No Arabic abstract
Single molecule localization microscopy (SMLM) techniques enable imaging biological samples well beyond the diffraction limit of light, but they vary significantly in their spatial and temporal resolutions. High-order statistical analysis of temporal fluctuations as in superresolution optical fluctuation imaging (SOFI) also enable imaging beyond diffraction limit, but usually at a lower resolution as compared to SMLM. Since the same data format is acquired for both methods, their algorithms can be applied to the same data set, and thus may be combined synergistically to improve overall imaging performance. Here, we find that SOFI converges much faster than SMLM, provides additive information to SMLM, and can efficiently reject background. We then show how SOFI-assisted SMLM imaging can improve SMLM image reconstruction by rejecting common sources of background, especially under low signal-to-background conditions. The performance of our approach was evaluated using a realistic simulation of fluorescence imaging we developed and further demonstrated on experimental SMLM images of the plasma membrane of activated fixed and live T cells. Our approach significantly enhances SMLM performance under demanding imaging conditions and could set an example for synergizing additional imaging techniques.
Super-resolution microscopy has catalyzed valuable insights into the sub-cellular, mechanistic details of many different biological processes across a wide range of cell types. Fluorescence polarization spectroscopy tools have also enabled important insights into cellular processes through identifying orientational changes of biological molecules typically at an ensemble level. Here, we combine these two biophysical methodologies in a single home-made instrument to enable the simultaneous detection of orthogonal fluorescence polarization signals from single fluorescent protein molecules used as common reporters on the localization of proteins in cellular processes. These enable measurement of spatial location to a super-resolved precision better than the diffraction-limited optical resolution, as well as estimation of molecular stoichiometry based on the brightness of individual fluorophores. In this innovation we have adapted a millisecond timescale microscope used for single-molecule detection to enable splitting of fluorescence polarization emissions into two separate imaging channels for s- and p- polarization signals, which are imaged onto separate halves of the same high sensitivity back-illuminated CMOS camera detector. We applied this fluorescence polarization super-resolved imaging modality to a range of test fluorescent samples relevant to the study of biological processes, including purified monomeric green fluorescent protein, single combed DNA molecules, and protein assemblies and complexes from live Escherichia coli and Saccharomyces cerevisiae cells. Our findings are qualitative but demonstrate promise in showing how fluorescence polarization and super-resolved localization microscopy can be combined on the same sample to enable simultaneous measurements of polarization and stoichiometry of tracked molecular complexes, as well as the translational diffusion coefficient.
Cells rely on focal adhesions (FAs) to carry out a variety of important tasks, including motion, environmental sensing, and adhesion to the extracellular matrix. Although attaining a fundamental characterization of FAs is a compelling goal, their extensive complexity and small size, which can be below the diffraction limit, have hindered a full understanding. In this study we have used single-molecule localization microscopy (SMLM) to investigate integrin $beta$3 and paxillin in rat embryonic fibroblasts growing on two different extracellular matrix-representing substrates (i.e. fibronectin-coated substrates and specifically bio-functionalized nano-patterned substrates). To quantify the substructure of FAs, we developed a method based on expectation maximization of a Gaussian mixture that accounts for localization uncertainty and background. Analysis of our SMLM data indicates that the structures within FAs, characterized as a Gaussian mixture, typically have areas between 0.01 and 1 $mu$m$^2$, contain 10 to 100 localizations, and can exhibit substantial eccentricity. Our approach based on SMLM opens new avenues for studying structural and functional biology of molecular assemblies that display substantial varieties in size, shape, and density.
Single molecule tracking in live cells is the ultimate tool to study subcellular protein dynamics, but it is often limited by the probe size and photostability. Due to these issues, long-term tracking of proteins in confined and crowded environments, such as intracellular spaces, remains challenging. We have developed a novel optical probe consisting of 5-nm gold nanoparticles functionalized with a small fragment of camelid antibodies that recognize widely used GFPs with a very high affinity, which we call GFP-nanobodies. These small gold nanoparticles can be detected and tracked using photothermal imaging for arbitrarily long periods of time. Surface and intracellular GFP-proteins were effectively labeled even in very crowded environments such as adhesion sites and cytoskeletal structures both in vitro and in live cell cultures. These nanobody-coated gold nanoparticles are probes with unparalleled capabilities; small size, perfect photostability, high specificity, and versatility afforded by combination with the vast existing library of GFP-tagged proteins.
Single molecule localization microscopy is widely used in biological research for measuring the nanostructures of samples smaller than the diffraction limit. This study uses multifocal plane microscopy and addresses the 3D single molecule localization problem, where lateral and axial locations of molecules are estimated. However, when we multifocal plane microscopy is used, the estimation accuracy of 3D localization is easily deteriorated by the small lateral drifts of camera positions. We formulate a 3D molecule localization problem along with the estimation of the lateral drifts as a compressed sensing problem, A deep neural network was applied to accurately and efficiently solve this problem. The proposed method is robust to the lateral drifts and achieves an accuracy of 20 nm laterally and 50 nm axially without an explicit drift correction.
Voltage-gated sodium (Na$_mathrm{v}$) channels are responsible for the depolarizing phase of the action potential in most nerve cells, and Na$_mathrm{v}$ channel localization to the axon initial segment is vital to action potential initiation. Na$_mathrm{v}$ channels in the soma play a role in the transfer of axonal output information to the rest of the neuron and in synaptic plasticity, although little is known about Na$_mathrm{v}$ channel localization and dynamics within this neuronal compartment. This study uses single-particle tracking and photoactivation localization microscopy to analyze cell-surface Na$_mathrm{v}$1.6 within the soma of cultured hippocampal neurons. Mean-square displacement analysis of individual trajectories indicated that half of the somatic Na$_mathrm{v}$1.6 channels localized to stable nanoclusters $sim$230 nm in diameter. Strikingly, these domains were stabilized at specific sites on the cell membrane for >30 min, notably via an ankyrin-independent mechanism, indicating that the means by which Na$_mathrm{v}$1.6 nanoclusters are maintained in the soma is biologically different from axonal localization. Nonclustered Na$_mathrm{v}$1.6 channels showed anomalous diffusion, as determined by mean-square-displacement analysis. High-density single-particle tracking of Na$_mathrm{v}$ channels labeled with photoactivatable fluorophores in combination with Bayesian inference analysis was employed to characterize the surface nanoclusters. A subpopulation of mobile Na$_mathrm{v}$1.6 was observed to be transiently trapped in the nanoclusters. Somatic Na$_mathrm{v}$1.6 nanoclusters represent a new, to our knowledge, type of Na$_mathrm{v}$ channel localization, and are hypothesized to be sites of localized channel regulation.