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Journal of Clinical Microbiology, October 2000, p. 3780-3784, Vol. 38, No. 10
0095-1137/00/$04.00+0
Copyright © 2000, American Society for Microbiology. All rights reserved.
Bacillus anthracis Diversity in Kruger
National Park
K. L.
Smith,1,2,*
V.
DeVos,3
H.
Bryden,3
L. B.
Price,1
M. E.
Hugh-Jones,2 and
P.
Keim1
Department of Biological Sciences, Northern
Arizona University, Flagstaff, Arizona
86011-56401; Scientific Services,
Kruger National Park, South African National Parks, Skukuza 1350, South
Africa3; and Department of
Epidemiology and Community Health, School of Veterinary Medicine,
Louisiana State University, Baton Rouge, Louisiana
70803-84042
Received 19 May 2000/Returned for modification 5 August
2000/Accepted 15 August 2000
 |
ABSTRACT |
The Kruger National Park (KNP), South Africa, has a recorded
history of periodic anthrax epidemics causing widespread disease among
wild animals. Bacillus anthracis is the causative agent of
anthrax, a disease primarily affecting ungulate herbivores. Worldwide
there is little diversity among B. anthracis isolates, but examination of variable-number tandem repeat (VNTR) loci has identified six major clones, with the most dissimilar types split into the A and B branches. Both the A and B types are found in southern
Africa, giving this region the greatest genetic diversity of B. anthracis worldwide. Consequently, southern Africa has been hypothesized to be the geographic origin of B. anthracis.
In this study, we identify the genotypic types of 98 KNP B. anthracis isolates using multiple-locus VNTR analysis. Two major
types are evident, the A branch and the B branch. The spatial and
temporal distribution of the different genotypes indicates that anthrax epidemic foci are independent, though correlated through environmental cues. Kruger B isolates were found on significantly higher-calcium and
higher-pH soils than were Kruger type A. This relationship between
genotype and soil chemistry may be due to adaptive differences among
divergent anthrax strains. While this association may be simply
fortuitous, adaptation of A types to diverse environmental conditions
is consistent with their greater geographic dispersal and genetic dissimilarity.
 |
INTRODUCTION |
Bacillus anthracis is a
gram-positive, rod-shaped, spore-forming bacterium. It is the causative
agent of anthrax, a disease primarily affecting ungulate herbivores,
occasionally carnivores, and less frequently humans (14).
Anthrax is a disease well documented in human history with suggestive
reports even in the Bible and Sanskrit manuscripts (5). The
field of microbiology was revolutionized by the anthrax studies of
Koch, Pasteur, and others (13). Though anthrax was never
eradicated, the development of an effective animal vaccine has reduced
its importance for humans and animals in developed countries over the
last century. Recently, however, anthrax research has been increasingly
important due to this pathogen's central position in biological
warfare and biological terrorism (6).
It is generally thought that B. anthracis is an obligate
pathogen and that little propagation occurs in soil (2, 4, 10). With the exception of scavengers, anthrax is almost never transmitted directly from victim to victim but is rather ingested by
herbivores while grazing or browsing. In such a model, the environmental spore reservoir becomes very important to the ecology and
evolution of this pathogen. Survival in the soil is crucial for
initiating subsequent anthrax epidemics, and these relatively long
periods of quiescence may greatly reduce evolutionary change. Thus, any
adaptive mutation altering spore survival will be under great
selection. Differential environmental selection will lead to the most
rapid adaptive changes in this pathogen.
Worldwide there is little diversity among B. anthracis
isolates, but examination of variable-number tandem repeat (VNTR)
loci has identified six major clones (9). The low diversity
among these clonal lineages is consistent with a slowly evolving
organism or one that recently derived from a common ancestor. The most dissimilar types are split into two major groups (A and B). Type A
strains are found around the world and are responsible for most epidemics and outbreaks. In contrast, type B strains are almost exclusively restricted to southern Africa. It is possible that one or
more adaptations allowed the greater geographic range (and diversity)
of type A, or the loss of adaptations has restricted type B. Both A and
B are found in southern Africa, giving this region the greatest genetic
diversity of B. anthracis worldwide. Consequently,
southern Africa has been hypothesized to be the geographic origin
of B. anthracis (7).
