Latest Articles Include:
- Focus on epigenetics
- Nat Neurosci 13(11):1299 (2010)
We present a special focus on epigenetics in the nervous system, highlighting recent advances in our understanding of epigenetic mechanisms and their regulation in neurons, as well as their role in nervous system function. - Taking animal rights personally
- Nat Neurosci 13(11):1301 (2010)
Nowadays it is certainly impossible to write any book about animal rights and animal welfare without raising the ire of a subset of readers. An Odyssey with Animals by Adrian Morrison, a professor of behavioral neuroscience at the University of Pennsylvania's School of Veterinary Medicine, is likely to be no exception. - Bringing SOD1 into the fold
- Nat Neurosci 13(11):1303-1304 (2010)
Could similar changes in superoxide dismutase 1 (SOD1) underlie both familial and sporadic amyotrophic lateral sclerosis (ALS)? A new study finds that wild-type SOD1 from sporadic ALS tissues shows conformational changes similar to those seen in familial ALS and may be pathogenic as a result of the same mechanism. - Categorizing speech
- Nat Neurosci 13(11):1304-1306 (2010)
Using direct electrode recordings in patients undergoing preoperative surgery, a new study demonstrates that neural responses in the secondary auditory cortex mirror perception, showing categorical responses to continuous stimuli. - "Yes! We're all individuals!": redundancy in neuronal circuits
- Nat Neurosci 13(11):1306-1307 (2010)
In the mouse olfactory bulb, cells with common input respond to odors with similar firing rates but with different timing. This suggests that such 'sister' cells make independent and unique connections with local interneurons. - Making glutamatergic neurons from GABAergic progenitors
- Nat Neurosci 13(11):1308-1309 (2010)
The mature phenotype of CNS neurons is thought to be set at an early progenitor stage. A study now shows that expression of Fezf2 alone can turn striatal GABAergic precursors into glutamatergic corticofugal neurons. - I see where you're hearing: how cross-modal plasticity may exploit homologous brain structures
- Nat Neurosci 13(11):1309-1311 (2010)
Sensory deprivation such as deafness or blindness leads to specific functional and neural reorganization. A new study gives insight into why and how certain abilities change, while others remain unaltered after the loss of a sense. - The importance of degradation
- Nat Neurosci 13(11):1311 (2010)
Neural stem cells can either self-renew, or differentiate into neurons, astrocytes and oligodendrocytes. How and why this decision is made is unclear. - Epigenetic regulation of the neural transcriptome: the meaning of the marks
- Nat Neurosci 13(11):1313-1318 (2010)
Nature Neuroscience | Commentary Neurodegeneration Focus issue: November 2010 Volume 13, No 11 * * Commentary * Perspectives * Reviews * * Contents * Library * Editorial Epigenetic regulation of the neural transcriptome: the meaning of the marks * Michael J Meaney1, 3michael.meaney@mcgill.ca Search for this author in: * NPG journals * PubMed * Google Scholar * Anne C Ferguson-Smith2, 3 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Corresponding authorJournal name:Nature NeuroscienceVolume: 13 ,Pages:1313–1318Year published:(2010)DOI:doi:10.1038/nn1110-1313Published online26 October 2010 Abstract * Abstract * Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The field of epigenetics provides neurobiologists with candidate mechanisms for experience-dependent changes in gene transcription. The ability to realize the potential of epigenetics in defining the causal pathways lying between environmental signals, transcriptional regulation and neural function will depend on moving beyond correlational studies focusing on individual epigenetic marks. Here we attempt to provide a conceptual framework for integrative research on nucleotide sequence, chromatin modifications, RNA signaling and their interactions in understanding experience-dependent phenotypic plasticity. Studies in genomic imprinting may serve as an existing model for such approaches. View full text Author information * Abstract * Author information Affiliations * Michael J. Meaney is in the Sackler Program for Epigenetics & Psychobiology at McGill University, Douglas Hospital Mental Health University Institute, McGill University, Montreal, Quebec, Canada, and * Anne C. Ferguson-Smith is in the Department of Physiology, Development, and Neuroscience, University of Cambridge, Cambridge, UK. * Both authors are at the Singapore Institute for Clinical Sciences, Singapore. * Michael J Meaney & * Anne C Ferguson-Smith Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Michael J Meaney (michael.meaney@mcgill.ca) Additional data - DNA methylation and memory formation
- Nat Neurosci 13(11):1319-1323 (2010)
Nature Neuroscience | Perspective Neurodegeneration Focus issue: November 2010 Volume 13, No 11 * * Commentary * Perspectives * Reviews * * Contents * Library * Editorial DNA methylation and memory formation * Jeremy J Day1 Search for this author in: * NPG journals * PubMed * Google Scholar * J David Sweatt1dsweatt@uab.edu Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Corresponding authorJournal name:Nature NeuroscienceVolume: 13 ,Pages:1319–1323Year published:(2010)DOI:doi:10.1038/nn.2666Published online26 October 2010 Abstract * Abstract * Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Memory formation and storage require long-lasting changes in memory-related neuronal circuits. Recent evidence indicates that DNA methylation may serve as a contributing mechanism in memory formation and storage. These emerging findings suggest a role for an epigenetic mechanism in learning and long-term memory maintenance and raise apparent conundrums and questions. For example, it is unclear how DNA methylation might be reversed during the formation of a memory, how changes in DNA methylation alter neuronal function to promote memory formation, and how DNA methylation patterns differ between neuronal structures to enable both consolidation and storage of memories. Here we evaluate the existing evidence supporting a role for DNA methylation in memory, discuss how DNA methylation may affect genetic and neuronal function to contribute to behavior, propose several future directions for the emerging subfield of neuroepigenetics, and begin to address some of the broader implicat! ions of this work. View full text Figures at a glance * Figure 1: DNA methylation. () Inside a cell nucleus, DNA is wrapped tightly around an octamer of highly basic histone proteins to form chromatin. Epigenetic modifications can occur at histone tails or directly at DNA via () DNA methylation occurs at cytosine bases when a methyl group is added at the 5′ position on the pyrimidine ring by a DNMT. () Two types of DNMTs initiate De novo DNMTs methylate previously nonmethylated cytosines, whereas maintenance DNMTs methylate hemi-methylated DNA at the complementary strand. * Figure 2: Potential mechanism for demethylation of methylated DNA. Methylated DNA is deaminated and converted to thymine. Base or nucleotide excision repair processes are then able to replace thymine with unmethylated cytosine. It is unclear how this potential mechanism would affect methylation status on the complementary DNA strand. * Figure 3: Putative actions of cell-wide DNA methylation changes on neuronal function. Changes in DNA methylation could induce a state change (left) that alters responsivity to existing inputs and acts permissively to enable other long-term changes that are ultimately responsible for memory. Altered patterns of DNA methylation could also directly or indirectly alter gene expression and contribute to changes in synaptic strength that are thought to underlie the formation and maintenance of memories (center). Alternatively, changes in methylation status in a cell may act to render it aplastic, in effect stabilizing the current synaptic weights and responsivity (right). Critically, these changes may occur in different brain regions or at different time points as part of the overall process of learning, memory consolidation and memory maintenance. It is important to note that the changes in DNA methylation driving altered neuronal function are likely to occur at a small subset of the total methylation sites in the cell so that the overall neuronal phenotype is pre! served. It also is worth considering that because the methyl-DNA binding proteins do not effectively recognize hemi-methylated DNA, hemi-demethylation of DNA is likely to be just as effective as double-stranded demethylation at triggering functional changes in the neuron. Author information * Abstract * Author information Affiliations * Department of Neurobiology and Evelyn F. McKnight Brain Institute, University of Alabama at Birmingham, Birmingham, Alabama, USA. * Jeremy J Day & * J David Sweatt Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * J David Sweatt (dsweatt@uab.edu) Additional data - Plasticity and specificity of the circadian epigenome
- Nat Neurosci 13(11):1324-1329 (2010)
Nature Neuroscience | Perspective Neurodegeneration Focus issue: November 2010 Volume 13, No 11 * * Commentary * Perspectives * Reviews * * Contents * Library * Editorial Plasticity and specificity of the circadian epigenome * Selma Masri1 Search for this author in: * NPG journals * PubMed * Google Scholar * Paolo Sassone-Corsi1psc@uci.edu Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Corresponding authorJournal name:Nature NeuroscienceVolume: 13 ,Pages:1324–1329Year published:(2010)DOI:doi:10.1038/nn.2668Published online26 October 2010 Abstract * Abstract * Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Circadian clocks control a variety of neuronal, behavioral and physiological responses, via transcriptional regulation of an appreciable portion of the genome. We describe the complex communication network between the brain-specific central clock and the tissue-specific peripheral clocks that serve to synchronize the organism to both external and internal demands. In addition, we discuss and speculate on how epigenetic processes are involved in creating transcriptional environments that are permissive to tissue-specific gene expression programs, which work in concert with the circadian machinery. Accumulating data show that chromatin remodeling events may be critical for providing specificity and plasticity in circadian regulation, and metabolic cues may be involved in directing such epigenetic events. A detailed understanding of the communication cues between the central and peripheral clocks is crucial for a more complete understanding of the circadian system and the sever! al levels of control that are implicated in maintaining biological timekeeping. View full text Figures at a glance * Figure 1: The circadian CLOCK network. The core circadian transcription factors, CLOCK and BMAL1, direct E-box–mediated transcription of clock-controlled genes (CCGs), including activators and repressors of the circadian system. PER and CRY protein translation occssurs at night and subsequently causes repression of the core CLOCK:BMAL1 transcriptional complex. Degradation of the repressors PER and CRY prompts a new circadian cycle whereby CLOCK:BMAL1 transcription is reinitiated. In addition to transcriptional regulation, post-translational modifications are crucial for the modulation of circadian proteins. The figure shows only phosphorylation, which can be elicited by several kinases, including CKIε, CKIδ, CK2α, GSK3β and AMPK. Other post-translational modifications of clock proteins include acetylation, sumoylation and ubiquitination. RRE, REV-ERB/ROR response element. * Figure 2: What underlies the different genomic responses of central versus peripheral clocks? Approximately 10% of transcripts in a given tissue show circadian expression. Within all oscillatory transcripts in each tissue (here schematically represented as a circle for SCN, liver and muscle), only ~5–10% are common between two given tissues, and that fraction decreases sharply when intersecting more than two tissues (the yellow area in the middle of the circles)12, 19, 20, 21, 22. These differences can be accounted by the contribution of tissue-specific transcription factors (TFs) that interact with the circadian machinery (here simplistically represented by the CLOCK:BMAL1 complex). The differential composition of these complexes in different tissues and circadian times might bestow selectivity of recruitment to chromatin loci corresponding to promoters of clock-controlled genes (CCGs). * Figure 3: Chromatin remodeling and the circadian clock. Directed chromatin-modifying events responsible for rhythmic CCG transcription comprise a major portion of the circadian epigenome. Our current understanding of post-translational modifications of the H3 tail suggests that phosphorylation (Ser10), acetylation (Lys9 and Lys14) and methylation (Lys4 and Lys27) are associated with circadian transcription. Some chromatin modifiers may be directly or indirectly modulated by the circadian system. Acetylation (Ac) of non-histone proteins can also occur in a clock-dependent manner; this is the case for BMAL1 (ref. 38) and the glucocorticoid receptor24. The involvement of the NAD+-dependent deacetylase SIRT1 in circadian control and its physical interaction with CLOCK revealed a link between circadian clock and cellular metabolism30, 39. The metabolic state of the cell has a robust effect on epigenetic control, and some metabolic cues have been found to oscillate. Author information * Abstract * Author information Affiliations * Department of Pharmacology, U904 INSERM 'Epigenetics and Neuronal Plasticity', School of Medicine, University of California, Irvine, California, USA. * Selma Masri & * Paolo Sassone-Corsi Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Paolo Sassone-Corsi (psc@uci.edu) Additional data - Dynamic epigenetic regulation in neurons: enzymes, stimuli and signaling pathways
- Nat Neurosci 13(11):1330-1337 (2010)
