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

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

doi:10.1038/s41588-019-0482-z

Cited by 22 publications

(12 citation statements)

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“…Most work on prediction of bacterial phenotypes has focused on antibiotic resistance, but many more complex phenotypes relating to bacterial virulence are now available. For these phenotypes, which are under weaker or no selection, instead of a few strong effects, multiple smaller effects are expected in the genome (44)(45)(46). Therefore, a model which may include more of these effects, which would be missed with a P value threshold, may be expected to perform well.…”

Section: Resultsmentioning

confidence: 99%

Improved Prediction of Bacterial Genotype-Phenotype Associations Using Interpretable Pangenome-Spanning Regressions

Lees

Mai

Galardini

et al. 2020

mBio

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130

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ABSTRACT Discovery of genetic variants underlying bacterial phenotypes and the prediction of phenotypes such as antibiotic resistance are fundamental tasks in bacterial genomics. Genome-wide association study (GWAS) methods have been applied to study these relations, but the plastic nature of bacterial genomes and the clonal structure of bacterial populations creates challenges. We introduce an alignment-free method which finds sets of loci associated with bacterial phenotypes, quantifies the total effect of genetics on the phenotype, and allows accurate phenotype prediction, all within a single computationally scalable joint modeling framework. Genetic variants covering the entire pangenome are compactly represented by extended DNA sequence words known as unitigs, and model fitting is achieved using elastic net penalization, an extension of standard multiple regression. Using an extensive set of state-of-the-art bacterial population genomic data sets, we demonstrate that our approach performs accurate phenotype prediction, comparable to popular machine learning methods, while retaining both interpretability and computational efficiency. Compared to those of previous approaches, which test each genotype-phenotype association separately for each variant and apply a significance threshold, the variants selected by our joint modeling approach overlap substantially. IMPORTANCE Being able to identify the genetic variants responsible for specific bacterial phenotypes has been the goal of bacterial genetics since its inception and is fundamental to our current level of understanding of bacteria. This identification has been based primarily on painstaking experimentation, but the availability of large data sets of whole genomes with associated phenotype metadata promises to revolutionize this approach, not least for important clinical phenotypes that are not amenable to laboratory analysis. These models of phenotype-genotype association can in the future be used for rapid prediction of clinically important phenotypes such as antibiotic resistance and virulence by rapid-turnaround or point-of-care tests. However, despite much effort being put into adapting genome-wide association study (GWAS) approaches to cope with bacterium-specific problems, such as strong population structure and horizontal gene exchange, current approaches are not yet optimal. We describe a method that advances methodology for both association and generation of portable prediction models.

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Section: Resultsmentioning

confidence: 99%

Improved Prediction of Bacterial Genotype-Phenotype Associations Using Interpretable Pangenome-Spanning Regressions

Lees

Mai

Galardini

et al. 2020

mBio

Self Cite

130

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“…A major component of the GAS cell wall is the GAC, building approximately 50% of the cell wall by weight [38]. The GAC is universally conserved amongst all isolated GAS strains on the basis of the gene cluster sequence conservation [39]. A number of S. dysgalactiae subsp.…”

Section: Resultsmentioning

confidence: 99%

Molecular basis for recognition of the Group A Carbohydrate backbone by the PlyC streptococcal bacteriophage endolysin

