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Journal of Clinical Microbiology, January 2001, p. 75-85, Vol. 39, No. 1
0095-1137/01/$04.00+0 DOI: 10.1128/JCM.39.1.75-85.2001
Evaluation of Pulsed-Field Gel Electrophoresis in Epidemiological
Investigations of Meningococcal Disease Outbreaks Caused by
Neisseria meningitidis Serogroup C
Tanja
Popovic,1,*
Susanna
Schmink,1
Nancy A.
Rosenstein,1
Gloria W.
Ajello,1
Michael W.
Reeves,1
Brian
Plikaytis,2
Susan B.
Hunter,3
Efrain M.
Ribot,3
David
Boxrud,4
Maria L.
Tondella,5
Chung
Kim,1
Corie
Noble,1
Elizabeth
Mothershed,1
John
Besser,4 and
Bradley
A.
Perkins1
Meningitis and Special Pathogens
Branch,1 Biostatistics and Information
Management Branch,2 Foodborne and
Diarrheal Diseases Branch,3 and
Respiratory Diseases Branch,5 Division
of Bacterial and Mycotic Diseases, National Center for Infectious
Diseases, Centers for Disease Control and Prevention, Atlanta,
Georgia, and Minnesota Department of Health, Minneapolis,
Minnesota4
Received 26 June 2000/Returned for modification 20 August
2000/Accepted 6 October 2000
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ABSTRACT |
Since 1990, the frequency of Neisseria meningitidis
serogroup C (NMSC) outbreaks in the United States has increased. Based on multilocus enzyme electrophoresis (MEE), the current molecular subtyping standard, most of the NMSC outbreaks have been caused by
isolates of several closely related electrophoretic types (ETs) within
the ET-37 complex. We chose 66 isolates from four well-described NMSC
outbreaks that occurred in the United States from 1993 to 1995 to
evaluate the potential of pulsed-field gel electrophoresis (PFGE) to
identify outbreak-related isolates specific for each of the four
outbreaks and to differentiate between them and 50 sporadic isolates
collected during the outbreak investigations or through active
laboratory-based surveillance from 1989 to 1996. We tested all isolates
collected during the outbreak investigations by four other molecular
subtyping methods: MEE, ribotyping (ClaI), random amplified
polymorphic DNA assay (two primers), and serotyping and serosubtyping.
Among the 116 isolates, we observed 11 clusters of 39 NheI
PFGE patterns. Excellent correlation between the PFGE and the
epidemiological data was observed, with an overall sensitivity of 85%
and specificity of 71% at the 95% pattern relatedness breakpoint using either 1.5 or 1.0% tolerance. For all four analyzed outbreaks, PFGE would have given public health officials additional support in
declaring an outbreak and making appropriate public health decisions.
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INTRODUCTION |
Studies in the areas of population
biology, pathogenesis, epidemiology, and molecular microbiology have
demonstrated the clonal nature of relationships among Neisseria
meningitidis isolates. While some clones have been isolated
repeatedly, spanning long periods of time and from multiple locations
throughout the world, others have been isolated rarely and then only
from certain geographic areas. Meningococci associated with epidemics
and outbreaks generally belong to uniform clonal groups, in contrast to
meningococci causing sporadic disease, which are more variable
(1). Multilocus enzyme electrophoresis (MEE) has been
proven to be a suitable method to detect such clones and therefore has
been the "gold standard" for molecular subtyping of N. meningitidis for over two decades (5, 19). Molecular
subtyping of isolates may provide useful information in determining
whether a group of cases actually represents an outbreak or simply
represents a change in the incidence of sporadic cases. Even though the
annual incidence of meningococcal disease caused by all serogroups in
the United States has remained stable at 1/100,000 to 1.5/100,000 over
the past 30 years, since 1990 the number of N. meningitidis serogroup C (NMSC) outbreaks has increased (11,
21; C. R. Woods, N. E. Rosenstein, and B. A. Perkins, Abstr. 38th Annu. Meet. Infect. Dis. Soc. Am., abstr. 125FR,
1998). In the United States a threshold attack rate is used to
differentiate outbreaks from sporadic meningococcal disease cases and
serves as the basis for initiation of mass vaccination campaigns
(6). Most of the NMSC outbreaks in the United States have
been caused by isolates of the closely related electrophoretic types
(ETs) within the ET-37 complex, but the same ETs are also commonly
found in endemic isolates. Also, MEE is labor-intensive, time-consuming, and difficult for interlaboratory comparison and therefore is limited to very few laboratories that currently maintain this capacity. Recently, pulsed-field gel electrophoresis (PFGE), being
rapid and easy to perform, has been successfully applied to the
molecular subtyping of numerous bacteria (24). It
currently serves as the basis for the PulseNet, a network for
nationwide monitoring of several food-borne disease pathogens, such as
Escherichia coli O157:H7, Salmonella spp.,
Listeria monocytogenes, and Shigella sonnei.
Reports on the use of PFGE to differentiate isolates of N. meningitidis of serogroups A and B (4, 13, 14, 25, 29) indicate that, especially for serogroup B, PFGE provides a
substantial level of discrimination comparable to that of ribotyping and better than those of serosubtyping, MEE, and PCR-restriction fragment length polymorphism analysis. However, the epidemiology of
meningococcal disease associated with serogroups A and B differs from
that of disease associated with NMSC. N. meningitidis
serogroup A has long been the main cause of meningococcal disease
outbreaks worldwide, especially in the African "meningitis belt."
