Optical imaging methods for the study of disease models from the nano to the mesoscale

The visualisation of disease phenotypes allows scientists to study fundamental mechanisms of disease. Optical imaging methods are useful not only to observe anatomical features of biological samples, but also to infer interactions between molecular species using fluorescence labelling. This thesis presents the development of imaging and analysis tools to study biological questions in three models of disease, with samples ranging from the sub-cellular to the organ scale. First, the role of the alpha-synuclein (a-syn) protein, whose dysfunction is a hallmark of Parkinson’s Disease, was studied with respect to vesicle trafficking at the synapse. Synaptic vesicles are ∼40 nm in diameter; imaging vesicles therefore requires methods with resolution below the diffraction limit. Single-molecule localisation microscopy (SMLM), which circumvents the diffraction limit by separating fluorophore emission in time to localise individual molecules in space with ∼20 nm precision, was thus implemented to study a-syn in purified synaptic boutons. A software package was developed to analyse the colocalisation of a-syn with internalised vesicles, and the clustering of a-syn under differing synaptic calcium levels. The colocalisation of a-syn and internalised vesicles was found to be temperature independent, suggesting that a-syn is involved in non-canonical trafficking mechanisms. Ground truth simulations from a synaptosome model were used to benchmark two cluster analysis methods. Both methods applied on the experimental data showed that a-syn becomes less clustered at low synaptic calcium levels. Second, the spatiotemporal association of ESCRT-II, a protein complex whose role in the budding of the human immunodeficiency virus (HIV) was previously considered dispensable, and the HIV polyprotein Gag was studied during viral egress using novel image analysis tools. A nearest-neighbour analysis showed the ESCRT-II protein EAP45 colocalises with Gag similarly to ALIX, a protein well known to be involved in HIV budding. However, upon deletion of EAP45’s N-terminus, its colocalisation with Gag was significantly impaired, highlighting the importance of this EAP45 domain in linking to Gag. Single particle tracking was used to trace the trajectories of EAP45 and Gag in live cells, and an algorithm was developed to visualise the simultaneous motion of two particles; these analyses revealed three types of potential dynamic interaction between EAP45 and Gag. Finally, an open-source instrument to visualise phenotypes from large organs in 3D was developed for the study of chronic obstructive pulmonary disease (COPD) models. The instrument implements Optical Projection Tomography, a technique which can reconstruct cross-sectional slices of a transparent object from its orthographic projections, using off-the- shelf components and novel ImageJ plugins for artefact correction and volume reconstructions. Excised and cleared mouse lungs were imaged in which high order airways can be discerned with 50 μm resolution. The raw lung data, instructions for building the instrument, the free ImageJ plugins, and a detailed software manual are available in an online repository to encourage the widespread use of OPT for imaging large samples.Gates Cambridg

Imaging, Tracking and Computational Analyses of Virus Entry and Egress with the Cytoskeleton

Viruses have a dual nature: particles are “passive substances” lacking chemical energy transformation, whereas infected cells are “active substances” turning-over energy. How passive viral substances convert to active substances, comprising viral replication and assembly compartments has been of intense interest to virologists, cell and molecular biologists and immunologists. Infection starts with virus entry into a susceptible cell and delivers the viral genome to the replication site. This is a multi-step process, and involves the cytoskeleton and associated motor proteins. Likewise, the egress of progeny virus particles from the replication site to the extracellular space is enhanced by the cytoskeleton and associated motor proteins. This overcomes the limitation of thermal diffusion, and transports virions and virion components, often in association with cellular organelles. This review explores how the analysis of viral trajectories informs about mechanisms of infection. We discuss the methodology enabling researchers to visualize single virions in cells by fluorescence imaging and tracking. Virus visualization and tracking are increasingly enhanced by computational analyses of virus trajectories as well as in silico modeling. Combined approaches reveal previously unrecognized features of virus-infected cells. Using select examples of complementary methodology, we highlight the role of actin filaments and microtubules, and their associated motors in virus infections. In-depth studies of single virion dynamics at high temporal and spatial resolutions thereby provide deep insight into virus infection processes, and are a basis for uncovering underlying mechanisms of how cells function

Pollen segmentation and feature evaluation for automatic classification in bright-field microscopy

