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Previous Article | Next Article 
Journal of Clinical Microbiology, September 1998, p. 2404-2407, Vol. 36, No. 9
0095-1137/98/$04.00+0
Copyright © 1998, American Society for Microbiology. All rights reserved.
Study of the Relatedness of Isolates of
Shigella flexneri and Shigella sonnei Obtained in
1986 and 1987 and in 1994 and 1995 from Hong Kong
E. T. S.
Houang,1,*
Y.-W.
Chu,1
T.-K.
Ng,2 and
A. F. B.
Cheng1
Department of Microbiology, Chinese
University of Hong Kong, Prince of Wales
Hospital,1 and
Princess Margaret
Hospital,2 Hong Kong
Received 17 December 1997/Returned for modification 5 May
1998/Accepted 29 May 1998
 |
ABSTRACT |
We used pulsed-field gel electrophoresis (PFGE) to study the
genetic relatedness of 235 isolates of Shigella flexneri
and Shigella sonnei collected in Hong Kong (97 isolates
from 1986 and 1987 and 138 isolates from 1994 and 1995). Altogether, 13 gels were run with bacteriophage lambda ladder DNA (Pharmacia) as an
external reference in every sixth lane, standardized reagents and
methods, and isolates randomized for species and years. For quantitative illustration of the relationships within a large body of
isolates, computer-generated dendrograms were used to determine the
number of isolates in pulsotypes at Dice coefficients of similarity of
75% (PT75) and 50% (PT50). For S. flexneri, there was a significant difference in the distribution
of isolates collected during the two periods in both PT75
and PT50, with 68% of isolates collected in 1994 and 1995 sharing a coefficient of similarity of 
68%. For S. sonnei, a significant difference was observed in PT50
only. We also used Upholt's formula for an approximation of the
fraction of nucleotide difference between isolates and Molecular
Evolutionary Genetics Analysis to determine relative genetic distances.
For both species, the relative genetic distances between isolates of
the earlier collection period were significantly greater
(P < 0.0001), i.e., they were further apart and
therefore more diverse than those of the later period. We conclude that it is possible for a typical clinical laboratory to analyze a large
amount of PFGE information on Shigella isolates obtained under controlled conditions. Such data analysis should enhance surveillance capabilities and give indications of further work to be
done on various aspects of bacterial pathogenicity of the species.
| |
INTRODUCTION |
Infections caused by
Shigella spp. are major causes of diarrheal disease in both
developing and developed countries. We studied the antimicrobial
resistance of Shigella flexneri and Shigella sonnei isolates collected in Hong Kong from 1986 to 1995 and found that there was a significant increase in the proportion of S. flexneri isolates showing resistance to four or more agents. No such increase was seen in S. sonnei isolates (1).
There is little information on the genetic relatedness of
Shigella isolates correlated over time. We report here our
analysis of genetic relatedness based on data obtained by pulsed-field
gel electrophoresis (PFGE), which shows a greater genetic diversity for
both species among isolates obtained in 1986 and 1987 than among those
obtained 10 years later.
| |
MATERIALS AND METHODS |
Bacterial strains.
In total, we studied 63 S. flexneri isolates collected in 1986 and 1987 and 100 collected in
1994 and 1995 and 34 S. sonnei isolates collected in 1986 and 1987 and 38 collected in 1994 and 1995. Details of these isolates
were described by Chu et al. (1). The isolates were obtained
from clinical stool samples of individual patients at the Prince of
Wales Hospital or the Princess Margaret Hospital. For S. flexneri, the proportions of isolates resistant to ampicillin,
amoxicillin-clavulanate, chloramphenicol, tetracycline, trimethoprim,
or sulfamethoxazole were significantly higher in the 1994 to 1995 collection than in the 1986 to 1987 collection. One antibiogram showed
resistance to seven antimicrobials in 44 of the 1994 to 1995 isolates.
The proportions of S. sonnei isolates showing resistance to
four or more agents were not statistically different between the two
collections (1).
In addition to the isolates described above, three epidemiologically
linked isolates of S. flexneri of serotype II were obtained in 1996. These came from three separate stool samples received on the
same day from the same patient.
Serotyping.
