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Setting Priorities for Molecular Neuroanatomy in the Postgenomic Era |
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Summary and recommendations from a workshop organized under the auspices of the NIMH, NIDA, and NINDS at Laguna Beach, CA in January 2002Marc Tessier-Lavigne and Lubert Stryer, organizers Contents:
Part I: Overview and Summary
The brain is the most complex organ in our body, responsible for perception, behavior, cognition, memory, and consciousness. It is comprised of about a trillion nerve cells, or neurons, whose intricate and precisely wired connections underlie all of these functions. But the neurons are not all the same: many thousands of different classes of neurons, defined by a variety of criteria such as morphology, patterns of connectivity, and expression of particular neurotransmitters and receptors, serve as the cellular building blocks of the brain. Each of these neuronal types has a specific physiological role in brain function. Neurological and psychiatric diseases are diseases of particular neurons or neural circuits. The complexity of brain cell types and circuits is reflected in the complexity of gene expression patterns in the brain. It is believed that perhaps a third to half of all genes are largely or exclusively dedicated to directing the development, maintenance and functioning of the brain. With more than 30,000 genes in the human genome, the task of mapping all genes to the many thousands of neuronal classes and neuronal circuits Ð what is being called molecular neuroanatomy Ð might seem beyond reach. In fact, this mapping is taking place. It is proving to be remarkably informative and illuminating despite being performed on a relatively small scale thus far, with about a thousand genes mapped, and some mapped only in particular subregions of the brain. Such studies have shown that analysis of gene expression in neurons can yield essential information on neural development and function, such as the identity of neurons involved in responses to particular drugs, or the genes that control the development of particular classes of neurons. Such analysis has also defined molecular markers of particular neuronal cell types, helping with the taxonomy of brain cell types Ð the division of known neuronal classes into further subclasses. Especially important, the availability of cell type-specific molecular markers for particular neuronal classes has provided tools to deliver genes and gene products to those neurons (in ways discussed below), dramatically facilitating the analysis of their development, connectivity, function, and dysfunction. The potential medical benefits that will derive from this knowledge are immense. The identification of genes expressed in particular classes of neurons linked to specific diseases provides new drug targets for the treatment of a wide range of ailments including stroke, spinal cord injury, neurodegenerative diseases like Parkinson's disease, brain tumors, schizophrenia, depression, anxiety disorders, and addiction. Neuronal cell type-specific markers provide a means for developing gene therapies that involved changing gene expression in particular neurons. They also make it possible to visualize neural circuits in their normal and abnormal states, which is likely to have a large impact on the diagnosis of disease and the evaluation of the effectiveness of therapy. The identification of transcription factors that control cell fate and connectivity in the brain will accelerate the development of therapies to regenerate nervous tissue. In the 1990s, several Institutes of the National Institutes of Health, recognizing the importance and promise of molecular neuroanatomy for public health, launched the Brain Molecular Anatomy Project (BMAP), a series of funding initiatives to map gene and gene product expression to neuronal cell types to create a Molecular Brain Map. In January 2002, a workshop was convened by NIMH, NINDS, and NIDA to bring together experts in the field (Table 1) to take stock of existing efforts, formulate recommendations for upcoming work in this field, and help establish scientific priorities, especially in light of the exceptional opportunities created by the completion of the Human Genome Project and the identification of nearly all genes in the genome. A consensus view of the working group, reiterating the premise of BMAP, is that enormous benefit will derive from a systematic, large-scale, and organized effort to generate a Molecular Brain Map for humans and the mouse. The utility of a systematic effort is well illustrated by the Human Genome Project. Prior to the Project, the genome was already being sequenced in a piecemeal fashion by thousands of investigators world-wide, but these laboratory-based initiatives involved considerable redundancy as well as inefficiencies because of their small scale. An organized effort to sequence the human genome Ð and that of other species Ð made it possible to achieve an enormous economy of scale and to complete the sequencing of genomes much more rapidly, thereby empowering the entire biomedical community and greatly accelerating the pace of discovery of new knowledge and novel therapeutics. In the same way, the creation of a Molecular Brain Map would eventually result from the independent activities of individual investigators, but an economy of scale can be achieved through more systematic efforts, like those already supported by the NIH (see below). The acceleration of this process will in turn accelerate the pace of discovery in the neurosciences, neurology, and psychiatry. The working group achieved consensus on the following principles, many of which have already been incorporated into existing efforts at the National Institutes of Health. In Parts II-IV of this report, we provide background information on molecular neuroanatomy, including a description of existing large scale initiatives, and discuss emerging opportunities. In part V, we discuss in detail the recommendations and priorities formulated by the participants that were summarized above. Table 1: Workshop Participants
Table 2: Enabling Reagents and Datasets
Table 3: Complementary Technologies
Top of PagePart II: Background: Gene-Based and Cell-Based Approaches to Creating a Map
