Gene gain and loss in bacterial genomes and the dynamics of ribosomes

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Although we now know the complete genome sequence of many organisms, we do not know the function of many genes and we have a poor understanding of the way genes are gained and lost. In bacteria, it is found that even when we look at different strains of the same species, they only share a fraction of their genes, and each genome contains unique genes not present in the others. For example, the presence or absence of certain genes can make the difference between a harmless bacterium and one that causes food poisoning, or it can explain why one strain is resistant to antibiotics but another is susceptible. More broadly, uptake of new genes may allow cells to change their lifestyle and colonize new niches. We will carry out a computational study of the distribution of presence and absence of genes across genomes. Genes are gained either by changes inside the cell or by insertion of 'foreign' genes from outside the cell - a process known as horizontal gene transfer. Horizontal transfer challenges the usual representation of evolution as a branching tree. We aim to estimate the rate of horizontal transfer and to understand to what extent the tree picture holds up to modern genomic data. The process of protein synthesis inside a cell is known as translation. Protein synthesis is vital to a cell, so we expect the translation process to be selected by evolution to efficiently produce proteins with limited resources. Ribosomes are the molecular complexes that are responsible for translation. Ribosomes move along messenger RNAs one after another like trains on a track. We expect there may be bottlenecks in translation that cause traffic jams of ribosomes to build up. We will develop computer simulations and mathematical theories of translation that can be used to interpret experimental data on the levels of expression of different genes and the way that natural selection operates on their gene sequences. Our work uses ideas from biophysics and links them to observations in genomics and microbiology. Trainees will gain skills in bioinformatics, genome analysis, statistical methods and software development that are sought after in Canada.