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Single molecule localization microscopy has seen a remarkable growth since its first
experimental implementations about a decade ago. Despite its technical challenges,
it is already widely used in medicine and biology and is valued as a unique tool
to gain molecular information with high specificity. However, common illumination techniques do not allow the use of single molecule sensitive super-resolution
microscopy techniques such as direct stochastic optical reconstruction microscopy
(dSTORM) for whole cell imaging. In addition, they can potentially alter the
quantitative information.
In this thesis, I combine dSTORM imaging in three dimensions with lattice lightsheet illumination to gain quantitative molecular information from cells unperturbed by the illumination and cover slip effects. Lattice light-sheet illumination
uses optical lattices for beam shaping to restrict the illumination to the detectable
volume. I describe the theoretical background needed for both techniques and detail
the experimental realization of the system as well as the software that I developed
to efficiently evaluate the data.
Eventually, I will present key datasets that demonstrate the capabilities of the
developed microscope system with and without dSTORM. My main goal here was
to use these techniques for imaging the neural cell adhesion molecule (NCAM, also
known as CD56) in whole cells. NCAM is a plasma membrane receptor known to
play a key role in biological processes such as memory and learning. Combining
dSTORM and lattice light-sheet illumination enables the collection of quantitative
data of the distribution of molecules across the whole plasma membrane, and shows
an accumulation of NCAM at cell-cell interfaces. The low phototoxicity of lattice
light-sheet illumination further allows for tracking individual NCAM dimers in living cells, showing a significant dependence of its mobility on the actin skeleton of
the cell.
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.
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.
Ziel dieser Arbeit war es, strukturelle Veränderungen präsynaptischer Aktiver Zonen als mögliches Korrelat synaptischer Plastizität zu detektieren. Damit soll die Hypothese getestet werden, dass strukturelle Plastizität Aktiver Zonen eine zentrale Rolle bei der Informationsverarbeitung im Gehirn und bei Lern- und Gedächtnisprozessen spielt. Dazu war es notwendig Methoden zu etablieren, die die strukturelle Analyse Aktiver Zonen und deren Veränderung in vitalem Gewebe ermöglichen. Um die Untersuchungen in einem Gewebe mit plastischen Eigenschaften durchzuführen, wurden Methoden zur Herstellung organotypischer hippocampaler Hirnschnittkulturen etabliert, da hippokampale Moosfasersynapsen ausgeprägte präsynaptische Plastizität aufweisen (Bliss und Collingridge, 1993). Durch Einzelzellelektroporation wurde es möglich, individuelle Neurone mit Transgenen zur Markierung der gesamten Zelle (DsRed) und synaptischer Substrukturen wie Aktive Zonen (z.B.: GFP-CAST, einem Fluorophor-markierten AZ-Protein) zu transfizieren. Mit konfokaler Bildgebung transfizierter Zellen konnten strukturierte Anreicherungen von GFP-CAST in Moosfaserboutons dargestellt werden. Konfokale Bildgebung von Doppelimmunfluoreszenzfärbungen zur detaillierten Analyse der Proteinlokalisation zeigte ein diffraktionsbedingtes Auflösungsdefizit, das auch durch die Anwendung von STED-Mikroskopie nicht zufriedenstellend gelöst werden konnte. Um eine präzise Karte synaptischer Proteine zu erstellen, wurde hochauflösende Mikroskopie (dSTORM) mit einer lateralen räumlichen Auflösung von 20 nm etabliert. Dabei erwiesen sich die ausgeprägte Plastizität, die hohe Dichte an Aktiven Zonen und die variable Gestalt der Boutons im hippokampalen Präparat als problematisch. Aus diesem Grund wurde die elektronenmikroskopisch gut charakterisierte neuromuskuläre Endplatte mit ihrer symmetrischen molekularen Struktur als Präparat für dSTORM verwendet. An der Endplatte konnte die molekulare Organisation der Aktiven-Zonen-Proteine Piccolo und Bassoon dargestellt werden. Zudem konnten erstmals die Mündungen postsynaptischer Falten lichtmikroskopisch aufgelöst werden. So gelang es Werkzeuge zu etablieren, die mit lichtmikroskopischen Methoden die Darstellung der Architektur Aktiver Zonen mit molekularer Auflösung ermöglichen. Die Herausforderung wird es sein, diese neue Dimension in funktionellem Kontext zu nutzen. Die experimentellen Grundlagen dazu wurden durch eine spezielle Badkammer und die Etablierung von Rollertubekulturen bereits gelegt. Dabei ermöglicht dSTORM die Adressierung quantitativer Fragestellungen bis hin zur Bestimmung der Molekülanzahl.
