Automated deep-phenotyping of the vertebrate brain

Here, we describe an automated platform suitable for large-scale deep-phenotyping of zebrafish mutant lines, which uses optical projection tomography to rapidly image brain-specific gene expression patterns in 3D at cellular resolution. Registration algorithms and correlation analysis are then used to compare 3D expression patterns, to automatically detect all statistically significant alterations in mutants, and to map them onto a brain atlas. Automated deep-phenotyping of a mutation in the master transcriptional regulator fezf2 not only detects all known phenotypes but also uncovers important novel neural deficits that were overlooked in previous studies. In the telencephalon, we show for the first time that fezf2 mutant zebrafish have significant patterning deficits, particularly in glutamatergic populations. Our findings reveal unexpected parallels between fezf2 function in zebrafish and mice, where mutations cause deficits in glutamatergic neurons of the telencephalon-derived neocortex.National Institutes of Health (U.S.) (Director’s Pioneer Award DP1-NS082101)David & Lucile Packard Foundation. Award in Science and EngineeringBroad Institute of MIT and Harvard (SPARC Award)Epilepsy Foundation of America (Postdoctoral Fellowship

Fast Objective Coupled Planar Illumination Microscopy

Among optical imaging techniques light sheet fluorescence microscopy stands out as one of the most attractive for capturing high-speed biological dynamics unfolding in three dimensions. The technique is potentially millions of times faster than point-scanning techniques such as two-photon microscopy. This potential is especially poignant for neuroscience applications due to the fact that interactions between neurons transpire over mere milliseconds within tissue volumes spanning hundreds of cubic microns. However current-generation light sheet microscopes are limited by volume scanning rate and/or camera frame rate. We begin by reviewing the optical principles underlying light sheet fluorescence microscopy and the origin of these rate bottlenecks. We present an analysis leading us to the conclusion that Objective Coupled Planar Illumination (OCPI) microscopy is a particularly promising technique for recording the activity of large populations of neurons at high sampling rate. We then present speed-optimized OCPI microscopy, the first fast light sheet technique to avoid compromising image quality or photon efficiency. We enact two strategies to develop the fast OCPI microscope. First, we devise a set of optimizations that increase the rate of the volume scanning system to 40 Hz for volumes up to 700 microns thick. Second, we introduce Multi-Camera Image Sharing (MCIS), a technique to scale imaging rate by incorporating additional cameras. MCIS can be applied not only to OCPI but to any widefield imaging technique, circumventing the limitations imposed by the camera. Detailed design drawings are included to aid in dissemination to other research groups. We also demonstrate fast calcium imaging of the larval zebrafish brain and find a heartbeat-induced motion artifact. We recommend a new preprocessing step to remove the artifact through filtering. This step requires a minimal sampling rate of 15 Hz, and we expect it to become a standard procedure in zebrafish imaging pipelines. In the last chapter we describe essential computational considerations for controlling a fast OCPI microscope and processing the data that it generates. We introduce a new image processing pipeline developed to maximize computational efficiency when analyzing these multi-terabyte datasets, including a novel calcium imaging deconvolution algorithm. Finally we provide a demonstration of how combined innovations in microscope hardware and software enable inference of predictive relationships between neurons, a promising complement to more conventional correlation-based analyses

Comparative Analysis of Locomotor Behavior and Descending Motor System Anatomy of Larval Zebrafish and Giant Danio

A major challenge for comparative biology is understanding what aspects of an animal’s locomotor repertoire represent general features of motor organization, versus specialized adaptations for its anatomy and ecological niche. In this thesis I investigate the Giant Danio larvae (Devario aequipinnatus) as a potential model for comparative studies with Zebrafish, a well-established animal model in neuroscience. To this end, I study the locomotor behavior of both species and how its differences are reflected in the underlying neural circuit structure. Initially, I compare the anatomy of the descending pathways controlling locomotion in Giant Danio to Zebrafish using retrograde labelling of reticulospinal neurons. I see a striking resemblance of the circuit in both species, with a roughly similar organization and the general division and number of cell clusters being very well conserved. Following, I compare visually guided behaviours in Giant Danio to different Zebrafish strains. Giant Danio show a stronger optomotor response than Zebrafish. The optomotor response of Giant Danio first appear around 4 days post fertilization and can be consistently and reliably evoked. During optomotor tracking Giant Danio show shorter interbout intervals and are able to track motion at higher speeds than Zebrafish. I also observe that the higher manoeuvrability of Giant Danio is also reflected during prey capture. Interestingly, Zebrafish strains derived from more recently wild-caught fish show more robust optomotor behaviour, closer to Giant Danio. Lastly, I demonstrate the suitability of using Giant Danio in a head-restrained preparation with a 3D virtual reality environment. Combined with the potential for comparative approaches with Zebrafish, the faster development, larger neurons, and the rich behavioural repertoire of Giant Danio make it a promising model for neuroscience

