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The interaction of synaptic proteins orchestrate the function of one of the most complex organs, the brain. The multitude of molecular elements influencing neurological correlations makes imaging processes complicated since conventional fluorescence microscopy methods are unable to resolve structures beyond the diffraction-limit.
The implementation of super-resolution fluorescence microscopy into the field of neuroscience allows the visualisation of the fine details of neural connectivity. The key element of my thesis is the super-resolution technique dSTORM (direct Stochastic Optical Reconstruction Microscopy) and its optimisation as a multi-colour approach. Capturing more than one target, I aim to unravel the distribution of synaptic proteins with nanometer precision and set them into a structural and quantitative context with one another. Therefore dSTORM specific protocols are optimized to serve the peculiarities of particular neural samples.
In one project the brain derived neurotrophic factor (BDNF) is investigated in primary, hippocampal neurons. With a precision beyond 15 nm, preand post-synaptic sites can be identified by staining the active zone proteins bassoon and homer. As a result, hallmarks of mature synapses can be exhibited. The single molecule sensitivity of dSTORM enables the measurement of endogenous BDNF and locates BDNF granules aligned with glutamatergic pre-synapses. This data proofs that hippocampal neurons are capable of enriching BDNF within the mature glutamatergic pre-synapse, possibly influencing synaptic plasticity.
The distribution of the metabotropic glutamate receptor mGlu4 is investigated in physiological brain slices enabling the analysis of the receptor in its natural environment. With dual-colour dSTORM, the spatial arrangement of the mGlu4 receptor in the pre-synaptic sites of parallel fibres in the molecular layer of the mouse cerebellum is visualized, as well as a four to six-fold increase in the density of the receptor in the active zone compared to the nearby environment. Prior functional measurements show that metabotropic glutamate receptors influence voltage-gated calcium channels and proteins that are involved in synaptic vesicle priming. Corresponding dSTORM data indeed suggests that a subset of the mGlu4 receptor is correlated with the voltage-gated calcium channel Cav2.1 on distances around 60 nm.
These results are based on the improvement of the direct analysis of localisation data. Tools like coordinated based correlation analysis and nearest neighbour analysis of clusters centroids are used complementary to map protein connections of the synapse. Limits and possible improvements of these tools are discussed to foster the quantitative analysis of single molecule localisation microscopy data.
Performing super-resolution microscopy on complex samples like brain slices benefits from a maximised field of view in combination with the visualisation of more than two targets to set the protein of interest in a cellular context. This challenge served as a motivation to establish a workflow for correlated structured illumination microscopy (SIM) and dSTORM. The development of the visualisation software coSIdSTORM promotes the combination of these powerful super-resolution techniques even on separated setups. As an example, synapses in the cerebellum that are affiliated to the parallel fibres and the dendrites of the Purkinje cells are identified by SIM and the protein bassoon of those pre-synapses is visualised threedimensionally with nanoscopic precision by dSTORM.
In this work I placed emphasis on the improvement of multi-colour super-resolution imaging and its analysing tools to enable the investigation of synaptic proteins. The unravelling of the structural arrangement of investigated proteins supports the building of a synapse model and therefore helps to understand the relation between structure and function in neural transmission processes.
Single-molecule super-resolution microscopy (SMLM) techniques like dSTORM can reveal biological structures down to the nanometer scale. The achievable resolution is not only defined by the localization precision of individual fluorescent molecules, but also by their density, which becomes a limiting factor e.g., in expansion microscopy. Artificial deep neural networks can learn to reconstruct dense super-resolved structures such as microtubules from a sparse, noisy set of data points. This approach requires a robust method to assess the quality of a predicted density image and to quantitatively compare it to a ground truth image. Such a quality measure needs to be differentiable to be applied as loss function in deep learning. We developed a new trainable quality measure based on Fourier Ring Correlation (FRC) and used it to train deep neural networks to map a small number of sampling points to an underlying density. Smooth ground truth images of microtubules were generated from localization coordinates using an anisotropic Gaussian kernel density estimator. We show that the FRC criterion ideally complements the existing state-of-the-art multiscale structural similarity index, since both are interpretable and there is no trade-off between them during optimization. The TensorFlow implementation of our FRC metric can easily be integrated into existing deep learning workflows.
We review fluorescent probes that can be photoswitched or photoactivated and are suited for single-molecule localization based super-resolution microscopy. We exploit the underlying photochemical mechanisms that allow photoswitching of many synthetic organic fluorophores in the presence of reducing agents, and study the impact of these on the photoswitching properties of various photoactivatable or photoconvertible fluorescent proteins. We have identified mEos2 as a fluorescent protein that exhibits reversible photoswitching under various imaging buffer conditions and present strategies to characterize reversible photoswitching. Finally, we discuss opportunities to combine fluorescent proteins with organic fluorophores for dual-color photoswitching microscopy.