Serotyping was carried out according to the
manufacturer's instructions (Denka Seiken, Tokyo, Japan).
PFGE.
PFGE was carried out as described by Kaufmann and Pitt
(7). Colonies were obtained from an overnight culture on
nutrient agar and were emulsified and suspended in sodium chloride-EDTA buffer to obtain a turbidity of about 1 × 109 CFU/ml.
PFGE genomic fingerprints were generated with a Clamped Homogeneous
Electric Fields electrophoretic apparatus (Mapper, BioRad). The
restriction enzyme XbaI was used to digest in situ the
agarose-embedded Shigella genomic DNA. Certified PFGE-grade
agarose from BioRad was used at 1% (wt/vol) for the electrophoretic
separation of the digested fragments. An electric field of 6 V/cm was
applied at an included field angle of 120° with pulsed time ramping
from 1 to 40 sec over 35 h. Tris-borate-EDTA buffer at half
strength (50 mM Tris, 40 mM borate, and 0.5 mM EDTA) was used as
running buffer and was maintained at 14°C. After electrophoresis, the gel was stained with ethidium bromide (1 µg/ml) for 10 min. The DNA
was visualized with a UV transilluminator, and images of the illuminated gels were digitized with a gel documentation device (Ultra
Violet Products Life Sciences, Cambridge, England). The images were
then processed with the GelCompar software (Applied Maths, Kortrijk,
Belgium). Dice coefficients of similarity were calculated as follows:
F = 2nxy/(nx + ny), where nx is the total number of fragments from isolate X,
ny is the total number of fragments from isolate
Y, and nxy is the number of fragments
shared by the two isolates. Comparison matrices were generated, and
dendrograms were constructed by the unweighed pair group method with
arithmetic averages (UPGMA).
Bacteriophage lambda ladder DNA (Pharmacia) was used as an external
reference in every sixth lane, and all test fingerprint images were
accordingly normalized. Individual gels contained randomly chosen
isolates obtained in different years and representing both
Shigella species. The additional three epidemiologically linked isolates from the same patient were included on two different gels. The same batches of agarose gel, chemicals for buffers, lambda
ladder, and restriction enzyme were used throughout the study.
Inference of relatedness.
The approximate degree of
nucleotide sequence similarity of chromosomal DNA in the S. flexneri and S. sonnei isolates was examined with the
computer programs GelCompar (see above) and Molecular Evolutionary
Genetics Analysis (MEGA), version 1.01 (8).
The relative genetic distances between isolates were estimated by using
the modification of the methods of Nei and Li (15) and
Upholt (21) applied by El-Adhami et al. (2) and
Jorgensen et al. (6). GelCompar constructed the matrix based
on the Dice coefficients of similarity. The fraction of nucleotide
difference between isolates was then calculated by using Upholt's
formula: p = 1 
{[(F2 + 8F)1/2 F]/2}1/n, where F is the Dice
coefficient of similarity and n has a value of 6 for
XbaI (21). The MEGA program was used on the
pair-wise matrix of p values to draw a dendrogram by
the neighbor-joining method (17). The relative genetic
distances (P) between isolates collected during the same period were
calculated by adding together the successive internodal values obtained
by MEGA. The distribution of P values for the two collection periods
were compared by the Mann-Whitney U test (SPSS).
| |
RESULTS |
Of the 63 S. flexneri isolates from 1986 and 1987, 21 were serotype I, 31 were serotype II, 9 were serotype III, 1 was
serotype IV, and 1 was serotype VI. Of the 100 S. flexneri isolates from 1994 and 1995, 3 were serotype I, 90 were serotype II, 4 were serotype III, and 3 were serotype
IV. The number of serotype II isolates increased significantly from
49% (31 of 63) among the isolates from 1986 and 1987 to 90% (90 of
100) among the isolates from 1994 and 1995 (chi-square test,
P < 0.001).
