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J Clin Microbiol. Sep 2005; 43(9): 4704–4707.
PMCID: PMC1234084

Comparison of a 3-Set Genotyping System with Multilocus Sequence Typing for Streptococcus agalactiae (Group B Streptococcus)

Abstract

Group B streptococcus (GBS; Streptococcus agalactiae) is the most common cause of neonatal and obstetric sepsis and is an increasingly important cause of septicemia in elderly individuals and immunocompromised patients. Epidemiological studies of GBS infections require comprehensive typing systems that provide information about variable characteristics, such as antigenic type, virulence, or antibiotic resistance, as well as the “backbone” structure or the genetic lineage of isolates. We have previously described a 3-set genotyping system that identifies the molecular serotype (MS) or molecular serosubtype (msst), the protein gene profile, and the presence of several mobile genetic elements (F. Kong, D. Martin, G. James, and G. L. Gilbert, J. Med. Microbiol. 52:337-344, 2003). In this study, 83 clinical GBS isolates which had been previously studied by multilocus sequence typing (MLST) (N. Jones, J. F. Bohnsack, S. Takahashi, K. A. Oliver, M. S. Chan, F. Kunst, P. Glaser, C. Rusniok, D. W. Crook, R. M. Harding, N. Bisharat, and B. G. Spratt, J. Clin. Microbiol. 41:2530-2536, 2003) were examined by using the 3-set genotyping system. Genotypes were assigned to five isolates that were nontypeable by conventional serotyping. There were 27 “3-set” genotypes, 24 multilocus sequence types (STs), and 35 unique combinations (or strains), of which the 4 most common, msst III-2 (ST-17), msst III-1 (ST-19), Ia-1 (ST-23), and V-1 (ST-1), accounted for more than 60% of isolates. The 83 isolates were grouped into seven clusters, with a good correlation between the multilocus STs and the genotypes. The combination of 3-set genotyping and MLST adds discriminatory power to strain typing of GBS, which will be useful for future studies of the epidemiology and pathogenesis of GBS disease.

Streptococcus agalactiae (group B streptococcus [GBS]) is an important human pathogen. It is the most common cause of neonatal sepsis, a frequent cause of maternal sepsis, and an emerging pathogen in the elderly individuals (6). However, GBS is usually a commensal organism and can be isolated from the genitourinary and gastrointestinal tracts of up to 50% of healthy adults (1). Nine capsular polysaccharide GBS serotypes are recognized (7), and these are usually identified by using serotype-specific antisera. Previously, we have described a 3-set genotyping system that can identify the molecular serotype (MS), the molecular serosubtypes (mssts) of MS III, protein gene profiles (pgps), and the presence of a number of mobile genetic elements (mges) (11). Whole-genome molecular typing methods, such as pulsed-field gel electrophoresis (13) and restriction digestion pattern analysis (2), are also useful for epidemiological studies because of their high discriminatory power and reproducibility (14). More recently, multilocus sequence typing (MLST), based on ~500-bp fragments of seven housekeeping genes, has been used to investigate the population structure and genetic lineage of GBS (8). The aim of our study was to compare the 3-set genotyping system with MLST.

MATERIALS AND METHODS

Isolates studied.

The 83 GBS isolates tested in this study were kindly provided by Nicola Jones, Department of Microbiology, John Radcliffe Hospital, Oxford, United Kingdom, who had previously examined them using MLST (8). Their geographic and clinical origins and sequence types (STs) are shown in Fig. Fig.11.

FIG. 1.
Relationships between 3-set genotypes and multilocus sequence types. The dendrogram shows seven major clusters based on the combination of sequence STs and genotypes based on a three-component system. The various combinations of serotype, protein gene ...

Three-set genotyping system.

The 3-set genotyping system has been described in detail previously (9-11). It involves identification of (i) nine MSs, Ia, Ib, and II to VIII (as for conventional serotypes), and four mssts of MS III; (ii) pgps (Table (Table1),1), based on genes encoding members of the family of variable surface proteins (Rib, Cα, Cα-like [Alp1 to Alp4]) and the immunoglobulin A (IgA) binding protein Cβ (and Cβ subtypes based on bac polymorphisms) (15); and (iii) mges, based on the presence of any of four insertion sequences (IS1381, IS861, IS1548, or ISSa4) and the group II intron GBSil (11).