Using histological tools like the Golgi staining method, neuroanatomists in the late 19th and early 20th centuries defined hundreds of different neuronal cell types based on their location in the brain, morphology, and connectivity. Throughout the 20th century, this number grew, and neuroscientists were also able to assign particular physiological functions to a large number of these neuronal types and many of the circuits linking these cells. At present, the number of distinct neuronal cell types is not precisely known, but it is estimated that there must be at least several thousand. This estimate is supported by the finding of novel subclasses whenever a particular population of neurons is studied in detail. For example, a recent assessment of amacrine cells subtypes in the retina, previously thought to number about a dozen, revealed the existence of more than thirty easily definable subtypes. These thousands of cell types, through their specific patterns of interconnections, direct the functioning of the brain. Subpopulations of neurons are increasingly being distinguished based on their pattern of gene expression. Historically, molecular neuroanatomy started with cellular pharmacology Ð the definition of the neurotransmitters and neurotransmitter receptors made by particular neurons, using a variety of physiological, in situ radioligand binding, and histochemical methods. The development of the technique of immunohistochemistry accelerated the mapping of proteins (such as neuropeptides) and other epitopes (such as specific carbohydrate moieties) to particular neurons in cases where a suitable antibody was available. However, it is the development of sensitive and reproducible mRNA in situ hybridization techniques that unleashed the systematic analysis of gene expression in neurons, because this approach can be readily applied to all genes without requiring the labor-intensive development of specific detection reagents (such as antibodies); in all cases, a small gene fragment is sufficient to develop an appropriate in situ hybridization probe. In situ hybridization methods have been supplemented by transgenic (promoter-based, and BAC-based) and knock-in approaches, which make it possible to visualize the pattern of expression of particular genes using genetically encoded reporters driven from the gene locus in transgenic mouse lines. (These approaches are explained further below). Existing powerful methods for mapping gene and gene product expression are summarized in Table 4, and are divided into gene- (and gene product) based and cell- (and region) based approaches. In situ hybridization is an example of a gene-based method for gene expression analysis. Such methods make it possible to detect a single gene product (e.g. a particular mRNA) in a very large number of cells in brain slices. A complementary approach is, however, provided by cell- (and region-) based methods of analysis. Such methods involve isolating small brain regions or, in the limit, specific neuronal populations or even single cells, extracting mRNA from these cells, and subjecting them to gene expression analysis using DNA arrays or other methods (such as direct cDNA library sequencing). These methods make it possible to detect a very large number (thousands) of gene products in a small number of cells. Table 4: Methods to Map Genes and Gene Products to Neurons
Gene-based and cell-based approaches are complementary, with different advantages and disadvantages. Thus, gene-based approaches give broad coverage of all brain regions but often with more limited cellular resolution. Cell-based approaches can provide high cellular resolution and give information on the complete set of transcripts expressed by a cell, but their throughput is lower and they are more difficult to apply to the human brain. Both types of approaches are needed. The utility of cell-based approaches is limited by the ability to isolate and to purify particular neuronal populations (for approaches based on cell isolation), or to recognize particular populations in tissue sections (in the case of laser capture microdissection). Some select populations of neurons can be purified based on physical characteristics, such as size, through the use of probes (such as antibodies) directed against particular cell surface epitopes, or by using fluorescent markers injected into the termination sites of the neurons' axons, which are taken up by the axons and retrogradely transported. However, these approaches are currently applicable only to small numbers of neurons. More general approaches to isolating particular populations of neurons involve transgenic approaches in which expression of a genetically-encoded reporter, such as the Green Fluorescent Protein (GFP) or some other molecular tag is driven in the neurons of interest in transgenic mice. The neurons can then be recognized and purified by some other method that makes use of the reporter tag, e.g. by Fluorescence Activated Cell Sorting using GFP fluorescence. (In principle, the molecular tagging of neurons should also permit their identification in tissue sections for laser-capture microdissection; current laser-capture methods are not readily compatible with such molecular tagging, although it can be expected that this technical problem will be solved before long). The transgenic labeling approaches require the ability to drive reporter expression in the cells. This is usually done by first identifying a particular marker gene expressed in the neurons of interest; the marker must be specific for those cells - at least in a particular region of brain that can be isolated through dissection from any other regions where the marker is expressed. Once an adequate marker gene is identified, the generation of a transgenic mouse in which the reporter is expressed from the marker gene locus is currently achieved primarily by three methods. The ability to deliver constructs selectively to particular neuronal populations is so important to generating and exploiting a Molecular Brain Map that a high priority should be assigned to generating the tools (such as BACs and promoter elements) that will make this possible (Table 2). In addition to allowing the marking and isolation of particular populations of neurons, these tools make it possible to deliver other transgenic constructs to the neurons, which facilitates identifying patterns of neuronal connections, and monitoring and manipulating electrical activity, and manipulating neuronal function. There are significant limitations on existing genetically encoded constructs for tracing connections and monitoring and manipulating neuronal activity, so that exploiting the Molecular Brain Map fully will require improving both sets of technologies (Table 3).
