The mysteries of bacterial genomes
E. coli MG1655 is probably the best studied model organism, yet about a third of its annotated genes have no known function and it's likely that significant numbers of functional genomic elements remain completely undiscovered. This issue is much worse for pathogens, even well studied organisms, like Pseudomonas aeruginosa, for which many genes are simply listed as "hypothetical protein". We are broadly interested in developing and applying high throughput genetic methods to shed light on the remaining mysteries within bacterial genomes. The Saunders Lab has active projects with E. coli and P. aeruginosa and seeks to understand the basic biology of these organisms at genomic scales, as well as specific antibiotic resistance mechanisms that can drive clinical outcomes.
Check out our ORBIT genetics project!
Better reverse genetics
Typically, strategies for modifying bacterial genomes take one of two approaches. Reverse genetics enables very accurate modifications, but is typically low throughput (e.g. GFP fusion). Forward genetics enables modifications to be made at high throughput across the genome, but these techniques are random and therefore imprecise (e.g. transposon mutagenesis).
What if we could perform bacterial genetics with high throughput and high accuracy?
Designer mutant libraries
The Saunders Lab has developed new genetic techniques for precisely constructing mutant libraries at high throughput. Genomic modifications can be specified by short DNA oligos that encode homology to different positions in bacterial genomes. With modern DNA synthesis, tens of thousands of oligos can be computationally designed and ordered routinely. Therefore mutant libraries can be designed and constructed to ask new questions about bacteria at genomic scales.
Genes and proteins do not work alone, but instead these components interact to form complex and dynamic networks that determine cellular physiology. Accurate and high throughput tools will enable the construction of double mutant and combinatorial libraries that can be used to measure interactions between cellular components.
Check out more details about our genetic methods here: