2D mapping of strongly deformable cell nuclei, based on contour matching

The spatiotemporal dynamics of protein complexes and genome loci are functionally linked to cellular health status. To study the inherent motion of subnuclear particles, it is essential to remove any superimposed component stemming from displacement and deformation of the nucleus. In this article, we propose a mapping of the nuclear interior, which is based on the deformation of the nuclear contour and has no shape constraints. This registration procedure enabled an accurate estimation of telomere mobility in living human cells undergoing dramatic nuclear deformations. Given the large variety of pathologies and cellular processes that are associated with strong nuclear shape changes, the contour mapping algorithm has generic value for improving the accuracy of mobility measurements of genome loci and intranuclear macromolecule complexes

Three-dimensional single particle tracking in a light sheet microscope

Technical development in microscopy, and particularly in fluorescence microscopy, has facilitated the investigation of ever smaller details in biological specimen. The combination of specific labeling of molecular compounds, sophisticated optical setups and sensitive detectors enables observation of single molecules. Using fast video microscopy, it is now possible to directly observe the cell’s molecular machinery at work by tracking single molecules with high spatial and temporal resolution. Single molecule tracking can reveal detailed information about the dynamics of biological processes. However, technical requirements for single molecule detection limit the depth of field to less than 1 μm. Thus, single molecule tracking is typically limited to studying phenomena in planar membranes or, in extended specimen, often relies on two dimensional projections of short trajectory fragments. The work presented here strives to overcome these limitations by combining real-time three-dimensional localization of single particles with an active feedback loop to keep a particle of interest within the observation volume. To this end, a light sheet microscopy setup was designed and assembled around a commercial microscope body. It was equipped with a fast piezo stage for axial sample positioning. Three-dimensional spatial information was encoded in the shape of the point spread function by astigmatic detection and retrieved by real-time image analysis code developed for this purpose. A novel localization metric based on cross-correlation template matching was devised to enable tracking based on a low number of photons detected per particle. During post-processing, relative axial localizations determined from the image data were combined with the piezo stage position to obtain full three-dimensional particle trajectories. Mechanical and optical properties of the setup were thoroughly characterized using appropriate test samples. A temporal resolution down to 1,12 ms was achieved. The localization precision of the method was experimentally determined by repeated imaging of immobilized fluorescent beads. The capability to track single emitters was validated in a biochemical model system. Lipids labeled with a synthetic dye molecule were incorporated in the bilayer membrane of giant unilamellar vesicles and tracked on their spherical surface. Trajectories of more than 20 s duration could be obtained at as little as 130 photons detected per frame. An analysis of the photophysical properties revealed that observation times per particle were limited not by failure of the tracking algorithm but by photobleaching. Applicability of the method in biological specimen was proved by tracking fluorescent nanoparticles micro-injected into C. tentans salivary gland cell nuclei for more than 270 s in several thousand frames. Subsequently, the method was applied to track mRNA and rRNA particles in C. tentans salivary gland cell nuclei. Biomolecules were specifically labeled by complementary oligonucleotides carrying up to three synthetic dye molecules. It was possible to routinely acquire trajectories of particles with a diffusion coefficient of D = 1-2 μm2/s spanning ≥ 4 s and 4-5 μm in axial direction. The longest trajectories lasted more than 16 s and covered 10 μm axially. Both, observation time and axial range, were increased by more than one order of magnitude as compared to standard 2D tracking experiments. It was thus possible to investigate mobility states not on the basis of an ensemble of short observations but for individual particles

Non-rigid Contour-Based Registration of Cell Nuclei in 2D Live Cell Microscopy Images Using a Dynamic Elasticity Model

International audienceThe analysis of the pure motion of subnuclear structures without influence of the cell nucleus motion and deformation is essential in live cell imaging. In this work, we propose a 2D contour-based image registration approach for compensation of nucleus motion and deformation in fluorescence microscopy time-lapse sequences. The proposed approach extends our previous approach which uses a static elasticity model to register cell images. Compared to that scheme, the new approach employs a dynamic elasticity model for forward simulation of nucleus motion and deformation based on the motion of its contours. The contour matching process is embedded as a constraint into the system of equations describing the elastic behavior of the nucleus. This results in better performance in terms of the registration accuracy. Our approach was successfully applied to real live cell microscopy image sequences of different types of cells including image data that was specifically designed and acquired for evaluation of cell image registration methods. An experimental comparison with existing contour-based registration methods and an intensity-based registration method has been performed. We also studied the dependence of the results on the choice of method parameters

Nano-Bio-Interactions on Intracellular Plasmonics and Mechanobiology of Human Cells

