Improved Single-Molecule Imaging Based on Photon Counting with an EMCCD Camera
2012
New breakthroughs in digital imaging have historically opened opportunities to scientists in bio-medical research. One important landmark of the last decade has been the development of the electron-multiplying charge coupled device (EMCCD), an imaging detector that uses an avalanche phenomenon to amplify the weak photo-electron signals. EMCCDs are well suited for ultralow light applications in that a single photo-electron can be amplified sufficiently to allow the possibility of photon counting. However, as with all electronic detectors, the noise increases greatly with an increase in gain, diminishing the overall sensitivity and dynamic range and thus compromising images.Recently, a new camera has been developed by Nuvu Cameras that significantly reduces the noise generated during the read-out process (up to 10 times) and allows more efficient photon counting. This major reduction of the noise threshold represents an opportunity for various low-light imaging applications including single-molecule studies.We present a demonstration of its applicability in a total internal reflection fluorescence microscopy (TIRFM) assay to visualize single biomolecules. In molecular biology, it is well established that most proteins exert their biological roles in complex with other proteins. Thus, detecting individual components and the structure of these complexes is essential to understand the mechanism of biological events. To this aim, we employ TIRFM imaged in photon counting mode for visualization of single centromeric nucleosomes, containing a histone variant known as CENP-A. We show that this technique is well suited to TIRFM and that it is capable of detecting single fluorescently labelled CENP-A in the nucleosome with an enhanced signal to noise ratio. The desired and improved properties of the assay such as high sensitivity and photon counting shall pave the way for comprehensive studies of single molecules in this and other biological contexts.
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