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Shared Molecular Targets Confer Resistance over Short and Long Evolutionary Timescales.

ABSTRACT: Pre-existing and de novo genetic variants can both drive adaptation to environmental changes, but their relative contributions and interplay remain poorly understood. Here we investigated the evolutionary dynamics in drug-treated yeast populations with different levels of pre-existing variation by experimental evolution coupled with time-resolved sequencing and phenotyping. We found a doubling of pre-existing variation alone boosts the adaptation by 64.1% and 51.5% in hydroxyurea and rapamycin, respectively. The causative pre-existing and de novo variants were selected on shared targets: RNR4 in hydroxyurea and TOR1, TOR2 in rapamycin. Interestingly, the pre-existing and de novo TOR variants map to different functional domains and act via distinct mechanisms. The pre-existing TOR variants from two domesticated strains exhibited opposite rapamycin resistance effects, reflecting lineage-specific functional divergence. This study provides a dynamic view on how pre-existing and de novo variants interactively drive adaptation and deepens our understanding of clonally evolving populations.

SUBMITTER: Li J

PROVIDER: S-EPMC6445301 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Shared Molecular Targets Confer Resistance over Short and Long Evolutionary Timescales.

Li Jing J Vázquez-García Ignacio I Persson Karl K González Asier A Yue Jia-Xing JX Barré Benjamin B Hall Michael N MN Long Anthony A Warringer Jonas J Mustonen Ville V Liti Gianni G

Molecular biology and evolution 20190401 4

Pre-existing and de novo genetic variants can both drive adaptation to environmental changes, but their relative contributions and interplay remain poorly understood. Here we investigated the evolutionary dynamics in drug-treated yeast populations with different levels of pre-existing variation by experimental evolution coupled with time-resolved sequencing and phenotyping. We found a doubling of pre-existing variation alone boosts the adaptation by 64.1% and 51.5% in hydroxyurea and rapamycin, ...[more]

PMID: 30657986

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Project description:PurposeThe importance of mechanical forces and microenvironment in guiding cellular behavior has been widely accepted. Together with the extracellular matrix (ECM), epithelial cells form a highly connected mechanical system subjected to various mechanical cues from their environment, such as ECM stiffness, and tensile and compressive forces. ECM stiffness has been linked to many pathologies, including tumor formation. However, our understanding of the effect of ECM stiffness and its heterogeneities on rapid force transduction in multicellular systems has not been fully addressed.MethodsWe used experimental and computational methods. Epithelial cells were cultured on elastic hydrogels with fluorescent nanoparticles. Single cells were moved by a micromanipulator, and epithelium and substrate deformation were recorded. We developed a computational model to replicate our experiments and quantify the force distribution in the epithelium. Our model further enabled simulations with local stiffness gradients.ResultsWe found that substrate stiffness affects the force transduction and the cellular deformation following an external force. Also, our results indicate that the heterogeneities, e.g., gradients, in the stiffness can substantially influence the strain redistribution in the cell monolayers. Furthermore, we found that the cells' apico-basal elasticity provides a level of mechanical isolation between the apical cell-cell junctions and the basal focal adhesions.ConclusionsOur simulation results show that increased ECM stiffness, e.g., due to a tumor, can mechanically isolate cells and modulate rapid mechanical signaling between cells over distances. Furthermore, the developed model has the potential to facilitate future studies on the interactions between epithelial monolayers and elastic substrates.Supplementary informationThe online version of this article (10.1007/s12195-023-00772-0) contains supplementary material, which is available to authorized users.

Dataset Information

Shared Molecular Targets Confer Resistance over Short and Long Evolutionary Timescales.

Publications

Shared Molecular Targets Confer Resistance over Short and Long Evolutionary Timescales.

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