Minerva Center

Live emulation of genome evolution in the lab


The known saying, “Nothing in biology makes sense except in light of evolution” (T. Dobzhansky) clearly exemplifies the pivotal role of evolutionary thinking in biology. Classical investigations in evolution are based on observing and comparing organisms in nature and they require inference of the past conditions and species history. Though extremely insightful this approach can be effectively complemented by “lab-evolution”, a newer research paradigm (c.f. Elena & Lenski Nature Reviews Genetics 2003; Shendure et al. Science 2005; Ibara et al. Nature 2002; Selmecki et al. Science 2006) in which organisms are evolved in the lab. In this controlled setup species can be challenged, and then assayed for a variety of physiological and genomic parameters. Rather than simply observing a snapshot, an entire evolutionary “movie” can be followed, during which the environment is not only known, but also manipulated. Our Minerva Center studies evolutionary mechanism and dynamics using lab-evolution. We evolve bacteria, yeast and worms in the lab for various challenges, interrogate their genome, transcriptome, proteome and physiology, analyze computationally the emerging genomes, and carry out mathematical modeling of the evolutionary dynamics.
Organisms often evolve by “mixing and matching” of existing solutions rather than by de novo “inventing” totally new solutions. Eukaryotes mainly exercise this general strategy by duplications of genes, chromosomes, and whole genomes, while bacteria often resort to horizontal transfer of genes between species. We use the lab evolution methodology to study the mechanisms and dynamics of both evolutionary modes in bacteria and yeast respectively. In addition we examine a novel concept of evolving new versions of existing genes through cycles of transcription followed by reverse transcription of RNAs back into the genome. This process may allow the capture and transfer of potentially beneficial transcription errors to the next generation, a process that might prove useful for new biotechnological applications and that might also operate spontaneously in cancer. It is anticipated that our approach of “live-simulation” of evolution will pave the way towards a new level of understanding of the mechanisms and dynamics of evolution.