Die Lokalisationsmikroskopie ist eine neue, vielversprechende Methode der hochauflösenden Fluoreszenzmikroskopie. Sie ermöglicht detaillierte Einblicke in die Organisation und den strukturellen Aufbau von Zellen. Da die Vorbereitung der Proben und das Aufnehmen der Bilder im Vergleich zu herkömmlichen Methoden höhere Anforderungen stellt, mussten ihr Potential und ihre Zuverlässigkeit erst noch überzeugend gezeigt werden. Bis vor kurzem wurde das Auflösungsvermögen vor allem an Mikrotubuli gezeigt, deren filamentöse Struktur allerdings schon in konfokalen Bildern zu erkennen ist. Deswegen wurde in dieser Dissertation der Kernporenkomplex (NPC), dessen Struktur in der konventionellen Fluoreszenzmikroskopie nicht auflösbar ist, als Modellstruktur für die hochauflösende Fluoreszenzmikroskopie eingeführt.
Dazu wurden Kernporenkomplexe aus Kernhüllen von Xenopus laevis Oocyten mit dSTORM (direct stochastic optical reconstruction microscopy), einer Methode der Lokalisationsmikroskopie, hochaufgelöst. Damit konnte nun erstmals die Achtfachsymmetrie dieses Proteinkomplexes lichtmikroskopisch dargestellt werden. Desweiteren konnte der Zentralkanal mit einem Durchmesser von ca. 40 nm aufgelöst werden. Die Daten eigneten sich außerdem für eine automatisierte Bildanalyse nach dem sogenannten "particle averaging" - einer aus der Elektronenmikroskopie bekannten Methode, um eine Durchschnittsstruktur zu ermitteln.
Darüber hinaus wurden Zweifach-Färbungen von NPCs benutzt, um verschiedene Ansätze für Zweifarben-Aufnahmen mit dSTORM zu testen. Neben dem mittlerweile standardmäßig benutzten, sequentiellen Ansatz mit zwei spektral getrennten Farbstoffen, wurde auch ein simultaner Ansatz mit zwei spektral überlappenden Farbstoffen erfolgreich angewandt. Auch für 3D-Messungen mit den Ansätzen Biplane und Astigmatismus eignete sich die Markierung der Kernhülle. Hier wurden jedoch A6-Zellen benutzt und die Krümmung des Zellkerns über die gefärbten Kernporen dargestellt.
dSTORM-Messungen können nicht nur an fixierten, sondern auch in lebenden Zellen durchgeführt werden. Hierzu eignen sich vor allem sehr immobile Proteine, wie H2B oder Lamin C. Anhand von SNAP-Tag- und Halo-Tag-Konstrukten konnte gezeigt werden, dass sich kommerziell erhältliche, organische Farbstoffe auch in endogener zellulärer Umgebung schalten lassen, wodurch Lebendzell-Aufnahmen mit dSTORM möglich sind.
Ein weiterer Teil dieser Arbeit befasst sich mit korrelativen Aufnahmen aus dSTORM und Rasterelektronenmikroskopie (SEM). Hierzu wurden Xenopus laevis Kernhüllen zuerst mit dSTORM hochaufgelöst und danach für die EM präpariert. Anschließend wurden zugehörige Bereiche am Rasterelektronenmikroskop aufgenommen. Mit den erhaltenen korrelativen Bildern konnte gezeigt werden, dass sich dSTORM und SEM bei geeigneten Proben durchaus kombinieren lassen. Proteine können somit spezifisch markiert und im Rahmen ihrer strukturellen Umgebung mit nahezu molekularer Auflösung dargestellt werden.
