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Journal of Clinical Microbiology, February 2006, p. 374-377, Vol. 44, No. 2
0095-1137/06/$08.00+0 doi:10.1128/JCM.44.2.374-377.2006
Copyright © 2006, American Society for Microbiology. All Rights Reserved.
Locus-Specific Mutational Events in a Multilocus Variable-Number Tandem Repeat Analysis of Escherichia coli O157:H7
Anna C. Noller,1,2
M. Catherine McEllistrem,1
Kathleen A. Shutt,1 and
Lee H. Harrison1*
Infectious Diseases Epidemiology Research Unit,1
Department of Infectious Diseases and Microbiology, University of Pittsburgh Graduate School of Public Health and School of Medicine, Pittsburgh, Pennsylvania2
Received 2 June 2005/
Returned for modification 17 August 2005/
Accepted 30 November 2005

ABSTRACT
Multilocus variable-number tandem repeat analysis (MLVA) is
a validated molecular subtyping method for detecting and evaluating
Escherichia coli O157:H7 outbreaks. In a previous study, five
outbreaks with a total of 21 isolates were examined by MLVA.
Nearly 20% of the epidemiologically linked strains were single-locus
variants (SLV) of their respective predominant outbreak clone.
This result prompted an investigation into the mutation rates
of the seven MLVA loci (TR1 to TR7). With an outbreak strain
that was an SLV at the TR1 locus of the predominant clone, parallel
and serial batch culture experiments were performed. In a parallel
experiment, none (0/384) of the strains analyzed had mutations
at the seven MLVA loci. In contrast, in the two 5-day serial
experiments, 4.3% (41/960) of the strains analyzed had a significant
variation in at least one of these loci (
P < 0.001). The
TR2 locus accounted for 85.3% (35/41) of the mutations, with
an average mutation rate of 3.5
x 10
3; the mutations
rates for TR1 and TR5 were 10-fold lower. Single additions accounted
for 77.1% (27/35) of the mutation events in TR2 and all (6/6)
of the additions in TR1 and TR5. The remaining four loci had
no slippage events detected. The mutation rates were locus specific
and may impact the interpretation of MLVA data for epidemiologic
investigations.

INTRODUCTION
Prokaryotic genomes contain a wide array of repetitive DNA elements
ranging from single-nucleotide repeats to large, complicated
repeats of dozens of nucleotides. Variable-number tandem repeats
(VNTRs) are repeats that are found in tandem and demonstrate
interstrain variability. Multilocus VNTR analysis (MLVA) has
become a reliable way to establish genetic relatedness for epidemiological
surveillance and molecular subtyping of organisms such as
Escherichia coli O157:H7 (
15,
16),
Salmonella enterica serovar Typhimurium
(
12),
Francisella tularensis (
4), and
Bacillus anthracis (
8).
The basis of molecular typing with VNTRs is that these elements
mutate, creating different alleles at the same VNTR locus.
Tandem repeat (TR) loci are among the most variable regions of many bacterial genomes (19). TRs arise through slippage and mispairing during DNA replication due to occasional DNA polymerase dissociation (17, 19, 20). Repeats can be inserted or deleted, depending on the strand orientation (13). If the tertiary structure occurs in the template strand during replication, a loss of at least one TR will result in the new DNA strand. Likewise, if the event occurs in the nascent strand, one or more TRs can be added. Multiple factors influence the frequency and type of TR mutation, such as the number of TRs and the unit size of the TR. As the number of TRs increases, the slippage mutation rate dramatically increases due to instability, which accounts for the fact that long TRs are relatively uncommon (10). The mutation rate also increases with perfectly homologous repeats (13). In contrast, the mutation rate decreases when a disruption occurs in the repeat, such as a point mutation that decreases the length of the homologous repeat. In addition to the number of TRs, the nucleotide length and composition of each TR can affect the rate of slippage mutation: the shorter the TR unit length, the higher the mutation rate (18). Poly(G-T) tracts and polypyrimidine tracts also have been shown to be associated with high mutation rates (11). Multiple studies have shown that certain repeats, such as repeating purine-pyrimidine sequences, result in a bias toward expansion if the sequence is on the leading strand (2, 6, 7). Estimations of the rate of change have been performed to a limited degree with human VNTRs due to their involvement with heritable diseases, but there is a paucity of literature on the rate of mutational changes of VNTRs in bacteria.
Knowledge of the rate of TR change is important when using MLVA as part of an outbreak investigation. In a previous study, we demonstrated that isolates from the same outbreak either had an identical MLVA type or were single-locus variants (SLVs), suggesting that mutations can occur during the course of an outbreak (15, 16). In five separate outbreaks, 19% (4/21) of the strains were SLVs of their respective predominant outbreak clone. Intraoutbreak events also have been observed with other molecular subtyping methods, such as pulsed-field gel electrophoresis (9, 15). All SLVs that were observed during outbreaks differed from the predominant MLVA type by a single repeat. In addition, analysis of our MLVA data demonstrates that the TR1, TR2, and TR5 loci had a greater number of alleles than the other four loci (15). These observations underscore the need to understand the complex dynamics of TR mutation events at each locus for the optimal interpretation of MLVA results.
With a known outbreak strain of E. coli O157:H7 that was an SLV of the predominant MLVA type at the TR1 locus, we performed both parallel (independent) and serial (dependent) mutation experiments to examine the seven MLVA locus mutation rates. By examining the in vitro mutation rate for each of the MLVA loci, we may be able to enhance MLVA's ability to characterize and define outbreaks.

