Frequency-dependent selection can forecast evolution in Streptococcus pneumoniae

Autor: Lindsay R. Grant, Mathuram Santosham, Nicholas J. Croucher, William P. Hanage, Marc Lipsitch, Brian J. Arnold, Taj Azarian, Robert Weatherholtz, Pamela P. Martinez, Laura L. Hammitt, Christophe Fraser, Jukka Corander, Raymond Reid, Xueting Qiu, Katherine L. O’Brien, Stephen D. Bentley
Přispěvatelé: Helsinki Institute for Information Technology, Department of Mathematics and Statistics, Biostatistics Helsinki
Rok vydání: 2020
Předmět:
0301 basic medicine
Frequency-dependent selection
Human pathogen
medicine.disease_cause
Pathology and Laboratory Medicine
Pneumococcal Vaccines
0302 clinical medicine
Medical Conditions
Medicine and Health Sciences
Public and Occupational Health
Biology (General)
Pathogen
112 Statistics and probability
Data Management
Genetics
education.field_of_study
Vaccines
Bacterial Genomics
General Neuroscience
Microbial Genetics
Genomics
Pneumococcus
Vaccination and Immunization
3. Good health
Bacterial Pathogens
Vaccination
Phylogenetics
Streptococcus pneumoniae
Infectious Diseases
Medical Microbiology
1181 Ecology
evolutionary biology
Pathogens
General Agricultural and Biological Sciences
Research Article
Computer and Information Sciences
Infectious Disease Control
QH301-705.5
Population
Immunology
Microbial Genomics
Biology
Models
Biological
Microbiology
General Biochemistry
Genetics and Molecular Biology
03 medical and health sciences
medicine
Bacterial Genetics
Computer Simulation
Evolutionary Systematics
education
Microbial Pathogens
Selection (genetic algorithm)
Taxonomy
Evolutionary Biology
General Immunology and Microbiology
Bacteria
Organisms
Biology and Life Sciences
Streptococcus
Bacteriology
030104 developmental biology
Genetic Loci
Conjugate Vaccines
Preventive Medicine
Directed Molecular Evolution
030217 neurology & neurosurgery
Zdroj: PLoS Biology
PLoS Biology, Vol 18, Iss 10, p e3000878 (2020)
ISSN: 1544-9173
Popis: Predicting how pathogen populations will change over time is challenging. Such has been the case with Streptococcus pneumoniae, an important human pathogen, and the pneumococcal conjugate vaccines (PCVs), which target only a fraction of the strains in the population. Here, we use the frequencies of accessory genes to predict changes in the pneumococcal population after vaccination, hypothesizing that these frequencies reflect negative frequency-dependent selection (NFDS) on the gene products. We find that the standardized predicted fitness of a strain, estimated by an NFDS-based model at the time the vaccine is introduced, enables us to predict whether the strain increases or decreases in prevalence following vaccination. Further, we are able to forecast the equilibrium post-vaccine population composition and assess the invasion capacity of emerging lineages. Overall, we provide a method for predicting the impact of an intervention on pneumococcal populations with potential application to other bacterial pathogens in which NFDS is a driving force.
Predicting how pathogen populations will change over time is challenging. This study predicts population changes in human pathogen Streptococcus pneumoniae after vaccination, using a model of negative frequency-dependent selection acting on accessory gene products.
Databáze: OpenAIRE
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