Ultrafast Bioimaging

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Project Summary: The PI proposes to develop an ultrafast bioimaging program which could open a new area of investigation and lead to a series of fundamental scientific discoveries. Space and time, two key physical dimensions, constitute the basis of modern metrology. In bio-imaging, as recognized by the 2014 Nobel Prize in chemistry, there have been breathtaking advances in improving the spatial resolution of microscopic imaging, resulting in an impressive arsenal of nanoscopy tools that can break the diffraction limit of light. Despite equally important, the pursuit of a high-temporal resolution has only recently caught attention thanks to the emergence of several enabling technologies. The motivation to develop these ultrafast imagers originates from the landscape shift of the contemporary biology from morphological explorations and phenotypic probing of organisms to seeking quantitative insights into underlying mechanisms at molecular levels. The transient molecular events occur at a timescale varying from tens and hundreds of microseconds that ligands take to bind, to tens of femtoseconds that molecules take to vibrate. Ultrafast imaging, therefore, is essential for observation and characterization of such dynamic events. Heretofore, most ultrafast phenomena at microscopic scales were probed using non-imaging-based methods. However, since most transient molecular events are a consequence of a cascade of molecular interactions, rather than occurring in isolation, the lack of images limits the scope of the analysis. On the other hand, despite the capability of capturing two-dimensional images, conventional cameras based on electronic image sensors, such as CCD and CMOS, fall short in providing a high frame rate under desirable imaging conditions due to electronic bandwidth limitations (data transfer, digitalization, and writing). To solve this fundamental problem, our strategy is to introduce the paradigm of compressed sensing into high-speed optical imaging. Rather than measuring each spatiotemporal voxel of an event datacube, we will leverage the compressibility of biological scenes and thereby utilizes the camera’s bandwidth more efficiently— the image data is compressed before being digitalized and transferred to the host computer. This feature will make our approaches especially advantageous for recording high-speed image data, which otherwise would require tremendous camera bandwidth and hardware resources if measured under Nyquist sampling. Based on this strategy, we will explore ultrafast bioimaging at a frame rate from a few MHz to ten THz, a range which is essential for understanding the biomolecular behaviors but currently inaccessible by conventional high-speed cameras. The resultant research program will ultimately lead to a new generation of ultrafast bioimagers and make transformative advancements to the state-of-the-art methods.