Many types of infections, especially chronic infections, are polymicrobial – meaning that two or more species of microbes occupy the infection site. Polymicrobial infections often display higher level of antimicrobial resistance and result in a longer time to host recovery compared with single-microbe infections. We focus on the chronic polymicrobial infections cystic fibrosis, chronic wounds, and periodontitis (gum disease). While the pathogens vary between these infections sites, across all these systems, we are interested in how polymicrobial interactions influence pathogen physiology and virulence.
Chronic wound infections affect 6.5 million Americans annually with an annual cost of ~$25 billion. These infections are predominantly polymicrobial, with an average of 6 species isolated from a single infection. S. aureus and P. aeruginosa are the most commonly isolated microorganisms from chronic wounds, and wounds that harbor both species are asociated with increased wound severity and increased healthcare costs. To understand the physiology of S. aureus and P. aeruginosa during polymicrobial chronic wound infection, we are using a murine infection model in combination with genomic techniques such as RNA-seq and transposon insertion sequencing (Tn-Seq) (Turner et al. 2015; Ibberson et al. 2017)
Cystic fibrosis (CF) is a genetic disorder, which results in patients that are highly susceptible to bacterial infection, with two of the most commonly associated pathogens being Pseudomonas aeruginosa and Staphylococcus aureus. Despite their clinical impact, there is a lack of robust models to study these infections. The Whiteley lab has developed a synthetic CF sputum media (SCFM2) – designed based on the chemical analyses of authentic CF sputum from patients (Palmer et al. 2005, Palmer et al. 2007). The physical and nutritional properties are similar to actual CF sputum and we have previously shown that the genes required for P. aeruginosa bacterial growth are almost identical in natural vs. synthetic sputum (Turner et al. 2015). SCFM2 also supports biofilm growth in the form of small dense clusters (~10-10,000 cells) called aggregates (Darch et al. 2017). We are currently utilizing this media in combination with multiple techniques, including high resolution microscopy and high throughput genomics to study how bacterial populations develop in an environment that closely mimics chronic infection.
The most common polymicrobial infection is periodontitis, or gum disease, which affects almost half of the adult population in the United States. The high prevalence of this disease is in part due its polymicrobial nature; over 400 unique species of bacteria have been identified in the oral cavity. In children and young adults, aggressive periodontitis can rapidly lead to oral soft tissue and bone damage. A key contributor to the development of aggressive periodontitis is the Gram-negative bacterium Aggregatibacter actinomycetemcomitans (Aa). We are focused on understanding the physiology of Aa in the host environment and how polymicrobial interactions impact the metabolism and spatial organization of Aa. In addition, we are interested in understanding the progression and metabolic profile of periodontitis in human patients using techniques such as metatranscriptomic sequencing analysis (Jorth et al. 2014).