Southern Africa has experienced many anthrax epidemics in the past
(1). The wide expanses of savannah and large populations of
wild ungulate herbivores are ideally suited for anthrax endemicity. Vestiges of the large wildlife populations and savannah ecosystems still exist today in the parks of southern Africa. One such area is the
Kruger National Park (KNP), South Africa.
The KNP has a recorded history of periodic anthrax epidemics
(3). There are areas within the KNP known to be anthrax
foci, where epidemics have been observed to begin. Two regions, the northernmost tip of the park (since 1959) and the central region (since
1990), are most notable, although the entire KNP region may be affected
during an epidemic. Previous investigations (8, 9, 11) show
that both A and B isolates occur in the KNP. Because of the close
proximity of these different types, the KNP provides a unique
opportunity to characterize B. anthracis in an ecological
setting and examine possible environmental associations specific to the
genotypic groups. In this study, we identified the genotypes of
98 KNP B. anthracis isolates using multiple-locus VNTR
analysis (MLVA) (9). Two major types were evident, branch A
and branch B. The spatial and temporal distribution of the
different genotypes indicates that anthrax epidemic foci are
independent, though correlated through environmental cues. Soil
chemistry (calcium and pH) differs among outbreak foci, as does the
genotypic composition. The relationship between genotype and soil
chemistry may be due to adaptive differences among divergent anthrax strains.
 |
MATERIALS AND METHODS |
Study site, B. anthracis isolates, and soil
parameters.
The KNP is an elongated conservation area consisting
of almost 2,000,000 ha of subtropical savannah woodland from 20°19'
to 25°32' S and 31°0' to 32°0' E, situated in the
northeasternmost corner of the Republic of South Africa. The eastern
border of the park adjoins Mozambique; the northern border adjoins
Zimbabwe. The entire area is enclosed with gameproof fencing and
adjoins commercial farms, traditional communal grazing areas, and
private nature reserves. The KNP contains approximately 2,300 kg of
biomass of large mammals per km2, made up of 20 different
species. The B. anthracis isolates selected for this study
were isolated within the park. The 98 isolates in the study range in
date of isolation from 1970 to 1997. The sources of isolates were
animal carcasses, soil, bone, water, dung, and diagnostic blood smears
taken in the field. The soil pH and calcium values from the site of
isolation were determined by reference to soil survey data collected
previously (15).
MLVA.
The MLVA strain typing procedure is described in
detail elsewhere (9). Briefly, a single colony of B. anthracis was "heat lysed" in TE buffer (10 mM Tris [pH
8.0], 1 mM EDTA) at 95°C for 20 min. Cellular debris was removed by
centrifugation. The supernatant was placed in a clean tube for storage.
The MLVA PCR amplification of the eight selected loci required four
PCRs: two multiplexed and two single amplifications. Each amplicon had
a single fluorescently labeled primer. Three different dyes were used
for the amplicons, while one was reserved for molecular weight
standards. Products from both reactions were pooled and then separated
by polyacrylamide gel electrophoresis under denaturing conditions on an
ABI 377 automated DNA sequencer. The resulting fragment profiles were analyzed using ABI Genescan and Genotyper software to determine allele
classification. Diversity group clusters were analyzed using sequential
agglomerative hierarchichal nested cluster analysis (SAHN) and
unweighted pair group method analysis using average linkages (UPGMA)
clustering routines (12) within the NTSYSpc software package
(F. J. Rohlf, NTSYSpc, ed. 2.02, Exeter Software, Stony Brook,
N.Y., 1998). A simple percent distance dissimilarity matrix of the
allele values for the isolates was constructed prior to cluster
analysis. Individual marker diversity (diversity index value [D]) is
calculated as being equal to 1
(allele
frequency)2 (16) and is based upon the entire
isolate collection in the study.
