Department of Biological Sciences, Northern
Arizona University, Flagstaff, Arizona
86011-56401; United States Army
Medical Research Institute of Infectious Diseases, Fort Detrick,
Frederick, Maryland 21702-50112; and
Microbial Diseases Laboratory, California Department of Health
Services, Berkeley, California 947043
Received 2 April 2001/Returned for modification 26 May
2001/Accepted 6 July 2001
 |
INTRODUCTION |
The etiologic agent of plague,
Yersinia pestis, is a gram-negative bacillus and a member of
the family Enterobacteriaceae (4). Hundreds of
millions of people have died in three major plague pandemics. The first
pandemic, known as Justinian's plague, occurred during the 6th
century, striking populations in Africa and the Mediterranean countries
(4). The well-known Black Death plague began in the 14th
century and by the 17th century had killed a fourth of the European
population (4). The third pandemic began in China in the
late 1800's and was quickly dispersed by boat and rail around the
world (16). The third pandemic persists today, primarily
in rodent reservoirs, and rarely causes human deaths. Three
biovars, antiqua, mediaevalis, and orientalis, have been
established for classification of Y. pestis based on
glucose fermentation and nitrate reduction. However, until
recently, strain differentiation within these biovars has been limited.
Recent technological advances in molecular biology have facilitated
strain discrimination among pathogenic bacteria. Multilocus sequence
typing has demonstrated extremely low diversity in genes of such
recently emerged pathogens as Y. pestis (1, 2,
5) and the gram-positive bacterium Bacillus anthracis
(18). Molecular techniques based on restriction enzyme
digestion patterns have recently been applied to Y. pestis strain differentiation. The hypothesis that the first,
second, and third pandemics were caused by progenitor strains of the
antiqua, mediaevalis, and orientalis biovars, respectively, has been
substantiated by strain typing using rRNA restriction patterns
(ribotyping) (6) and the IS100 insertion
element restriction fragment length polymorphism (RFLP) (1). Pulsed-field gel electrophoresis detects large
restriction fragment size differences and has been applied
to Y. pestis strain typing, but it has resulted in
mixed findings (6, 12). Of these methods, the
IS100 insertion element RFLP analysis appears to have the
highest resolution, perhaps due to the higher mutation rates associated
with IS elements (1).
It has been known since the late 1960s that eukaryotic genomes contain
large numbers of repeated DNA sequences (3). However, not
until two decades later were these hypervariable minisatellite regions used to detect DNA fingerprints in the human
genome (8). Because of repetitive sequence length
variation observed among individuals, these tandem repeat arrays were
renamed variable number of tandem repeat (VNTR) loci by Nakamura et al.
(14). The ongoing sequencing efforts for a number of
archaeal and bacterial genomes have led to the discovery and
application of VNTRs to DNA fingerprinting of prokaryotic species as
well. For example, high-diversity VNTR loci have been used to genotype
strains of Neisseria gonorrhoeae (17),
Helicobacter pylori (13), Haemophilus influenzae (23), B. anthracis
(9), and, in a limited case, Y. pestis
(2).
In the work presented here, we report the analysis of the
Y. pestis chromosomal and two plasmid, pMT1 and
pCD1, DNA sequences in order to identify and characterize VNTR
loci. We further analyzed the relationship between sequence structure
and diversity using 42 VNTR loci. We report here the effects of
sequence structure on VNTR polymorphism and the phylogenetic potential
for Y. pestis strain discrimination using VNTR markers.
| |
MATERIALS AND METHODS |
Nomenclature.
Any DNA sequence repeated side by side is
referred to as a direct repeat or tandem repeat array. The simplest
sequence motif of a direct repeat array has a repeat length,
measured in base pairs. The number of times that this simple sequence
motif is present in the array is referred to as the copy number. The
repeat length multiplied by the copy number is the array size, also
measured in base pairs. For example, the tandem repeat array NATATATN, where N is any DNA, contains the dinucleotide motif AT with a repeat
length of 2 bp, a copy number of 3 bp, and an array length of 6 bp. By
convention, we state the repeat length before the copy number. For
instance, the array in the above example is a 2 by 3.
A direct repeat array may contain either a mononucleotide repeat motif,
also called a homopolymeric motif, such as a poly(T) tract, or a
heteropolymeric motif, which is a dinucleotide or greater repeat
motif of mixed nucleotide composition. A tandem repeat array with a
short repeat length is frequently referred to as a simple sequence
repeat (SSR) or short tandem repeat. van Belkum et al.
