Structured illumination microscopy can achieve super-resolution in fluorescence imaging. The sample is illuminated with periodic light patterns, and a series of images are acquired for different pattern positions, also called phases. From these a super-resolution image can be computed. However, for an artefact-free reconstruction it is important that the pattern phases be known with very high precision. If the necessary precision cannot be guaranteed experimentally, the phase information has to be retrieved a posteriori from the acquired data. We present a fast and robust algorithm that iteratively determines these phases with a precision of typically below λ/100. Our method, which is based on cross-correlations, allows optimisation of pattern phase even when the pattern itself is too fine for detection, in which case most other methods inevitably fail. We analyse the performance of this method using simulated data from a synthetic 2D sample as well as experimental single-slice data from a 3D sample and compare it with another previously published approach.

Due to diffraction, the resolution of imaging emitted light in a fluorescence microscope is limited to about 200 nm in the lateral direction. Resolution improvement by a factor of two can be achieved using structured illumination, where a fine grating is projected onto the sample, and the final image is reconstructed from a set of images taken at different grating positions. Here we demonstrate that with the help of a spatial light modulator, this technique can be used for imaging slowly moving structures in living cells.

The spatial distribution of the target (t-)SNARE proteins (syntaxin and SNAP-25) on the plasma membrane has been extensively characterized. However, the protein conformations and interactions of the two t-SNAREs in situ remain poorly defined. By using super-resolution optical techniques and fluorescence lifetime imaging microscopy, we observed that within the t-SNARE clusters syntaxin and SNAP-25 molecules interact, forming two distinct conformations of the t-SNARE binary intermediate. These are spatially segregated on the plasma membrane with each cluster exhibiting predominantly one of the two conformations, representing the two- and three-helical forms previously observed in vitro. We sought to explain why these two t-SNARE intermediate conformations exist in spatially distinct clusters on the plasma membrane. By disrupting plasma membrane lipid order, we found that all of the t-SNARE clusters now adopted a single conformational state corresponding to the three helical t-SNARE intermediates. Together, our results define spatially distinct t-SNARE intermediate states on the plasma membrane and how the conformation adopted can be patterned by the underlying lipid environment.

The structural and functional organization of biological tissues relies on the intricate interplay between chemical and mechanical signaling. Whereas the role of constant and transient mechanical perturbations is generally accepted, several studies recently highlighted the existence of longrange mechanical excitations (i.e., waves) at the supracellular level. Here, we confine epithelial cell mono-layers to quasi-one dimensional geometries, to force the establishment of tissue-level waves of well-defined wavelength and period. Numerical simulations based on a self-propelled Voronoi model reproduce the observed waves and exhibit a phase transition between a global and a multi-nodal wave, controlled by the confinement size. We confirm experimentally the existence of such a phase transition, and show that wavelength and period are independent of the confinement length. Together, these results demonstrate the intrinsic origin of tissue oscillations, which could provide cells with a mechanism to accurately measure distances at the supracellular level.