Statistical data analysis.
Space-time cluster calculations
were performed using the SatScan software Bernoulli model and are
described elsewhere in detail (M. Kulldorff et al., SatScan, ed. v2.1,
National Cancer Institute, Bethesda, Md., 1998). In brief, a space-time
scan statistic is defined by a cylindrical window with a circular
geographic base and with height corresponding to time. The base is
defined by an infinite number of distinct geographic circles, with
different sets of neighboring census areas within them and each being a possible candidate for a cluster, while the height reflects the time
period of potential clusters. The cylindrical window is then moved in
space and time, so that for each possible geographic location and size,
it visits each possible time period. In effect, we obtain an infinite
number of overlapping cylinders different in size and shape, jointly
covering the entire study region, where each cylinder reflects a
possible cluster. For each location and size of the scanning window,
the alternative hypothesis is that there is an elevated rate within the
window compared to outside. A likelihood function for the Bernoulli
model (used here) is calculated as
(n/m)n(1-n/m)(m-n)[(N-m)/(M-m)](N-n){1-[(N-m)/(M-m)]}(M-m)-(N-n)I(x),
where I(x) is the indicator function, set at 1 when the space-time scan
window has more cases than expected under the null hypothesis and set
at 0 otherwise. The likelihood function is maximized over all windows,
identifying the window that constitutes the likeliest cluster. This is
the cluster that is least likely to have occurred by chance. The
likelihood ratio for this window is noted and constitutes the maximum
likelihood ratio test statistic. Its distribution under the null
hypothesis and its corresponding P value are obtained by
repeating the same analytic exercise on a large number of random
replications of the data set generated under the null hypothesis in a
Monte Carlo simulation.
Probability contour kernel density maps were produced using ArcView GIS
software and extensions. These maps portray the probability that a
sample taken will be a member of the underlying point population for
which a kernel density function was applied from a given geographic area. The kernel density is a moving, three-dimensional function calculated for each map cell by distributing outward the value found in
the point population field for each point found within the search
radius and then dividing by the area of the circle in area units. The
output density values are the occurrences of the measured quantity per
specified area unit. In this analysis, the map units were square
kilometers and the search radius was 10 km.
The Wilcoxon rank-sum test is a nonparametric analysis of variance and
was performed for this study using SAS software. Soil
calcium values
and pH were set as the dependent variables and
classified by genotype
group
affiliation.
 |
RESULTS |
Genetic diversity of B. anthracis in the KNP.
We
examined the genetic diversity of 98 B. anthracis isolates
from the KNP by using MLVA (9) to better understand the
dynamics of anthrax in this region. The isolates included in the study were collected over more than 20 years and spanned multiple epidemics. Alleles detected are listed by size for each of the eight VNTR markers
in Fig. 1, along with the numerical
designations of their global diversity groups, based on our worldwide
strain analysis (9).

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FIG. 1.
Genetic relationships among KNP B. anthracis
isolates. Eight VNTR marker loci (9) were used to estimate genetic
relationships among the 98 B. anthracis isolates in the
study. UPGMA cluster analysis generated a dendrogram to graphically
represent dissimilarity among the unique types observed. On average,
the A and B isolates have different alleles at two-thirds of the eight
loci. The allele size at each VNTR locus is shown along with the number
of isolates (N) in each genotypic group (G). Genotype number and VNTR
marker alleles are consistent with a previous report (9). The major
diversity group (9) represented in each of the branches is shown in
parentheses beside the branch designation. The D calculated for each of
the eight markers is listed below the dendrogram.
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|
We found two dominant and four distinct MLVA strain types (genotypes)
in this collection of 98 isolates. Kruger A (number
67) is represented
by the most isolates (74 of 98). The Kruger
B genotype (number 87) is
the second most common (21 of 98), while
the other genotypes (number
45, 2 of 98; number 39, 1 of 98) are
rare. Kruger A is a member of
major cluster A3, which was previously
found to be the most widely
distributed worldwide, though the
Kruger A genotype itself has thus far
been isolated and identified
only in the KNP. The rare genotype 39, also a member of cluster
A3, has been isolated in Namibia in addition
to South Africa (
9).
