Networks of gene sharing among viruses
Bacteriophages (phage) are viruses that infect bacteria, and their genomes often contain genes that reflect different evolutionary histories thanks to horizontal gene transfer among phages and between phages and their hosts. As part of my work in the Putonti Lab, we explored how gene sharing among phages reflects viral ecology and evolution. In a recent paper, we built a network where each node is a gene and two nodes are connected if a homolog of each gene is found in the same genome. Using this network, we observed that virus genes cluster together in groups corresponding to the genus of the phage's host, and host-by-host proximity in the network reflected the phylogenetic relationships among bacteria.
Bacteriophages (phage) are viruses that infect bacteria, and their genomes often contain genes that reflect different evolutionary histories thanks to horizontal gene transfer among phages and between phages and their hosts. As part of my work in the Putonti Lab, we explored how gene sharing among phages reflects viral ecology and evolution. In a recent paper, we built a network where each node is a gene and two nodes are connected if a homolog of each gene is found in the same genome. Using this network, we observed that virus genes cluster together in groups corresponding to the genus of the phage's host, and host-by-host proximity in the network reflected the phylogenetic relationships among bacteria.
Studying phage transmission using host phylogenies
A prophage is a phage that is maintained within a bacterial genome over several generations. When a prophage is found in a bacterial genome, it is not generally known how recently it was acquired or how actively it might spread to related hosts. Because these phages are sequenced along with their hosts, it is possible to put the ecological history of phage transmission into the context of their hosts' evolution. To that end, I borrowed tools from phylogenetics for estimating rates of evolution to instead estimate rates of phage acquisition. The first example of this method was recently published, and I am currently extending it to additional hosts.
Coevolution of filamentous phage M13 and E. coli
Filamentous phages (Inoviridae) are a family of (super-cool) bacteriophages that infect a variety of bacterial species. These viruses are especially interesting, because they can reproduce in extraordinary numbers (a culture of E. coli infected with M13 can produce a trillion phages per mL in a matter of hours) without killing their hosts. Interestingly, these phages often encode genes that affect the virulence of human pathogens (e.g. Vibrio cholerae) and agricultural pests (e.g. Ralstonia solanacearum).
In my PhD research, I studied how these viruses coevolve with E. coli under different conditions, including cases where the phage evolved to benefit the bacteria. The first paper from this work can be found here. In my research in the Harcombe Lab, I also examined how these viruses affect the metabolism of their hosts.
Filamentous phages (Inoviridae) are a family of (super-cool) bacteriophages that infect a variety of bacterial species. These viruses are especially interesting, because they can reproduce in extraordinary numbers (a culture of E. coli infected with M13 can produce a trillion phages per mL in a matter of hours) without killing their hosts. Interestingly, these phages often encode genes that affect the virulence of human pathogens (e.g. Vibrio cholerae) and agricultural pests (e.g. Ralstonia solanacearum).
In my PhD research, I studied how these viruses coevolve with E. coli under different conditions, including cases where the phage evolved to benefit the bacteria. The first paper from this work can be found here. In my research in the Harcombe Lab, I also examined how these viruses affect the metabolism of their hosts.
How does transmission mode affect the evolution of benefits provided by symbionts to their hosts?
Most models of host-symbiont evolution make assumptions about how symbiont transmission mode correlates with the costs of interaction (e.g. parasitic symbionts that are better at transmitting between hosts will also be more harmful to their hosts). Very few models also account for possible correlations between symbiont transmission and the benefits that mutualistic symbionts might offer their hosts. I considered a set of adaptive dynamics models and showed that any source of positive covariance between symbiont horizontal transmission and these beneficial traits may shift our predictions for how transmission mode affects symbiont evolution. Under these conditions, horizontal transmission will actually increase selection on beneficial traits, whereas greater vertical transmission will weaken selection. The published work can be found here.
Most models of host-symbiont evolution make assumptions about how symbiont transmission mode correlates with the costs of interaction (e.g. parasitic symbionts that are better at transmitting between hosts will also be more harmful to their hosts). Very few models also account for possible correlations between symbiont transmission and the benefits that mutualistic symbionts might offer their hosts. I considered a set of adaptive dynamics models and showed that any source of positive covariance between symbiont horizontal transmission and these beneficial traits may shift our predictions for how transmission mode affects symbiont evolution. Under these conditions, horizontal transmission will actually increase selection on beneficial traits, whereas greater vertical transmission will weaken selection. The published work can be found here.
Coevolution in complex communities
Unlike most laboratory environments, microorganisms are generally found in complex communities and engage in direct and indirect interactions with other community members. Exploring more complex communities in the lab creates a number of exciting opportunities for exploring the ecology and (co)evolution of microbes.
In the Harcombe Lab, I worked with a synthetic community composed of E. coli, S. enterica, and M. extorquens. Each species in the community can provide resources used by other community members, and this metabolic exchange means that we can manipulate interactions within the community by altering the media composition. My work with this system has largely focused on comparing how each species evolves in response to selection for rapid settling when grown on their own versus when grown as a cooperative community. Each species also encodes a different fluorescent protein, which enables some really fun microscopy!
Unlike most laboratory environments, microorganisms are generally found in complex communities and engage in direct and indirect interactions with other community members. Exploring more complex communities in the lab creates a number of exciting opportunities for exploring the ecology and (co)evolution of microbes.
In the Harcombe Lab, I worked with a synthetic community composed of E. coli, S. enterica, and M. extorquens. Each species in the community can provide resources used by other community members, and this metabolic exchange means that we can manipulate interactions within the community by altering the media composition. My work with this system has largely focused on comparing how each species evolves in response to selection for rapid settling when grown on their own versus when grown as a cooperative community. Each species also encodes a different fluorescent protein, which enables some really fun microscopy!
