Fluorescence lifetime measurements using photon pair correlations generated via spontaneous parametric down conversion (SPDC).

We have used photon pair correlations generated via spontaneous parametric downconversion (SPDC) to measure the fluorescence lifetime of the organic dye rhodamine 6 G, demonstrating that fluorescence lifetime measurements can be achieved using a continuous wave (CW) laser, without pulsed or modulated lasers. Our entangled photon method, quantum fluorescence lifetime (Q-FL) measurements, uses one photon to excite fluorescence and the resulting fluorescence photon is timed and referenced to the arrival time of the other entangled photon. Thus, we can exploit the short timescale of photon pair correlations to conduct experiments that are typically carried out with pulsed lasers and we show that the inherent timing of the photons is fast enough to resolve the nanosecond scale fluorescence lifetime of the sample. This measurement paves the way towards using the time correlations of entangled photons for fluorescence imaging; capitalizing on the presence of fast, sub-100 ps correlations that have not been demonstrated classically.

PySOFI: an open source Python package for SOFI.

Super-resolution optical fluctuation imaging (SOFI) is a highly democratizable technique that provides optical super-resolution without requirement of sophisticated imaging instruments. Easy-to-use open-source packages for SOFI are important to support the utilization and community adoption of the SOFI method, they also encourage the participation and further development of SOFI by new investigators. In this work, we developed PySOFI, an open-source Python package for SOFI analysis that offers the flexibility to inspect, test, modify, improve, and extend the algorithm. We provide complete documentation for the package and a collection of Jupyter Notebooks to demonstrate the usage of the package. We discuss the architecture of PySOFI and illustrate how to use each functional module. A demonstration on how to extend the PySOFI package with additional modules is also included in the PySOFI package. We expect PySOFI to facilitate efficient adoption, testing, modification, dissemination, and prototyping of new SOFI-relevant algorithms.

Tailored approach to study Legionella infection using a lattice light sheet microscope (LLSM).

Legionella is a genus of ubiquitous environmental pathogens found in freshwater systems, moist soil, and composted materials. More than four decades of Legionella research has provided important insights into Legionella pathogenesis. Although standard commercial microscopes have led to significant advances in understanding Legionella pathogenesis, great potential exists in the deployment of more advanced imaging techniques to provide additional insights. The lattice light sheet microscope (LLSM) is a recently developed microscope for 4D live cell imaging with high resolution and minimum photo-damage. We built a LLSM with an improved version for the optical layout with two path-stretching mirror sets and a novel reconfigurable galvanometer scanner (RGS) module to improve the reproducibility and reliability of the alignment and maintenance of the LLSM. We commissioned this LLSM to study Legionella pneumophila infection with a tailored workflow designed over instrumentation, experiments, and data processing methods. Our results indicate that Legionella pneumophila infection is correlated with a series of morphological signatures such as smoothness, migration pattern and polarity both statistically and dynamically. Our work demonstrates the benefits of using LLSM for studying long-term questions in bacterial infection. Our free-for-use modifications and workflow designs on the use of LLSM system contributes to the adoption and promotion of the state-of-the-art LLSM technology for both academic and commercial applications.

Rapid ensemble measurement of protein diffusion and probe blinking dynamics in cells.

We present a fluorescence fluctuation image correlation analysis method that can rapidly and simultaneously measure the diffusion coefficient, photoblinking rates, and fraction of diffusing particles of fluorescent molecules in cells. Unlike other image correlation techniques, we demonstrated that our method could be applied irrespective of a nonuniformly distributed, immobile blinking fluorophore population. This allows us to measure blinking and transport dynamics in complex cell morphologies, a benefit for a range of super-resolution fluorescence imaging approaches that rely on probe emission blinking. Furthermore, we showed that our technique could be applied without directly accounting for photobleaching. We successfully employed our technique on several simulations with realistic EMCCD noise and photobleaching models, as well as on Dronpa-C12-labeled ß-actin in living NIH/3T3 and HeLa cells. We found that the diffusion coefficients measured using our method were consistent with previous literature values. We further found that photoblinking rates measured in the live HeLa cells varied as expected with changing excitation power.

Cusp-artifacts in high order superresolution optical fluctuation imaging.

Superresolution optical fluctuation imaging (SOFI) is a simple and affordable super-resolution imaging technique, and attracted a growing community over the past decade. However, the theoretical resolution enhancement of high order SOFI is still not fulfilled. In this study, we identify "cusp artifacts" in high order SOFI images, and show that the high-order cumulants, odd-order moments and balanced-cumulants (bSOFI) are highly vulnerable to cusp artifacts. Our study provides guidelines for developing and screening for fluorescence probes, and improving data acquisition for SOFI. The new insight is important to inspire positive utilization of the cusp artifacts.

Moments reconstruction and local dynamic range compression of high order superresolution optical fluctuation imaging.

Super-resolution optical fluctuation imaging (SOFI) offers a simple and affordable alternative to other super-resolution (SR) imaging techniques. The theoretical resolution enhancement of SOFI scales linearly with the order of cumulants, while the imaging conditions exhibit less photo-toxicity to the living samples as compared to other SR methods. High order SOFI could, therefore, be a method of choice for dynamic live cell imaging. However, due to the cusp-artifacts and dynamic range expansion of pixel intensities, this promise has not been materialized as of yet. Here we investigated and compared high order moments vs. high order cumulant SOFI reconstructions. We demonstrate that even-order moments reconstructions are intrinsically free of cusp artifacts, allowing for a subsequent deconvolution operation to be performed, hence enhancing the resolution even further. High order moments reconstruction performance was examined for various (simulated) conditions and applied to (experimental) imaging of QD labeled microtubules in fixed cells, and actin stress fiber dynamics in live cells.

Synergizing superresolution optical fluctuation imaging with single molecule localization microscopy.

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.

Characterization of Porous Materials by Fluorescence Correlation Spectroscopy Super-resolution Optical Fluctuation Imaging.

Porous materials such as cellular cytosol, hydrogels, and block copolymers have nanoscale features that determine macroscale properties. Characterizing the structure of nanopores is difficult with current techniques due to imaging, sample preparation, and computational challenges. We produce a super-resolution optical image that simultaneously characterizes the nanometer dimensions of and diffusion dynamics within porous structures by correlating stochastic fluctuations from diffusing fluorescent probes in the pores of the sample, dubbed here as "fluorescence correlation spectroscopy super-resolution optical fluctuation imaging" or "fcsSOFI". Simulations demonstrate that structural features and diffusion properties can be accurately obtained at sub-diffraction-limited resolution. We apply our technique to image agarose hydrogels and aqueous lyotropic liquid crystal gels. The heterogeneous pore resolution is improved by up to a factor of 2, and diffusion coefficients are accurately obtained through our method compared to diffraction-limited fluorescence imaging and single-particle tracking. Moreover, fcsSOFI allows for rapid and high-throughput characterization of porous materials. fcsSOFI could be applied to soft porous environments such hydrogels, polymers, and membranes in addition to hard materials such as zeolites and mesoporous silica.