(22) have previously defined SSRs as repeat arrays with
repeat lengths of 2 to 6 bp. For the sake of consistency with one of
the direct repeat search programs used, here we refer to SSRs as arrays
with repeat lengths of 1 to 10 nucleotides. A VNTR maintains a repeat
length but differs among strains in copy number. PCR amplification of a
VNTR locus from different strains will reveal PCR fragment length
polymorphisms that reflect the increased or decreased copy number as a
result of insertion or deletion events within the array.
Detection of tandemly repeated sequences in the Y.
pestis genome.
In these studies, we have used and compared
two approaches for identifying direct repeat arrays. One approach
employed the Genequest software program (Dnastar package; LaserGene,
Inc., Madison, Wis.) direct repeat function set for the smallest
scanning window size possible (8 nucleotides) to locate direct repeat
arrays. This setting permits detection of arrays as small as 1 by 9, 2 by 5, 3 by 3, 4 by 3, etc.; however, it will not detect arrays of 8 bases or less. Genequest will also readily detect open reading frames
(ORFs) and was used in conjunction with the direct repeat searches to
determine their presence in and out of probable coding regions. The
second approach used software designed by Gur-Arie et al.
(7) to detect SSRs with a repeat length between 1 and 10 bp (ftp://ftp.technion.ac.il/pub/supported/biotech/ssr.exe). The SSR program generates an output file that contains the repeat length in base pairs, the nucleotide composition of the motif, the copy
number, and the location of the array.
The unfinished Y. pestis strain Colorado 92 (CO92)
chromosome sequence was downloaded from the Sanger Center Microbial
Genomes web page (http://sanger.ac.uk/Projects/Y_pestis/) on 21 April 2000 in 105 contigs. The complete sequences for the Y. pestis plasmids pCD1 and pMT1 were downloaded from the National
Center for Biotechnology Information (NCBI) web site (GenBank accession numbers NC_001976 for pCD1 and NC_001976 for pMT1). Plasmid sequences were screened for direct repeats in Genequest according to the parameters described above.
Clustering of arrays in the chromosome as detected with Genequest
was examined in 10-, 25-, and 50-kbp intervals and was compared to
an expected Poisson distribution [P(x) = e
µµx/x!, µ = 2.14 arrays per 10-kbp interval] as previously described (25).
PCR screening of direct repeats for variability.
All
reagents were obtained from Life Technologies, unless otherwise noted.
A diverse collection of 77 tandem repeat arrays identified with
Genequest was screened for locus variability. When available,
three representatives were screened for each repeat length. These
loci were amplified from 12 Y. pestis isolates, representing all biovar types (Table
1). Variability was detected in 42 of
the screened loci (Table 2). Thirty-five loci were
dropped from further analyses due to lack of variability (27 loci),
poor amplification (5 loci), or no amplification (3 loci). Six of
the 27 monomorphic loci showed significant homology to ORFs identified in members of the Enterobacteriaceae when BLAST searched on
the NCBI database (http://www.ncbi.nlm.nih.gov/BLAST/). Another
five, detected in an earlier incomplete Y. pestis
chromosome sequence assembly, were no longer present in multiple copies
in the 21 April 2000 sequence, suggesting they were artifacts of an
inaccurate assembly. Sequences from the 42 VNTR loci were checked
against the 21 April 2000 Y. pestis genome sequence to
ensure that the same VNTR locus was not duplicated in our analyses. The
completed Y. pestis sequence (February 2001) was
revisited to establish final genomic coordinates (Table 2).
DNA was extracted from the 12 diverse strains using a traditional
phenol-chloroform method. For the 12 California strains, DNA was
prepared by a simple heat-soak method, previously described by Keim et
al. (9). Primers were designed using Primer Select (Dnastar) with annealing temperatures as close to 65°C as possible but ranging from 59 to 69°C. However, primer-annealing temperatures did not differ by more than 2°C within a pair.
