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Journal of Bacteriology, May 2000, p. 2928-2936, Vol. 182, No. 10
0021-9193/00/$04.00+0
Copyright © 2000, American Society for Microbiology. All rights reserved.
Multiple-Locus Variable-Number Tandem Repeat Analysis Reveals
Genetic Relationships within Bacillus anthracis
P.
Keim,1,*
L. B.
Price,1
A. M.
Klevytska,1
K. L.
Smith,1,2
J. M.
Schupp,1
R.
Okinaka,3
P. J.
Jackson,3 and
M.
E.
Hugh-Jones2
Department of Biological Sciences, Northern Arizona
University, Flagstaff, Arizona 86011-56401;
Department of Epidemiology and Community Health, School of
Veterinary Medicine, Louisiana State University, Baton Rouge, Louisiana
70803-84042; and Environmental Molecular
Biology Group, Los Alamos National Laboratory, Los Alamos, New Mexico
875453
Received 6 December 1999/Accepted 24 February 2000
 |
ABSTRACT |
Bacillus anthracis is one of the most genetically
homogeneous pathogens described, making strain discrimination
particularly difficult. In this paper, we present a novel molecular
typing system based on rapidly evolving variable-number tandem repeat (VNTR) loci. Multiple-locus VNTR analysis (MLVA) uses the combined power of multiple alleles at several marker loci. In our system, fluorescently labeled PCR primers are used to produce PCR amplification products from eight VNTR regions in the B. anthracis
genome. These are detected and their sizes are determined using an
ABI377 automated DNA sequencer. Five of these eight loci were
discovered by sequence characterization of molecular markers
(vrrC1, vrrC2,
vrrB1, vrrB2, and CG3),
two were discovered by searching complete plasmid nucleotide sequences
(pXO1-aat and pXO2-at), and one was known previously (vrrA). MLVA characterization of 426 B. anthracis isolates identified 89 distinct genotypes. VNTR markers
frequently identified multiple alleles (from two to nine), with Nei's
diversity values between 0.3 and 0.8. Unweighted pair-group method
arithmetic average cluster analysis identified six genetically distinct
groups that appear to be derived from clones. Some of these clones show
worldwide distribution, while others are restricted to particular
geographic regions. Human commerce doubtlessly has contributed to the
dispersal of particular clones in ancient and modern times.
 |
INTRODUCTION |
Anthrax is a disease that has
plagued mankind for millennia. The earliest suspected reports occur in
Sanskrit manuscripts and in the biblical book of Exodus
(4). More recently, anthrax played an important role in the
advancement of modern microbiology with the development of Koch's
postulates and of the first vaccine using an attenuated bacterial
strain (12, 16). While anthrax currently affects mostly
livestock and wildlife around the world, it can and does kill humans
(4). Indeed, the great current interest in anthrax is due to
its potential as a bioterrorism and biowarfare agent (3, 4).
Bacillus anthracis spores can remain stable for decades and
can be readily packaged into biological weapons (3). This
same longevity may greatly influence the ecology and evolution of this
pathogen. The initiating spores for an anthrax outbreak may emanate
from a single long-deceased victim. This resting stage probably greatly
reduces the rate of evolutionary change, and this may contribute to the
extremely homogeneous nature of B. anthracis
(10).
Numerous studies have demonstrated the lack of molecular polymorphism
within B. anthracis (6, 7, 10). Previous analyses using amplified fragment length polymorphisms (AFLP) revealed only 30 differences among >1,000 DNA fragments (10). In addition, many of these AFLP markers have low diversity values and little discriminatory power. Comparative analysis of the protective antigen gene sequence in 25 diverse strains found only five differences across
2,500 nucleotides (18). An exception to this trend was revealed by the work of Andersen et al. (1), who sequenced a
previously identified arbitrarily primed PCR marker (7). They found the vrrA open reading frame (ORF), which
contained a variable-number tandem repeat (VNTR) sequence. In contrast
to the extremely monomorphic nature of the genome, five different allelic states were observed in the vrrA VNTR among diverse
strains (1, 7, 8). This demonstrated that even highly
similar B. anthracis strains could be differentiated if
polymorphic genomic regions could be identified and analyzed. Such
discrimination is essential if molecular epidemiology is to aid in the
understanding and control of anthrax.