It has been associated with a particular clonal group, identified by MEE as subgroup III-1, and with only a few PFGE patterns identified over extended periods of time. In contrast, N. meningitidis
serogroup B has demonstrated the most diversity of all serogroups, with over 1,000 ETs identified to date. Due to that diversity and to the
fact that in the United States it is mainly associated with sporadic
meningococcal disease, PFGE analysis would not be particularly useful
for epidemiological purposes. PFGE has been used as a tool to
molecularly characterize NMSC isolates from sporadic cases of
meningococcal disease and in NMSC outbreak investigations (3, 7,
8, 18, 28; T. L. Bannerman, K. B. Sohner, S. Karam, S. Nowicki, Abstr. 99th Gen. Meet. Am. Soc. Microbiol., abstr. C-396, p. 186, 1999; R. Danila, R. Rainbow, D. Boxrud, J. Besser, K. Moore, M. Osterholm, Abstr. 39th Intersci. Conf. Antimicrob. Agents Chemother., abstr. L-2094, p. 691, 1999). However, isolates from a single outbreak either have not been analyzed along with isolates from sporadic cases or have not been extensively compared with
the epidemiological data.
We chose four well-described NMSC outbreaks occurring from 1993 to 1995 in Texas, New Mexico, Arizona, and California (15, 22, 26)
to systematically evaluate the potential of PFGE to identify
outbreak-associated isolates. We also included in the study 26 NMSC
isolates, representing sporadic disease in the United States, collected
through the active laboratory-based surveillance program from 1989 to
1996. Since an outbreak is defined based on the epidemiological
criteria and supported by the current gold standard for subtyping, MEE,
we assayed all isolates by MEE as well. To further assess the
relative differentiation capabilities of PFGE, we tested all
isolates collected during the outbreak investigations by three
additional molecular subtyping methods: ribotyping, serotyping and
serosubtyping, and random amplified polymorphic DNA (RAPD) assay.
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MATERIALS AND METHODS |
Serogroup C meningococcal disease (SCMD) outbreaks.
An
outbreak is defined, by the Advisory Committee on Immunization
Practices of the Centers for Disease Control and Prevention (CDC), as
an occurrence of three or more confirmed or probable cases of
meningococcal disease during a period of <3 months in persons who have
a common affiliation but no close contact with one another (an
organization-based outbreak) or in persons residing in the same
area who are not close contacts and who do not share a common
affiliation (a community-based outbreak), resulting in a primary
disease attack rate of at least 10 cases per 100,000 persons
(6). A total of 90 isolates were collected during the investigations of four well-defined NMSC outbreaks. Epidemiological information was solicited from state and local health authorities as
well as from CDC investigators, and all available reports concerning these outbreaks were reviewed. Isolates epidemiologically defined as
being a part of a particular outbreak will be referred to as outbreak-associated, isolates, while those that were identified as not
being part of an outbreak will be referred to as sporadic isolates. For
easy reference, the prefix OA or SP, respectively, is used as part of
each isolate's designation.
(i) Texas.
Between 14 February 1993 and 2 September 1995, 41 cases of meningococcal disease were reported in Gregg County, Tex.
(22). We analyzed isolates from 26 of these
outbreak-associated cases and nine additional isolates from sporadic
cases throughout Texas from 1995 to 1996.
(ii) New Mexico.
Between 2 and 16 March 1994, seven
confirmed cases of meningococcal disease occurred in five rural New
Mexico communities, yielding an attack rate of 200 per 100,000 persons
(15). In addition to the seven isolates epidemiologically
defined as outbreak associated, we included in this study five isolates
from patients with sporadic meningococcal disease in New Mexico
isolated in the same year.
(iii) Arizona.
We included a total of 23 isolates from cases
of SCMD from Maricopa County, Ariz., collected in 1993 and 1994. Using
a combination of epidemiological data and PFGE analysis (carried out
with a different restriction enzyme) at the Arizona State Health
Department, 19 of the isolates were identified as outbreak associated
and four were identified as sporadic isolates from other geographic locations in Arizona.
(iv) California.
Between 1 January and 31 March 1993, 54 cases of meningococcal disease occurred in Los Angeles County, Calif.;
45 were among community residents and 9 were in inmates in the
county's jail system (26). In this study we included 10 isolates from nine inmates (OA29, OA30, OA31, OA32, OA33, OA140, OA141,
OA145, OA148, and OA149), 4 isolates from community residents with
reported contact with inmates (OA34, OA147, OA151, and OA152), and 6 isolates from community residents with no contact with inmates (SP128, SP131, SP143, SP144, SP146, and SP153).
(v) Active surveillance.
Population-based surveillance for
invasive disease caused by N. meningitidis is part of an
ongoing multistate active surveillance project coordinated by the CDC.
Between 1989 and 1996, CDC collaborated on active surveillance with
investigators in state and local health departments or universities in
as many as seven geographically dispersed areas of the United States
with an aggregate population of 22 million. A surveillance case of
meningococcal disease was defined as the isolation of N. meningitidis from a normally sterile site, such as blood or
cerebrospinal fluid, in a resident of a surveillance area, and 807 cases of meningococcal disease were detected, for an average annual
incidence of 1.1/100,000 persons during this period. Twenty-six
isolates were selected randomly to represent a temporal and geographic
distribution of all isolates, and these will be consistently referred
to as surveillance isolates, with the prefix SU as part of the isolate designation.
Laboratory methods.
All isolates of N. meningitidis were characterized at CDC using standard
microbiological procedures (16). Initial serogrouping was
done at hospital microbiology laboratories or at state health departments, and the serogrouping was then repeated at CDC.
(i) PFGE.
The PFGE method used in this study is based upon
procedures for testing E. coli O157:H7 as described by
Barrett et al. (2) and by Gautom (9).