Nature Neuroscience | Review Neurodegeneration Focus issue: November 2010 Volume 13, No 11 * * Commentary * Perspectives * Reviews * * Contents * Library * Editorial Dynamic epigenetic regulation in neurons: enzymes, stimuli and signaling pathways * Antonella Riccio1a.riccio@ucl.ac.uk Search for this author in: * NPG journals * PubMed * Google ScholarJournal name:Nature NeuroscienceVolume: 13 ,Pages:1330–1337Year published:(2010)DOI:doi:10.1038/nn.2671Published online26 October 2010 Abstract * Abstract * Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The development and function of neurons require the regulated expression of large numbers of very specific gene sets. Epigenetic modifications of both DNA and histone proteins are now emerging as fundamental mechanisms by which neurons adapt their transcriptional response to developmental and environmental cues. In the nervous system, the mechanisms by which extracellular signals regulate the activity of chromatin-modifying enzymes have just begun to be characterized. In this Review, I discuss how extracellular cues, including synaptic activity and neurotrophic factors, influence epigenetic modifications and regulate the neuronal transcriptional response. I also summarize additional mechanisms that induce chromatin remodeling events by combinatorial assembly of multiprotein complexes on neuronal gene promoters. View full text Figures at a glance * Figure 1: Activity-dependent epigenetic regulation. () Synaptic activity and depolarizing stimuli phosphorylate CBP and influence transcription by increasing intracellular Ca2+ through both NMDA receptors and L-type Ca2+ channels, although activation of CaMKIV is required only for the latter. The concomitant phosphorylation of histone H3 on serine-10 cooperates with histone acetylation (ac) to induce chromatin infolding and gene expression. Neural activity also induces the recruitment of CBP, CREB and the cofactor NPAS4 to transcriptional enhancers of synaptic activity-dependent genes. () In differentiated neurons, certain neuronal genes such as Bdnf are maintained in a repressed state through a mechanism that includes the recruitment of coREST, HDAC1, HDAC2 and MeCP2. After synaptic stimulation, HDAC2, and possibly HDAC1, are S-nitrosylated (SNO), whereas MeCP2 is phosphorylated, resulting in the dissociation of the co-repressor complex from gene regulatory regions and the recruitment of co-activators. ACT, activator; ORF, o! pen reading frame; PP1, protein phosphatase 1; RHA, RNA helicase A; TAbe, transcriptional activator binding element. * Figure 2: Epigenetic regulation by neurotrophins. Binding of neurotrophins to Trk receptors initiates a number of signaling pathways that induce phosphorylation of CREB and CBP. BDNF-dependent activation of nNOS increases nuclear NO and triggers S-nitrosylation (SNO) of several nuclear proteins, including HDAC2. The dissociation of S-nitrosylated HDAC2 and the recruitment of phosphorylated CBP and transcription factors such as CREB lead to transcriptional activation. Both phosphorylation of histone H3 through RSK2 and CBP-dependent histone acetylation (ac) contribute to gene activation. AC, adenylyl cyclase; ac, acetyl. * Figure 3: Composition of BAF complexes at different stages of neuronal differentiation. A number of subunits of the BAF complex are switched during neuronal differentiation (,). The subunits labeled undergo developmentally regulated switches, and most of them have been shown not to be exchangeable under various experimental conditions. () In postmitotic neurons, the association of BRG1 with the calcium-responsive factor CREST mediates synaptic activity–dependent dendrite outgrowth. Author information * Abstract * Author information Affiliations * Medical Research Council Laboratory for Molecular and Cell Biology and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK. * Antonella Riccio Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Antonella Riccio (a.riccio@ucl.ac.uk) Additional data - Epigenetic choreographers of neurogenesis in the adult mammalian brain
- Nat Neurosci 13(11):1338-1344 (2010)
Nature Neuroscience | Review Neurodegeneration Focus issue: November 2010 Volume 13, No 11 * * Commentary * Perspectives * Reviews * * Contents * Library * Editorial Epigenetic choreographers of neurogenesis in the adult mammalian brain * Dengke K Ma1 Search for this author in: * NPG journals * PubMed * Google Scholar * Maria Carolina Marchetto2 Search for this author in: * NPG journals * PubMed * Google Scholar * Junjie U Guo3, 4 Search for this author in: * NPG journals * PubMed * Google Scholar * Guo-li Ming3, 4, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Fred H Gage2 Search for this author in: * NPG journals * PubMed * Google Scholar * Hongjun Song3, 4, 5shongju1@jhmi.edu Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Corresponding authorJournal name:Nature NeuroscienceVolume: 13 ,Pages:1338–1344Year published:(2010)DOI:doi:10.1038/nn.2672Published online26 October 2010 Abstract * Abstract * Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Epigenetic mechanisms regulate cell differentiation during embryonic development and also serve as important interfaces between genes and the environment in adulthood. Neurogenesis in adults, which generates functional neural cell types from adult neural stem cells, is dynamically regulated by both intrinsic state-specific cell differentiation cues and extrinsic neural niche signals. Epigenetic regulation by DNA and histone modifiers, non-coding RNAs and other self-sustained mechanisms can lead to relatively long-lasting biological effects and maintain functional neurogenesis throughout life in discrete regions of the mammalian brain. Here, we review recent evidence that epigenetic mechanisms carry out diverse roles in regulating specific aspects of adult neurogenesis and highlight the implications of such epigenetic regulation for neural plasticity and disorders. View full text Figures at a glance * Figure 1: Basic modes of epigenetic regulation implicated in adult neurogenesis. () To initiate epigenetic processes, extracellular and intracellular signals may trigger epigenetic 'perpetuators' that form self-sustaining feedback loops or intrinsically produce long-lasting cellular effects in the absence of the initial trigger stimuli. Typical mechanisms by which this process occurs include transcription regulator and non-coding RNA–mediated feedback pathways, DNA methylation with associated methyl-binding proteins (MBDs), and histone H3K27 methylation with associated PcG (polycomb group) and TrxG (trithorax group) complexes. () DNA modifications. DNA methyltransferases (DNMTs) catalyze DNA methylation, whereas the pathway leading to DNA demethylation might include 5-methylcytosine (5mC) hydroxylase TET (ten-eleven translocation-1) proteins and DNA excision repair enzymes that are regulated by Gadd45 (growth arrest and DNA-damage-inducible) family proteins. () Histone modifications. Specific amino acid residues of histone N-terminal tails can be rever! sibly modified with a variety of 'tags' including acetylation (ac), phosphorylation (p), methylation (me), ubiquitination (ub), SUMOylation (su) and isomerization (iso). The varying turnover rates and biological interpreters of these modifications might execute different cellular functions for epigenetic regulation. C, cytosine; 5mC, 5-methylcytosines; 5hmC, 5-hydroxymethylcytosine; BER, base-excision repair; NER, nucleotide-excision repair; K, lysine; S, serine; T, threonine; R, arginine; P, proline; KAT, lysine acetyltransferase; HDAC, histone deacetylase; KMT, lysine methyltransferase; KDM, lysine deacetylase; PRMT, protein arginine methyltransferase; PADI4, peptidyl arginine deiminase type IV; JMJD6, Fe(II) and 2-oxoglutarate–dependent dioxygenase Jumonji domain-6 protein; DUB, deubiquitinase; SENP, sentrin-specific protease. * Figure 2: Classic and emerging technologies for epigenetic analysis of adult neurogenesis. During adult neurogenesis in the SGZ, neural stem cells (nestin+ and GFAP+) differentiate into immediate neural progenitors (Trb2+) and then newborn neurons (DCX+ and PSA-NCAM+) and finally into mature new neurons (NeuN+). To profile gene-specific epigenetic modifications, homogeneous target cell populations should be isolated and purified using laser capture microdissection or various prospective cell-labeling strategies. DNA methylation analysis can then be performed using bisulfite sequencing or methylation-sensitive restriction-based approaches. ChIP can be used to profile both DNA and histone modifications. The emerging technology of next-generation sequencing platforms allows rapid, genome-scale, high-resolution mapping of both DNA and histone modifications. RNA expression profiling may validate and further reveal new biological signatures for activated or repressed chromatin states. * Figure 3: Major epigenetic regulators of adult neurogenesis. () Current understanding of epigenetic regulation of adult neurogenesis in SGZ and SVZ. Adult neural progenitors undergo proliferation and generate neuroblasts that can further differentiate into mature, functional neurons. Neurogenesis can be regulated by intrinsic epigenetic mechanisms within the neuronal lineage of adult neural progenitors and extrinsically by nearby niche signaling cells, such as mature neurons, astrocytes and endothelial cells. During the stages of adult neurogenesis, diverse epigenetic mechanisms use common or different sets of molecules, including DNMT, PcG and TrxG, HDAC, MBD and Gadd45 family proteins, in either adult neural progenitors and their progeny or nearby niche cells to choreograph cell state transitions in coordination with other internal and external cues. Common molecules, such as HDACs, are likely to have different partners or binding sites depending on the differentiation stage during neurogenesis. Prototypical cell stages are shown to! reflect identified epigenetic regulators for both SVZ and SGZ adult neurogenesis. () During early stages of adult hippocampal neurogenesis in the SGZ, L1 transcription is regulated by the transcription factors Sox2 and TCF to maintain the long-term silencing state, even during cell division. In response to external stimuli such as neuronal activity or Wnt signaling, the balance of co-repressor and co-activator in the L1 promoter is tipped to activation of L1 expression, driving its genomic retrotransposition. After terminal differentiation, adult neural progenitor–specific expression of Sox2 is downregulated and L1 transcription and retrotransposition are decreased. DNA methylation and MBD-mediated epigenetic mechanisms could act to ensure the long-term silencing of L1 by recruiting transcriptional co-repressors. CoA, co-activator; CoR, co-repressor; DG, dentate gyrus. Author information * Abstract * Author information Affiliations * Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. * Dengke K Ma * Laboratory of Genetics, The Salk Institute for Biological Studies, La Jolla, California, USA. * Maria Carolina Marchetto & * Fred H Gage * Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. * Junjie U Guo, * Guo-li Ming & * Hongjun Song * The Solomon Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. * Junjie U Guo, * Guo-li Ming & * Hongjun Song * Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. * Guo-li Ming & * Hongjun Song Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Hongjun Song (shongju1@jhmi.edu) Additional data - Fezf2 directs the differentiation of corticofugal neurons from striatal progenitors in vivo
- Nat Neurosci 13(11):1345-1347 (2010)
Nature Neuroscience | Brief Communication Fezf2 directs the differentiation of corticofugal neurons from striatal progenitors in vivo * Caroline Rouaux1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Paola Arlotta1, 2, 3, 4paola_arlotta@hms.harvard.edu Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 13 ,Pages:1345–1347Year published:(2010)DOI:doi:10.1038/nn.2658Received09 July 2010Accepted23 August 2010Published online17 October 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg In the developing cerebral cortex, cell-extrinsic and cell-intrinsic signals govern the establishment of neuron subtype-specific identity. Here we show that, within the niche of the striatum, the expression of a single transcription factor, Fezf2, is sufficient to generate corticofugal neurons from progenitors fated to become medium spiny neurons. This demonstrates that a specific population of cortical projection neurons can be directed to differentiate outside of the cortex by cell-autonomous signaling. View full text Figures at a glance * Figure 1: LGE progenitors generate neurons with corticofugal molecular properties in response to Fezf2. Fezf2GFP-expressing neurons located in the striatum express SOX5, TBR1, BHLHB5 and ZFPM2 (arrows), which are absent from the contralateral striatum (arrowheads). Ctx, cortex; LV, lateral ventricle; Str, striatum; CC, corpus callosum. Scale bars, 500 μm. * Figure 2: Fezf2GFP-electroporated neurons do not express markers of MSN. () Coronal sections from contralateral and Fezf2GFP-electroporated striatum showing absence of Meis2, Islet1 and Drd2 from TBR1-expressing CFu neurons. () Fezf2GFP-expressing neurons do not express Gad67 (consecutive sections). Ctx, cortex; LV, lateral ventricle; Str, striatum; CC, corpus callosum. Scale bars, 500 μm and, in magnifications of boxed areas, 100 μm. * Figure 3: Fezf2 instructs the generation of CFu neurons from LGE progenitors without expression of cortical progenitor-specific genes. () Consecutive coronal sections showing that Fezf2GFP-expressing LGE progenitors do not express Ngn2. (,) Fezf2GFP-expressing LGE progenitors did not express PAX6 and TBR2. Confocal images of areas indicated in the low-magnification merged panels by dotted lines were combined to produce three-dimensional reconstructions (far right). Side bars represent projections along the x-z axes (right) and the y-z axes (below). Dotted lines in the reconstructions indicate nuclei, which are positive for PAX6 and TBR2 in cortex and negative for both in the LGE. Ctx, cortex; LV, lateral ventricle; Sept, septum. Scale bars: 500 μm in low-magnification panels (-), 100 μm in magnifications of boxed areas () and 20 μm in magnifications of confocal images (,, far right). Author information * Author information * Supplementary information Affiliations * Center for Regenerative Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA. * Caroline Rouaux & * Paola Arlotta * Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA. * Caroline Rouaux & * Paola Arlotta * Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts, USA. * Paola Arlotta * Harvard Stem Cell Institute, Harvard University, Cambridge, Massachusetts, USA. * Paola Arlotta Contributions P.A. and C.R. conceived the experiments and wrote the manuscript. P.A. supervised the project and C.R. executed all the experiments. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Paola Arlotta (paola_arlotta@hms.harvard.edu) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (4M) Supplementary Figures 1–5 and Supplementary Methods Additional data - N-type Ca2+ channels carry the largest current: implications for nanodomains and transmitter release
- Nat Neurosci 13(11):1348-1350 (2010)
