Raw data and calculations used in this study.

Long term laboratory-based evolution experiments are a powerful tool that are increasingly being used to study fundamental aspects of evolution and to identify genes that contribute to overall fitness under different conditions. However, even with automation, the time that they take to execute limits the extent to which evolution experiments can be used as part of a high throughput approach to understand the links between genotype and phenotype. Mutations that lead to genetic loss of function (LoF) are frequently selected for in evolution experiments. Thus, in principle these experiments could be done more rapidly by starting not with clonal isolates but with dense transposon libraries that will contain loss of function mutations in all non-essential genes. Here, we test this hypothesis by comparing the results of long term (5 month) evolution experiment, in which E. coli was grown with daily transfers in unbuffered LB starting at pH 4.5, with short term (5 and 10 day) experiments on a high-density transposon library in the same strain and under the same conditions. We show that there is a overlap in the genes and pathways identified using the two methods, as well as identifying other gene of interest whose LoF contributes to fitness. This approach has the potential to complement laboratory-based evolution, enabling rapid, higher throughput, testing of a wide range of parameters that may have an influence on evolutionary trajectories.