Hongkui Zeng - US grants

[unreadable] DESCRIPTION (provided by applicant): The utility of transgenic tools that can selectively label each particular type of neuron, and furthermore, selectively inactivate genes or manipulate the activity of one type of neuron at a time, has high impact in many different areas of neuroscience research. Current approaches taken by many, e.g. the Cre-driver line creation, usually utilize genes relatively specifically expressed in certain cell types. However, such "marker" genes rarely label a really specific neuronal population. It is highly desirable to further refine the target specificity into a particular region or a specific population of neurons. To achieve this we propose to systematically evaluate a number of combinatorial strategies and develop a series of transgenic tools to drive highly specific gene expression through the intersection of the expression of 2 marker genes. Through mining our genome-wide database, Allen Brain Atlas, Dr. Zeng and colleagues have identified a large set of gene markers for different cortical cell types. Dr. Nagy has developed a set of gene targeting and allele replacement strategies for expressing multiple genes efficiently. Allen Institute has a high throughput ISH platform and capability of high resolution image acquisition and databasing. By combining the superb technologies developed by both parties, we will examine the colocalization of different marker genes by double fluorescent ISH (dFISH), create both driver and reporter/responder mouse lines to test different intersection strategies, and use the dFISH again to systematically characterize and database where the controlled gene expression occurs in the entire mouse brain. In this grant we will use the neocortex as a model to establish the technology. Once completed, it can be applied easily into other brain regions as well. PUBLIC HEALTH RELEVANCE: Studying the extreme complexity of the brain demands ways to tease apart its components. Traditional transgenic tools have been widely used in every area of neuroscience research. Our proposed research will provide two types of powerful tools to the neuroscience community: transgenic mouse lines that can direct genetic manipulation to highly specific neuronal populations, and an image database comprehensively documenting where such manipulation occurs. Both of these tools will have major impact on the broad neuroscience community, from molecular to systems neuroscience, from development to behavior studies, from studies of normal brain physiology to disease mechanisms. [unreadable] [unreadable] [unreadable]

DESCRIPTION (provided by applicant): The use of transgenic tools to selectively label and detect individual neuronal populations and modulate gene expression in those cells to manipulate activity can have significant impact in neuroplasticity research. In recent years a number of molecular tools have been developed to study neural circuitry and plasticity at exquisite detail and control. However, application of these tools in different neuronal cell types and circuits at cellular and subcellular level has been limited, in particular because of the time and effort needed to develop each individual transgenic animal. This issue has been partially addressed by putting in great effort into the development of cell type specific Cre-driver lines. However, there have still been hurdles to overcome in creating the necessary numbers of Cre responsive transgenic lines that can express the molecular tools at sufficiently strong levels for imaging and for functional manipulation in a cell type specific, subcellularly targeted manner for use by academic researchers. To attempt to address this issue, we propose to systematically target a set of genomic loci that will convey strong ubiquitous expression or selective pre and post-synaptic specific targeting of genes in inhibitory and excitatory neurons respectively, to develop a Cre-responder platform in these genomic loci to which any existing or newly developed molecular tools can be easily inserted. We are committed to use this program to provide diverse transgenic mice to the academic community that will exploit many of the new tools and probes to study neural networks and in particular study neuronal plasticity as it relates to behavior and physiology. The Allen Institute has a high throughput ISH platform and capability of high resolution image acquisition and data-basing. By combining these innovative technologies with the transgenic lines to be developed, we will be able to increase the utility of the transgenic mice as an approach to study neuroplasticity by making such experimental animals freely available for the neuroscience community. PUBLIC HEALTH RELEVANCE: Neuroplasticity is a fundamental process underlying brain development and brain's ability to acquire knowledge and skills, as well as a component of many brain disorders. Genetic tools have been widely used in every area of plasticity research. Our proposed research will provide to the neuroscience community a transgenic platform to incorporate state-of-the-art probes and tools for monitoring and manipulating plasticity at cellular and subcellular levels. Use of these genetic tools by the neuroscience community will have major impact on the further understanding of the roles of plasticity plays in brain function and diseases, leading to ways in treating diseases and improving public health.

