SBIR-STTR Award

Bacterial identification using DNA hybridization probes has become increasingly sophisticated and accurate as probe technology and methods have improved. Up to now, however, instrumentation for detecting fluorescently- labeled probes has not been able to fully exploit the capabilities of such probes to identify high complex mixtures of genotypes in situ. Positive identification of single variant organisms in large populations of similar cells is also problematic. Fluorescent labeling methods are ultimately limited by the number of different spectral 'fingerprints' that can be distinguished by the imaging system that is used to measure and sort them. We propose to use a set of compatible fluorophores and recently developed KAIROS instrumentation and spectral deconvolution and sorting algorithms to increase the number of fluorescent tags that can be simultaneously distinguished, thus enabling accurate 'fingerprinting' of bacteria. In Phase 1 we will develop a set of these probes and demonstrate their efficacy on microscopic test targets. In Phase 2 we will apply the library of probes and the spectral deconvolution software to correctly identify highly complex mixtures of cells in situ by spectral sorting. This new technology for multispectral bacterial identification (Mbid) will benefit clinical and environmental microbiology as well as biotechnology. PROPOSED COMMERCIAL APPLICATION: Rapid and accurate fingerprinting of bacteria by multispectral fluorescent probes and fluorescence imaging microspectrophotometry is an enabling technology for both clinical and environmental aspects of microbial ID

During Phase 1, a multispectral optical technique was developed to simultaneously classify individual bacterial cells within mixed populations. Multispectral Bacterial Identification (mBID) combines innovations in microscopy with a software analysis program to measure and categorize the fluorescence signals from multiplexed 16S ribosomal RNA probes hybridized to populations of different bacteria. Software was developed to identity individual bacteria at the level of species within these mixed populations. In Phase 2, we plan to couple this new multispectral technology to existing identification technologies that utilize 16S rRNA sequence alignment. Using this integrated identification protocol, bacteria that may be associated with chronic conditions (e.g., prostatitis and vaginosis) will be identified first by analyzing their 16S rDNA sequences and then by visualizing them with fluorescent probes hybridized to their 16S rRNA in situ. Phase 2 activities will also include a merger of many of the steps required in both sequence-based and spectral-based ID. A major focus of this work will be to further automate the Phase 1 prototype instrument in terms of acquisition and radiometric processing of multispectral image stacks. These efforts will facilitate a single technology platform for multispectral rRNA-based bacterial ID that is generally applicable to populations of (unculturable) bacteria growing within consortia and biofilms, with applications in both clinical and environmental microbiology. PROPOSED COMMERCIAL APPLICATIONS: We shall provide an integrated technology platform to the general microbiology research community for rRNA-based identification of multiple bacterial species in a single sample. In Phase 3, this technology could be used in clinical research laboratories to follow diseases that may be caused by bacterial consortia or biofilms. The size of the in vitro microbiology diagnostic market was recently estimated by Market Data International to be $1.4 billion.