Journal of Medical Microbiology (2006), 55, 1549–1557
DOI 10.1099/jmm.0.46779-0
An improved multiple-locus variable number of
tandem repeats analysis for Leptospira interrogans
serovar Australis: a comparison with fluorescent
amplified fragment length polymorphism analysis
and its use to redefine the molecular epidemiology
of this serovar in Queensland, Australia
Andrew Slack, Meegan Symonds, Michael Dohnt and Lee Smythe
Correspondence
Andrew Slack
[email protected]
Received 13 June 2006
Accepted 27 July 2006
WHO/FAO/OIE Collaborating Centre for Reference and Research on Leptospirosis, Western
Pacific Region, Centre for Public Health Sciences, Queensland Health Scientific Services,
Brisbane, Australia
In this study, an improved multiple-locus variable number of tandem repeats analysis (MLVA)
method based upon a previously published method is described. Improvements to the method
included redesigned primers and PCR conditions, combined with pooled capillary electrophoresis
using multicolored dyes. Allele sizes were converted into an allele string, and each unique allele
string was assigned a numerical MLVA type (MVT). The improved MLVA method was then applied to
96 previously characterized Leptospira interrogans serovar Australis isolates from human and
animal sources. The improved MLVA was found to have between six and 13 alleles at each locus,
compared with three to eight in the original. The mean Hunter–Gaston diversity index (HGDI) for the
improved MLVA method was 0?654, compared with 0?599 in the original; this increase in
diversity was largely due to changes in the analysis of the variable number of tandem repeat (VNTR)
data. When the improved MLVA method was compared with the fluorescent amplified fragment
length polymorphism (FAFLP) method, there was a high level of concordance between the profiles;
however, the MLVA method produced an additional four unique profiles amongst the subset of 30
isolates tested. Given that the improved MLVA method was found to be superior to the original
MLVA method, it was subsequently used to redefine the molecular epidemiology of L. interrogans
serovar Australis in Queensland, Australia. Using cluster analysis, the authors were able to
demonstrate clonal links amongst rodent isolates, rodent and human isolates, and rodent and
canine isolates. These results highlight the role of rodents in the disease, and also the potential role
of MLVA in defining the molecular epidemiology of L. interrogans.
INTRODUCTION
Leptospira interrogans is one of the causative agents of the
disease leptospirosis. Leptospirosis is considered an emerging zoonotic disease with a worldwide distribution
[Bharti et al., 2003; World Health Organization (WHO),
1999]. Molecular investigations into the epidemiology of
Leptospira infections are important to determine whether an
outbreak caused by a clonal source has occurred, and which
Abbreviations: FAFLP, fluorescent amplified fragment length polymorphism; FAM, 6-carboxyfluorescein; HEX, 6-hexachlorofluorescein;
HGDI, Hunter–Gaston diversity index; Ia, index of association; MLVA,
multiple-locus variable number of tandem repeats analysis; MLST,
multilocus sequence typing; MST, minimum spanning tree; MVT, MLVA
type; NED, 2,7,8-benzo-5-fluoro-2,4,7-trichloro-5-carboxyfluorescein;
SLV, single-locus variant; VNTR, variable number of tandem repeat.
46779 G 2006 SGM
species of animal is the vector of the disease (Slack et al.,
2005).
Various molecular techniques have been described for
studying the molecular epidemiology of Leptospira, including PFGE, and randomly amplified polymorphic DNA
(RAPD) and fluorescent amplified fragment length polymorphism (FAFLP) analysis. All of these methods suffer
from significant drawbacks, including low discriminatory
power, poor reproducibility, and the high level of technical
skill required to perform the method. As an alternative to
these methods we have developed a multiple locus variable
number of tandem repeats analysis (MLVA) based upon
agarose gel electrophoresis. Whilst this method fulfils the
aim of producing a technically simple method that is
reproducible and suitable for any laboratory with the bare
minimum of equipment, it does have several drawbacks,
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1549
A. Slack and others
Table 1. Primers and PCR conditions used in the L. interrogans MLVA method
Locus
V27
V29
V30
V36
V50
Forward primer
Reverse primer
HEX–AAGTTCGTCGGGTGAGC
NED–TGGGTGCCGGGTTGT
FAM–ATAGGTTCGGCGTTTAGTA
HEX–TGGCGTCGAAGACAAA
NED–CTTGTTGGATCACAATACGAACTATA
TGATTTCTTTCGGTGGC
ATGCCACATCTCATCCATTAC
TTTAGATGTTTCGCTTTGG
ACTCTACCAGGAGATTATCAAA
GGTAAGGGACAAAGTAAGTGAAGC
including a loss of resolution through the use of agarose gel
electrophoresis and the rounding of repeats to whole
numbers to simplify analysis (Slack et al., 2005).