14 págs.; 10 figs.; 7 tabs.; 1 app.© 2014 Elsevier B.V. Besides the well-established healthy properties of pollen, palynology and apiculture are of extreme importance to avoid hard and fast unbalances in our ecosystems. To support such disciplines computer vision comes to alleviate tedious recognition tasks. In this paper we present an applied study of the state of the art in pattern recognition techniques to describe, analyze, and classify pollen grains in an extensive dataset specifically collected (15 types, 120 samples/type). We also propose a novel contour-inner segmentation of grains, improving 50% of accuracy. In addition to published morphological, statistical, and textural descriptors, we introduce a new descriptor to measure the grain's contour profile and a logGabor implementation not tested before for this purpose. We found a significant improvement for certain combinations of descriptors, providing an overall accuracy above 99%. Finally, some palynological features that are still difficult to be integrated in computer systems are discussed.This work has been supported by the European project APIFRESH FP7-SME-2008-2 ‘‘Developing European standards for bee pollen and royal jelly: quality, safety and authenticity’’ and we would like to thank to Mr. Walter Haefeker, President of the European Professional Beekeepers Association (EPBA). J. Victor Marcos is a ‘‘Juan de la Cierva’’ research fellow funded by the Spanish Ministry of Economy and Competitiveness. Rodrigo Nava thanks Consejo Nacional de Ciencia y Tecnología (CONACYT) and PAPIIT Grant IG100814.Peer Reviewe

Blood flow measurement in the zebrafish heart using light sheet microscopy

The link between haemodynamics and cardiac tissue mechanics is an active area of research in developmental biology. Nevertheless, previous study of fluid-structure interaction in the developing heart was mostly confined to single projection blood flow measurements or computational fluid dynamics simulations using only the information of the heart wall structure. Hence, techniques capable of direct 3D + time resolved blood flow and heart wall motion are necessary to deepen the understanding of the cardiac function in the developing heart. This work presents an imaging system which combines selective plane illumination microscopy (SPIM), with optical gating techniques, and micro particle image velocimetry (uPIV). This combination (referred here as SPIM-uPIV) allowed non-invasively measuring blood flow in the developing zebrafish heart in a depth and time-resolved manner. Our system surpasses conventional uPIV measurement systems based on wide-field illumination which suffer from measurement errors due to volume illumination of the sample. The proposed SPIM-uPIV system was validated in a control microfluidics experiment where flow of fluorescent microspheres was measured in a 50 um diameter tube. Both qualitative and quantitative analysis was performed to compare our SPIM-uPIV against conventional brightfield-uPIV measurements. Furthermore, this work implements a different metric for “cross-correlation” which was empirically found to perform better than the traditional algorithm used in PIV analysis, when motion of large particles is measured. By implementing optical gating techniques to our analysis, 3D + time blood flow measurements in the beating hearts of 3, 4, and 5 day old zebrafish hearts were obtained. The recovered 3D + time velocity information enabled further investigation of the heart function such as the pumping efficiency which was obtained by calculating the flow rate through a section of a heart chamber. In summary, it is proposed that SPIM-uPIV system can be a useful tool for direct bloodflow measurements in transparent small-animal models. Such measurements would benefit the current knowledge of fluid-structure interaction phenomena in the developing heart, and could be used to validate previous work by other group

A high-speed microscopy approach to single-molecule studies of eukaryote signal transduction

Metabolic processes underlie all forms of life. An organism’s ability to utilise chemical energy to stay alive and eventually reproduce is a central feature of life, regardless of organism length scale. To achieve this, an organism must be adaptable. That is, it must be able to adjust to varying surrounding environmental conditions. Cells must be able to sense this environment, ‘transduce’ the signal and bring about some cell level response. Cells respond to external stimuli by releasing chemical cascades along often intricate signalling pathways which regulate cellular function. In this thesis, I have developed a novel optical microscopy system coupled to microfluidics and image analysis tools to help address challenging biological questions relating to metabolic sensing in eukaryotic life, using Saccharomyces cerevisiæ, as a model system. A set of biophysical tools was developed to monitor signal transduction events in live yeast cells. A bespoke optical microscope was developed that can monitor single living cells and determine their response to controlled variations in environmental nutrient concentration at high sampling speeds comparable to the molecular diffusion time scale in a cells internal environment. High-speed imaging at up to 200 frames per second and exposure times of 4.7 ms can be achieved. An electronic gain of 300x makes the camera system sensitive enough to track diffusion of single or small clusters of fluorescent protein molecules under physiological conditions. A high intensity laser excitation system was developed to deliver the light required to follow single fluorescent proteins in the living cells. A bespoke microfluidics system was built wherein cells can be exposed to rapidly changing extracellular environments and make it possible to follow individual cell responses to changing glucose conditions. Image analysis tools were adapted and developed to facilitate the automated measurement of protein mobility, stoichiometry and copy number, one cell at a time