Deviations from the published protocols are as follows. Overnight
growth from a sheep blood agar plate was harvested with a 1-µl
disposable loop. The loop was gently rubbed against the side wall of a
test tube containing 2 ml of cell suspension buffer, followed by gentle
mixing to result in a final suspension with a reading of 0.48 to 0.52 in a Dade Microscan turbidity meter. Plugs were prepared with 400 µl
of cell suspension, 20 µl of a 2% proteinase K solution (Amresco,
Solon, Ohio), and an equal volume of 1% SeaKem Gold-1% sodium
dodecyl sulfate-agarose and dispensed into reusable plug molds.
Incubation for 1.5 to 2 h in a shaker water bath at 50 to 54°C
range allowed for lysing the cells of one plug in a 2-ml round-bottom
tube containing 1.5 ml of cell lysis buffer. After washing of the
plugs, microtubes containing endonuclease NheI diluted in
restriction buffer to 50 U per plug slice were incubated in a 37°C
water bath for 1.5 to 2 h. Restricted plug slices were placed at
the bottom of each tooth of a 10-tooth comb and submerged in 95 ml of
molten 1.0% SeaKem Gold agarose in 0.5× Tris-borate-EDTA buffer until
the gel hardened. After comb removal, the wells were sealed with molten agarose and the gel was placed in the prepared electrophoresis chamber.
Electrophoresis conditions were as follows: chamber, CHEF-DR III
(Bio-Rad Laboratories, Hercules, Calif.) containing 2 liters of freshly
prepared 0.5× Tris-borate-EDTA buffer cooled to 14°C, initial switch
time, 2.2 s; final switch time, 35 s; duration of run,
18 h, angle, 120°; gradient, 6 V/cm with a linear ramping factor.
For data analysis, Tiff images of the gels were normalized using the
Molecular Analyst Fingerprinting Plus software, version 1.11 (Bio-Rad
Laboratories), by aligning the standard NMSC isolate (M413), located in
lanes 1, 5, and 10 of each gel, with the global standard for the
database (M413). Isolates were tested two times and bands that were
faint, not consistent on repeat testing of the isolate, and larger than
the largest band on the standard were not included in the analysis.
Analysis of band patterns was performed with the Dice coefficient using
0.5, 1, and 1.5% tolerances for the band migration distance. Patterns
were defined as indistinguishable using the Molecular Analyst software
if the patterns had the same number of marked bands and if the band
positions were within 2, 4, or 6 points of each other for a 0.5, 1.0, or 1.5% tolerance, respectively. All patterns were visually inspected
after computer analysis. Patterns that were identified as
indistinguishable by the computer and were indistinguishable after
visual inspection were assigned a pattern designation. Four exceptions
were seen where patterns were identified as indistinguishable by the
computer but were visually distinguishable after inspection. These
patterns were assigned a different designation. PFGE patterns were
designated using the organism, enzyme, and pattern number scheme
recommended by the CDC PFGE committee and used by PulseNet. Clustering
of patterns was performed by unweighted pair group with arithmetic averaging (UPGMA). The percentage of similarity between patterns is
used only to address the relatedness among the PFGE patterns and is not
an indication of (quantitative) genetic relatedness among respective
isolates, a measurement that can be appropriately determined by other
techniques such as MEE.
(ii) MEE.
MEE, using 24 enzymes, was performed as described
previously (23). Numbers were assigned to enzyme alleles
on the basis of enzyme mobilities, and each unique set of alleles was
defined as an ET. An index of genetic relatedness was determined by
weighting the degree of diversity at each of the 24 enzyme loci, and
similarities among the ETs were assessed by dendrogram analysis
(12).
(iii) RAPD assay.
The RAPD assay was carried out as
described previously (S. E. Schmink, M. W. Reeves, B. Plikaytis, and T. Popovic, submitted for publication).
(iv) Serotyping and serosubtyping.
The meningococcal
isolates were tested with a set of 15 monoclonal antibodies (MAbs)
against the variable regions of PorB outer membrane proteins
(serotyping) and against 15 murine MAbs produced against the variable
regions of PorA outer membrane proteins (serosubtyping) by dot blot
analysis as previously described (27). Briefly, the
whole-cell suspensions were dotted on nitrocellulose, and strips were
blocked for 30 min using bovine serum albumin (3% in
phosphate-buffered saline). MAbs were pipetted into the blocking buffer
at dilutions ranging from 1 in 4,000 to 1 in 32,000. After overnight
incubation, the strips were incubated for 2 h with goat anti-mouse
immunoglobulin G conjugated to peroxidase (1 in 4,000) (Sigma, St.
Louis, Mo.) and developed with the substrate 3-amino-9-ethylcarbazole
(Sigma) and hydrogen peroxidase. MAbs against serotypes 2a (5D4-5), 2b
(2H10-2), 2c (6-D9-5.6-F3), 4 (5DC4-C8-G8), 5 (7BG5-H2), 11 (9-1-P11),
15 (8-B5-5-B9), and 21 (6B11-C2-F1) and serosubtypes P1.2 (OD6-4), P1.3
(5G8-B2-F9), P1.16 (OF11-4), and P1.19 (7A2-11) were supplied by
W. D. Zollinger, Walter Reed Army Medical Center, Washington, D.C.
MAbs against serotypes 1 (MN3C6B) and 14 (MN5C8C) and serosubtypes P1.1
(MN14C2.3), P1.4 (MN20B9.34), P1.5 (MN22A9.19), P1.6 (MN19D6.13), P1.7
(MN14C11.6), P1.9 (MN5A10.7), P1.10 (MN20F4.17), P1.12 (MN20A7.10),
P1.13 (MN25H10.75), P1.14 (MN21G3.17), and P1.15 (95-718) were supplied
by I. M. Feavers, National Institute for Biological Standards and
Control, Herts, United Kingdom. MAbs against serotypes 7 (F22-8B5/1D10), 9 (F24-11F5/3B4), 10 (F11-6D12/1C5), and 17 (F4-3C1/1A6) were provided by C. T. Sacchi, Institute Adolfo Lutz,
San Paulo, Brazil. MAb against serotype 22 (IA5D90) was supplied by P. Kriz, National Institute of Public Health, Prague, Czech Republic.