Reaction mixtures for PCR amplifications contained the final
concentrations of the following reagents: 1× PCR buffer without MgCl2; 2 mM MgCl2; 200 µM
dATP; 200 µM dCTP; 200 µM dGTP; 200 µM dTTP; 1 µM R110, R6G, or
Tamra phosphoramidite fluorescently labeled dUTP (Applied Biosystems,
Foster City, Calif.); 0.5 U of Taq polymerase; 0.5 ng of
template DNA; 0.2 µM forward primer; 0.2 µM reverse primer; and
filtered sterile water to a final volume of 20 µl. The primers
marked by an asterisk in Table 2 have a phosphoramidite fluorescent dye
(Fam, Hex, or Ned) covalently linked to the 5' nucleotide.
Reaction conditions using the 5'-labeled primers were identical
to those given above, with two exceptions. The fluorescent dUTP was
omitted from the reaction mixture, and 5'-labeled primers were
multiplexed, such that 18 primers were combined in four mixes. Mix 1 contained primers for the M06, M09, M18, M21, M28, and M34 loci; mix 2 contained primers for the M12, M23, M31, M58, and M82 loci; mix 3 contained primers for the M27, M29, and M33 loci; and mix 4 contained
primers for the M22, M25, and M59 loci. All PCRs were performed in MJ
Research 96-well DNA Engines equipped with hot bonnets. Reaction
mixtures were raised to an initial temperature of 94°C for 5 min to
denature the DNA. Thereafter, reaction mixtures were cycled
for 20 s at 94°C, 20 s at 60°C, and 45 s at 72°C
for a total of 35 cycles, followed by a final polymerase extension step
at 72°C for 5 min.
Fluorescently labeled amplicons were visualized by polyacrylamide
gel electrophoresis (PAGE) on an Applied Biosystems 377 DNA sequencer
using GeneScan fragment analysis. The PCR product was diluted fivefold
and then mixed with formamide, dextran blue loading dye, and a custom
Bio Ventures Rox 1000 fluorescently labeled size standard at a ratio of
12:5:1:6, respectively. Virtual filter set A was used to detect
amplicons labeled by direct incorporation with fluorescent dUTP.
Virtual filter set D was used to detect primer-labeled amplicons.
Amplicons were sized with Applied Biosystems GeneScan analysis software.
Statistical and phylogenetic analyses.
The degree of VNTR
variability for a locus was assessed by the number of alleles observed
or by Nei's diversity index [DI = 1 
(allele
frequency2)]. Because the calculations for
Nei's diversity index were based on allelic frequency, only the 12 mixed-biovar strains were used to calculate the diversity index for
each VNTR locus. The neighbor-joining dendrogram was generated using
all 42 VNTR marker loci (Table 2) in PAUP4a (software program; D. Swofford, Sinauer Associates, Inc., Sunderland, Mass.). The
simple matching coefficient and midpoint rooting options were used for
this analysis.
| |
RESULTS |
VNTR types and occurrence in the Y. pestis
genome.
In order to identify tandem repeat arrays and potential
VNTRs, we examined 105 contigs of Y. pestis genomic
sequence undergoing gap closure prior to final assembly. The
chromosomal sequence of the CO92 strain was analyzed using two
approaches for identifying tandem repeat arrays, Genequest and an SSR
search program (7).
We used Genequest to identify an average of 2.18 arrays per 10 kbp, with repeat lengths ranging from 1 to 143 bp. SSRs with repeat
lengths of 9 bp or less comprised the vast majority (84%) of all
detected tandem repeat arrays. The two most common repeat lengths among
these SSRs were 3 and 6 bp (46%) (Fig.
1). Just over half (53%) of all tandem
repeat arrays were found in ORFs of at least 700 bp. A substantial
portion (72%) of tandem repeat arrays identified in these ORFs had
repeat lengths of 3 bp or a multiple of 3. However, a surprisingly
large fraction (17%) of ORF tandem repeat arrays contained 7- or 8-bp
repeat lengths. Given the high density of genes in most bacterial
genomes, the triplet ORF bias and the nontriplet non-ORF bias strongly
suggest that tandemly repeated sequences mutate by insertion
and/or deletion events that must stay in frame if present in genes.
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FIG. 1.
Number of tandem repeat sequence arrays in the
Y. pestis chromosome. Log of array numbers with
repeat lengths from 1 to 21 bp detected by Genequest (black bars) and
repeat lengths from 1 to 10 bp detected by the SSR program (gray bars)
are presented. Larger repeat lengths of 22, 30, 36, 41, 45, 49, 115, 122, 123, 141, and 145 bp were observed but are not presented, as each
was observed only once (except the 123-bp repeat length, which was
observed three times).
