Accessible software frameworks for reproducible image analysis of host-pathogen interactions

Um die Mechanismen hinter lebensgefährlichen Krankheiten zu verstehen, müssen die zugrundeliegenden Interaktionen zwischen den Wirtszellen und krankheitserregenden Mikroorganismen bekannt sein. Die kontinuierlichen Verbesserungen in bildgebenden Verfahren und Computertechnologien ermöglichen die Anwendung von Methoden aus der bildbasierten Systembiologie, welche moderne Computeralgorithmen benutzt um das Verhalten von Zellen, Geweben oder ganzen Organen präzise zu messen. Um den Standards des digitalen Managements von Forschungsdaten zu genügen, müssen Algorithmen den FAIR-Prinzipien (Findability, Accessibility, Interoperability, and Reusability) entsprechen und zur Verbreitung ebenjener in der wissenschaftlichen Gemeinschaft beitragen. Dies ist insbesondere wichtig für interdisziplinäre Teams bestehend aus Experimentatoren und Informatikern, in denen Computerprogramme zur Verbesserung der Kommunikation und schnellerer Adaption von neuen Technologien beitragen können. In dieser Arbeit wurden daher Software-Frameworks entwickelt, welche dazu beitragen die FAIR-Prinzipien durch die Entwicklung von standardisierten, reproduzierbaren, hochperformanten, und leicht zugänglichen Softwarepaketen zur Quantifizierung von Interaktionen in biologischen System zu verbreiten. Zusammenfassend zeigt diese Arbeit wie Software-Frameworks zu der Charakterisierung von Interaktionen zwischen Wirtszellen und Pathogenen beitragen können, indem der Entwurf und die Anwendung von quantitativen und FAIR-kompatiblen Bildanalyseprogrammen vereinfacht werden. Diese Verbesserungen erleichtern zukünftige Kollaborationen mit Lebenswissenschaftlern und Medizinern, was nach dem Prinzip der bildbasierten Systembiologie zur Entwicklung von neuen Experimenten, Bildgebungsverfahren, Algorithmen, und Computermodellen führen wird

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

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

Scalable image analysis for quantitative microscopy

Seit der Erfindung des Mikroskops haben mikroskopische Bilder zu neuen Erkenntnissen in der biomedizinischen Forschung geführt. Moderne Mikroskope sind in der Lage große Bilddatensätze von zunehmender Komplexität zu erzeugen, was eine manuelle Analyse ineffizient, wenn nicht gar undurchführbar macht. In dieser Arbeit stelle ich zwei neue Methoden für die automatische Bildanalyse von Mikroskopiedaten vor. 1. Die Fourier-Ringkorrelations-basierte Qualitätsschätzung (FRC-QE), ist eine neue Metrik für die automatisierte Bildqualitätsschätzung von 3D-Fluoreszenzmikroskopieaufnahmen, hier getestet am Beispiel von menschlichen Hirnorganoiden. FRC-QE automatisiert die Qualitätskontrolle, eine Aufgabe, die häufig manuell durchgeführt wird und somit einen Engpass bei der Skalierung bildbasierter Experimente auf tausend oder mehr Bilder darstellt. Die Methode kann die Clearing-Effizienz über experimentelle Replikate und Protokolle quantifizieren. Sie ist auf verschiedene Mikroskopiemodelle übertragbar und lässt sich effizient auf Tausende von Bildern skalieren. 2. Der von mir entwickelte "WormObserver" ermöglicht Langzeitaufnahmen, verarbeitet automatisch die aufgenommenen Videos und erleichtert die Datenintegration über Tausende von Individuen hinweg, um Verhaltensmuster zu entschlüsseln. Darauf aufbauend, habe ich mich auf ein Beispiel für die Plastizität des Nervensystems konzentriert: Die Verhaltenstrajektorie des "C. elegans Dauer Exits". Um den Entscheidungsmechanismus beim Verlassen des Dauer Larvenstadiums zu charakterisieren, habe ich Zeitrafferdaten von Larvenpopulationen in verschiedenen Umgebungen erfasst, analysiert und wichtige Entscheidungspunkte identifiziert. Indem ich die Verhaltensanpassung mit der Genexpression kontextualisiert habe, konnte ich neue Erkenntnisse gewinnen, wie ein sich entwickelndes Nervensystem externe Stimuli robust integrieren und das Verhalten des Organismus an neue Umgebungen anpassen kann.Since the invention of the microscope, microscopy images have generated new insights in biomedical research. While in the past these images were used for illustrative purposes, state-of-the-art microscopy images provide quantitative measurements. Moreover, modern microscopes are capable of autonomously producing large image datasets of increasing complexity, rendering manual analysis inefficient if not infeasible. Thus, extracting biologically relevant information from these datasets requires computational analysis using appropriate algorithms and software. While some analysis methods generalize to different microscope set-ups and types of images, others need to be well tailored to a particular problem. In this work, I present two new methods for automated image analysis of microscopy data. First, Fourier ring correlation-based quality estimation (FRC-QE) is a new metric for automated image quality estimation of 3D fluorescence microscopy acquisitions. I benchmarked the method in the context of evaluating clearing efficiency in human brain organoids. FRC-QE automates image quality control, a task that is often performed manually and thereby represents a bottleneck when scaling image-based experiments to thousand or more images. The method can estimate clearing efficiency across experimental replicates and clearing protocols. It generalizes to different microscopy modalities and efficiently scales to thousands of images. Second, I have developed a new method for behavioral imaging of C. elegans larvae. The “WormObserver” enables long-term imaging (>12h, >80k images/experiment), automatically processes the acquired videos