To improve resolution and accuracy in bacterial variable
number of tandem repeat (VNTR) methods, capillary
electrophoresis has become the preferred methodology, due
to the availability of multiple fluorescent labels, and to
greater accuracy and reproducibility (Lindstedt et al., 2004a,
b; Lista et al., 2006). Whilst capillary electrophoresis is the
preferred methodology, the expense of purchasing a DNA
sequencer may prevent some laboratories from changing
from agarose gel electrophoresis; however, this can be
compensated by the other critical improvements to the
method, such as the optimized PCR amplification reactions
and reaction conditions.
To further harness the power of capillary electrophoresis, we
utilized pooled PCR products, and used three fluorescent
dyes and a commercially available labelled DNA marker,
which allowed the sizing of fragments of up to 1000 bp. The
analysis of the MLVA data was also improved by using an
allele designation system proven in several published MLVA
articles (Lindstedt et al., 2004a; Whatmore et al., 2006)
combined with the assignment of an MLVA type number
similar to that used in multilocus sequence typing (MLST)
experiments. To ascertain the effects of these changes, we
applied the improved MLVA method to the L. interrogans
serovar Australis strains that had been previously characterized by the original MLVA method, and present in this study
a redefined epidemiological model of this serovar in
Queensland, Australia. Furthermore, in this research, we
established the relative value of the MLVA method as an
epidemiological tool by comparing it with a previously
published FAFLP method, using a subset of the L.
interrogans serovar Australis isolates.
METHODS
L. interrogans serovar Australis strains. A total of 96 isolates of
L. interrogans serovar Australis were obtained from the culture collection housed at the WHO/FAO/OIE Collaborating Centre for
Reference and Research on Leptospirosis. Fifty-seven isolates were
from human sources, whilst 39 were from non-human sources, such
1550
PCR conditions
Number
of cycles
Annealing
temperature (6C)
25
25
25
33
25
50
50
54
52
58
as rodents, dogs and native Australian animals. All isolates had been
previously identified using standard serological methods, including
the cross-agglutination absorption test (CAAT). All isolates had
been previously characterized by MLVA (Slack et al., 2005).
DNA extraction. Leptospira DNA was extracted by the following
method: Ellinghausen McCullough Johnson Harris (EMJH) broth
(500 ml) containing actively growing leptospires was centrifuged in a
microcentrifuge tube at 12 000 g for 4 min. The supernatant was
removed and the pellet resuspended in 200 ml PBS. This suspension
was then extracted using the High Pure PCR Template Preparation
kit (Roche) as per the manufacturer’s instructions.
MLVA analysis. The VNTR loci used in this method have been
previously described (Slack et al., 2005); however, the primers were
redesigned to prevent the spurious PCR products that were evident
in the previous version of the method. The primers were synthesized
by Invitrogen or Applied Biosystems, and the 59 end of the forward
primers was labelled with the fluorophores 6-carboxyfluorescein
(FAM),
2,7,8-benzo-5-fluoro-2,4,7-trichloro-5-carboxyfluorescein
(NED) or 6-hexachlorofluorescein (HEX) (Table 1). PCR amplification was performed in 25 ml final volumes. All reactions contained
16 PCR buffer, 2 mM MgCl2, 200 mM dNTPs, 12?5 pmol forward
and reverse primer (Table 1), 1 U AmpliTaq Gold (Applied
Biosystems), 2?0 ml template DNA, and double-distilled water
(ddH2O) to make up the final volume. The PCR reactions were run
on a PE9700 thermal cycler (Applied Biosystems) using the following conditions: 95 uC for 10 min, varying cycles of 94 uC for 30 s,
annealing at varying temperatures (refer to Table 1) for 30 s, and
extension at 72 uC for 1 min. The high-stringency conditions combined with the use of minimal thermal cycling prevented the formation of spurious PCR products that could interfere with the
subsequent fragment sizing. Five microlitres of the PCR products
from loci V27, V29 and V30 were pooled in a microcentrifuge tube,
as were the products from V36 and V50. Both pooled PCR mixes
were further diluted with 100 ml ddH2O, and 3 ml of each pooled
PCR product was combined with 21?5 ml HiDi formamide (Applied
Biosystems) and 0?5 ml X-rhodamine MapMarker 1000 XL
(BioVenture). The samples were denatured at 95 uC for 5 min and
cooled rapidly to 4 uC before being loaded onto the ABI 310 capillary sequencer (Applied Biosystems). Electrophoresis was performed
using a 47 cm capillary filled with performance-optimized polymer
4 (Applied Biosystems) at 60 uC for 45 min with a running voltage of
15 kV, and an injection time of 10 s at an injection voltage of 15 kV.