Molecular typing of pathogens has long been a part of pathogen
identification and control and has recently been accelerating with new
technologies. Traditionally, serotyping has been extremely valuable and
has often been able to identify important cellular components
associated with virulence. While serotyping will continue to be an
important tool, it often has limited discriminatory power, resolving
pathogens into only a few types. Multilocus enzyme electrophoresis provides a multiple-factor genetic analysis, with as many as 40 genetic
loci analyzed (2). Moreover, enzyme loci frequently have
more than two alleles, providing increased genetic resolution per
locus. However, DNA typing is more rapid and less expensive and has an
even greater capacity for genetic dissection of bacterial pathogens. It
is limited only by the genome size and the technology. Because most
microbial genomes consist of millions of nucleotides, technology is
invariably limiting. Pulsed-field gel electrophoresis (PFGE) can
resolve very large and sometimes polymorphic DNA restriction fragments.
PFGE typing has proven generally applicable to many pathogens and has
notable successes in epidemiological tracking (14). However,
this is a cumbersome technology that cannot easily handle very large
sample sets. Moreover, PFGE data sets are not easily standardized for
transfer throughout the public health community. Ribotyping uses
restriction fragment length polymorphisms associated with rRNA genes
(17) and, again, is generally applicable to all bacteria.
However, it is limited by the number of ribosomal loci in the genome.
Such methods often do not distinguish among closely related species,
and many strains within a species show identical patterns (e.g.,
Bacillus cereus and B. anthracis).
Recently, PCR-based methods have become increasingly important to
molecular typing efforts. These approaches include AFLPs, repetitive
element polymorphisms-PCR, randomly amplified polymorphic DNA, and
arbitrarily primed PCR (24, 26, 27). The power of PCR-based
methods is the ease with which they can be applied to many bacterial
pathogens and their multilocus discrimination. These methods have
proven valuable for genetic dissection of pathogens for which other
approaches have failed. However, a limitation of many PCR-based
approaches is the biallelic (binary) nature of their data, frequently,
the presence or absence of a marker fragment. Finally, comparative gene
sequencing is becoming feasible for strain characterization and can be
performed at multiple loci. In its best applications, multiple-locus
sequence typing (MLST) can provide data for multiple alleles
(haplotypes) spread across dispersed genomic locations (13).
Nucleotide data are well understood, standardized into four defined
categories, and easily analyzed using phylogenetic approaches. If
sufficient nucleotide diversity is present, MLST can distinguish among
both species and strains. While routine clinical MLST is still
unfeasible, hybridization arrays (e.g., chip technology) could make
single-nucleotide polymorphisms a mainstream approach to pathogen
typing in the future (22).
One of the most recent developments in molecular typing involves the
analysis of VNTR sequences (5, 11, 23). Short nucleotide
sequences that are repeated multiple times often vary in copy number,
creating length polymorphisms that can be detected easily by PCR using
flanking primers. VNTRs appear to contain greater diversity and, hence,
greater discriminatory capacity than any other type of molecular typing
system (19, 23). Many bacteria have VNTRs, although
development of the PCR primers for these markers is specific to each
pathogen. In this report, we describe a multiple-locus VNTR analysis
(MLVA) system that uses eight marker loci to discriminate among
different B. anthracis isolates. Five of these markers
(vrrC1, vrrC2,
vrrB1, vrrB2, and CG3)
were identified by the nucleotide sequence characterization of B. anthracis AFLP markers (10). One marker
(vrrA) was identified previously (1), and two
were identified by analysis of the pXO1 and pXO2 plasmid sequences
(pXO1-aat and pXO2-at) (14). Because of the nearly
monomorphic molecular nature of B. anthracis, MLVA may be
the only reasonable method with which to study the diversity,
evolution, and molecular epidemiology of this pathogen. Our analysis of
a worldwide B. anthracis collection reveals 89 distinct MLVA
genotypes that cluster into about six major genetic groups that
represent worldwide clones.
 |
MATERIALS AND METHODS |
DNA preparation.
