Fully automated cellular-resolution vertebrate screening platform with parallel animal processing

The zebrafish larva is an optically-transparent vertebrate model with complex organs that is widely used to study genetics, developmental biology, and to model various human diseases. In this article, we present a set of novel technologies that significantly increase the throughput and capabilities of our previously described vertebrate automated screening technology (VAST). We developed a robust multi-thread system that can simultaneously process multiple animals. System throughput is limited only by the image acquisition speed rather than by the fluidic or mechanical processes. We developed image recognition algorithms that fully automate manipulation of animals, including orienting and positioning regions of interest within the microscope's field of view. We also identified the optimal capillary materials for high-resolution, distortion-free, low-background imaging of zebrafish larvae.National Institutes of Health (U.S.) (Director's New Innovator Award DP2 OD002989)National Institutes of Health (U.S.) (Transformative Research Award R01 NS073127)David & Lucile Packard Foundation (Award in Science and Engineering)Broad Institute of MIT and Harvard (SPARC Award)Foxconn International Holdings Ltd.Athinoula A. Martinos Center for Biomedical Imaging (Training Grant

High-throughput hyperdimensional vertebrate phenotyping

Most gene mutations and biologically active molecules cause complex responses in animals that cannot be predicted by cell culture models. Yet animal studies remain too slow and their analyses are often limited to only a few readouts. Here we demonstrate high-throughput optical projection tomography with micrometer resolution and hyperdimensional screening of entire vertebrates in tens of seconds using a simple fluidic system. Hundreds of independent morphological features and complex phenotypes are automatically captured in three dimensions with unprecedented speed and detail in semi-transparent zebrafish larvae. By clustering quantitative phenotypic signatures, we can detect and classify even subtle alterations in many biological processes simultaneously. We term our approach hyperdimensional in vivo phenotyping (HIP). To illustrate the power of HIP, we have analyzed the effects of several classes of teratogens on cartilage formation using 200 independent morphological measurements and identified similarities and differences that correlate well with their known mechanisms of actions in mammals

High-throughput hyperdimensional vertebrate phenotyping

Most gene mutations and biologically active molecules cause complex responses in animals that cannot be predicted by cell culture models. Yet animal studies remain too slow and their analyses are often limited to only a few readouts. Here we demonstrate high-throughput optical projection tomography with micrometre resolution and hyperdimensional screening of entire vertebrates in tens of seconds using a simple fluidic system. Hundreds of independent morphological features and complex phenotypes are automatically captured in three dimensions with unprecedented speed and detail in semitransparent zebrafish larvae. By clustering quantitative phenotypic signatures, we can detect and classify even subtle alterations in many biological processes simultaneously. We term our approach hyperdimensional in vivo phenotyping. To illustrate the power of hyperdimensional in vivo phenotyping, we have analysed the effects of several classes of teratogens on cartilage formation using 200 independent morphological measurements, and identified similarities and differences that correlate well with their known mechanisms of actions in mammals.National Institutes of Health (U.S.) (NIH Transformative Research Award (R01 NS073127))National Institutes of Health (U.S.) (NIH (R01 GM095672)National Institutes of Health (U.S.) (NIH Director’s New Innovator award (1-DP2-OD002989))Howard Hughes Medical Institute (International Student Fellowship)Broad Institute of MIT and Harvard (SPARC grant)David & Lucile Packard Foundation (Award in Science and Engineering

Methods for 2D and 3D Quantitative Microscopy of Biological Samples

New microscopy techniques are continuously developed, resulting in more rapid acquisition of large amounts of data. Manual analysis of such data is extremely time-consuming and many features are difficult to quantify without the aid of a computer. But with automated image analysis biologists can extract quantitative measurements and increases throughput significantly, which becomes particularly important in high-throughput screening (HTS). This thesis addresses automation of traditional analysis of cell data as well as automation of both image capture and analysis in zebrafish high-throughput screening.  It is common in microscopy images to stain the nuclei in the cells, and to label the DNA and proteins in different ways. Padlock-probing and proximity ligation are highly specific detection methods that  produce point-like signals within the cells. Accurate signal detection and segmentation is often a key step in analysis of these types of images. Cells in a sample will always show some degree of variation in DNA and protein expression and to quantify these variations each cell has to be analyzed individually. This thesis presents development and evaluation of single cell analysis on a range of different types of image data. In addition, we present a novel method for signal detection in three dimensions.  HTS systems often use a combination of microscopy and image analysis to analyze cell-based samples. However, many diseases and biological pathways can be better studied in whole animals, particularly those that involve organ systems and multi-cellular interactions. The zebrafish is a widely-used vertebrate model of human organ function and development. Our collaborators have developed a high-throughput platform for cellular-resolution in vivo chemical and genetic screens on zebrafish larvae. This thesis presents improvements to the system, including accurate positioning of the fish which incorporates methods for detecting regions of interest, making the system fully automatic. Furthermore, the thesis describes a novel high-throughput tomography system for screening live zebrafish in both fluorescence and bright field microscopy. This 3D imaging approach combined with automatic quantification of morphological changes enables previously intractable high-throughput screening of vertebrate model organisms