Kruger B is a member of the B1
diversity group, which is found
almost exclusively in southern African
countries. The rare genotype
45 is from the A3 cluster and has also
been found in Argentina,
Turkey, and the United States. It is identical
with the U.S. vaccine
strain (V770-NPI-R), according to examination of
seven of the
eight VNTR loci (
9).
The dominant KNP strain types, Kruger A and B, are genetically quite
dissimilar. Five of the eight MLVA markers had allele
differences
between these genotypes. This considerable genetic
distance is
equivalent to the greatest distance reported in the
entire worldwide
collection (
9).
In this set of isolates, it is interesting to note that the most
informative marker was not from the pXO1 plasmid VNTR (Fig.
1), in
contrast to what was found in the worldwide study (
9).
In
fact, the pXO1 VNTR marker had a low diversity index value
(D = 0.06) in this collection. The pXO2 marker was the second
most
informative marker (D = 0.37) and closer to previous observations.
The genomic marker
vrrA (D = 0.38) showed the greatest
diversity
index value. The genomic markers
vrrB1,
vrrB2, and
vrrC1 provided
equal discriminatory power
(D = 0.34), while the markers
vrrC2 and CG3
revealed no diversity and therefore contributed no discriminatory
information to the analysis. The mean diversity index value of
the
eight VNTR markers used in this study was 0.23, much lower
than for the
worldwide study, where the average was 0.52. And
yet, two of the most
dissimilar strains known are found in overlapping
spatial distributions
in the
KNP.
Geographic and temporal distribution of isolates.
Although the
northernmost and central regions within the KNP are known to be foci
where epidemics have begun, anthrax cases were found throughout the
geographic extent of the park while we collected isolates. Figure
2I indicates the geographic locations of
sample isolates, but it alone inadequately represents the true isolate
sample density due to close or overlapping locations. As shown in Fig.
3, it is apparent that Kruger A and B
were present during the same year, showing temporal overlap. Kruger A
and B both contributed to mortality during the same epidemics in the KNP. This was especially true in 1970 to 1981, when about half of the
isolates were from each major strain type. This is in contrast to the
expectation that a single outbreak will emanate from a single source
and that pathogen isolates will have great similarity or even be
indistinguishable.

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FIG. 2.
Isolate locations and Bernoulli regression clusters. (I)
This map shows the individual isolate locations within the KNP. At the
scale presented, many isolate locations overlap and may appear less
dense than the actual total. (II) This map shows the geographic areas
included in the Bernoulli regression for time-space cluster detection.
The secondary time-space cluster for Kruger A isolates is in the middle
of the park (the primary cluster included the entire park), and the
primary time-space cluster for Kruger B isolates includes all of the
north of the park.
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FIG. 3.
Isolate-year relationships. This histogram shows the
number of isolates (in parentheses) and branch affiliation by year of
field isolation.
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|
In a previous investigation, we showed that all isolates, when
considered together, exhibit space-time clustering (as would
be
expected in epidemic situations) (
11). In this
investigation,
we used MLVA first to define individual samples as
either Kruger
A or B and then to demonstrate that differences existed
between
the spatial and temporal distributions of the two groups. When
we used a Bernoulli regression model for space-time clustering,
Kruger
A and B showed statistically significant independence from
each
other (Fig.
2II, log-likelihood ratio [LLR] = 21.39,
P <
0.001). The differently shaded areas
are the management blocks
included in clusters detected for Kruger A
and B (in the northern
region of the KNP for B and in the south for A).
The contour maps
of kernel density probability (Fig.
4) provide a clearer indication
of the
geographic distribution of Kruger A and B, which are overlapping
yet
distinctly different.