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The two larger Y. pestis plasmids were also analyzed
using Genequest in order to identify extrachromosomal tandem repeat
arrays. The pCD1 (GenBank accession no. NC_001972) and the pMT1
(GenBank accession no. NC_001976) plasmids had array densities of 2.13 and 2.18 per 10 kbp, respectively. The plasmid results were essentially identical to that of the chromosome direct repeat array composition. Hence, at this stage there is no evidence for gross differences in the
repeat array composition between Y. pestis plasmids and its chromosome.
While Genequest permits detection of imperfect and nontandem (or
interspersed) repeat arrays, it will not detect arrays of less than 9 bp. In contrast, the SSR search program identifies direct repeat arrays
with repeat lengths from 1 to 10 bp and was able to identify many
additional SSRs that were not discovered via the Genequest analysis.
This approach identified 950 SSR arrays per 10 kbp. This is notably
higher than the 1.86 SSR arrays per 10 kbp found with Genequest (Fig.
1) and was largely due to the detection of many more short,
mononucleotide arrays. The frequency of detected SSR arrays declines
logarithmically with increasing repeat length (Fig. 1). The
ORF detection program that accompanies the SSR search program was not
available for determination of potential ORF bias patterns.
Clearly, the SSR search program is effective at identifying very small
arrays that the Genequest program misses. The SSR search program,
however, does not identify arrays with imperfect repeats or with repeat
lengths larger than 10 bp (Fig. 1). In addition, the large number of
short, mononucleotide repeat arrays identified by the SSR program are
not generally useful as molecular markers because of the difficulty in
scoring 1-bp fragment length polymorphisms. The Genequest direct repeat
pattern recognition is primarily a function of the human user and,
hence, is capable of identifying repeated sequences that are more
difficult to define in an algorithm. We find that both programs are
useful and complementary in the identification of repeated sequence
arrays in large genomic sequence databases.
In order to discern whether direct repeat arrays (as detected with
Genequest) occur randomly or in genomic clusters, their frequency in
10-, 25-, and 50-kbp intervals was compared to a model Poisson
distribution (Fig. 2). We found that
array frequency did not deviate from random at these three interval
scales, as tested by a chi-square test for independence. The observed
and Poisson expectations were so close that the chi-square
probabilities were equal to 1.0 for all three intervals. Therefore, it
appears that direct repeat arrays are randomly distributed in the
Y. pestis chromosome over these genomic interval sizes,
which are larger than most single genes. It would not be surprising if
particular genes were intolerant of repeated sequence arrays.
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FIG. 2.
Tandem repeat array distribution in the Y.
pestis chromosome. Array distribution observed per 10-kbp
interval (black bars) versus the expected Poisson distribution
(µ = 2.14 arrays per 10-kbp interval) (gray bars).
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Sequence structure versus diversity.
Among 77 direct repeat
loci PCR amplified from a group of 12 mixed-biovar strains of
Y. pestis, 42 were polymorphic. In order to compare
sequence structure parameters with VNTR variability we have determined
the diversity and number of alleles at these 42 VNTR loci for 24 selected Y. pestis isolates (Table 2). For these
studies, a group of 12 potentially closely related isolates from a
restricted geographic range (Siskiyou County, Calif.) were chosen, in
addition to the 12 isolates representing all three biovar types from a
broad worldwide distribution (Table 1). Among these 42 VNTR loci, the
number of alleles observed per locus ranged from 2 to 11 (Fig.
3). Nei's diversity index,
calculated from allele frequencies observed in the 12 mixed-biovar strains, ranged widely from 0 (only 1 allele detected) to
0.86.
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FIG. 3.
VNTR locus diversity. The 42 VNTR loci examined in this
study are displayed based on the total number of alleles present in the
24 strains exampled.
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Variability at VNTR loci was compared with different sequence structure
parameters in order to determine which component provides the greatest
power for predicting and understanding VNTR diversity levels.
Correlations were performed between copy number, repeat length or array
length, and the number of alleles or the diversity index for all 42 VNTR loci. Maximum copy number and number of alleles are highly
correlated (R value of 0.86) (Fig.
4). However, this strong
relationship is problematic for predictive purposes, because maximum
copy number is determined after screening a locus against a group of
diverse strains. More useful in a VNTR discovery program is the
correlation between the number of alleles and copy number in a
reference genomic sequence, such as CO92. In this study this
correlation is lower but still of great predictive power at 0.67.