Da hochwertige Aufnahmen eine ausgereifte Probenpräparation voraussetzen, darf deren Etablierung nicht zu kurz kommen. Unter dieser Prämisse wurde ein optimiertes Markierungsprotokoll mit dem Namen ClickOx entwickelt. Mit ClickOx bleibt bei der kupferkatalysierten Azid-Alkin-Cycloaddition die Feinstruktur von Aktinfilamenten, sowie die Fluoreszenz fluoreszierender Proteine, deutlich sichtbar erhalten. Während bei den klassischen Click-Protokollen auf Grund der Entstehung von reaktiven Sauerstoff-Spezies (ROS) feine zelluläre Strukturen, wie Aktinfilamente, angegriffen oder zerstört werden, schützt das neue Protokoll mit enzymatischem Sauerstoffentzug Proteine und somit Strukturen vor Reaktionen mit ROS. Das unterstreicht, wie wichtig es ist auch sogenannte "etablierte" Protokolle weiterzuentwickeln, denn bestimmte Nebeneffekte in Präparationen werden unter Umständen erstmals in der Hochauflösung sichtbar.
Ein weiterer Aspekt war die Untersuchung des Einflusses von D1 auf die Chromatinorganisation. Mit verschiedenen mikroskopischen Methoden konnten Hinweise auf eine mögliche DNA-Cross-Linking-Fähigkeit dieses Proteins gesammelt werden. Hier wurde die Einzelmolekülinformation der dSTORM-Filme genutzt, um unterschiedliche Grade von DNA- bzw. Chromatin-Akkumulation zu vergleichen. Die Ergebnisse deuten darauf hin, dass wildtypisches D1 DNA vernetzen kann. Dies erfolgt über die sogenannten AT-Haken-Motive. Sobald diese alle durch Mutation funktionsunfähig gemacht werden - wie bei der verwendeten R10xG-Mutante - lässt sich keine Akkumulation der DNA mehr beobachten. Neben der Chromatinaggregation durch D1-Expression konnte in FRAP-Experimenten gezeigt werden, dass nur die "echten" AT-Haken eine hohe Affinität zum Chromatin aufweisen, die sogenannten "potentiellen" hingegen nicht.
The active zone (AZ) protein Bruchpilot (Brp) is essential for rapid glutamate release at Drosophila melanogaster neuromuscular junctions (NMJs). Quantal time course and measurements of action potential-waveform suggest that presynaptic fusion mechanisms are altered in brp null mutants (brp\(^{69}\)). This could account for their increased evoked excitatory postsynaptic current (EPSC) delay and rise time (by about 1 ms). To test the mechanism of release protraction at brp\(^{69}\) AZs, we performed knock-down of Synaptotagmin-1 (Syt) via RNAi (syt\(^{KD}\)) in wildtype (wt), brp\(^{69}\) and rab3 null mutants (rab3\(^{rup}\)), where Brp is concentrated at a small number of AZs. At wt and rab3\(^{rup}\) synapses, syt\(^{KD}\) lowered EPSC amplitude while increasing rise time and delay, consistent with the role of Syt as a release sensor. In contrast, syt\(^{KD}\) did not alter EPSC amplitude at brp\(^{69}\) synapses, but shortened delay and rise time. In fact, following syt\(^{KD}\), these kinetic properties were strikingly similar in wt and brp\(^{69}\), which supports the notion that Syt protracts release at brp\(^{69}\) synapses. To gain insight into this surprising role of Syt at brp\(^{69}\) AZs, we analyzed the structural and functional differentiation of synaptic boutons at the NMJ. At tonic type Ib motor neurons, distal boutons contain more AZs, more Brp proteins per AZ and show elevated and accelerated glutamate release compared to proximal boutons. The functional differentiation between proximal and distal boutons is Brp-dependent and reduced after syt\(^{KD}\). Notably, syt\(^{KD}\) boutons are smaller, contain fewer Brp positive AZs and these are of similar number in proximal and distal boutons. In addition, super-resolution imaging via dSTORM revealed that syt\(^{KD}\) increases the number and alters the spatial distribution of Brp molecules at AZs, while the gradient of Brp proteins per AZ is diminished. In summary, these data demonstrate that normal structural and functional differentiation of Drosophila AZs requires concerted action of Brp and Syt.
