization poses difficulty in
establishing interlaboratory reproducibility.
Numerous networks have used PFGE analysis as the primary genotyping
tool for surveillance and monitoring of outbreak strains, including food-borne
pathogens and multidrug-resistant organisms such as MRSA (42,43,44) . Here,
even with the assistance of sophisticated, commercially available, pattern-
matching software packages (45) , such as BioImage and BioNumerics, there
has been limited success in generating reproducible and comparable images
between laboratories and in assessing genetic relatedness on the basis of subtle
restriction fragment length polymorphisms. Therefore, while this method is
useful for distinguishing recent or closely related S. aureus isolates from
unrelated ones, image-based systems are limited in their ability to objectively
discern the degree of relatedness between geographically and temporally distal
isolates. In contrast, a recent international multicenter study demonstrated that
spa typing showed 100% intra- and interlaboratory reproducibility without
extensive synchronization of protocols between the laboratories (39) .
3.5.2. MLST
The limitations noted above have paved the way for genotyping methods
that are based on comparative DNA sequence analysis. Currently, the “gold-
standard” of DNA sequence-based genotyping methods is MLST, which
compares the DNA sequence variation of a number of housekeeping genes
dispersed around the bacterial genome and has been widely used to decipher the
population structure of bacterial pathogens, such as Streptococcus pneumoniae
and Neisseria meningitidis (5,46) . While the target genes used for MLST are
similar to those in MLEE, the former generates objective and unambiguous
data that is highly amenable to database storage and analysis (47,48) . However,
although MLST analysis provides a sound approach to assess genetic relat-
edness, the limited sequence variation within each target requires that numerous
genes be compared to increase discrimination. The number of MLST target
gene fragments needed to genotype bacterial isolates is dependent on the