bioRxiv2025
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 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 very significant overlap in the genes and pathways identified using the two methods. Use of this approach thus has the potential to significantly increase the throughput of laboratory-based evolution and enable rapid testing of a wide range of parameters that may have an impact on evolutionary trajectories. Author summaryUnderstanding how bacterial populations adapt to environmental stress is central to microbiology and evolutionary biology. Laboratory evolution experiments are commonly used to uncover the genetic changes that confer increased fitness, but these experiments are often slow and laborious. In this study, we asked whether the results of long-term adaptive laboratory evolution (ALE) could be predicted using a faster method: short-term selection of a dense transposon mutant library, analysed by transposon-directed insertion site sequencing (TraDIS). We evolved E. coli K-12 MG1655 in unbuffered LB at pH 4.5 for 5 months and compared the mutations that arose to those selected after just 10 days of evolution using a high-density transposon library in the same strain and conditions. We observed significant overlap in the genes identified by both approaches, including independent disruptions in shared regulatory pathways. This suggests that short-term selection on a diverse mutant population can uncover many of the same adaptive changes seen in long-term evolution experiments. We also identified and validated the fitness effects of several mutations uniquely found in the transposon approach. Rather than predicting specific mutations from first principles, this method offers a rapid, empirical means of anticipating which genes are likely to be involved in adaptation under defined conditions, helping to guide further mechanistic studies by offering a powerful shortcut for investigating microbial evolution.