Dataset Information

Assignment of Streptococcus agalactiae isolates to clonal complexes using a small set of single nucleotide polymorphisms.

ABSTRACT:

Background

Streptococcus agalactiae (Group B Streptococcus (GBS)) is an important human pathogen, particularly of newborns. Emerging evidence for a relationship between genotype and virulence has accentuated the need for efficient and well-defined typing methods. The objective of this study was to develop a single nucleotide polymorphism (SNP) based method for assigning GBS isolates to multilocus sequence typing (MLST)-defined clonal complexes.

Results

It was found that a SNP set derived from the MLST database on the basis of maximization of Simpsons Index of Diversity provided poor resolution and did not define groups concordant with the population structure as defined by eBURST analysis of the MLST database. This was interpreted as being a consequence of low diversity and high frequency horizontal gene transfer. Accordingly, a different approach to SNP identification was developed. This entailed use of the "Not-N" bioinformatic algorithm that identifies SNPs diagnostic for groups of known sequence variants, together with an empirical process of SNP testing. This yielded a four member SNP set that divides GBS into 10 groups that are concordant with the population structure. A fifth SNP was identified that increased the sensitivity for the clinically significant clonal complex 17 to 100%. Kinetic PCR methods for the interrogation of these SNPs were developed, and used to genotype 116 well characterized isolates.

Conclusion

A five SNP method for dividing GBS into biologically valid groups has been developed. These SNPs are ideal for high throughput surveillance activities, and combining with more rapidly evolving loci when additional resolution is required.

SUBMITTER: Honsa E

PROVIDER: S-EPMC2533671 | biostudies-literature | 2008 Aug

REPOSITORIES: biostudies-literature

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Publications

Assignment of Streptococcus agalactiae isolates to clonal complexes using a small set of single nucleotide polymorphisms.

Honsa Erin E Fricke Thomas T Stephens Alex J AJ Ko Danny D Kong Fanrong F Gilbert Gwendolyn L GL Huygens Flavia F Giffard Philip M PM

BMC microbiology 20080819

<h4>Background</h4>Streptococcus agalactiae (Group B Streptococcus (GBS)) is an important human pathogen, particularly of newborns. Emerging evidence for a relationship between genotype and virulence has accentuated the need for efficient and well-defined typing methods. The objective of this study was to develop a single nucleotide polymorphism (SNP) based method for assigning GBS isolates to multilocus sequence typing (MLST)-defined clonal complexes.<h4>Results</h4>It was found that a SNP set ...[more]

PMID: 18710585

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Project description:BackgroundThe clinical significance of group B streptococcus (GBS) was different among different clonal complexes (CCs), accurate strain typing of GBS would facilitate clinical prognostic evaluation, epidemiological investigation and infection control. The aim of this study was to construct a practical and facile CCs prediction model for S. agalactiae.MethodsA total of 325 non-duplicated GBS strains were collected from clinical samples in Xinhua Hospital, Shanghai, China. Multilocus sequence typing (MLST) method was used for molecular classification, the results were analyzed to derive CCs by Bionumeric 8.0 software. Antibiotic susceptibility test was performed using Vitek-2 Compact system combined with K-B method. Multiplex PCR method was used for serotype identification. A total of 45 virulence genes associated with adhesion, invasion, immune evasion were detected by PCR method and electrophoresis. Three types of features, including antibiotic susceptibility (A), serotypes (S) and virulence genes (V) tests, and XGBoost algorithm was established to develop multi-class CCs identification models. The performance of proposed models was evaluated by the receiver operating characteristic curve (ROC).ResultsThe 325 GBS were divided into 47 STs, and then calculated into 7 major CCs, including CC1, CC10, CC12, CC17, CC19, CC23, CC24. A total of 18 features in three kinds of tests (A, S, V) were significantly different from each CC. The model based on all the features (S&A&V) performed best with AUC 0.9536. The model based on serotype and antibiotic resistance (S&A) only enrolled 5 weighed features, performed well in predicting CCs with mean AUC 0.9212, and had no statistical difference in predicting CC10, CC12, CC17, CC19, CC23 and CC24 when compared with S&A&V model (all p > 0.05).ConclusionsThe S&A model requires least parameters while maintaining a high accuracy and predictive power of CCs prediction. The established model could be used as a promising tool to classify the GBS molecular types, and suggests a substantive improvement in clinical application and epidemiology surveillance in GBS phenotyping.

Project description:As a leading cause of neonatal sepsis, Streptococcus agalactiae, commonly known as Group B Streptococcus, is a major neonatal pathogen. Current global screening practices employ risk- or culture-based protocols for detection of these organisms. In Western Australia (WA), universal culture-based screening is provided, with subsequent intrapartum antibiotic prophylaxis for all S. agalactiae-positive women during labour. Widespread antibiotic exposure is not ideal and this is one of the factors driving development of vaccines against S. agalactiae. Vaccine candidates have focused on the capsule, surface proteins and pilus types, however, capsule serotypes are known to vary geographically. The aim of this study was to use genome sequencing to gain an understanding of the circulating genotypes in WA, and to assess variations in the associated gene pools. We sequenced 141 antenatal carriage (vaginal/rectal) isolates and 10 neonatal invasive disease isolates from WA. Based on the global PubMLST database, the 151 strains were characterised into 30 sequence types, with clustering of these mainly into clonal complexes 1, 12, 17, 19 and 23. Of the genes encoding eleven surface proteins that were analysed, the most prevalent were fbp, lmb and scpB which were present in ≥ 98% of isolates. A cluster of non-haemolytic isolates, one of which was a neonatal invasive disease isolate, appeared to lack the entire cyl locus. Admixture analysis of population structure revealed evidence of genetic transfer among the WA isolates across structural groups. When compared against the PubMLST S. agalactiae data, WA isolates showed high levels of strain diversity with minimal apparent clustering. This is the first whole genome sequence study of WA S. agalactiae isolates and also represents the first addition of Australian isolate data to PubMLST. This report provides insight into the distribution and diversity of vaccine targets of S. agalactiae within Western Australia, indicating that the most appropriate capsular vaccine for this population would be the proposed pentavalent (Cps Ia, Ib, II, III and V) preparation, whilst vaccines targeting surface proteins should ideally utilise Fbp, Lmb and/or ScpB.

Dataset Information

Assignment of Streptococcus agalactiae isolates to clonal complexes using a small set of single nucleotide polymorphisms.

Background

Results

Conclusion

Publications

Assignment of Streptococcus agalactiae isolates to clonal complexes using a small set of single nucleotide polymorphisms.

Similar Datasets

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