A principal skeleton algorithm for standardizing confocal images of fruit fly nervous systems

Motivation: The fruit fly (Drosophila melanogaster) is a commonly used model organism in biology. We are currently building a 3D digital atlas of the fruit fly larval nervous system (LNS) based on a large collection of fly larva GAL4 lines, each of which targets a subset of neurons. To achieve such a goal, we need to automatically align a number of high-resolution confocal image stacks of these GAL4 lines. One commonly employed strategy in image pattern registration is to first globally align images using an affine transform, followed by local non-linear warping. Unfortunately, the spatially articulated and often twisted LNS makes it difficult to globally align the images directly using the affine method. In a parallel project to build a 3D digital map of the adult fly ventral nerve cord (VNC), we are confronted with a similar problem

Quantification of Morphogen Gradients and Patterning Scale Invariance along Dorsal-Ventral Embryonic Axis

Morphogen gradients provide positional information to underlying cells that translate the information into differential gene expression and eventually different cell fates. Scale invariance is the property where the gradients of the morphogen adjust proportionately to the size of the domain. Scale invariance of morphogen gradients or patterns of differentiation is a common phenomenon observed between individuals within the same species and between homologous tissues or structures in different species. To determine whether a pattern is scale invariant, we and others developed definitions and measurements of gradient scaling. These include point-wise and global scaling errors as well as global scaling power. Furthermore, there are several mathematical conditions for scale invariance of advection-diffusion-reaction models that inform mechanisms of scaling. Herein we provide a deeper perspective on modeling and measurement of scale-invariance of morphogen gradients. Scale invariance of DV patterning has been investigated in invertebrates but remains poorly-understood in vertebrates. In both vertebrates and invertebrates, spatial patterning progression along Dorsal-ventral (DV) embryonic axis depends on a morphogen gradient of Bone Morphogenetic Protein (BMP) signaling. Here, we introduce a method for studying DV patterning scale invariance by precisely altering the size of zebrafish embryos by reducing vegetal yolk. Use of this method in scaling experiments indicated that the degree of scaling for intraspecies scaling within zebrafish is greater than that between Danioninae species. Specifically, through analysis of experimentally re-sized embryos, we determined that DV patterning and its underlying morphogen gradients are scale invariant within species of zebrafish. We then extended our study to investigate DV patterning between Danioninae species (zebrafish and giant danio) and found that morphogen gradients do not scale between Danioninae species. In the process of developing tools to quantify morphogen gradients from fluorescent images, we created a novel method to match points in two partially overlapping images. Point cloud data sets, or simply point clouds (PCs), originating from a common specimen but containing different measurement parameters (i.e. using different sensors, times, depths, viewpoints, etc.) usually contain both overlapping and non-overlapping points. Registration aligns these distinct PCs into one coordinate system by assigning point-bypoint correspondence between PCs and applying a transformation. Registration shows great potential for practical applications, but the effectiveness of current methods is limited in PCs having large differences in relative initial positions, low overlapping ratios, and excessive noise. We introduce a point matching algorithm called Signature that relaxes these constraints. We approach the problem of identifying corresponding points between PCs by assigning and matching point identification (ID), or the distance of a point to a select number of closest points in the same PC. Signature has been tested on both computationally generated images and experimentally generated images from confocal microscopy of biological samples. Signature accurately identifies point correspondence in PCs with any initial angles, with overlapping ratios as low as 15%, and shows some improvement in aligning noisy PCs. Preprocessing with Signature also intelligently relaxes point-wise registration of initial point positions. Furthermore, combining Signature with Anchor Point Alignment allows for robust alignment of noise-free PCs under any initial position

Morphological diversity of single neurons in molecularly defined cell types.