In this study, we have analyzed 426 B. anthracis isolates from around the world (Table
1). These samples include previously described samples (8, 10) plus more than 300 additional
clinical and environmental isolates (Table 1). DNA from each isolate
was obtained by either large-batch procedures (8, 10) or a
greatly simplified approach requiring only heat lysis of a single
colony. In this abbreviated protocol, B. anthracis cells
were streaked onto blood agar plates and then incubated at 37°C
overnight. A single colony from each plate was transferred into a
microcentrifuge tube containing 200 µl of TE (Tris-HCl [pH 8.0],
1.0 mM EDTA). The colony was resuspended by vortexing or repetitive
pipetting. The cellular suspension was heated to 95°C for 20 min and
then cooled to room temperature. Cellular debris was removed by
centrifugation at 15,000 × g for 1 min. Centrifugation
was conducted inside a biosafety cabinet to contain any aerosols. The
supernatant was then transferred to a new tube for storage. One
microliter of the lysate contains sufficient template to support a
single PCR, which means that this procedure can supply template for 200 reactions. We periodically optimize our reactions by titrating the heat
lysate template concentrations using serial dilutions. Results obtained using either DNA preparation protocol gave the same MLVA results. However, the heat lysis procedure is much more rapid and easily adapted
to large-scale processing of samples and was the method used for most
of the samples in this study.
MLVA PCR.
MLVA reaction primers (Table
2) were designed to provide uniquely
labeled or sized amplicons for every allele at the eight VNTR loci. PCR
amplification of all eight VNTR loci was routinely accomplished using
four reactions. Two of the amplicons (vrrC1 and
vrrC2) are significantly larger than the others
and, in addition, are amplified using partially complementary primers.
Likewise, vrrB1 and vrrB2
are amplified using complementary primers. Limited unique sequences in
these repeated regions necessitated the overlap of these primers and
thus required these amplicons to be divided into separate PCRs. Large
amplicons tend to be outcompeted by small amplicons and thus require
separate PCRs. These restraints led to a four-reaction design in which
vrrB1 is grouped with CG3 and vrrA,
vrrB2 is grouped with pXO1-aat and pXO2-at,
vrrC1 is amplified alone, and
vrrC2 is amplified alone.
Reaction 1 contained 1× PCR buffer (20 mM Tris-HCl [pH 8.4], 50 mM
KCl); 2 mM MgCl
2; the four deoxynucleoside triphosphates
(dNTPs; 0.2 mM each); 0.04 U of Platinum
Taq DNA polymerase
(Gibco-Life
Technologies) per µl; 0.1 µM CG3-F1 and CG3-R1; 0.2 µM each
vrrA-F1,
vrrA-R1,
vrrB1-F1, and
vrrB1-R1;
and 0.04 to 0.2 ng of template
DNA per µl or simply 1 µl of the
single-colony
lysate.
Reaction 2 contained 1× PCR buffer; 4 mM MgCl
2; dNTPs (0.2 mM each); 0.04 U of Platinum
Taq DNA polymerase per µl;
0.4 µM
each
vrrB2-F1,
vrrB2-R1, pXO1-aat-F1, pXO1-aat-R1, pXO2-at-F1,
and pXO2-at-R1; and 0.04 to 0.2 ng of template DNA per µl or simply
1 µl of the single-colony
lysate.
Reaction 3 contained 1× PCR buffer; 2 mM MgCl
2; dNTPs (0.2 mM each); 0.04 U of Platinum
Taq DNA polymerase per µl;
0.2 µM
each
vrrC1-F1 and
vrrC1-R1; and 0.04 to 0.2 ng of template DNA
per
µl or simply 1 µl of the single colony
lysate.
Reaction 4 contained 1× PCR buffer; 2 mM MgCl
2; dNTPs (0.2 mM each); 0.04 U of Platinum
Taq DNA polymerase per µl;
0.2 µM
each
vrrC2-F1 and
vrrC2-R1; and 0.04 to 0.2 ng of template DNA
per
µl or simply 1 µl of the single-colony
lysate.
The PCR thermocycling program for all four reactions was identical.
Once the reactions were assembled, they were raised to
94°C for 5 min
to activate the DNA polymerase. Thereafter, each
temperature cycle was
94°C for 20 s, 60°C for 20 s, and 65°C for
20 s.
These three steps were repeated 34 times. The final step
was at 65°C
for 5
min.
Automated genotype analysis.