We review fluorescent probes that can be photoswitched or photoactivated and are suited for single-molecule localization based super-resolution microscopy. We exploit the underlying photochemical mechanisms that allow photoswitching of many synthetic organic fluorophores in the presence of reducing agents, and study the impact of these on the photoswitching properties of various photoactivatable or photoconvertible fluorescent proteins. We have identified mEos2 as a fluorescent protein that exhibits reversible photoswitching under various imaging buffer conditions and present strategies to characterize reversible photoswitching. Finally, we discuss opportunities to combine fluorescent proteins with organic fluorophores for dual-color photoswitching microscopy.
Since its first experimental implementation in 2005, single-molecule localization microscopy (SMLM) emerged as a versatile and powerful imaging tool for biological structures with nanometer resolution. By now, SMLM has compiled an extensive track-record of novel insights in sub- and inter- cellular organization.\\
Moreover, since all SMLM techniques rely on the analysis of emission patterns from isolated fluorophores, they inherently allocate molecular information $per$ $definitionem$.\\
Consequently, SMLM transitioned from its origin as pure high-resolution imaging instrument towards quantitative microscopy, where the key information medium is no longer the highly resolved image itself, but the raw localization data set.\\
The work presented in this thesis is part of the ongoing effort to translate those $per$ $se$ molecular information gained by SMLM imaging to insights into the structural organization of the targeted protein or even beyond. Although largely consistent in their objectives, the general distinction between global or segmentation clustering approaches on one side and particle averaging or meta-analyses techniques on the other is usually made.\\
During the course of my thesis, I designed, implemented and employed numerous quantitative approaches with varying degrees of complexity and fields of application.\\ \\
In my first major project, I analyzed the localization distribution of the integral protein gp210 of the nuclear pore complex (NPC) with an iterative \textit{k}-means algorithm. Relating the distinct localization statistics of separated gp210 domains to isolated fluorescent signals led, among others, to the conclusion that the anchoring ring of the NPC consists of 8 homo-dimers of gp210.\\
This is of particular significance, both because it answered a decades long standing question about the nature of the gp210 ring and it showcased the possibility to gain structural information well beyond the resolution capabilities of SMLM by crafty quantification approaches.\\ \\
The second major project reported comprises an extensive study of the synaptonemal complex (SNC) and linked cohesin complexes. Here, I employed a multi-level meta-analysis of the localization sets of various SNC proteins to facilitate the compilation of a novel model of the molecular organization of the major SNC components with so far unmatched extend and detail with isotropic three-dimensional resolution.\\
In a second venture, the two murine cohesin components SMC3 and STAG3 connected to the SNC were analyzed. Applying an adapted algorithm, considering the disperse nature of cohesins, led to the realization that there is an apparent polarization of those cohesin complexes in the SNC, as well as a possible sub-structure of STAG3 beyond the resolution capabilities of SMLM.\\ \\
Other minor projects connected to localization quantification included the study of plasma membrane glycans regarding their overall localization distribution and particular homogeneity as well as the investigation of two flotillin proteins in the membrane of bacteria, forming clusters of distinct shapes and sizes.\\ \\
Finally, a novel approach to three-dimensional SMLM is presented, employing the precise quantification of single molecule emitter intensities. This method, named TRABI, relies on the principles of aperture photometry which were improved for SMLM.\\
With TRABI it was shown, that widely used Gaussian fitting based localization software underestimates photon counts significantly. This mismatch was utilized as a $z$-dependent parameter, enabling the conversion of 2D SMLM data to a virtual 3D space. Furthermore it was demonstrated, that TRABI can be combined beneficially with a multi-plane detection scheme, resulting in superior performance regarding axial localization precision and resolution.\\
Additionally, TRABI has been subsequently employed to photometrically characterize a novel dye for SMLM, revealing superior photo-physical properties at the single-molecule level.\\
Following the conclusion of this thesis, the TRABI method and its applications remains subject of diverse ongoing research.
One rarely finds practical guidelines for the implementation of complex optical setups. Here, we aim to provide technical details on the decision making of building and revising a custom sensor-based adaptive optics (AO) direct stochastic optical reconstruction microscope (dSTORM) to provide practical assistance in setting up or troubleshooting similar devices.
