Single-molecule-localization-microscopy (SMLM) and superresolution-optical-fluctuation-imaging (SOFI) enable imaging biological samples well beyond the diffraction-limit of light. SOFI imaging is typically faster, yet has lower resolution than SMLM. Since the same (or similar) data format is acquired for both methods, their algorithms could presumably be combined synergistically for reconstruction and improvement of overall imaging performance. For that, we first defined a measure of the acquired-SNR for each method. This measure was ∼x10 to x100 higher for SOFI as compared to SMLM, indicating faster recognition and acquisition of features by SOFI. This measure also allowed fluorophore-specific optimization of SOFI reconstruction over its time-window and time-lag. We show that SOFI-assisted SMLM imaging can improve image reconstruction by rejecting common sources of background (e.g. out-of-focus emission and auto-fluorescence), especially under low signal-to-noise ratio conditions, by efficient optical sectioning and by shortening image reconstruction time. The performance and utility of our approach was evaluated by realistic simulations and by SOFI-assisted SMLM imaging of the plasma membrane of activated fixed and live T-cells (in isolation or in conjugation to antigen presenting cells). Our approach enhances SMLM performance under demanding imaging conditions and could set an example for synergizing additional imaging techniques.

Cell-cell interfaces convey mechanical and chemical information in multicellular systems. Microscopy has revealed intricate structure of such interfaces, yet typically with limited resolution due to diffraction and unfavourable orthogonal orientation of the interface to the coverslip. We present a simple and robust way to align cell-cell interfaces in parallel to the coverslip by adhering the interacting cells to two opposing coverslips. We demonstrate high-quality diffraction-limited and super-resolution imaging of interfaces (immune-synapses) between fixed and live CD8+ T-cells and either antigen presenting cells or melanoma cells. Imaging methods include bright-field, confocal, STED, dSTORM, SOFI, SRRF and large-scale tiled images. The low background, lack of aberrations and enhanced spatial stability of our method relative to existing cell-trapping techniques allow use of these methods. We expect that the simplicity and wide-compatibility of our approach will allow its wide dissemination for super-resolving the intricate structure and molecular organization in a variety of cell-cell interfaces.

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Single-molecule-localization-microscopy (SMLM) enables superresolution imaging of biological samples down to ~ 10–20 nm and in single molecule detail. However, common SMLM reconstruction largely disregards information embedded in the entire intensity trajectories of individual emitters. Here, we develop and demonstrate an approach, termed time-correlated-SMLM (tcSMLM), that uses such information for enhancing SMLM reconstruction. Specifically, tcSMLM is shown to increase the spatial resolution and fidelity of SMLM reconstruction of both simulated and experimental data; esp. upon acquisition under stringent conditions of low SNR, high acquisition rate and high density of emitters. We further provide detailed guidelines and optimization procedures for effectively applying tcSMLM to data of choice. Importantly, our approach can be readily added in tandem to multiple SMLM and related superresolution reconstruction algorithms. Thus, we expect that our approach will become an effective and readily accessible tool for enhancing SMLM and superresolution imaging.