The MLVA PCR products were
electrophoretically analyzed with a Perkin-Elmer Applied Biosystems 377 automated fluorescent DNA sequencer (Fig.
1). The four reactions were mixed in
equal amounts prior to electrophoretic analysis, which provides
relatively equal fluorescent signal from each amplicon. Genescan and
Genotyper software packages (Perkin-Elmer, ABI) were used to analyze
the gel images. Custom macro programs (available upon request)
associated with Genotyper allow the automated scoring of alleles.

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FIG. 1.
Electrophoretic analysis of MLVA fragments from
different B. anthracis isolates. Fluorescent image of an
ABI377 electrophoresis gel containing amplification products from 45 different B. anthracis isolates. All eight VNTR loci are
present in each lane. Each marker allele is a unique size and color
combination, allowing easy identification of similar-sized fragments
from different alleles. The 48 isolates were chosen randomly from the
worldwide diversity set shown in Table 1. Sizes are shown in bases.
|
|
The apparent electrophoretic size of DNA fragments is not always
exactly the same as the size determined by DNA sequencing.
This could
be due to DNA conformational differences, 3' adenine
addition by the
polymerase, migrational deviations of the size
standard, or mass
asymmetry between the amplicon strands that
affect the comparison with
the single-stranded standards. We have
determined the actual nucleotide
sequence of most marker alleles
by DNA sequencing and report these
values in all cases. These
differences are usually only one or two
nucleotides, but we recommend
the use of standard genotypes selected
from Fig.
2 as references.

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FIG. 2.
MLVA-based dendrogram and genotype scores. The
eight VNTR marker loci were used to calculate a simple matching
coefficient among all 89 unique MLVA genotypes. UPGMA cluster analysis
was performed to identify groups of similar genotypes from the
worldwide collection. The genetic distance is presented as the absolute
number of differences in marker alleles among genotypes. The amplicon
sizes presented are based upon nucleotide sequence determinations using
the primers listed in Table 2. Country abbreviations are defined in
Table 1. The vaccine strains Sterne, STI-1, and V770-NP1 are lacking
the pXO2 plasmid marker and were not included in the cluster analysis.
However, we have annotated the data set (see Geographical [Geo.]
Region column) to indicate where these important strains match other
genotypes based on analysis using seven marker loci. STI-1 did not
match any of the genotypes but is related to the cluster A1.a isolates
(see text for details). In addition, we have labeled the genotypes of
the well-known strains Ames and Vollum. Marker alleles are presented as
their sizes in nucleotides. The vrrA allele 313 corresponds
to VNTR4 described previously (7, 8). G,
genotype number; N, no. of isolates.
|
|
Data analysis.
Only genotypes generating
data from all eight markers were included in these analyses. About 5%
of the samples examined were missing one or both virulence plasmids,
which precludes complete genotyping with this MLVA system. This
includes the commonly used vaccine strains that lack the pXO2 plasmid.
These important strains are annotated on Fig. 2 next to their
seven-marker genotypic matches. Analysis of the raw genotype scores was
accomplished by using a phenetic approach, unweighted pair group method
arithmetic average (UPGMA) cluster analysis (26). UPGMA
cluster analysis was performed with PAUP 4.0 (20) with a
simple matching coefficient to estimate genetic differences. Individual
marker diversity (D) was calculated as equal to 1
(allele frequency)2 (25) and based upon
allele frequencies in the 89 distinct B. anthracis
genotypes, not the complete 426-isolate collection.
 |
RESULTS |
MLVA.
We have developed an MLVA approach for molecular typing
of B. anthracis strains. The system presented here uses
eight genetic loci that provide high levels of discrimination among
different isolates. These marker loci were identified by DNA sequencing of variable AFLP marker fragments (CG3, vrrB1,
vrrB2, vrrC1, and vrrC2), examination of virulence plasmid
sequences (pXO2-at and pXO1-aat), and from the previously described
vrrA VNTR locus (1). Five of the eight MLVA
markers (vrrA, vrrB1,
vrrB2, vrrC1, and vrrC2) are found in ORFs and variation in repeat
number does not affect the translational reading frame (data not
shown). The pXO1 and pXO2 VNTR markers allow monitoring for the
presence or absence of the plasmids as well as for plasmid-based
variation. This plus-minus assay provides important information about
virulence because the lack of either plasmid attenuates a B. anthracis strain (21). Phylogenetic comparison of
nucleotide variation did not detect natural horizontal transfer among
strains (18), suggesting that plasmid and chromosomal
evolution in B. anthracis has been generally congruent.
