New super-oscillatory technology for unlabelled super-resolution cellular imaging with polarisation contrast

Super-resolution microscopy is already showing huge benefits across the biosciences, but all widely-used techniques require the addition of fluorescent probes. We have demonstrated optical-super-resolution imaging in unlabelled living cells, using the phenomenon of super-oscillation. Super-oscillation is originally a mathematical phenomenon, first described in quantum mechanics. It is widely accepted that any function that is band-limited (in frequency) oscillates no faster (in time) than its fastest Fourier component. However, a band-limited super-oscillatory function may oscillate arbitrarily fast in regions of relatively low intensity. In optics, this means that we can create an arbitrarily small hotspot at the focus of a lens using engineered interference of light. However, super-oscillatory hotspots are necessarily surrounded by sidebands that contain some fraction of the optical power – trading efficiency for resolution. We replace the objective in a confocal microscope with a super-oscillatory lens and use the confocal pinhole to reject the light scattered from the sidebands. The resolution of the image is determined by the size of the super-oscillatory hotspot.We have developed a super-oscillatory system to image unlabelled cells at super-resolution and high speed. To do this we combine our super-oscillatory microscope with advanced polarisation-contrast imaging. The instrument is a modification of a standard confocal microscope, with two key components: spatial light modulators to shape the laser beam entering the microscope, and a liquid crystal panel to control the input polarisation. We capture four differently-polarised super-resolved images of the sample and then calculate the anisotropy and orientation angle of each pixel. This highlights those parts of a cell with significant molecular structuring, such as actin filaments, microtubules, and even protein-enriched lipid bilayers such as vesicles and cell membranes. We have applied this to a number of systems showing it is able to reveal new levels of information in living and moving biological samples