Three-dimensional Super-resolution Optical Fluctuation Imaging

Super-resolution optical fluctuation imaging (SOFI) achieves three-dimensional super-resolution by computing higher-order spatio-temporal cross-cumulants of stochastically blink-ing fluorophores. In contrast to localization microscopy, SOFI is compatible with weakly emitting fluorophores and a wider range of blinking conditions. The main drawback of SOFI is the nonlinear response to brightness and blinking heterogeneities in the sample, which limits the use of higher cumulant orders. We present a balanced SOFI algorithm for mapping molecular parameters and for linearizing the brightness response and we outline a MATLAB toolbox for two- and three-dimensional SOFI analysis. We show super-resolved three-dimensional cell structures imaged with a multi-plane wide-field microscope. The simultaneous acqui-sition of several focal planes significantly reduces the acquisition time and helps limiting the photo-bleaching of the marker fluorophores

Optical Coherence Correlation Spectroscopy (OCCS)

A classical technique to monitor dynamical processes at the molecular level is fluorescence correlation spectroscopy (FCS). FCS requires fluorescent labels that are typically limited by photobleaching and saturation. We present a new method that uses noble-metal nanoparticles instead of fluorophores: optical coherence correlation spectroscopy (OCCS). OCCS is a correlation spectroscopy technique based on dark-field optical coherence microscopy, a Fourier domain optical coherence tomography technique. In OCCS, several sampling volumes are measured simultaneously with high detection sensitivity. OCCS measures the time correlation function of the light back-scattered by the nanoparticles. Using a mode-locked Ti:Sapphire laser (780nm central wavelength) we performed first experiments with different nanoparticles down to 30nm in diameter. We present experimental results and a preliminary model to fit the correlation curves and extract the particles’ concentrations and diffusion coefficients. The experimental determination of the diffusion times of gold nanoparticles using this model is presented, showing the potential of our method. In the near future, we aim at investigating smaller gold nanoparticles that interfere less with the biological phenomena under study

Optical Coherence Correlation Spectroscopy (OCCS)

A classical technique to monitor dynamical processes at the single-molecule level is fluorescence correlation spectroscopy (FCS). However, FCS requires fluorescent labels that are typically limited by photobleaching and saturation. We present a new method, optical coherence correlation spectroscopy (OCCS), based on noble-metal nanoparticles that overcome those photobleaching and saturation limitations. OCCS is a correlation spectroscopy technique based on dark-field optical coherence microscopy (dfOCM), a Fourier domain optical coherence microscopy technique. OCCS is based on the amplified backscattered light caused by diffusing nanoparticles. Due to the interferometric principle of OCCS, several sampling volumes along the optical axis are measured simultaneously with high detection sensitivity. This adds the possibility to assess axial flow, which is similar to a lateral flow measurement in dual-focus fluorescence correlation. Using a mode-locked Ti:Sapphire laser (780nm central wavelength) we performed experiments with nanoparticles down to 30nm in diameter. We present these first experimental results and an associated theoretical fit model allowing the extraction of the particles’ concentrations and diffusion parameters. The experimental determination of the diffusion time and concentration of gold nanoparticles based on this method is presented as a proof of principle and shows the potential of this technique. In the near future, we aim at investigating smaller gold nanoparticles assessing biological phenomena. As a first application we apply this method to membrane receptor interaction using functionalized nanoparticles

An affordable, quality-assured community-based system for high-resolution entomological surveillance of vector mosquitoes that reflects human malaria infection risk patterns.

ABSTRACT: BACKGROUND: More sensitive and scalable entomological surveillance tools are required to monitor low levels of transmission that are increasingly common across the tropics, particularly where vector control has been successful. A large-scale larviciding programme in urban Dar es Salaam, Tanzania is supported by a community-based (CB) system for trapping adult mosquito densities to monitor programme performance. Methodology An intensive and extensive CB system for routine, longitudinal, programmatic surveillance of malaria vectors and other mosquitoes using the Ifakara Tent Trap (ITT-C) was developed in Urban Dar es Salaam, Tanzania, and validated by comparison with quality assurance (QA) surveys using either ITT-C or human landing catches (HLC), as well as a cross-sectional survey of malaria parasite prevalence in the same housing compounds. RESULTS: Community-based ITT-C had much lower sensitivity per person-night of sampling than HLC (Relative Rate (RR) [95% Confidence Interval (CI)] = 0.079 [0.051, 0.121], P < 0.001 for Anopheles gambiae s.l. and 0.153 [0.137, 0.171], P < 0.001 for Culicines) but only moderately differed from QA surveys with the same trap (0.536 [0.406,0.617], P = 0.001 and 0.747 [0.677,0.824], P < 0.001, for An. gambiae or Culex respectively). Despite the poor sensitivity of the ITT per night of sampling, when CB-ITT was compared with QA-HLC, it proved at least comparably sensitive in absolute terms (171 versus 169 primary vectors caught) and cost-effective (153US$versus 187US$ per An. gambiae caught) because it allowed more spatially extensive and temporally intensive sampling (4284 versus 335 trap nights distributed over 615 versus 240 locations with a mean number of samples per year of 143 versus 141). Despite the very low vectors densities (Annual estimate of about 170 An gambiae s.l bites per person per year), CB-ITT was the only entomological predictor of parasite infection risk (Odds Ratio [95% CI] = 4.43[3.027,7. 454] per An. gambiae or Anopheles funestus caught per night, P =0.0373). Discussion and conclusion CB trapping approaches could be improved with more sensitive traps, but already offer a practical, safe and affordable system for routine programmatic mosquito surveillance and clusters could be distributed across entire countries by adapting the sample submission and quality assurance procedures accordingly