Methods for 2D and 3D Quantitative Microscopy of Biological Samples

New microscopy techniques are continuously developed, resulting in more rapid acquisition of large amounts of data. Manual analysis of such data is extremely time-consuming and many features are difficult to quantify without the aid of a computer. But with automated image analysis biologists can extract quantitative measurements and increases throughput significantly, which becomes particularly important in high-throughput screening (HTS). This thesis addresses automation of traditional analysis of cell data as well as automation of both image capture and analysis in zebrafish high-throughput screening.  It is common in microscopy images to stain the nuclei in the cells, and to label the DNA and proteins in different ways. Padlock-probing and proximity ligation are highly specific detection methods that  produce point-like signals within the cells. Accurate signal detection and segmentation is often a key step in analysis of these types of images. Cells in a sample will always show some degree of variation in DNA and protein expression and to quantify these variations each cell has to be analyzed individually. This thesis presents development and evaluation of single cell analysis on a range of different types of image data. In addition, we present a novel method for signal detection in three dimensions.  HTS systems often use a combination of microscopy and image analysis to analyze cell-based samples. However, many diseases and biological pathways can be better studied in whole animals, particularly those that involve organ systems and multi-cellular interactions. The zebrafish is a widely-used vertebrate model of human organ function and development. Our collaborators have developed a high-throughput platform for cellular-resolution in vivo chemical and genetic screens on zebrafish larvae. This thesis presents improvements to the system, including accurate positioning of the fish which incorporates methods for detecting regions of interest, making the system fully automatic. Furthermore, the thesis describes a novel high-throughput tomography system for screening live zebrafish in both fluorescence and bright field microscopy. This 3D imaging approach combined with automatic quantification of morphological changes enables previously intractable high-throughput screening of vertebrate model organisms

Methods for 2D and 3D Quantitative Microscopy of Biological Samples

New microscopy techniques are continuously developed, resulting in more rapid acquisition of large amounts of data. Manual analysis of such data is extremely time-consuming and many features are difficult to quantify without the aid of a computer. But with automated image analysis biologists can extract quantitative measurements and increases throughput significantly, which becomes particularly important in high-throughput screening (HTS). This thesis addresses automation of traditional analysis of cell data as well as automation of both image capture and analysis in zebrafish high-throughput screening.  It is common in microscopy images to stain the nuclei in the cells, and to label the DNA and proteins in different ways. Padlock-probing and proximity ligation are highly specific detection methods that  produce point-like signals within the cells. Accurate signal detection and segmentation is often a key step in analysis of these types of images. Cells in a sample will always show some degree of variation in DNA and protein expression and to quantify these variations each cell has to be analyzed individually. This thesis presents development and evaluation of single cell analysis on a range of different types of image data. In addition, we present a novel method for signal detection in three dimensions.  HTS systems often use a combination of microscopy and image analysis to analyze cell-based samples. However, many diseases and biological pathways can be better studied in whole animals, particularly those that involve organ systems and multi-cellular interactions. The zebrafish is a widely-used vertebrate model of human organ function and development. Our collaborators have developed a high-throughput platform for cellular-resolution in vivo chemical and genetic screens on zebrafish larvae. This thesis presents improvements to the system, including accurate positioning of the fish which incorporates methods for detecting regions of interest, making the system fully automatic. Furthermore, the thesis describes a novel high-throughput tomography system for screening live zebrafish in both fluorescence and bright field microscopy. This 3D imaging approach combined with automatic quantification of morphological changes enables previously intractable high-throughput screening of vertebrate model organisms

BlobFinder, a tool for fluorescence microscopy image cytometry

Images can be acquired at high rates with modern fluorescence microscopy hardware, giving rise to a demand for high-speed analysis of image data. Digital image cytometry, i.e., automated measurements and extraction of quantitative data from images of cells, provides valuable information for many types of biomedical analysis. There exists a number of different image analysis software packages that can be programmed to perform a wide array of useful measurements. However, the multi-application capability often compromises the simplicity of the tool. Also, the gain in speed of analysis is often compromised by time spent learning complicated software. We provide a free software called BlobFinder that is intended for a limited type of application, making it easy to use, easy to learn and optimized for its particular task. BlobFinder can perform batch processing of image data and quantify as well as localize cells and point like source signals in fluorescence microscopy images, e.g., from FISH, in situ PLA and padlock probing, in a fast and easy way

