Although infection rates following orthopaedic surgery are considered to be low 2,3
, implant-associated OM remains a catastrophic outcome that often requires revision surgery and can lead to sepsis and death 1
. This problem is compounded by the emergence of multi-drug resistant strains and the absence of effective treatments for patients with methicillin-resistant S. aureus
. Progress in this area has been limited due to the absence of a quantitative animal model that can be utilized to elucidate molecular targets and evaluate novel interventions. From our assessment of the literature, we surmise that a quantitative OM model has not been developed for two reasons. First, the field has been overly concerned with intramedullary implant models, since this represents the more serious clinical condition 8–13
. Unfortunately, we found that this model gave rise to highly variable (temporal and spatial) lesions, making a reproducible, quantitative model very challenging, although others have recently succeeded 24
. In contrast, we have found that implantation of an infected transcortical pin always produces lesions adjacent to the pin, and never results in distal OM, hematogenous infection or death (). Thus, while it could be argued that the mechanisms of infection and treatment modalities differ between intramedullary and external fixation implants, we find the transcortical pin model to be the best approach to study OM in vivo
The second roadblock towards the development of a quantitative OM model is the difficulty in extracting individual live bacteria, classically known as colony forming units (CFU), from infected bone. Here we demonstrate two independent methods to overcome this obstacle. The first, nuc
RTQ-PCR, is a highly specific and sensitive method that has been successfully used to quantify S. aureus
levels in contaminated cheese 18
. It should be noted that although we control for DNA integrity via β-actin
RTQ-PCR, we have no way of knowing the total nuc
yield following our rigorous extraction procedures. Thus, it is likely that the nuc
genes per tibia that we present represent a fraction of the total number of bacteria originally present in the sample. Furthermore, it is likely that our ability to extract nuc
genes from infected tibiae becomes less efficient when the bacteria are residing in dense biofilm. Thus, the rather low nuc
gene levels observed in latent infections (day 18), may be an under representation of the actual bacterial load. This may also explain the remarkable effects of the anti-S. aureus
antibodies on nuc
gene levels (), as it is known that biofilm provide bacteria with an immune-privileged environment. Nevertheless, our RTQ-PCR results provide the first demonstration that: i) in vivo
bacterial load levels can be quantified during the establishment of OM, and ii) that the peak bacterial load is coincident with the generation of humoral immunity against the bacteria.
As mentioned above, two critical aspects of OM research that cannot be addressed by our RTQ-PCR approach are longitudinal studies and assessment of microbial metabolic activity. As research on the regulators of in vivo
biofilm formation has become a central focus in this field, developing a surrogate outcome measure of pre and post-biofilm growth is of great value. To this end we have investigated the utility of BLI, which has emerged as a research technique with enormous potential 25
. Contag and colleagues were the first to utilize bioluminescent strains of pathogens to study infection longitudinally in mice 26
. Subsequent studies have proven the value of BLI over conventional methods in studying disease and therapeutic interventions in animals 25
. More recently, this group generated bioluminescent S. aureus
Xen29 for this purpose 19
. In our hands, Xen29 behaves essentially the same at UAMS-1, which is the most widely used strain of S. aureus
used in OM research 9–13
. Thus, we adopted this approach to be compatible with μCT quantification of osteolysis and RTQ-PCR in our model of OM.
The first interesting result we obtained with BLI was that it peaked on day 4 (), well before the peak of bacterial load and the appearance of adaptive immunity (). Since BLI is a function of metabolic activity (protein synthesis), not bacterial load, our interpretation of these results is that there is a brief exponential bacterial growth phase that peaks on day 4, and is followed by the initiation of the biofilm growth phase that occurs at a low metabolic rate. Once this biofilm growth phase is initiated, perhaps due to the exhaustion of nutrients in the necrotic tissue, the bacterial load continues to increase. Microbes are shed from the biofilm until protective immunity is acquired on day 11. Afterwards, bacterial persistence is restricted to the biofilm in necrotic tissue indefinitely. To test this theory we postulated that at a given time during infection, nuc copy number (1 nuc gene per bacterium) only correlates with BLI (mean rate of luxA-E protein synthesis for all of the bacteria) during periods of homogenous growth. In support of this theory we found that no correlation exist during concomitant planktonic (high metabolic rate) and colonized (lower metabolic rate) bacterial growth, which is known to occur 48hr after infection, and when the inter-animal variability between the proportion of planktonic to colonized bacteria is expected to be great (). In contrast, when the bacteria are restricted to biofilm growth (low metabolic rate), due to acquired immunity at day 18, and there is no inter-animal variability between the proportions of planktonic to colonized bacteria, a significant correlation exists between nuc and BLI (). Furthermore, we found that the BLI:nuc ratio early on in infection (day 2) is 15-fold greater vs. chronic infection (day 18). While further studies are needed to formally demonstrate the kinetics of biofilm formation in vivo, our findings clearly distinguish these two phases of bacterial growth.
In summary, the development of a quantitative model of implant-associated OM opens the field to research that was previously unapproachable. New avenues include: the identification of biofilm genes through the characterization of mutant phenotypes, identification of diagnostic and/or protective antigens, and facile evaluation of infection-resistant implants such as the Selfprotective 'smart' devices 27
, and novel drug efficacy. Although there are some fundamental limitations of this model with regard to its ability to accurately represent the true clinical problems associated with infected intramedullary implants and prostheses, we find that this transtibial mouse model, which displays all of the salient features of infected external fixation pins, to be a quantitative model suitable for most of these needs.