Structural and Functional Stochastic Super-Resolution Microscopy

Super-resolution fluorescence microscopy is a promising tool with the potential to strengthen our understanding of living processes. Based on the ability to switch fluorophores on and off in an either deterministic or stochastic manner, the fundamental limit of diffraction can be overcome. The first concepts have been invented 20 years ago, but first discoveries in biology have been reported only recently. As with every new technology, its successful application is challenging. In particular, super-resolution microscopy sets much higher demands on the sample preparation and labeling quality than researchers are used to. In addition, the super-resolution microscopes often require tedious alignment procedures and/or rely on complicated data analysis software. Not surprisingly, commercially available systems are rather expensive and not yet widely spread. This thesis focused on the development and characterization of novel concepts for super-resolution microscopy based on stochastic fluorescence fluctuations in order to extend and/or simplify existing techniques. In particular, we developed a framework for the image-based simultaneous estimation of three-dimensional position and orientation of fluorescent emitters. Unlike many localization-based super-resolution techniques, our approach accounts for the dipole characteristics of the fluorescence emission whilst staying compatible with standard widefield fluorescence microscopes. In a comparative study of two well-established techniques for super-resolution microscopy, namely super-resolution optical fluctuation imaging (SOFI) and stochastic optical reconstruction microscopy (STORM), we determined their characteristics and demonstrated a complementary performance, which suggested a beneficial impact upon combination of both techniques. This has led to a further development of the original SOFI analysis. The resulting balanced SOFI analyzes molecular statistics and linearizes the response with respect to brightness and blinking heterogeneities in the sample, which significantly improves the image contrast and thereby facilitates the access to higher resolutions. We experimentally demonstrated nearly five-fold resolution improvements as compared to diffraction-limited images of fluorescently labeled cells. The super-resolved molecular parameter maps obtained with balanced SOFI, such as the blinking lifetimes, fluctuation amplitudes and label densities, are sensitive to static differences and/or dynamic changes in the chemical microenvironment of the fluorophores and can thus report functional information that has not been exploited before, for instance, the local pH or the concentration of reducing and oxidizing agents. Finally, by using cross-cumulation between multiple depth and/or color channels, we demonstrated whole-cell three-dimensional super-resolution microscopy with a normal widefield illumination and without mechanical scanning as well as spectral unmixing of multiple fluorophores with overlapping emission spectra

Balanced Super-resolution Optical Fluctuation Imaging (bSOFI)

Super-resolution optical fluctuation imaging (SOFI) achieves 3D super-resolution by computing higher-order cumulants of stochastically blinking fluorophores. In contrast to localization microscopy, SOFI is compatible with weakly emitting fluorophores and a wide range of blinking conditions. The main drawback of SOFI is the nonlinear response to brightness and blinking heterogeneities in the sample, which limits the use of higher cumulant orders. Balanced super-resolution optical fluctuation imaging (bSOFI), extends SOFI by the combination of several cumulant orders to map fluorescence-related molecular statistics, such as molecular state lifetimes, concentrations and brightness distributions with super-resolution. Since these parameters are often linked to the chemical microenvironment of the fluorophores, they report on static differences and/or dynamic changes within cells and thus add a “functional” dimension to super-resolution microscopy based on stochastic switching. Furthermore, the information obtained can be used to correct for the nonlinear brightness and blinking response of cumulants. We show experimental results of Alexa647-labeled microtubules in fixed HeLa cells with an up to five-fold resolution improvement compared to diffraction-limited widefield microscopy. Using a total-internal-reflection illumination scheme, we obtain depth information through the estimation of the spatial distributions of the molecular brightness as well as the blinking on-ratio

Super-resolved position and orientation estimation of fluorescent dipoles using 3D steerable filters

Fluorescence localization microscopy techniques such as PALM and STORM achieve super-resolution by sequentially imaging sparse subsets of fluorophores, which are localized by means of Gaussian-based localization. Applied to fixed fluorophores, with dipole radiation characteristics, this can lead to an estimation bias in the range of 5-20nm. We introduce a method for the joint estimation of position and orientation of single fluorophores, based on an accurate image formation model expressed as a 3-D steerable filter. In addition to avoiding bias in PALM/STORM, it can remove the ambiguity of the orientation factor for studying dipole-dipole interactions at the single-molecule level

Three-Dimensional Localization of Nano-Emitters with Nanometer-Level Precision

We show nanometer-level localization accuracy of a single quantum-dot in three dimensions by self-interference and diffraction-pattern analysis. We believe that this approach has the capacity to push optical microscopy to the molecular level

Super-resolved position and orientation from defocused images of fluorescent dipoles

Fluorophores that are fixed during image acquisition produce a diffraction pattern that is characteristic of the orientation of the fluorophore’s underlying dipole. Fluorescence localization microscopy techniques such as PALM and STORM achieve super-resolution by applying Gaussian-based fitting algorithms to in-focus images of individual fluorophores; when applied to fixed dipoles, this can lead to a bias in the range of 5-20 nm.We introduce a method for the joint estimation of position and orientation of dipoles, based on the representation of a physically realistic image formation model as a 3-D steerable filter. Our approach relies on a single, defocused acquisition. We establish theoretical, localization-based resolution limits on estimation accuracy using Cram´er-Rao bounds, and experimentally show that estimation accuracies of at least 5 nm for position and of at least 2 degrees for orientation can be achieved. Patterns generated by applying the image formation model to estimated position/orientation pairs closely match experimental observations