Each VNTR locus could be identified by colour and assigned a size by
the GENESCAN software (Applied Biosystems). This size was then converted into an allele designation, as shown in Table 2, which in
turn formed the allele string for the five loci. The allele string was
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Journal of Medical Microbiology 55
Epidemiology of L. interrogans serovar Australis
Table 2. Allele designation for L. interrogans serovar
Australis
Allele designation
1
2
3
4
5
6
7
8
9
10
11
12
13
Improvements to the published MLVA method
Size (bp) of:
V27
V29
V30
V36
V50
317
363
367
414
644
818
2
2
2
2
2
2
2
415
744
791
651
464
840
697
701
774
607
2
2
2
583
722
676
532
630
475
576
555
2
2
2
2
2
746
709
532
593
796
737
758
643
695
500
658
2
2
491
583
480
796
537
396
345
632
465
531
486
445
404
constructed in the following order: V27-V29-V30-V36-V50. Each
unique allele string was given a unique MLVA type (MVT) number,
using a process similar to that used in MLST experiments (Fig. 1).
FAFLP analysis. FAFLP analysis was performed as described else-
where, using the AFLP Microbial Fingerprinting kit (Applied
Biosystems) (Vijayachari et al., 2004). One microlitre of the six
selective PCR products generated by the kit was mixed with 23 ml
HiDi formamide and 1 ml Geneflo-625 (CHIMERx), and denatured
at 95 uC for 5 min. The products were then loaded onto the ABI 310
instrument, and injected into a 47 cm capillary filled with performance-optimized polymer 4 at 15 kV for 12 s. The fragments were
separated at 13 kV for 35 min. The resulting electropherograms
were manipulated using the Genotyper version 2.5 software (Applied
Biosystems), and the combined allele sizes were exported into an
Excel spreadsheet. An Excel macro described elsewhere (Rinehart,
2004) was used to convert the alleles into a binary sequence suitable
for analysis, using Bionumerics software (Applied Maths). Each
unique FAFLP binary pattern was assigned a letter code (e.g. AA,
BB, CC) to allow easier referencing of the data.
Phylogenetic and statistical data analysis. Phylogenetic analy-
sis was performed using Bionumerics version 4.0 (Applied Maths).
Dendrograms were constructed using the categorical MLVA combined with the Ward algorithm. Population modelling was performed using the minimum spanning tree (MST) algorithm with the
highest number of single-locus variants (SLVs) as the priority rule
and the creation of hypothetical types was disabled. The Hunter–
Gaston diversity index (HGDI) was calculated as previously
described (Hunter & Gaston, 1988), using the VNTR diversity and
confidence extractor software (V-DICE) available at the Health
Protection Agency bioinformatics tools website (http://www.hpabioinfotools.org.uk/cgi-bin/DICI/DICI.pl). The degree of linkage disequilibrium was determined using the index of association (Ia) using
the software available at the MLST website (http://www.mlst.net). Ia
is calculated by comparing the observed variance (Vo) in the distribution of allelic mismatches in all pair-wise comparisons of the allelic profiles with that of the expected variance (Ve) in a freely
recombining population minus one [Ia=(Vo/Ve)21]. Significant
linkage disequilibrium is established if the observed variance in the
MLVA allele profiles is greater than the maximum variance observed
with 1000 randomized allele profiles (P<0?001) (Smith et al., 1993).
http://jmm.sgmjournals.org
RESULTS AND DISCUSSION
The improved MLVA method incorporated several notable
changes from the original MLVA method (Slack et al., 2005).
