Competition for resources can reshape the evolutionary properties of spatial structure.

Anush Devadhasan, Oren Kolodny, Oana Carja
Author Information
  1. Anush Devadhasan: Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.
  2. Oren Kolodny: Department of Ecology, Evolution, and Behavior, E. Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.
  3. Oana Carja: Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America. ORCID

Abstract

Many evolving ecosystems have spatial structures that can be conceptualized as networks, with nodes representing individuals or homogeneous subpopulations and links the patterns of spread between them. Prior models of evolution on networks do not take ecological niche differences and eco-evolutionary interplay into account. Here, we combine a resource competition model with evolutionary graph theory to study how heterogeneous topological structure shapes evolutionary dynamics under global frequency-dependent ecological interactions. We find that the addition of ecological competition for resources can produce a reversal of roles between amplifier and suppressor networks for deleterious mutants entering the population. We show that this effect is a nonlinear function of ecological niche overlap and discuss intuition for the observed dynamics using simulations and analytical approximations. We use these theoretical results together with spatial representations from imaging data to show that, for ductal carcinoma, where tumor growth is highly spatially constrained, with cells confined to a tree-like network of ducts, the topological structure can lead to higher rates of deleterious mutant hitchhiking with metabolic driver mutations, compared to tumors characterized by different spatial topologies.

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Grants

  1. R35 GM147445/NIGMS NIH HHS
  2. T32 EB009403/NIBIB NIH HHS

MeSH Term

Ecosystem
Humans
Biological Evolution
Computational Biology
Mutation
Models, Biological
Computer Simulation

Word Cloud

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