ZeVis: A Visual Analytics System for Exploration of a Larval Zebrafish Brain in Serial-Section Electron Microscopy Images

The automation and improvement of nano-scale electron microscopy imaging technologies have expanded a push in neuroscience to understand brain circuits at the scale of individual cells and their connections. Most of this research effort, called 'connectomics', has been devoted to handling, processing, and segmenting large-scale image data to reconstruct graphs of neuronal connectivity. However, connectomics datasets contain a wealth of high-resolution information about the brain that could be leveraged to understand its detailed anatomy beyond just the connections between neurons, such as cell morphologies and distributions. This study introduces a novel visualization system, ZeVis, for the interactive exploration of a whole larval zebrafish brain using a terabyte-scale serial-section electron microscopy dataset. ZeVis combines 2D cross-sectional views and 3D volumetric visualizations of the input serial-section electron microscopy data with overlaid segmentation results to facilitate the analyses of various brain structures and their interpretations. The system also provides a graph-based data processing interface to generate subsets of feature segmentation data easily. The segmentation data can be filtered by morphological features or anatomical constraints, allowing statistical analysis and comparisons across regions. We applied ZeVis to actual data of a terabyte-scale whole-brain larval zebrafish and analyzed cell nucleus distributions in several anatomical regions

Reconstruction of neuronal activity and connectivity patterns in the zebrafish olfactory bulb

In the olfactory bulb (OB), odors evoke distributed patterns of activity across glomeruli that are reorganized by networks of interneurons (INs). This reorganization results in multiple computations including a decorrelation of activity patterns across the output neurons, the mitral cells (MCs). To understand the mechanistic basis of these computations it is essential to analyze the relationship between function and structure of the underlying circuit. I combined in vivo twophoton calcium imaging with dense circuit reconstruction from complete serial block-face electron microscopy (SBEM) stacks of the larval zebrafish OB (4.5 dpf) with a voxel size of 9x9x25nm. To address bottlenecks in the workflow of SBEM, I developed a novel embedding and staining procedure that effectively reduces surface charging in SBEM and enables to acquire SBEM stacks with at least a ten-fold increase in both, signal-to-noise as well as acquisition speed. I set up a high throughput neuron reconstruction pipeline with >30 professional tracers that is available for the scientific community (ariadne-service.com). To assure efficient and accurate circuit reconstruction, I developed PyKNOSSOS, a Python software for skeleton tracing and synapse annotation, and CORE, a skeleton consolidation procedure that combines redundant reconstruction with targeted expert input. Using these procedures I reconstructed all neurons (>1000) in the larval OB. Unlike in the adult OB, INs were rare and appeared to represent specific subtypes, indicating that different sub-circuits develop sequentially. MCs were uniglomerular whereas inter-glomerular projections of INs were complex and biased towards groups of glomeruli that receive input from common types of sensory neurons. Hence, the IN network in the OB exhibits a topological organization that is governed by glomerular identity. Calcium imaging revealed that the larval OB circuitry already decorrelates activity patterns evoked by similar odors. The comparison of inter-glomerular connectivity to the functional interactions between glomeruli indicates that pattern decorrelation depends on specific, non-random inter-glomerular IN projections. Hence, the topology of IN networks in the OB appears to be an important determinant of circuit function

Synaptic Cleft Segmentation in Non-Isotropic Volume Electron Microscopy of the Complete Drosophila Brain

Neural circuit reconstruction at single synapse resolution is increasingly recognized as crucially important to decipher the function of biological nervous systems. Volume electron microscopy in serial transmission or scanning mode has been demonstrated to provide the necessary resolution to segment or trace all neurites and to annotate all synaptic connections. Automatic annotation of synaptic connections has been done successfully in near isotropic electron microscopy of vertebrate model organisms. Results on non-isotropic data in insect models, however, are not yet on par with human annotation. We designed a new 3D-U-Net architecture to optimally represent isotropic fields of view in non-isotropic data. We used regression on a signed distance transform of manually annotated synaptic clefts of the CREMI challenge dataset to train this model and observed significant improvement over the state of the art. We developed open source software for optimized parallel prediction on very large volumetric datasets and applied our model to predict synaptic clefts in a 50 tera-voxels dataset of the complete Drosophila brain. Our model generalizes well to areas far away from where training data was available