Altogether, 10 gels with 20 to 24 test lanes and five to six lambda
ladders and 3 gels with 12 test lanes and three lambda ladders were
run. Of the 67 lanes of lambda DNA, 1 lane from each of 7 gels was not
included as a reference track because of an unsatisfactory image. Of
the remaining 60 lanes, 59 shared a coefficient of similarity of 90%
and 1 shared 85%. These 60 lanes were used as reference tracks for
both Shigella species. Figures
1 and
2 are the dendrograms of S. flexneri and S. sonnei, respectively, constructed
with GelCompar. Two of the three S. flexneri isolates from 1996 clustered at 100% on the same gel and at 90% with their duplicates on a separate gel. All three isolates clustered with their
duplicates at 85% (Fig. 1).
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FIG. 1.
Dendrogram based on Dice coefficients of similarity for
100 S. flexneri isolates collected in 1994 and 1995 and
63 collected in 1986 and 1987, together with duplicates of the 3 isolates collected in 1996. The
dendrogram was constructed by UPGMA (GelCompar). Asterisks in column A
and column B indicate isolates collected in 1994 and 1995 and those
collected in 1986 and 1987, respectively. The bracketed isolates (C)
are duplicates of the three 1996 isolates.
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FIG. 2.
Dendrogram based on Dice coefficients of similarity for
34 S. sonnei isolates collected in 1986 and 1987 and 38 isolates collected in 1994 and 1995. The dendrogram was constructed by
UPGMA (GelCompar). Asterisks in column A and column B indicate isolates
collected in 1994 and 1995 and those collected in 1986 and 1987, respectively.
|
|
Isolates that showed a coefficient of similarity 75% (a
difference of four bands) were grouped as one pulsotype
(PT75) and labeled numerically. Similarly, those showing a
coefficient of similarity 50% (a difference of seven to eight bands
or more) were grouped as one pulsotype and labeled PT50s.
Table 1 shows the distribution of
S. flexneri isolates and their corresponding serotypes in different PT75s. With two exceptions, all
PT75s contained one serotype only. Comparing the
distribution of isolates from the two collection periods, there was a
significant difference in PT75s as well as in
PT50s (Mann-Whitney U test, P = 0.0001). Of
the 27 PT75s among the isolates from 1994 and 1995, PT75s 1, 2, and 4 contained 67 of the 100 isolates, sharing
a coefficient of similarity of 68% (a difference of four to five
bands) (Fig. 1). Of the 44 isolates from 1994 and 1995 showing the same
pattern of antimicrobial resistance to seven agents (1), 36 (82%) were also found in these three PT75s. For
S. sonnei isolates, a similar comparison shows there
was a significant difference in the distribution of isolates in
different pulsotypes in PT50 only (P = 0.0007) (Table 2).
The relative genetic distances of isolates from the two collection
periods were calculated as described above and were compared. For
S. flexneri isolates, the mean relative genetic
distance for those collected in 1986 and 1987 was 0.016 and the 90th
percentile was 
0.089. The corresponding figures for isolates
collected in 1994 and 1995 were 0.013 and 0.045 (P < 0.0001), respectively. Because of the large number of isolates from
1994 and 1995 in PT75s 1, 2, and 4, the analysis was also
performed with the 67 isolates in these three groups excluded.
The significant difference between the two collections remained
(P < 0.0001). For S. sonnei, the mean
relative genetic distance for isolates from 1986 and 1987 was 0.046, and the 90th percentile was 0.078. The corresponding figures
for isolates collected in 1994 and 1995 were 0.030 and 0.044 (P < 0.001), respectively. For both species, the
relative genetic distances between isolates of the earlier collection
period were significantly larger and therefore more diverse than those of the later period.
| |
DISCUSSION |
For the estimation of chromosomal genotypic diversity and
relationships, methods commonly used by population geneticists include multilocus enzyme electrophoresis to examine protein polymorphisms or
nucleotide sequencing of selected genes to examine DNA polymorphisms (9). These techniques are not readily performable in a
typical clinical laboratory like ours which nonetheless has collected and typed a substantial number of human pathogens over the years for
the investigation of outbreaks of infections. For these investigations, PFGE is now accepted as an effective tool (13). With the
introduction of bench top PFGE apparatuses and computer programs to
handle large numbers of gel images, it may be possible for typical
clinical laboratories, particularly in collaboration with each other,
to consider what Tibayrenc labeled long-term epidemiology of the species (country- or continent-wide investigations lasting months or
years) (20). Such investigations may contribute to studies of pathogenicity, resistance to drugs, adaptative significance, immunological patterns, and vector and host specificity of microbial genetic diversity (20). It will be interesting to see
whether digital networking can further enhance surveillance in
different locations.