MATERIALS AND METHODS
Isolate.
E. coli O157:H7 isolate PHIDL #53, provided by the Allegheny
County Health Department in Pittsburgh, PA, was selected for
two reasons. The outbreak strain was an SLV of the predominant
MLVA outbreak type, with 16 repeats rather than 15 repeats at
the TR1 locus. Moreover, the strain's MLVA alleles were close
to the median number of repeats of the 80 isolates in our previous
study (Table
1) (
15).
Parallel (independent) mutation experiment.
To alleviate the potential issue of nonindependent mutation
events, 10 parallel cultures were propagated simultaneously.
From a frozen culture, the study isolate was streaked for isolation
on 5% sheep blood agar (SBA) and incubated overnight at 37°C.
A single colony was inoculated into 110 µl of Luria broth
(LB), and then 10 µl of the bacterial suspension was added
to 10 flasks containing 9.99 ml of LB and incubated for 15 h
at 37°C in a rotating water bath. Ten microliters of the
original bacterial suspension was withheld to analyze the seven
MLVA loci of the founder colony. One hundred microliters of
a 10
6 dilution from each flask was subcultured onto 5%
SBA plates. After 24 h of incubation at 37°C, 8 of 10 plates
had at least 48 colonies/plate. The remaining two plates were
excluded from the analysis since the low colony count precluded
random sampling. DNA was obtained from single colonies by suspending
each colony in 50 µl of sterile water and boiling it for
2 min. The boiled suspensions were centrifuged for a short pulse
at full speed to spin down cellular debris. The supernatant
was collected in new tubes. PCR was performed with this DNA,
and the MLVA types of 384 colonies were compared to the molecular
subtype of the original founder colony of PHIDL #53 (
15,
16).
Serial (dependent) mutation experiment.
An isolated colony of PHIDL #53 was suspended in 10 ml of LB and incubated at 37°C in a rotating water bath for 12 h. After the 12-h incubation, 100 µl of a 104 dilution was aliquoted into 9.9 ml of LB. This 12-h incubation-aliquoting into LB cycle was done a total of 10 times. At each 12-h time point, a sample of the bacterial suspension was taken for MLVA analyses (15, 16). Specifically, 100 µl of a 106 dilution was subcultured on 5% SBA and incubated overnight at 37°C, and 48 colonies/plate were analyzed by MLVA. The MLVA types of these colonies were compared to the molecular subtype of the original founder colony of PHIDL #53. The number of generations per time point was calculated as follows: [log10 (no. of CFUend of 12 h) log10 (no. of CFUbeginning of 12 h)]/log10 2.
Data analysis.
The mutation rate was based on the mutant fraction and number of generations. The mutant fraction was the number of mutation events divided by the number of colonies screened at that time (14). This value was multiplied by 2/number of generations to compute the mutation rate (14). At each time point over the 5-day period, the mutation rate for TR2 was calculated. These nine rates were averaged to determine an overall rate for each experiment.

