Bacteria have small, streamlined genomes and evolve rapidly. Their large population sizes allow selection to be the main driver of evolution. With advances in sequencing technologies and precise methods for genetic engineering, many bacteria are excellent models for studying elementary questions in evolutionary biology. The work in this thesis has broadly been devoted to adaptive evolution and fitness effects of different types of mutations.
In Paper I we experimentally tested the fitness constrains of horizontal gene transfer (HGT), which could be used to predict how the fixation of HGT events are affected by selection and fitness effects. We found that the majority of the examined HGT inserts were indistinguishable from neutral, implying that extra DNA transferred by HGT, even though it does not confer an immediate selective advantage, could be maintained at transfer-selection balance and serve as a reservoir for the evolution of novel beneficial functions.
Paper II examined why four synonymous mutations in rpsT (encoding ribosomal protein S20) reduced fitness, and how this cost could be genetically compensated. We found that the cause for the fitness reduction was low S20 levels and that this lead to a defective subpopulation of 30S subunits lacking S20. In an adaptive evolution experiment, these impairments were compensated by up-regulation of S20 though various types of mutations.
In Paper III we continued the studies of how the deleterious rpsT mutations could be compensated. The mutations either down-regulated the global regulator Fis or altered a subunit of the RNA polymerase (rpoA). We found that the decreased S20 levels in the cells causes an assembly defect of the 30S particles and that the fis and rpoA mutations restored the skewed S20:ribosome ratio by both increasing S20 levels and decreasing other ribosomal components.
Paper IV examined adaptation of two bacterial species to different growth media. A total of 142 different adaptive mutations were identified and 112 mutants were characterized in terms of fitness. We found that the experimental variation in fitness measurements could be reduced 10-fold by introducing some adaptive mutations prior to the experiment, allowing measurements of fitness differences as small as 0.04%.