Unlocking CNS Cell Type Heterogeneity
2008; Cell Press; Volume: 135; Issue: 4 Linguagem: Inglês
10.1016/j.cell.2008.10.031
ISSN1097-4172
Autores Tópico(s)Neuroscience and Neuropharmacology Research
ResumoA major challenge to understanding how cells work together in the central nervous system (CNS) is the heterogeneous cellular composition of the brain. In this issue, Heiman et al., 2008Heiman M. Schaefer A. Gong S. Peterson J. Day M. Ramsey K.E. Suarez-Farinas M. Schwarz C. Stefan D.A. Surmeier J. et al.Cell. 2008; (this issue)Google Scholar and Doyle et al., 2008Doyle J.P. Dougherty J.D. Heiman M. Schmidt E.F. Stevens T.R. Ma G. Bupp S. Shrestha P. Shah R.D. Doughty M.L. et al.Cell. 2008; (this issue)PubMed Google Scholar introduce a new strategy (TRAP) that enables the profiling of translated mRNAs in specific CNS cell populations without the need for purifying cells to homogeneity. A major challenge to understanding how cells work together in the central nervous system (CNS) is the heterogeneous cellular composition of the brain. In this issue, Heiman et al., 2008Heiman M. Schaefer A. Gong S. Peterson J. Day M. Ramsey K.E. Suarez-Farinas M. Schwarz C. Stefan D.A. Surmeier J. et al.Cell. 2008; (this issue)Google Scholar and Doyle et al., 2008Doyle J.P. Dougherty J.D. Heiman M. Schmidt E.F. Stevens T.R. Ma G. Bupp S. Shrestha P. Shah R.D. Doughty M.L. et al.Cell. 2008; (this issue)PubMed Google Scholar introduce a new strategy (TRAP) that enables the profiling of translated mRNAs in specific CNS cell populations without the need for purifying cells to homogeneity. Understanding how myriad different cell types in the brain communicate to give rise to cognition and perception is the central challenge of neurobiology today. One powerful method for helping to understand how cells communicate is genome-wide gene profiling. However, because of the large degree of cellular heterogeneity, the mammalian central nervous system (CNS) poses particular challenges for gene profiling. Not only is the CNS composed of multiple distinct and often ill-defined regions, but each of these regions also consists of multiple cell types, many of which are rare and contribute only a small fraction of mRNAs to the total pool of transcripts. Although ambitious projects such as the Allen and GENSAT brain atlases that map gene expression patterns in the brain have provided invaluable information about the spatial expression of large numbers of genes within the CNS, the exact identities of the cells expressing the genes are not always evident. Moreover, these databases cannot hope to be comprehensive in capturing the gene expression changes that occur in different CNS cell populations in various disease states or experimental scenarios. A variety of clever strategies have been successfully applied to profile gene expression using mRNAs isolated from highly purified populations of specific CNS cell types. These methods have taken advantage of transgenic mice expressing fluorescent proteins in the specific CNS population of interest or the use of retrograde tracer marking to label specific populations (Arlotta et al., 2005Arlotta P. Molyneaux B.J. Chen J. Inoue J. Kominami R. Macklis J.D. Neuron. 2005; 45: 207-221Abstract Full Text Full Text PDF PubMed Scopus (743) Google Scholar, Sugino et al., 2006Sugino K. Hempel C.M. Miller M.N. Hattox A.M. Shapiro P. Wu C. Huang Z.J. Nelson S.B. Nat. Neurosci. 2006; 9: 99-107Crossref PubMed Scopus (417) Google Scholar, Lobo et al., 2006Lobo M.K. Karsten S.L. Gray M. Geschwind D.H. Yang X.W. Nat. Neurosci. 2006; 9: 443-452Crossref PubMed Scopus (297) Google Scholar, Dugas et al., 2008Dugas J.C. Mandemakers W. Rogers M. Ibrahim A. Daneman R. Barres B.A. J. Neurosci. 2008; 28: 8294-8305Crossref PubMed Scopus (83) Google Scholar, Cahoy et al., 2008Cahoy J.D. Emery B. Kaushal A. Foo L.C. Zamanian J.L. Christopherson K.S. Xing Y. Lubischer J.L. Krieg P.A. Krupenko S.A. et al.J. Neurosci. 