Biological model representation and analysis

In this thesis, we discuss solutions of phenotype description based on the microscopy image analysis to deal with biological problems both in 2D and 3D space. Our description of patterns goes beyond conventional features and helps to visualize the unseen in feature dataset. These solutions share several common processes which are based on similar principles. Furthermore, we notice that advanced features and classier strategies can help us improve the performance of the solutions. The biological problems that we have studied include the endocytosis routing using high-throughput screening in 2D and time and 3D geometrical representation from biological structures.China Scholarship CouncilComputer Systems, Imagery and Medi

Model and learning-based strategies for intensity diffraction tomography

Intensity Diffraction Tomography (IDT) is a recently developed quantitative phase imaging tool with significant potential for biological imaging applications. This modality captures intensity images from a scattering sample under diverse illumination and reconstructs the object's volumetric permittivity contrast using linear inverse scattering models. IDT requires no through-focus sample scans or exogenous contrast agents for 3D object recovery and can be easily implemented with a standard microscope equipped with an off-the-shelf LED array. These factors make IDT ideal for biological research applications where easily implementable setups providing native sample morphological information are highly desirable. Given this modality's recent development, IDT suffers from a number of limitations preventing its widespread adoption: 1) large measurement datasets with long acquisition times limiting its temporal resolution, 2) model-based constraints preventing the evaluation of multiple-scattering samples, and 3) low axial resolution preventing the recovery of fine axial structures such as organelles and other subcellular structures. These factors limit IDT to primarily thin, static objects, and its unknown accuracy and sensitivity metrics cast doubt on the technology's quantitative recovery of morphological features. This thesis addresses the limitations of IDT through advancements provided from model and learning-based strategies. The model-based advancements guide new computational illumination strategies for high volume-rate imaging as well as investigate new imaging geometries, while the learning-based enhancements to IDT present an efficient method for recovering multiple-scattering biological specimens. These advancements place IDT in the optimal position of being an easily implementable, computationally efficient phase imaging modality recovering high-resolution volumes of complex, living biological samples in their native state. We first discuss two illumination strategies for high-speed IDT. The first strategy develops a multiplexed illumination framework based on IDT's linear model enabling hardware-limited 4Hz volume-rate imaging of living biological samples. This implementation is hardware-agnostic, allowing for fast IDT to be added to any existing setup containing programmable illumination hardware. While sacrificing some reconstruction quality, this multiplexed approach recovers high-resolution features in live cell cultures, worms, and embryos highlighting IDT's potential across numerous ranges of biological imaging. Following this illumination scheme, we discuss a hardware-based solution for live sample imaging using ring-geometry LED arrays. Inspired from the linear model, this hardware modification optimally captures the object's information in each LED illumination allowing for high-quality object volumes to be reconstructed from as few as eight intensity images. This small image requirement allows IDT to achieve camera-limited 10Hz volume rate imaging of live biological samples without motion artifacts. We show the capabilities of this annular illumination IDT setup on live worm samples. This low-cost solution for IDT's speed shows huge implications for enabling any biological imaging lab to easily study the form and function of biological samples of interest in their native state. Next, we present a learning-based approach to expand IDT to recovering multiple-scattering samples. IDT's linear model provides efficient computation of an object's 3D volume but fails to recover quantitative information in the presence of highly scattering samples. We introduce a lightweight neural network architecture, trained only on simulated natural image-based objects, that corrects the linear model estimates and improves the recovery of both weakly and strongly scattering samples. This implementation maintains the computational efficiency of IDT while expanding its reconstruction capabilities allowing for more generic imaging of biological samples. Finally, we discuss an investigation of the IDT modality for reflection mode imaging. IDT traditionally captures only low axial resolution information because it cannot capture the backscattered fields from the object that contain rich information regarding the fine details of the object's axial structures. Here, we investigated whether a reflection-mode IDT implementation was possible for recovering high axial resolution structures from this backscattered light. We develop the model, imaging setup, and rigorously evaluate the reflection case in simulation and experiment to show the possibility for reflection IDT. While this imaging geometry ultimately requires a nonlinear model for 3D imaging, we show the technique provides enhanced sensitivity to the object's structures in a complementary fashion to transmission-based IDT