DESCRIPTION (provided by applicant): The use of transgenic tools to selectively label and detect individual neuronal populations and modulate gene expression in those cells to manipulate activity can have significant impact in neuroplasticity research. In recent years a number of molecular tools have been developed to study neural circuitry and plasticity at exquisite detail and control. However, application of these tools in different neuronal cell types and circuits at cellular and subcellular level has been limited, in particular because of the time and effort needed to develop each individual transgenic animal. This issue has been partially addressed by putting in great effort into the development of cell type specific Cre-driver lines. However, there have still been hurdles to overcome in creating the necessary numbers of Cre responsive transgenic lines that can express the molecular tools at sufficiently strong levels for imaging and for functional manipulation in a cell type specific, subcellularly targeted manner for use by academic researchers. To attempt to address this issue, we propose to systematically target a set of genomic loci that will convey strong ubiquitous expression or selective pre and post-synaptic specific targeting of genes in inhibitory and excitatory neurons respectively, to develop a Cre-responder platform in these genomic loci to which any existing or newly developed molecular tools can be easily inserted. We are committed to use this program to provide diverse transgenic mice to the academic community that will exploit many of the new tools and probes to study neural networks and in particular study neuronal plasticity as it relates to behavior and physiology. The Allen Institute has a high throughput ISH platform and capability of high resolution image acquisition and data-basing. By combining these innovative technologies with the transgenic lines to be developed, we will be able to increase the utility of the transgenic mice as an approach to study neuroplasticity by making such experimental animals freely available for the neuroscience community. PUBLIC HEALTH RELEVANCE: Neuroplasticity is a fundamental process underlying brain development and brain's ability to acquire knowledge and skills, as well as a component of many brain disorders. Genetic tools have been widely used in every area of plasticity research. Our proposed research will provide to the neuroscience community a transgenic platform to incorporate state-of-the-art probes and tools for monitoring and manipulating plasticity at cellular and subcellular levels. Use of these genetic tools by the neuroscience community will have major impact on the further understanding of the roles of plasticity plays in brain function and diseases, leading to ways in treating diseases and improving public health.

DESCRIPTION (provided by applicant): The cells of the brain exhibit a diversity of expressed genes, morphologies, and electrophysiological properties, and have come to be grouped into cell types that are distinguished by one or more of these characteristics. However, there is no one-to-one correspondence between cell type-defining expressed genes, morphological characteristics, and electrophysiological properties and no unified taxonomy of brain cells. Furthermore, cells routinely change their expressed genes, morphologies, and electrophysiological properties, as a result of development, plasticity, or disease, raising the question of how to categorize cell types as they change their states as a result of experience. Accordingly, we propose to develop a powerful, easy-to-use tool that enables the integrative phenotyping of cells of the brain - namely, a robot that can acquire simultaneously the gene expression patterns, morphologies, and electrophysiological properties of single cells in brain tissue, in an automated fashion. Recently, two of our labs developed a prototype autopatching robot that enables automated whole-cell patch clamp recording of neurons in living mouse brain, significantly increasing the efficiency of this highly challenging task. In a multidisciplinary tea, we propose to augment this robot, coupling it to transcriptional and morphological analysis strategies, yielding a platform for the comprehensive characterization of single cells in intact tissues. We will develop variants of the robot and its algorithms to enable it to patch in brain slices, including in an image guided fashion (Aim 1), to extract transcriptomic information (Aim 2), and to perform morphological fills (Aim 3) and gene delivery to cells (Aim 5). We will also create massively parallel autopatching robots (Aim 4). We will autopatch hundreds to thousands of single cells from different cortical regions of mice (Aim 6), in vivo as well as in slices, both broadly surveying cells, as well as targeting specific fluorescently labeled neural populations. We will create visualization software to help with analysis of the integrated cell profiles that emerge, aiming to estimate the dimensionality of cell type space, characterize cell- to-cell heterogeneity, and discover optimal cell type markers for molecular targeting. Our goal is to create a powerful, easy-to-use toolbox that makes fundamentally new kinds of science possible, converting the critical tasks of categorizing cell types, and characterizing cell states, into routne, simple tasks. As our goal is to develop a toolbox which will have very broad applicability, we are focusing our innovation not only on power, but ease of use, aiming to enable fields across biology to characterize normal and diseased organ states at the single cell level. We will distribute all tools, methods, and datasets as freely as possible, and teach others to use these technologies. As many diseases affect different cells to different extents, we will seek to commercialize our work to enable diagnostic or therapeutic tools that directly improve human health. PUBLIC HEALTH RELEVANCE: Our project will generate a new kind of robot, as well as relevant methods of use, that enable biologists and clinicians to automatically assess the gene expression profile, shape, and electrical properties of individual cells embedded in intact tissues such as the brain. By enabling the automated characterization of cells in complex organ systems, our technology will empower scientists across biology to map the cell types present in organ systems (e.g., brain circuits) in disease states, enabling new mechanistic understandings of disease, and enabling new molecular drug targets to be identified. Our robot will also enable new kinds of biopsy analysis and diagnostic, helping empower personalized medicine in arenas ranging from epilepsy to cancer, to utilize information about cellular diversity in disease states towards patient care optimization.