RESULTS
Parallel (independent) mutation experiment.
Due to low colony counts, 2 of the 10 subcultured plates were
excluded from the analysis. An analysis of 48 colonies from
each of the eight plates revealed no mutation events (0/384).
All colonies had the same MLVA type as the original colony of
PHIDL #53.
Serial (dependent) mutation experiment.
The serial (dependent) mutation experiment, performed in duplicate, detected a similar mutation rate for each experiment (experiment A and experiment B; Table 2). Among all seven loci, TR2 accounted for the highest proportion of mutation events: 11/13 (84.6%) in experiment A and 24/28 (85.7%) in experiment B. The TR2 mutation frequency did not differ over time for either experiment A or experiment B. When the data from experiment A or B were combined, the mutation frequency appeared to increase over time, although this did not reach statistical significance (P = 0.063). The majority of events were single TR additions, but both deletion and addition events of single and multiple TR units were observed (Fig. 1). The average mutation rate for TR2 in experiment A was 2.1 x 103, while in experiment B the average rate was 4.8 x 103; the rates did not differ statistically significantly between the experiments. TR1 and TR5 had single addition events but resulted in a lower mutation rate than TR2. TR1 was associated with one event in both experiments, and TR5 was associated with one event in experiment A and three in experiment B. For TR1, the average mutation rate for experiment A was 1.7 x 104 and for experiment B it was 2.1 x 104. For TR5, experiment A demonstrated an average mutation rate of 1.7 x 104 and experiment B demonstrated an average mutation rate of 6.2 x 104. The remaining four loci had no slippage events in either of the experiments.
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TABLE 2. Numbers of observed mutation events in the two serial mutation experiments and average mutation rates by TR locus
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In summary, the main difference between the parallel and serial
experiments was the number of cells that were inoculated into
broth at the beginning of the study. A whole colony was used
in the serial experiments, while 1/11 of a colony was used to
inoculate each of the 10 flasks for the parallel experiments.
Therefore, a smaller number of cells was present in the flasks
at the onset of the parallel compared to the serial study. However,
similar numbers of generations were present in the serial and
parallel experiments. In the parallel experiment, none (0/384)
of the strains analyzed had mutations in the seven MLVA loci.
In contrast, in the 5-day serial experiments, 4.3% (41/960)
of the strains analyzed had a variation in at least one of these
loci (
P < 0.001).