While no effort was made to make the MLVA primers specific to
B. anthracis templates, most sets will not support amplification
from
other bacterial species. A limited number of
B. cereus and
Bacillus thuringiensis strains have been examined using the
standard
reaction conditions; at most a couple, and frequently none, of
the markers were amplified in reactions containing these templates
(data not shown). The
vrrA locus amplified most often in
other
species, but the resulting allele sizes did not correspond to
any
of the five alleles observed in
B. anthracis isolates. These
Bacillus species are the most closely related to
B. anthracis.
Therefore, this MLVA system represents a credible
method of identifying
B. anthracis as well as determining
what strain type is
present.
B. anthracis genotypes.
We used MLVA to
characterize 426 B. anthracis isolates from diverse
geographic locations. This analysis divided them into 89 MLVA genotypes
(Fig. 2). It is clear that multiple isolates from the same anthrax
outbreak frequently have identical genotypes. This reduces the number
of distinguishable isolates relative to the total number of samples. In
addition, many genotypes are found at multiple locations, especially
within a restricted geographical region. The number of distinct
genotypes collected from particular countries is reported in Table 1.
The distribution may be more a function of isolate availability for
this study than intrinsic diversity within a limited geographic area,
so it is difficult to draw conclusions from these numbers. However,
multiple genotypes are observed in all regions for which a large
collection of samples are available. The Australian collection is
heavily biased by 28 samples from the short 1997 Victoria outbreak. All
of these are one genotype. The restricted nature of the collection may therefore explain the lack of multiple genotypes discovered to date in Australia.
VNTR marker diversity.
The discriminatory power of each MLVA
marker can be estimated by the number of alleles it detects and by its
diversity. These two simple descriptive statistics were determined
using only the 89 B. anthracis genotypes to minimize the
effect of sampling on allele frequency (Table
3). The isolate collection is biased towards numerous samples from easily accessed B. anthracis
collections. This could unduly influence allele frequencies. MLVA
markers average over five alleles per locus, with a range of from two
to nine alleles (Table 3). The diversity index (D) is based
on the number of alleles and the allele frequency. This provides a
better measure of discriminatory power than allele number
(25). MLVA markers have an average diversity of 0.54, with a
range of 0.30 to 0.80. Note that vrrB1 has the
lowest diversity (0.30) in spite of having five alleles, whereas CG3
detects only two alleles but has a diversity index of 0.38. The two
plasmid-based markers have the highest diversity and greatest number of
alleles, perhaps due to the simple sequence nature of their repeats
(Table 3).
While most of the
B. anthracis allelic variation observed in
this study is consistent with the repeat unit size, some alleles
contain fractions of a repeat. The nucleotide structures found
in
vrrA,
vrrB, and
vrrC have evolved from
simpler trinucleotide
repeats, and remnants of these structures still
exist within each
repeat (
1; unpublished data). No
fractional-size alleles were
observed for
vrrA or
vrrB among the different
B. anthracis strains,
but we did observe several for the
vrrC markers. Nucleotide
sequencing
determined that these were due to insertion or deletion
events
within the subrepeats (see the
vrrC2
alleles in genotypes 8 and
9, Fig.
2).
B. anthracis genetic relationships.
UPGMA cluster
analysis reveals major genetic affiliations among the MLVA genotypes
(Fig. 2). Six major clusters are apparent that may represent older
clonal separations in the evolutionary history of this species. Similar
major groups were identified by AFLP marker analysis (10),
most of which were independent of the MLVA markers in this study.
The most obvious separation in the dendrogram is the split between the
A and B genotypes (Fig.
2). The B cluster contains
approximately 12%
of the isolates and genotypes in this study.
Cluster B is further
subdivided into two groups, B1 and B2. Southern
African isolates
dominate (93%) group B1 and far outnumber the
samples found in group
B2. Only two genotypes are present in the
B2 group. These are rare and
collected exclusively in Europe.
