Predictive genotype-phenotype-fitness mapping in E.coli.

Abstract

Central to understanding and predicting evolution is the ability to predict the effects of mutations. Mutations can alter the immediate phenotype of the gene or regulatory element they appear in, and those changes can impact organismal fitness. The aim of this thesis is to contribute, through experiments and computational models, to the ability to connect mutations in bacterial promoters (genotype) to their effects on gene expression levels (phenotype) and then link those changes in phenotypes to organismal fitness. In a synthetic plasmid system, we generated promoters with different architectures – meaning a different number and relative position of transcription factor binding sites. We explored how promoter architecture impacts the regulatory logic and expression of the associated gene. We introduced random mutations into these promoters to understand the relationship between promoter architecture and the evolvability of the promoter. To study the consequences of mutations in promoters, which alter gene expression levels, we used a metabolic model and Flux Balance Analysis of E. coli. We explored how changes in expression levels of every gene involved in E. coli metabolism altered organismal fitness, and identified general trends of this relationship. We also investigated potential factors that influence how the changes in gene expression levels affected fitness. We used experimental evolution to test the predictions of our modelling approach, albeit with limited success. Connecting genotype to phenotype to fitness is a major challenge in biology, and this thesis contributes novel insights into the relationship as it pertains to bacterial promoters. This work contributes to the ability to predict mutational effects on both phenotype and fitness from first principles and directly from sequence.

Date of Award	13 Mar 2026
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Mato Lagator (Main Supervisor), Philip Day (Co Supervisor) & Jean-Marc Schwartz (Co Supervisor)