Model and Appearance Based Analysis of Neuronal Morphology from Different Microscopy Imaging Modalities

The neuronal morphology analysis is key for understanding how a brain works. This process requires the neuron imaging system with single-cell resolution; however, there is no feasible system for the human brain. Fortunately, the knowledge can be inferred from the model organism, Drosophila melanogaster, to the human system. This dissertation explores the morphology analysis of Drosophila larvae at single-cell resolution in static images and image sequences, as well as multiple microscopy imaging modalities. Our contributions are on both computational methods for morphology quantification and analysis of the influence of the anatomical aspect. We develop novel model-and-appearance-based methods for morphology quantification and illustrate their significance in three neuroscience studies. Modeling of the structure and dynamics of neuronal circuits creates understanding about how connectivity patterns are formed within a motor circuit and determining whether the connectivity map of neurons can be deduced by estimations of neuronal morphology. To address this problem, we study both boundary-based and centerline-based approaches for neuron reconstruction in static volumes. Neuronal mechanisms are related to the morphology dynamics; so the patterns of neuronal morphology changes are analyzed along with other aspects. In this case, the relationship between neuronal activity and morphology dynamics is explored to analyze locomotion procedures. Our tracking method models the morphology dynamics in the calcium image sequence designed for detecting neuronal activity. It follows the local-to-global design to handle calcium imaging issues and neuronal movement characteristics. Lastly, modeling the link between structural and functional development depicts the correlation between neuron growth and protein interactions. This requires the morphology analysis of different imaging modalities. It can be solved using the part-wise volume segmentation with artificial templates, the standardized representation of neurons. Our method follows the global-to-local approach to solve both part-wise segmentation and registration across modalities. Our methods address common issues in automated morphology analysis from extracting morphological features to tracking neurons, as well as mapping neurons across imaging modalities. The quantitative analysis delivered by our techniques enables a number of new applications and visualizations for advancing the investigation of phenomena in the nervous system

AUTOMATED ANALYSIS OF NEURONAL MORPHOLOGY: DETECTION, MODELING AND RECONSTRUCTION

Ph.DDOCTOR OF PHILOSOPH

Improvements in optical techniques to investigate the behavior and neuronal network dynamics over long timescales

