Frequency-dependent selection can forecast evolution in Streptococcus pneumoniae

Taj Azarian; Pamela P. Martinez; Brian J. Arnold; Xueting Qiu; Lindsay R. Grant; Jukka Corander; Christophe Fraser; Nicholas J. Croucher; Laura L. Hammitt; Raymond Reid; Mathuram Santosham; Robert C. Weatherholtz; Stephen D. Bentley; Katherine L. O’Brien; Marc Lipsitch; William P. Hanage

doi:10.1371/journal.pbio.3000878

Frequency-dependent selection can forecast evolution in Streptococcus pneumoniae

Taj Azarian, Pamela P. Martinez, Brian J. Arnold, Xueting Qiu, Lindsay R. Grant, Jukka Corander, Christophe Fraser, Nicholas J. Croucher, Laura L. Hammitt, Raymond Reid, Mathuram Santosham, Robert C. Weatherholtz, Stephen D. Bentley, Katherine L. O’Brien, Marc Lipsitch, William P. Hanage

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1 Scopus citations

Abstract

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.

Original language	English (US)
Article number	e3000878
Journal	PLoS biology
Volume	18
Issue number	10
DOIs	https://doi.org/10.1371/journal.pbio.3000878
State	Published - Oct 22 2020

ASJC Scopus subject areas

General Neuroscience
General Biochemistry, Genetics and Molecular Biology
General Immunology and Microbiology
General Agricultural and Biological Sciences

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10.1371/journal.pbio.3000878

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Azarian, T., Martinez, P. P., Arnold, B. J., Qiu, X., Grant, L. R., Corander, J., Fraser, C., Croucher, N. J., Hammitt, L. L., Reid, R., Santosham, M., Weatherholtz, R. C., Bentley, S. D., O’Brien, K. L., Lipsitch, M., & Hanage, W. P. (2020). Frequency-dependent selection can forecast evolution in Streptococcus pneumoniae. PLoS biology, 18(10), Article e3000878. https://doi.org/10.1371/journal.pbio.3000878

Azarian, T, Martinez, PP, Arnold, BJ, Qiu, X, Grant, LR, Corander, J, Fraser, C, Croucher, NJ, Hammitt, LL , Reid, R , Santosham, M , Weatherholtz, RC, Bentley, SD, O’Brien, KL, Lipsitch, M & Hanage, WP 2020, 'Frequency-dependent selection can forecast evolution in Streptococcus pneumoniae', PLoS biology, vol. 18, no. 10, e3000878. https://doi.org/10.1371/journal.pbio.3000878

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abstract = "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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AU - Bentley, Stephen D.

AU - O’Brien, Katherine L.

AU - Lipsitch, Marc

AU - Hanage, William P.

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PY - 2020/10/22

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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.

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Frequency-dependent selection can forecast evolution in Streptococcus pneumoniae

Abstract

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