Experimental evolution and proximate mechanisms in biology

Xiao Yi

Research output: Contribution to journalReview articlepeer-review

2 Scopus citations

Abstract

Biological functions – studied by molecular, systems and behavioral biology – are referred to as proximate mechanisms. Why and how they have emerged from the course of evolution are referred to as ultimate mechanisms. Despite the conceptual and technical schism between the disciplines that focus on each, studies from one side can benefit the other. Experimental evolution is an emerging field at the crossroads of functional and evolutionary biology. Herein microorganisms and mammalian cell lines evolve in well-controlled laboratory environments over multiple generations. Phenotypic changes arising from the process are then characterized in genetics and function to understand the evolutionary process. While providing empirical tests to evolutionary questions, such studies also offer opportunities of new insights into proximate mechanisms. Experimental evolution optimizes biological systems by means of adaptation; the adapted systems with their mutations present unique perturbed states of the systems that generate new and often unexpected output/performance. Hence, learning about these states not only adds to but also might deepen knowledge on the proximate processes. To demonstrate this point, five examples in experimental evolution are introduced, and their relevance to functional biology explicated. In some examples, from evolution experiments, updates were made to known proximate processes – gene regulation and cell polarization. In some examples, new contexts were found for known proximate processes – cell division and drug resistance of cancer. In one example, a new cellular mechanism was discovered. These cases identify ways the approach of experimental evolution can be used to ask questions in functional biology.

Original languageEnglish (US)
Pages (from-to)253-258
Number of pages6
JournalSynthetic and Systems Biotechnology
Volume2
Issue number4
DOIs
StatePublished - Dec 2017

Bibliographical note

Funding Information:
The author thanks Profs. Romas Kazlauskas, Mike Travisiano, Dr. Bryan Jones, Pei Xu, Katherine Liu for comments on earlier versions of the manuscript, and BioTechnology Institute, University of Minnesota for financial support.

Keywords

  • Experimental evolution
  • Gene network
  • Modules
  • Proximate mechanisms
  • Ultimate mechanisms

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