A high-speed microscopy approach to single-molecule studies of eukaryote signal transduction

Metabolic processes underlie all forms of life. An organism’s ability to utilise chemical energy to stay alive and eventually reproduce is a central feature of life, regardless of organism length scale. To achieve this, an organism must be adaptable. That is, it must be able to adjust to varying surrounding environmental conditions. Cells must be able to sense this environment, ‘transduce’ the signal and bring about some cell level response. Cells respond to external stimuli by releasing chemical cascades along often intricate signalling pathways which regulate cellular function. In this thesis, I have developed a novel optical microscopy system coupled to microfluidics and image analysis tools to help address challenging biological questions relating to metabolic sensing in eukaryotic life, using Saccharomyces cerevisiæ, as a model system. A set of biophysical tools was developed to monitor signal transduction events in live yeast cells. A bespoke optical microscope was developed that can monitor single living cells and determine their response to controlled variations in environmental nutrient concentration at high sampling speeds comparable to the molecular diffusion time scale in a cells internal environment. High-speed imaging at up to 200 frames per second and exposure times of 4.7 ms can be achieved. An electronic gain of 300x makes the camera system sensitive enough to track diffusion of single or small clusters of fluorescent protein molecules under physiological conditions. A high intensity laser excitation system was developed to deliver the light required to follow single fluorescent proteins in the living cells. A bespoke microfluidics system was built wherein cells can be exposed to rapidly changing extracellular environments and make it possible to follow individual cell responses to changing glucose conditions. Image analysis tools were adapted and developed to facilitate the automated measurement of protein mobility, stoichiometry and copy number, one cell at a time

Microgel Suspensions for Tissue Engineering and Tumor Models

Human tissues are complex materials with hierarchical organizations of a variety of different cell types and matrix properties. Capturing these properties in vitro has been a chief goal of tissue engineering since its inception. However, full recapitulation of native tissue structures and functions remains unresolved. This thesis explores a new methodology to capture native tissue’s complexity using hydrogel matrices composed of microgel suspensions. In this thesis, I developed a new microgel particle using a water in oil emulsion technique with methacrylated gelatin. The mechanics and size of individual microgels are readily tunable. Packing particles tight enough forms jammed suspensions that enable direct extrusion of the particles as a 3D printing ink. And exposure to purple light photocrosslinks microgels together into annealed cell-laden matrices for long term culture. When jammed, microgels also function as a support bath for 3D printing. To demonstrate the utility of a microgel support bath, I created a model tumor microenvironment to study cancer metastasis. Direct writing of a Pluronic sacrificial ink into a stromal cell-microgel suspension was used to form endothelialized vessel structures. Further 3D printing of melanoma cancers enabled freeform spatial control over tumor architectures and relative distances to vessel structures. Tumor cells were found to migrate into the prototype vessels as a function of distance. I next explored microgel suspensions as a platform for stem cell differentiation. Current efforts to recapitulate native tissue structures using stem cells lack tight spatial control over cell locations and matrix architectures. To address this issue, I first demonstrate how modifications to microgel properties can direct stem cell differentiation. By combining varied microgels together, I created gradients of microgel sizes and stiffness to spatially direct cell lineage using adipose derived stromal cells (ADSCs) as a model stem cell system. Further optimizations of cell printing enabled high spatial control over cell location and differentiation outcomes. As a final demonstration, I created heterogenous matrices of microgels with interspersed or directly printed functional microcapsules. The novel capsule design enabled the highest recorded loading of protein in a microscale volume, accommodating up to 40 mg/mL of biologically active species within a single microcapsule. By adding in enzymes, gas releasing hydrogels, and nanoparticles, I successfully perturbed the local gas concentrations within the matrix. I demonstrate the capsules capacity as a 3D printable ink, enabling spatial control over gradients of gas release to direct secondary messenger signals. The modularity of the system was demonstrated through several potential applications including attenuation of peroxide activity to combat radiation damage, and creating hypoxic cell culture conditions for wound healing and tumor microenvironment mimicry Together, these findings demonstrate the versatility of GelMa microgel suspensions as a tool with unique advantages for biofabrication and scaffolding for tissue engineering. This work has scope across the fields of material science, bioengineering, regenerative medicine, and cancer modeling