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.
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.
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 fusion of methods from several disciplines is a crucial component of scientific development. Artificial Neural Networks, based on the principle of biological neuronal networks, demonstrate how nature provides the best templates for technological advancement. These innovations can then be employed to solve the remaining mysteries of biology, including, in particular, processes that take place on microscopic scales and can only be studied with sophisticated techniques. For instance, direct Stochastic Optical Reconstruction Microscopy combines tools from chemistry, physics, and computer science to visualize biological processes at the molecular level. One of the key components is the computer-aided reconstruction of super-resolved images. Improving the corresponding algorithms increases the quality of the generated data, providing further insights into our biology. It is important, however, to ensure that the heavily processed images are still a reflection of reality and do not originate in random artefacts.
Expansion microscopy is expanding the sample by embedding it in a swellable hydrogel. The method can be combined with other super-resolution techniques to gain additional resolution. We tested this approach on microtubules, a well-known filamentous reference structure, to evaluate the performance of different protocols and labelling techniques.
We developed LineProfiler an objective tool for data collection. Instead of collecting perpendicular profiles in small areas, the software gathers line profiles from filamentous structures of the entire image. This improves data quantity, quality and prevents a biased choice of the evaluated regions. On the basis of the collected data, we deployed theoretical models of the expected intensity distribution across the filaments. This led to the conclusion that post-expansion labelling significantly reduces the labelling error and thus, improves the data quality. The software was further used to determine the expansion factor and arrangement of synaptonemal complex data.
Automated Simple Elastix uses state-of-the-art image alignment to compare pre- and post-expansion images. It corrects linear distortions occurring under isotropic expansion, calculates a structural expansion factor and highlights structural mismatches in a distortion map. We used the software to evaluate expanded fungi and NK cells. We found that the expansion factor differs for the two structures and is lower than the overall expansion of the hydrogel.
Assessing the fluorescence lifetime of emitters used for direct Stochastic Optical Reconstruction Microscopy can reveal additional information about the molecular environment or distinguish dyes emitting with a similar wavelength. The corresponding measurements require a confocal scanning of the sample in combination with the fluorescent switching of the underlying emitters. This leads to non-linear, interrupted Point Spread Functions. The software ReCSAI targets this problem by combining the classical algorithm of compressed sensing with modern methods of artificial intelligence. We evaluated several different approaches to combine these components and found, that unrolling compressed sensing into the network architecture yields the best performance in terms of reconstruction speed and accuracy.
In addition to a deep insight into the functioning and learning of artificial intelligence in combination with classical algorithms, we were able to reconstruct the described non-linearities with significantly improved resolution, in comparison to other state-of-the-art architectures.
Die Einführung der Fluoreszenzmikroskopie ermöglicht es, Strukturen in Zellen spezifisch und mit hohem Kontrast zu markieren und zu untersuchen. Da die Lichtmikroskopie jedoch in ihrer Auflösung begrenzt ist, bleiben Strukturinformationen auf molekularer Ebene verborgen. Diese als Beugungsgrenze bekannte Limitierung, kann mit modernen Verfahren umgangen werden. Die Lokalisationsmikroskopie nutzt hierfür photoschaltbare Fluorophore, deren Fluoreszenz räumlich und zeitlich separiert wird, um so einzelne Fluorophore mit
Nanometer-Genauigkeit lokalisieren zu können. Aus tausenden Einzelmolekül-Lokalisationen wird ein künstliches, hochaufgelöstes Bild rekonstruiert. Die
hochauflösende Mikroskopie ist grade für die Lebendzell-Beobachtung ein wertvolles Werkzeug, um subzelluläre Strukturen und Proteindynamiken jenseits der Beugungsgrenze unter physiologischen Bedingungen untersuchen zu können.