Nature Neuroscience | Brief Communication N-type Ca2+ channels carry the largest current: implications for nanodomains and transmitter release * Alexander M Weber1, 2, 4 Search for this author in: * NPG journals * PubMed * Google Scholar * Fiona K Wong1, 2, 4 Search for this author in: * NPG journals * PubMed * Google Scholar * Adele R Tufford1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Lyanne C Schlichter2 Search for this author in: * NPG journals * PubMed * Google Scholar * Victor Matveev3 Search for this author in: * NPG journals * PubMed * Google Scholar * Elise F Stanley1, 2estanley@uhnres.utoronto.ca Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 13 ,Pages:1348–1350Year published:(2010)DOI:doi:10.1038/nn.2657Received06 July 2010Accepted09 September 2010Published online17 October 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Presynaptic terminals favor intermediate-conductance CaV2.2 (N type) over high-conductance CaV1 (L type) channels for single-channel, Ca2+ nanodomain–triggered synaptic vesicle fusion. However, the standard CaV1>CaV2>CaV3 conductance hierarchy is based on recordings using nonphysiological divalent ion concentrations. We found that, with physiological Ca2+ gradients, the hierarchy was CaV2.2>CaV1>CaV3. Mathematical modeling predicts that the CaV2.2 Ca2+ nanodomain, which is ~25% more extensive than that generated by CaV1, can activate a calcium-fusion sensor located on the proximal face of the synaptic vesicle. View full text Figures at a glance * Figure 1: Single-channel currents and external calcium. (,) Cell-attached patch-clamp recordings of CaV2.2 (N type) single-channel current fluctuations during voltage ramps (top, 2 and 4 superimposed traces; zero current, dashed line in all figures) and step depolarizations (bottom). Closed (C) and open (not labeled) current levels are indicated by cursor lines. Some openings were too short to reach the fully open level. Mean (± s.e.m.) single-channel amplitudes (i, circles) from step depolarizations are superimposed on the ramp currents in the upper panels. The fitted regression line (solid line) slope was taken as the single-channel conductance, γ. () Semi-log plot of Ca2+EXT versus γ, fitted by Hill equations with four (dashed line) or three (γMIN = 0, r2 = 0.89, solid line) free parameters. () Cell-attached patch-clamp recordings during voltage ramps (4 traces) with the fitted regression line extended (dashed line) along the peaks of the single-channel current fluctuations. () Single-channel current amplitude (i−65 mV) ! plotted and fitted as in . Each γ or i value is from a different patch recording (N = 26). () CaV1 (L type) channel step and ramp recording. Data are presented as in . () Top, representative single-channel CaV3.2 (T type) current fluctuations evoked by steps to indicated membrane potentials. Bottom, i-V relation, with fitted regression line and slope (γ). () Plot of i−65 mV versus Ca2+EXT, fitted with the three-parameter Hill equation as in (r2 = 0.92, N = 22). * Figure 2: Comparison of CaV channel Ca2+ permeation. () Mean (± s.e.m.) single-channel current (i−65 mV) values versus Ca2+EXT for CaV1 (L type, N = 36 patches recorded), CaV2.2 (N type) and CaV3.2 (T type) with Hill equation fits, setting i−65,MIN = 0. Vertical dashed gray line indicates 2 mM Ca2+EXT. Inset, physiological Ca2+EXT range plotted on an expanded linear scale. () Plot of mean CaV1 (pooled data from 8 patches, γ = 2.0 pS) and CaV2.2 (N = 6, γ = 2.7 pS) single-channel amplitudes at Ca2+EXT = 2 mM. () Diagram of a calcium channel (center) and presynaptic surface membrane (narrow blue box). Semi-circular lines show the calculated iso-concentration domains at 0.5 ms after opening of a CaV2.2 (black) or CaV1 (gray) channel, assuming a mobile Ca2+ 1 μM affinity buffer at 50 μM concentration (Supplementary Methods). () Scale diagram of synaptic vesicle (SV)-triggering domains at −65 and −40 mV. These domains represent the calculated distance for saturation of ≥50% of calcium sensors, each with five identica! l Ca2+ binding sites and indicated dissociation constants (KD). Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Alexander M Weber & * Fiona K Wong Affiliations * Laboratory of Synaptic Transmission, Toronto Western Research Institute, Toronto, Ontario, Canada. * Alexander M Weber, * Fiona K Wong, * Adele R Tufford & * Elise F Stanley * Genes and Development Division, Toronto Western Research Institute, Toronto, Ontario, Canada. * Alexander M Weber, * Fiona K Wong, * Adele R Tufford, * Lyanne C Schlichter & * Elise F Stanley * Department of Mathematical Sciences, New Jersey Institute of Technology, Newark, New Jersey, USA. * Victor Matveev Contributions A.M.W., F.K.W. and A.R.T. collected data and critiqued the manuscript. L.C.S. contributed RT-PCR data and biophysical and editorial insight. V.M. carried out the mathematical simulations. E.F.S. conceived and directed the project, carried out the analysis and interpretation, and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Elise F Stanley (estanley@uhnres.utoronto.ca) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (1M) Supplementary Figures 1–9, Supplementary Table 1, Supplementary Notes 1–4 and Supplementary Methods Additional data - Resilience to social stress coincides with functional DNA methylation of the Crf gene in adult mice
- Nat Neurosci 13(11):1351-1353 (2010)
Nature Neuroscience | Brief Communication Resilience to social stress coincides with functional DNA methylation of the Crf gene in adult mice * Evan Elliott1 Search for this author in: * NPG journals * PubMed * Google Scholar * Gili Ezra-Nevo1 Search for this author in: * NPG journals * PubMed * Google Scholar * Limor Regev1 Search for this author in: * NPG journals * PubMed * Google Scholar * Adi Neufeld-Cohen1 Search for this author in: * NPG journals * PubMed * Google Scholar * Alon Chen1alon.chen@weizmann.ac.il Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 13 ,Pages:1351–1353Year published:(2010)DOI:doi:10.1038/nn.2642Received14 June 2010Accepted24 August 2010Published online03 October 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg DNA methylation regulates gene transcription and has been suggested to encode psychopathologies derived from early life stress. We found that methylation regulated the expression of the Crf (also known as Crh) gene and that chronic social stress in adult mice induced long-term demethylation of this genomic region. Demethylation was observed only in the subset of defeated mice that displayed social avoidance and site-specific knockdown of Crf attenuated the stress-induced social avoidance. View full text Figures at a glance * Figure 1: Methylation of the Crf promoter regulates gene expression. () Analysis of DNA methylation at the mouse Crf locus by sequencing of PCR clones derived from sodium bisulfite–treated mouse genomic DNA extracted from the PVN. Each row represents an independent clone. () Incubation of N42 immortalized mouse hypothalamic cells with 5-Aza increased Crf mRNA expression (n = 4). Bars represent mean ± s.e.m. *P = 0.029. () Co-incubation of 5-Aza and N6,O2′-dibutyryl-cAMP increased Crf mRNA expression (n = 4). **P = 0.0021. () Luciferase assays with constructs containing the Crf promoter or Crf promoter with a point mutation in the CRE sequence (mutCrf). Basal and cAMP-activated Crf promoter activity was attenuated by methylation (n = 4). ***P = 0.0088; effect of methylation, #P = 0.0017; effect of methylation, ##P < 0.0001. All experimental protocols were approved by the Institutional Animal Care and Use Committee of the Weizmann Institute of Science. * Figure 2: Stress-induced demethylation of Crf promoter coincides with social avoidance behavior. () Schematic representation of social interaction test. () Statistical analysis of the time unstressed or defeated mice spent in the interaction zone (unstressed, n = 18; susceptible, n = 24; resilient, n = 8). *P < 0.01. () Representative video traces of unstressed and socially defeated mice in a social avoidance test. () Quantitative RT-PCR analysis of Crf mRNA expression in the PVN (unstressed, n = 6; susceptible, n = 7; resilient, n = 4). **P = 0.004. () Methylation of the combined CpGs examined in the promoter region (n = 5 animals, 16 clones per animal (unstressed and susceptible) or 4 animals, 19 clones per animal (resilient)). ***P = 0.001. () Percentage of methylated CpG at each CpG. #P < 0.05. () Imipramine attenuated the defeat-induced increase in Crf mRNA expression (n = 8). ##P = 0.028. () Imipramine attenuated the defeat-induced decrease in Crf promoter methylation (n = 5). ###P = 0.046. * Figure 3: Knockdown of Crf in PVN attenuates social avoidance after chronic social defeat. (,) Schematic representation of the four different siRNA target sequences designed from the open reading frame of the mouse Crf gene and the lentiviral construct designed to knockdown Crf. () Western blot analysis revealed that all of the siCrf lentiviruses were able to reduce Crf expression in HEK293T cells transfected with a Crf-expressing plasmid. PreproCRF, CRF precursor peptide. () Brain slices of a mouse injected with siCrf#3 viruses or control were in situ hybridized for Crf and immunostained for GFP. Purple-stained cells represent Crf mRNA and DAB-stained cells represent GFP immunoreactivity. Scale bar represents 100 μm. 3V, third ventricle. () GFP was expressed at the site of injection in mice injected with siCrf-expressing lentiviruses in the PVN. Section map adapted from ref. 15. Scale bar represents 100 μm. (,) Mice injected with scramble or Crf siRNA–expressing lentiviruses were tested for social interaction behavior both before and after social defeat (n = ! 8–11). *P = 0.048 Author information * Author information * Supplementary information Affiliations * Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel. * Evan Elliott, * Gili Ezra-Nevo, * Limor Regev, * Adi Neufeld-Cohen & * Alon Chen Contributions E.E. performed the cell culture experiments, in vivo DNA methylation and mRNA analysis, and behavioral experimentation. G.E.-N. performed stereotaxic surgery and viral injections. L.R. and A.N.-C. verified the Crf knockdown lentivirus. E.E. and A.C. designed the experiments, interpreted the results and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Alon Chen (alon.chen@weizmann.ac.il) Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (1M) Supplementary Figures 1–6, Supplementary Table 1 and Supplementary Methods Additional data - The habenula is crucial for experience-dependent modification of fear responses in zebrafish
- Nat Neurosci 13(11):1354-1356 (2010)
Nature Neuroscience | Brief Communication The habenula is crucial for experience-dependent modification of fear responses in zebrafish * Masakazu Agetsuma1 Search for this author in: * NPG journals * PubMed * Google Scholar * Hidenori Aizawa1 Search for this author in: * NPG journals * PubMed * Google Scholar * Tazu Aoki1 Search for this author in: * NPG journals * PubMed * Google Scholar * Ryoko Nakayama1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Mikako Takahoko1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Midori Goto1 Search for this author in: * NPG journals * PubMed * Google Scholar * Takayuki Sassa1, 7 Search for this author in: * NPG journals * PubMed * Google Scholar * Ryunosuke Amo1, 3 Search for this author in: * NPG journals * PubMed * Google Scholar * Toshiyuki Shiraki1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Koichi Kawakami4 Search for this author in: * NPG journals * PubMed * Google Scholar * Toshihiko Hosoya1 Search for this author in: * NPG journals * PubMed * Google Scholar * Shin-ichi Higashijima5 Search for this author in: * NPG journals * PubMed * Google Scholar * Hitoshi Okamoto1, 6hitoshi@brain.riken.jp Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 13 ,Pages:1354–1356Year published:(2010)DOI:doi:10.1038/nn.2654Received21 June 2010Accepted07 September 2010Published online10 October 2010Erratum17 October 2010 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The zebrafish dorsal habenula (dHb) shows conspicuous asymmetry in its connection with the interpeduncular nucleus (IPN) and is equivalent to the mammalian medial habenula. Genetic inactivation of the lateral subnucleus of dHb (dHbL) biased fish towards freezing rather than the normal flight response to a conditioned fear stimulus, suggesting that the dHbL-IPN pathway is important for controlling experience-dependent modification of fear responses. View full text Figures at a glance * Figure 1: The habenula-IPN projection pattern and the genetic manipulation of dHbL-d/iIPN transmission. (–) Anterograde labeling of dIPN efferents by DiI (1,1′-dioctadecyl-3,3,3′3′-tetramethylindocarbocyanine perchlorate, red) in adult Tg(brn3a-hsp70:GFP), which expressed GFP specifically in the dHbM-v/iIPN pathway (arrowhead). Arrows indicate the cross-sections of the labeled tracts. Counter staining, SYTOX green. MLF, medial longitudinal fascicle. (–) Anterograde labeling from the IPN with Neurobiotin. Counter staining, neutral red. The efferents from the dIPN (, asterisk) terminated in the griseum centrale (, arrow). The efferents from the vIPN (, asterisk) terminated in the median raphe (, bracket). (–) Expression patterns of an adult Tg(narp:GAL4VP16; UAS:DsRed2; brn3a-hsp70:GFP) fish. (,) TeTxLC mRNA expression in adult Tg(narp:GAL4VP16; UAS:TeTxLC) () and control fish (). Black arrowheads, dHbL. All panels are coronal sections except for (horizontal) and and (sagittal). D, dorsal; L, left; P, posterior; R, right. Scale bars represent 200 μm (,–), 100 μm ! (,,–) and 50 μm (). * Figure 2: The dHbL-silenced fish showed enhanced freezing responses to the conditioned stimulus instead of flight behaviors. (,) Examples of the control () and dHbL-silenced () fish locomotion trajectories during retrieval sessions, before (20 s, red dotted lines), during (8.5 s, red solid lines) and after (20 s, blue lines) the conditioned stimulus (CS) exposure. () The change in the turning frequency, which was evoked during conditioned stimulus presentation. The values are normalized to the averages of the adaptation sessions. Means ± s.e.m. are plotted. *P < 0.05, Wilcoxon signed-rank test (comparison with the first conditioning session). (,) Total average of freezing ratios () and immobility times (s) () for 50 s after the offset of the conditioned stimulus. Means ± s.e.m. are plotted. Two-way repeated-measure ANOVA, habenula state (control, silenced) × conditioning (before conditioning, after conditioning) (, F = 4.66, P = 0.04; , F = 6.04, P = 0.02). **P < 0.01 and *P < 0.05, Bonferroni post-tests (control versus dHbL silenced). () The unconditioned stimulus (US)-triggered locomotor acti! vity at each trial of the first (1–5) and second (6–10) conditioning sessions. Means ± s.e.m. are plotted. Two-way repeated-measure ANOVA, the main effect of Habenula state (F = 0.27, P = 0.61). () Exploration time spent in the center of the field (Mann-Whitney U test, P = 0.16). () The locomotor activity during the last 5 min before the onset of the retrieval session (Mann-Whitney U test, P = 0.08). For and , the middle line represents the median, the box edges indicate quartiles and the vertical bars indicate the range. () Ratio of freezing individuals in response to the unconditioned stimulus presentations during the conditioning sessions (first, 1–5; second, 6–10). () Total average of freezing ratios in the first and second conditioning sessions. Means ± s.e.m. are plotted. *P < 0.05, χ2 test with total number of freezing and nonfreezing responses at each session. AD, adaptation session; CD, conditioning session; dHbL-SL, dHbL-silenced fish; RT, retrieval ses! sion; ns, nonsignificant (P > 0.05). Change history * Change history * Author information * Supplementary informationErratum 17 October 2010In the version of this article initially published online, there was an error on page 2, right column, second paragraph, 14th line. Here, 'Mtz' should read 'metronidazole'. The supplementary material file was also missing some information from the images. Both errors have been corrected for the print, PDF and HTML versions of this article. Author information * Change history * Author information * Supplementary information Affiliations * RIKEN Brain Science Institute, Wako, Saitama, Japan. * Masakazu Agetsuma, * Hidenori Aizawa, * Tazu Aoki, * Ryoko Nakayama, * Mikako Takahoko, * Midori Goto, * Takayuki Sassa, * Ryunosuke Amo, * Toshiyuki Shiraki, * Toshihiko Hosoya & * Hitoshi Okamoto * Research Resource Center, RIKEN Brain Science Institute, Wako, Saitama, Japan. * Ryoko Nakayama, * Mikako Takahoko & * Toshiyuki Shiraki * Department of Life Science and Medical Bioscience, Graduate School of Advanced Science and Engineering, Waseda University, Shinjuku-ku, Tokyo, Japan. * Ryunosuke Amo * Division of Molecular and Developmental Biology, National Institute of Genetics, and Department of Genetics, the Graduate University for Advanced Studies, Mishima, Shizuoka, Japan. * Koichi Kawakami * National Institutes of Natural Sciences, Okazaki Institute for Integrative Bioscience, National Institute for Physiological Sciences, Okazaki, Aichi, Japan. * Shin-ichi Higashijima * Core Research for Evolutional Science and Technology, Japan Science and Technology Agency, Sanbancho, Chiyoda-ku, Tokyo, Japan. * Hitoshi Okamoto * Present address: Laboratory of Biochemistry, Faculty of Pharmaceutical Sciences, Hokkaido University, Higashi, Kita-ku, Sapporo, Japan. * Takayuki Sassa Contributions M.A., H.A. and H.O. designed the experiments and wrote the manuscript. H.O. supervised the research project. M.A. performed most of the experiments using transgenic fish with T.A., R.N., M.T., T. Sassa, T. Shiraki, K.K., T.H. and S.H. H.A. performed the neural tracing study with M.G., M.T. and R.A. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Hitoshi Okamoto (hitoshi@brain.riken.jp) Supplementary information * Change history * Author information * Supplementary information Movies * Supplementary Movie 1 (496K) Response of the control fish at the first trial of the retrieval session. * Supplementary Movie 2 (1M) Response of the dHbl-silenced fish at the first trial of the retrieval session. * Supplementary Movie 3 (584K) Persistent rotation of the dHbl-silenced fish at the first trial of the retrieval session. PDF files * Supplementary Text and Figures (3M) Supplementary Figures 1–24, Supplementary Table 1, Supplementary Methods and Supplementary Data Additional data - APC/CFzr/Cdh1-dependent regulation of cell adhesion controls glial migration in the Drosophila PNS
- Nat Neurosci 13(11):1357-1364 (2010)
Nature Neuroscience | Article APC/CFzr/Cdh1-dependent regulation of cell adhesion controls glial migration in the Drosophila PNS * Marion Silies1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Christian Klämbt1klaembt@uni-muenster.de Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 13 ,Pages:1357–1364Year published:(2010)DOI:doi:10.1038/nn.2656Received16 July 2010Accepted31 August 2010Published online03 October 2010 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Interactions between neurons and glia are a key feature during the assembly of the nervous system. During development, glial cells often follow extending axons, implying that axonal outgrowth and glial migration are precisely coordinated. We found that the anaphase-promoting complex/cyclosome (APC/C) co-activator fizzy-related/Cdh1 (Fzr/Cdh1) is involved in the non-autonomous control of peripheral glial migration in postmitotic Drosophila neurons. APC/CFzr/Cdh1 is a cell-cycle regulator that targets proteins that are required for G1 arrest for ubiquitination and subsequent degradation. We found that Fzr/Cdh1 function is mediated by the immunoglobulin superfamily cell adhesion molecule Fasciclin2 (Fas2). In motor neurons Fzr/Cdh1 is crucial for the establishment of a graded axonal distribution of Fas2. Axonal Fas2 interacts homophilically with a glial isoform of Fas2. Glial migration is initiated along axonal segments that have low levels of Fas2 but stalls in axonal domains ! with high levels of Fas2 on their surfaces. This represents a simple mechanism by which a subcellular gradient of adhesiveness can coordinate glial migration with axonal growth. View full text Figures at a glance * Figure 1: Identification of fzr/cdh1 mutants. (–) Frontal views of dissected Drosophila stage 16 nervous system preparations. CNS is to the left and anterior is up in all figures. Neuronal membranes are shown in green (HRP), glial cell nuclei in magenta (Repo). Schematic views focusing on glial cells along the segmental nerve are shown below. () In wild-type (WT) embryos, axonal tracts run in a highly stereotyped pattern. The axons of the PNS are organized in a few peripheral nerves with a regular distribution of glial cell nuclei. () In hemizygous fzr/cdh18F3 mutant embryos there are severe axonal patterning defects in the CNS, whereas the major axonal tracts are still present in the PNS. Compared with the wild type, fzr/cdh1 mutants have more glial cells, which do not migrate into the periphery and stay close to the CNS-PNS boundary (arrowheads). () Similar phenotypes were found in the fzr/cdh1ie28 null allele. () Protein blot analysis of protein extracts generated from different mutant fzr/cdh1 embryos; genotypes a! s indicated. Scale bar, 20 μm. * Figure 2: Postmitotic Fzr/Cdh1 non-autonomously regulates glial cell migration. () Frontal views of dissected Drosophila stage 16 nervous system preparations (–) or whole mount embryos (–); anterior is up. Neuronal membranes are shown in green (HRP), glial cell nuclei in magenta (Repo). Schematic views focusing on glial cells along the segmental nerve are shown below. () In wild-type embryos, glial cells are regularly distributed along the nerve. () In fzr/cdh1 null mutants, extra glial cells are formed and glial migration is disrupted. () In cycAC8LR1 mutants, only a few glial cells are born. () In fzrie28cycAC8LR1 double mutants, a normal number of glial cells develop, but do not migrate (arrowheads). () Re-expression of fzr/cdh1 in all glial cells in a fzr/cdh1ie28 mutant using the repoGal4 driver does not affect the glial phenotype. () Re-expression of fzr/cdh1 in a fzr/cdh1ie28 mutant directed by elavGal4C155 rescues the glial cell migration phenotype but does not rescue the glial cell number. The quantification is shown in and . () Re-expressi! on of fzr/cdh1 in a fzr/cdh1ie28 mutant directed by a elavGal4 driver construct on the third chromosome results in an almost complete phenotypic rescue of both the glial and axonal phenotypes. (,) Quantification of the results obtained in the different cell type–specific rescue experiments. Error bars show the s.d.; n represents the number of analyzed embryos; the number of hemisegments is given in parentheses. Statistical analyses were performed with a Welch t-test. Significant differences of the mean are indicated by asterisks (P < 0.01, 99% confidence). Scale bars, 20 μm. * Figure 3: Postmitotic APC/C acts in motor neurons to control glial migration. (,) Ventral views of Drosophila stage 16 nervous systems imaged at the same settings. αCycB (magenta or gray), α-βGal (green), HRP (neurons, blue). In wild-type embryos expressing fas2Gal4Mz507 UAScycB UASλlacZ, CycB protein is hardly detectable, although βGal overexpression is readily visible (arrowhead). (,) In fzr/cdh1ie28 mutant embryos, both proteins are expressed (arrowheads) in motor neurons. Additional CycB-expressing cells represent single neurons that accumulate CycB due to the absence of fzr (open arrowheads). () The PNS of whole-mount embryos is marked with HRP (green) and glial cell nuclei with αRepo (magenta); genotypes as indicated. Arrowheads point at the distal most dorsally migrating glial cells. (,) lmg/APC11EY11317 or mr/APC2Df(Chi[g230]) mutant embryos do not show glial migration phenotypes. () In embryos homozygous for both lmg/APC11EY11317 and mr/APC2Df(Chi[g230]), glial cells accumulate close to the PNS and do not migrate into the periphery. () ! The phenotype is rescued by neuronal expression (elavGal4) of UASmr/APC2, showing that lmg/APC11 and mr/APC2 genetically interact and are required for glial cell migration. Scale bars, 20 μm. * Figure 4: Fzr/Chd1 regulates glial cell migration through the homophilic cell adhesion molecule Fas2. (–,) Dissected Drosophila nervous systems, stage 15 (), stage 14 (,) and stage 16 (–,). () Expression of the enhancer trap fzrG0418 is shown in green (α-βGal), glial cell nuclei are marked in magenta (αRepo). fzrG0418 shows labeling in postmitotic cells, including broad expression in the nervous system. Some glial cells are only very weakly labeled (arrowheads). () Subcellular localization of N-terminally Myc-tagged Fzr protein in motor neurons carrying fas2Gal4Mz507. MycFzr (green) localizes predominantly to the cytoplasm and the motor axon. () shows the Myc staining of a single confocal plane of the boxed area shown in . (–) Neurons are marked with HRP (green) and glial cell nuclei with αRepo (magenta). Whereas in fzr/cdh1ie28 mutants, glial cells fail to migrate and fas2EB112 alone does not affect the glial pattern, only the glial migration phenotype is rescued in fzr/cdh1ie28fas2EB112 double mutants. All axonal phenotypes and the increased glial cell number are! unaffected. () Quantification of the results shown in – and Supplementary Figure 6. The fzr/cdh1 glial cell migration phenotype is suppressed by loss of fas2, but not by loss of the related gene nrg. (,) Axonal phenotypes are not suppressed in fas2 fzr/cdh1 mutants. () Stage 16 fas2EB112fzrie28 double-mutant embryo. Sensory neurons are marked with 22C10 (magenta), neurons are marked with HRP (green). In double-mutant embryos, neurons still target to adjacent segments. () In stage 16 embryos, sensory neurons are marked with 22C10. The embryos are from the same staining, imaged with the same settings. Scale bars: 5 μm in , 20 μm in other panels. * Figure 5: Broad expression of fas2. () The fas2 genomic region. The positions of the GFP397 and the CB03613 exon trap insertions are indicated. () fas2 is expressed in four isoforms that all comprise five immunoglobulin (Ig) and two fibronectin type III (FNIII) domains, but have distinct C termini. The differences are highlighted in and with the same color code. SP, signal peptide; PEST, PEST domain; GPI, glycosylphosphatidylinositol membrane anchor. () Frontal views of stage 16 nervous systems. () The monoclonal antibody 1D4 reveals expression of Fas2 on motor neurons (gray). Only the isoforms Fas2PA PEST+ and Fas2PA PEST− are recognized. () The P[lacZ] enhancer trap fas2rG272 (α-βGal, green) is expressed in motor neurons (arrow) as well as in non-neuronal cells including peripheral glia (arrowheads). Glial nuclei are marked with αRepo (magenta), neurons with HRP (blue). () One hemineuromere is shown in which all neurons are marked with HRP (blue), motor neurons are labeled with αFas2 (magenta) and the ! Fas2GFP397-expressing cells are labeled with αGFP (green). In addition to strong expression on motor neurons (arrows), Fas2GFP397 is expressed on peripheral glial cells (arrowheads). Glial Fas2 expression decreases with distance from the CNS (open arrowheads). Asterisks indicate identified glial cell nuclei. Fas2GFP397 reflects the expression of Fas2PA PEST+, Fas2PA PEST− and Fas2PB (). (,) Co-labeling of glial outlines with repo>CD2 and Fas2GFP397 confirms the expression of Fas2PB on glia (arrowheads). () Schematic representation of Fas2 expression on glia. Scale bars: 100 amino acids in ; 20 μm in ,; 10 μm in . * Figure 6: Fzr/Cdh1 regulates the graded expression of Fasciclin 2 at the onset of glial migration. () In stage 14 embryos, HRP labeling is shown in green or gray and Fas2 labeling in magenta, gray or in false color reflecting the intensity (,). () In the wild type, motor neuronal Fas2 is expressed in a graded fashion at the onset of glial cell migration with high Fas2 levels on distal parts of the motor axons and lower Fas2 levels towards the CNS. () In fzrie28 mutants, Fas2 is no longer distributed in a gradient. () Quantification of the stage 14 Fas2 expression data. Ratio of Fas2 levels measured behind the growth cone and close to the CNS-PNS boundary. Box-whisker plot represents the median (bold line), 25% and 75% quartiles (box), 1,5 times interquartile distance (whiskers) and extreme values (circles). Statistical analyses were performed with a Welch t-test (P < 0.01, 99% confidence). (–) In stage 16 embryos, neuronal membranes are marked with HRP (blue), glial cell nuclei with αRepo (magenta) and the expressed constructs with αGFP (green). () Overexpression of t! he intracellular domain of fas2PA-PEST+ (UASfas2intraYFP50) in both neurons and glia (elavGal4 + repoGal4) does not affect glial migration. (,) Overexpression of both UASfas2extraYFP and UASfas2intactYFP50 leads to an accumulation of glial cells at the CNS-PNS boundary and to a failure in glial migration. Scale bars, 20 μm. * Figure 7: Disruption of the endocytic pathway disrupts glial migration and reduces the graded expression of Fas2. () In a stage 16 CNS, Fas2 marks the longitudinal axon tracks. In addition, many vesicle-like structures can be detected in the regions where motor neurons reside. () Boxed region as indicated in . αFas2 (magenta) labels neuronal vesicles expressing UASrab11GFP (), UASrab5GFP () or UASrab4GFP () (neurons: green, arrowheads). The right-hand image of each pair shows only Fas2 expression. () Disruption of the endocytic pathway in neurons leads to glial migration defects. Frontal views of dissected Drosophila stage 16 nervous system preparations. Neuronal membranes are shown in green (HRP) and glial cell nuclei in magenta (Repo); genotypes as indicated. (,) Whereas elavGal4 embryos shifted to 34 °C look like the wild type, glial migration is disrupted in elav>>shits1 embryos at 34 °C. (,) Stage 14 embryos marked with anti-Fas2 (false color representing intensity). Compared with control embryos from the same staining (), there is a weaker gradient of Fas2 expression in embryos! expressing dominant-negative Rab4 in neurons (). () Quantification of the distal/proximal-ratio of Fas2 expression in control and elav>>rab4SN embryos. Plot details as in Figure 6. Statistical analyses were performed with a Welch t-test (P < 0.01, 99% confidence). Scale bars: 5 μm in ; 20 μm in , . Author information * Abstract * Author information * Supplementary information Affiliations * Institut für Neurobiologie, Universität Münster, Münster, Germany. * Marion Silies & * Christian Klämbt * Present address: Department of Neurobiology, Stanford University, Stanford, California, USA. * Marion Silies Contributions M.S. conducted the experiments and analysed the data. C.K. contributed ideas. M.S. and C.K. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Christian Klämbt (klaembt@uni-muenster.de) Supplementary information * Abstract * Author information * Supplementary information Movies * Supplementary Movie 1 (1M) Wild type embryo carrying two repoGal4 and two UAS-GFPstinger transgenes. * Supplementary Movie 2 (4M) fzr/cdh1ie28 mutant type embryo carrying two repoGal4 and two UAS-GFPstinger transgenes. PDF files * Supplementary Text and Figures (6M) Supplementary Figures 1–10 Additional data - Fbw7 controls neural stem cell differentiation and progenitor apoptosis via Notch and c-Jun
- Nat Neurosci 13(11):1365-1372 (2010)