2008; 28: 264-278Crossref PubMed Scopus (2012) Google Scholar). Although these techniques have yielded much useful information, they share several potential disadvantages, including the concern that the act of isolating the cells may alter their transcriptional profile. Moreover, depending on the cell type in question, isolation of specific cells to a suitable level of homogeneity can be cumbersome, thus making repeated or parallel cell type isolations to assess transcriptional changes under different experimental conditions unfeasible. In this issue, two complementary studies (Heiman et al., 2008Heiman M. Schaefer A. Gong S. Peterson J. Day M. Ramsey K.E. Suarez-Farinas M. Schwarz C. Stefan D.A. Surmeier J. et al.Cell. 2008; (this issue)Google Scholar, Doyle et al., 2008Doyle J.P. Dougherty J.D. Heiman M. Schmidt E.F. Stevens T.R. Ma G. Bupp S. Shrestha P. Shah R.D. Doughty M.L. et al.Cell. 2008; (this issue)PubMed Google Scholar) present an elegant new technique, called translating ribosome affinity purification (TRAP), for determining the translational profiles of specific cell types within the brain. The GENSAT Project (http://www.gensat.org/) database contains a gene expression atlas of the central nervous system of the mouse based on bacterial artificial chromosomes (BACs). BAC mouse lines are made with BAC transgenic vectors in which the endogenous protein coding sequences of a gene of interest have been replaced by the sequence for enhanced green fluorescent protein (EGFP), thus putting EGFP under the control of the normal regulatory sequences of the gene of interest. This EGFP reporter is integrated in the mouse, and EGFP is expressed in the same spatial and temporal pattern as the endogenous protein of interest (Gong et al., 2003Gong S. Zheng C. Doughty M.L. Losos K. Didkovsky N. Schambra U.B. Nowak N.J. Joyner A. Leblanc G. Hatten M.E. Nature. 2003; 425: 917-925Crossref PubMed Scopus (1498) Google Scholar, Heintz, 2004Heintz N. Nat. Neurosci. 2004; 7: 483Crossref PubMed Scopus (218) Google Scholar). Heiman et al. and Doyle et al. have now created new bacTRAP mouse lines in which the BAC vectors all encode an EGFP-tagged L10a ribosomal protein within specific CNS cell types. Affinity purification of this EGFP-L10a fusion protein with anti-EGFP antibodies thus yields the ribosome and its associated mRNAs, allowing the isolation of transcripts from the EGFP-L10a-expressing cell type of interest (Figure 1). This is an enhancement of a technique previously used in the worm Caenorhabditis elegans in which the targeted expression of epitope-tagged poly(A)-binding protein enabled purification of bound RNA from cell types of interest for gene profiling (e.g., Roy et al., 2002Roy P.J. Stuart J.M. Lund J. Kim S.K. Nature. 2002; 418: 975-979Crossref PubMed Scopus (3) Google Scholar). As a demonstration of what can be done with this new method, Heiman et al. generated BAC mouse lines expressing the EGFP-L10a ribosomal protein from the D1 or D2 dopamine receptor promoters in striatonigral and striatopallidal medium spiny neurons (MSNs), respectively. The immunoaffinity-purified mRNAs from each mouse line not only were enriched for almost all of the previously reported differentially expressed MSN markers, but also revealed numerous new striatopallidal- or striatonigral-enriched transcripts. Importantly, Heiman et al. also demonstrated that this technique is sufficiently sensitive to detect translational changes in cell populations after an experimental manipulation (cocaine administration). The two neuronal populations responded differently to cocaine administration, leading to new experimentally testable predictions for molecular responses to this molecule. Doyle et al. further extended the use of the technique by reporting the transgene expression patterns for the four EGFP-L10a bacTRAP mouse lines described in the Heiman et al. study. They also describe an additional 12 bacTRAP mouse lines targeting the EGFP-L10a ribosomal transgene to a variety of different neuronal and glial populations. Using these bacTRAP transgenic mouse lines and dissection of different CNS regions, Doyle et al. report the translational profiles of 24 CNS cell types, including astrocytes, oligodendrocytes, and different types of neurons. The TRAP approach offers several advantages that distinguish it from current methods. The most obvious of these may be its relative experimental simplicity, as it makes laborious and technically challenging cell isolation procedures unnecessary. Even relatively rare cell types such as the unipolar brush cells of the cerebellum can now be readily studied. In addition, this method greatly enhances the ability to generate reproducible results. Doyle et al. demonstrate that results from different mouse lines with the same BAC transgene are highly consistent. Needless