Microbial Evolutionary Dynamics: Research

Current Research Projects

The research theme of our group is the evolution of genetic structure. We currently have projects on the evolution of genome structure (evolution of codon usage bias and tRNA pools) and the evolution of population genetic structure (the emergence of bet hedging strategies).

Evolution of genome structure: codon usage and tRNA gene pools

<p align="center"><strong>Figure 1. Biased and different use of the six leucine codons in the genomes of two bacterial species.</strong></p> Zoom Image

Figure 1. Biased and different use of the six leucine codons in the genomes of two bacterial species.

Most amino acids are coded for by more than one DNA codon. Codons within an amino acid set are not generally used equally; some are used more frequently than others. The precise nature of codon usage bias depends on the organism in question (Fig. 1). Optimal codon usage correlates with intracellular gene pools of tRNAs - the molecules that match DNA codons with the appropriate amino acid during protein synthesis (Duret, 2000; Dong et al., 1996). Organisms contain various tRNA species, each of which recognizes a different codon. Some tRNA species are present much more frequently than others. Codons matching high frequency tRNAs tend to be employed when translational speed is important (e.g., stress response genes; Rocha, 2004). The aim of our research is to gain empirical insight into the co-evolution of codon usage and tRNA pools. In particular, we are interested in whether codon usage drives the evolution of tRNA pools, or vice versa.

For these experiments we use Pseudomonas fluorescens: a diverse, naturally occurring bacterial species. We currently use three P. fluorescens strains: SBW25 (isolated in the UK), A506 (from East Coast USA) and Pf0-1 (from West Coast USA). These strains show different degrees of evolutionary relatedness and, correspondingly, their codon usage patterns and tRNA gene pools diverge to different extents. This makes P. fluorescens ideal for dissecting the co-evolution of codon use and tRNA pools in a natural system.

Our experimental approach has two main angles: (i) PhD student Anuradha Mukherjee is using synonymous genes - genes that differ at the level of DNA but not protein sequence - to investigate codon usage differences among our three strains, and (ii) PhD stduent Zahra Khomarbaghi is dissecting differences in tRNA gene pools.

Duret (2000). Trends Genet
Dong et al. (1996). J Mol Biol
Rocha (2004). Genome Res

Evolution of population genetic structure: the emergence of bet hedging

This project is in collaboration with Paul Rainey (Department of Microbial Population Dynamics), Frederic Bertels, Philippe Remigi and Gayle Ferguson (Massey University, NZ).

<p align="center"><strong>Figure 2: Two bet hedging genotypes evolved in parallel. </strong>Each produces two colony (left) and cell (right) types.</p> Zoom Image

Figure 2: Two bet hedging genotypes evolved in parallel. Each produces two colony (left) and cell (right) types.

Bet hedging – stochastic switching between phenotypes – is a widespread evolutionary adaptation that facilitates survival in unpredictable environments. There are many examples of bet hedging behaviour in nature, ranging from microbes to humans. However, very little is known about how bet hedging strategies emerge. An experiment in Paul Rainey’s laboratory saw the evolution of a bet hedging strategy in two parallel, independent evolutionary lineages of the bacterium P. fluorescens SBW25 (Beaumont et al., 2009). In both cases, the evolved bet hedging type produces colonies of two distinct phenotypes, with each type rapidly giving rise to both itself and the opposite type. This phenotype switching is mirrored at the cellular level by the production of capsulated and non-capsulated cells (Fig. 2).

We have already characterized the first of these two bet hedging types (line 1), including the phenotype, genotype, evolutionary history and - to some extent - molecular mechanism behind phenotype switching (Gallie et al., 2015; Beaumont et al., 2009). We are now interested in the second lineage (line 6). The aim is to characterize this genotype and contrast it with line 1. So far, we have seen that the phenotypes of the lineages are very similar, but the evolutionary and genetic basis of each type differ.

Gallie et al. (2015). PLoS Biol
Rainey et al. (2010). Microbial Cell Fact
Beaumont et al. (2009). Nature

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