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FIG. 4.
Maximum repeat copy number predicts the number of
alleles. Correlation between copy number and allele number observed in
42 polymorphic loci. This is presented for 12 Siskiyou County isolates
(open circles and line with short dashes), 12 globally dispersed
isolates (open triangles and solid line), and all 24 isolates combined
(filled circle and line with long dashes).
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The two additional sequence parameters, array length and repeat length,
moderately correlate with VNTR diversity. In neither case does the
correlation coefficient exceed 0.6, and both are correlated with copy
number. Interestingly, the repeat length correlates negatively with the
number of alleles (0.50); VNTR arrays with larger repeat lengths
display fewer alleles.
Among the 35 direct repeat arrays that did not show variability, the
SSR category (1- to 10-bp repeat length) exhibited a higher frequency
of monomorphism than the larger repeat length arrays. BLAST searches in
the NCBI database found that the majority of these monomorphic SSRs
showed significant homology to known genes, and they very likely reside
in related ORFs of Y. pestis (data not shown). The SSRs
that exhibited polymorphism, however, showed moderate to very high
diversity levels. The most diverse VNTRs tended to have repeat lengths
between 6 and 9 bp. The arrays with repeat lengths larger than those of
SSRs were more often polymorphic but generally showed low diversity levels.
Diversity in closely and distantly related isolates.
In order
to understand the relationship between VNTR diversity and evolutionary
time, we have examined the VNTR diversity between the 12 Siskiyou
County Y. pestis isolates with that of the 12 global
strains. While all Siskiyou County isolates were of the biovar
orientalis, the globally dispersed isolates had representatives from
the orientalis, mediaevalis, and antiqua biovars. As expected, the
mixed-biovar isolates are much more diverse, with an average of 4 alleles per locus versus 1.8 for the Siskiyou County isolates. In
addition, the average Nei's diversity index for the mixed-biovar
isolates is 0.54 versus 0.18 for the Siskiyou County samples. With all
24 samples combined, the total number of alleles per locus and the
diversity index shift to 4.6 and 0.46, respectively.
The slight increase in total allele number when all 24 samples are
combined is due to unique alleles in the Siskiyou samples not
represented among the four orientalis strains in the global isolate
group. Not surprisingly, this contrast indicates a geographic component
to polymorphism due to the length of time separating diversifying
isolates. Likewise, the maximum copy number effect upon allele number
is depressed in the closely related Siskiyou County isolates (Fig. 4).
The correlation is only 0.66 for Siskiyou County isolates but is 0.82 for the 12 global isolates. In this case, the geographic proximity may
also be an indicator of evolutionary distance. In the Siskiyou County
isolates, the VNTR loci have not had sufficient time to fully diversify
and therefore exhibit reduced allele number. Because of the differences
in diversity among the VNTR loci in this comparison, differential
mutation rates among VNTR loci must also be important.
Genetic relationships among strains based upon VNTR
analysis.
A phylogenetic analysis was performed on the 24 Y. pestis isolates using all 42 VNTR loci and the
neighbor-joining method. The purpose of this analysis was
not to construct an extensive phylogeny for many Y. pestis strains but to identify the utility of VNTRs as molecular
markers in Y. pestis using biovar-classified isolates. The resulting phylogenetic tree (Fig.
5) grouped all orientalis biovar isolates
into a single clade, supported with a high bootstrap value of 85. This
strongly supported branch, of course, also separates the
mediaevalis and antiqua biovar isolates from the orientalis isolates.
Mediaevalis and antiqua isolates also were consistently categorized to
their biovar, with the exception of the Pestoides F strain. Branch
lengths among the orientalis isolates were relatively short and
frequently well supported by bootstrap values. In contrast, branch
lengths among mediaevalis and antiqua isolates were long and seldom
supported by strong bootstrap values. This phylogenetic analysis is
generally consistent with IS100-based analysis and common
biovar evolutionary scenarios (2).
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FIG. 5.
Phylogenetic analysis using VNTR loci. Neighbor-joining
analysis with midpoint rooting using 42 markers identified genetically
similar and dissimilar strains. Biovar identities are indicated in
parentheses following the strain names. O, orientalis; M, mediaevalis;
A, antiqua. Bootstrap values based upon 1,000 simulations for
individual branches are indicated. Branches with no numbers had values
of less than 50.
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| |
DISCUSSION |
Because Y. pestis is a recently emerged pathogen,
very little (2) or no (1) nucleotide
variation among strains has been detected in comparative
sequencing studies. With nucleotide substitutions so rare, more
frequent types of mutational changes are needed for strain
identification and phylogenetic analysis. IS100-based analysis is very promising (2), as is multiple-locus VNTR
analysis (MLVA), which uses the VNTR-based polymorphism reported here. In both cases, multiple-variable loci are used to provide genome-wide coverage and increase the precision in genetic relationship estimation. MLVA has the additional attraction of providing multiple character states at each locus (IS100 RFLPs are binary), which
increases discriminatory potential between closely related isolates.
Binary data have a maximum possible diversity index value of 0.5 per locus, whereas the multiple allelic VNTRs may approach 1.0 per locus. The greater diversity and, probably, higher mutation rates of
VNTRs can provide high-resolution analysis of epidemics where isolates may be very closely related. MLVA is PCR based and
requires only small amounts of low-quality DNA templates. With these
favorable attributes, MLVA represents a promising approach for the
characterization of Y. pestis isolates.
Our analysis of the genome has identified numerous potential VNTR loci
and defined attributes related to their diversity in natural
populations of Y. pestis. The high densities of both
large repeat length arrays (ca. 1.86 per 10 kbp) and SSR arrays (ca. 980 per 10 kbp) in the genome offer a plentiful resource for marker development. The contrasting relationships between copy number and
diversity and between repeat length and diversity will provide a guide
for designing typing systems that match the research goals of
particular projects. If phylogenetic analysis of global diversity is
required, the less diverse, longer repeat length VNTR loci may be more
fruitful for analysis due to slower evolutionary change maintained
in the genome. If epidemiological or forensic analysis of a plague
outbreak is the goal, the most rapidly evolving, high-copy-number SSR
loci are best suited for inclusion in a typing system. Combining multiple loci in an analysis will provide great precision in genetic estimation and minimize the effect of convergent evolution on the
analysis. An assumption intrinsic to VNTR analysis is that alleles of
the same length are identical (homologous). However, this will not be
universally true due to convergent evolution, and it necessitates
identity between isolates to be confirmed at multiple loci. The 42 marker loci described in this study will provide a high level of
confidence in identifying genetic relationships.
The exceedingly high number of direct repeat arrays within the
Y. pestis genome may be an important feature of its
evolution. More than half of the tandem arrays we identified
contain triplet (or multiples of 3 bp) repeat lengths and comprise the
majority of direct repeats found in probable protein-coding ORFs.
Variation in these VNTRs generated by insertion and/or deletion
events, such as during mismatch repair (10, 21), will not
affect the reading frame but rather will change the amino acid
sequences in these proteins and may result in altered phenotypes. In
addition, VNTRs found in intergenic regions, such as a previously
described tetranucleotide VNTR in Y. pestis
(2), have the capacity to modify expression of adjacent
genes. For example, SSR-mediated phase variation of virulence
factor expression in many pathogenic bacteria, including H. influenzae (24), Neisseria spp., and Moraxella catarrhalis (15), is well characterized.
Surprisingly, we found that over one quarter of the direct repeats
detected in ORFs contain nontriplet repeat lengths, mostly of 7 or 8 bp. Nontriplet repeat array variation within coding regions has the
potential to radically modify proteins and shift bacterial phenotypes.
However, such variation is expected most often to produce a frameshift
mutation, leading to loss-of-function or undetected lethal phenotypes.
Nontriplet tandem repeat-associated loss-of-function mutations
have been previously characterized for Y. pestis.
The spontaneous loss of Psn, the yersiniabactin/pestin receptor, arises
from a 5-bp deletion, removing one of a pair of tandem pentameric
repeats in psn (11, 20). The naturally nonureolytic state of Y. pestis has also been
attributed to urease silencing by the addition of a single G residue at
a poly(G) tract in ureD (19). Hence, the high
frequency of monomorphism we observed among SSRs found in ORFs may
reflect a selective bias against such high-stakes changes that
accompany nontriplet repeat variation.