Top of PagePart III: Requirements of a Molecular Brain MapWith this background, we now discuss what needs to be discovered.
We first discuss the challenges involved in establishing a Molecular Brain Map for the normal adult mouse brain. We focus on the mouse because its brain is highly analogous in structure and organization to the human brain, but at the same time it is readily amenable to manipulation of gene activity and function in a manner not yet possible in species more closely related to humans. These properties have made the mouse the key model organism for molecular studies of brain function and dysfunction, and there was consensus at the workshop on the need to give highest priority to generating a mouse Map. A comprehensive Molecular Brain Map should provide the pattern of expression of all genes in all neurons throughout the brain, and involves the following component parts. One specific initiative in proteomics deserves mention and high priority at this time: the generation of antibodies to transcription factors. It is estimated that there are approximately 1,500 transcription factors encoded in the genome. The identity of particular neural cell types is controlled by combinatorial expression of specific transcription factors, and the availability of antibody probes to detect transcription factors in histological sections of the brain will accelerate attempts to identify neural cells, including neural stem cells, and to devise means to alter the development and fate of these cells for neural repair. Furthermore, transcription factors as a class have proven in general to be readily amenable to the generation antibodies that work in immunohistochemistry, whereas many other important classes of proteins (e.g. G protein-coupled receptors) are often more refractory. The combination of importance and ease justifies giving priority to the generation of antibodies to transcription factors (Table 2). From this description, it is evident that the development of a comprehensive Molecular Brain Map will be an iterative process, as information from gene-based and cell-based approaches accumulates and is incorporated into an ever more refined Atlas incorporating information not just about the locations of cells but also about their interconnectivity and function. In particular, it can be expected that in many cases what is thought of as a single homogeneous class of neurons defined by expression of a particular maker gene will, on further analysis, be discovered to comprise two or more subpopulations. Such refinements, subdivisions and reinterpretations are expected, and will be facilitated by the integration of information obtained from gene-based and cell-based approaches, and the integration of that information with other anatomical and functional data. As part of this refinement process, more accurate cell-type specific markers are likely to be defined that will permit gene manipulation in particular populations of neurons with high selectivity. A single Molecular Brain Map of the adult mouse brain would already provide an invaluable tool, dramatically accelerating the pace of discovery by freeing individual investigators of the need to derive the information in a piecemeal and inefficient way. However, the full utility of the Map will be evident only as a variety of Maps are generated to document gene expression in different species, developmental stages, and disease conditions.
Top of PagePart IV: Existing Large Scale Efforts Funded by the NIHThe NIH recognized the need for a Molecular Brain Map in the 1990s. Many pilot efforts have been funded to further the development of this Map, and are not described here because of space constraints. Three large-scale efforts funded at high levels by various Institutes of the NIH are, however, discussed in detail in Appendix 1 and introduced briefly here.
This resource and dataset, created by Dr. Bento Soares (University of Iowa) complements the Genome Projects in helping identify transcripts and splice-variants of genes expressed in the brain, and in generating cDNA libraries and full-length cDNA/EST probes that can facilitate analysis of these genes. The GENSAT project, initiated by Drs. Gabrielle Leblanc, Bob Baughman, and colleagues at NINDS, aims to systematically map the expression patterns of thousands of genes in histological sections of the mouse brain and spinal cord in the adult and at three stages of development (E10.5, E15.5, and P7). The gene expression data are being collected by two groups of investigators, one led by Dr. Gregor Eichele (Baylor College of Medicine and Max Planck Institute, Hannover), and another led by Drs. Nathaniel Heintz, Mary-Beth Hatten (Rockefeller University) and Alexandra Joyner (New York University). Dr. Eichele's group is collecting data using high throughput in situ hybridization, whereas Dr. Heintz's group is using BAC (bacterial artificial chromosome) transgenic technology. In the latter approach, transgenic mouse lines are generated in which expression of a reporter, Green Fluorescent Protein (GFP) is driven in the same patterns as selected genes. The gene expression data from both efforts is to be placed in a public database at the National Center for Biotechnology Information (NCBI). The project is collecting data for 300 genes in its first year, and aims to ramp up to at least a thousand genes per year in future years. Dr. Arthur Toga of the University of California at Los Angeles and his colleagues have been developing computerized brain Atlases, and tools to map data obtained from gene expression analysis or other approaches (e.g. functional MRI) onto those Atlases. In the case of the mouse, the result is a formal computerized representation of the mouse brain, providing coordinates that define the diverse anatomical structures and landmarks. These projects are helping set the groundwork for accelerating the generation of comprehensive Molecular Brain Maps for the human and the mouse. Top of PagePart V: Goals and PrioritiesThe working group applauded existing large-scale efforts for the establishment of a Molecular Brain Map, and achieved broad consensus on the following priorities going forward, building on those initial efforts.