Ribotyping.
Ribotyping was performed as previously described
(17) with the following modifications. DNA was extracted
from the isolates using the Puregene DNA isolation kit (Gentra Systems,
Inc., Minneapolis, Minn.) according to the manufacturer's
instructions. The extracted DNA was restricted using ClaI at
37°C for 4 h. Hybridization was performed using a mixture of
five oligonucleotide probes as described by Renault et al.
(20).
 |
RESULTS |
A total of 116 NMSC isolates were included in this study. Of 90 isolates collected during the investigations of four epidemiologically well-defined outbreaks of SCMD, 66 were epidemiologically defined as
outbreak associated, while the remaining 24 were from sporadic cases of
meningococcal disease. An additional 26 isolates were from the
laboratory-based surveillance.
Texas.
Among the 35 isolates from Texas (26 outbreak
associated and nine sporadic), two distinct PFGE clusters composed of
seven PFGE patterns were identified, with 85% overall relatedness
(Fig. 1). The larger cluster contained 27 isolates and two very similar PFGE patterns (96% relatedness).
Twenty-two of the 26 outbreak-associated isolates had indistinguishable
PFGE patterns (H46N06.0004), which they shared with four sporadic
isolates. In addition, these 22 outbreak-associated isolates were
either of ET-24 (20 isolates) or of ET-164 (2 isolates). There is
only a single enzyme difference between these two ETs. Pattern
H46N06.0005, seen in isolate OA1968, differed from the
predominant H46N06.0004 pattern by a single band. The smaller cluster
contained eight isolates and five PFGE patterns. Three isolates
(OA1953, OA1956, and OA1957) were epidemiologically identified as part
of the outbreak, while the remaining five were isolated from sporadic
cases of meningococcal disease in Texas. Two of these three
outbreak-associated isolates (OA1953 and OA1957) had an H46N06.0008
pattern indistinguishable from that of two sporadic isolates
(SP786 and SP2836). The H46N06.0008 pattern showed only 85%
relatedness to the predominant H46N06.0004 pattern. ET-163,
identified in isolates OA1953 and OA1957, differed from ET-24, seen in
the outbreak-associated isolates, in a single enzyme (relatedness
between these two ETs was >98%). Patterns of two sporadic isolates,
SP2835 and SP3039, were identified as indistinguishable in the computer
analysis, but visual inspection showed spacing differences between
bands in these two isolates. The pattern of isolate SP2835 was
designated H46N06.0011 and the pattern of isolate SP3039 was designated
H46N06.0031. This is one of four exceptions made in the assigning of
patterns.

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FIG. 1.
Designations, molecular characterization, and PFGE
analysis (with NheI) of chromosomal DNAs of 35 NMSC isolates
collected during an investigation of a meningococcal disease outbreak
in Texas in 1995. The PFGE patterns of isolates SP2835 and SP3039 were
identified as indistinguishable using the 1.5% tolerance, but based on
visual differences in spacing between the bands, isolate SP3039 was
defined as distinct and was given a pattern designation of H46N06.0031
(asterisk). ID, isolate identification number; ST/SST, serotype and
serosubtype; RT, ribotype; RAPD, RAPD type (with two primers).
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New Mexico.
Analysis of the 12 New Mexico isolates resulted in
three separate clusters of PFGE patterns at the 85% relatedness
breakpoint (Fig. 2). One cluster
contained only a single PFGE pattern (H46N06.0023), which was
identified in all seven outbreak-associated isolates. These
isolates also had identical ETs (ET-17), identical serotype and
serosubtype, and identical RAPD types. The five sporadic isolates were grouped within the two remaining PFGE clusters. The first sporadic cluster had four PFGE patterns (H46N06.0004,
H46N06.0038, H46N06.0002, and H46N06.0013). Isolates SP1530 and SP1531,
with patterns H46N06.0004 and H46N06.0038 (identified as
indistinguishable by the computer analysis but defined as different
upon visual inspection, based on band spacing differences), were
distinguishable from the New Mexico outbreak-associated isolates by MEE
(SP1531) or ribotyping and RAPD analysis (SP1530). Another isolate
within this cluster (SP1541) with an unique PFGE pattern (H46N06.0013) had an ET, serotype and serosubtype, and RAPD type identical to those
of the outbreak-associated isolates. A fourth sporadic isolate (SP1533)
in this cluster had a unique PFGE pattern (H46N06.0002), but its ET,
serotype and serosubtype, and ribotype were indistinguishable from
those of the outbreak isolates. The second sporadic cluster contained only a single isolate (SP1532), whose H46N06.0033 pattern showed less than 65% relatedness with all other PFGE patterns. Results
from the other molecular subtyping methods also suggested that this
isolate was unique.

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FIG. 2.
