Comparison of 3 real-time, quantitative murine models of staphylococcal biofilm infection by using in vivo bioluminescent imaging.

Staphylococcus aureus is a leading cause of cutaneous, pulmonary, bloodstream, and surgical infections worldwide. The growing prevalence of antimicrobial-resistant species in both hospital and community settings has inhibited therapeutic success considerably, resulting in increased rates of chronic and recurrent infections and rising healthcare costs.1,3 More than half of all S. aureus isolates from hospital-acquired infections currently are classified as methicillin-resistant S. aureus, which are resistant to all β-lactam antimicrobials.9 In addition, some strains of methicillin-resistant S. aureus have developed resistance to additional antimicrobial agents, including those previously reserved for multiply resistant organisms.8 One of the most complex resistance mechanisms of the S. aureus organism is the ability to form biofilms. The term biofilm refers to communities of bacterial cells that are organized within an extracellular polysaccharide matrix, which attaches to surfaces including indwelling medical devices and contaminated skin wounds. Organisms within a biofilm have increased protection from many components of the host's immune defenses as well as from exogenously administered antimicrobials, making this growth pattern a hallmark of chronic infection.6 Due to variations among virulence factors expressed by biofilm organisms in comparison with their planktonic counterparts, therapies that are developed by using well-established models of septicemia or pneumonia may not be effective against biofilm infections involving the same species of bacteria.1 The structure of the biofilm matrix itself further inhibits penetration and bacterial clearance by therapeutic compounds.6 It is therefore of considerable interest to the biomedical research community to develop and evaluate reliable models of biofilm infections to facilitate the study of therapeutic candidates targeting this important defense mechanism. Historically, the study of infectious disease has required euthanasia of large cohorts of animals at several experimental time points to enable tissue collection and culture. However, recent advances in in vivo imaging technology have established improved systems for studying these disease processes through noninvasive methods. Bioluminescent imaging (BLI) is often used to study tumor progression and metastasis, inflammation, and infection by using cells and organisms engineered to express the enzyme luciferase. This enzyme catalyzes a light-producing reaction that allows detection and image generation by specialized CCD cameras.2,4 The bioluminescent signal emitted by metabolically active luciferase-expressing cells are detected by the CCD camera through the tissues of living animals, eliminating the need to euthanize subjects for bacterial quantification.4 This advance not only decreases the number of animals required to obtain statistically significant results but also reduces interindividual variability by allowing each animal to serve as its own control over time. An effective model of biofilm infections that uses in vivo imaging technology must have several characteristics to permit accurate assessment of therapeutic efficacy in the setting of antimicrobial drug development. The model must be able to establish a reliable and robust infection capable of producing a strong bioluminescent signal of sufficient duration to allow the detection of differences between treated and untreated animals. In addition, complications such as the development of septicemia and implant loss should be minimal, because these events can significantly reduce sample size and result in the need to use additional animals. Furthermore, a useful model of biofilm infections must permit reliable correlation between bioluminescent signal measurement and actual bacterial counts. The present study evaluated 3 previously described implant-associated infection models into which specific modifications have been incorporated to facilitate the use of BLI. These 3 models are the tibial intramedullary pin model, subcutaneous catheter model, and the subcutaneous mesh model. Each model has particular benefits for modeling certain aspects of chronic bacterial infection. We hypothesized that one of these models would prove most effective for adaptation to the BLI system of repeated evaluation of bacterial burden at the infection site over time.