TABLE 1.
Protein gene profiles

Since our previous study, we have designed primers targeting newly described Cα-like protein genes, namely, Alp1, Alp5, epsilon (alp1, alp5, and epsilon genes), and Alp4 (alp4) (4). Analysis of sequence data in GenBank showed that the alp1, alp5, and epsilon gene sequences are very similar and indistinguishable by use of our primers. Therefore, all three are designated alp1 (Table (Table1).1). We also designed new primers targeting the Cβ protein gene (bac). These primers produce longer amplicons and better sequencing results. The new primers used in the study are shown in Table Table22.

TABLE 2.
New oligonucleotide primers targeting the Cα-like and Cβ (bac) protein gene used in this study

Sequencing.

We sequenced the Cβ protein (bac) gene of all 14 isolates in which it was found. Sequencing and sequence analysis were performed as described previously (10).

Statistical analysis and dendrogram formation.

A dendrogram was formed by using the programs for average linkage (between groups) and hierarchical cluster analysis in SPSS, version 11, software (Fig. (Fig.1).1). The presence or absence of each marker was determined as described previously (10, 11).

Nucleotide sequence accession numbers.

The new bac gene sequences were deposited in GenBank, and the accession numbers are shown in Table Table33.

TABLE 3.
Genotypes and bac (Cβ protein gene) subtypes, based on amplicon length (using primers IgAS and IgAA) and sequence heterogeneity

RESULTS AND DISCUSSION

GBS MLST results.

The 83 isolates studied represented 24 STs, of which 17 were identified only once or twice. Fifty isolates (60%) belonged to one of the four most common STs, namely, ST-17 (14 isolates), ST-19 (13 isolates), ST-23 (12 isolates), and ST-1 (11 isolates) (Fig. (Fig.11).

Three-set genotyping results. (i) MS identification.

The capsular serotypes of 78 isolates, based on conventional serotyping with antisera, were known and were confirmed by MS. They were as follows: 35 MS-III isolates (14 msst III-1 isolates, 14 msst III-2 isolates, 2 msst III-3 isolates, and 5 msst III-4 isolates), 13 MS-Ib isolates, 12 MS-Ia isolates, 11 MS-V isolates, 7 MS-II isolates, 2 MS-VI isolates, 2 MS-VII isolates, and 1 MS-IV isolate. Five previously nontypeable isolates were identified as MS-Ib, MS-II, and MS-IV (one isolate each) and MS-VII (two isolates) (Fig. (Fig.11).

(ii) Distributions of pgps.

The major surface-localized antigens of GBS are a family of related proteins represented by Rib, Cα, and several Cα-like proteins (Alp1/Alp5/episilon, Alp2, Alp3, and Alp4 [4]) which are encoded by stable mosaic genes, generated by recombination of modules at the same chromosomal locus. They are potential virulence factors (3) and exhibit size variations between strains, depending on the number of large tandem repeats in the corresponding gene. During the course of an infection, the number of repeats can change as a result of internal deletions, allowing the organism to evade the host immune response (12). These proteins are important in the pathogenesis and epidemiology of GBS disease and have been proposed as components of GBS conjugate vaccines.

Among the 83 isolates studied, we identified various pgps, based on the genes encoding these surface proteins and the IgA binding protein Cβ (Fig. (Fig.1)1) (15), of which the most common were “AB,” “A,” “alp1,” “alp3,” and “R.” Alp2, which is typically associated with msst III-3, was uncommon among these isolates. Each pgp was commonly, but not exclusively, associated with one or two MSs or mssts and MLSTs, as shown in Table Table44.

TABLE 4.
Typical associations between MS, pgp, and multilocus ST

(iii) Distribution of mges.

The distribution of different mge combinations, from none to four per isolate, is shown in Fig. Fig.1.1. Five (6%) isolates contained none of the five mges studied. IS1381, IS861, IS1548, GBSi1, and ISSa4 were identified in 77% (n = 64), 54% (n = 45), 20% (n = 17), 27% (n = 22), and 1% (n = 1) of the isolates, respectively. IS1381 was found in nearly all isolates except those containing GBSi1. IS861 was found in most genotypes with pgp AB (cluster 7) and all genotypes with pgp R (clusters 2 and 4).