? DESCRIPTION (provided by applicant): The brain circuit is an intricately interconnected network of a vast number of neurons with diverse molecular, anatomical and physiological properties. Neuronal cell types are fundamental building blocks of neural circuits. To understand the principles of information processing in the brain circuit, it is essential to have a systematic understanding of the common and unique properties for each of its components - the cell types, how they are connected to each other, and what are their functions in the circuit. From the study of numerous circuits, many types of mechanisms have been proposed regarding the roles of different cell types in signal processing. However, despite of the importance, we are far from a comprehensive understanding of the number and kinds of cell types in the brain or a given circuit. We do have a wealth of knowledge on the major cell types in each region, and many examples of specific types. But for the most part, due to the lack of systematic efforts, we don't know the complete cell type composition of most circuits, and we have very little idea about the degree of variation and heterogeneity among single cells, both within a given type and between different types. To address this issue, we propose to establish a comprehensive and standardized cell type characterization platform that can be scaled up to systematically examine the properties and function of cell type components in any neural circuits throughout the brain. To implement this, we propose a model for collaboration between academic labs/centers and Allen Institute for characterizing cell types in specific brain circuits, with all the QC-passed daa going into the Allen Institute Cell Types Database and becoming publicly available. We will test a range of experimental approaches, encompassing molecular, anatomical and physiological measurements and their integration at the single cell level. Our proof of principle studies are based on comparison of three major brain neural circuits in the mouse brain: two closely related cortical circuits - primary visual cortex (V1) and primary somatosensory cortex (S1), and a more distinct circuit - the hypothalamus/amygdala emotional pathway. These two axes of comparison should be very informative in assessing the reliability and generality of the cell type characterization approaches we will be testing. We thereby hope to determine the critical parameters and metrics necessary to classify neurons into discrete cell types, guided by their functions. Thus, we anticipate that this project and the resources it produces will have a broad impact and catalytic effect on the scientific community studying brain circuitry function and dysfunction.

Project Summary (Overall) For the brain (or any other biological systems), cells are a fundamentally important level of organization between genes/molecules and networks/systems. The mammalian brain is composed of millions to billions of neurons and non-neuronal cells with diverse properties and extremely intricate connections to form highly specific and hierarchically organized circuits and networks. To unravel the principles of information processing in brain circuits, it is essential to have a systematic understanding of its components ? the cell types, and to have tools to monitor and manipulate them in the living brain to probe their roles in the circuits. However, it is still unclear how many cell types there are in the brain and how to even define them. Recent high-throughput technology advancement, especially in the areas of sequencing and imaging, has created an unprecedented opportunity to collect comprehensive information about individual cells in large scales to enable data-driven cell type classification. We will form a Comprehensive Center on Mouse Brain Cell Atlas, and our goal is to create a comprehensive whole-brain atlas of cell types in the mouse encompassing molecular, anatomical and functional annotations of cell types. We will conduct large-scale single-cell transcriptomic analysis across the entire mouse brain, as well as systematic sampling of neuronal morphology and connectivity in a wide range of brain areas. In selected proof-of-principle cases, we will examine the correspondence among the transcriptomic, morphological, connectional and/or functional properties of the same cells, to gain an understanding what defines a cell type. Finally, we will generate a census of the number and location of cells for each type, and new genetic tools targeting selected cell types. We will establish a Data Core to provide data management systems for integrating the diverse data collections and to provide data processing and mapping infrastructure and expertise to transform raw data into quantitative cell characterization features. We will also establish an Administrative Core to address the operational management of the Center, including fiscal management, project management, strategic planning, progress reporting, and support for collaboration and communication. Altogether this project will create a first version of a comprehensive cell type atlas for an entire mammalian brain with enduring values to the community towards the understanding of brain function in healthy and diseased states.