Als Marker können sowohl photoaktivierbare fluoreszierende Proteine als auch photoschaltbare organische Fluorophore eingesetzt werden. Während die
Markierung mit fluoreszierenden Proteinen einfach zu verwirklichen ist, haben organische Farbstoffe hingegen den Vorteil, dass sie auf Grund der höheren Photonenausbeute eine präzisere Lokalisation erlauben. In lebenden Zellen wird die Markierung von Strukturen mit synthetischen Fluorophoren über sogenannte
chemische Tags ermöglicht. Diese sind olypeptidsequenzen, die genetisch an das Zielprotein fusioniert werden und anschließend mit Farbstoff-gekoppelten Substraten gefärbt werden. An der Modellstruktur des Histonproteins H2B
werden in dieser Arbeit Farbstoffe in Kombination mit chemischen Tags identifiziert, die erfolgreich für die Hochauflösung mit direct stochastic optical
reconstruction microscopy (dSTORM) in lebenden Zellen eingesetzt werden können. Für besonders geeignet erweisen sich die Farbstoffe Tetramethylrhodamin,
505 und Atto 655, womit der gesamte spektrale Bereich vertreten ist. Allerdings können unspezifische Bindung und Farbstoffaggregation ein Problem bei der effizienten Markierung in lebenden Zellen darstellen. Es wird
gezeigt, dass die Beschichtung der Glasoberfläche mit Glycin die unspezifische Adsorption der Fluorophore erfolgreich minimieren kann. Weiterhin wird der
Einfluss des Anregungslichtes auf die lebende Zelle diskutiert. Es werden Wege beschrieben, um die Photoschädigung möglichst gering zu halten, beispielsweise
durch die Wahl eines Farbstoffs im rotem Anregungsbereich.
Die Möglichkeit lebende Zellen mit photoschaltbaren organischen Fluorophoren spezifisch markieren zu können, stellt einen großen Gewinn für die Lokalisationsmikroskopie dar, bei der ursprünglich farbstoffgekoppelte Antikörper zum Einsatz kamen. Diese Markierungsmethode wird in dieser Arbeit eingesetzt, um
das Aggregationsverhalten von Alzheimer verursachenden -Amyloid Peptiden im Rahmen einer Kooperation zu untersuchen. Es werden anhand von HeLa Zellen verschiedene beugungsbegrenzte Morphologien der Aggregate aufgeklärt. Dabei wird gezeigt, dass intrazellulär vorhandene Peptide größere Aggregate formen als die im extrazellulären Bereich. In einer zweiten Kollaboration wird mit Hilfe des photoaktivierbaren Proteins
mEos2 und photoactivated localization microscopy (PALM) die strukturelle Organisation zweier Flotillinproteine in der Membran von Bakterien untersucht.
Diese Proteine bilden zwei Cluster mit unterschiedlichen Durchmessern, die mit Nanometer-Genauigkeit bestimmt werden konnten. Es wurde außerdem festgestellt, dass beide Proteine in unterschiedlichen Anzahlen im Bakterium
vorliegen.
