Single-objective selective-plane illumination microscopy (soSPIM) is achieved with micromirrored cavities combined with a laser beam-steering unit installed on a standard inverted microscope. The illumination and detection are done through the same objective. soSPIM can be used with standard sample preparations and features high background rejection and efficient photon collection, allowing for 3D single-molecule-based super-resolution imaging of whole cells or cell aggregates. Using larger mirrors enabled us to broaden the capabilities of our system to image Drosophila embryos.

Multicolor single-molecule localization microscopy (λSMLM) is a powerful technique to reveal the relative nanoscale organization and potential colocalization between different molecular species. While several standard analysis methods exist for pixel-based images, λSMLM still lacks such a standard. Moreover, existing methods only work on 2D data and are usually sensitive to the relative molecular organization, a very important parameter to consider in quantitative SMLM. Here, we present an efficient, parameter-free colocalization analysis method for 2D and 3D λSMLM using tessellation analysis. We demonstrate that our method allows for the efficient computation of several popular colocalization estimators directly from molecular coordinates and illustrate its capability to analyze multicolor SMLM data in a robust and efficient manner.

SummaryCell shape in vitro can be directed by geometrically defined micropatterned adhesion substrates. However conventional methods are limited by the fixed micropattern design, which cannot recapitulate the dynamic changes of the cell microenvironment. Here, we manipulate the shape of living cells in real time by using a tightly focused pulsed laser to introduce additional geometrically defined adhesion sites. The sub-micrometer resolution of the laser patterning allowed us to identify the critical distances between cell adhesion sites required for cell shape extension and contraction. This easy-to-handle method allows the precise control of specific actin-based structures that regulate cell architecture. Actin filament bundles or branched meshworks were induced, displaced or removed in response to specific dynamic modifications of the cell adhesion pattern. Isotropic branched actin meshworks could be forced to assemble new stress fibers locally and polarised in response to specific geometrical cues.

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.

Mammalian cells developed two main migration modes. The slow mesenchymatous mode, like crawling of fibroblasts, relies on maturation of adhesion complexes and actin fibre traction, while the fast amoeboid mode, observed exclusively for leukocytes and cancer cells, is characterized by weak adhesion, highly dynamic cell shapes, and ubiquitous motility on 2D and in 3D solid matrix. In both cases, interactions with the substrate by adhesion or friction are widely accepted as a prerequisite for mammalian cell motility, which precludes swimming. We show here experimental and computational evidence that leukocytes do swim, and that efficient propulsion is not fuelled by waves of cell deformation but by a rearward and inhomogeneous treadmilling of the cell external membrane. Our model consists of a molecular paddling by transmembrane proteins linked to and advected by the actin cortex, whereas freely diffusing transmembrane proteins hinder swimming. Furthermore, continuous paddling is enabled by a combination of external treadmilling and selective recycling by internal vesicular transport of cortex-bound transmembrane proteins. This mechanism explains observations that swimming is five times slower than the retrograde flow of cortex, and also that lymphocytes are motile in non-adherent confined environments. Resultantly, the ubiquitous ability of mammalian amoeboid cells to migrate in 2D or 3D, and with or without adhesion, can be explained for lymphocytes by a single machinery of heterogeneous membrane treadmilling. SIGNIFICANCE STATEMENT Leukocytes have a ubiquitous capacity to migrate on or in solid matrices, and with or without adhesion, which is instrumental to fight infections. The precise mechanisms sustaining migration remain however arguable. It is for instance widely accepted that leukocytes cannot crawl on 2D substrates without adhesion. In contrast, we showed that human lymphocytes swim on nonadherent 2D substrates and in suspension. Furthermore, our experiments and modelling suggest that propulsion rely hardly on cell body deformations and predominantly on molecular paddling by transmembrane proteins protruding outside the cell. For physics, this study reveals a new type of micro-swimmer, and for biology it suggests that leukocytes ubiquitous crawling may have evolved from an early machinery of swimming shared by various eukaryotic cells.

Current imaging approaches limit the ability to perform multiscale characterization of 3D organotypic cultures (organoids) in large numbers. Here, we present an automated multiscale 3D imaging platform synergizing high-density organoid cultures with 3D live single objective light-sheet imaging. It is composed of disposable microfabricated organoid culture chips embedding optical components and a custom laser beam steering unit coupled to a commercial inverted microscope. It streamlines organoid culture and high content 3D imaging on a single user-friendly instrument with minimal manipulations and unprecedented throughput of 300 organoids per hour in 3D. Collecting large number of 3D stacks allowed training deep learning-based algorithms to quantify the organoids morphogenetic organizations at multi-scales, ranging from the sub-cellular scale to the whole organoid level.We validated the versatility and robustness of our approach on intestine, hepatic, neuroectoderm organoids and oncospheres.

A promising approach to improve the performance of microelectronic devices is to build three-dimensional (3D) chips made of stacked circuits. However, a major hurdle lies in the fabrication of dense arrays of electrical interconnections between these layers, where accessibility is limited. Here we show that the directed growth and self-organization of actin filaments can offer a solution to this problem. We defined the shape and orientation of 3D actin networks through both micropatterning of actin nucleation factors and biochemical control of actin filament polymerization. Networks growing from two opposing layers were able to interpenetrate and form mechanically stable connections, which were then coated with gold using a selective metallization process. The electrical conductivity, robustness and modularity of the metallized self-organized connections make this approach potentially attractive for 3D chip manufacturing.

The three-dimensional (3D) architecture of the cell nucleus plays an important role in protein dynamics and in regulating gene expression. However, protein dynamics within the 3D nucleus are poorly understood. Here, we present, to our knowledge, a novel combination of 1) single-objective based light-sheet microscopy, 2) photoconvertible proteins, and 3) fluorescence correlation microscopy, to quantitatively measure 3D protein dynamics in the nucleus. We are able to acquire >3400 autocorrelation functions at multiple spatial positions within a nucleus, without significant photobleaching, allowing us to make reliable estimates of diffusion dynamics. Using this tool, we demonstrate spatial heterogeneity in Polymerase II dynamics in live U2OS cells. Further, we provide detailed measurements of human-Yes-associated protein diffusion dynamics in a human gastric cancer epithelial cell line.