The B2 group is only tentatively
associated with the B1 subgroup,
as other analytical approaches (e.g.,
maximum parsimony) place
B2 loosely with the A cluster (data not
presented). All B genotypes
are uncommon in much of the world, yet
genotype 87 (Fig.
2) is
an important contributor to the ongoing anthrax
outbreak in Kruger
National Park (K. L. Smith, V. DeVos, H. Bryden, M. E. Hugh-Jones,
L. B. Price, A. Klevytska, D. T. Scholl, and P. Keim, unpublished
data).
Members of the A cluster are found worldwide and can be subdivided into
at least four groups (Fig.
2). Isolates in the A1
cluster are found
throughout the world, but they dominate the
western North America
collection. The most common A1 genotypes
are geographically distributed
from the Canadian Wood Bison National
Park (genotypes 3 and 5) to
southern Texas in the United States
(genotype 6). The CG3 marker locus
represents a defining diagnostic
marker for the A1.a group, as the
153-bp allele is only found
in this group. This marker locus consists
of a five-nucleotide
sequence present in two copies in most strains,
but only once
in isolates found in cluster A1.a. This difference may
not be
readily reversible, and all allelic contrasts may be due to a
single evolutionary event. While STI-1 was not included in the
UPGMA
analysis due to its lack of the pXO1 plasmid, it most closely
resembles
members of the A1.a group. As the sole representative
from Russia in
this study, it did not exactly match any of the
89 genotypes with its
seven markers. However, it is clearly related
to isolates from the A1.a
cluster. STI-1 marker alleles (Fig.
2, allele sizes = 313, 229, 162, 613, 604, 153, 129,

) matched
six of seven markers for 11 different genotypes in A1.a. In addition,
STI-1 contains the CG3 153 allele that is only present in A1.a
isolates. The close genetic
relationship between the western North
American isolates and this
single Russian representative needs
further research and would benefit
significantly from examination
of additional Russian isolates. The A1.b
cluster isolates occur
most commonly in Africa and only rarely in other
parts of the
world.
The A2 branch is represented by a single isolate from Pakistan. It is
distinct from other genotypes and may represent a
B. anthracis that is common in this undersampled
region.
The A3 cluster is perhaps the single most important
B. anthracis group due to its wide distribution and prevalence. This
highly
diverse cluster contains 44% of the genotypes (39 of 89) and
58%
of the isolates (260 of 419) examined in this study (Fig.
2).
Genotypes in this group are involved in some of the largest outbreaks
that we have examined: Kruger National Park (genotype 67); Victoria,
Australia (genotype 66); Turkey (genotype 35); and southern Africa
(genotypes 30 and 40). Genotypes matching the well-known vaccine
strains V770-NPR (genotypes 45, 46, and 49) and Sterne (genotypes
59 and 61) are also found in this cluster. The well known and
highly
virulent strain Ames (genotype 62) is found in A2 and is
similar to
Sterne at most marker alleles. The Ames strain played
a central role in
the United States biological warfare program
before it was dismantled
(David Huxsoll, personal
communication).
The A4 cluster is distinct and yet underrepresented in our current
collection (Fig.
2). It is notable primarily for the well-known
strain
Vollum (genotype 77), which was used in the British biological
warfare
program (Peter Turnbull, personal communication). Vollum
has been
studied in many laboratories, and most of the 15 isolates
identical to
genotype 77 are from laboratory archival collections.
One sample of the
Vollum 1B strain differed at the
vrrA markers
by one repeat
from other Vollum samples. This seemingly represents
an
"in-laboratory" mutational event. A natural isolate matching
the
Vollum genotype was collected in Spain. Other closely related
isolates
have been found in the United States, Norway, Europe,
and Asia but not
in
Africa.
 |
DISCUSSION |
The MLVA typing method presented in this paper represents a robust
and easily transferable approach to characterizing B. anthracis isolates. The protocols presented are rapid and require
only crudely isolated DNA to provide high-resolution molecular typing
analysis. The individual marker alleles are uniquely identified by a
combination of size and fluorescent color. Therefore, automated gel
analysis is routine. Instrumentation and software to perform MLVA are
widely available with the exception of the custom macro software that will be provided by the authors upon request. Standardized data are
presented in this report to provide a uniform reference to all anthrax
research teams (Fig. 2). Future analyses by any laboratory in the world
can be easily compared to the standardized data and particular strains
(Table 4) reported here. We hope that the availability of PCR primers, protocols, and a reference data set will
encourage anthrax research teams to use a common genetic typing system
and to share their results. In the future, combinations of data sets
from around the world will lead to novel and comprehensive insights
into anthrax biology.