The foundation of this report is an instrument constructed as part of a master's thesis in 2021, which was built for deep tissue imaging. The setup is presented in the following way: (1) An optical and mechanical overview of the system at the beginning of this internship is given. (2) The optical components are described in detail in the order at which the light passes through, highlighting their working principle and implementation in the system. The optical component include (2A) a focus on even sample illumination, (2B) restoring telecentricity when working with commercial microscope bodies, (2C) the AO elements, namely the deformable mirror (DM) and the wavefront sensor, and their integration, and (2D) the separation of wavefront and image capture using fluorescent beads and a dichroic mirror. After addressing the limitations of the existing setup, modification options are derived. The modifications include the implementation of adjustment only light paths to improve system stability and revise the degrees of freedom of the components and changes in lens choices to meet the specifications of the AO components. Last, the capabilities of the modified setup are presented and discussed: (1) First, we enable epifluorescence imaging of bead samples through 180 µm unstained murine hippocampal tissue with wavefront error correction of ~ 90 %. Point spread function, wavefront shape and Zernike decomposition of bead samples are presented. (2) Second, we move from epifluorescent to dSTORM imaging of tubulin stained primary mouse hippocampal cells, which are imaged through up to 180 µm of unstained murine hippocampal tissue. We show that full width at half maximum (FWHM) of prominent features can be reduced in size by nearly a magnitude from uncorrected epiflourescence images to dSTORM images corrected by the adaptive optics. We present dSTORM localization count and FWHM of prominent features as as a function of imaging depth.
Point-spread function engineering for single-molecule localization microscopy in brain slices
(2022)
Single-molecule localization microscopy (SMLM) is the method of choice to study biological specimens on a nanoscale level. Advantages of SMLM imply its superior specificity due to targeted molecular fluorescence labeling and its enhanced tissue preservation compared to electron microscopy, while reaching similar resolution. To reveal the molecular organization of protein structures in brain tissue, SMLM moves to the forefront: Instead of investigating brain slices with a thickness of a few µm, measurements of intact neuronal assemblies (up to 100 µm in each dimension) are required. As proteins are distributed in the whole brain volume and can move along synapses in all directions, this method is promising in revealing arrangements of neuronal protein markers. However, diffraction-limited imaging still required for the localization of the fluorophores is prevented by sample-induced distortion of emission pattern due to optical aberrations in tissue slices from non-superficial planes. In particular, the sample causes wavefront dephasing, which can be described as a summation of Zernike polynomials. To recover an optimal point spread function (PSF), active shaping can be performed by the use of adaptive optics. The aim of this thesis is to establish a setup using a deformable mirror and a wavefront sensor to actively shape the PSF to correct the wavefront phases in a super-resolution microscope setup. Therefore, fluorescence-labeled proteins expressed in different anatomical regions in brain tissue will be used as experiment specimen. Resolution independent imaging depth in slices reaching tens of micrometers is aimed.
Cellular responses to outer stimuli are the basis for all biological processes. Signal integration is achieved by protein cascades, recognizing and processing molecules from the environment. Factors released by pathogens or inflammation usually induce an inflammatory response, a signal often transduced by Tumour Necrosis Factor alpha (TNF). TNFα receptors TNF-R1 and TNF-R2 can in turn lead to apoptosis or proliferation via NF-B. These processes are closely regulated by membrane compartimentalization, protein interactions and trafficking. Fluorescence microscopy offers a reliable and non-invasive method to probe these cellular events. However, some processes on a native membrane are not resolvable, as they are well below the diffraction limit of microscopy. The recent development of super-resolution fluorescence microscopy methods enables the observation of these cellular players well below this limit: by localizing, tracking and counting molecules with high spatial and temporal resolution, these new fluorescence microscopy methods offer a previously unknown insight into protein interactions at the near-molecular level. Direct stochastic optical reconstruction microscopy (dSTORM) utilizes the reversible, stochastic blinking events of small commercially available fluorescent dyes, while photoactivated localization microscopy (PALM) utilizes phototransformation of genetically encoded fluorescent proteins. By photoactivating only a small fraction of the present fluorophores in each observation interval, single emitters can be localized with high precision and a super-resolved image can be reconstructed. Quantum Dot Triexciton imaging (QDTI) utilizes the three-photon absorption (triexcitonic) properties of quantum dots (QD) and to achieve a twofold resolution increase using conventional confocal microscopes. In this thesis, experimental approaches were implemented to achieve super-resolution microscopy in fixed and live-cells to study the spatial and temporal dynamics of TNF and other cellular signaling events. We introduce QDTI to study the three-dimensional cellular distribution of biological targets, offering an easy method to achieve resolution enhancement in combination with optical sectioning, allowing the preliminary quantification of labeled proteins. As QDs are electron dense, QDTI can be used for correlative fluorescence and transmission electron microscopy, proving the versatility of QD probes. Utilizing the phototransformation properties of fluorescent proteins, single-receptor tracking on live cells was achieved, applying the concept of single particle tracking PALM (sptPALM) to track the dynamics of a TNF-R1-tdEos chimera on the membrane. Lateral receptor dynamics can be tracked with high precision and the influences of ligand addition or lipid disruption on TNF-R1 mobility was observed. The results reveal complex receptor dynamics, implying internalization processes in response to TNFα stimulation and a role for membrane domains with reduced fluidity, so-called lipid raft domains, in TNF-R1 compartimentalization prior or post ligand induction. Comparisons with previously published FCS data show a good accordance, but stressing the increased data depth available in sptPALM experiments. Additionally, the active transport of NF-κB-tdEos fusions was observed in live neurons under chemical stimulation and/or inhibition. Contrary to phototransformable proteins that need no special buffers to exhibit photoconversion or photoactivation, dSTORM has previously been unsuitable for in vivo applications, as organic dyes relied on introducing the probes via immunostaining in concert with a reductive, oxygen-free medium for proper photoswitching behaviour. ATTO655 had been previously shown to be suitable for live-cell applications, as its switching behavior can be catalyzed by the reductive environment of the cytoplasm. By introducing the cell-permeant organic dye via a chemical tag system, a high specificity and low background was achieved. Here, the labeled histone H2B complex and thus single nucleosome movements in a live cell can be observed over long time periods and with ~20 nm resolution. Implementing these new approaches for imaging biological processes with high temporal and spatial resolution provides new insights into the dynamics and spatial heterogeneities of proteins, further elucidating their function in the organism and revealing properties that are usually only detectable in vitro.