Designations, molecular characterization, and PFGE
analysis (with NheI) of chromosomal DNAs of 12 NMSC isolates
collected during an investigation of a meningococcal disease outbreak
in New Mexico in 1994. The PFGE patterns of isolates SP1530 and SP1531
were identified as indistinguishable using the 1.5% tolerance, but
based on visual differences in spacing between the bands, isolate
SP1531 was defined as distinct and given a pattern designation of
H46N06.0038 (asterisk). ID, isolate identification number; ST/SST,
serotype and serosubtype; RT, ribotype; RAPD, RAPD type (with two
primers).
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Arizona.
Among the 23 isolates from the Arizona outbreak
investigation, four PFGE pattern clusters were identified at the 85%
relatedness level (Fig. 3). The largest
cluster contained 19 isolates and four PFGE patterns; 14 of the 19 outbreak-associated isolates had pattern H46N06.0026. Ten of these 14 isolates were ET-17. The other four isolates had three different ETs,
which differed from ET-17 by three or four enzymes. Results from
serotyping and serosubtyping, ribotyping, and RAPD analysis gave
indistinguishable results for all 14 isolates. The remaining three PFGE
patterns of this cluster were identified in five isolates: pattern
H46N06.0023 was identified in OA800, OA801, and SP418; pattern
H46N06.0024 was identified in OA416; and pattern H46N06.0025 was
identified in OA632. The results from the molecular subtyping for
OA800, OA632, and SP418 were identical to the results for isolates with the H46N06.0026 pattern, while OA801 and OA416 differed from the isolates with the H46N06.0026 pattern only in their ribotype. The final
four isolates, SP638, OA160, SP415, and SP414, had four different PFGE
patterns, which were related to the H46N06.0026 pattern by less than
78%. Isolates SP638 and OA160 were identified as indistinguishable by
the computer analysis but after visual inspection were assigned
patterns H46N06.0001 and H46N06.0037 due to spacing differences
between bands. These four isolates had molecular markers that were
diverse and in unique, individual combinations.

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FIG. 3.
Designations, molecular characterization, and PFGE
analysis (with NheI) of chromosomal DNAs of 23 NMSC isolates
collected during an investigation of a meningococcal disease outbreak
in Arizona in 1993 to 1994. The PFGE patterns of isolates SP638 and
OA160 were identified as indistinguishable using the 1.5% tolerance,
but based on visual differences in spacing between the bands, isolate
OA160 was defined as distinct and given a pattern designation of
H46N06.0037 (asterisk). ID, isolate identification number; ST/SST,
serotype and serosubtype; RT, ribotype; RAPD, RAPD type (with two
primers).
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California.
Among the 20 isolates tested, 15 isolates had
pattern H46N06.0001 (Fig. 4). Eight of
those isolates were from inmate cases, four were from community cases
with reported contact with the inmates (OA34, OA147, OA151, and OA152),
and three were from community cases with no reported contact with the
inmates (SP131, SP146, and SP153). With two exceptions (SP153 and
SP131), 13 of the isolates were also indistinguishable as defined by
the four other molecular subtyping methods (MEE, serotyping and
serosubtyping, ribotyping, and RAPD assay). The PFGE patterns of the
remaining five isolates were 84% similar to the PFGE patterns of the
outbreak-associated isolates. Two of these five isolates were
substantially different by both PFGE and all other molecular subtyping
methods. These two were isolated from community cases without contact
with the inmates (SP128 and SP144). The PFGE patterns of the three
additional isolates (OA29, OA30, and SP143) were closer to the
H46N06.0001 pattern of the outbreak-associated isolates (but still less
than 85% related) and had all other molecular markers identical to those of the outbreak-associates isolates.

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FIG. 4.
Designations, molecular characterization, and PFGE
analysis (with NheI) of chromosomal DNAs of 20 NMSC isolates
collected during an investigation of a meningococcal disease outbreak
in California in 1993. ID, isolate identification number; ST/SST,
serotype and serosubtype; RT, ribotype; RAPD, RAPD type (with two
primers).
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Surveillance isolates.
Among the 26 surveillance isolates, 22 different PFGE patterns in eight clusters (at 85% relatedness) were
identified (Fig. 5). No specific
geographic or temporal grouping was observed. Patterns of two
surveillance isolates, SU680 and SU810, were defined as distinguishable
upon visual inspection (based on the spacing between two mid-sized
bands) and designated H46N06.0017 and H46N06.0039, respectively, even
though they were defined as indistinguishable by computer analysis.

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FIG. 5.
Designations, molecular characterization, and PFGE
analysis (with NheI) of chromosomal DNAs of 26 NMSC isolates
collected from sporadic cases of meningococcal disease through active
laboratory-based surveillance, 1989 to 1996. The PFGE patterns of
isolates SU680 and SU810 were identified as indistinguishable using the
1.5% tolerance, but based on visual differences in spacing between the
bands, isolate SU810 was defined as distinct and given a pattern
designation of H46N06.0039 (asterisk). ID, isolate identification
number. GA, Georgia; CT, Connecticut; TN, Tennessee; CA, California;
OK, Oklahoma; MN, Minnesota; MO, Missouri; MD, Maryland; OR, Oregon.
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Overall analysis.