Nature Neuroscience | Article Fbw7 controls neural stem cell differentiation and progenitor apoptosis via Notch and c-Jun * Joerg D Hoeck1 Search for this author in: * NPG journals * PubMed * Google Scholar * Anett Jandke1 Search for this author in: * NPG journals * PubMed * Google Scholar * Sophia M Blake1 Search for this author in: * NPG journals * PubMed * Google Scholar * Emma Nye2 Search for this author in: * NPG journals * PubMed * Google Scholar * Bradley Spencer-Dene2 Search for this author in: * NPG journals * PubMed * Google Scholar * Sebastian Brandner3 Search for this author in: * NPG journals * PubMed * Google Scholar * Axel Behrens1axel.behrens@cancer.org.uk Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 13 ,Pages:1365–1372Year published:(2010)DOI:doi:10.1038/nn.2644Received26 July 2010Accepted26 August 2010Published online10 October 2010 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Neural stem and progenitor cells (NSCs/NPCs) give rise to neurons, astrocytes and oligodendrocytes. However, the mechanisms underlying the decision of a stem cell to either self-renew or differentiate are incompletely understood. We demonstrate here that Fbw7 (F-box and WD repeat domain containing-7), the substrate recognition component of an SCF (complex of SKP1, CUL1 and F-box protein)-type E3 ubiquitin ligase, is a key regulator of NSC/NPC viability and differentiation. The absence of Fbw7 in the mouse brain caused severely impaired stem cell differentiation and increased progenitor cell death. Fbw7 deficiency resulted in accumulation of two SCF(Fbw7) substrates, the transcription factors active Notch1 and N-terminally phosphorylated c-Jun. Genetic and pharmacological rescue experiments identified c-Jun as a key substrate of Fbw7 in controlling progenitor cell viability, whereas inhibition of Notch signaling alleviated the block in stem cell differentiation. Thus Fbw7 con! trols neurogenesis by antagonizing Notch and c-Jun N-terminal kinase (JNK)/c-Jun signaling. View full text Figures at a glance * Figure 1: Fbw7 controls cell number and survival in the brain. () Hematoxylin and eosin staining of the E18.5 forebrain from Fbxw7f/f and Fbxw7ΔN mouse embryos. Rectangles mark comparable regions of the cortex shown below in high magnification. Scale bars, 100 μm. () H&E staining of comparable regions of the Fbxw7f/f and Fbxw7ΔN E18.5 midbrain. Rectangles mark the area of the tectum shown below in high magnification. Scale bars, 200 μm. () Histogram showing the relative quantity of cells in the ventricular zone (VZ), subventricular zone (SVZ), intermediate zone (IZ) and cortical plate (CP) of the Fbxw7f/f and Fbxw7ΔN E18.5 cortex. Cell number in the Fbxw7f/f E18.5 cortex is normalized to 1 (100%); n = 3. () Histogram showing the relative quantity of cells in the VZ and the mantle layer (ML) of the Fbxw7f/f and Fbxw7ΔN E18.5 tectum. Cell numbers in the Fbxw7f/f E18.5 tectum are normalized to 1 (100%); n = 5. () 3,3′-Diaminobenzidine (DAB) staining for the mitotic marker phosphorylated histone H3 (pH3) on representative sections o! f the Fbxw7f/f and Fbxw7ΔN E16.5 tectum. Cells are counterstained with hematoxylin. Scale bars, 50 μm. () Immunohistochemistry for active caspase-3 (Casp3; green) on representative sections of the Fbxw7f/f and Fbxw7ΔN E16.5 tectum. DNA (blue) is counterstained with DAPI. Scale bars, 50 μm. () Quantification of pH3+ and active Casp3+ cells in the Fbxw7f/f and Fbxw7ΔN E16.5 tectum; n = 3. Error bars, s.e.m. NS, not significant; *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001 (unpaired t-test). * Figure 2: Fbw7 controls stem cell differentiation and neurogenesis in the brain. () Fbxw7 (probe specific to exons 6–10) in situ hybridization and sense control with hematoxylin stain (left) on the Fbxw7f/f E14.5 cortex. Scale bars, 50 μm. () Immunohistochemistry for Nestin (red) on the Fbxw7f/f and Fbxw7ΔN E14.5 cortex. White rectangles mark areas shown in high magnification in panels at the top. DNA (blue) is counterstained with DAPI. Scale bars, 50 μm. () Immunohistochemistry for Nestin (red; left panels) and BLBP (red; right panels) on the Fbxw7f/f and Fbxw7ΔN E16.5 cortex. White rectangles mark areas shown in high magnification in panels at the top. DNA (blue) is counterstained with DAPI. Scale bars, 50 μm. () DAB staining for Nestin on the Fbxw7f/f and Fbxw7ΔN E18.5 cortex. Black rectangles mark areas shown in high magnification in panels at the top. Cells are counterstained with hematoxylin. Scale bars, 50 μm. () Immunohistochemistry for GLAST (green) on the Fbxw7f/f and Fbxw7ΔN E18.5 cortex. White rectangles mark areas shown in high mag! nification in panels at the top. DNA (blue) is counterstained with DAPI. Scale bars, 50 μm. (–) DAB staining for () BLBP, () Tbr2, () NeuN, () Tbr1, () Ctip2 and () Brn2 on the Fbxw7f/f and Fbxw7ΔN E18.5 cortex. Black rectangles mark areas shown in high magnification in panels at the top. Cells are counterstained with hematoxylin. Scale bars, 50 μm. () Quantification of BLBP-positive cells in the SVZ and Tbr2, NeuN, Tbr1, Ctip2 and Brn2-positive cells in the intermediate zone (IZ) and the cortical plate (CP) of the Fbxw7f/f and Fbxw7ΔN E18.5 cortex. n = 3. Error bars, s.e.m. *P ≤ 0.05 (unpaired t-test); **P ≤ 0.01. VZ, ventricular zone. * Figure 3: Absence of Fbw7 leads to retention of markers for immature cells and induces apoptosis in vitro. () Phase contrast pictures of Fbxw7f/f and Fbxw7ΔN neurosphere (arrowheads) cultures under self-renewal conditions. Scale bars, 100 μm. (,) Histograms showing () the size (in μm) and () the relative quantity of Fbxw7f/f and Fbxw7ΔN neurospheres. Neurosphere numbers in Fbxw7f/f cultures are normalized to 1 (100%); n = 4. () Immunocytochemistry for Nestin (green) and Musashi-1 (Msi1; red) on Fbxw7f/f and Fbxw7ΔN neurosphere sections. DNA (blue) was counterstained with DAPI. Scale bars, 100 μm. () Quantification of Msi1+ cells per neurosphere in Fbxw7f/f and Fbxw7ΔN neurosphere cultures; n = 3. () DAB staining for TUNEL (TdT-mediated dUTP-biotin nick end labeling)-positive cells (arrowheads) on Fbxw7f/f and Fbxw7ΔN neurosphere sections. Cells are counterstained with hematoxylin. Scale bars, 100 μm. () Histogram showing the percentage of TUNEL-positive cells in Fbxw7f/f and Fbxw7ΔN neurosphere cultures; n = 3. Error bars, s.e.m. **P ≤ 0.01; ***P ≤ 0.001 (unpaired t! -test). * Figure 4: Absence of Fbw7 blocks differentiation in vitro. (–) Immunocytochemistry for RC2 (green) and Nestin (red) (), Map2 (green) and connexin-43 (Cx43; red) (), and O4 () on Fbxw7f/f and Fbxw7ΔN neurosphere cultures after 5 d under differentiation conditions. White squares mark areas shown in high magnification in panels on the right. DNA (blue) was counterstained with Hoechst 33342. Scale bars, 50 μm. () Quantification of RC2/Nestin-, Map2-, Cx43- and O4-positive cells in Fbxw7f/f and Fbxw7ΔN neurosphere cultures after 5 d under differentiation conditions. Error bars, s.e.m. NS, not significant; *P ≤ 0.05 (unpaired t-test). * Figure 5: Negative regulation of c-Jun by Fbw7 controls neural cell viability. () Western blot analysis of Fbw7, c-Jun, activated Notch1 (NICD1), Thr58- and Ser62-phosphorylated c-Myc (p-c-Myc), Thr395-phosphorylated cyclin E (p-Cyclin E) and β-actin on protein lysates from Fbxw7f/f and Fbxw7ΔN neurospheres (cropped images; full-length blots are presented in Supplementary Fig. 15). () Immunohistochemistry for Ser73-phosphorylated c-Jun (p-c-Jun; red) on representative sections of Fbxw7f/f, Fbxw7ΔN and Fbxw7ΔN; JunΔN/+ E18.5 tectum. DNA (blue) was counterstained with DAPI. Scale bars, 50 μm. () Histogram showing the relative quantity of cells in the ventricular zone (VZ) and the mantle layer (ML) of Fbxw7f/f (n = 5), Fbxw7ΔN (n = 5) and Fbxw7ΔN; JunΔN/+ (n = 3) E18.5 tectum. Cell numbers in the Fbxw7f/f E18.5 tectum are normalized to 1 (100%). () Histogram showing the relative quantity of neurospheres in Fbxw7f/f (n = 4), Fbxw7ΔN (n = 4) and Fbxw7ΔN; JunΔN/+ (n = 2) neurosphere cultures after 2 weeks under self-renewal conditions. Neurospher! e numbers in Fbxw7f/f neurosphere cultures are normalized to 1 (100%). () Histogram showing the percentage of TUNEL-positive cells in Fbxw7f/f (n = 3), Fbxw7ΔN (n = 3) and Fbxw7ΔN; JunΔN/+ (n = 2) neurosphere cultures. () Quantitative real-time PCR analysis of Fbxw7, Jun, Bad, Bcl2l1l and Bcl2 transcripts in Fbxw7f/f, Fbxw7ΔN and Fbxw7ΔN; JunΔN/+ neurosphere cells. The data are normalized to Gapdh and represented as fold change relative to RNA levels in Fbxw7f/f neurosphere cells, which are set to 1. Error bars represent the s.e.m. NS, not significant; *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001 (unpaired t-test). * Figure 6: Fbw7 controls stem cell differentiation by antagonizing Notch. () Immunohistochemistry for activated Notch1 (NICD1; red) on representative sections of the Fbxw7f/f, Fbxw7ΔN and Fbxw7ΔN; Notch1Δ/+ E18.5 cortex. DNA (blue) was counterstained with DAPI. Scale bars, 50 μm. (,) DAB staining for () Nestin and () BLBP on the Fbxw7f/f, Fbxw7ΔN and Fbxw7ΔN; Notch1Δ/+ E18.5 cortex. Cells are counterstained with hematoxylin. Scale bars, 50 μm. () Quantification of BLBP-positive cells in the intermediate zone (IZ) and the cortical plate (CP) of the Fbxw7f/f, Fbxw7ΔN and Fbxw7ΔN; Notch1Δ/+ E18.5 cortex. n = 3. () Quantitative real-time PCR analysis of Hes5, Hey1 and Hes1 transcripts in Fbxw7f/f, Fbxw7f/f; Notch1Δ/+, Fbxw7ΔN and Fbxw7ΔN; Notch1Δ/+ neurospheres. The data are normalized to Gapdh and represented as fold change relative to RNA levels in Fbxw7f/f neurospheres, which is set to 1. () Immunocytochemistry for Nestin (green) on Fbxw7f/f, Fbxw7f/f; Notch1Δ/+, Fbxw7ΔN and Fbxw7ΔN; Notch1Δ/+ neurosphere cultures after 5 d under! differentiation conditions. White squares mark areas shown in high magnification in panels on the right. DNA (blue) was counterstained with Hoechst 33342. Scale bars, 50 μm. () Histogram showing the percentage of Nestin-positive cells in Fbxw7f/f, Fbxw7f/f; Notch1Δ/+, Fbxw7ΔN and Fbxw7ΔN; Notch1Δ/+ neurosphere cultures after 5 d under differentiation conditions. n = 3. Error bars, s.e.m. NS, not significant; *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001 (unpaired t-test). VZ, ventricular zone. Author information * Abstract * Author information * Supplementary information Affiliations * Mammalian Genetics Laboratory, Cancer Research UK London Research Institute, London, UK. * Joerg D Hoeck, * Anett Jandke, * Sophia M Blake & * Axel Behrens * Experimental Pathology Laboratory, Cancer Research UK London Research Institute, London, UK. * Emma Nye & * Bradley Spencer-Dene * Division of Neuropathology, Department of Neurodegenerative Disease, University College London, Institute of Neurology, London, UK. * Sebastian Brandner Contributions J.D.H. designed and conducted the majority of the experiments, did the data analyses and co-wrote the manuscript. A.J. generated the Fbxw7f/f mice and performed the radioactive in situ hybridization. S.M.B. performed the experiments on adherent NSC cultures. E.N. did the IHC stainings. B.S.-D. performed the nonradioactive in situ hybridization. S.B. gave advice on neurosphere sectioning. A.B. supervised the project, directed the experiments and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Axel Behrens (axel.behrens@cancer.org.uk) Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (4M) Supplementary Figures 1–19 Additional data - The MAP kinase phosphatase MKP-1 regulates BDNF-induced axon branching
- Nat Neurosci 13(11):1373-1379 (2010)
Nature Neuroscience | Article The MAP kinase phosphatase MKP-1 regulates BDNF-induced axon branching * Freddy Jeanneteau1, 4freddy.jeanneteau@med.nyu.edu Search for this author in: * NPG journals * PubMed * Google Scholar * Katrin Deinhardt1, 4katrin.deinhardt@med.nyu.edu Search for this author in: * NPG journals * PubMed * Google Scholar * Goichi Miyoshi2 Search for this author in: * NPG journals * PubMed * Google Scholar * Anton M Bennett3 Search for this author in: * NPG journals * PubMed * Google Scholar * Moses V Chao1 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 13 ,Pages:1373–1379Year published:(2010)DOI:doi:10.1038/nn.2655Received26 July 2010Accepted08 September 2010Published online10 October 2010 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The refinement of neural circuits during development depends on a dynamic process of branching of axons and dendrites that leads to synapse formation and connectivity. The neurotrophin brain-derived neurotrophic factor (BDNF) is essential for the outgrowth and activity-dependent remodeling of axonal arbors in vivo. However, the mechanisms that translate extracellular signals into the formation of axonal branches are incompletely understood. We found that MAP kinase phosphatase-1 (MKP-1) controls axon branching. MKP-1 expression induced by BDNF signaling caused spatiotemporal deactivation of c-jun N-terminal kinase (JNK), which reduced the phosphorylation of JNK substrates that destabilize microtubules. Indeed, neurons from mkp-1 null mice could not produce axon branches in response to BDNF. Our results identify a signaling mechanism that regulates axonal branching and provide a framework for studying the molecular mechanisms of innervation and axonal remodeling under normal ! and pathological conditions. View full text Figures at a glance * Figure 1: Gain- and loss-of-function of MKP-1 in vivo affect neural development. () Developmental expression of endogenous MKP-1 in the cortex. () Knockdown efficiency of shRNAs (shRNA#3–7; –, empty vector) against MKP-1. () Representative images of individual cortical layer II–III neurons from in utero electroporated brains expressing control (GFP), mkp-1IRES-GFP (mkp-1GFP) or shRNA#7 (shRNA#7GFP) plasmids. Arrows highlight differences in dendritic development. () Summary of the morphological effects of MKP-1 gain and loss-of-function on layer II–III cortical neurons. () Traces of axon terminals in the contralateral cortical layers of transfected brains. Primary (purple), secondary (blue), tertiary (yellow) and quartenary (green) branches from axons (red) are highlighted. (–) Representative images of sections from P7 brains electroporated at E15.5 with control (GFP; ), mkp-1IRES-GFP (mkp-1GFP; ) or shRNA#7 (shRNA#7GFP; ) plasmids. Red lines indicate the boundary between white matter (WM) and lateral striatum (str.). Data from MKP-1 (n = 23), G! FP (n = 14) and shRNA#7 (n = 11) animals were collected from at least 3 independent experiments. Scale bars, 200 μm. (,) Number of axonal branches in the contralateral cortical layers (mean ± s.e.m.). Data were collected from individual axons expressing GFP (n = 8), mkp-1GFP (n = 11), shRNA#7GFP (Sh#7; n = 16), shRNA#6GFP (sh#6; n = 10) from at least five different brains and at least three independent electroporations per condition. Significant differences are indicated as follows: P < 0.05, t-test: *MKP-1 versus GFP; †GFP versus shRNA#7; ‡shRNA#7 versus shRNA#6. * Figure 2: JNK is the MKP-1 substrate that alters axonal morphology. (,) Localization of MKP-1 in primary cortical neurons. () Cytosolic (C) and nuclear (N) extracts were analyzed for endogenous MKP-1. () Transfected Flag-MKP-1. Scale