King

Castro

Bueren-Calabuig

et al. 2021

Preprint

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Endolysins are peptidoglycan (PG) hydrolases that function as part of the bacteriophage (phage) lytic system to release progeny phage at the end of a replication cycle. Notably, endolysins alone can produce lysis without phage infection, which offers an attractive alternative to traditional antibiotics. Endolysins from phage that infect Gram-positive bacterial hosts contain at least one enzymatically active domain (EAD) responsible for hydrolysis of PG bonds and a cell wall binding domain (CBD) that binds a cell wall epitope, such as a surface carbohydrate, providing some degree of specificity for the endolysin. Whilst the EADs typically cluster into conserved mechanistic classes with well-defined active sites, relatively little is known about the nature of the CBDs and only a few binding epitopes for CBDs have been elucidated. The major cell wall components of many streptococci are the polysaccharides that contain the polyrhamnose (pRha) backbone modified with species-specific and serotype-specific glycosyl side chains. In this report, using molecular genetics, microscopy, flow cytometry and lytic activity assays, we demonstrate the interaction of PlyCB, the CBD subunit of the streptococcal PlyC endolysin, with the pRha backbone of the cell wall polysaccharides, Group A Carbohydrate (GAC) and serotype c-specific carbohydrate (SCC) expressed by the Group A Streptococcus and Streptococcus mutans, respectively. Molecular dynamics simulations reveal a previously unidentified binding pocket that is regulated by a gatekeeper residue and uncover that a previously reported inactive PlyC mutant is locked into a 'closed' conformation. Docking studies with the short GAC backbone oligosaccharides expose potential protein-carbohydrate interactions and are consistent with PlyCB binding to the unmodified pRha or pRha decorated with the GAC side chains.

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“…The global distribution of emm types in GAS is extremely diverse. Davies et al [10] compiled a database of the GAS genome sequences of 645 geographically and clinically diverse strains. The database comprises 150 emm types which are clustered into 39 M proteins according to their protein sequences.…”

Section: Diverse Group a Streptococcus Strains And Antigenic Variationmentioning

confidence: 99%

“…Whole GAS genome sequencing has revealed two major issues: (i) an extensive genomic heterogenicity of GAS isolates due to frequent genetic recombination events, including gene exchange and single nucleotide polymorphisms, and (ii) subsequent protein sequence variations. No single protein that has been exploited for vaccine development so far, is 100% conserved throughout all GAS isolates [ 10 ]. Hence, the challenges that require to be addressed to deliver a universal GAS vaccine include (i) the attributed burden of GAS disease, (ii) safety, and (iii) diversity and antigenic variation in GAS strains (electronic supplementary material, figure S1).…”

Section: Why Is It Challenging To Develop a Universal Group A Streptococcus Vaccine?mentioning

confidence: 99%

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A brief review on Group A Streptococcus pathogenesis and vaccine development

Castro

Dorfmueller

2021

R. Soc. open sci.

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Streptococcus pyogenes , also known as Group A Streptococcus (GAS), is a Gram-positive human-exclusive pathogen, responsible for more than 500 000 deaths annually worldwide. Upon infection, GAS commonly triggers mild symptoms such as pharyngitis, pyoderma and fever. However, recurrent infections or prolonged exposure to GAS might lead to life-threatening conditions. Necrotizing fasciitis, streptococcal toxic shock syndrome and post-immune mediated diseases, such as poststreptococcal glomerulonephritis, acute rheumatic fever and rheumatic heart disease, contribute to very high mortality rates in non-industrialized countries. Though an initial reduction in GAS infections was observed in high-income countries, global outbreaks of GAS, causing rheumatic fever and acute poststreptococcal glomerulonephritis, have been reported over the last decade. At the same time, our understanding of GAS pathogenesis and transmission has vastly increased, with detailed insight into the various stages of infection, beginning with adhesion, colonization and evasion of the host immune system. Despite deeper knowledge of the impact of GAS on the human body, the development of a successful vaccine for prophylaxis of GAS remains outstanding. In this review, we discuss the challenges involved in identifying a universal GAS vaccine and describe several potential vaccine candidates that we believe warrant pursuit.

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

Abstract: In the version of the paper initially published, no competing interests were declared. The 'Competing interests' statement should have stated that B.M.N. is on the Scientific Advisory Board of Deep Genomics. The error has been corrected in the HTML and PDF versions of the article.

Cited by 22 publications

References 0 publications

Improved Prediction of Bacterial Genotype-Phenotype Associations Using Interpretable Pangenome-Spanning Regressions

Improved Prediction of Bacterial Genotype-Phenotype Associations Using Interpretable Pangenome-Spanning Regressions

Molecular basis for recognition of the Group A Carbohydrate backbone by the PlyC streptococcal bacteriophage endolysin

A brief review on Group A Streptococcus pathogenesis and vaccine development

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