The first change was the redesign of the primers used to
amplify the VNTR loci; the original primers for V27-V36
produced spurious products due to partial homology of the
primer to the flanking regions of the target sequence. The
primers used in this method were redesigned to prevent mispriming and thus produce a single band for each locus. In
addition, the V8 locus used in the previous MLVA method
(Slack et al., 2005) was not used in this study, as under
capillary electrophoresis it produced two alleles in certain
strains (A. T. Slack and others, unpublished data). Alhough
the changes to the PCR primers and conditions increased the
complexity of the method and would make multiplexing
the PCR difficult, the priority of this study was to ensure that
the correct PCR product could be identified during capillary
electrophoresis, with no interference from background or
spurious amplification products. To utilize the full potential
of the ABI 310 instrument, we pooled the PCR products
labelled with three spectrally separate fluorophores (FAM,
HEX and NED) and employed filter set D to sort and size the
VNTR products. This resulted in clear and interpretable
electropherograms for analysis. MapMarker 1000 XL contains 23 single-stranded DNA bands from 50 to 1000 bp, and
the use of this marker was critical to the study, given that there
is no GENESCAN marker available to size fragments >500 bp.
The final improvement to the method was the conversion of
VNTR allele sizes into a numerical string that would
ultimately be suitable for both the end-user and the analysis
software. The method used was adapted from a previously
published method (Lindstedt et al., 2004a). Briefly, the
fragment sizes were assigned an allele designation as shown
in Table 2; this designation was converted into an allele
string in the following order: V27-V29-V30-V36-V50. To
further simplify this allele string for both the end-user and
also for discussion, we assigned an MVT number for every
unique allele string present in the dataset, e.g. the allele
string 1-1-1-1-1 was designated MVT1. This reduction of
the allele string to an MVT brings the method into line with
other common typing methods, such as PFGE and MLST,
and allows easier interpretation of the result by nonspecialist end-users of the data.
Comparison of MLVA data from the improved
method with that from the original method
When the improved MLVA method was applied to the
previously characterized L. interrogans serovar Australis
isolates, each VNTR locus was found to have between six
(V27) and 13 (V50) different alleles (Table 3). This is an
increase in the number of alleles found in the VNTR loci
when compared with the original method, which had
between three (V27) and eight (V50) alleles. The differences
in the number of alleles found in the modified method could
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A. Slack and others
Categorical
MLVA
_80 _60 _40 _20
0
20
40
80 100
ID
A
B
C
Location
Year
Source
MVT
Allele string
(V27,V29,V30,V36,V50)
LT1338
(a)