HMGA1 Proteine sind kleine, basische, Nicht-Histon Proteine, die in Lösung keine Struktur aufweisen, durch drei AT-Haken, als DNA-Bindungsmotive, gekennzeichnet sind und präferentiell an die kleine Furche der DNA binden. Als differenziell exprimierte Architekturelemente des Chromatins erfüllen sie wichtige Funktionen bei der Regulation DNA abhängiger Prozesse in Zellen und während Entwicklungsprozessen. Aberrante Expressionen führen zu Entwicklungsdefekten und Krebs. In dieser Arbeit wurde der Einfluss von HMGA1 Proteinen auf die Organisation des Chromatins untersucht. Als Modell diente dabei zunächst die Differenzierung von C2C12 Muskelvorläuferzellen. Wie in einer früheren Arbeit gezeigt wurde, ist die Herunterregulation von HMGA1a essentiell für den Eintritt von C2C12 Zellen in die Myogenese. Eine konstante Überexpression von HMGA1a-eGFP hingegen verhindert die Muskeldifferenzierung durch Beeinflussung der Expression myogenesespezifischer Gene und Etablierung einer stabilen Chromatinstruktur. Wie in der vorliegenden Arbeit herausgefunden wurde, nimmt die differenzielle HMGA1a Expression nicht nur Einfluss auf die Expression muskelspezifischer Gene, sondern auch auf die globale Zusammensetzung des Chromatins durch eine reduzierte Expression von H1 Histonen und einer aberranten Expression von HMGB1, HMGN1 und HP1 Proteinen. HMGA1a wurde zusammen mit ORC Proteinen eine Funktion bei der Definition von Replikationsursprüngen in eukaryotischen Zellen zugesprochen. ORC Proteine wurden auch als Komponenten des Heterochromatins und als Interaktionspartner von HP1α identifiziert. Hier konnte mit Hilfe von Co-Immunpräzipitationen, Pull-down Assays und Verdrängungsexperimenten gezeigt werden, dass HMGA1 ein weiterer, direkter Interaktionspartner von ORC Proteinen im Heterochromatin ist und zusammen mit HP1α kooperiert. Pull-down-, Verdrängungs- und siRNA-Experimente zeigten zudem, dass HMGA1 zwar nicht direkt mit HP1α interagiert, die Kooperation der Proteine über ORC aber dennoch wichtig für die Aufrechterhaltung der Heterochromatinsstruktur ist. Damit erweisen sich HMGA1 Proteine als wichtige Stabilisierungsfaktoren des Heterochromatins. Bislang ging man davon aus, dass HMGA1 Moleküle linear, also eindimensional, an ein DNA Molekül binden. Das Vorhandensein von drei DNA-Bindungsmotiven und die eher struktur- als sequenzabhängige Bindung an die DNA lassen vermuten, dass HMGA1 Proteine auch gleichzeitig an benachbarte DNA-Stränge, also auch dreidimensional, binden könnten. Bekräftigt wurde diese Vermutung durch die Bildung von Chromatinaggregaten in Zellen die HMGA1a-eGFP überexprimierten. Dies wurde mittels konfokaler und hochauflösender Mikroskopie (dSTORM) analysiert. Um das Potential einer DNA-Quervernetzung durch HMGA1 Proteine nachzuweisen, wurde eine neue Methode entwickelt. Mit Hilfe eines neuartigen DNA Cross-linking Assays wurde nachgewiesen, dass HMGA1 Proteine in der Lage sind, zwei individuelle DNA Stränge zu vernetzen. Zudem wurde eine neue Domäne in HMGA1 entdeckt die maßgeblich zum Cross-linking beiträgt. Elektronenmikroskopische Analysen bestätigten, dass HMGA1 Proteine in der Lage sind Kreuzungen und Schleifen in DNA Molekülen zu erzeugen. Diese Ergebnisse unterstützen die Vermutung, dass HMGA1 Proteine im Zellkern ein DNA Gerüst bilden können, das Einfluss auf die zelltypische Chromatinorganisation nimmt und dadurch DNA abhängige Prozesse beeinflusst. In wie weit eine HMGA1 induzierte DNA Quervernetzung in vivo zum Beispiel in Chromozentren von C2C12 Zellen oder in Krebszellen, in denen HMGA1 Proteine stark überexprimiert sind, eine Rolle spielen, müssen künftige Untersuchungen zeigen. In dieser Arbeit konnte also gezeigt werden, dass HMGA1 Proteine die Chromatinstruktur auf drei Ebenen organisieren können: Durch Beeinflussung der Chromatinzusammensetzung durch Veränderung der Expression von Chromatinproteinen, durch Interaktion mit anderen Architekturelementen des Chromatins und durch Organisation eines potentiellen DNA Gerüsts.
