Correlative light and electron microscopy (CLEM) is becoming increasingly popular within the life sciences. The diversity of light microscopy (LM) and electron microscopy (EM) modalities has led researchers to develop a multitude of CLEM workflows tailored to different scientific investigations^{1, 2}. Finding the corresponding area between LM and EM images can be facilitated with specific sample holders, finder grids, laser marks or pattern recognition¹. However, for all these workflows, the accurate association of a fluorescent object with its corresponding ultrastructure from data sets differing in scales by several orders of magnitude remains a universal bottleneck. Although several software solutions to the problem of achieving accurate association have been proposed (Supplementary Note 1), there is currently no available open-access software to achieve high-accuracy localization independent of specific registration fiducials that also offer nonrigid registration both in two and three dimensions (2D and 3D) and semisupervised registration.

We have developed a 3D super-resolution microscopy method that enables deep imaging in cells. This technique relies on the effective combination of multifocus microscopy and astigmatic 3D single-molecule localization microscopy. We describe the optical system and the fabrication process of its key element, the multifocus grating. Then, two strategies for localizing emitters with our imaging method are presented and compared with a previously described deep 3D localization algorithm. Finally, we demonstrate the performance of the method by imaging the nuclear envelope of eukaryotic cells reaching a depth of field of ~4µm.

Optogenetic control of individual neurons with high temporal precision within intact mammalian brain circuitry would enable powerful explorations of how neural circuits operate. Two-photon computer-generated holography enables precise sculpting of light and could in principle enable simultaneous illumination of many neurons in a network, with the requisite temporal precision to simulate accurate neural codes. We designed a high-efficacy soma-targeted opsin, finding that fusing the N-terminal 150 residues of kainate receptor subunit 2 (KA2) to the recently discovered high-photocurrent channelrhodopsin CoChR restricted expression of this opsin primarily to the cell body of mammalian cortical neurons. In combination with two-photon holographic stimulation, we found that this somatic CoChR (soCoChR) enabled photostimulation of individual cells in mouse cortical brain slices with single-cell resolution and <1-ms temporal precision. We used soCoChR to perform connectivity mapping on intact cortical circuits.

Single-molecule localization microscopy techniques have proven to be essential tools for quantitatively monitoring biological processes at unprecedented spatial resolution. However, these techniques are very low throughput and are not yet compatible with fully automated, multiparametric cellular assays. This shortcoming is primarily due to the huge amount of data generated during imaging and the lack of software for automation and dedicated data mining. We describe an automated quantitative single-molecule-based super-resolution methodology that operates in standard multiwell plates and uses analysis based on high-content screening and data-mining software. The workflow is compatible with fixed- and live-cell imaging and allows extraction of quantitative data like fluorophore photophysics, protein clustering or dynamic behavior of biomolecules. We demonstrate that the method is compatible with high-content screening using 3D dSTORM and DNA-PAINT based super-resolution microscopy as well as single-particle tracking.

Multifocus microscopy (MFM) allows sensitive and fast three-dimensional imaging. It relies on the efficient design of diffraction phase gratings yielding homogeneous intensities in desired diffraction orders. Such performances are however guaranteed only for a specific wavelength. Here, we discuss a novel approach for designing binary phase gratings with dual color properties and improved diffraction efficiency for MFM. We simulate binary diffraction gratings with tunable phase shifts to explore its best diffraction performances. We report the design and fabrication of a binary array generator of 3 × 3 equal-intensity diffraction orders with 74% efficiency, 95% uniformity and dual color capability. The multicolor properties of this new design are highlighted by two-color MFM imaging. Finally, we discuss the basics of extending this approach to a variety of diffraction pattern designs.

Superresolution light microscopy allows the imaging of labeled supramolecular assemblies at a resolution surpassing the classical diffraction limit. A serious limitation of the superresolution approach is sample heterogeneity and the stochastic character of the labeling procedure. To increase the reproducibility and the resolution of the superresolution results, we apply multivariate statistical analysis methods and 3D reconstruction approaches originally developed for cryogenic electron microscopy of single particles. These methods allow for the reference-free 3D reconstruction of nanomolecular structures from two-dimensional superresolution projection images. Since these 2D projection images all show the structure in high-resolution directions of the optical microscope, the resulting 3D reconstructions have the best possible isotropic resolution in all directions.

Chromosomes of a broad range of species, from bacteria to mammals, are structured by large topological domains whose precise functional roles and regulatory mechanisms remain elusive. Here, we combine super-resolution microscopies and chromosome-capture technologies to unravel the higher-order organization of the Bacillus subtilis chromosome and its dynamic rearrangements during the cell cycle. We decipher the fine 3D architecture of the origin domain, revealing folding motifs regulated by condensin-like complexes. This organization, along with global folding throughout the genome, is present before replication, disrupted by active DNA replication, and re-established thereafter. Single-cell analysis revealed a strict correspondence between sub-cellular localization of origin domains and their condensation state. Our results suggest that the precise 3D folding pattern of the origin domain plays a role in the regulation of replication initiation, chromosome organization, and DNA segregation.

Various rod-shaped bacteria mysteriously glide on surfaces in the absence of appendages such as flagella or pili. In the deltaproteobacterium Myxococcus xanthus, a putative gliding motility machinery (the Agl-Glt complex) localizes to so-called focal adhesion sites (FASs) that form stationary contact points with the underlying surface. Here we show that the Agl-Glt machinery contains an inner-membrane motor complex that moves intracellularly along a right-handed helical path; when the machinery becomes stationary at FASs, the motor complex powers a left-handed rotation of the cell around its long axis. At FASs, force transmission requires cyclic interactions between the molecular motor and the adhesion proteins of the outer membrane via a periplasmic interaction platform, which presumably involves contractile activity of motor components and possible interactions with peptidoglycan. Our results provide a molecular model of bacterial gliding motility.

Accurately detecting subcellular particles in fluorescence microscopy is of primary interest for further quantitative analysis such as counting, tracking, or classification. Our primary goal is to segment vesicles likely to share nearly the same size in fluorescence microscopy images. Our method termed adaptive thresholding of Laplacian of Gaussian (LoG) images with autoselected scale (ATLAS) automatically selects the optimal scale corresponding to the most frequent spot size in the image. Four criteria are proposed and compared to determine the optimal scale in a scale-space framework. Then, the segmentation stage amounts to thresholding the LoG of the intensity image. In contrast to other methods, the threshold is locally adapted given a probability of false alarm (PFA) specified by the user for the whole set of images to be processed. The local threshold is automatically derived from the PFA value and local image statistics estimated in a window whose size is not a critical parameter. We also propose a new data set for benchmarking, consisting of six collections of one hundred images each, which exploits backgrounds extracted from real microscopy images. We have carried out an extensive comparative evaluation on several data sets with ground-truth, which demonstrates that ATLAS outperforms existing methods. ATLAS does not need any fine parameter tuning and requires very low computation time. Convincing results are also reported on real total internal reflection fluorescence microscopy images.