To be truly useful, the data generated by these approaches must be organized into a central data repository that is easily accessible to the community Ð the ÒGenbankÓ equivalent for brain gene expression. All data must be mapped onto a digital brain Atlas, accessible through graphical interfaces, that can integrate data from both quantitative gene expression analysis (such as that provided from DNA arrays) with histochemical data (immunostaining, in situ hybridization), and which is accessible for Òwhere isÓ and Òwhat is inÓ queries. The format must be user-friendly and make it straightforward for researchers who are focusing on a particular brain region (for instance, researchers interested in a particular region because of fMRI data implicating it in some cognitive task) to obtain clues to the function of the region from the data contained within the Map. The development of this database will require the establishment of standards for the organization and display of data, as well as standards for data collection that are compatible with the digital atlas framework of the database. The absence of such standards is severely limiting the utility of data that are already being generated by existing large-scale efforts. Various Institutes at the NIH have initiated discussions on setting these standards, and they should be encouraged to drive this process to completion as rapidly as possible, broadly involving the community in the process. The full impact of a Molecular Brain Map will be felt only if all data in the database is accessible to the scientific community at large. Standards for the timing of public release of data therefore need to be defined and implemented. Early release of data, for example on a quarterly basis or more frequently, is essential both to ensure access and to ensure quality control by the community. For example, data generated in large-scale efforts funded by NIH and described in Part IV should be released to the scientific community according to these standards. There was consensus on the need to develop novel technologies to allow the Molecular Brain Map to be leveraged to its fullest. The first priority is to develop a bank of specific promoters and modified BACs, to permit delivery of transgenes to specific neuronal populations, and the simultaneous improvement of efficient transgenic and/or viral delivery methods for gene delivery in species other than mouse (including rats and primates). The impact of having this bank will be greatly increased by the further development of genetically encoded reporter and modulator constructs to allow: (i) the marking and isolation of neurons, (ii) the tracing of all connections made by a neuron, (iii) the persistent or time-lapse labeling of connections, to help identify plastic changes in connections (iv) the detection of electrical activity in neurons by optical and other means, and (v) the controlled modulation of electrical activity in specific neuronal populations (e.g. by expression of an ion channel that can be gated by a specific pharmacological agent or by light). The latter two applications in particular will help define the function of particular neurons and neuronal circuits. Finally, whereas the analysis of gene transcripts (mRNAs) in neurons is amenable to high-throughut analysis today and hence should be the initial focus of effects to construct Molecular Brain Maps, the characterization of protein products and their subcellular localization, i.e. the proteomic characterization of neurons, is an essential longer term goal that will rely on improvements in proteomic analysis methods throughout the biomedical community. As discussed, one proteomic initiative that deserves priority at this time is the generation of antibodies to transcription factors. These tools, reagents and methods are summarized in Tables 2 and 3. The successful development of a Molecular Brain Map will require a concerted and large-scale effort. It is therefore imperative that an ongoing Working Group be established, comprising members of the scientific community as well as granting agencies, to monitor developments and continually define and refine priorities for molecular neuroanatomy. The collection of initiatives required to generate and leverage a series of Molecular Brain Maps require a mix of funding initiatives. Some aspects, such as the high throughput generation, collection, and collation of gene expression data, will benefit greatly from large-scale integrated funding initiatives. Others, such as the development of tools to leverage the Molecular Brain Maps, will continue to benefit from smaller-scale individual investigator initiated projects. Both types of funding initiatives should be supported by the NIH.