Among our 116 isolates, 39 PFGE patterns
were identified, 35 by the computer analysis and 4 additional ones
based on the visual inspection, due to the differences in spacing
between particular bands. At the 85% relatedness breakpoint they
formed 11 clusters. Six of the clusters contained only a single
isolate, while the remaining 110 isolates, characterized by 33 PFGE
patterns, formed five clusters, containing from 2 to 65 isolates per
cluster (Fig. 6). Clear
grouping of the isolates within these clusters was observed based on
their designation as being either outbreak associated or not. With only
two exceptions (OA29 and OA30), two clusters (clusters 1 and 5)
contained all outbreak-associated isolates from the four analyzed
outbreaks (64 isolates). They also contained 19 sporadic isolates and
13 surveillance isolates: 14 of these 32 isolates had a PFGE pattern
indistinguishable from that of one of the four major
outbreak-associated patterns. The presence of such indistinguishable
PFGE patterns in some sporadic isolates is not unusual; the margins of
an outbreak are somewhat arbitrary, and several chains of transmission
may be occurring at once. Also, sporadic cases can continue to occur
while an outbreak is taking place. In two additional clusters
(clusters 2 and 10) that contained multiple isolates (seven and five
isolates, respectively), no outbreak-associated isolates were
found. Cluster 4 contained two isolates from California, one
outbreak associated and one sporadic. Finally, within the six clusters
that contained only a single isolate, only isolate OA30 was
epidemiologically defined as outbreak associated. All others were
isolated from patients with sporadic meningococcal disease, collected
either as a part of the outbreak investigations (one isolate) or
through the active laboratory-based surveillance (four isolates).

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FIG. 6.
Dendrogram showing relatedness by PFGE analysis (with
NheI) of 116 NMSC isolates collected during investigations
of four meningococcal disease outbreaks in Texas, New Mexico, Arizona,
and California and from sporadic cases of meningococcal disease
collected through the active laboratory-based surveillance, 1989 to
1996. Pairs of isolates (SP2835 and SP3039, SP1530 and SP1531, SP638
and OA160, and SU680 and SU810) were identified as having
indistinguishable PFGE patterns using the 1.5% tolerance. Based on
visual inspection, differences in spacing between the bands were
observed, and therefore the additional patterns H46N06.0031,
H46N06.0037, H46N06.0038, and H46N06.0039, respectively, were
established (asterisks). $, isolates on the smaller dendrograms
identified as follows: OA147, pattern H46N06.0001; SP153, pattern
H46N06.0001; SU785, pattern H46N06.0004; SU2656, pattern H46N06.0004.
Their designations as given in Fig. 4 and 5 were used throughout the
analysis. ID, isolate identification number.
|
|
Additional analysis was possible when all isolates were incorporated
into the overall database. Pattern H46N06.0004, characteristic
for the
Texas outbreak, was also identified in three isolates
from Georgia
(SU3790), New Mexico (SP1530), and California (SP153).
Of the
three outbreak-associated isolates (OA1953, OA1956, and
OA1957) with
patterns H46N06.0008 and H46N06.0010, the H46N06.0008
pattern was
also seen in a surveillance isolate from Oklahoma
(SU980). No
other isolates with the H46N06.0010 pattern were identified,
but this
pattern was closely related to the H46N06.0009 pattern,
which was seen
in a single surveillance isolate from Minnesota
(SU4214). Pattern
H46N06.0023, seen in the New Mexico outbreak-associated
isolates,
was also identified in three isolates from Arizona (SP418,
OA800, and OA801). Of the five New Mexico sporadic isolates, two
were
randomly distributed throughout the dendrogram (SP1541 and
SP1532), and
their unique patterns (H46N06.0013 and H46N06.0033)
showed less than
88% relatedness to any other pattern in the database.
The remaining
two sporadic isolates (SP1530 and SP1531) had patterns
H46N06.0004 and
H46N06.0038, which were seen in 22 Texas outbreak-associated
isolates
as well as in a sporadic isolate from California (SP153)
and a
surveillance isolate from Georgia (SU3790). The last sporadic
isolate
(SP1533) from New Mexico, with pattern H46N06.0002, shared
that pattern
with three other isolates from California (OA147),
Connecticut
(SU2656), and Georgia (SU785). This pattern was closely
related to the
H46N06.0001 pattern, which is typical for the majority
of California
outbreak isolates. Pattern H46N06.0026, seen in
14 Arizona
outbreak-associated isolates, was shared with a single
surveillance
isolate from California (SU1591) and another sporadic
isolate from the
California jail outbreak investigation (SP144).
Additionally, two
surveillance isolates from California (SU3686
and SU2286) and one from
Oregon (SU4212) had patterns H46N06.0027
and H46N06.0028, which are
very similar to H46N06.0026 found in
the 14 Arizona outbreak-associated
isolates (95% relatedness).
Of the five isolates that were related to
the 14 outbreak-associated
isolates at the 87% relatedness level when
only Arizona isolates
were analyzed, three (SP418, OA800, and OA801)
had pattern H46N06.0023,
which is typical for the New Mexico
outbreak-associated isolates.
Of the 26 surveillance isolates, 22 isolates with 19 PFGE patterns
were located in four multi-isolate
clusters. The remaining four
isolates made up clusters that contained a
single isolate. Only
three surveillance isolates had PFGE patterns
indistinguishable
from one of the outbreak-associated patterns. An
isolate from
Tennessee (SU1171) had a PFGE pattern indistinguishable
from the
H46N06.0001 pattern of the outbreak-associated isolates from
California.
An isolate from Georgia (SU3790) had a pattern
(H46N06.0004) that
was identified in the outbreak-associated isolates
from Texas.
A single surveillance isolate from California (SU1591) had
an
H46N06.0026 pattern indistinguishable from that of the
outbreak-associated
isolate from
Arizona.
Effects of the tolerance window (0.5, 1.0, or 1.5%) on the
clustering of the PFGE patterns.
Using the 1.5% tolerance window,
39 PFGE patterns were identified among the 116 isolates and were
grouped in 11 clusters at the 85% relatedness level. Changing the
window tolerances only slightly affected the clustering of the PFGE
patterns of isolates from the investigated outbreaks and subsequent
specificity and sensitivity (Table 1).