Danionella translucida, ein transparenter und genetisch manipulierbarer Modelorganismus mit komplexem Verhalten zum Studium des Vertebraten-Gehirns

Understanding how the brain orchestrates behaviours is a major objective in systems neuroscience. This quest involves accomplishing the following tasks: First, to characterise the behaviour of interest. Second, to identify the neurons and their networks responsible for the behaviour. Third, to study the computations performed by these neurons and fourth, to reveal the underlying mechanisms. As of yet, tackling all of these steps in adult vertebrates has been very challenging due to the size and opacity of their brains. Molecular component of cells, especially lipids and proteins, have light scattering properties and prevent excitation and retrieval of fluorescent signals in deeper brain areas. As a result, only limited optical access can be achieved using microscopy techniques in adult vertebrate brains. In this thesis I introduce a freshwater teleost fish, Danionella translucida (DT), as a new laboratory species. Unlike other vertebrates, it remains small and transparent throughout adulthood, with a majority of its cells accessible to optical recording techniques. Furthermore, DT shows rich social behaviours e.g. sexual behaviour, shoaling, schooling, fighting and, remarkably, vocalisation. This thesis focuses on foundational experiments to establish DT as a new model organism for systems neuroscience. First, I characterise essentials of DT behaviour, in particular its ability to vocalise. Second, I demonstrate genetic tractability to tailor DT for anatomical and functional circuit studies using Tol2-mediated gene insertion of a calcium-sensor and Crispr/Cas9-targeted gene editing for depigmentation. Third, I implement a proof of-principle experiment to show that circuit functionality during sensory stimulation can be tested in the immobilised transgenic animal using two-photon calcium imaging. DT’s optical features combined with rich behaviour and genetic amenability open the way to investigate the underlying mechanisms for neural computations performed by single cells. Hence, establishing DT as a new model organism throughout this thesis enables targeting the fourth and ultimate goal of systems neuroscience in the adult vertebrate.Im Forschungsbereich systemische Neurowissenschaften ist eine der grossen Herausforderung zu verstehen, wie das Gehirn Verhalten dirigiert. Dieses Ziel erfordert vier Schritte beginnend mit dem Charakterisieren eines interessanten Verhaltens. Zweitens, müssen dazu entsprechend relevante Neurone und neuronale Netzwerke identifizieren werden. Drittens gilt es die Verrechnungen innerhalb beteiligter Neurone zu studieren und letztlich die dahinter steckenden Mechanismen zu erkennen. Durch die Grösse und Undurchsichtigkeit von Gehirnen adulter Wirbeltiere war es bis dato unmöglich all diese Ziele gemeinsam in einem Modell zu studieren. Zellulaere Bestandteile, insbesondere Lipide und Proteine, haben lichtstreuende Eigenschaften und verhindern das Anregen und Messen von Fluoreszenzsignalen in tieferen Bereichen des Gehirns. Als Folge koennen nur sehr begrenzte Ausschnitte des erwachsenen Wirbeltiergehirns optisch untersucht werden. In dieser Doktorarbeit etabliere ich einen neuen Modelorganismus - den teleosten Süsswasserfisch Danionella translucida (DT). Anders als die meisten Vertebraten bleibt die DT auch während erwachsener Entwicklungsstadien klein und transparent, welches die Mehrheit ihrer Neurone optischen Methoden zugänglich macht. Desweiteren zeigt die DT komplexe Verhalten wie Fortpflanzungsverhalten, koordiniertes Schwimmen in der Gruppe, Kampfverhalten und beachtlicherweise Vokalisierungsverhalten. Ziel dieser Arbeit war es grundlegende Experimente durchzufuehren, um die DT als neuen Modelorganismus für systemische Neurowissenschaften zu etablieren. Dazu charakterisiere ich als Erstes die Grundzüge verschiedener Verhalten mit Schwerpunkt auf dem Vokalisierungsverhalten. Zweitens zeige ich, dass die DT genetisch manipulierbar ist, um sie für optische Studien neuronaler Netzwerkanatomie und -funktionalität anzupassen. Dazu inseriere ich mit Tol2-Transgenese einen Kalziumsensor in das Genom der DT und unterbinde mit Crispr/Cas9 ihre Pigmentierung durch Genveränderung des Enzyms Tyrosinase. Drittens, demonstriere ich in einem proof-of-principle Experiment am transgenen Tier, dass die DT sich während sensorischer Stimulierung unter dem Zwei-photonen Mikroskop auf Aktivitätseigenschaften in einzelnen Zellen innerhalb neuronaler Netzwerke untersuchen lässt. Die genetisch veränderbare DT eignet sich durch ihre optischen Eigenschaften und ihr komplex ausgebildetes Verhalten sehr gut zur Untersuchung neuronaler Netzwerke und der mechanistischen Verarbeitung innerhalb individueller Zellen. Damit trägt das Etablieren der DT als neuen Modelorganismus innerhalb dieser Arbeit direkt zur Adressierung der vierten Fragestellung systemischer Neurowissenschaften bei