to say, selection of the appropriate bacTRAP line that correctly represents the cell type of interest is essential. Finally, the TRAP technique makes it possible to profile the gene expression patterns of specific cell types in adult mouse neural tissues. In contrast, fluorescence-activated cell sorting (FACS)—a method currently used to purify the same cell types—generally requires the use of early postnatal mice. TRAP provides an exciting step forward because it means that specific neural cell types can now be profiled in adult mouse models of neurological disease. An intriguing aspect to the TRAP approach is that it targets translated RNAs rather than total mRNAs and is thus possibly a better reflection of protein expression. Through comparison of TRAP profiles with profiles obtained with total mRNAs, it may be possible to identify mRNAs that are under strong translational control. That said, at least some supposedly untranslated mRNAs, such as those encoding the neuronal protein Gap43 and the glial prion protein Prnp, are highly represented in the TRAP data sets, suggesting that some translationally inhibited mRNAs remain bound to ribosomes. On the other hand, noncoding RNAs such as Gtl2 that are never translated are not detectable in the TRAP-bound samples, although they can be detected by standard gene profiling methods. One potential caveat of the TRAP technique is that during preparation of the tissue lysate (Figure 1), mixing of mRNAs between all of the cell types occurs, providing an opportunity for mRNAs from unwanted cell types to bind to the EGFP-L10a-tagged ribosomes. Fortunately, use of conditions that stabilize mRNA binding to ribosomes minimizes this problem. Indeed, for the most part, the TRAP gene profiles for glia are strikingly similar to those previously elucidated for purified astrocytes and oligodendrocytes (Cahoy et al., 2008Cahoy J.D. Emery B. Kaushal A. Foo L.C. Zamanian J.L. Christopherson K.S. Xing Y. Lubischer J.L. Krieg P.A. Krupenko S.A. et al.J. Neurosci. 2008; 28: 264-278Crossref PubMed Scopus (2012) Google Scholar; B.A.B., unpublished data). One interesting difference resides in the relative levels of expressed mRNAs, which vary widely between the two methods. It is not yet clear whether this difference reflects physiological differences in the samples used (for example, the age of the CNS tissue) or whether it reflects variables in experimental conditions, such as the efficiency of affinity purification. Regardless, the possibilities offered by the TRAP approach seem limitless, as it can theoretically be applied to any cell type, in any tissue, under any condition. In particular, the applications of TRAP analysis for understanding neurological disease will be an exciting area for future exploration. A Translational Profiling Approach for the Molecular Characterization of CNS Cell TypesHeiman et al.CellNovember 14, 2008In BriefThe cellular heterogeneity of the brain confounds efforts to elucidate the biological properties of distinct neuronal populations. Using bacterial artificial chromosome (BAC) transgenic mice that express EGFP-tagged ribosomal protein L10a in defined cell populations, we have developed a methodology for affinity purification of polysomal mRNAs from genetically defined cell populations in the brain. The utility of this approach is illustrated by the comparative analysis of four types of neurons, revealing hundreds of genes that distinguish these four cell populations. Full-Text PDF Open ArchiveApplication of a Translational Profiling Approach for the Comparative Analysis of CNS Cell TypesDoyle et al.CellNovember 14, 2008In BriefComparative analysis can provide important insights into complex biological systems. As demonstrated in the accompanying paper, translating ribosome affinity purification (TRAP) permits comprehensive studies of translated mRNAs in genetically defined cell populations after physiological perturbations. To establish the generality of this approach, we present translational profiles for 24 CNS cell populations and identify known cell-specific and enriched transcripts for each population. We report thousands of cell-specific mRNAs that were not detected in whole-tissue microarray studies and provide examples that demonstrate the benefits deriving from comparative analysis. Full-Text PDF Open Archive
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