Literature DB >> 12695982

Experimental evolution and the Krogh principle: generating biological novelty for functional and genetic analyses.

Albert F Bennett1.   

Abstract

August Krogh counseled the careful selection of the best subject organism on which to undertake mechanistic physiological research. But what if an organism with the desired properties does not exist? It is now within our power to engineer organisms genetically to achieve novel combinations of traits. I propose that it is a logical extension of the Krogh principle that we use biological methodologies to create novel organisms ideally suited for particular physiological studies. Transgenics may first come to mind as the method for such transformations, but here I suggest that an alternative and complementary technique for generating biological novelty is experimental evolution. The latter has several advantages, including modification of multiple characters in one experiment, the production of advantageous traits, the testing of evolutionary hypotheses, and the identification of previously unsuspected factors involved in adaptation. Three experiments are reviewed, each of which examined the evolution of different physiological characters in different environments and organisms: locomotor performance in mice, desiccation tolerance in fruit flies, and high temperature adaptation in bacteria. While diverse in experimental type and subject, all resulted in the successful production of new variants with enhanced function in their new environments. Each experiment successfully tested hypotheses concerning physiological evolution, and in each case, unanticipated results emerged, which suggests previously unsuspected adaptive pathways and mechanisms. In addition, replicate populations in each experiment adjusted to their common environments by several different means, which indicates that physiological evolution may follow diverse stochastic pathways during adaptation. Experimental evolution can be a valuable method to produce and investigate new physiological variants and traits. The choice of experimental subjects, according to the Krogh principle, is no longer limited to currently existing organisms but is open to our imaginations and our ingenuity.

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Year:  2003        PMID: 12695982     DOI: 10.1086/374275

Source DB:  PubMed          Journal:  Physiol Biochem Zool        ISSN: 1522-2152            Impact factor:   2.247


  8 in total

1.  An experimental test of evolutionary trade-offs during temperature adaptation.

Authors:  Albert F Bennett; Richard E Lenski
Journal:  Proc Natl Acad Sci U S A       Date:  2007-05-09       Impact factor: 11.205

2.  Genome-Wide Analysis of Starvation-Selected Drosophila melanogaster-A Genetic Model of Obesity.

Authors:  Christopher M Hardy; Molly K Burke; Logan J Everett; Mira V Han; Kathryn M Lantz; Allen G Gibbs
Journal:  Mol Biol Evol       Date:  2018-01-01       Impact factor: 16.240

Review 3.  Genetic approaches in comparative and evolutionary physiology.

Authors:  Jay F Storz; Jamie T Bridgham; Scott A Kelly; Theodore Garland
Journal:  Am J Physiol Regul Integr Comp Physiol       Date:  2015-06-03       Impact factor: 3.619

4.  Camels, Cormorants, and Kangaroo Rats: Integration and Synthesis in Organismal Biology After World War II.

Authors:  Joel B Hagen
Journal:  J Hist Biol       Date:  2015       Impact factor: 1.326

5.  Variation in within-bone stiffness measured by nanoindentation in mice bred for high levels of voluntary wheel running.

Authors:  Kevin M Middleton; Beth D Goldstein; Pradeep R Guduru; Julie F Waters; Scott A Kelly; Sharon M Swartz; T Garland
Journal:  J Anat       Date:  2010-01       Impact factor: 2.610

Review 6.  Transcellular and paracellular pathways of transepithelial fluid secretion in Malpighian (renal) tubules of the yellow fever mosquito Aedes aegypti.

Authors:  K W Beyenbach; P M Piermarini
Journal:  Acta Physiol (Oxf)       Date:  2010-11-16       Impact factor: 6.311

7.  Maternal investment in reproduction and its consequences in leatherback turtles.

Authors:  Bryan P Wallace; Paul R Sotherland; Pilar Santidrian Tomillo; Richard D Reina; James R Spotila; Frank V Paladino
Journal:  Oecologia       Date:  2007-01-26       Impact factor: 3.298

8.  Transcriptomic Analysis Following Artificial Selection for Grasshopper Size.

Authors:  Shuang Li; Dong-Nan Cui; Hidayat Ullah; Jun Chen; Shao-Fang Liu; Douglas W Whitman; Ze-Hua Zhang; Xiong-Bing Tu
Journal:  Insects       Date:  2020-03-10       Impact factor: 2.769

  8 in total

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