The Dynamics of Fitness and Pleiotropy in a Long-Term Evolution Experiment with Escherichia coli

Abstract

Life on earth is shaped by a delicate balance between chance and necessity. A combination of natural selection and genetic drift has moulded random genetic variations over the course of billions of years to generate the complex and interconnected biosphere we see today. These evolutionary dynamics are ultimately the product of numerous genetic mechanisms operating in genomes with highly complex architectures. Unravelling the rules of genetic mechanisms responsible for evolutionary innovation is critical to developing a comprehensive and predictive evolutionary theory, but has evaded direct experimentation since the scale of resources and technology needed to study the patterns of genetic evolution has only recently become achievable. In this dissertation, I explore the use of microbial experimental evolution as a powerful tool for probing evolutionary questions, particularly by leveraging DNA-barcoding and high-throughput DNA sequencing. In chapter 1, I provide an overview of the field of microbial experimental evolution, dividing its history into two eras marked by qualitatively different methodological advancements. I make the case that we now stand at the dawn of a third era, where advances in genome-engineering coupled with low-cost, high-throughput DNA sequencing will allow experiments to finally probe evolution on a statistical scale. I then present two research studies that take advantage of microbial experimental evolution to investigate distinct genetic mechanisms key to the evolutionary process. In Chapter 2, I explore whether fitness can continue increasing in a population that has already adapted to its environment for over 30,000 generations, and whether fixations of beneficial mutations from population-wide DNA sequencing can predict jumps in fitness. My findings reveal that fitness continues to monotonically increase in step with the fixation of beneficial mutations, even though the rate of fixation has dramatically slowed down, highlighting the potential for ongoing adaptation even under constant environmental conditions. In Chapter 3, I develop a novel conjugation-based DNA-barcoding method for the Long-Term Evolution Experiment (LTEE) with Escherichia coli, allowing me to examine the pleiotropic consequences of adaptation to glucose over 50,000 generations in 15 novel resource environments. My observations reveal broad patterns of both convergent and divergent evolution that correspond with mutations in key metabolic genes in clonal sequencing datasets, shedding light on the nature of pleiotropy and its evolution over extended timescales. Using microbial model systems in an evolutionary context has the unique advantage of being relevant both to fundamental evolutionary biology and human health. Since genetic drift and rare mutational events both play an outsized role in determining the evolutionary trajectories of populations, evolutionary questions in the modern age will increasingly be faced with issues of scale. Microbial experimental evolution offers both scale and tractability to solve this problem. Uniquely, this does not sacrifice on human relevance. Building a coarse-grained and comprehensive evolutionary theory is more significant to society today than ever before as the importance of clonal evolution in cancer, gut microbiomes and even pandemics becomes more clearly understood.