Monosynaptic targets of utricular afferents in the larval zebrafish

The larval zebrafish acquires a repertoire of vestibular-driven behaviors that aid survival early in development. These behaviors rely mostly on the utricular otolith, which senses inertial (tilt and translational) head movements. We previously characterized the known central brainstem targets of utricular afferents using serial-section electron microscopy of a larval zebrafish brain. Here we describe the rest of the central targets of utricular afferents, focusing on the neurons whose identities are less certain in our dataset. We find that central neurons with commissural projections have a wide range of predicted directional tuning, just as in other vertebrates. In addition, somata of central neurons with inferred responses to contralateral tilt are located more laterally than those with inferred responses to ipsilateral tilt. Many dorsally located central utricular neurons are unipolar, with an ipsilateral dendritic ramification and commissurally projecting axon emerging from a shared process. Ventrally located central utricular neurons tended to receive otolith afferent synaptic input at a shorter distance from the soma than in dorsally located neurons. Finally, we observe an unexpected synaptic target of utricular afferents: afferents from the medial (horizontal) semicircular canal. Collectively, these data provide a better picture of the gravity-sensing circuit. Furthermore, we suggest that vestibular circuits important for survival behaviors develop first, followed by the circuits that refine these behaviors

Development of a rod photoreceptor mosaic revealed in transgenic zebrafish

AbstractThe number and distribution of neurons within the vertebrate retina are tightly regulated. This is particularly apparent in the highly ordered, crystalline-like arrangement of the cone photoreceptors in the teleost. In this report, using a transgenic line of zebrafish, a novel and developmentally regulated mosaic pattern of the rod photoreceptors is described. The spatial and temporal expression of EGFP, under the control of the Xenopus rhodopsin gene promoter, was nearly identical to the endogenous rhodopsin. EGFP was first detected in the ventral nasal retinal in an area of precocious neurogenesis referred to as the “ventral patch”. Subsequent expression of EGFP was observed in isolated cells sporadically distributed across the dorsal and central retina. However, confocal microscopy and spatial analysis of larval eyes or retinal explants from adults revealed a precise arrangement to the rod photoreceptors. The rod terminals were arranged in regularly spaced rows with clearly identifiable telodendria linking neighboring cells. The rod inner segments projected through the cone mosaic in a predictable pattern. In the adult, the rod mosaic originated near the retinal margin where clusters of rods differentiated around the immature short single cone. In the embryo, the sporadic differentiation of the rods led to the gradual formation of the mosaic pattern. With the growing interest in neuronal stem cells, revisiting this model of neurogenesis provides an avenue to uncover mechanisms underlying the precise integration of new neuronal elements into a preexisting neural network