Cancer is a complex disease that originates from various mutations in cells, influencing cellular growth and proliferation. During cancer progression, the biophysical properties of cells, as well as their responses to surrounding mechanical stimuli, are altered. These alterations impact their interactions and communications with their microenvironment and enhance the motility of cancer cells, allowing them to detach from the primary tumor and invade other healthy tissues/organs. Progress in nanotechnology and nanoscience has resulted in the nano-bio-interaction field in which the interaction between nanoparticles and cells are studied to develop innovative nanomedicines to optimize and revolutionize classical methods for cancer treatment and management. While nanomedicines could directly and selectively target cancer cells and deliver anti-cancer reagents to cancer cells, their presence into cells (even without drugs) could cause significant changes in the mechanobiological properties of cells. Although many studies showed that nano-bio-interaction could induce cytoskeletal changes in cancer cells, it is not yet clearly known or understood how these changes could potentially influence cancer progression. This dissertation focused on how cell-nanoparticle interactions and the resulting mechanobiological change in cancer cells would influence their cellular functions. Here, we utilized three different types of gold particles with different physicochemical properties to study their interactions with both healthy and cancer cells. In the first step of this research, we employed various nanotechnology and microscopic techniques including fluorescent imaging, SEM, Raman spectroscopy, dark-field imaging and hyperspectral imaging to study the behavior of gold nanoparticles in cells in terms of cellular uptake, cytotoxicity, internalization level, and subcellular localization. The findings revealed that all types of particles, sphere-shaped, star-shaped, and Swarna Bhasma, are non-toxic to the cells even with increasing doses and exposure times. Raman enhancement results highlighted the importance of nano-morphology in mediating changes in the affinity of gold nanoparticles to different chemical structures in cells, which is essential for developing nanomedicines. The hyperspectral technique was then utilized to detect particles in different regions of cells with measuring the intracellular plasmonic responses of nanoparticles. It was found that the regional-dependent plasmonic shifts of gold nanoparticles could be used to estimate the subcellular localization of nanoparticles. Nanospheres showed higher accumulation in cells, and they exhibited a greater plasmonic shift with more sensitivity to their neighboring medium compared to Swarna Bhasma and nanostars. This dissertation then used Atomic Force Microscopy for mechanobiological measurements and to study their alterations upon incubation with gold nanoparticles. Imaging techniques confirmed morphological and cytoskeletal changes in cancer cells after uptake of gold nanoparticles. Migration assays revealed that nanospheres cause stronger changes than nanostars in the dynamic capability of cancer cells, by significantly slowing down their migration. In support of this, biomechanical measurements showed that internalized gold nanospheres reduce the elasticity of cancer cells by 66% more compared to nanostars. The same trend was also observed in the adhesion levels of treated cells. We observed that nanospheres are mainly distributed in regions where force is generated and translocated for cell migration, and their distribution reasons why their impacts are stronger than nanostars. Furthermore, our simulations showed that the bulk stiffness of cells has contradictory effects on cell deformation and overcoming forces at the cell-substrate interfaces required for cell migration. To approximate the migratory capability of cells, we defined a stiffness-dependent energy term, migratory index, to uniquely capture the effects of both phenomena. Our modeling revealed that there is an optimal stiffness value/range associated with maximal migration, and when bulk stiffness deviates from the optimal range, the rate of migration is predicted to decrease. Our experimental results showed that nanospheres could change the bulk stiffness of cancer cells outside of the optimal range for efficient migration, and we hypothesize that this could suppress their metastatic potential of cancer cells

Quantitative single-molecule mapping of neuronal proteins at the nanoscale

The advent of super-resolution microscopy, also called nanoscopy, allowed a substantial improvement of spatial resolution, opening the door for the observation of biological structures beyond the diffraction limit impossible with conventional light microscopy. Among the super-resolution techniques, single-molecule localization microscopies have proven to be a powerful tool to address many biological issues, since they provide an imaging resolution of the order of tens of nanometers and the possibility to perform quantitative measurements. Neuroscience has been one of the fields in biology to benefit most from super-resolution microscopy. During the last years, single-molecule localization microscopies have been widely exploited to study diffraction-limited subcellular structures in neurons, allowing a deeper understanding of molecular mechanisms underlying neural network functioning and its impairments in pathologies. In this thesis, we developed a tool to investigate the distribution, spatial organization, clustering, and density of neural proteins at the nanoscale. In particular, we focused on the quantitative study of synaptic neurotransmitter receptors and focal adhesions. The knowledge of the distribution and stoichiometry of synaptic proteins is fundamental to understand the regulation of the synaptic transmission in neurons. However, a detailed characterization of the protein architecture within synapses can be achieved only by visualizing them at a nanometric level. Here we propose a quantitative approach based on stochastic optical reconstruction microscopy combined with cluster analysis to investigate the molecular rearrangement of GABAA receptors into subsynaptic domains during synaptic plasticity of the inhibitory neurotransmission. This approach was also applied to the study of the adhesion machinery of mammalian cells and neurons at the interface with single-layer graphene to investigate the interaction between cells and nanostructured materials. Due to their excellent properties and biocompatibility, graphene and its derivatives are the ideal candidates for many biomedical applications, such as neural tissue engineering. However, the adhesion processes at the graphene/neuron interface are still not clear nowadays. Our method offers an easy way to study how graphene substrates can affect adhesion and migration of different types of cells