1552
60
Upper Darradgee 2002 Human
16
1 1 6 1
9
QHR 515 A Innisfail
2003 R. sordidus
17
1 1 7 1
9
LT1063
2000 Human
47
1 1 8 10 3
QHR 581 B Innisfail
2003 Rattus spp.
3
1 1 5 1
1
QHR 581 A Innisfail
2003 Rattus spp.
3
1 1 5 1
1
QHR 527 A Innisfail
2003 Rattus spp.
37
1 1 5 5
5
QHR 544 A Innisfail
2003 R. leucopus 45
1 1 4 9
12
LT1013
Tully
1999 Human
46
2 3 5 9
12
LT1577
Gordonvale
2004 Human
5
1 4 4 1
1
LT1586
Aloomba
2004 Human
5
1 4 4 1
1
LT1059
Cairns
2000 Human
13
1 4 4 1
3
QHR 132
Tully
1999 Rattus spp.
41
1 4 2 7
8
QHR 571 A Innisfail
2003 Rattus spp.
22
1 1 1 2
1
QHR 554 A Innisfail
2003 Rattus spp.
22
1 1 1 2
1
LT1238
2002 Human
34
1 1 2 4
1
QHR 214-2 Innisfail
2002 R. sordidus
19
1 1 1 1
11
QHR 525 B Innisfail
2003 R. leucopus 12
1 1 1 1
3
LT738
Innisfail
1995 Human
1
1 1 1 1
1
LT1068
Innisfail
2000 Human
1
1 1 1 1
1
LT1318
Innisfail
2002 Human
1
1 1 1 1
1
LT1328
South Johnstone
2002 Human
1
1 1 1 1
1
LT1334
Innisfail
2002 Human
1
1 1 1 1
1
LT1336
Innisfail
2002 Human
1
1 1 1 1
1
LT1573
Innisfail
2004 Human
1
1 1 1 1
1
LT1614
Innisfail
2004 Human
1
1 1 1 1
1
QHR 250
Innisfail
2002 R. fuscipes
1
1 1 1 1
1
QHR 253 A Innisfail
2002 R. sordidus
1
1 1 1 1
1
QHR 137
1999 Rattus spp.
1
1 1 1 1
1
QHR 520 A Innisfail
2003 R. lorf
1
1 1 1 1
1
QHR 550 B Innisfail
2003 R. lorf
1
1 1 1 1
1
LT1007
1999 Human
1
1 1 1 1
1
QHR 253 B Innisfail
2002 R. sordidus
1
1 1 1 1
1
QHR 246
2002 R. leucopus 1
1 1 1 1
1
QHR 604 B Innisfail
2003 Rattus spp.
1
1 1 1 1
1
QHR 468 B Unknown
2003 Rattus spp.
1
1 1 1 1
1
QHR 534 B Innisfail
2003 Rattus spp.
1
1 1 1 1
1
QHR 514 A Innisfail
2003 R. sordidus
1
1 1 1 1
1
QHR 534
Innisfail
2003 Rattus spp.
1
1 1 1 1
1
LT1022
Innisfail
1999 Human
1
1 1 1 1
1
LT992
Innisfail
1999 Human
1
1 1 1 1
1
LT1626
Unknown
2004 Human
8
3 5 1 1
1
QHR 536
Innisfail
2002 R. leucopus 8
3 5 1 1
1
QHR 525 A Innisfail
2002 R. leucopus 8
3 5 1 1
1
QHR 126
Tully
1999 Uromys spp. 20
3 5 1 1
11
QHR 214
Innisfail
2002 R. sordidus
44
3 5 1 9
1
QHR 347
Innisfail
2002 Rattus spp.
44
3 5 1 9
1
LT1044
Nerada
2000 Human
44
3 5 1 9
1
LT1622
Innisfail
2004 Human
40
3 5 1 6
1
QHR 536
Innisfail
2003 R. leucopus 39
3 5 5 5
10
Innisfail
Sarina
Palmerston
Innisfail
Innisfail
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Epidemiology of L. interrogans serovar Australis
(b)
D
E
F
G
LT1171
Tully
2001
Human
2
1
1
3 1
1
LT1196
Cardwell
2001
Human
49
1
3
3 1
1
LT743
Mossman
1995
Human
4
1
2
3 1
1
LT860
Mossman
1997
Human
4
1
2
3 1
1
LT1168
Tully
2000
Human
9
3
5
3 1
1
LT1243
Cardwell
2002
Human
10
3
8
3 1
1
QHR 415 B
Tully
2003
Rattus spp. 18
2
4
3 1
9
LT979
Tully
1999
Human
21
6
10 3 1
13
LT1624
Tully
2004
Human
14
4
6
3 1
6
LT1625
Tully
2004
Human
15
4
6
3 1
7
LT1505
Tully
2003
Human
11
4
6
3 1
1
QHR 371 A
Mackay
2003
R. sordidus 26
4
6
3 2
1
LT1169
Innisfail
2001
Human
33
4
6
5 3
4
LT1535
Tully
2003
Human
24
2
3
3 2
1
LT1538
Tully
2003
Human
24
2
3
3 2
1
LT1535
Tully
2003
Human
24
2
3
3 2
1
QHR 472 A
Tully
2003