Construction and Utilization of Digital Brain Atlases in Larval Zebrafish

Rapid escape responses are critical for predator avoidance in fish. Yet, while short-latency C-start (SLCs) circuitry is well-known (e.g., Mauthner and related cells), neurons integral to long-latency C-starts (LLCs) remain uncharacterized. In this dissertation, I identify neurons critical for LLC through the genetic and laser ablations of neurons in transgenic lines. Although transgenic lines provide powerful tools for implicating neurons in behavior, they suffer a number of limitations. Transgene expression is frequently broad, incompletely mapped, or off-target, making it difficult to accurately compare en masse or to other modalities. I addressed this by designing a UAS reporter that suppresses off-target expression through microRNA binding and building a digital atlas from hundreds of transgenic zebrafish lines. By co-imaging and registering lines with a broadly expressed structural marker, the Zebrafish Brain Browser aligns expression to within approximately one cell diameter allowing rapid and accurate comparison of expression, identification of transgenes, and prediction of genetic overlap in almost any set of cells in the larval zebrafish brain. Other modalities (e.g., neural activity and anatomic segmentation) were also incorporated from Z-Brain, another popular zebrafish brain atlas, by a novel multichannel secondary registration. Together, this work increases the fidelity, interoperability, and accessibility of brain atlases and provides a powerful platform for the dissection of neural circuits in larval zebrafish. Using these tools to design and analyze genetic ablations, I performed a 'circuit-breaking' screen to identify neurons underlying LLC behavior. Three of the screened lines reduced LLC probability by >50%. These lines labeled two shared cell clusters: one adjacent to the locus coeruleus (LC) and another in the dorsal hindbrain. Through laser ablation and optogenetic stimulation, LC-adjacent neurons were shown to be both necessary and sufficient for LLC startle. Projections of individual LC-adjacent neurons were characterized by a novel genetic intersection approach. These neurons were strikingly homogeneous, projecting bilaterally to midbrain and hindbrain structures. From this work, I hypothesize that ipsilateral hindbrain projections activate premotor neurons, while contralateral neurites subserve reciprocal inhibition. For the first time, I have identified a core component of the circuit mediating long-latency C-starts, an ethologically important behavior in zebrafish

Neuronal circuits underlying visual attention during naturalistic behaviour in zebrafish larvae

To survive, animals need to sustain behavioural responses towards specific environmental stimuli to achieve an overall goal. One example is the hunting behaviour of zebrafish larvae, which is characterised by a set of discrete visuomotor events that begin with prey detection, followed by target-directed swims and end with prey capture. Several studies have begun elucidating the neuronal circuits that govern prey detection and initiation of hunting routines, which are largely dependent on the midbrain optic tectum (OT). However, it is not known how the brain is able to sustain a behavioural routine directed towards a specific target, especially in complex environments containing distractors. In this study, I have discovered that the nucleus isthmus (NI), a midbrain nucleus implicated in visual attention in other vertebrates, is required for sustained tracking of prey during hunting routines in zebrafish larvae. NI neurons co-express cholinergic and glutamatergic markers and possess two types of axonal projection morphology. The first type targets the ipsilateral OT and AF7, a retinorecipient pretectal region involved in hunting. The second type projects bilaterally to the deep OT layers. Laser ablation of the NI followed by tracking of naturalistic hunting behaviour, revealed that while hunting initiation rates and motor kinematics were unaltered, ablated animals showed an elevated probability of aborting hunting routines midway. Moreover, 2-photon calcium imaging of tethered larvae during a closed-loop virtual reality hunting assay, showed that NI neurons are specifically active during hunting. These results suggest that the NI supports the maintenance of action sequences towards specific prey targets during hunting, most likely by modulating pretectal and tectal activity. This in turn supports its presence at the centre of an evolutionarily conserved circuit to control selective attention to ethologically relevant stimuli in the presence of competing distractors