The only significant change was seen in the grouping of the PFGE
pattern from the California jail outbreak investigation. Overall, among
the 90 isolates collected during the four outbreak investigations, 66 were epidemiologically defined as outbreak related; of those, 56 had
PFGE patterns that were either indistinguishable (54 isolates) or
related to each other at >95% (2 isolates). In 7 of 66 isolates PFGE
patterns were related to the predominant outbreak-associated PFGE
pattern at the 85 to 95% relatedness level. Using the epidemiological
definition for an isolate to be outbreak associated or sporadic, this
translates to a sensitivity of 85% (percentage of true
outbreak-associated isolates correctly identified as such) and a
specificity of 71% (percentage of sporadic isolates correctly
identified as such) using the 95% relatedness breakpoint and either
the 1.5 or 1.0% tolerance (Table 1).
View this table:
[in this window]
[in a new window]
|
TABLE 1.
Sensitivity and specificity of PFGE in differentiating
outbreak-associated isolates from sporadic isolates
of NMSCa
|
|
 |
DISCUSSION |
The management of NMSC outbreaks differs from that of sporadic
meningococcal disease and requires substantial public health action and
resources. Vaccination with the currently available quadrivalent
polysaccharide vaccine is not routinely indicated for prevention of
sporadic disease, but it is useful for control of NMSC outbreaks
(6). Looking for a rapid aid in identifying an outbreak
and its extent, we focused on assessing PFGE to parallel the ability of
MEE to reliably and consistently identify outbreak-associated isolates
and then to differentiate outbreak-associated isolates from sporadic
isolates. We chose isolates from four well-described NMSC outbreaks for
analysis with PFGE, and for comparative purposes we analyzed all
isolates by MEE, RAPD assay, ribotyping, and serotyping and
serosubtyping as well. In addition, we randomly selected isolates representing sporadic disease in the areas where these four outbreaks have occurred, as well as isolates from the ongoing, national, active
laboratory-based surveillance program.
Molecular subtyping of NMSC by MEE showed that most of the outbreaks in
the United States have been caused by isolates of the ET-37 complex.
Isolates of this complex are also the most common cause of sporadic
disease in the United States. Indeed, all 66 outbreak-associated
isolates from the four outbreaks in this study belonged to this
complex: 36 were of ET-24, 21 were of the closely related ET-17, and 9 were of five other closely related ETs. However, among the 24 sporadic
isolates collected during the investigations of these four outbreaks,
20 were also characterized by an ET of the ET-37 complex. Furthermore,
among the 26 randomly chosen surveillance isolates, only 5 were not members of the ET-37 complex. Interestingly, only 3 of these 21 isolates had a PFGE pattern indistinguishable from one of the outbreak-associated PFGE patterns from the four analyzed outbreaks. This suggests that perhaps PFGE might distinguish outbreak-associated isolates from sporadic isolates, even when they are members of the same
ET complex.
We observed excellent correlation between the epidemiological data and
PFGE results, and the overall analysis strongly suggests that PFGE
patterns related to each other at >95% are typical for the isolates
most likely to be a part of the same outbreak. Among the 90 isolates
collected during the four outbreak investigations, 66 were
epidemiologically defined as outbreak related. Fifty-six of these 66 isolates had PFGE patterns that were either indistinguishable (54 isolates) or related to each other at >95% (2 isolates). This high
degree of similarity allows for defining an isolate as outbreak associated. However, in 7 of 66 isolates (11%), PFGE patterns were
related to the predominant outbreak-associated PFGE pattern at the 85 to 95% relatedness level; similarities between PFGE patterns and
clusters in that range do not always correlate with the epidemiological
assessment. In such cases, analysis of PFGE patterns in the context of
a larger database provides more information on their potential
relatedness to patterns of isolates circulating in that particular
geographic setting or beyond. However, the clustering of two PFGE
patterns in an overall dendrogram, and consequently the calculated
degree of their relatedness, may vary slightly from the actual degree
of relatedness expressed when the two patterns are directly compared to
each other. This is only true when the windows of tolerance are defined
as a proportion of the size of a particular band, rather than a fixed
value identical for all bands regardless of their size. Consequently,
in some cases, patterns are identified as indistinguishable when
compared to each other. However, when incorporated in the larger
database they become parts of pattern clusters that are then compared
one cluster to another, rather than each pattern against every
other one, and these clusters are then presented as
related to each other at less than 100% relatedness. In this
study this was the case for OA147 and SP153, which were identified as
H46N06.0001 when only California isolates were analyzed but were
grouped with isolates having H46N06.0002 and H46N06.0004, respectively,
in the overall dendrogram. This was also seen with SU785 and
SU2656, which were identified as H46N06.0004 when only surveillance
isolates were analyzed but were grouped with H46N06.0002 when
incorporated in the overall dendrogram. All of these patterns were more
than 90% similar. Sending Tiff images from gels run by this protocol, obtained in individual outbreak investigations, to CDC's N. meningitidis PFGE database is encouraged to allow for a better
glimpse into the diversity of the circulating isolates and their PFGE
patterns and to form a national database of N. meningitidis
PFGE patterns so that each of the newly identified PFGE patterns could
be compared to this database of PFGE patterns. In this way, local
health authorities may be more rapid and effective in assessing whether
or not they are dealing with an outbreak.