Fluorescence labeling of difficult to access protein sites, e.g., in confined compartments, requires small fluorescent labels that can be covalently tethered at well-defined positions with high efficiency. Here, we report site-specific labeling of the extracellular domain of γ-aminobutyric acid type A (GABA-A) receptor subunits by genetic code expansion (GCE) with unnatural amino acids (ncAA) combined with bioorthogonal click-chemistry labeling with tetrazine dyes in HEK-293-T cells and primary cultured neurons. After optimization of GABA-A receptor expression and labeling efficiency, most effective variants were selected for super-resolution microscopy and functionality testing by whole-cell patch clamp. Our results show that GCE with ncAA and bioorthogonal click labeling with small tetrazine dyes represents a versatile method for highly efficient site-specific fluorescence labeling of proteins in a crowded environment, e.g., extracellular protein domains in confined compartments such as the synaptic cleft.
The plasma membrane is one of the most thoroughly studied and at the same time most complex, diverse, and least understood cellular structures. Its function is determined by the molecular composition as well as the spatial arrangement of its components. Even after decades of extensive membrane research and the proposal of dozens of models and theories, the structural organization of plasma membranes remains largely unknown. Modern imaging tools such as super-resolution fluorescence microscopy are one of the most efficient techniques in life sciences and are widely used to study the spatial arrangement and quantitative behavior of biomolecules in fixed and living cells. In this work, direct stochastic optical reconstruction microscopy (dSTORM) was used to investigate the structural distribution of mem-brane components with virtually molecular resolution. Key issues are different preparation and staining strategies for membrane imaging as well as localization-based quantitative analyses of membrane molecules.
An essential precondition for the spatial and quantitative analysis of membrane components is the prevention of photoswitching artifacts in reconstructed localization microscopy images. Therefore, the impact of irradiation intensity, label density and photoswitching behavior on the distribution of plasma membrane and mitochondrial membrane proteins in dSTORM images was investigated. It is demonstrated that the combination of densely labeled plasma membranes and inappropriate photoswitching rates induces artificial membrane clusters. Moreover, inhomogeneous localization distributions induced by projections of three-dimensional membrane structures such as microvilli and vesicles are prone to generate artifacts in images of biological membranes. Alternative imaging techniques and ways to prevent artifacts in single-molecule localization microscopy are presented and extensively discussed.
Another central topic addresses the spatial organization of glycosylated components covering the cell membrane. It is shown that a bioorthogonal chemical reporter system consisting of modified monosaccharide precursors and organic fluorophores can be used for specific labeling of membrane-associated glycoproteins and –lipids. The distribution of glycans was visualized by dSTORM showing a homogeneous molecule distribution on different mammalian cell lines without the presence of clusters. An absolute number of around five million glycans per cell was estimated and the results show that the combination of metabolic labeling, click chemistry, and single-molecule localization microscopy can be efficiently used to study cell surface glycoconjugates.
In a third project, dSTORM was performed to investigate low-expressing receptors on cancer cells which can act as targets in personalized immunotherapy. Primary multiple myeloma cells derived from the bone marrow of several patients were analyzed for CD19 expression as potential target for chimeric antigen receptor (CAR)-modified T cells. Depending on the patient, 60–1,600 CD19 molecules per cell were quantified and functional in vitro tests demonstrate that the threshold for CD19 CAR T recognition is below 100 CD19 molecules per target cell. Results are compared with flow cytometry data, and the important roles of efficient labeling and appropriate control experiments are discussed.