Cell-to-Cell Variation in Antibiotic Resistance
While heritable changes such as mutations or genetic exchange have traditionally been studied as the source of drug resistance, they cannot explain circumstances where antibiotics fail to completely eradicate infection. Recent studies at the single-cell level have revealed that transient, non-genetic mechanisms play a critical role in the persistence and recurrence of infection. We have shown that these mechanisms can also predispose cells towards mutation, and we specifically focused on expression of multi-drug efflux pumps in these studies (El Meouche, Dunlop - Science 2018). We have also studied a prototypical example of a transcription factor implicated in drug resistance called MarA. We have shown that stochastic expression of MarA can generate a continuum of resistance levels within an isogenic population. By using a combination of stochastic mathematical models and single-cell time-lapse microscopy experiments, we have confirmed the presence of stochastic expression of MarA (Garcia-Bernardo, Dunlop - PLOS Comp. Bio. 2013; El Meouche, et al. - Scientific Reports 2016). Critically, we have demonstrated that stochastic MarA expression correlates with survival of antibiotic exposure.
Improving Biofuel Synthesis
We are working on a high-throughput chemical imaging platform for optimizing biofuel synthesis using synthetic biology tools. Through a collaboration with the Cheng Lab and Wong Lab, we are working on a label-free method for detecting biofuels and other bioproducts within single cells.
In previous work, we focused on engineering robust hosts for microbial biofuel production. Microbes can be engineered to produce biologically-derived replacements for gasoline, diesel, and jet fuel. However, a major technical challenge in using microorganisms to produce biofuel is that cells can only tolerate limited concentrations of typical fuels. We have shown that efflux pumps are very effective at removing biofuel from cells, leading to improvements in biofuel tolerance (Dunlop, et al. - Molecular Systems Biology 2011). However, overexpressing these membrane transporters can also decrease cell viability. Thus, there is a trade-off between biofuel toxicity and pump overexpression toxicity, which we have characterized experimentally and through modeling (Turner, Dunlop - ACS Synthetic Biology 2014). We developed a novel synthetic feedback strategy for controlling pump expression (Siu, et al. - ACS Synthetic Biology 2017).
Feedback Control Systems for Synthetic Biology
Feedback allows biological systems to control gene expression precisely and reliably, even in the presence of uncertainty. However, experimental implementations of biomolecular control systems are still far from satisfying performance specifications typically achieved by electrical or mechanical control systems.
We have designed and modeled controllers that employ RNA transcriptional regulators to achieve closed loop control where feedback is introduced via molecular sequestration. Our results indicate that RNA regulators are well-suited for building robust and precise feedback controllers for regulating gene expression, providing a promising direction for future biochemical feedback circuit designs (Agrawal, et al. - ACS Synthetic Biology 2018). In a second project, we used a mathematical model to predict that there is a trade-off between biofuel and pump toxicity. We addressed this by experimentally constructing a synthetic feedback loop in E. coli using a sensor for biofuel stress coupled with an efflux pump that can export biofuel (Siu, et al. - ACS Synthetic Biology 2017). We are also interested in implementing feedback via a computer or micro-controller, developing systems that integrate biological parts with computer-based feedback control (Lugagne, Dunlop - Current Opinions in Systems Biology 2019).