These observations have two consequences for our understanding of the
Y. pestis genome. First, the mechanisms (e.g., mismatch repair) responsible for tandemly repeated sequences and their associated variation are potent. Their random distribution suggests that VNTR development can occur throughout the genome and that selection against debilitating mutation defines VNTR composition within
genes. Secondly, there is tremendous potential for generating genetic
diversity within protein-coding genes over a very short evolutionary
time. The diversity associated with VNTRs is great, especially in
contrast to the lack of nucleotide substitutions among Y. pestis strains. Evolutionary adaptation of Y. pestis as it has moved across the globe and into new hosts,
vectors, and reservoirs would require genetic variation. As a recently emerged pathogen, VNTR diversity along with other highly mutable loci (e.g., IS elements) may have played an important role in Y. pestis evolution in the recent past.
We thank Christine Keys and an anonymous referee for reviewing the
manuscript and making critical suggestions.
| 1.
|
Achtman, M.,
K. Zurth,
G. Morelli,
G. Torrea,
A. Guiyoule, and E. Carniel.
1999.
Yersinia pestis, the cause of plague, is a recently emerged clone of Yersinia pseudotuberculosis.
Proc. Natl. Acad. Sci. USA
96:14043-14048[Abstract/Free Full Text]. (Erratum, 97:8192, 2000.)
|
| 2.
|
Adair, D. M.,
P. L. Worsham,
K. K. Hill,
A. M. Klevytska,
P. J. Jackson,
A. M. Friedlander, and P. Keim.
2000.
Diversity in a variable-number tandem repeat from Yersinia pestis.
J. Clin. Microbiol.
38:1516-1519[Abstract/Free Full Text].
|
| 3.
|
Britten, R. J., and D. E. Kohne.
1968.
Repeated sequences in DNA. Hundreds of thousands of copies of DNA sequences have been incorporated into the genomes of higher organisms.
Science
161:529-540[Free Full Text].
|
| 4.
|
Brubaker, R. R.
1991.
Factors promoting acute and chronic diseases caused by yersiniae.
Clin. Microbiol. Rev.
4:309-324[Abstract/Free Full Text].
|
| 5.
|
Buchrieser, C.,
C. Rusniok,
L. Frangeul,
E. Couve,
A. Billault,
F. Kunst,
E. Carniel, and P. Glaser.
1999.
The 102-kilobase pgm locus of Yersinia pestis: sequence analysis and comparison of selected regions among different Yersinia pestis and Yersinia pseudotuberculosis strains.
Infect. Immun.
67:4851-4861[Abstract/Free Full Text].
|
| 6.
|
Guiyoule, A.,
F. Grimont,
I. Iteman,
P. A. Grimont,
M. Lefevre, and E. Carniel.
1994.
Plague pandemics investigated by ribotyping of Yersinia pestis strains.
J. Clin. Microbiol.
32:634-641[Abstract/Free Full Text].
|
| 7.
|
Gur-Arie, R.,
C. J. Cohen,
Y. Eitan,
L. Shelef,
E. M. Hallerman, and Y. Kashi.
2000.
Simple sequence repeats in Escherichia coli: abundance, distribution, composition, and polymorphism.
Genome Res.
10:62-71[Abstract/Free Full Text].
|
| 8.
|
Jeffreys, A. J.,
V. Wilson, and S. L. Thein.
1992.
Hypervariable 'minisatellite' regions in human DNA.
Bio/Technology
24:467-472[Medline].
|
| 9.
|
Keim, P.,
L. B. Price,
A. M. Klevytska,
K. L. Smith,
J. M. Schupp,
R. Okinaka,
P. J. Jackson, and M. E. Hugh-Jones.
2000.
Multiple-locus variable-number tandem repeat analysis reveals genetic relationships within Bacillus anthracis.
J. Bacteriol.
182:2928-2936[Abstract/Free Full Text].
|
| 10.
|
Levinson, G., and G. A. Gutman.
1987.
Slipped-strand mispairing: a major mechanism for DNA sequence evolution.
Mol. Biol. Evol.
4:203-221[Abstract].
|
| 11.
|
Lucier, T. S.,
J. D. Fetherston,
R. R. Brubaker, and R. D. Perry.
1996.
Iron uptake and iron-repressible polypeptide in Yersinia pestis.
Infect. Immun.
64:3023-3031[Abstract].
|
| 12.
|
Lucier, T. S., and R. R. Brubaker.
1992.