bar, 20 μm. () Cortical neurons were infected with wild-type MKP-1, MKP-1ASA or GFP during DIV1–5 and analyzed by protein blot. () Representative images of neurons expressing MKP-1, MKP-1ASA or GFP. Arrows indicate the longest neurite in each panel. Scale bar, 40 μm. () Length of the longest neurite per cell (mean ± s.e.m.). Numbers in bars indicate the number of cells analyzed. ***P < 0.0001, t-test, n = 3 independent experiments. () Rescue of axon growth by an MKP-1-insensitive JNK mutant (JNKR69S/D326N) when co-transfected with MKP-1. **P < 0.001, t-test, n = 4 independent experiments. () MKP-1 overexpression during DIV1–5 in cortical neurons affected the phosphorylation of stathmins, expressed as percentage of amount in control GFP-expressing cells (mean ± s.e.m.; *P < 0.015, MKP1 versus GFP; **P < 0! .001, MKP1ASA versus GFP using t-test; n = 3 independent experiments). Mono (1p) and multi (4p) phosphoisoforms are active and inactive, respectively. () Tubulin tyrosination (Tyr) and acetylation (Ace) were analyzed to assess microtubule stability. Results are expressed as percentage of control (mean ± s.e.m., n = 3 independent experiments). Significant differences are as follows: MKP-1 versus GFP (#P = 0.03, ##P = 0.006, ***P = 0.0001) and MKP-1ASA versus GFP (**P = 0.001, ###P = 0.004, ***P < 0.0001) using t-test. * Figure 3: Induction of MKP-1 expression by BDNF. Dissociated cortical neurons were cultured for 7 d or the indicated DIV before pharmacological treatments. MKP-1 is highly inducible by BDNF (50 ng ml−1) at any stage in culture () in both flow cytometry–sorted GFP-positive interneurons and GFP-negative excitatory neurons (), as well as by depolarization () using 25 mM KCl for 3 h. (,) Induction was prevented when TrkB signaling (TrkB.Fc, 100 ng ml−1; K252a, 100 nM), the Erk pathway (U0126, 10 μM) or gene expression (CHX, 20 μg ml−1; ActD, 5 μM) were pharmacologically blocked. (,) Treatment of inhibitory or excitatory neurons sorted by flow cytometry from transgenic mice expressing GFP in all cortical interneurons () and mixed cortical neuron cultures () with BDNF (50 ng ml−1) or 45 mM KCl for 2 h leads to a decrease in pJNK immunoreactivity. Results from four independent experiments were quantified, normalized to JNK and expressed as percentage of amount in control cells (mean ± s.e.m., *P = 0.004, t-test). * Figure 4: BDNF controls MKP-1 expression in a spatiotemporal manner. () A 5-min pulse treatment with 50 ng ml−1 BDNF induces transient expression of MKP-1. Arc is shown for comparison. MKP-1 protein levels were expressed as fold induction compared to pre-stimulation (mean + s.d., n = 3). MG132 was added just after the BDNF pulse for the indicated times. () Scheme of the tetOFF system composed of two plasmids used to uncouple MKP-1 expression from BDNF signaling. () MKP-1 protein turnover was rapid but prolonged by BDNF-induced phosphorylation in 293-TrkB cells when MKP-1 induction was uncoupled from BDNF signaling. Addition of doxycyclin (dox) turned off MKP-1 expression. The asterisk indicates that the sample was not treated with BDNF. () Schematic representation of the setup used to physically separate axons from the somatodendritic compartment. () Representative protein blots of the material scraped from both sides of the filter membrane. Pretreatment of the total side with K252a, TrkB.Fc or U0126 had distinct effects on retrograde BDNF ! signaling and MKP-1 induction. Tau and MAP2 are markers of the axons and somatodendritic compartments, respectively. () To uncouple the induction of MKP-1ASA from BDNF signaling we used a tetON system in which doxycyclin induced MKP-1 in cortical neurons infected at DIV1–5. 1p and 4p indicate the mono- and multi-phosphorylated forms of STMN1, respectively. * Figure 5: MKP-1 mediates BDNF-induced axon branching. () Timeline of the experimental procedure used to manipulate axonal branching in vitro. () Number of primary axonal branches (mean ± s.e.m.). Black bars denote TrkB.Fc-treated cells, and open bars represent a BDNF-treated sample. The effect of GFP and TrkB.Fc is significantly different from those of MKP-1 (***P = 0.0004, n = 6 experiments), MKP-1ASA (**P = 0.0046, n = 3 experiments) and GFP-BDNF (*P < 0.0001, n = 5 experiments) using a t-test. () Images of primary branches in GFP-transfected cortical neurons derived from mkp-1−/− mice and wild-type littermates. Scale bar, 50 μm. () Scheme summarizing the effects on branching. Cultured neurons grow axons and branch (black outline). This branching can be enhanced by BDNF or KCl (red lines) in wild-type neurons, but mkp-1 null neurons fail to increase arborization in response to stimulation. () Quantification of the results shown in . Results from 3 mkp-1+/+ and 6 mkp-1−/− embryos expressed as mean ± s.e.m. The numbe! r of cells analyzed is indicated in the bars. BDNF induces branching in wild-type neurons only (wild type, TrkB.Fc versus BDNF: P = 0.0036; mkp-1−/−, N.S. (not significant), TrkB.Fc versus BDNF: P = 0.547; t-test). () Incubation with BDNF for 3 h decreases pJNK in wild-type neurons (Fig. 3e,f) but not in mkp-1−/− cells. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Freddy Jeanneteau & * Katrin Deinhardt Affiliations * Molecular Neurobiology Program, Skirball Institute of Biomolecular Medicine, New York, New York, USA. * Freddy Jeanneteau, * Katrin Deinhardt & * Moses V Chao * Smilow Neuroscience Program, New York University Langone School of Medicine, New York, New York, USA. * Goichi Miyoshi * Department of Pharmacology, Yale University School of Medicine, New Haven, Connecticut, USA. * Anton M Bennett Contributions F.J. and K.D. designed, performed and analyzed experiments. F.J., K.D. and M.V.C. wrote the manuscript. G.M. helped with the in utero electroporations. G.M. and A.M.B. provided mice and reagents. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Freddy Jeanneteau (freddy.jeanneteau@med.nyu.edu) or * Katrin Deinhardt (katrin.deinhardt@med.nyu.edu) Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (1M) Supplementary Figures 1–6 Additional data - Zebrafish atlastin controls motility and spinal motor axon architecture via inhibition of the BMP pathway
- Nat Neurosci 13(11):1380-1387 (2010)
Nature Neuroscience | Article Zebrafish atlastin controls motility and spinal motor axon architecture via inhibition of the BMP pathway * Coralie Fassier1, 2, 3 Search for this author in: * NPG journals * PubMed * Google Scholar * James A Hutt4 Search for this author in: * NPG journals * PubMed * Google Scholar * Steffen Scholpp4, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Andrew Lumsden4 Search for this author in: * NPG journals * PubMed * Google Scholar * Bruno Giros1, 2, 3, 6 Search for this author in: * NPG journals * PubMed * Google Scholar * Fatiha Nothias1, 2, 3 Search for this author in: * NPG journals * PubMed * Google Scholar * Sylvie Schneider-Maunoury3, 7 Search for this author in: * NPG journals * PubMed * Google Scholar * Corinne Houart4, 8corinne.houart@kcl.ac.uk Search for this author in: * NPG journals * PubMed * Google Scholar * Jamilé Hazan1, 2, 3, 4, 8jhazan@snv.jussieu.fr Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 13 ,Pages:1380–1387Year published:(2010)DOI:doi:10.1038/nn.2662Received22 July 2010Accepted26 August 2010Published online10 October 2010 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg To better understand hereditary spastic paraplegia (HSP), we characterized the function of atlastin, a protein that is frequently involved in juvenile forms of HSP, by analyzing loss- and gain-of-function phenotypes in the developing zebrafish. We found that knockdown of the gene for atlastin (atl1) caused a severe decrease in larval mobility that was preceded by abnormal architecture of spinal motor axons and was associated with a substantial upregulation of the bone morphogenetic protein (BMP) signaling pathway. Overexpression analyses confirmed that atlastin inhibits BMP signaling. In primary cultures of zebrafish spinal neurons, Atlastin partially colocalized with type I BMP receptors in late endosomes distributed along neurites, which suggests that atlastin may regulate BMP receptor trafficking. Finally, genetic or pharmacological inhibition of BMP signaling was sufficient to rescue the loss of mobility and spinal motor axon defects of atl1 morphants, emphasizing the im! portance of fine-tuning the balance of BMP signaling for vertebrate motor axon architecture and stability. View full text Figures at a glance * Figure 1: Zebrafish atl1 expression and knockdown. () Whole-mount atl1 in situ hybridization associated with immunostaining for the pan-neural marker HuC/D. Top left, lateral view of the head and anterior part of the trunk at 22 hpf; middle left, transverse sections of the trunk at 22 hpf; bottom left, lateral view of head and eye (inset) at 40 hpf; top middle and right, lateral view of trunks at 22 hpf; center and middle right, higher magnification of lateral views of the spinal cord (arrow marks atl1 expression in SMNs); bottom middle and right, dorsal view of flat-mounted hindbrains at 22 hpf. atl1 transcript is enriched in post-mitotic neurons in the different compartments of the neural tube. Scale bars, 100 μm. () Protein blot analysis of atlastin expression during zebrafish development. () Protein blot analysis of atl1 knockdown efficiency. Atlastin is markedly decreased in 24-hpf atl1 morphant embryos (MOatl) compared to control embryos (Ctl). Full-length protein blots are shown in Supplementary Figure 2. * Figure 2: Knockdown of atl1 causes a strong decrease in larval mobility. () Tracking analyses of 72-hpf control, atl1 morphant (MOatl) and rescued larvae injected with both atl1 morpholino and human ATL1 transcript (MOatl + mRNAatl) in a touch-response test. Each plot line represents the trajectory of one larva after touch stimulation. () Quantification of the mean swimming speed. () Quantification of the mean covered distance; atl1 morphant larvae swim significantly slower (***P < 0.0001) and over shorter distances (**P = 0.0092) than control larvae. These locomotor defects are fully rescued by concomitant overexpression of human ATL1 (P < 0.0001 for both covered distance and speed, Student's unpaired t-test). Error bars show s.e.m. * Figure 3: Knockdown of atl1 leads to abnormal architecture of SMN axons. () Immunostaining of 58-hpf control, morphant (MOatl) and rescued larvae (MOatl + mRNAatl) with znp1 antibody, showing lateral views of the trunk (anterior to left; right column shows higher magnification of left column). Arrows indicate abnormal additional branching of MOatl SMN axons. () Immunostaining of 58-hpf control and morphant (MOatl) larvae with antibody to acetylated α-tubulin. Left, dorsal view of the head. Arrows indicate defects in cerebellum organization in MOatl larvae. Right, lateral view of the trunk, anterior to the left. Atlastin depletion induces a marked decrease in acetylated α-tubulin staining of SMN axons. () Quantification of SMN axon branching (mean ± s.e.m.) in eight somites centered around the anus in control, morphant (MOatl) and rescued (MOatl + mRNAatl) larvae. The number of axonal branches is significantly higher in MOatl larvae than in controls and is partially rescued by overexpressing human ATL1 (***P < 0.0001, Student's unpaired t-test)! . () Mauthner fibers are not affected in MOatl larvae. Dorsal views of 4-dpf control and MOatl embryos immunolabeled with 3A10 antibody, anterior to the left. (,,) Scale bars, 50 μm. * Figure 4: Effect of transplanted SMNs on larval mobility. () Homotopic transplantation of control or morphant Hb9:GFP ventral spinal cord precursors into wild-type (WT) hosts at 70–80% epiboly and resulting prim-5 embryo. Hb9:GFP stands for Tg(mnx1:mGFP) transgenic embryos. The anterior neural plate is framed in the top left part of the embryo, while the spinal precursors are located below the dashed line (sensory neurons, interneurons and motor neurons from left to right). Scale bars, 100 μm. () Tracking analyses of motor behavior in 4-dpf control (Hb9:GFP; WT), atl1 morphant (Hb9:GFP; MOatl) and transplanted (Hb9:GFP; MOatl>WT) larvae in a touch-response test. Each plot line represents the trajectory of one larva after a touch stimulation. () Quantification of the mean swimming speed and mean covered distance (± s.e.m.); both atl1 morphant (Hb9:GFP; MOatl) and transplanted (Hb9:GFP; MOatl>WT) larvae swim significantly slower and over shorter distances than control larvae (***P < 0.0001 for both covered distance and speed, Stu! dent's unpaired t-test). () Immunostaining of 50-hpf transplanted control (Hb9:GFP; WT>WT) and morphant (Hb9:GFP; MOatl>WT) larvae with antibodies to znp1 and GFP. Lateral views of the trunk, anterior to the left. Scale bars, 50 μm. On the higher magnification images (right), asterisks indicate aberrant branching of transplanted MOatl SMN axons in a wild-type host. The presence of hyper-branched MOatl SMN axons in a wild-type context is correlated with the impaired mobility of the larvae. * Figure 5: Atlastin inhibits BMP signaling. () Overexpression of atl1 generates dorsalized embryos. Lateral view of a 48-hpf wild-type and two atl1 mRNA-injected embryos. In the mildly dorsalized embryo (middle), the arrows mark the absence of ventral tail fin. () Misexpression of atl1 partially rescues the ventralized phenotype of the chordino mutant. Lateral views of the trunks of noninjected (left) and atl1-overexpressing (right) chordin−/− embryos at 24 hpf (anterior to the left). The arrow indicates the reduction in the accumulation of ventral blood islands in atl1-injected chordin−/− embryos. () Immunolabeling of 60%-epiboly wild-type and atl1 mRNA-injected embryos with an antibody to P-Smad1/5/8. Embryos were flat mounted, ventral to left. Nuclei are stained with DAPI (left panels). Right panels show higher magnifications of the boxed regions of middle panels; atl1 overexpression causes a reduction in the size of the ventral P-Smad1/5/8–positive domain and in the fluorescence intensity of P-Smad1/5/8 ! staining in 93% of atl1-injected embryos (n = 40) compared with control embryos (n = 38). () Expression pattern of GATA3, a transcriptional target of BMP signaling, in 80%-epiboly wild-type and atl1-overexpressing embryos. Lateral (left) and animal (right) pole views of the embryo, ventral on the left. The GATA3 expression domain is reduced in 70% of atl1-injected embryos (n = 149) compared to controls (n = 146). Scale bars, 200 μm, except for higher magnification images (, right), scale bar, 20 μm. * Figure 6: Upregulation of BMP signaling in atl1 morphant embryos. () Increased phosphorylation of Smad1/5/8 in 24-hpf atl1 morphants (MOatl). Protein blot analyses showing the differential levels of atlastin and phosphorylated Smad1/5/8 (P-Smad1/5/8) relative to the level of total Smad1 and type I BMP receptor (BMPRI) between 24-hpf control and MOatl embryos. H2b was used as a loading control. The full-length blot is shown in Supplementary Figure 2. (b) Quantification of P-Smad1/5/8 and BMPRI expression (immunoblot band density, mean ± s.e.m.) in 24-hpf control and MOatl embryos, normalized to H2b value in three independent experiments. Thirty