Optical coherence tomography for label-free detection and characterization of methicillin-resistant S. aureus biofilms.

Abstract

Significance: Orthopedic implant-associated infections cause serious complications primarily attributed to bacterial biofilm formation and are often characterized by increased antibiotic resistance and diminished treatment response. Yet, no methods currently exist to identify biofilms intraoperatively-surgeons rely solely on their eyes and hands and cannot detect or differentiate infected tissue to determine the location and extent of contamination.

Aim: As the first step in addressing this unmet clinical need, here, we develop an optical coherence tomography (OCT)-based imaging method capable of detection in situ and quantification of one of the most dangerous orthopedic biofilms formed by methicillin-resistant Staphylococcus aureus (MRSA).

Approach: Growing biofilms on orthopedic hardware, we identify MRSA distinct optical signature through histogram-based multi-parametric texture analysis of OCT images and support the findings with bioluminescence imaging and scanning electron microscopy. Under identical experimental conditions, we identify an optical signature of Escherichia coli (E. coli) biofilms and use it to distinguish and quantify both species within MRSA-E. coli biofilms.

Results: The developed OCT-based methodology was successfully tested for (1) MRSA colonies delineation, (2) detection of metal hardware (an important feature for clinical translation where the metal surface of most orthopedic hardware is not flat), (3) automated quantification of biofilm thickness and roughness, and (4) identification of pores and, therefore, ability to evaluate the role of porosity-one of the critical biological metrics in relation to biofilm maturity and response to treatment. For the first time, we demonstrated complex pore structures of thick ( $>100\text{microns}$ ) MRSA biofilms in situ with an unprecedented level of detail.

Conclusions: The proposed rapid noninvasive detection/quantification of MRSA biofilms on metal surfaces and delineation of their complex network of pores opens new venues for label-free MRSA detection in preclinical models of trauma surgery, expansion to other bacterial strains, and further clinical translation.