Rattus spp. 48
2
3
3 11 1
LT1167
Tully
2000
Human
29
2
3
3 2
2
LT958
Tully
1999
Human
30
2
9
3 2
2
LT1180
Mourilyan
2001
Human
6
2
3
1 1
1
LT1241
Silkwood
2002
Human
6
2
3
1 1
1
LT1170
Tully
2001
Human
7
2
3
3 1
1
LT1653
Tully
2004
Human
7
2
3
3 1
1
LT1539
Tully
2003
Human
7
2
3
3 1
1
LT1021
Mackay
1999
Canine
23
1
3
3 2
1
QHR 136
Tully
1999
Rattus spp. 23
1
3
3 2
1
LT1581
Cairns
2004
Human
43
1
3
3 9
1
LT930
Gordonvale
1998
Human
50
1
3
2 2
1
LT985
Innisfail
1999
Human
50
1
3
2 2
1
LT1508
Murray Upper
2003
Human
35
5
7
2 4
1
LT1504
Tully
2003
Human
36
5
7
2 4
6
LT1197
Rockhampton
2001
Human
27
5
7
3 2
1
LT1340
Miallo
2002
Human
38
1
7
2 5
5
LT1506
Tully
2003
Human
42
5
7
2 8
5
LT1337
Tully
2002
Human
32
3
8
3 2
2
LT1395
Murray Upper
2002
Human
32
3
8
3 2
2
LT1244
Tully
2002
Human
31
3
5
3 2
2
QHR 142
Tully
1999
Rattus spp. 25
3
8
3 2
1
LT1057
Tully
2000
Human
28
1
4
3 2
2
LT1342
Tully
2002
Human
28
1
4
3 2
2
QHR 115
Palmerston
1999
Melomys sp. 28
1
4
3 2
2
74-962
Tully
1999
Rattus spp. 28
1
4
3 2
2
QHR 143
Tully
1999
Rattus spp. 28
1
4
3 2
2
LT973
Tully
2003
Human
28
1
4
3 2
2
QHR 141
Tully
1999
Rattus spp. 28
1
4
3 2
2
74-629
Tully
1999
Rattus spp. 28
1
4
3 2
2
QHR 143
Tully
1999
Rattus spp. 28
1
4
3 2
2
Fig. 1. (a, b) Clustering analysis of L. interrogans serovar Australis using improved MLVA data. R. sordidus, Rattus sordidus;
R. leucopus, Rattus leucopus; R. fuscipes, Rattus fuscipes; R. Iorf, Rattus lorf.
be attributed to the change in the data analysis: every unique
size was given a unique allele designation, whereas in the
original method the size was converted to a repeat unit and
was further rounded to a whole number.
http://jmm.sgmjournals.org
In addition to the changes in the number of alleles present in
the VNTR loci, there was also a change in the diversity index
for each locus. The diversity index is usually modelled on the
mathematical equations of Nei (Weir, 1990), Simpson
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A. Slack and others
Table 3. Comparison of data between the original (Slack et al., 2005) and modified MLVA methods
Locus
V27
V29
V30
V36
V50
Original MLVA method
Modified MLVA method
HDGI
(n=96)*
Confidence
intervalD
Number of different repeats
present at each locus
Max
(pi)d
HDGI
(n=96)*
Confidence
intervalD
Number of different repeats
present at each locus
Max
(pi)d
0?098
0?817
0?763
0?642
0?674
0?060–0?135
0?799–0?835
0?745–0?780
0?617–0?667
0?648–0?699
3
8
7
5
6
0?949
0?323
0?333
0?475
0?424
0?594
0?794
0?689
0?633
0?563
0?548–0?640
0?769–0?819
0?663–0?715
0?595–0?671
0?510–0?616
6
10
8
11
13
0?604
0?375
0?396
0?542
0?646
*HGDI (Hunter & Gaston, 1988) as calculated by the V-DICE software (http://www.hpa-bioinfotools.org.uk/cgi-bin/DICI/DICI.pl).
DConfidence interval: the precision of the HGDI, expressed as the 95 % upper and lower boundaries.
dMax (pi): the proportion of samples (expressed as a decimal) that possess the most frequently found repeat at the VNTR locus.