DISCUSSION
In this investigation, we detected no mutation events in the
parallel mutation study. In contrast, a significant number of
mutation events was reproducibly observed in the serial mutation
study. Eighty-five percent of the mutation events were detected
at the TR2 locus, with only two and four events occurring at
the TR1 and TR5 loci, respectively. During both serial mutation
experiments, there was an overwhelming tendency toward the addition
of TRs, and most involved a single TR change at all three loci
that mutated. This is consistent with our previous study, in
which we observed three intraoutbreak SLVs, all differing by
a single TR (
15). The single addition at the TR1 locus for PHIDL
#53 in the in vitro experiment mirrored the type of addition
observed in this strain compared to the predominant outbreak
strain in vivo.
As the inoculation size should not make a difference in the mutation rate, undetected differences may have accounted for the significant variation in the mutation rate between the serial and parallel experiments. Multiple cycles through the stationary phase may have been important for the generation of mutations. To validate this hypothesis, additional experiments with a standardized initial inoculum size are needed.
VNTRs have been shown to be a powerful tool for the molecular subtyping of a wide range of organisms, including humans, plants, and bacteria (1-4, 8, 12, 15). However, interpretation of assays that exploit these genetic elements for epidemiologic purposes requires an understanding of the dynamics of TR mutations. Many studies of VNTR mutations have been focused on those VNTRs associated with human disease (2, 7, 17). While general VNTR mutation comparisons can be made between bacteria and eukaryotes due to the highly conserved genes involved in mutation repair, an MLVA of mutations needs to be made for each locus in each bacterial species (5).
In an unpublished study of E. coli O157:H7, a single colony seeded 96 parallel cultures that were subsequently subcultured 40 times (C. Keys, Z. Jay, A. Fleishman, J. Fox, G. Evans, and P. Keim, poster, 103rd Gen. Meet. Am. Soc. Microbiol. 2003; 9). Despite the ability to circumvent the issue of independence, this study also detected the hypermutability of TR2. The current literature suggests that TRs have a tendency toward expansion, depending on the nucleotide sequence composition. Previous research, mostly done with mono-, di-, tri-, and tetranucleotide sequences, has shown that certain sequences can form tertiary structures, which increases the rate of mutation (3, 6, 7). To our knowledge, there is no literature describing hexanucleotide TRs and their mutation propensities.
Although no mutations were detected in TR3, TR4, TR6, and TR7 in these in vitro experiments, the epidemiologic data indicate that these loci do mutate (15). Perhaps the lack of mutations observed at these four loci was because the frequency was below the limit of detection in the in vitro experiments. Further experiments are required to better understand the mutational dynamics at these loci. In addition, to fully characterize how the MLVA loci mutate, a more detailed investigation would need to be undertaken. The allelic extremes of each locus would need to be examined to determine how the length of the TR influences the mutational dynamics. These questions must be answered to completely understand how TRs change for the optimal interpretation of MLVA data.
In light of the results from these experiments and our previous study, several generalizations can be made about the interpretation of MLVA data during outbreak investigations. Among epidemiologically linked strains, isolates with identical MLVA types likely acquired their infection from the same source. In addition, SLVs that differ by either a single or a double TR might have arisen from a point source and should be investigated accordingly. If an isolate differs from presumed outbreak isolates at two different loci (i.e., a double-locus variant), then the mutational characteristics of the specific loci and the degree of variation in the number of TRs would be important issues to consider. Based on this in vitro study, a double-locus variant that includes an increase in TR size of two at the TR2 locus might be part of the outbreak. Additional research, as described above, is required to develop more specific guidelines for MLVA data interpretation. In general, precise cutoffs will be difficult to develop because some variables, such as the duration of the outbreak and the environment outside the host, will likely increase the likelihood that additional intraoutbreak variability will be observed. Therefore, as with all molecular subtyping methods, interpretation of MLVA results must be done in conjunction with epidemiologic data.

ACKNOWLEDGMENTS
We thank the Allegheny County Health Department for its support,
especially Bruce Dixon, Joan McMahon, and Mary Blazina for assistance
in obtaining the isolates, and the Minnesota Department of Health
for its isolates, especially David Boxrud.
Support for this study was provided in part by the Technical Support Working Group through the Department of Defense (N41745-03-C-4005) and Research Career Awards (K24 AI52788 to L.H.H. and K23 AI01788 to M.C.M.) from the National Institute of Allergy and Infectious Diseases.
Any opinions, findings, conclusions, or recommendations expressed herein are ours and do not reflect the views of the Public Health Service or the University of Pittsburgh.

FOOTNOTES
* Corresponding author. Mailing address: Infectious Diseases Epidemiology Research Unit, University of Pittsburgh Graduate School of Public Health and School of Medicine, 521 Parran Hall, 130 DeSoto St., Pittsburgh, PA 15261. Phone: (412) 624-3137. Fax: (412) 624-2256. E-mail:
lharriso{at}edc.pitt.edu.


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Journal of Clinical Microbiology, February 2006, p. 374-377, Vol. 44, No. 2
0095-1137/06/$08.00+0 doi:10.1128/JCM.44.2.374-377.2006
Copyright © 2006, American Society for Microbiology. All Rights Reserved.
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