Project Summary (Research Segment 1) Metazoan organs, including the brain, are composed of various cell types, but the cell type census for even a relatively simple mammalian brain such as the one of the mouse is not available. A whole mouse brain database of molecularly defined cell types organized in a taxonomy and annotated with their precise locations within the brain, would be of unprecedented importance for understanding the functions of mammalian brains. Recent technological advancements have enabled transcriptomic characterization of large numbers of individual cells through single cell RNA-sequencing (scRNA-seq). However, a number of methodologies exist, and differences in experimental and analysis methods employed by different labs, animal ages and strains, and spatial resolutions of dissections, make data comparison and integration challenging. In order to create a brain-wide atlas of cell types in the mouse as a standard for the field, we propose to utilize two scRNA-seq technologies at different scales and sequencing depths in a standardized manner across the entire mouse brain, to achieve consistency and comparability across different brain regions. We will compare these two methods, Smart-seq and droplet-based sequencing, to systematically assess to what extent they can distinguish different cell types. We will focus on the non-multiplexed, deeper sequencing method, Smart-seq, to generate a high-quality, foundational single-cell transcriptomic cell type atlas for all brain regions that are also precisely dissected and registered into a mouse brain common coordinate framework so that the spatial origin of each cell or cell type can be easily visualized. We will use RNA fluorescence in situ hybridization (FISH) to confirm expression patterns of cell type-specific gene markers derived from scRNA-seq data and further delineate the anatomical specificity of different cell types. Finally, we will obtain Smart-seq data from a selected set of retrogradely labeled neurons to define the correspondence between transcriptomic cell types and their connectional specificity. We will employ various computational approaches for clustering analysis of the large scRNA-seq datasets, to create a taxonomy of cell types within the whole mouse brain. This dataset will be useful for the entire community to mine and to compare with their own studies using a diverse range of existing and future single cell techniques.

Project Summary/Abstract Administrative Core ?A comprehensive whole-brain atlas of cell types in the mouse? proposal consists of four Research Segments: Molecular Signatures, Anatomy, Functional Measures, Cell-specific Targeting Approaches and Tools; a Data Core and an Administrative Core with six PIs and eleven collaborative sites. To address the operational management of the Center, including fiscal management, project management, strategic planning, progress reporting, and support for collaboration and communication, an Administrative Core will be established to provide the necessary leadership and organizational structure to achieve the goals and milestones as well as to coordinate and integrate with the Brain Initiative Cell Census Network (BICCN) and BRAIN Cell Data Center (BCDC). The Administrative Core will provide the structure that fosters communication and collaboration among the Center members by organizing the Center into a Steering Committee, Project Teams, and an Administrative Core Subcommitee to oversee the collaborative, standardized, and on-time data generation, analysis, and public data sharing process. In addition, the Administrative Core will establish the infrastructure and tools for coordination and communication among the Center members. Project management best practices, such as milestones, progress reporting and tracking, collaborative software programs, and a responsibility matrix are just some of the tools that will be applied to the Center to ensure achievement of performance objectives and milestones, optimized communication, and resource utilization and prioritization. Further, the Administrative Core will support the implementation of standard operating procedures and quality control standards for data generation, data processing, and analysis. To produce a high-quality atlas of cell types in the mouse brain, rigorous standardization and quality control practices will be adopted by all members. This adoption will also facilitate the data transfer and data integration with the BCDC. Finally, the Administrative Core will implement and maintain fiscal and subcontractor management processes for all members. With the implementation of this entire infrastructure, we anticipate that this project and the resources it produces will have a broad and meaningful impact on the generation of a comprehensive 3D brain cell reference atlas.

Project Summary (Research Segment 2) The brain circuit is an intricately interconnected network of numerous cell types. To understand the principles of information processing in the brain circuit, it is essential to determine a catalog of cell types, how they are distributed throughout the brain, and how they are connected to each other. A cell's precise location within the brain (where is it?), its specific dendritic and axonal morphology (what does it look like?), and its structural connectivity with other cells in circuits and networks (who does it connect to?) are all critical anatomical factors which contribute to the definition and accounting of different cell types. We will produce comprehensive anatomical cell census data from brains of adult male and female mice, leveraging our existing mouse brain reference and connectivity atlases, and employing three major scalable approaches. We will map the spatial organization of transcriptomic cell types identified in Research Segment 1 using multiplexed error-robust fluorescence in situ hybridization (MERFISH) with combinatorial marker gene sets identified in the single-cell RNA-seq experiments. Furthermore, we will use MERFISH to determine the microenvironment, tissue composition and ratio of various cell types. We will generate full neuronal morphologies of representative cell types in major brain regions, using two different high-throughput and high-resolution whole-brain fluorescent imaging approaches and semi-automated morphology reconstruction methods. These systematically collected data will be used to discover rules underlying cell types as defined by their full dendritic and axonal morphologies. We will use an optimized rabies tracing system to do monosynaptic, retrograde trans-synaptic tracing to map whole-brain inputs to genetically-identified cell populations brain-wide. By combining this with the Allen Institute's already created anterograde projectome, we will be able to generate a first iteration of the mesoscale, input/output circuit wiring diagram. These different types of anatomical data will be integrated with each other and with other cell type characterization data modalities in a variety of ways, including coupling rabies tracing, full neuronal morphology, or in vivo functional imaging with multiplexed FISH, to derive an integrated cell type classification scheme.