During an outbreak of infection, the aim of bacterial typing is to
provide laboratory evidence that epidemiologically related isolates are
also genetically related. For this purpose, PFGE should be applied to
small sets of isolates (typically 30) that are epidemiologically
related (19). In this study, we investigated the relatedness
of a large number of isolates collected 10 years apart and used PFGE to
distinguish strains at the coefficient of similarity of <50% (showing
a difference of seven to eight bands or more and representing three or
more independent genetic events) (19). The isolates were
obtained from symptomatic patients over a period of 24 months by the
same laboratories serving the same population. Detailed epidemiological
information normally collected in the investigation of individual
outbreaks of infection is not relevant to an investigation such as
ours, which looks at the long-term epidemiology.
We used Upholt's formula to obtain an approximation of the fraction of
nucleotide difference between isolates and MEGA to obtain relative
genetic distances so that a quantitative comparison of the
relationships among a large body of isolates could be made. The
p values obtained should not be seen as precise quantitative estimates of genetic distances. As pointed out by El-Adhami et al., one
of the important assumptions inherent in this type of analysis is that
the changes seen in the fragment sizes and numbers result from simple
point mutations which change endonuclease recognition sites.
Insertions, deletions, or transpositions are not theoretically accommodated in the calculations (2). The relatedness of
the bacteria may be further ascertained by using several restriction enzymes in PFGE, as has been demonstrated through the analysis of
Pseudomonas species (4).
The careful control that should be exercised during PFGE cannot be
overemphasized. We standardized reagents and methods of preparation
and randomized isolates for the species and the year. We used five to
six lanes of lambda ladder on each gel as reference tracks. Ideally,
DNA plugs of a suitable control strain, prepared as a single batch,
should also be included in each gel (19).
Of the 100 isolates of S. flexneri collected in 1994 and 1995 67 (65%) were found in three PT75s which shared a
coefficient of similarity at 68% and included 82% of the 44 isolates with the same pattern of resistance to seven antimicrobials
(1). This suggests that they may have belonged to the same
clone(s). A small number of the 1994 and 1995 isolates (10%) shared
the same PT75s (pulsotypes 5, 6, 9, and 14) with some of
the 1986 and 1987 isolates (Table 1). Further work, however, is
necessary to confirm such parentages. It should also be borne in mind
that over time there is an opportunity for isolates of the same
parentage to exhibit differences in phenotypic or actual genotypic
variations.
With two exceptions, individual PT75s contained only one
serotype of S. flexneri (Table 1). Comparison of
serotypes and ribotypes showed that different ribotypes belonged to
the same serotype but also that similar ribotypes might belong to
different serotypes (3). PFGE has also been used
successfully to identify genetic subtypes among small numbers of both
epidemiologically related and unrelated S. sonnei and
S. flexneri isolates (12, 18). Other genetic
methods have been used, and the extent of genetic variability varied
with the molecular method used (3, 5, 10, 11, 14, 16).
Our results demonstrate that it is possible to analyze a large amount
of PFGE information about Shigella isolates when it is
obtained under controlled conditions. It remains to be seen whether
intra- or interlaboratory results of PFGE from typical clinical
laboratories could become comparable through the use of carefully
standardized procedures. Such data would enhance surveillance and
give indications for further work on various aspects of bacterial
pathogenicity as suggested by Tibayrenc (20).
| |
ACKNOWLEDGMENT |
This project was supported by grant 2040496 from the University
Research Grants Council, Hong Kong.
| |
FOOTNOTES |
*
Corresponding author. Mailing address: Department of
Microbiology, Chinese University of Hong Kong, Prince of Wales
Hospital, Shatin N.T., Hong Kong. Phone: (852) 2632 3333. Fax: (852)
2647 3227. E-mail: ehouang{at}cuhk.edu.hk.
| |
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Journal of Clinical Microbiology, September 1998, p. 2404-2407, Vol. 36, No. 9
0095-1137/98/$04.00+0
Copyright © 1998, American Society for Microbiology. All rights reserved.
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Abstract
Introduction