Circuit Neuroscience in Zebrafish

A central goal of modern neuroscience is to obtain a mechanistic understanding of higher brain functions under healthy and diseased conditions. Addressing this challenge requires rigorous experimental and theoretical analysis of neuronal circuits. Recent advances in optogenetics, high-resolution in vivo imaging, and reconstructions of synaptic wiring diagrams have created new opportunities to achieve this goal. To fully harness these methods, model organisms should allow for a combination of genetic and neurophysiological approaches in vivo. Moreover, the brain should be small in terms of neuron numbers and physical size. A promising vertebrate organism is the zebrafish because it is small, it is transparent at larval stages and it offers a wide range of genetic tools and advantages for neurophysiological approaches. Recent studies have highlighted the potential of zebrafish for exhaustive measurements of neuronal activity patterns, for manipulations of defined cell types in vivo and for studies of causal relationships between circuit function and behavior. In this article, we summarize background information on the zebrafish as a model in modern systems neuroscience and discuss recent results

Methods for Mapping Neuronal Activity to Synaptic Connectivity: Lessons From Larval Zebrafish

For a mechanistic understanding of neuronal circuits in the brain, a detailed description of information flow is necessary. Thereby it is crucial to link neuron function to the underlying circuit structure. Multiphoton calcium imaging is the standard technique to record the activity of hundreds of neurons simultaneously. Similarly, recent advances in high-throughput electron microscopy techniques allow for the reconstruction of synaptic resolution wiring diagrams. These two methods can be combined to study both function and structure in the same specimen. Due to its small size and optical transparency, the larval zebrafish brain is one of the very few vertebrate systems where both, activity and connectivity of all neurons from entire, anatomically defined brain regions, can be analyzed. Here, we describe different methods and the tools required for combining multiphoton microscopy with dense circuit reconstruction from electron microscopy stacks of entire brain regions in the larval zebrafish

Integrated Array Tomography for 3D Correlative Light and Electron Microscopy

Volume electron microscopy (EM) of biological systems has grown exponentially in recent years due to innovative large-scale imaging approaches. As a standalone imaging method, however, large-scale EM typically has two major limitations: slow rates of acquisition and the difficulty to provide targeted biological information. We developed a 3D image acquisition and reconstruction pipeline that overcomes both of these limitations by using a widefield fluorescence microscope integrated inside of a scanning electron microscope. The workflow consists of acquiring large field of view fluorescence microscopy (FM) images, which guide to regions of interest for successive EM (integrated correlative light and electron microscopy). High precision EM-FM overlay is achieved using cathodoluminescent markers. We conduct a proof-of-concept of our integrated workflow on immunolabelled serial sections of tissues. Acquisitions are limited to regions containing biological targets, expediting total acquisition times and reducing the burden of excess data by tens or hundreds of GBs

Integrated Array Tomography for 3D Correlative Light and Electron Microscopy

Volume electron microscopy (EM) of biological systems has grown exponentially in recent years due to innovative large-scale imaging approaches. As a standalone imaging method, however, large-scale EM typically has two major limitations: slow rates of acquisition and the difficulty to provide targeted biological information. We developed a 3D image acquisition and reconstruction pipeline that overcomes both of these limitations by using a widefield fluorescence microscope integrated inside of a scanning electron microscope. The workflow consists of acquiring large field of view fluorescence microscopy (FM) images, which guide to regions of interest for successive EM (integrated correlative light and electron microscopy). High precision EM-FM overlay is achieved using cathodoluminescent markers. We conduct a proof-of-concept of our integrated workflow on immunolabelled serial sections of tissues. Acquisitions are limited to regions containing biological targets, expediting total acquisition times and reducing the burden of excess data by tens or hundreds of GBs.</p