Barcoding the Lenski Long-Term Evolution Experiment for Massively Parallel Bulk Fitness Assays
Authors: Tanush Jagdish; Eliot Fenton; Jack Edwards; Michael Desai
Affiliation: Organismic and Evolutionary Biology, Harvard University, Cambridge, MA
Keywords: Experimental evolution
How evolution in a constant environment affects a population’s adaptation to other novel conditions is an open question. While studies have used massively parallel sequencing and lineage tracking experiments to address this problem, they are generally limited by short evolutionary timescales. We intend to study pleiotropy by taking advantage of the longest-running evolution experiment, the Long-Term Evolution Experiment with Escherichia coli (LTEE), which consists of 12 parallel E. coli populations started from a single ancestral clone that have been propagated for roughly 75,000 generations. A fundamental limitation of the LTEE has been that fitness assays are limited to colony-counting-based methods, which do now allow for high-throughput multiplexed assays. Given the sheer size of the LTEE library, which spans 150 timepoints for each of the12 populations, and many more coexisting subpopulations, a more high-throughput approach to measure fitness is essential. Here we propose to uniquely barcode multiple clones at all timepoints in every population in the LTEE, which would roughly amount to ~10,000 barcoded clones. We will then use the barcoded LTEE library to measure fitness in a series of environmental conditions using barcoded bulk fitness assays. We show results from our barcoding effort and preliminary data from bulk fitness assays in select environmental conditions from our pilot experiments. Understanding the dynamics of pleiotropy, especially over long evolutionary timescales relevant to natural populations, is essential to building a complete framework of evolutionary theory. We take a small step in this direction by taking advantage of an existing model system.