Predicting the evolution of bacterial populations with an epistatic selection-mutation model
A general model, based on evolutionary first-order principles, is proposed and applied to the experimentally observed evolution of Escherichia coli in the long-term evolution experiment. It incorporates two recently noticed phenomena related to mutations: (i) the fact that the marginal im...
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Academia.edu Journals
2024-06-01
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| Series: | Academia Biology |
| Online Access: | https://www.academia.edu/121593869/Predicting_the_evolution_of_bacterial_populations_with_an_epistatic_selection_mutation_model |
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| author | Raul Donangelo Hugo Fort |
| author_facet | Raul Donangelo Hugo Fort |
| author_sort | Raul Donangelo |
| collection | DOAJ |
| description |
A general model, based on evolutionary first-order principles, is proposed and applied to the experimentally observed evolution of Escherichia coli in the long-term evolution experiment. It incorporates two recently noticed phenomena related to mutations: (i) the fact that the marginal improvement from a beneficial mutation declines with increasing fitness or diminishing returns epistasis and (ii) for some hypermutator variants, the mutation rate for the bacterial DNA undergoes a sudden increase by at least one order of magnitude. The model can simultaneously predict the experimental mean fitness trajectory, as well as other observables, such as the variance trajectory and the mean substitution trajectory, all through the 50,000 bacterial generations presently available. |
| format | Article |
| id | doaj-art-92efc660bcde445eafd09c8ee3793044 |
| institution | Kabale University |
| issn | 2837-4010 |
| language | English |
| publishDate | 2024-06-01 |
| publisher | Academia.edu Journals |
| record_format | Article |
| series | Academia Biology |
| spelling | doaj-art-92efc660bcde445eafd09c8ee37930442025-02-11T00:42:01ZengAcademia.edu JournalsAcademia Biology2837-40102024-06-012210.20935/AcadBiol6255Predicting the evolution of bacterial populations with an epistatic selection-mutation modelRaul Donangelo0Hugo Fort1Instituto de Física, Facultad de Ingeniería, Universidad de la República, Montevideo 11300, Uruguay.Instituto de Física, Facultad de Ciencias, Universidad de la República, Montevideo 11400, Uruguay. A general model, based on evolutionary first-order principles, is proposed and applied to the experimentally observed evolution of Escherichia coli in the long-term evolution experiment. It incorporates two recently noticed phenomena related to mutations: (i) the fact that the marginal improvement from a beneficial mutation declines with increasing fitness or diminishing returns epistasis and (ii) for some hypermutator variants, the mutation rate for the bacterial DNA undergoes a sudden increase by at least one order of magnitude. The model can simultaneously predict the experimental mean fitness trajectory, as well as other observables, such as the variance trajectory and the mean substitution trajectory, all through the 50,000 bacterial generations presently available.https://www.academia.edu/121593869/Predicting_the_evolution_of_bacterial_populations_with_an_epistatic_selection_mutation_model |
| spellingShingle | Raul Donangelo Hugo Fort Predicting the evolution of bacterial populations with an epistatic selection-mutation model Academia Biology |
| title | Predicting the evolution of bacterial populations with an epistatic selection-mutation model |
| title_full | Predicting the evolution of bacterial populations with an epistatic selection-mutation model |
| title_fullStr | Predicting the evolution of bacterial populations with an epistatic selection-mutation model |
| title_full_unstemmed | Predicting the evolution of bacterial populations with an epistatic selection-mutation model |
| title_short | Predicting the evolution of bacterial populations with an epistatic selection-mutation model |
| title_sort | predicting the evolution of bacterial populations with an epistatic selection mutation model |
| url | https://www.academia.edu/121593869/Predicting_the_evolution_of_bacterial_populations_with_an_epistatic_selection_mutation_model |
| work_keys_str_mv | AT rauldonangelo predictingtheevolutionofbacterialpopulationswithanepistaticselectionmutationmodel AT hugofort predictingtheevolutionofbacterialpopulationswithanepistaticselectionmutationmodel |