I am interested in the development and application of state-of-the-art high-throughput genomic approaches to studying bacterial disease. In particular, I am interested in the genetics, gene regulation, polymicrobial interactions and antibiotic resistance of the opportunistic pathogen Pseudomonas aeruginosa, which causes a wide range of infections in immunocompromised patients. The general approach I am applying to the study of these infections centers around the application of high-throughput sequencing-based technology to profile differential gene expression and the genetic bases of fitness in a variety of disease-related conditions. Currently, my studies focus on two main types of P. aeruginosa infections:
1.) Infections in the lungs of patients with the recessive genetic disease cystic fibrosis (CF). In patients with CF, the normal capacity of the lungs to clear microbes from the conducting airways is inhibited by a molecular defect in ion transport that results in a thick, dehydrated mucus layer. In addition to being difficult for the ciliated epithelium to clear from the airways, this mucus serves as a potent nutritional substrate for the microbes that inhabit these airways. For example, P. aeruginosa can grow to densities as high as 10 billion cells per mL of this mucus. Furthermore, work in the Whiteley lab has shown that certain nutrients present in this mucus signal to P. aeruginosa to increase virulence factor production. Yet fundamental questions remain about the lifestyle exhibited by P. aeruginosa in this mucus. What are the primary sources of nutrition for P. aeruginosa in the CF lung? What genes contribute to metabolism of these nutrients? I am seeking answers to these questions using a high-throughput sequencing technology known as Tn-Seq. I am also interested in how the presence of coinfecting microbes in the CF lung can affect the metabolism and antibiotic resistance exhibited by P. aeruginosa.
2.) Infections in chronic wounds. These wounds, which include bedsores and diabetic ulcers, are a rapidly growing healthcare problem in the United States, where their treatment is thought to comprise upwards of 10% of the national healthcare budget. And as factors that predispose patients to chronic wounds, such as diabetes, obesity and low socioeconomic status, are increasing in incidence nationwide, the impact of these wounds is set to increase. Infections in chronic wounds are typically polymicrobial in nature, yet P. aeruginosa is the most frequently isolated bacterium from these wounds. Interestingly, the presence of other bacteria in model P. aeruginosa chronic wound infections is associated with delayed healing and increased antibiotic resistance. The main hypothesis of my work on these infections is that interfering with these polymicrobial interactions can alleviate some of these synergistic outcomes seen in real polymicrobial chronic wound infections. To generate hypotheses regarding the molecular mechanisms of these interactions, I am applying Tn-Seq-based approaches to these model infections in the presence or absence of coinfecting microbes, and determining how the contribution of known or novel antibiotic resistance determinants to fitness changes in coinfection.