GBSi1 was associated with msst III-2 and ST-17, a previously recognized virulent clone commonly associated with neonatal sepsis, but was also found in a small number of other isolates belonging to MS II and MS V. IS1548 is characteristically found in msst III-1 strains ST-19 (and occasionally strains of other STs).

(iv) Genotypes based on MSs and mssts, pgps, bac subtypes, and mges (“3-set” genotypes).

The 83 invasive isolates in this study represented eight MSs (none of the isolates belonged to MS VIII) and 27 “3-set” genotypes. The Cβ protein gene (bac) (pgp B) was found, always in association with the Cα protein (pgp A), in 14 (17%) isolates, all but 2 of which belonged to MS Ib. They were divisible into nine subtypes, based on bac amplicon length (determined with primers IgAS and /IgAA) and sequence heterogeneity, and are shown in Table Table3.3. Among the subtypes are four with new GenBank sequence accession numbers.

Phylogenetic relationships between 3-set genotyping system and MLST.

Based on different combinations of the 27 “3-set” genotypes and 24 STs, there were 35 different clonal types among the 83 isolates studied. As shown in Fig. Fig.1,1, there is, generally, a close correlation between the types identified by these two typing systems, especially in the four largest clusters. For example, in cluster 1, 9 of 11 isolates were genotype V-1 and ST-1; the other 2 isolates were identical except that they belonged to MS VII, indicating probable “serotype switching” or lateral gene transfer (5). Thirteen of 16 isolates in cluster 2 were msst III-1 and ST-19, but two were genotype II-1 and ST-19 and one was genotype II-1 and ST-28; 3 additional msst III-1 isolates belonged to STs in different clusters. Thirteen of 14 msst III-2 isolates belonged to ST-17 (cluster 4). The majority of isolates in cluster 6 belonged to either genotype Ia-1 or genotype III-3 (which have closely related cps sequences but different pgps and mges) and ST-23, but a significant minority belonged to III-4 and ST-11.

The combination of “3-set” genotyping with MLST provides complementary data and increased discriminatory power for GBS strain typing. MLST provides information about the “backbone” structures of isolates and their phylogenetic lineages, whereas “3-set” genotyping reflects the genetic basis of variable phenotypic characteristics, such as capsular polysaccharide and surface protein antigens and mges, which may reflect virulence potential. The results have confirmed previous observations, obtained with various typing systems, that the relatively homogeneous clone, represented by genotype III-2 and ST-17, is strongly associated with invasive neonatal infection (11 of 13 isolates).

In this relatively small set of isolates, there were no other statistically significant associations between genotype or ST and invasive disease or carriage (Fig. (Fig.1).1). Although preliminary data suggest some association between genotype and virulence, interpretation is complicated by the fact that invasive isolates almost always originate from sites of carriage and that there are differences in the disease susceptibilities of different populations, e.g., preterm versus full-term infants. Comparison of the genotype and ST distributions among large numbers of invasive isolates from different patient groups and systematic collection of carriage isolates will be required to determine which genetic characteristics, if any, predict invasiveness. The characteristics identified by these genotyping systems are likely to be only markers rather than direct determinants of virulence. However, further investigation of specific virulence mechanisms will be facilitated by a highly discriminatory, unambiguous strain typing system, such as that described in this study.

The combination of our genotyping system and MLST provides complementary information about important variable characteristics (antigens and mobile elements) as well as the “backbone” structure of GBS. It provides evidence of lateral gene transfer and will facilitate further investigation of the evolution and population biology of the organism and the epidemiology of GBS disease. Currently, it involves multiple PCRs and sequencing reactions, which are cumbersome and impracticable for regular use. In the future, our aim will be to incorporate both methods and, potentially, additional markers of virulence and/or antibiotic resistance into a microarray format.

Acknowledgments

We thank Nicola Jones for providing 83 GBS isolates that had been previously characterized by MLST.

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