Developments in optical technology have produced an important shift in experimental neuroscience from electrophysiological methods for observation and stimulation to all-optical solutions. One expects this trend to continue as future developments continue to deliver, and improve upon, the original promises of the technology: 1) minimally invasive actuation and recording of neurons, and 2) a drastic increase in targets that can be treated simultaneously. Moreover, as the high costs of the technology are reduced, one may expect its larger-scale adoption in the neuroscience community. In this thesis, I describe the development and implementation of two alloptical solutions for the analysis of behavior, neuronal signaling, and stimulation, which improve on previous state-of-the-art: (1) A minimally-invasive, high signal-to-noise twophoton microscopy setup capable of simultaneous, live-imaging of a large subset of sensory neurons post activation, and (2) a low-cost tracking solution to stimulate and record behavior. I begin this thesis with a review of recent advances in optical neuroscience techniques for the study of neuronal networks with the focus on work done in Caenorhabditis elegans. Then, in chapter 2, I describe my implementation of a two-photon temporal focusing microscopy setup and show significant improvements through the use of a high power/ high pulse repetition rate excitation system, enabling live imaging with high resolution for extended periods of time. I model temperature increase during a physiological imaging scenario for different repetition rates at fixed peak intensities and find range centered around 1 MHz to be optimal. Lastly, I describe the low-cost tracking setup with the ability to stimulate and record behavior over the course of hours. The setup is capable of two-color stimulation of optogenetic proteins over the area of the behavioral arena in combination with volatile chemicals. To showcase the utility of the system, I demonstrate behavioral analysis of integration of contradictory cues. In summary, I present a set of techniques for the interrogation of neural networks from animal behavior to neuronal activity, over timescales of potentially hours and days. These techniques can be used to address a new dimension of scientific questions.Okinawa Institute of Science and Technology Graduate Universit

Exploring behavioral circuits with holographic optogenetics and network imaging

Included works This thesis contains three previously published works: Semmelhack, Donovan, et al.; eLife 2014 Temizer, Donovan, et al.; Current Biology 2015 Thiele, Donovan, Baier; Neuron 2014 And one full manuscript, soon to be in the second round of review: Dal Maschio*, Donovan*, et al. *(Equal contributions) The work presented in these manuscripts is equivalent to a standard thesis

Large-scale Cellular Imaging of Neuronal Activity: a Study of Neural Individuality and a Method for Imaging Mouse Cortex

The brain contains an enormous number of neurons with diverse gene expression, morphology, and connectivity. These neurons exhibit distinct activity in the course of behaviors. The study of neural coding of a specific behavior necessitates recording activity from multifarious neurons in the circuit.One appealing approach is to simultaneously image the activity of a very large neuronal population at cellular resolution. However, recording calcium signals from tens of thousands of neurons at one time is not trivial. The gold standard technique, two-photon laser-scanning microscopy, typically permits recording from hundreds of neurons. Recently, we developed objective-coupled planar illumination (OCPI) microscopy, which uses thin sheets of light to image whole volumes of ∼ 10, 000 neurons within 2 seconds. Mydissertation includes an application and a further methodological development of such a fast large-scale imaging technique: 1) Large-scale functional imaging revealsindividuality, dimorphism, and plasticity of mouse pheromone-sensing neurons.Different individuals exhibit distinctive behaviors, which is presumably attributed to the neuronal differences between brains. However, studying neural individuality, especially at the level of the function of single neurons, requires an effective approach to measure cellular activity of a diverse neuronal population in a circuit. Here using OCPI microscopy, I performed calcium imaging of pheromone-sensing neurons in the intact mouse vomeronasal organ. Exhaustive recording enabled robust detection of 17 functionally-defined neuronal types in each animal. Inter-animal differences were much larger than expected from random sampling, and different cell types showed distinct degrees of variability. One prominent difference was a neuronal type present in males and virtually absent in females, and animals exhibited a corresponding dimorphism in investigatory behavior. Surprisingly, this dimorphism was not innate but generated by plasticity, as exposure to female scents led to both the elimination of this cell type and alterations in behavior. The finding that an all-or-none dimorphism in neuronal types is controlled by experience--even in a sensory system devoted to innate responses--highlights the extraordinary role of nurture in neural individuality. 2) A new generation of OCPI microscopy enables unprecedentedlarge-scalein vivoimaging of mouse brain activity by light-sheet microscopy. I have built a new variant of OCPI microscope, horizontal scanning objective-coupled planar lumination (hsOCPI) microscope, with enhanced imaging volume and speed by ∼ 15 fold compared to OCPI, thereby capable of recording ∼ 100, 000 neurons simultaneously. Using this technique, I imaged the entire nervous system of the larval zebrafish (including the spinal cord) and a square-millimeter patch of mouse cortexex vivo. The miniaturized optics around the specimen allowed in vivo imaging through a cranial window of a head-fixed mouse. This technique is the first application of light-sheet microscopy in calcium imaging of mouse cortexin vivo. The exceptional large-scale sampling of cortical activity with cellular resolution should usher new insights into the functions of brain circuits