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FIG. 4.
Kernel density probability of Kruger isolates. (I) This
map shows the kernel density probabilities estimated for the Kruger A
strains included in this study. Representation of minor strain subtypes
(genotypes [G] 39 and 45) is indicated. (II) This map shows the
kernel density probabilities for the Kruger B strains. The actual
number of samples for each area (N) is also shown for both maps.
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|
Correlation of calcium content and pH with strain
distributions.
Soil calcium and pH are believed to be associated
ecologically with regions of anthrax endemicity (4). We
performed a nonparametric analysis of variance in order to explore the
strain-specific associations to these two environmental factors. The
results of a Wilcoxon rank-sum analysis show that Kruger A and B differ
statistically significantly in their association with both soil calcium
and pH (for pH, Z = 4.870 and P < 0.0001; for
calcium, Z = 3.999 and P < 0.0001). Kruger B
isolates were found on significantly higher-calcium and higher-pH soils
than were Kruger type A isolates (Fig.
5). The different geographic
distributions and distinct associations with soil calcium and pH
suggest unique environmental requirements and different ecological
constraints acting on each group.

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FIG. 5.
Genotype relationships with soil pH and calcium values.
(I) Mean soil pH in parentheses (95% confidence interval and range of
values for Kruger A and B genotype groups at the field isolate sites).
(II) Mean soil calcium content (95% confidence interval and range of
values for Kruger A and B genotype groups). In a nonparametric analysis
of variance, the two strain type groups were statistically
significantly different with respect to both soil pH (Z = 4.870 and P < 0.0001) and soil calcium (Z = 3.999 and
P < 0.0001).
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|
 |
DISCUSSION |
We describe the genetic diversity of 98 B. anthracis
isolates from the KNP, which we determined by using MLVA, a new, rapid, and robust molecular typing system (9). We have extended
previous ecological analyses (11) by classifying the
isolates into particular strain types (Kruger A and B) and showed that
the two dominant types are clustered in time and space, though not
identically. Lastly, we demonstrated that Kruger A and B have
significantly different environmental associations in the KNP.
The B. anthracis types in the KNP have the greatest genetic
distance among dominant isolates observed in a relatively small geographic area. The genetic distance between Kruger A and B (Fig. 1)
is equal to the greatest observed in an extensive worldwide collection
(9). Given the inherent homogeneity among B. anthracis strains, we must conclude that the great KNP genetic
distances are the result neither of intraepidemic evolution nor of
genetic divergence within the time period of this study. Rather, the
evolutionary time separating Kruger A and B represents either ancient
divergent evolution in the KNP or more recent dispersal of divergent
B. anthracis into this area.
The Kruger A strains may represent a diverse B. anthracis
type that evolved in southern Africa. Keim et al. hypothesized that southern Africa was the geographic origin of B. anthracis,
precisely because of the large genetic diversity observed in the region (7). The rare Kruger A genotypes 39 and 45 may represent
older displaced progenitors of the more common genotype 67. Alternatively, it is possible that Kruger A genotype 67 represents an
ancient, divergent endemic strain, while the rare genotypes 39 and 45 are recent, independent reintroductions to the area. We cannot,
however, rule out the possibility that all Kruger A isolates found in
the KNP are the result of one or more introductions via historic or contemporary commerce. While genotype 45 is identical to isolates from
Turkey, Argentina, and the United States, it is impossible to discern
from these data whether this genotype evolved in southern Africa or was
transported to the region.
All of the Kruger B isolates were identical in the study, showing no
diversity. Indeed, in a worldwide collection, all B1 genotypes analyzed
to date are identical or closely related to those found in the KNP
(9). In contrast to type A B. anthracis, the type
B isolates are relatively rare and almost exclusive to southern Africa
(9). If one of these isolates migrated to the KNP, it would
seem more likely that the Kruger A's are more recent introductions and
that Kruger B is truly endemic to the proximate KNP region.
