Multiple scales of selection influence the evolutionary emergence of novel pathogens
Open accessAbstract
When pathogens encounter a novel environment, such as a new host species or treatment with an antimicrobial drug, their fitness may be reduced so that adaptation is necessary to avoid extinction. Evolutionary emergence is the process by which new pathogen strains arise in response to such selective pressures. Theoretical studies over the last decade have clarified some determinants of emergence risk, but have neglected the influence of fitness on evolutionary rates and have not accounted for the multiple scales at which pathogens must compete successfully. We present a cross-scale theory for evolutionary emergence, which embeds a mechanistic model of within-host selection into a stochastic model for emergence at the population scale. We explore how fitness landscapes at within-host and between-host scales can interact to influence the probability that a pathogen lineage will emerge successfully. Results show that positive correlations between fitnesses across scales can greatly facilitate emergence, while cross-scale conflicts in selection can lead to evolutionary dead ends. The local genotype space of the initial strain of a pathogen can have disproportionate influence on emergence probability. Our cross-scale model represents a step towards integrating laboratory experiments with field surveillance data to create a rational framework to assess emergence risk.
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- Authors
- Park, M., Loverdo, C., Schreiber, S. J., & Lloyd-Smith, J. O.
- Affiliations
- University of California, Los Angeles (US)
- University of California, Davis (US)
- 1
- Corresponding author
- Park, Miran
- Venue
- Philosophical Transactions of the Royal Society B: Biological Sciences
- Publisher
- The Royal Society
- Published
- 2013-03-19
- Volume
- 368
- Issue
- 1614
- Pages
- 20120333-20120333
- ISSN
- 0962-8436 (ISSN-L)
- 1471-2970
- PMC
- PMC3678334
- OpenAlex
- W2171590867
- Cited by
- 51
- References
- 69
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 3 · 2023: 1 · 2022: 2 · 2021: 7 · 2020: 2 · 2019: 8 · 2018: 6 · 2017: 3 · 2016: 5 · 2015: 3 · 2014: 5 · 2013: 3
- FWCI
- 3.54
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Philosophical Transactions of the Royal Society B Biological Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institute of General Medical Sciences (T32GM008185)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mathematical and Theoretical Epidemiology and Ecology Models
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Zoonotic diseases and public health
- Keywords
- evolutionary emergence, novel pathogens, fitness landscape, stochastic population models, genotype space, host adaptation, antimicrobial resistance
- MeSH terms
- Computer Simulation, Biological Evolution, Genotype, Humans, Models, Genetic, Selection, Genetic, Communicable Diseases, Emerging, Host-Pathogen Interactions, Genetic Fitness
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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