We are interested in the tempo and mode of evolution in bacteria. Many traits of interest, scientifically and practically, involve a large number of genes and complex interactions with other organisms and the environment.  We integrate comparative and functional genomics over different evolutionary time-scales to better understand how and why these complex traits vary within and between bacterial populations and species.

We focus primarily on enterobacteria, a group that includes Escherichia coli K-12, a model strain of bacteria that has been studied by laboratories around the world since its original isolation in 1922.  This allows us to leverage the E. coli K-12 knowledgebase to understand related bacteria, but also allows us to examine the limits of generality of knowledge from this model system.  Along the way, this scientific journey has led us to develop new computational tools and resources.  Wherever possible, we try to leverage the investment to create tools that are useful to a broader research community.

The following vignettes describe some of the biological questions that motivate our research and some of the resources we have built.  That said, our scientific interests range beyond what is described here, and we welcome all opportunities to discuss these, and other past, present and future research endeavors!

Evolution of the Response to Oxygen Availability

We use computational and experimental approaches to study variation in regulatory and metabolic networks associated with the response to oxygen availability.

Metabolic Network Diagram

Enterobacteria, like many other types of bacteria and fungi, are able to live with, or without oxygen.  As cells transition between aerobic and anaerobic growth conditions, transcriptional regulation of up to 25% of the genes in the genome changes, and metabolic flux is redirected through different pathways to shift the mode of energy generation from aerobic respiration to anaerobic respiration or fermentation.  Oxygen availability also serves as a signal of other biological processes, including virulence of significant animal and plant pathogens.

By characterizing and comparing the structure and expression of oxygen-responsive regulatory and metabolic networks, we aim to understand how dynamic changes in oxygen availability shapes the distribution of bacteria in natural environments.

Evolution of Plant Pathogenic Enterobacteria

Often, when we think of enterobacteria, the first thing that comes to mind are the types that cause human disease, like E. coli and Salmonella.  Phylogenetic analyses using complete genomes, many of which were sequenced by our lab, show that several lineages have specialized in living in and on plant hosts.  We use comparative and functional analyses to understand the evolutionary history of enterobacteria associated with plants, learn the molecular and genetic basis of how they cause disease, and help improve surveillance of important agricultural pathogens.

This potato is infected with enterobacteria that cause diseases called soft rot (shown here) and blackleg. These pathogens can cause disease on a wide variety of plants. Damage from enterobacteria pose a significant agricultural and economic burden.

Mauve Genome Alignment Software

Mauve is a system for generating and visualizing alignments of complete genome sequences, that was originally developed in our laboratory.  The software is now maintained by Aaron Darling (Ph.D. 2006) at the University of Technology Sydney.

Mauve is used by many genome researchers around the world.  It is not uncommon for us to see figures made using Mauve at scientific conferences and in publications.  We were pleasantly surprised to find a Mauve alignment in a display at the Field Museum in Chicago (Photo by lab alumnus Guy Plunkett III, Spring 2018).

Genome Sequencing and Annotation

Many of our research projects involve sequencing and annotating genomes.  A Systematic Annotation Platform (ASAP) is a resource we developed to support these efforts.  ASAP can also be used to update annotations for published genomes over time as we learn more about gene functions and other features of interest.  It also allows us to store comparative genomics data, such as a lists of which genes are found in which organisms.

Feel free to explore the hundreds of genomes currently found in ASAP at here.

If you are interested in using ASAP for a genome you have sequenced, please contact us.