Passive in-vehicle driver breath alcohol detection using advanced sensor signal acquisition and fusion

Objective: The research objective of the present investigation is to demonstrate the present status of passive in-vehicle driver breath alcohol detection and highlight the necessary conditions for large-scale implementation of such a system. Completely passive detection has remained a challenge mainly because of the requirements on signal resolution combined with the constraints of vehicle integration. The work is part of the Driver Alcohol Detection System for Safety (DADSS) program aiming at massive deployment of alcohol sensing systems that could potentially save thousands of American lives annually. Method: The work reported here builds on earlier investigations, in which it has been shown that detection of alcohol vapor in the proximity of a human subject may be traced to that subject by means of simultaneous recording of carbon dioxide (CO2) at the same location. Sensors based on infrared spectroscopy were developed to detect and quantify low concentrations of alcohol and CO2. In the present investigation, alcohol and CO2 were recorded at various locations in a vehicle cabin while human subjects were performing normal in-step procedures and driving preparations. A video camera directed to the driver position was recording images of the driver's upper body parts, including the face, and the images were analyzed with respect to features of significance to the breathing behavior and breath detection, such as mouth opening and head direction. Results: Improvement of the sensor system with respect to signal resolution including algorithm and software development, and fusion of the sensor and camera signals was successfully implemented and tested before starting the human study. In addition, experimental tests and simulations were performed with the purpose of connecting human subject data with repeatable experimental conditions. The results include occurrence statistics of detected breaths by signal peaks of CO2 and alcohol. From the statistical data, the accuracy of breath alcohol estimation and timing related to initial driver routines (door opening, taking a seat, door closure, buckling up, etc.) can be estimated.The investigation confirmed the feasibility of passive driver breath alcohol detection using our present system. Trade-offs between timing and sensor signal resolution requirements will become critical. Further improvement of sensor resolution and system ruggedness is required before the results can be industrialized. Conclusions: It is concluded that a further important step toward completely passive detection of driver breath alcohol has been taken. If required, the sniffer function with alcohol detection capability can be combined with a subsequent highly accurate breath test to confirm the driver's legal status using the same sensor device. The study is relevant to crash avoidance, in particular driver monitoring systems and driver-vehicle interface design

Source code 2: Test datasets for OPT reconstruction and registration (part 1)

These RAR archive files contain the following: (1) acquisition data from our OPT platform of a 2 dpf fezf2 mutant embryo stained with an in situ probe for ascl1a (folder 'data\OPT', extension '.mat'). This file serves as a test dataset for our OPT reconstruction source code. (2) Unstained reference fish (URFs; folder 'data\Registration\ referenceFish') and OPT reconstructions from 8 wild-type embryos (folder 'data\Registration\TestData_th_2dpf\wt') and 8 fezf2 mutant embryos (folder 'data\Registration\TestData_th_2dpf\mt') stained with an in situ probe for tyrosine hydroxylase (th). URFs for 2 dpf and 3 dpf are provided. All th-stained embryos are 2 dpf. These images serve as a test dataset for our registration source code. Source code for both OPT reconstruction and registration is available at https://github.com/aallalou/OPT-InSitu-Toolbox. Download all RAR archive files (parts 1 through 7) prior to extraction

The broad role of Nkx3.2 in the development of the zebrafish axial skeleton

The transcription factor Nkx3.2 (Bapx1) is an important chondrocyte maturation inhibitor. Previous Nkx3.2 knockdown and overexpression studies in non-mammalian gnathostomes have focused on its role in primary jaw joint development, while the function of this gene in broader skeletal development is not fully described. We generated a mutant allele of nkx3.2 in zebrafish with CRISPR/Cas9 and applied a range of techniques to characterize skeletal phenotypes at developmental stages from larva to adult, revealing loss of the jaw joint, fusions in bones of the occiput, morphological changes in the Weberian apparatus, and the loss or deformation of bony elements derived from basiventral cartilages of the vertebrae. Axial phenotypes are reminiscent of Nkx3.2 knockout in mammals, suggesting that the function of this gene in axial skeletal development is ancestral to osteichthyans. Our results highlight the broad role of nkx3.2 in zebrafish skeletal development and its context-specific functions in different skeletal elements