Dendritic and axonal morphology reflects the input and output of neurons and is a defining feature of neuronal types1,2, yet our knowledge of its diversity remains limited. Here, to systematically examine complete single-neuron morphologies on a brain-wide scale, we established a pipeline encompassing sparse labelling, whole-brain imaging, reconstruction, registration and analysis. We fully reconstructed 1,741 neurons from cortex, claustrum, thalamus, striatum and other brain regions in mice. We identified 11 major projection neuron types with distinct morphological features and corresponding transcriptomic identities. Extensive projectional diversity was found within each of these major types, on the basis of which some types were clustered into more refined subtypes. This diversity follows a set of generalizable principles that govern long-range axonal projections at different levels, including molecular correspondence, divergent or convergent projection, axon termination pattern, regional specificity, topography, and individual cell variability. Although clear concordance with transcriptomic profiles is evident at the level of major projection type, fine-grained morphological diversity often does not readily correlate with transcriptomic subtypes derived from unsupervised clustering, highlighting the need for single-cell cross-modality studies. Overall, our study demonstrates the crucial need for quantitative description of complete single-cell anatomy in cell-type classification, as single-cell morphological diversity reveals a plethora of ways in which different cell types and their individual members may contribute to the configuration and function of their respective circuits

Cytoskeletal Mechanics and Mobility in the Axons of Sensory Neurons

The axon is a long specialized signaling projection of neurons, whose cytoskeleton is composed of networks of microtubules and actin filaments. The dynamic nature of these networks and the action of their associated motor and cross-linking proteins drives axonal growth. Understanding the mechanisms that control these processes is vitally important to neuroregenerative medicine and in this dissertation, evidence will be presented to support a model of interconnectivity between actin and microtubules in the axons of rat sensory neurons. First, the movement of GFP-actin was evaluated during unimpeded axonal outgrowth and a novel transport mechanism was discovered. Most other cargoes in the axon are actively moved by kinesin and dynein motor proteins along stationary microtubules, or are moved along actin filaments by myosin motor proteins. Actin, however, appears to be collected into short-lived bundles that are either actively carried as cargoes along other actin filaments, or are moved as passive cargoes on short mobile microtubules. Additionally, in response to an applied stretch, the axon does not behave as a uniform visco-elastic solid but rather exhibits local heterogeneity, both in the instantaneous response to stretch and in the remodeling which follows. After stretch, heterogeneity was observed in both the realized strain and long term reorganization along the length of the axon suggesting local variation in the distribution and connectivity of the cytoskeleton. This supports a model of stretch response in which sliding filaments dynamically break and reform connections within and between the actin and microtubule networks. Taken together, these two studies provide evidence for the mechanical and functional connectivity between actin and microtubules in the axonal cytoskeleton and suggest a far more important role for actin in the development of the peripheral nervous system. Moreover this provides a biological framework for the exploration of future regenerative therapies

Computational methods to create and analyze a digital gene expression atlas of embryo development from microscopy images