(Simpson, 1949) or Hunter and Gaston (Hunter & Gaston,
1988), and is based on the probability of two unrelated
strains being characterized as the same type. These indexes
may be used to compare typing methods and select the most
discriminatory system (Hunter & Gaston, 1988). For this
study we used the HGDI, as calculated by the V-DICE
software. With the exception of V27, all other loci showed a
drop in the HGDI when compared with the results of the
original MLVA method. However, this drop in the HGDI at
the individual locus must be tempered by the change in the
mean diversity across the five loci, given that the allele string
is analysed rather than individual loci. The modified method
had a mean diversity of 0?654 and the original had a mean
diversity of 0?599. The reason for positive change in mean
diversity is that the V27 locus had an increase in diversity
from 0?098 in the original method to 0?549 in the modified
method (Table 3).
The Ia for the modified MLVA data was 0?827 (P<0?001);
this result shows that there was significant linkage
disequilibrium, which implies a low rate of recombination
between the alleles (Smith et al., 1993).
Comparison of the improved MLVA method with
FAFLP analysis
FAFLP analysis was performed on 30 MLVA-typed L.
interrogans serovar Australis isolates, and clustering analysis
was performed using Bionumerics for comparison with the
modified MLVA (Fig. 2). Sixteen FAFLP profiles (AA–PP)
were present amongst the 30 isolates. FAFLP type PP was the
most prevalent type in the dataset (9/30 profiles, 30 %). The
results from the comparison show that the FAFLP results
were comparable with those obtained by MLVA. To
highlight the concordance of the two methods, we have
linked the two cluster analyses using a series of connecting
solid and dashed lines and roman numeral designations
(i–v). MVT clones such as MVT1 (FAFLP type PP), MVT32
(LL) MVT50 (NN), MVT5 (OO) and MVT6 (MM) were
grouped together with the respective isolates by FAFLP. The
majority of the remaining MVTs had unique FAFLP profiles
1554
(AA–KK), with the exception of the following two isolates:
QHR581B (MVT3) belonged to profile PP by FAFLP (the
same FAFLP profile as MVT1) and LT1342 (MVT28) was
found to have profile OO (the same as MVT5) in the FAFLP
analysis (Fig. 2). Overall, the two methods were found to be
comparable with each other; however, the MLVA method
produced a greater number of unique patterns than the
FAFLP method. A larger comparison study using other
serovars may need to be conducted to establish which of the
two methods has the highest resolution for the typing of L.
interrogans strains. MLVA and FAFLP required equivalent
levels of technical skill and equipment to perform the
method; however, the data analysis for the MLVA method
was easier to perform, given that it involves only five alleles
compared with the 150–200 alleles produced by the FAFLP
method. A further advantage of the MLVA method over
FAFLP analysis is that the MLVA method could be applied
in a non-culture-based situation, i.e. it could be possible to
type an organism directly from a Leptospira PCR-positive
DNA extract.
Redefining the molecular epidemiology of L.
interrogans serovar Australis in Queensland,
Australia, using the improved MLVA method
As the improved MLVA method was found to be superior to
the original MLVA method, we used the data generated
from the improved method to redefine the molecular
epidemiology of L. interrogans serovar Australis in
Queensland, Australia. Fifty MVTs were found in the 96
isolates tested in this study (Fig. 1a, b). When clustering
analysis was applied to the isolates, it revealed eight clades
(A–G), each containing isolates from both human and nonhuman sources (Fig. 1a, b). Clades A, B and C contained
mostly the isolates from the Innisfail region (36/49, 73 %),
and clades D, E, F and G contained mostly isolates from the
Tully region (30/46, 65 %). Clade B was the largest group,
containing 28 isolates, the majority of which were from the
Innisfail area (24/28 isolates, 86 %). In the Innisfail region,
MVT1 was the dominant clone (20/39, 51 %) (Fig. 3), and
in the Tully region, MVT28 (8/32, 25 %) was the dominant
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Journal of Medical Microbiology 55
Epidemiology of L. interrogans serovar Australis
Categorical
MLVA
_50
0
50
100
Isolate
ID
MLVA
type
Categorical
FAFLP
_50
0
Isolate
50
100 ID
FAFLP
type
LT1170
7
LT1170
AA
LT1535
24
LT1238
BB
LT1180
6
LT1244
CC
LT1241
6
LT1622
DD
LT1622
40
LT1197
EE
LT1196
49
LT1581
FF
LT1581
43
LT1243
10
LT1243
GG
LT1197
27
LT1171
HH
LT1624
14
LT1535
II
LT1337
32 iii
LT1340
JJ
LT1395
32
LT1338
KK
LT1244
31
LT1337
LL
LT1342
28
LT1395
LL
LT1171
2
LT1180
MM
LT1241
MM
LT930
NN
LT985
NN
LT1196
NN
LT1342
OO
LT1577
OO
LT1586
OO
LT738
PP
LT1318
PP
LT1328
PP
LT1336
PP
5
LT1573
PP
50
LT1614
PP
PP
i
ii
iii
iv
QHR 581 B 3
LT738
1
LT1318
1
LT1328
1
LT1334
1
LT1336
1
LT1573
1
LT1614
1
QHR 250
1
LT1338
16
LT1577
5
LT1586
LT930
i
ii
v
iv
iv
v
ii
LT985
50
QHR 250
LT1238
34
QHR 581 B
PP
LT1340
38
LT1334
PP
Fig. 2. Clustering analysis of FAFLP data in comparison with that of the improved MLVA method.