PROJECT SUMMARY A major barrier in the field of opioid research is our limited understanding of the organization of the opioid system in the brain: we still do not know which cell types express each opioid receptor (mu, delta, kappa, nociceptin) to mediate the effects of endogenous and exogenous opioids, nor what other molecules are present in these cells. Without this knowledge, understanding how opioids alter activity in circuits to produce behavioral effects remains elusive. This gap in knowledge prevents the identification of molecular targets to potentiate opioid analgesia and mitigate the deleterious effects of opioid use disorder (OUD), including addiction and respiratory depression. To fill this gap in knowledge, we propose to leverage the uniquely massive single-cell RNA sequencing (scRNA-seq) database generated by the Allen Institute for Brain Science (>3.4 million cells throughout the entire mouse brain) as part of the BRAIN Initiative Cell Census Network (BICCN) effort. Using this database, we will establish a comprehensive catalog of all the cell types that express each opioid receptor and peptide throughout the brain, as well as the co-expression of gene networks that mediate or regulate opioid actions, including other G protein-coupled receptors and cellular effectors of opioid receptors (Aim 1). Further, we will use our well- established high-throughput single-cell RNA-seq pipelines to characterize the cell-type-specific molecular adaptations that occur during chronic opioid exposure, withdrawal, and abstinence, using a clinically relevant model of post-surgical pain for which opioids are typically prescribed (Aim 2). Finally, we will leverage this novel knowledge to dissect the mechanisms of action of opioids by performing advanced circuit mapping and in vivo functional imaging studies of cell types expressing opioid receptors in the prefrontal cortex (PFC), a region critical to both opioid analgesia and addiction (Aim 3). Our transformative work will be the first to combine several highly innovative technologies at the molecular, circuit, and neural ensemble levels, including high-throughput scRNA-seq, new viral strains with improved transsynaptic transfer and decreased toxicity for circuit mapping, the crystal skull and miniscope- microprism optical approaches for in vivo wide-field imaging of brain state and for recording dynamics of molecularly defined neuron types in freely moving mice undergoing opioid analgesia and addiction paradigms. We have an extraordinary interdisciplinary team of investigators with highly complementary expertise in the neurobiology of opioids and the distribution and function of their receptors in pain and addiction circuits, the molecular and anatomical brain architecture, large-scale cell type characterization and circuit mapping, and highly innovative brain imaging methods as applied to the study of neural circuits. Overall, this research aims to generate an exceptional resource for the opioid field (to be made publicly available through the NIDA-funded SCORCH data coordination center) to explain how opioids change the brain, and discover novel therapeutic approaches to prevent and treat OUD.

Project Summary One of the most fundamental questions in brain aging research is whether age-related alterations affect all brain regions equally, or whether some regions, and cell types within those regions, are more vulnerable to the effects of aging than others. Aging is associated with cognitive decline, and is reported to cause alterations in a variety of important cellular processes and in a variety of cell types (e.g., microglia, astrocytes, neurons). Broad classes of cells in affected brain regions are known to be selectively vulnerable to age-related neurodegenerative diseases, but the specific molecular mechanisms underlying this vulnerability are unclear. An essential prerequisite to understanding this selective vulnerability is to understand the detailed changes at cell type and circuit levels during the aging process. Cataloging brain cell types and their connectivity in normal aging brain is foundational to uncovering the mechanisms and therapeutic opportunities for age-related brain disorders. State-of-the-art single-cell technologies, in particular single-cell transcriptomics with its high dimensional molecular information, but also spatial transcriptomics, single-cell epigenomics and single-cell morphology, are providing transformative information about brain cell types at an unprecedented scale and resolution. We propose to utilize our well-established omics pipelines to characterize and classify cell types in 18 months old male and female C57BL/6J mice and compare the results with the extensive brain-wide datasets in young adult (~P56) mice already being generated in the current BRAIN Initiative Cell Census Network (BICCN). We will use single-nucleus transcriptomics and epigenomics to obtain a high-level survey of neuronal and non-neuronal cell classes/types across the entire mouse brain, and then an in-depth single-cell and spatial transcriptomic study in brain areas showing age-related changes and/or vulnerable to neurodegenerative diseases. We will utilize our imaging?based registration process to map all data into the Common Coordinate Framework (CCF), which allows accurate cross-age quantitative comparisons that will be crucial for uncovering age-related changes. By conducting concurrent single-cell gene expression and chromatin accessibility measurements in the same brain regions, and a detailed spatial transcriptomic map of the proportion and distribution of different cell types and specific molecular pathways, we will chart an integrated path towards gaining mechanistic insight underlying the cognitive decline in aging and age-related disease pathology.