TY - JOUR
T1 - Frequency-dependent selection can forecast evolution in Streptococcus pneumoniae
AU - Azarian, Taj
AU - Martinez, Pamela P.
AU - Arnold, Brian J.
AU - Qiu, Xueting
AU - Grant, Lindsay Renee
AU - Corander, Jukka
AU - Fraser, Christophe
AU - Croucher, Nicholas J.
AU - Hammitt, Laura L.
AU - Reid, Raymond
AU - Santosham, Mathuram
AU - Weatherholtz, Robert C.
AU - Bentley, Stephen D.
AU - O’Brien, Katherine L.
AU - Lipsitch, Marc
AU - Hanage, William P.
N1 - Funding Information:
TA and WPH were funded by NIH grant R01 AI106786. TA, PPM, and ML were funded by NIH grant R01 AI048935. XQ was supported by the National Institute of General Medical Sciences of NIH under Award Number U54GM088558. NJC was funded by a Sir Henry Dale fellowship and jointly funded by the Wellcome Trust and Royal Society (Grant Number 104169/Z/14/A). JC was funded by European Research Council grant number 742158. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Publisher Copyright:
© 2020 Azarian et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2020/10/22
Y1 - 2020/10/22
N2 - 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.
AB - 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.
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U2 - 10.1371/journal.pbio.3000878
DO - 10.1371/journal.pbio.3000878
M3 - Article
C2 - 33091022
AN - SCOPUS:85094110677
SN - 1544-9173
VL - 18
JO - PLoS Biology
JF - PLoS Biology
IS - 10
M1 - e3000878
ER -