Determination of genome size, macrorestriction pattern polymorphism, and nonpigmentation-specific deletion in Yersinia pestis by pulsed-field gel electrophoresis.
J. Bacteriol.
174:2078-2086[Abstract/Free Full Text].
|
| 13.
|
Marshall, D. G.,
D. C. Coleman,
D. J. Sullivan,
H. Xia,
C. A. O'Morain, and C. J. Smyth.
1996.
Genomic DNA fingerprinting of clinical isolates of Helicobacter pylori using short oligonucleotide probes containing repetitive sequences.
J. Appl. Bacteriol.
81:509-517[Medline].
|
| 14.
|
Nakamura, Y.,
M. Leppert,
P. O'Connell,
R. Wolff,
T. Holm,
M. Culver,
C. Martin,
E. Fujimoto,
M. E. Hoff. Kumlin, et al.
1987.
Variable number of tandem repeat (VNTR) markers for human gene mapping.
Science
235:1616-1622[Abstract/Free Full Text].
|
| 15.
|
Peak, I. R.,
M. P. Jennings,
D. W. Hood,
M. Bisercic, and E. R. Moxon.
1996.
Tetrameric repeat units associated with virulence factor phase variation in Haemophilus also occur in Neisseria spp. and Moraxella catarrhalis.
FEMS Microbiol. Lett.
137:109-114[CrossRef][Medline].
|
| 16.
|
Perry, R. D., and J. D. Fetherston.
1997.
Yersinia pestis etiologic agent of plague.
Clin. Microbiol. Rev.
10:35-66[Abstract].
|
| 17.
|
Poh, C. L.,
V. Ramachandran, and J. W. Tapsall.
1996.
Genetic diversity of Neisseria gonorrhoeae IB-2 and IB-6 isolates revealed by whole-cell repetitive element sequence-based PCR.
J. Clin. Microbiol.
34:292-295[Abstract].
|
| 18.
|
Price, L. B.,
M. Hugh-Jones,
P. J. Jackson, and P. Keim.
1999.
Genetic diversity in the protective antigen gene of Bacillus anthracis.
J. Bacteriol.
181:2358-2362[Abstract/Free Full Text].
|
| 19.
|
Sebbane, F.,
A. Devalckenaere,
J. Foulon,
E. Carniel, and M. Simonet.
2001.
Silencing and reactivation of urease in Yersinia pestis is determined by one G residue at a specific position in the ureD gene.
Infect. Immun.
69:170-176[Abstract/Free Full Text].
|
| 20.
|
Sikkema, D. J., and R. R. Brubaker.
1987.
Resistance to pesticin, storage of iron, and invasion of HeLa cells by yersiniae.
Infect. Immun.
55:572-578[Abstract/Free Full Text].
|
| 21.
|
Strand, M.,
T. A. Prolla,
R. M. Liskay, and T. D. Petes.
1993.
Destabilization of tracts of simple repetitive DNA in yeast by mutations affecting DNA mismatch repair.
Nature
365:274-276[CrossRef][Medline]. (Erratum, 368:569, 1994.)
|
| 22.
|
van Belkum, A.,
S. Scherer,
L. van Alphen, and H. Verbrugh.
1998.
Short-sequence DNA repeats in prokaryotic genomes.
Microbiol. Mol. Biol. Rev.
62:275-293[Abstract/Free Full Text].
|
| 23.
|
van Belkum, A.,
S. Scherer,
W. van Leeuwen,
D. Willemse,
L. van Alphen, and H. Verbrugh.
1997.
Variable number of tandem repeats in clinical strains of Haemophilus influenzae.
Infect. Immun.
65:5017-5027[Abstract].
|
| 24.
|
Weiser, J. N.,
D. J. Maskell,
P. D. Butler,
A. A. Lindberg, and E. R. Moxon.
1990.
Characterization of repetitive sequences controlling phase variation of Haemophilus influenzae lipopolysaccharide.
J. Bacteriol.
172:3304-3309[Abstract/Free Full Text].
|
| 25.
|
Young, W. P.,
J. M. Schupp, and P. Keim.
1999.
DNA methylation and AFLP marker distribution in the soybean genome.
Theor. Appl. Genet.
99:785-790[CrossRef].
|
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Abstract
Introduction
Present address: Johns Hopkins School of Medicine, Department of
Pathology, Baltimore, MD 21287-6417.