Top of PageAppendix 1: Existing Large-Scale EffortsVarious institutes at the NIH recognized the need for a Molecular Brain Map in the 1990s. Many small-scale efforts have been funded to further the development of this Map, and are not described here in the interests of space. Several large-scale efforts funded at high levels by various Institutes of the NIH are, however, discussed.
Under contract to the NIMH, Dr. Bento Soares (University of Iowa) has undertaken the generation of cDNA libraries from mouse brain regions, and the direct sequencing of cDNAs from these libraries, in an effort to identify all transcripts expressed in the brain. In phase I, completed in the year 2000, a non-redundant collection comprising approximately 30,000 brain and 9,000 retina cDNAs/ESTs was identified, re-arrayed, sequence verified and made publicly available. In phase II, initiated in September 2001, cDNA libraries enriched in full-length transcripts are being generated from whole brain and eyes at various developmental stages, and sequenced. The identification of all transcripts has, of course, been greatly accelerated by the sequencing of the human and mouse genomes. Dr. Soares's project was initiated before it was clear how long the sequencing of the human and mouse genomes would take. It still remains complementary to the genome sequencing projects in important ways. First, programs for identifying individual genes from genomic sequence remain imperfect, so that cDNA sequencing efforts continue to provide valuable information on the identity of individual genes. Second, direct sequencing of cDNAs also provides important information on the usage of alternative exons of particular genes (alternative splicing and promoter usage) that is not always easily inferred from genomic sequence. Finally, the project also provides a physical series of cDNA probes for each of the genes that is identified. As part of NINDS's GENSAT project, Dr. Gregor Eichele (Baylor College and Max Planck Institute, Hannover) and his colleagues have undertaken an effort to map gene expression through high-throughput in situ hybridization. This has involved the development of a robot for performing reproducible in situ hybridization analysis on sections of adult or embryonic brain, which will in the first instance provide a collection of brain sections on microscope slides on which the pattern of expression of individual genes is visualized with a histochemical reaction product. The aim of the project, in the first instance, is to map expression of over one thousand genes per year to the adult mouse brain and the developing brain (at E10.5, E15.5, and P7) Also under the auspices of NINDS's GENSAT project, a consortium of Dr. Nathaniel Heinz, Dr. Mary-Beth Hatten and Dr. Alex Joyner (Rockefeller University and New York University) and their colleagues has undertaken to use BAC (bacterial artificial chromosome) transgenic technology to map gene expression in the brain. In this approach, for each gene a transgenic mouse is generated in which the reporter GFP (green fluorescent protein) is expressed in a pattern mimicking that of the starting gene. This is achieved by isolating a bacterial artificial chromosome (BAC) containing the gene locus of interest (including its regulatory regions), recombining a GFP cDNA into the locus, and creating a transgenic mouse containing the modified BAC. At high frequency, expression of GFP in such mice is representative of expression of the endogenous gene. The aim of the project is to ramp up to the production of about a thousand modified BACs per year, which are then used to generate transgenic mouse lines, followed by visualization of GFP in a select series of sections from adult brains, and collection of images with this information. This approach is complementary to the in situ hybridization approach in (a). It is slower to make the modified BACs and transgenic mouse lines than simply to perform in situ hybridization. However, the GFP signal, unlike the in situ hybridization signal, can often give more information on the particular cell type expressing the gene because the morphology of the cell and its pattern of projections often provides a unique identifier of the cell. In addition, the modified BAC construct in principle provides a valuable tool that can be used by other investigators in transgenic mouse lines to mark cells expressing the gene or to deliver other gene-modifying constructs to those cells for functional studies in transgenic mice. Under a grant supported by NIMH, NINDS, NIDA, NIA, NIAAA, and NIDCD, Dr. Arthur Toga of the University of California at Los Angeles, Dr. Russell Jacobs at the California Institute of Technology, Dr. Larry Swanson of the University of Southern California, and their colleagues, have been developing computerized brain Atlases and tools to map data obtained from gene expression analysis or other approaches (e.g. connectional data, structural or functional MRI data, immunocytochemical data, chemo- or cytoarchitectural data, etc. ) onto those Atlases. In the case of the mouse, the result is a formal computerized representation of the mouse brain, providing a systematic and comprehensive digital space with links between a coordinate system and systems of nomenclature for the structural subdivisions of the nervous system. In addition, tools have been developed to map information derived from brain sections onto this three-dimensional Atlas, making it possible to correct for distortions of brain tissue that occur during various histological procedures to visualize gene expression. Such Atlases are being developed for adult mice and mice of specific ages through development. Similarly, an Atlas of the human brain has been devised, and software tools generated to import information derived from multiple modalities (e.g. fMRI) and map it onto the Atlas. Top of Page |
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