In this study we used the 1.5% tolerance window for analysis of PFGE
pattern relatedness. The PFGE patterns in the Molecular Analyst program
are compared using the band-matching option of the program. This option
uses a band tolerance value in determining the relationship of the
patterns. The tolerance value is expressed as a percentage of the total
normalized gel length. Two bands on different PFGE patterns are
considered to be the same if the difference in the position of the
bands is less than the tolerance percentage. If the difference in the
positions of the bands is greater than the tolerance percentage, then
the bands are considered to be two different bands. A low tolerance
(0.5%) allows for a minimal amount of shifting of the bands when
comparing bands of different PFGE patterns. A tolerance of 1.5% allows
for more shifting of the bands when comparing different PFGE patterns.
In our analysis there were four exceptions due to the consistent
differences in the spacing between two bands observed by visual
inspection, i.e., four patterns were defined as distinct even though
the computer analysis identified them as indistinguishable from four
other PFGE patterns. In order to allow for differences observed in the band migration when identical isolates were tested on different gels,
and especially for the interlaboratory comparison purposes, the 1.5%
tolerance is more appropriate. An overall sensitivity of 85% and
specificity of 71% were observed using the 1.5% tolerance for the
band migration distance at the 95% relatedness level. Using the same
tolerance, the sensitivity increased to 95%, while the specificity
decreased to 46% at the 85% relatedness level among the clusters of
PFGE profiles. Similar values, i.e., 88% sensitivity and 71%
specificity at both the 85 and 95% relatedness levels, were observed
using the 1.0% tolerance, and only a slight decrease in sensitivity
(to 61%) was detected at the 95% relatedness level using the 0.5%
tolerance (Table 1).
The range of genomic diversity differs in different species, and
therefore, in very homogeneous species small differences may be even
more significant and vice versa. However, a number of genetic events
known as genetic drift (point mutations, insertions, deletions, and
rearrangements, etc.) can significantly affect the applicability of a
particular molecular approach to subtype the organism of interest
(10). Horizontal exchange of genetic material in N. meningitidis is common, and it is reasonable to expect that such
events would have greater effects on PFGE than on MEE or ribotyping,
which are methods that deal with specific well-conserved genes, unlike
PFGE. All of these factors need to be carefully considered in setting
the criteria for using molecular markers as an aid in outbreak
definition, and they may vary from one species to another. Therefore,
we addressed the PFGE differentiation capability in relation to the
epidemiological definition of an outbreak, as well as the comparison of
its differentiation potential with those of other molecular subtyping
methods, primarily MEE. We demonstrated that PFGE consistently provided
a greater level of diversity than MEE. We recently experienced a
situation where two cases of meningococcal disease were identified in
contacts at a school in New Hampshire within a 1-week period. Isolates from these two cases were identified as identical by ET, but their PFGE
patterns differed from each other by three bands, relating to each
other at an 84.5% relatedness level, which is right at the level of
85% which was established as the borderline for definition of outbreak
association in this study. Analysis of these isolates by other
molecular subtyping methods showed that they also have an identical
serotype and serosubtype (2a:P1.23,14) and RAPD type (II, II). These
data suggest that the isolates were similar, consistent with an
outbreak, and emphasize the need to analyze the PFGE patterns not only
by band-to-band comparison but also according to the overall PFGE
pattern relatedness.
The importance of the reproducibility of the method cannot be
overstated. It is well known that factors such as different sources of
reagents, laboratorians performing the method, and levels of
experience, and even minimal deviations from the agreed-upon procedure,
can have substantial effects on the interlaboratory comparison. Data
from our small pilot study on 22 isolates from the Texas outbreak were
quite encouraging. These isolates were analyzed by PFGE in four
different laboratories (Florida Department of Health, Minnesota
Department of Health, New York State Department of Health, and CDC)
using the same restriction enzyme but with PFGE protocols that were
developed or modified from already existing protocols in the individual
laboratories. Regardless of the method used and the technical demands
imposed by the software used for the data analysis, all isolates were
grouped in the same manner. In developing this PFGE protocol, we
followed the protocol used by the PulseNet (2).
Laboratorians familiar with the PulseNet PFGE procedures should be able
to easily analyze NMSC isolates by making only small adjustments to
achieve the optimal technical results. At the recent annual PulseNet
meeting (Minneapolis, Minn., May 2000), PFGE analysis of N. meningitidis was accepted as an integral part of the PulseNet
activities. Data presented in the present study demonstrated that PFGE
data correlated very well with epidemiological data for all four
analyzed outbreaks. Subsequent inclusion of N. meningitidis
into PulseNet will provide laboratorians, epidemiologists, and other
public health officials throughout the country additional support in
declaring an outbreak and thereby in making informed appropriate public
health decisions.
 |
ACKNOWLEDGMENTS |
We are grateful to colleagues at the State Health Departments in
Arizona, California, New Mexico, and Texas for providing us with the
outbreak-associated isolates and relevant clinical and epidemiological
information, as well as to the members of the Active Bacterial Core
Surveillance Team for their efforts in providing us with the isolates
collected from patients with sporadic meningococcal disease. We thank
Paul Fiorella (Florida Department of Health, Jacksonville) and Dianna
Schoonmaker-Bopp (New York State Department of Health, Albany) for
their participation in the PFGE pilot interlaboratory comparison study.
We also thank Chris Jambois and Gwen Barnett for their assistance in
the design and production of the figures.
 |
FOOTNOTES |
*
Corresponding author. Mailing address: Epidemic
Investigations Laboratory, Meningitis and Special Pathogens Branch,
DBMD, NCID, Centers for Disease Control and Prevention, Building 5, Room 346, MS D11, 1600 Clifton Road N.E., Atlanta, GA 30333. Phone: (404) 639-1730. Fax: (404) 639-3179. E-mail: txp1{at}cdc.gov.
 |
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