Molecular typing in many pathogenic bacterial species is accomplished
without focusing on hypervariable VNTR loci. In B. anthracis, however, this has proven extremely difficult due to the
homogeneous nature of all available strains (10). In this
pathogen, only the most rapidly evolving genomic regions are useful for
strain discrimination. VNTR loci fall into this category and have been used successfully in this study to separate B. anthracis
isolates into 89 distinct genotypes. As a first approximation, one can assume that the diversity of a particular VNTR is correlated with its
evolutionary rate, and in the absence of selective constraints, this
would be the mutation rate. In this study, the simple di- and
trinucleotide tandem repeats (pXO1-aat and pXO2-at) are the most
diverse, while complex longer repeats have lower diversity (Table 3).
Slip strand repair mutations by DNA polymerase are thought to occur
more frequently on short repeats (23), and our data are
consistent with this model. Markers of higher diversity obviously
provide great discriminatory power among strains. However, it is less
obvious that highly diverse markers have less power for defining older
evolutionary relationships. Our MLVA markers have different diversity
levels and contribute in different ways to the analysis of B. anthracis.
VNTR mutation rates are apparently fast on an evolutionary scale but
slow enough that mutations are very difficult to observe in the
laboratory. We have passaged a plasmid-cured strain of Ames for more
than 100,000 generations and observed only a single VNTR mutation (313 to 301) in vrrA (G. Zinser and P. Keim, unpublished observations). At least in the six chromosomal loci, marker alleles appear stable to routine and even long-term handling in the laboratory. As stated above, variation in different Vollum strain (genotype 77)
accessions illustrates the stability of these markers. There are 15 different Vollum examples in this study from different sources in the
United States and the United Kingdom. One of these was passaged three
times through rats and three times through rabbit hosts without MLVA
changes. The only difference was observed in the vrrA marker
(301 instead of 289) for the substrain Vollum 1B. These anecdotal and
preliminary results need additional confirmation but suggest that VNTR
mutation rates are slower than 10
5 and that mutational
changes occur in single-repeat steps.
The existence of a limited number of B. anthracis clones can
be hypothesized from the genetic similarities observed within each of
the six major clusters in Fig. 2. The number and distribution of these
hypothesized clones have doubtlessly been influenced by human activity.
This may have started with domestication of animals but continues
through modern-day international commerce. Note that not all of the
putative clones are equally widespread. For example, the A3 cluster is
very common and distributed across many continents, while the B1
cluster is restricted mostly to southern Africa. The A1 cluster splits
into two distinctive groups, with one branch primarily North American
(A1.a) and one mostly African (A1.b). These differences in cluster
prevalence and distribution may be influenced by inherent biological
properties (Smith et al., unpublished data) or just due to stochastic
historical events.
While the biological significance of B. anthracis VNTR
variation is unknown, some VNTR variation examples have pronounced effects on pathogen biology (23). Five of the eight MLVA
loci in the MLVA system are found in ORFs (data not presented).
Therefore, VNTR variation could easily affect the bacterial phenotype
via altered translational products. Moreover, it has also been shown that extragenic VNTRs can influence adjacent gene expression
(23). This provides a possible genetic role for even
intergenic VNTRs. Given the extreme homogeneity of B. anthracis, VNTRs represent the only significant source for
molecular variation among the strains known at this time. Whether this
variation is biologically significant or only useful for diagnostic
analysis of B. anthracis will be determined by future VNTR studies.
 |
ACKNOWLEDGMENTS |
This work was supported by funding from the U.S. Department of Energy
(NN20-CBNP), the National Institutes of Health (RO1 GM60795), and the
Cowden Endowment in Microbiology.