Image analysis platforms for exploring genetic and neuronal mechanisms regulating animal behavior

An important aim of neuroscience is to understand how gene interactions and neuronal networks regulate animal behavior. The larvae of the marine annelid Platynereis dumerilii provide a convenient system for such integrative studies. These larvae exhibit a wide range of behaviors, including phototaxis, chemotaxis and gravitaxis and at the same time exhibit relatively simple nervous system organization. Due to its small size and transparent body, the Platynereis larva is compatible with whole-body light microscopic imaging following tissue staining protocols. It is also suitable for serial electron microscopic imaging and subsequent neuronal connectome reconstruction. Despite advances in imaging techniques, automated computational tools for large data analysis are not well-established in Platynereis. In the current work, I developed image analysis software for exploring genetic and nervous system mechanisms modulating Platynereis behavior. Exploring gene expression patterns Current labeling and imaging techniques restrict the number of gene expression patterns that can be labelled and visualized in a single specimen, which hinders the study of behaviors driven by multi-molecular interactions. To address this problem, I employed image registration to generate a gene expression atlas that integrates gene expression information from multiple specimens in a common reference space. The gene expression atlas was used to investigate mechanisms regulating larval locomotion, settlement and phototaxis in Platynereis. The atlas can assist in the identification of inter-individual and inter-species variations in gene expression. To provide a representation convenient for exploring gene expression patterns, I created a model of the atlas using 3D graphics software, which enabled convenient data visualization and efficient data storage and sharing. Exploring neuronal networks regulating behavior Neuronal circuitry can be reconstructed from the images obtained from electron microscopy, which resolves very fine structures such as neuron morphology or synapses. The amount of data resulting from electron microscopy and the complexity of neuronal networks represent a significant challenge for manual analysis. To solve this problem, I developed the NeuroDetective software, which models a neuronal circuitry and analyzes the information flow within it. The software combines the advantages of 3D visualization and graph analysis software by integrating neuron morphology and spatial distribution together with synaptic connectivity. NeuroDetective allowed studying the neuronal circuitry responsible for phototaxis in Platynereis larvae, revealing the connections and the neurons important for the network functionality. NeuroDetective facilitated the establishment of a relationship between the function and the structure of the neuronal circuitry in Platynereis phototaxis. Integrating gene expression patterns with neuronal connectivity Neuronal circuitry and its associated modulating biomolecules, such as neurotransmitters and neuropeptides, are thought to be the main factors regulating animal behavior. Therefore it was important to integrate both genetic and neuronal information in order to fully understand how biomolecules in conjunction with neuronal anatomy elicit certain animal behavior. To resolve the difference in specimen preparation for gene expression versus electron microscopy preparations, I developed an image registration procedure to match the signals from these two different datasets. This method enabled the integration the spatial distribution of specific modulators into the analysis of neuronal networks, leading to an improved understanding of the genetic and neuronal mechanisms modulating behavior in Platynereis

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

Enhanced characterization of the zebrafish brain as revealed by super-resolution track-density imaging

In this study, we explored the use of super-resolution track-density imaging (TDI) for neuroanatomical characterization of the adult zebrafish brain. We compared the quality of image contrast and resolution obtained with T-2* magnetic resonance imaging (MRI), diffusion tensor-based imaging (DTI), TDI, and histology. The anatomical structures visualized in 5 mu m TDI maps corresponded with histology. Moreover, the super-resolution property and the local-directional information provided by directionally encoded color TDI facilitated delineation of a larger number of brain regions, commissures and small white matter tracks when compared to conventional MRI and DTI. In total, we were able to visualize 17 structures that were previously unidentifiable using MR microimaging, such as the four layers of the optic tectum. This study demonstrates the use of TDI for characterization of the adult zebrafish brain as a pivotal tool for future phenotypic examination of transgenic models of neurological diseases