embryos from each set were used in each experiment; atl1 knockdown significantly increased P-Smad1/5/8 expression (**P = 0.005, Student's unpaired t-test) and to a lesser extent BMPRI expression (*P = 0.006). () Increased P-Smad1/5/8 signal in the nuclei of MOatl spinal neurons. Immunodetection of P-Smad1/5/8 and acetylated α-tubulin in control and MOatl zebrafish cultured spinal neurons 5 h after ! plating. The mean fluorescence intensity of the P-Smad1/5/8 signal is significantly higher in MOatl spinal neuron nuclei than in control nuclei (P < 0.001, Student's unpaired t-test). Scale bar, 10 μm. () Distribution of P-Smad1/5/8 mean fluorescence intensity in control and MOatl spinal neuron nuclei. * Figure 7: Atlastin and type I BMP receptor (BMPRI) partially co-localize to late endosomes in zebrafish spinal neurons. Panels show immunolabeling of zebrafish cultured spinal neurons 28 h after plating using polyclonal antibodies to atlastin, BMPRI and Rab7. Images, and thereby neuron cell bodies, are voluntarily overexposed to detect signals in the axons and focus on axonal co-localization. Right column shows higher magnification images of axon regions boxed in left column. Insets show enlarged views of axon regions. Arrowheads and arrows mark examples of double and triple co-localization, respectively. All images are single confocal sections. Scale bars, 10 μm. * Figure 8: Genetic inhibition of BMP signaling rescues atl1 morphant mobility and spinal motor axon architecture. () Tracking analyses of touch-evoked motility in 72-hpf heat-shocked control Tg(hs:DN-BMPRI) larvae (left), atl1 morphant Tg(hs:DN-BMPRI) larvae that were not submitted to heat shock (MOatl Tg(hs:DN-BMPRI); middle) and heat-shocked MOatl Tg(hs:DN-BMPRI) expressing a dominant-negative version of type-I BMP receptor (right). () Each plot line represents the trajectory of one larva after a touch stimulation. () Quantification of the mean (± s.e.m.) covered distance. () Quantification of the mean (± s.e.m.) swimming speed. MOatl Tg(hs:DN-BMPRI) larvae that were not heat shocked swam significantly slower and over shorter distances (***P < 0.0001) than heat-shocked MOatl Tg(hs:DN-BMPRI) and Tg(hs:DN-BMPRI) control larvae (Student's unpaired t-test). (,) Whole-mount immunolabeling of 56-hpf control and atl1 morphant Tg(hs:DN-BMPRI) transgenic larvae with antibodies to acetylated α-tubulin and znp1. Lateral view of the trunk, anterior to the left. Tg(hs:DN-BMPRI) are non-injected! transgenic larvae that were heat shocked or not, and MOatl Tg(hs:DN-BMPRI) are atl1 morphant transgenic larvae that were submitted to heat shock or not. Asterisks indicate axon stumps, arrows mark abnormal branches. Scale bars, 50 μm. () Quantification of axon branching and stumps. The histogram represents the average number of spinal motor axon branches or stumps in eight somites centered around the anus for each embryo (n = 12 for each condition). The number of stumps and branches in heat-shocked MOatl Tg(hs:DN-BMPRI) embryos is significantly less than in MOatl Tg(hs:DN-BMPRI) that were not heat shocked (P < 0.001, Student's unpaired t-test). Error bars are s.e.m. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Corinne Houart & * Jamilé Hazan Affiliations * CNRS UMR 7224, Physiopathologie des Maladies du Système Nerveux Central, Paris, France. * Coralie Fassier, * Bruno Giros, * Fatiha Nothias & * Jamilé Hazan * INSERM U952, Paris, France. * Coralie Fassier, * Bruno Giros, * Fatiha Nothias & * Jamilé Hazan * UPMC, University Paris 06, Paris, France. * Coralie Fassier, * Bruno Giros, * Fatiha Nothias, * Sylvie Schneider-Maunoury & * Jamilé Hazan * Medical Research Council Centre for Developmental Neurobiology, King's College London, London, UK. * James A Hutt, * Steffen Scholpp, * Andrew Lumsden, * Corinne Houart & * Jamilé Hazan * Institute of Toxicology and Genetics, Karlsruhe Institute of Technology, Karlsruhe, Germany. * Steffen Scholpp * Douglas Hospital, Department of Psychiatry, McGill University, Montreal, Canada. * Bruno Giros * CNRS UMR7622, Biologie du Développement, Paris, France. * Sylvie Schneider-Maunoury Contributions J.H. and C.F. performed most experiments and analyzed the data with C.H. J.A.H. and S.S. helped with image acquisition and in situ hybridization and C.H. with transplantation. Half of the study was carried out in the C.H. lab by J.H., S.S.-M. and F.N. A.L. and B.G. welcomed J.H. and C.F. in their labs and gave insightful advice on the project. J.H. and C.H. designed all experiments and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Jamilé Hazan (jhazan@snv.jussieu.fr) or * Corinne Houart (corinne.houart@kcl.ac.uk) Supplementary information * Abstract * Author information * Supplementary information Movies * Supplementary Video 1 (1M) Abnormal touch-evoked motility of atlastin (atl1) morphant larvae. Touch-response mobility of 72-hpf () control larvae. * Supplementary Video 1 (3M) Abnormal touch-evoked motility of atlastin (atl1) morphant larvae. Touch-response mobility of 72-hpf () atl1 morphant larvae. * Supplementary Video 1 (1M) Abnormal touch-evoked motility of atlastin (atl1) morphant larvae. Touch-response mobility of 72-hpf () rescued larvae co-injected with atl1 MO and human ATL1 transcript. * Supplementary Video 2 (2M) The motility deficit of atlastin (atl1) The motility deficit of atlastin (atl1) morphant larvae is tightly correlated with abnormal branching of spinal motor axons. Touch-response mobility of 4-dpf () control (Hb9:GFP; WT). * Supplementary Video 2 (2M) The motility deficit of atlastin (atl1) The motility deficit of atlastin (atl1) morphant larvae is tightly correlated with abnormal branching of spinal motor axons. Touch-response mobility of 4-dpf () atl1 morphant Hb9:GFP; MOatl). * Supplementary Video 2 (2M) The motility deficit of atlastin (atl1) The motility deficit of atlastin (atl1) morphant larvae is tightly correlated with abnormal branching of spinal motor axons. Touch-response mobility of 4-dpf () transplanted (Hb9:GFP; MOatl>WT) mosaic larvae. * Supplementary Video 3 (2M) The swimming deficit of atlastin (atl1) morphants is rescued by genetic inhibition of BMP signaling. Touch-response mobility of 72-hpf () heatshocked and non-injected Tg(hs:DN-BMPRI) transgenic larvae. * Supplementary Video 3 (2M) The swimming deficit of atlastin (atl1) morphants is rescued by genetic inhibition of BMP signaling. Touch-response mobility of 72-hpf () atl1 morphant Tg(hs:DN-BMPRI) larvae which were not submitted to heat shock. * Supplementary Video 3 (2M) The swimming deficit of atlastin (atl1) morphants is rescued by genetic inhibition of BMP signaling. Touch-response mobility of 72-hpf () MOatl/Tg(hs:DN-BMPRI) that were heat-shocked at 32-36 hpf and therefore expressed a dominant-negative version of type-I BMP receptor. PDF files * Supplementary Text and Figures (5M) Supplementary Figures 1–10, and Tables 1 and 2 Additional data - A crosstalk between β1 and β3 integrins controls glycine receptor and gephyrin trafficking at synapses
- Nat Neurosci 13(11):1388-1395 (2010)
Nature Neuroscience | Article A crosstalk between β1 and β3 integrins controls glycine receptor and gephyrin trafficking at synapses * Cécile Charrier1 Search for this author in: * NPG journals * PubMed * Google Scholar * Patricia Machado1 Search for this author in: * NPG journals * PubMed * Google Scholar * Ry Y Tweedie-Cullen2 Search for this author in: * NPG journals * PubMed * Google Scholar * Dorothea Rutishauser3 Search for this author in: * NPG journals * PubMed * Google Scholar * Isabelle M Mansuy2 Search for this author in: * NPG journals * PubMed * Google Scholar * Antoine Triller1triller@biologie.ens.fr Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 13 ,Pages:1388–1395Year published:(2010)DOI:doi:10.1038/nn.2645Received24 March 2010Accepted26 August 2010Published online10 October 2010 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The regulation of glycine receptor (GlyR) number at synapses is necessary for the efficacy of inhibition and the control of neuronal excitability in the spinal cord. GlyR accumulation at synapses depends on the scaffolding molecule gephyrin and is linked to GlyR synaptic dwell time. However, the mechanisms that tune GlyR synaptic exchanges in response to different neuronal environments are unknown. Integrins are cell adhesion molecules and signaling receptors. Using single quantum dot imaging and fluorescence recovery after photobleaching, we found in rats that β1 and β3 integrins adjust synaptic strength by regulating the synaptic dwell time of both GlyRs and gephyrin. β1 and β3 integrins crosstalked via calcium/calmodulin-dependent protein kinase II and adapted GlyR lateral diffusion and gephyrin-dependent trapping at synapses. This provides a mechanism for maintaining or adjusting the steady state of postsynaptic molecule exchanges and the level of glycinergic inhibit! ion in response to neuron- and glia-derived signals or extracellular matrix remodeling. View full text Figures at a glance * Figure 1: RGD peptides increase GlyR numbers at synapses. () Spinal cord neurons (12 d in vitro) stained for α1-GlyR and synapsin I in control conditions or after treatment with echistatin (1 h, 100 nM). Scale bar represents 20 μm. () Cumulative probability plot of synaptic GlyR cluster–associated fluorescence in control conditions (black) and after a 1-h echistatin treatment (gray) (control, n = 2,740; echistatin, n = 2,549; from 21 cells by condition, P < 0.001, Mann-Whitney test). a.u., arbitrary unit. () Increased GlyR-associated fluorescence intensity at synapses after treatment with echistatin or GRGDSP peptide (gray) compared with control or treatment with GRGESP peptide (black). Ctr, control; Echis, ehcistatin; RGE, GRGESP; RGD, GRGDSP Mean ± s.e.m. (***P < 0.001, t test). * Figure 2: β1 and β3 integrin blocking antibodies have opposite effects on GlyR numbers at synapses. () Nonpermeabilized cells stained for α1-GlyR in control conditions or after 1-h treatment with β3 (aβ3) or β1 (aβ1) function-blocking antibodies. Scale bar represents 20 μm. () Normalized fluorescence intensity associated with GlyR clusters (mean ± s.e.m., ***P < 0.001, t test). () Examples of glycinergic mIPSCs and cumulative probability plot of their amplitudes from 2-min recording periods from the same cells before and 20 min after aβ3 or aβ1 treatment. Scale bars represent 100 pA and 1 s. () Average mIPSC amplitude before and after aβ1 or aβ3 treatment or after a 20-min time lag (control) for each cell (control, not significant (NS), P > 0.05; aβ1 and aβ3, P < 0.01; Mann-Whitney test). () Relative effects on mIPSC amplitudes. Mean amplitudes after treatment are plotted relative to the mean amplitudes before treatment (***P < 0.001, ANOVA). () Mean effects on mIPSC frequency (P > 0.05, ANOVA). Error bars indicate s.e.m. * Figure 3: β1 and β3 integrins control GlyR lateral diffusion. () Maximum intensity projections of 512 frames recorded at 13 Hz for 38.4 s. The GlyR-QD traces and FM4-64–stained synapses are green and red, respectively; yellow denotes their overlap. The GyR-QD–explored area increased after aβ3 or aβ1 treatment in the extrasynaptic membrane (arrowheads). At synapses, aβ3 and aβ1 reduced and increased GlyR-QD mobility (arrows), respectively. Scale bar represents 5 μm. () Cumulative probability plot of GlyR-QD diffusion coefficients in the extrasynaptic membrane (ES, P < 0.001, Mann-Whitney test). () Cumulative probability plot of GlyR-QD diffusion coefficients at synapses (S: aβ3, P < 0.01; aβ1, P < 0.001; Mann-Whitney test). () Normalized effects of aβ1 and aβ3 on GlyR-QD diffusion coefficients (mean ± s.e.m., ***P < 0.001, ANOVA). Control values indicate the relative fluctuation between two control distributions (Ctra and Ctrb) of diffusion coefficients (ES: nCtra = 300, nCtrb = 524; S: nCtra = 300, nCtrb = 524). Note that! β1 and β3 integrin inhibition had comparable effects in the extrasynaptic membrane and opposite effects at synapses. * Figure 4: β1 and β3 integrins modulate GlyR confinement and dwell time at synapses. () Examples of GlyR-QD trajectories (black) over FM4-64–stained synapses (red) from control, aβ3- and aβ1-treated neurons. Trajectories analyzed in are denoted with an asterisk. Scale bar represents 1 μm. (,) Treatment with aβ3 (green) and aβ1 (red) increased and decreased confinement of GlyR-QDs, respectively. MSD versus time plot for GlyR-QD trajectories indicated in is shown in . The normalized size of the confinement domain at synapses is shown in . Note that the smaller the confinement domain, the greater the confinement (mean ± s.e.m., ***P < 0.001, Mann-Whitney test). (,) Dwell time of GlyR-QDs at synapses. A cumulative probability plot () and mean dwell time index () are shown. Error bars indicate s.e.m. (*P < 0.05, Mann-Whitney test). * Figure 5: β1 and β3 integrins control gephyrin amount and exchanges at synapses. () Immunostaining for gephyrin in control conditions or after aβ3 or aβ1 treatment. Scale bar represents 20 μm. () Normalized fluorescence intensity associated with endogenous gephyrin clusters (mean ± s.e.m., ***P < 0.001, t test). () Representative example of transfected neurons expressing VeGe (green). VeGe forms clusters in front of active presynaptic boutons stained with FM4-64 (red). The white square outlines the region shown in . Scale bar represents 1 μm. () Photobleaching of an individual synaptic VeGe cluster (arrow) and time-lapse recording of the fluorescence recovery over 20 min. The color scale indicates the level of fluorescence. () Fluorescence recovery curves (mean ± s.e.m.). () Mean fluorescence recovery 10 min after photobleaching (error bars represent s.e.m., **P < 0.01 and ***P < 0.001, Mann-Whitney test). F0, initial fluorescence. * Figure 6: Actin, PKC and CaMKII mediate integrin-dependent regulation of GlyR lateral dynamics. (,,) Cumulative distributions of GlyR-QD diffusion coefficients. (,,) Histograms of normalized fluorescence intensity associated with GlyR clusters (mean ± s.e.m.). (,) Effects of aβ1 (red) and aβ3 (green) treatment after F-actin disruption with latrunculin (Lat, 3 μM, black). Latrunculin abolished the extrasynaptic (P > 0.05, Mann-Whitney test), but not the synaptic, effects on GlyR diffusion (Lat and ab1, P < 0.05; Lat and ab3, P < 0.001, Mann-Whitney test) and cluster immunoreactivity. (,) Effects of aβ1 (red) and aβ3 (green) treatment after PKC inhibition (GFX, 50 nM, black). GFX abolished both the extrasynaptic and synaptic effects on GlyR diffusion (P > 0.05, Mann-Whitney test) and cluster immunoreactivity. (,) Effects of CaMKII inhibition (KN-93, 10 μM, black) compared with the control (blue) and effects of aβ1 (red) and aβ3 (green) treatment after CaMKII inhibition. () In the extrasynaptic membrane, KN-93 had no effect on GlyR mobility. At synapses, KN-93 in! creased GlyR mobility (P < 0.001, Mann-Whitney test) and prevented the effects of aβ1 and aβ3 (P > 0.05, Mann-Whitney test). () At synapses, CaMKII inhibition decreased GlyR cluster immunoreactivity (blue scale, left) and prevented the effects of aβ1 and aβ3 treatments (black scale, right). ***P < 0.001 and **P < 0.01, NS indicates P > 0.05, ANOVA. * Figure 7: TSP1 and fibrinogen have opposite effects at inhibitory synapses. () Typical behavior of GlyR-QDs after 1-h treatment with thrombospondin 1 (TSP1, 2 μg ml−1). Maximum intensity projections of 512 frames recorded at 13 Hz. The GlyR-QD explored area is shown in green and FM4-64–stained synapses in red. GlyR-QDs have a reduced mobility in (arrows) and out (arrowheads) of synapses. Scale bar represents 1 μm. () Distributions of GlyR-QD diffusion coefficients at extrasynaptic and synaptic locations in control condition (black) or after TSP1 treatment (red) (P < 0.001, Mann-Whitney test). () Normalized fluorescence intensity associated with GlyR and gephyrin clusters at synapses (mean ± s.e.m., ***P < 0.001, t test). () Typical behavior of GlyR-QD after 1-h treatment with fibrinogen (Fib, 1.5 mg ml−1). Colors are as described in . GlyR-QDs were very mobile at synapses, but not in the extrasynaptic membrane. () Distributions of GlyR-QD diffusion coefficients at extrasynaptic and synaptic locations after treatment with fibrinogen (green) ! or with its vehicle (veh, black) (P < 0.001, Mann-Whitney test). () Data are presented as in (mean ± s.e.m.). Colors are as described in . Note that TSP1 increased the stabilization and the number of GlyRs at synapses, whereas fibrinogen had the opposite effect. Author information * Abstract * Author information * Supplementary information Affiliations * Biologie Cellulaire de la Synapse, IBENS, Ecole Normale Supérieure, Inserm U1024, CNRS UMR8197, Paris, France. * Cécile Charrier, * Patricia Machado & * Antoine Triller * Brain Research Institute, University of Zürich, Swiss Federal Institute of Technology, Zürich, Switzerland. * Ry Y Tweedie-Cullen & * Isabelle M Mansuy * Functional Genomics Center Zürich, University of Zürich, Swiss Federal Institute of Technology, CH-8057 Zürich, Switzerland. * Dorothea Rutishauser Contributions C.C. designed, performed and analyzed the experiments except for the in vitro phosphorylation assays and mass spectrometry and wrote the manuscript with help from the other authors. P.M. performed the in vitro phosphorylation assays. R.Y.T.