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.
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.
Background
Localization-based super-resolution microscopy resolves macromolecular structures down to a few nanometers by computationally reconstructing fluorescent emitter coordinates from diffraction-limited spots. The most commonly used algorithms are based on fitting parametric models of the point spread function (PSF) to a measured photon distribution. These algorithms make assumptions about the symmetry of the PSF and thus, do not work well with irregular, non-linear PSFs that occur for example in confocal lifetime imaging, where a laser is scanned across the sample. An alternative method for reconstructing sparse emitter sets from noisy, diffraction-limited images is compressed sensing, but due to its high computational cost it has not yet been widely adopted. Deep neural network fitters have recently emerged as a new competitive method for localization microscopy. They can learn to fit arbitrary PSFs, but require extensive simulated training data and do not generalize well. A method to efficiently fit the irregular PSFs from confocal lifetime localization microscopy combining the advantages of deep learning and compressed sensing would greatly improve the acquisition speed and throughput of this method.
Results
Here we introduce ReCSAI, a compressed sensing neural network to reconstruct localizations for confocal dSTORM, together with a simulation tool to generate training data. We implemented and compared different artificial network architectures, aiming to combine the advantages of compressed sensing and deep learning. We found that a U-Net with a recursive structure inspired by iterative compressed sensing showed the best results on realistic simulated datasets with noise, as well as on real experimentally measured confocal lifetime scanning data. Adding a trainable wavelet denoising layer as prior step further improved the reconstruction quality.
Conclusions
Our deep learning approach can reach a similar reconstruction accuracy for confocal dSTORM as frame binning with traditional fitting without requiring the acquisition of multiple frames. In addition, our work offers generic insights on the reconstruction of sparse measurements from noisy experimental data by combining compressed sensing and deep learning. We provide the trained networks, the code for network training and inference as well as the simulation tool as python code and Jupyter notebooks for easy reproducibility.
Localization microscopy is a class of super-resolution fluorescence microscopy techniques. Localization microscopy methods are characterized by stochastic temporal isolation of fluorophore emission, i.e., making the fluorophores blink so rapidly that no two are
likely to be photoactive at the same time close to each other. Well-known localization microscopy methods include dSTORM}, STORM, PALM, FPALM, or GSDIM. The biological community has taken great interest in localization microscopy, since it can enhance the resolution of common fluorescence microscopy by an order of magnitude at little experimental cost.
However, localization microscopy has considerable computational cost since millions of individual stochastic emissions must be located with nanometer precision. The computational cost of this evaluation, and the organizational cost of implementing the complex algorithms, has impeded adoption of super-resolution microscopy for a long time.
In this work, I describe my algorithmic framework for evaluating localization microscopy data.
I demonstrate how my novel open-source software achieves real-time data evaluation, i.e., can evaluate data faster than the common experimental setups can capture them.
I show how this speed is attained on standard consumer-grade CPUs, removing the need for computing on expensive clusters or deploying graphics processing units.
The evaluation is performed with the widely accepted Gaussian PSF model and a Poissonian maximum-likelihood noise model.
I extend the computational model to show how robust, optimal two-color evaluation is realized, allowing correlative microscopy between multiple proteins or structures. By employing cubic B-splines, I show how the evaluation of three-dimensional samples can be made simple and robust, taking an important step towards precise imaging of micrometer-thick samples.
I uncover the behavior and limits of localization algorithms in the face of increasing emission densities.
Finally, I show up algorithms to extend localization microscopy to common biological problems.
I investigate cellular movement and motility by considering the in vitro movement of myosin-actin filaments. I show how SNAP-tag fusion proteins enable imaging with bright and stable organic fluorophores in live cells. By analyzing the internal structure of protein clusters, I show how localization microscopy can provide new quantitative approaches beyond pure imaging.
