Flexible implementation of modulated localisation microscopy based on DMD.

Localisation microscopy of individual molecules allows one to bypass the diffraction limit, revealing cellular organisation on a nanometric scale. This method, which relies on spatial analysis of the signal emitted by molecules, is often limited to the observation of biological objects at shallow depths, or with very few aberrations. The introduction of a temporal parameter into the localisation process through a time-modulated excitation was recently proposed to address these limitations. This method, called ModLoc, is demonstrated here with an alternative flexible strategy. In this implementation, to encode the time-modulated excitation a digital micromirror device (DMD) is used in combination with a fast demodulation approach, and provides a twofold enhancement in localisation precision. Layout: Nowadays, we can use an optical microscope to observe how proteins are organised in 3D within a cell at the nanoscale. By carefully controlling the emission of molecules in both space and time, we can overcome the limitations set by the diffraction limit. This allows us to pinpoint the exact location of molecules more precisely. However, the usual spatial analysis method limits observations to shallow depths or causing low distortion of optical waves. To overcome these restrictions, a recent approach introduces a temporal element to the localisation process. This involves changing the illumination over time to enhance the precision of localisation. This method, known as ModLoc, is showcased here using a flexible and alternative strategy. In this setup, a matrix of micrometric mirrors, working together with a fast demodulation optical module, is used to encode and decode the time-modulated information. This combination results in a twofold improvement in localisation precision.

Combining deep learning approaches and point spread function engineering for simultaneous 3D position and 3D orientation measurements of fluorescent single molecules.

Point Spread Function (PSF) engineering is an effective method to increase the sensitivity of single-molecule fluorescence images to specific parameters. Classical phase mask optimization approaches have enabled the creation of new PSFs that can achieve, for example, localization precision of a few nanometers axially over a capture range of several microns with bright emitters. However, for complex high-dimensional optimization problems, classical approaches are difficult to implement and can be very time-consuming for computation. The advent of deep learning methods and their application to single-molecule imaging has provided a way to solve these problems. Here, we propose to combine PSF engineering and deep learning approaches to obtain both an optimized phase mask and a neural network structure to obtain the 3D position and 3D orientation of fixed fluorescent molecules. Our approach allows us to obtain an axial localization precision around 30 nanometers, as well as an orientation precision around 5 degrees for orientations and positions over a one micron depth range for a signal-to-noise ratio consistent with what is typical in single-molecule cellular imaging experiments.

Time-modulated excitation for enhanced single-molecule localization microscopy.

Structured illumination in single-molecule localization microscopy provides new information on the position of molecules and thus improves the localization precision compared to standard localization methods. Here, we used a time-shifted sinusoidal excitation pattern to modulate the fluorescence signal of the molecules whose position information is carried by the phase and recovered by synchronous demodulation. We designed two flexible fast demodulation systems located upstream of the camera, allowing us to overcome the limiting camera acquisition frequency and thus to maximize the collection of photons in the demodulation process. The temporally modulated fluorescence signal was then sampled synchronously on the same image, repeatedly during acquisition. This microscopy, called ModLoc, allows us to experimentally improve the localization precision by a factor of 2.4 in one direction, compared to classical Gaussian fitting methods. A temporal study and an experimental demonstration both show that the short lifetimes of the molecules in blinking regimes impose a modulation frequency in the kilohertz range, which is beyond the reach of current cameras. A demodulation system operating at these frequencies would thus be necessary to take full advantage of this new localization approach. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 2)'.

Combining 3D single molecule localization strategies for reproducible bioimaging.

Here, we present a 3D localization-based super-resolution technique providing a slowly varying localization precision over a 1 µm range with precisions down to 15 nm. The axial localization is performed through a combination of point spread function (PSF) shaping and supercritical angle fluorescence (SAF), which yields absolute axial information. Using a dual-view scheme, the axial detection is decoupled from the lateral detection and optimized independently to provide a weakly anisotropic 3D resolution over the imaging range. This method can be readily implemented on most homemade PSF shaping setups and provides drift-free, tilt-insensitive and achromatic results. Its insensitivity to these unavoidable experimental biases is especially adapted for multicolor 3D super-resolution microscopy, as we demonstrate by imaging cell cytoskeleton, living bacteria membranes and axon periodic submembrane scaffolds. We further illustrate the interest of the technique for biological multicolor imaging over a several-µm range by direct merging of multiple acquisitions at different depths.