Book contents
- Frontmatter
- Dedication
- Contents
- Preface
- List of abbreviations
- 1 Introduction
- I Network Reconstruction
- II Mathematical Properties of Reconstructed Networks
- III Determining the Phenotypic Potential of Reconstructed Networks
- IV Basic and Applied Uses
- 22 Environmental Parameters
- 23 Genetic Parameters
- 24 Analysis of Omic Data
- 25 Model-Driven Discovery
- 26 Adaptive Laboratory Evolution
- 27 Model-driven Design
- V Conceptual Foundations
- 29 Epilogue
- References
- Index
26 - Adaptive Laboratory Evolution
from IV - Basic and Applied Uses
Published online by Cambridge University Press: 05 February 2015
- Frontmatter
- Dedication
- Contents
- Preface
- List of abbreviations
- 1 Introduction
- I Network Reconstruction
- II Mathematical Properties of Reconstructed Networks
- III Determining the Phenotypic Potential of Reconstructed Networks
- IV Basic and Applied Uses
- 22 Environmental Parameters
- 23 Genetic Parameters
- 24 Analysis of Omic Data
- 25 Model-Driven Discovery
- 26 Adaptive Laboratory Evolution
- 27 Model-driven Design
- V Conceptual Foundations
- 29 Epilogue
- References
- Index
Summary
Darwin would be amazed to see where his ideas have led
– Richard LenskiEvolution is fundamental to biology. We now have the potential to observe it in the laboratory, to define its dynamics, and to determine the genetic bases that enable new phenotypes. What happens in the laboratory may not be directly applicable to what happens in natural habitats, however, unless that habitat can be reproduced accurately in the laboratory setting. Nevertheless, adaptive laboratory evolution (ALE) is opening up new possibilities for the fundamental research of biology. The term distal causation is used to describe changes in biological properties over many generations. We can now not only control short-term evolutionary processes in the laboratory, but through inexpensive whole genome re-sequencing, also determine the genetic basis for distal causation.
A New Line of Biological Inquiry
ALE can be used to study the genotype–phenotype relationship ALE has been used extensively to study the genetic and biochemical basis for bacterial adaptation. Using whole-genome re-sequencing, the mutations that are selected during ALE can be identified readily. The introduction of these mutations into the starting strain allows for the determination of causality of the identified mutations. This determination is performed by first introducing one mutation at a time, then the pairwise combinations, then triple combinations, and so forth until the full complement of the mutations found has been introduced. Newer genome editing methods allow the introduction of multiple genetic changes simultaneously.
Experience to date has shown that if the dominant mutations are relatively few, then the determination of the genetic basis for adaptation is possible. For a more complex genetic basis, new methods like MAGE [450] may enable one to delineate the effect of many mutations, where each one contributes in a small way to the overall phenotypic change. However, finding the biochemical functional changes in the gene products and how they affect the phenotype has proven to be a challenging task. When successful, the elucidation of the underlying molecular mechanisms leads to the discovery of new cellular processes and a deeper understanding of the functions of the mutated gene products.
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- Systems BiologyConstraint-based Reconstruction and Analysis, pp. 422 - 437Publisher: Cambridge University PressPrint publication year: 2015
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