Fluctuations and response in complex biological systems: Watching stochastic evolutionary and ecological pattern dynamics

stochastic patterns;Turing patterns;stochastic Turing patterns;evolution;transposable elements;transposon;retrotransposon;bistability;ant foraging

Martini, K. Michael

关键词: stochastic patterns;    Turing patterns;    stochastic Turing patterns;    evolution;    transposable elements;    transposon;    retrotransposon;    bistability;    ant foraging;   

Others  :  https://www.ideals.illinois.edu/bitstream/handle/2142/101464/MARTINI-DISSERTATION-2018.pdf?sequence=1&isAllowed=y

美国|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

My research uses computational and analytical techniques from statistical physics to examine spatial patterns and dynamics in complex biological systems. More specifically I used these techniques to analyze aspects of three different complex biological systems, namely stochastic Turing patterns, transposon and retrotransposon dynamics in live cells, and bistability in ant foraging.In collaboration with experimentalists at MIT and UIUC, I have shown how noise can stabilize emergent behaviors such as Turing patterns in biofilms. Normally, one would think that noise destroys patterns but we found that fluctuations in the copy number of signaling molecules acting as activator and inhibitors of gene expression leads to pattern formation.Surprisingly, we can show theoretically that these fluctuations increase the range of experimental conditions in which patterns can form. In collaboration with experimentalists at UIUC, we have observed how evolution acts on variation in time, space, and genome locus by imaging live cells with fluorescent reporters that allow us to track transposon dynamics. Transposons, also known as "jumping genes," are found in all organisms and have activity that can cause mutations and drive evolution. As part of this collaboration I developed the software for image analysis of the cells and analyzed the resulting statistics of events. We discovered that the excision rate of transposons depends on orientation of the element, spatial location of the cell, and some heritable factors. In a follow-up experiment, I recently developed a model to explain our collaborators' observation that the number of retrotransposon transcripts, transcripts produced by a copy and paste type of mobile genetic element, produces an exponential growth dependence defect. I developed a model for the copy number dynamics of retroelements and the time it takes these elements to be lost from a population of cells depending on the observed growth rate defect, transposition rate, and inactivation rate.This model explains why Group II introns are present in about 30% of bacterial species, while retrotransposons are essentially absent.This research sheds light on the early evolution of the eukaryotic spliceosome, the cellular machinery allowing complex organisms to remove intra-gene junk DNA during gene expression. I have extended a model for ants foraging from two food sources to include indirect recruitment of ants with pheromones rather than direct recruitment by the ants themselves. This model continues to show bistable foraging for ants when their population is below a critical population size that depends on the deposition rate and evaporation rate of pheromones.