Atlas of group A streptococcal vaccine candidates compiled using large-scale comparative genomics

Mark R. Davies, Liam McIntyre, Ankur Mutreja, Jake A. Lacey, John A. Lees, Rebecca J. Towers, Sebastián Duchêne, Pierre R. Smeesters, Hannah R. Frost, David J. Price, Matthew T.G. Holden, Sophia David, Philip M. Giffard, Kate A. Worthing, Anna C. Seale, James A. Berkley, Simon R. Harris, Tania Rivera-Hernandez, Olga Berking, Amanda J. CorkRosângela S.L.A. Torres, Trevor Lithgow, Richard A. Strugnell, Rene Bergmann, Patric Nitsche-Schmitz, Gusharan S. Chhatwal, Stephen D. Bentley, John D. Fraser, Nicole J. Moreland, Jonathan R. Carapetis, Andrew C. Steer, Julian Parkhill, Allan Saul, Deborah A. Williamson, Bart J. Currie, Steven Y.C. Tong, Gordon Dougan, Mark J. Walker

Research output: Contribution to journalArticleResearchpeer-review

34 Citations (Scopus)

Abstract

Group A Streptococcus (GAS; Streptococcus pyogenes) is a bacterial pathogen for which a commercial vaccine for humans is not available. Employing the advantages of high-throughput DNA sequencing technology to vaccine design, we have analyzed 2,083 globally sampled GAS genomes. The global GAS population structure reveals extensive genomic heterogeneity driven by homologous recombination and overlaid with high levels of accessory gene plasticity. We identified the existence of more than 290 clinically associated genomic phylogroups across 22 countries, highlighting challenges in designing vaccines of global utility. To determine vaccine candidate coverage, we investigated all of the previously described GAS candidate antigens for gene carriage and gene sequence heterogeneity. Only 15 of 28 vaccine antigen candidates were found to have both low naturally occurring sequence variation and high (>99%) coverage across this diverse GAS population. This technological platform for vaccine coverage determination is equally applicable to prospective GAS vaccine antigens identified in future studies.

Original languageEnglish
Pages (from-to)1035-1043
Number of pages9
JournalNature Genetics
Volume51
Issue number6
DOIs
Publication statusPublished - 1 Jun 2019

Keywords

  • data mining
  • microbial genetics
  • population genetics

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