The temporal and spatial distributions of the Kruger A and B isolates
are overlapping, yet distinct. While analyses performed prior to
genotypic group classification yielded positive results for time-space
clustering over all isolates (11), classifying the isolates
into their genotypic groups reveals the independent time-space
clustering of Kruger A and B. This correlated distinction becomes
apparent when associations with the environmental factors, soil pH and
calcium, are examined.
Kruger A and B have had opportunity over multiple epidemics to be
distributed geographically throughout the KNP. However, the genotypic
groups show neither a random nor totally overlapping distribution since
1970. Instead, they show distinctly different cluster patterns. The
different cluster patterns displayed by Kruger A and B isolates can be
attributed to distinct associations with factors in their environment.
Kruger B B. anthracis was very important in the epidemics of
1970 to 1981 and in the northern area of endemicity of the KNP. This
epidemic began in the northern KNP and then proceeded to the central
and southern areas of the park (3). In the north, isolates
that were collected from 1970 to 1981 are both Kruger A and B, while
the central isolates are predominantly Kruger A. From these data, we
conclude that the earlier anthrax spread was an ecological or
environmental progression more than a classic epidemic in which the
actual pathogen dispersed. The independence of these foci was masked by
correlated environmental cues.
In contrast, the major anthrax outbreak in 1990 was almost entirely
composed of Kruger A B. anthracis. This outbreak began in
the central regions and progressed to the north. In this epidemic, either environmental induction of independent foci or pathogen dispersal is consistent with this single-strain outbreak. The lack of
Kruger B in the northern region in 1990 is puzzling due to its
dominance in 1970. However, in early 1990, torrential rains scoured the
northern regions and may have severely impacted the spores of the
endemic strains. As the anthrax epidemic began in the central region,
Kruger A may have physically migrated into an open niche in the
northern region. When strain typing is coupled with the geographic and
temporal data, it is obvious that anthrax is a dynamic disease that may
emanate from several independent foci in close proximity and that these
foci may vary across the years. The presence of both types in the
northern outbreak of 1970 suggests that independent but environmentally
coordinated (induced) foci may exist within regions thought to be
single foci.
The important link of calcium and pH to the ecology of B. anthracis has been previously noted in the scientific literature (4). However, the exact nature of this relationship remains the subject of theory and speculation. Regardless of the specific role
that these two environmental factors play in the ecology of anthrax, it
is seemingly well established that endemicity of B. anthracis is associated with elevated calcium and
neutral-to-alkaline soils (4). In this study we have shown a
differential association of strain type with these two important
environmental factors.
Kruger A strains are associated with broader ranges of soil calcium and
pH than Kruger B's (Fig. 5). In the KNP, Kruger A isolates have a
wider geographic range and greater genetic diversity than Kruger B
isolates (Fig. 1 and 4). Locally and globally, B. anthracis
type A isolates reflect a broader geographic range (worldwide) and
greater genetic diversity than type B isolates, which are restricted to
southern Africa. While this association may be simply fortuitous,
adaptation of type A to diverse environmental conditions is consistent
with its greater geographic dispersal and genetic dissimilarity.
Conversely, type B may have lost the adaptive ability to survive
diverse environmental conditions, limiting its geographic dispersal and
opportunity to evolve the genetic dissimilarity of type A.
 |
ACKNOWLEDGMENTS |
This work was supported by funding from the U.S.
Department of Energy (NN20-CBNP), the National Institutes of
Health (RO1GM60795), and the Cowden Endowment in Microbiology.
 |
FOOTNOTES |
*
Corresponding author. Mailing address: Department of
Biological Sciences, Northern Arizona University, Flagstaff, AZ
86011-5640. Phone: (520) 523-4418. Fax: (520) 523-0639. E-mail:
Kimothy.Smith{at}nau.edu.
 |
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Journal of Clinical Microbiology, October 2000, p. 3780-3784, Vol. 38, No. 10
0095-1137/00/$04.00+0
Copyright © 2000, American Society for Microbiology. All rights reserved.
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