Measuring autofluorescence spectral signatures for detecting antibiotic-resistant bacteria using Bigfoot spectral flow cytometer

Application of flow cytometry to microbiology has been limited due to inadequate availability of bacterial-specific stains, expensive antibody-based fluorophores, ineffective stain cell permeability and challenges in differentiating bacterial cells from cell debris due to their similarity and their small size. In addition, staining cells demands multiple washing steps which limits the sensitivity of detection due to the cell volume that is up to two orders smaller than typical eukaryotic cells. Further, most flow cytometers are not equipped to handle pathogenic organisms. Autofluorescence-based detection of cells can be a useful method for bacterial detection as multiple washing steps can be avoided and it also reduces the time and cost of using stains. Multiple studies have shown that the autofluorescence in bacterial cells are mainly linked to specific proteins, enzymes, or enzyme cofactors such as Flavin Adenine Dinucleotide (FAD) and Nicotinamide Adenine Dinucleotide (NAD) which are involved in bacterial metabolism. In this report, we present a novel method for differentiation between clinically isolated antibiotic resistant and non-resistant bacteria by utilizing their autofluorescence spectral signatures. We utilized a spectral cytometer known as Bigfoot which is equipped with an integrated biosafety cabinet allowing easy handling of pathogenic organisms unlike any other flow cytometers. Bigfoot also has 9 lasers and 54 fluorescence detectors which we utilize to capture the bacterial spectral autofluorescence signatures. As a proof of principle, we initially stressed different types of bacteria (E.coli and Salmonella sp.) using gentamicin antibiotics by collecting spectral autofluorescence over different time points. The spectral signatures were compared with the non-stressed bacteria. We observed that the stressed bacteria showed an increase in autofluorescence at distinct excitation (Ultraviolet, Violet, and blue color) and emission wavelengths whereas the non-stressed did not. The same experiments were repeated to compare the autofluorescence signatures between Methicillin-resistant and methicillin susceptible staphylococcus aureus (MRSA and MSSA) which were stressed with oxacillin antibiotics. MSSA showed an increase in autofluorescence between 4 - 6 h after exposure to oxacillin. MRSA on the other hand showed no increase in autofluorescence and the autofluorescence between stressed and non-stressed MRSA had similar signatures. This demonstrated that the antibiotic resistant or susceptible strain can be detected by observing the change in autofluorescence signature at specific wavelengths in a few hours. This label-free, quantitative, and resistant-specific autofluorescence spectral signatures from the Bigfoot spectral flow cytometer could potentially be utilized for rapid detection of antibioticresistant strain.