clone (Fig. 4). Similarities in the clustering analysis were
present between the improved and the original MLVA
method, such as the geographical specificity of certain MVTs
to either the Innisfail or the Tully areas. The two dominant
clones, MVT1 and MVT28, showed remarkable geographical specificity for the Innisfail and Tully regions (Figs 2 and
3). The improved MLVA method allowed the examination
of the epidemiological links between the animal and human
Fig. 3. Distribution of MVTs in the Innisfail
region.
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1555
A. Slack and others
Fig. 4. Distribution of MVTs in the Tully
region.
isolates of L. interrogans serovar Australis. Using the
clustering analysis we could demonstrate strain clonality
between rodent isolates, human and rodent isolates, and also
rodent and canine isolates (Fig. 1a, b).
When population modelling was performed using the MST
algorithm (Fig. 5), all MVTs, with the exception of MVT21,
33, 39, 41 and 45, clustered together. MVT1 was considered
to be the progenitor clone, given that it had the highest
number of SLV isolates within the dataset. The population
modelling using MST paralleled the geographical proximity
of the isolates, with the majority of MVTs belonging to a
single, albeit quite diverse, complex (Fig. 5).
In conclusion, in this study we have described an improved
MLVA method for L. interrogans that utilizes novel primers
Fig. 5. MST population modelling of L.
interrogans serovar Australis based upon
MLVA data. The numbers shown are the
MVT numbers.
1556
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Journal of Medical Microbiology 55
Epidemiology of L. interrogans serovar Australis
and optimized PCR conditions for VNTR amplification,
and multiple fluorescent dye capillary electrophoresis to sort
and size the PCR products. This improved method was
found to be superior to the original method, and produced a
greater number of unique profiles when compared with
FAFLP analysis. Additionally, we were able to use the
improved MLVA method to redefine the molecular
epidemiology of L. interrogans serovar Australis, and
through clustering analysis we were able to demonstrate
strain clonality amongst rodent, canine and human isolates.
using PCR multiplexing and multi-colored capillary electrophoresis.
J Microbiol Methods 58, 213–222.
Lista, F., Faggioni, G., Valjevac, S. & 13 other authors (2006).
Genotyping of Bacillus anthracis strains based on automated capillary
25-loci multiple locus variable-number tandem repeats analysis.
BMC Microbiol 6, 33.
Rinehart, T. A. (2004). AFLP analysis using GeneMapper software
and an Excel macro that aligns and converts output to binary.
Biotechniques 37, 186–188.
Simpson, E. H. (1949). Measurement of diversity. Nature 163,
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Slack, A. T., Dohnt, M. F., Symonds, M. L. & Smythe, L. D. (2005).
ACKNOWLEDGEMENTS
The authors wish to thank Mr Shane Byrne for critically reviewing this
manuscript.
Development of a multiple-locus variable number of tandem repeat
analysis (MLVA) for Leptospira interrogans and its application to
Leptospira interrogans serovar Australis isolates from Far North
Queensland, Australia. Ann Clin Microbiol Antimicrob 4, 10.
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clonal are bacteria? Proc Natl Acad Sci U S A 90, 4384–4388.
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