Abstract The creation of atlases, or digital models where information from different subjects can be combined, is a field of increasing interest in biomedical imaging. When a single image does not contain enough information to appropriately describe the organism under study, it is then necessary to acquire images of several individuals, each of them containing complementary data with respect to the rest of the components in the cohort. This approach allows creating digital prototypes, ranging from anatomical atlases of human patients and organs, obtained for instance from Magnetic Resonance Imaging, to gene expression cartographies of embryo development, typically achieved from Light Microscopy. Within such context, in this PhD Thesis we propose, develop and validate new dedicated image processing methodologies that, based on image registration techniques, bring information from multiple individuals into alignment within a single digital atlas model. We also elaborate a dedicated software visualization platform to explore the resulting wealth of multi-dimensional data and novel analysis algo-rithms to automatically mine the generated resource in search of bio¬logical insights. In particular, this work focuses on gene expression data from developing zebrafish embryos imaged at the cellular resolution level with Two-Photon Laser Scanning Microscopy. Disposing of quantitative measurements relating multiple gene expressions to cell position and their evolution in time is a fundamental prerequisite to understand embryogenesis multi-scale processes. However, the number of gene expressions that can be simultaneously stained in one acquisition is limited due to optical and labeling constraints. These limitations motivate the implementation of atlasing strategies that can recreate a virtual gene expression multiplex. The developed computational tools have been tested in two different scenarios. The first one is the early zebrafish embryogenesis where the resulting atlas constitutes a link between the phenotype and the genotype at the cellular level. The second one is the late zebrafish brain where the resulting atlas allows studies relating gene expression to brain regionalization and neurogenesis. The proposed computational frameworks have been adapted to the requirements of both scenarios, such as the integration of partial views of the embryo into a whole embryo model with cellular resolution or the registration of anatom¬ical traits with deformable transformation models non-dependent on any specific labeling. The software implementation of the atlas generation tool (Match-IT) and the visualization platform (Atlas-IT) together with the gene expression atlas resources developed in this Thesis are to be made freely available to the scientific community. Lastly, a novel proof-of-concept experiment integrates for the first time 3D gene expression atlas resources with cell lineages extracted from live embryos, opening up the door to correlate genetic and cellular spatio-temporal dynamics. La creación de atlas, o modelos digitales, donde la información de distintos sujetos puede ser combinada, es un campo de creciente interés en imagen biomédica. Cuando una sola imagen no contiene suficientes datos como para describir apropiadamente el organismo objeto de estudio, se hace necesario adquirir imágenes de varios individuos, cada una de las cuales contiene información complementaria respecto al resto de componentes del grupo. De este modo, es posible crear prototipos digitales, que pueden ir desde atlas anatómicos de órganos y pacientes humanos, adquiridos por ejemplo mediante Resonancia Magnética, hasta cartografías de la expresión genética del desarrollo de embrionario, típicamente adquiridas mediante Microscopía Optica. Dentro de este contexto, en esta Tesis Doctoral se introducen, desarrollan y validan nuevos métodos de procesado de imagen que, basándose en técnicas de registro de imagen, son capaces de alinear imágenes y datos provenientes de múltiples individuos en un solo atlas digital. Además, se ha elaborado una plataforma de visualization específicamente diseñada para explorar la gran cantidad de datos, caracterizados por su multi-dimensionalidad, que resulta de estos métodos. Asimismo, se han propuesto novedosos algoritmos de análisis y minería de datos que permiten inspeccionar automáticamente los atlas generados en busca de conclusiones biológicas significativas. En particular, este trabajo se centra en datos de expresión genética del desarrollo embrionario del pez cebra, adquiridos mediante Microscopía dos fotones con resolución celular. Disponer de medidas cuantitativas que relacionen estas expresiones genéticas con las posiciones celulares y su evolución en el tiempo es un prerrequisito fundamental para comprender los procesos multi-escala característicos de la morfogénesis. Sin embargo, el número de expresiones genéticos que pueden ser simultáneamente etiquetados en una sola adquisición es reducido debido a limitaciones tanto ópticas como del etiquetado. Estas limitaciones requieren la implementación de estrategias de creación de atlas que puedan recrear un multiplexado virtual de expresiones genéticas. Las herramientas computacionales desarrolladas han sido validadas en dos escenarios distintos. El primer escenario es el desarrollo embrionario temprano del pez cebra, donde el atlas resultante permite constituir un vínculo, a nivel celular, entre el fenotipo y el genotipo de este organismo modelo. El segundo escenario corresponde a estadios tardíos del desarrollo del cerebro del pez cebra, donde el atlas resultante permite relacionar expresiones genéticas con la regionalización del cerebro y la formación de neuronas. La plataforma computacional desarrollada ha sido adaptada a los requisitos y retos planteados en ambos escenarios, como la integración, a resolución celular, de vistas parciales dentro de un modelo consistente en un embrión completo, o el alineamiento entre estructuras de referencia anatómica equivalentes, logrado mediante el uso de modelos de transformación deformables que no requieren ningún marcador específico. Está previsto poner a disposición de la comunidad científica tanto la herramienta de generación de atlas (Match-IT), como su plataforma de visualización (Atlas-IT), así como las bases de datos de expresión genética creadas a partir de estas herramientas. Por último, dentro de la presente Tesis Doctoral, se ha incluido una prueba conceptual innovadora que permite integrar los mencionados atlas de expresión genética tridimensionales dentro del linaje celular extraído de una adquisición in vivo de un embrión. Esta prueba conceptual abre la puerta a la posibilidad de correlar, por primera vez, las dinámicas espacio-temporales de genes y células