Single molecule photobleaching (SMPB) technology for counting of RNA, DNA, protein and other molecules in nanoparticles and biological complexes by TIRF instrumentation

Direct counting of biomolecules within biological complexes or nanomachines is demanding. Single molecule counting using optical microscopy is challenging due to the diffraction limit. The single molecule photobleaching (SMPB) technology for direct counting developed by our team (Shu et al., 2007 [18]; Zhang et al., 2007 [19]) offers a simple and straightforward method to determine the stoichiometry of molecules or subunits within biocomplexes or nanomachines at nanometer scales. Stoichiometry is determined by real-time observation of the number of descending steps resulted from the photobleaching of individual fluorophore. This technology has now been used extensively for single molecule counting of protein, RNA, and other macromolecules in a variety of complexes or nanostructures. Here, we elucidate the SMPB technology, using the counting of RNA molecules within a bacteriophage phi29 DNA-packaging biomotor as an example. The method described here can be applied to the single molecule counting of other molecules in other systems. The construction of a concise, simple and economical single molecule total internal reflection fluorescence (TIRF) microscope combining prism-type and objective-type TIRF is described. The imaging system contains a deep-cooled sensitive EMCCD camera with single fluorophore detection sensitivity, a laser combiner for simultaneous dual-color excitation, and a Dual-View (TM) imager to split the multiple outcome signals to different detector channels based on their wavelengths. Methodology of the single molecule photobleaching assay used to elucidate the stoichiometry of RNA on phi29 DNA packaging motor and the mechanism of protein/RNA interaction are described. Different methods for single fluorophore labeling of RNA molecules are reviewed. The process of statistical modeling to reveal the true copy number of the biomolecules based on binomial distribution is also described. (C) 2014 Elsevier Inc. All rights reserved.