Single-molecule localization microscopy (SMLM) greatly advances structural studies of diverse biological tissues. For example, presynaptic active zone (AZ) nanotopology is resolved in increasing detail. Immunofluorescence imaging of AZ proteins usually relies on epitope preservation using aldehyde-based immunocompetent fixation. Cryofixation techniques, such as high-pressure freezing (HPF) and freeze substitution (FS), are widely used for ultrastructural studies of presynaptic architecture in electron microscopy (EM). HPF/FS demonstrated nearer-to-native preservation of AZ ultrastructure, e.g., by facilitating single filamentous structures. Here, we present a protocol combining the advantages of HPF/FS and direct stochastic optical reconstruction microscopy (dSTORM) to quantify nanotopology of the AZ scaffold protein Bruchpilot (Brp) at neuromuscular junctions (NMJs) of Drosophila melanogaster. Using this standardized model, we tested for preservation of Brp clusters in different FS protocols compared to classical aldehyde fixation. In HPF/FS samples, presynaptic boutons were structurally well preserved with ~22% smaller Brp clusters that allowed quantification of subcluster topology. In summary, we established a standardized near-to-native preparation and immunohistochemistry protocol for SMLM analyses of AZ protein clusters in a defined model synapse. Our protocol could be adapted to study protein arrangements at single-molecule resolution in other intact tissue preparations.
The development of cellular life on earth is coupled to the formation of lipid-based biological membranes. Although many tools to analyze their biophysical properties already exist, their variety and number is still relatively small compared to the field of protein studies. One reason for this, is their small size and complex assembly into an asymmetric tightly packed lipid bilayer showing characteristics of a two-dimensional heterogenous fluid. Since membranes are capable to form dynamic, nanoscopic domains, enriched in sphingolipids and cholesterol, their detailed investigation is limited to techniques which access information below the diffraction limit of light. In this work, I aimed to extend, optimize and compare three different labeling approaches for sphingolipids and their subsequent analysis by the single-molecule localization microscopy (SMLM) technique direct stochastic optical reconstruction microscopy (dSTORM). First, I applied classical immunofluorescence by immunoglobulin G (IgG) antibody labeling to detect and quantify sphingolipid nanodomains in the plasma membrane of eukaryotic cells. I was able to identify and characterize ceramide-rich platforms (CRPs) with a size of ~ 75nm on the basal and apical membrane of different cell lines. Next, I used click-chemistry to characterize sphingolipid analogs in living and fixed cells. By using a combination of fluorescence microscopy and anisotropy experiments, I analyzed their accessibility and configuration in the plasma membrane, respectively. Azide-modified, short fatty acid side chains, were accessible to membrane impermeable dyes and localized outside the hydrophobic membrane core. In contrast, azide moieties at the end of longer fatty acid side chains were less accessible and conjugated dyes localized deeper within the plasma membrane. By introducing photo-crosslinkable diazirine groups or chemically addressable amine groups, I developed methods to improve their immobilization required for dSTORM. Finally, I harnessed the specific binding characteristics of non-toxic shiga toxin B subunits (STxBs) and cholera toxin B subunits (CTxBs) to label and quantify glycosphingolipid nanodomains in the context of Neisseria meningitidis infection. Under pyhsiological conditions, these glycosphingolipids were distributed homogenously in the plasma membrane but upon bacterial infection CTxB detectable gangliosides accumulated around invasive Neisseria meningitidis. I was able to highlight the importance of cell cycle dependent glycosphingolipid expression for the invasion process. Blocking membrane accessible sugar headgroups by pretreatment with CTxB significantly reduced the number of invasive bacteria which confirmed the importance of gangliosides for bacterial uptake into cells. Based on my results, it can be concluded that labeling of sphingolipids should be carefully optimized depending on the research question and applied microscopy technique. In particular, I was able to develop new tools and protocols which enable the characterization of sphingolipid nanodomains by dSTORM for all three labeling approaches.