We thank Ms. Karen Hill, Debra Adair, Guenevier Zinser, and A. S. Kalif for excellent technical assistance. In addition, this research
would have been impossible without the help and unstinting generosity
of many people across the world who provided us with cultures from
outbreaks and from their collections; we are extremely grateful for
their patience and contributions: Argentina
Dept. Bacteriologia
General, GELAB/SENASA, Buenos Aires (Luis Betancor). Australia
Elizabeth MacArthur Agricultural Institute, New South Wales
(Michael Hornitzky); Princess Alexandria Hospital, Queensland (Jacqueline Harper); Yeerongpilly Veterinary Laboratory, Queensland (Rod Thomas); Department of Natural Resources & Environment, Victoria (Andrew Turner and Maria Yates). Canada
Animal Diseases Research Institute, Alberta (Jack Burchak and Greg Tiffin). China
Institute of
Epidemiology & Microbiology, Changping (Xudong Liang). France
Institut Pasteur, Paris (Michelle Mock); Hôpital du Bocage, Dijon (C. Neuwirth). Germany
Institut für Umwelt und Tierhygiene Sowie Tiermedizin mit Tierklinik, Stuttgart (Reinard Bohm).
Hungary
Veterinary Medical Research Institute, Budapest (Bela Nagy).
India
Christian Medical College & Hospital, Tamil Nadu (M. K. Lalitha). Indonesia
Research Institute for Veterinary Science, Bogor
(Sjamsul Bahri). Italy
Instituto Zooprofilattico Sperimentale, Terama
(Vincenzo Caporale). Korea
Department of Microbiology, National
Institutes of Health, Seoul (Ho-Hoon Kim). Mozambique
Instituto
Nacional de Veterinaria, Maputo (Sara Acha). Namibia
Directorate of
Resource Management, Windhoek (Pauline Lindeque). Nepal
National
Zoonoses & Food Hygiene Research Centre, Kathmandu (D. D. Joshi).
Norway
Central Veterinary Laboratory, Oslo (Finn Saxegaard).
Pakistan
Veterinary Research Institute, Lahore (Shabbir Ahmad).
Poland
Wojskowy Instytut Higieny, Pulawy (Jerzy Mierzejewski).
Portugal
Regional Veterinary Diagnostic Laboratory, Evora (Patricio
Nuncio and Armando Louzo). South Africa
Kruger National Park (Helena
Bryden and Valerius de Vos); Onderstepoort Biological Products (Huck
Jager); Onderstepoort Veterinary Institute (Maryke Henton).
Tanzania
Department of Veterinary Microbiology & Parasitology, Sokoine
University of Agriculture (Saddrudin Jiwa). Thailand
Department of
Livestock Development, Bangkok (Vichitr Sukhapesna). Turkey
Enstitusu
Muduriugu, Ankara (Metin Kerman); Infeksiyon Hastaliklari Klinigi,
Erciyes Universitesi, Kayseri (Mehmet Dogany). United Kingdom
Centre
for Applied Microbiology & Research, Porton (Peter Turnbull); DERA,
Porton (Tony Philipps and Richard Manchee). USA
California Veterinary
Diagnostic Laboratory System, California (Richard Walker); Centers for
Disease Control & Prevention, Georgia (Rob Weyant); United States Army
Medical Research Institute for Infectious Diseases, Maryland (Art
Friedlander and John Ezzell); Veterinary Diagnostic Services, NM Dept
of Agriculture, New Mexico (Linda Nims); Veterinary Diagnostic
Laboratory, NDSU, North Dakota (David White); Animal Disease Diagnostic
Laboratory, Oklahoma (Ronald Welsh); Animal Disease Research & Diagnostic Laboratory, SDSU, South Dakota (David Zeman); Texas
Veterinary Medical Diagnostic Laboratory, Texas (Howard Whitford).
Zimbabwe
Veterinary Research Laboratory, Causeway (U. Ushewokunze-Obatolu). Zambia
Central Veterinary Laboratory, Lusaka
(P. M. Muyoyeta).
 |
FOOTNOTES |
*
Corresponding author. Mailing address: Department of
Biological Sciences, Northern Arizona University, Flagstaff, AZ
86011-5640. Phone: (520) 523-1078. Fax: (520) 523-0639. E-mail:
Paul.Keim{at}nau.edu.
 |
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Journal of Bacteriology, May 2000, p. 2928-2936, Vol. 182, No. 10
0021-9193/00/$04.00+0
Copyright © 2000, American Society for Microbiology. All rights reserved.
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