Special issue on high-resolution optical imaging

The pace of development in the field of advanced microscopy is truly breath-taking, and is leading to major breakthroughs in our understanding of molecular machines and cell function. This special issue of Journal of Optics draws attention to a number of interesting approaches, ranging from fluorescence and imaging of unlabelled cells, to computational methods, all of which are describing the ever increasing detail of the dynamic behaviour of molecules in the living cell. This is a field which traditionally, and currently, demonstrates a marvellous interplay between the disciplines of physics, chemistry and biology, where apparent boundaries to resolution dissolve and living cells are viewed in ever more clarity. It is fertile ground for those interested in optics and non-conventional imaging to contribute high-impact outputs in the fields of cell biology and biomedicine. The series of articles presented here has been selected to demonstrate this interdisciplinarity and to encourage all those with a background in the physical sciences to ‘dip their toes’ into the exciting and dynamic discoveries surrounding cell function. Although single molecule super-resolution microscopy is commercially available, specimen preparation and interpretation of single molecule data remain a major challenge for scientists wanting to adopt the techniques. The paper by Allen and Davidson [1] provides a much needed detailed introduction to the practical aspects of stochastic optical reconstruction microscopy, including sample preparation, image acquisition and image analysis, as well as a brief description of the different variants of single molecule localization microscopy. Since super-resolution microscopy is no longer restricted to three-dimensional imaging of fixed samples, the review by Fiolka [2] is a timely introduction to techniques that have been successfully applied to four-dimensional live cell super-resolution microscopy. The combination of multiple high-resolution techniques, such as the combination of light sheet and structured illumination microscopy (SIM), which efficiently utilize photon budget and avoid illuminating regions of the specimen not currently being imaged, hold the greatest promise for future biological applications. Therefore, the combined setup for SIM and single molecule localization microscopy (SMLM) described by Rossberger et al [3] will be very helpful and stimulating to advanced microscopists in further modifying their setups. The SIM image helps in identifying artefacts in SMLM reconstruction, e.g. when two active fluorophores are close together and get rejected as ‘out-of-focus’. This combined setup is another way to facilitate imaging live samples. The article by Thomas et al [4] presents another advance for biological super-resolution imaging with a new approach to reconstruct optically sectioned images using structured illumination. The method produces images with higher spatial resolution and greater signal to noise compared to existing approaches. This algorithm demonstrates great promise for reconstructing biological images where the signal intensities are inherently lower. Shevchuk et al [5] present a non-optic near field approach to imaging with a review of scanning ion-conductance microscopy. This is a powerful alternative approach for examining the surface dynamics of living cells including exo and endocytosis, unlabelled, and at the level of the single event. Here they present the first data on combining this approach with fluorescence confocal microscopy—adding that extra dimension. Different approaches to label-free live cell imaging are presented in the papers by Patel et al [6], Mehta and Oldenbourg [7], as well as Rogers and Zheludev [8]. All three papers bring home the excitement of looking at live cell dynamics without reporters—Patel et al [6] review both the potential of coherent anti-Stokes Raman scattering and biological applications, where specific biomolecules are detected on the basis of their biophysical properties. Polarized light microscopy as presented by Mehta and Oldenbourg [7], describe a novel implementation of this technology to detect dichroism, and demonstrate beautifully its use in imaging unlabelled microtubules, mitochondria and lipid droplets. Sub-wavelength light focusing provides another avenue to super-resolution, and this is presented by Rogers and Zheludev [8]. Speculating on further improvements, these authors expect a resolution of 0. 15λ. To date, the method has not been applied to low contrast, squishy and motile biotargets, but is included here for the clear potential to drive label-free imaging in new directions. A similar logic lies behind the inclusion of Parsons et al [9] where ultraviolet coherent diffractive imaging is further developed. These authors have demonstrated a shrink-wrap technique which reduces the integration time by a factor of 5, bringing closer the time when we have lab based imaging systems based on extreme ultraviolet and soft x-ray sources using sophisticated phase retrieval algorithms. Real biological specimens have spatially varying refractive indices that inevitably lead to aberrations and image distortions. Global refractive index matching of the embedding medium has been an historic solution, but unfortunately is not practical for live cell imaging. Adaptive optics appears an attractive solution and Simmonds and Booth [10] demonstrate the theoretical benefits of applying several adaptive optical elements, placed in different conjugate planes, to create a kind of ‘inverse specimen’ that unwarps phase distortions of the sample—but these have yet to be tested on real specimens. A difficulty in single molecule localization microscopy has been the determination of whether or not two molecules are colocalized. Kim et al [11] present a method for correcting bleed-through during multi-colour, single molecule localization microscopy. Such methods are welcome standards when trying to quantifiably interpret how close two molecules actually are. Rees et al [12] provide an invaluable overview of key image processing steps in localization microscopy. This paper is an excellent starting point for anyone implementing localization algorithms and the Matlab software provided will be invaluable; a strong paper on which to conclude our overview of the excellent articles brought together in this issue. One aspect brought home in several of these articles is the volume of data now being collected by high resolution live cell imaging. Data processing and image reconstruction will continue to be pressure points in the further development of instrumentation and analyses. We would hope that the series of papers presented here will motivate software engineers, optical physicists and biologists to contribute to the further development of this exciting field. References [1] Allen J R et al 2013 J. Opt. 15 094001 [2] Fiolka R et al 2013 J. Opt. 15 094002 [3] Rossberger S et al 2013 J. Opt. 15 094003 [4] Thomas B et al 2013 J. Opt. 15 094004 [5] Shevchuk A et al 2013 J. Opt. 15 094005 [6] Patel I et al 2013 J. Opt. 15 094006 [7] Mehta S B et al 2013 J. Opt. 15 094007 [8] Rogers E T F et al 2013 J. Opt. 15 094008 [9] Parsons A D et al 2013 J. Opt. 15 094009 [10] Simmonds R et al 2013 J. Opt. 15 094010 [11] Kim D et al 2013 J. Opt. 15 094011 [12] Rees E J et al 2013 J. Opt. 15 094012