Local image correlation methods for the characterization of subcellular structure and dynamics by confocal and super-resolution microscopy

This thesis work aspires to present a new concept for the application of correlation techniques to the study of the cellular environment. By exploiting local analysis in combination to a fast fit-free technique (the phasor approach) we provide an exhaustive high-resolution analysis of structural and dynamic properties while maintaining a reasonable computation time. The dissertation will be articulated as follows: In CHAPTER 1 we aim to provide the reader with a description of the techniques that will be exploited during the rest of the dissertation together with the open questions and problematics that our techniques will try to answer to. In CHAPTER 2 we present the local analysis concept and its application to a correlation technique capable of measuring size and concentration (ICS). We will show how we coupled ICS to the phasor approach to create a technique (PLICS) for the assessment of size heterogeneity. PLICS will be demonstrated with simulations as well as with cellular samples and will be applied to the study of endocytic vesicles uptake and to the characterization of other organelles. In CHAPTER 3 the concept is extended to two-colors samples for the determination of local inter-structure distance (PLICCS). We will present a pattern analysis method we developed that exploits this information in order to evaluate the relative distribution of the structures imaged in the two channels, comparing it to a random distribution. This method will be validated with simulations and applied to the study of replication-transcription collisions. Successively, we will show that PLICCS can be converted to a localization algorithm for single particle tracking that will be used for tracking membrane receptors in living neurons. CHAPTER 4 will describe the extension of our local analysis to RICS, a correlation technique capable of measuring the diffusion coefficient of a fluorescent probe. The resulting algorithm (L-RICS) provides high resolution diffusion maps that will be used to characterize the diffusion of a fluorescent probe (GFP) within the nucleus and nucleolus of living cells. We will show that the algorithm can be implemented also in non-linear scanning systems. CHAPTER 5 will conclude the dissertation by introducing advanced correlation methods for the analysis of non-Brownian diffusion and their coupling to super-resolution techniques. In particular, we will present a super-resolution correlation technique (SPLIT) recently developed capable of analyzing the cellular environment and a microcamera-based approach (Airyscan comprehensive correlation analysis) we developed for the parallel implementation, in super-resolution, of several complementary correlation techniques

Multimodal image analysis of the human brain

Gedurende de laatste decennia heeft de snelle ontwikkeling van multi-modale en niet-invasieve hersenbeeldvorming technologieën een revolutie teweeg gebracht in de mogelijkheid om de structuur en functionaliteit van de hersens te bestuderen. Er is grote vooruitgang geboekt in het beoordelen van hersenschade door gebruik te maken van Magnetic Reconance Imaging (MRI), terwijl Elektroencefalografie (EEG) beschouwd wordt als de gouden standaard voor diagnose van neurologische afwijkingen. In deze thesis focussen we op de ontwikkeling van nieuwe technieken voor multi-modale beeldanalyse van het menselijke brein, waaronder MRI segmentatie en EEG bronlokalisatie. Hierdoor voegen we theorie en praktijk samen waarbij we focussen op twee medische applicaties: (1) automatische 3D MRI segmentatie van de volwassen hersens en (2) multi-modale EEG-MRI data analyse van de hersens van een pasgeborene met perinatale hersenschade. We besteden veel aandacht aan de verbetering en ontwikkeling van nieuwe methoden voor accurate en ruisrobuuste beeldsegmentatie, dewelke daarna succesvol gebruikt worden voor de segmentatie van hersens in MRI van zowel volwassen als pasgeborenen. Daarenboven ontwikkelden we een geïntegreerd multi-modaal methode voor de EEG bronlokalisatie in de hersenen van een pasgeborene. Deze lokalisatie wordt gebruikt voor de vergelijkende studie tussen een EEG aanval bij pasgeborenen en acute perinatale hersenletsels zichtbaar in MRI

Guidelines for DNA recombination and repair studies: Mechanistic assays of DNA repair processes

Genomes are constantly in flux, undergoing changes due to recombination, repair and mutagenesis. In vivo, many of such changes are studies using reporters for specific types of changes, or through cytological studies that detect changes at the single-cell level. Single molecule assays, which are reviewed here, can detect transient intermediates and dynamics of events. Biochemical assays allow detailed investigation of the DNA and protein activities of each step in a repair, recombination or mutagenesis event. Each type of assay is a powerful tool but each comes with its particular advantages and limitations. Here the most commonly used assays are reviewed, discussed, and presented as the guidelines for future studies