-C. and D.R. performed mass spectrometry and analyzed data. I.M.M. supervised mass spectrometry and phosphorylation analyses. A.T. supervised the project. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Antoine Triller (triller@biologie.ens.fr) Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (3M) Supplementary Figures 1–10 Additional data - Wild-type and mutant SOD1 share an aberrant conformation and a common pathogenic pathway in ALS
- Nat Neurosci 13(11):1396-1403 (2010)
Nature Neuroscience | Article Wild-type and mutant SOD1 share an aberrant conformation and a common pathogenic pathway in ALS * Daryl A Bosco1, 8daryl.bosco@umassmed.edu Search for this author in: * NPG journals * PubMed * Google Scholar * Gerardo Morfini2, 7, 8 Search for this author in: * NPG journals * PubMed * Google Scholar * N Murat Karabacak3 Search for this author in: * NPG journals * PubMed * Google Scholar * Yuyu Song2, 7 Search for this author in: * NPG journals * PubMed * Google Scholar * Francois Gros-Louis4 Search for this author in: * NPG journals * PubMed * Google Scholar * Piera Pasinelli5 Search for this author in: * NPG journals * PubMed * Google Scholar * Holly Goolsby6 Search for this author in: * NPG journals * PubMed * Google Scholar * Benjamin A Fontaine1 Search for this author in: * NPG journals * PubMed * Google Scholar * Nathan Lemay1 Search for this author in: * NPG journals * PubMed * Google Scholar * Diane McKenna-Yasek1 Search for this author in: * NPG journals * PubMed * Google Scholar * Matthew P Frosch6 Search for this author in: * NPG journals * PubMed * Google Scholar * Jeffrey N Agar3 Search for this author in: * NPG journals * PubMed * Google Scholar * Jean-Pierre Julien4 Search for this author in: * NPG journals * PubMed * Google Scholar * Scott T Brady2, 7 Search for this author in: * NPG journals * PubMed * Google Scholar * Robert H Brown Jr1robert.brown@umassmed.edu Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 13 ,Pages:1396–1403Year published:(2010)DOI:doi:10.1038/nn.2660Received19 July 2010Accepted10 September 2010Published online17 October 2010 Abstract * Abstract * Accession codes * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Many mutations confer one or more toxic function(s) on copper/zinc superoxide dismutase 1 (SOD1) that impair motor neuron viability and cause familial amyotrophic lateral sclerosis (FALS). Using a conformation-specific antibody that detects misfolded SOD1 (C4F6), we found that oxidized wild-type SOD1 and mutant SOD1 share a conformational epitope that is not present in normal wild-type SOD1. In a subset of human sporadic ALS (SALS) cases, motor neurons in the lumbosacral spinal cord were markedly C4F6 immunoreactive, indicating that an aberrant wild-type SOD1 species was present. Recombinant, oxidized wild-type SOD1 and wild-type SOD1 immunopurified from SALS tissues inhibited kinesin-based fast axonal transport in a manner similar to that of FALS-linked mutant SOD1. Our findings suggest that wild-type SOD1 can be pathogenic in SALS and identify an SOD1-dependent pathogenic mechanism common to FALS and SALS. View full text Figures at a glance * Figure 1: Mass spectrometry confirms the oxidation of wild-type SOD1 on exposure to hydrogen peroxide (H2O2). (,) The FT-MS spectra for untreated wild-type SOD1 () and oxidized wild-type SOD1 (SOD1ox, ). The data shown here have been automatically deconvoluted and reconstructed into a mass domain. The conditions under which the FT-MS analysis was performed reduced the integrity of the SOD1 dimer interface and the SOD1 metal-binding capacity (). Thus, the apo form of wild-type SOD1 (15,844 Da, average nominal mass) was the predominate species in the mass spectrum of unmodified wild-type SOD1. Peaks representing SOD1 adducts containing sodium, potassium and phosphate ions from the buffers employed during the purification of SOD1 are indicated. The predominant species in the SOD1ox spectrum had a mass increase of 48 Da (15,892 Da) relative to apo-SOD1, which corresponds to the incorporation of three oxygens (+3ox, +48 Da) (). () SOD1 proteins were subjected to gas-phase isolation followed by ECD (shown for SOD1ox). MS/MS fragments were assigned using monoisotopic masses with a 5 ppm cu! toff and superimposed on the SOD1 primary sequence (top), where indicates unmodified c-type fragment ions that include the N terminus, indicates unmodified z-type fragment ions that include the C terminus and the red indicates +48 Da modified z-type fragment ions corresponding to the conversion of the sulfhydryl group at Cys 111 into sulfonic acid (+3ox). Inset shows raw data for c729+ fragment. The SOD1ox peptides resulting from ECD that were used to deduce the Cys111 site of oxidation are shown in Supplementary Table 1. * Figure 2: The structure of wild-type SOD1. The X-ray crystallographic structure of wild-type SOD1 (Protein database, accession #2C9V)48 is shown, modeled in PyMOL. Wild-type SOD1 residues G93 and C111 in exon 2 are highlighted and labeled in purple. The zinc and copper atoms are shown in cyan and orange, respectively. SOD1 conformation-specific antibodies epitope mapped to the following regions: C4F6 to exon 4 (residues H80–V118 highlighted in red), A9G3 (Fig. 4c) to exons 1 and 2 (comprised of β strands 1–4), SEDI38 to β strand 8 and USOD33 to β strand 4. * Figure 3: The C4F6 monoclonal antibody reacts with a conformational epitope shared by SOD1ox and mutant SOD1. () Recombinant SOD1ox and wild-type SOD1 (6 μg per lane) were subjected to a western analysis using native (nondenaturing) gels with the C4F6 and SDG6 monoclonal antibodies. Native SOD1ox, but not wild-type SOD1, was detected by C4F6, whereas SDG6 was reactive for both proteins. The samples were diluted (1 ng per lane) and subjected to an SDS (denaturing) western analysis with a polyclonal anti-SOD1 antibody (binding site) to demonstrate equal gel loading. () The native western blot revealed that C4F6 only reacted to native SOD1 G93A, whereas SDG6 only reacted to native wild-type SOD1 in lysates (30 μg total protein per lane) that were derived from the respective transgenic mouse. The SDS (denaturing) western analysis, performed as in , indicated that gel loading was equal. () C4F6 was reactive for recombinant SOD1 G93A (55 ng per lane), but not SODox (55 ng per lane), whereas a polyclonal antibody to SOD1 (Calbiochem) detected both proteins. () Under denaturing conditions! , C4F6 was only reactive for SOD1 G93A and not for the other indicated SOD1 mutants. () C4F6 epitope mapped to exon 4. Lysates (30 μg total protein) from HEK 293 mammalian cells transfected with the indicated GST-tagged construct (Δ1–5 denote the respective exon-deleted construct; FL, full length) were probed with C4F6 or a polyclonal antibody to SOD1 (Binding Site). * Figure 4: SOD1ox recapitulates the inhibitory effect of FALS-linked mutant SOD1 on anterograde FAT. (–) Vesicle motility assays in isolated squid axoplasm. Individual fast axonal transport (FAT) velocity (μm s−1) measurements (arrowheads) are plotted as a function of time (min). Dark arrowheads and line represent anterograde, conventional kinesin-dependent FAT rates. Gray arrows and line represent retrograde, dynein-dependent FAT rates. Perfusion of 5 μM of the FALS-linked H46R mutant into squid axoplasm caused a marked reduction in the rate of anterograde FAT (n = 4, ). In contrast, perfusion of 5 μM wild-type SOD1 in the squid axoplasm had no effect on anterograde or retrograde FAT rates (n = 4, ). Perfusion of 5 μM SOD1ox mimicked the inhibitory effect of SOD1 H46R on anterograde FAT (n = 4, ). * Figure 5: p38 mediates the inhibition of anterograde FAT induced by SOD1ox. () Immunoblotting analysis using activation-specific phosphoantibodies revealed a marked activation of p38 (p-p38) in axoplasms perfused with recombinant oxidized SOD1 (SOD1ox), compared to those perfused with recombinant unmodified wild-type SOD1 (WT). In contrast, no changes were found in the activities of ERK (pERK) and GSK3 (pGSK3) in association with a specific SOD1 species. A monoclonal antibody against SOD1 (D3H5)22 confirmed similar levels of SOD1 perfusion, and antibodies to kinesin-1 (KHC) provided a loading control for total levels of axoplasmic protein. Results from three independent experiments are shown (Squid 1–3). () Quantification of results in reveals an approximately fourfold increase in the phosphorylation of p38 kinase (indicative of p38 activation) in SOD1ox-perfused axoplasms, compared to unmodified wild-type SOD1-perfused axoplasms (n = 6, *P < 0.05 by the pooled t test of μ1-μ2). Error bars reflect the standard error of multiple measurements. Co-! perfusion of the highly specific p38 inhibitors SB203580 () and MW01-2-069SRM () blocked the inhibitory effect of SOD1ox on anterograde FAT (compare to Fig. 4c). Similarly, FALS-linked mutant SOD1 polypeptides inhibit anterograde FAT through a mechanism involving activation of p38 kinase (G.M. and S.T.B., unpublished observations, and ref. 10). * Figure 6: The C4F6 monoclonal antibody is reactive for wild-type SOD1 in SALS tissues. () C4F6 positive staining is shown for a SALS case (SALS1). (,) The positive staining observed for SALS1 was lost when C4F6 was excluded from the staining protocol () or when the alternative SOD1-mutant specific A9G3 antibody was employed (). (–) C4F6 positive staining is shown for three SALS cases (SALS2–4). (–) Representative control cases (,) and an SOD1-negative FALS case () showing the lack of positive C4F6 reactivity for such cases. In total, four out of nine SALS cases exhibited positive C4F6 staining, whereas 0 of 17 control cases exhibited positive staining. For clinical and demographic information on these cases, see Supplementary Tables 2 and 3. * Figure 7: Wild-type SOD1 purified from SALS tissues inhibits anterograde FAT. hSOD1 immunopurified from SpCs of SALS (SALS hSOD1) and control (Ctrl hSOD1) were perfused into isolated squid axoplasm and the effects on FAT were evaluated as in Figure 4. () Perfusion of SALS-derived hSOD1 (1 μM) selectively inhibited anterograde FAT (dark lines, right arrowheads) while retrograde FAT (gray lines, left arrowheads) remained unchanged (n = 5 motility plots from 2 independent immunopurifications of hSOD1). The inhibitory effect of SALS-derived hSOD1 on FAT mimicked that of FALS-SOD1 H46R and SOD1ox (Fig. 4). () Perfusion of control-derived hSOD1 had no effect on FAT (n = 3 motility plots from 2 independent immunopurifications). () Co-perfusion of the C4F6 monoclonal antibody (22.5 ng) with SALS-derived hSOD1 blocked the inhibitory effect of SOD1 on anterograde FAT (n = 3 axoplasms), demonstrating that the C4F6-reactive SOD1 species mediate the inhibitory effect on FAT. Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions Protein Data Bank * 2C9V * 2C9V Author information * Abstract * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Daryl A Bosco & * Gerardo Morfini Affiliations * Department of Neurology, University of Massachusetts Medical Center, Worcester, Massachusetts, USA. * Daryl A Bosco, * Benjamin A Fontaine, * Nathan Lemay, * Diane McKenna-Yasek & * Robert H Brown Jr * Department of Anatomy and Cell Biology, University of Illinois at Chicago, Chicago, Illinois, USA. * Gerardo Morfini, * Yuyu Song & * Scott T Brady * Department of Chemistry, Brandeis University, Waltham, Massachusetts, USA. * N Murat Karabacak & * Jeffrey N Agar * Department of Psychiatry and Neuroscience, Laval University, Research Centre of CHUQ, Quebec, Canada. * Francois Gros-Louis & * Jean-Pierre Julien * Weinberg Unit for ALS Research, Farber Institute for the Neurosciences, Thomas Jefferson University, Philadelphia, Pennsylvania, USA. * Piera Pasinelli * C.S. Kubik Laboratory for Neuropathology, Massachusetts General Hospital, Boston, Massachusetts, USA. * Holly Goolsby & * Matthew P Frosch * Marine Biological Laboratory, Woods Hole, Massachusetts, USA. * Gerardo Morfini, * Yuyu Song & * Scott T Brady Contributions D.A.B., G.M., S.T.B. and R.H.B. Jr wrote the manuscript. D.A.B. prepared recombinant and immunopurified SOD1 proteins. G.M., Y.S. and S.T.B. performed vesicle motility assays and biochemical experiments in isolated squid axoplasm. N.M.K. and J.N.A. performed the mass spectrometry. F.G.-L. and J.-P.J. prepared the mutant-specific antibodies. P.P. made the SOD1 exon deleted constructs. H.G., D.M.-Y. and M.P.F. provided human tissues for staining. D.A.B., B.A.F. and N.L. performed western analyses. All of the authors reviewed and edited the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Daryl A Bosco (daryl.bosco@umassmed.edu) or * Robert H Brown Jr (robert.brown@umassmed.edu) Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (428K) Supplementary Figures 1–3 and Supplementary Tables 1–3 Additional data - Non-redundant odor coding by sister mitral cells revealed by light addressable glomeruli in the mouse
- Nat Neurosci 13(11):1404-1412 (2010)
Nature Neuroscience | Article Non-redundant odor coding by sister mitral cells revealed by light addressable glomeruli in the mouse * Ashesh K Dhawale1, 2 Search for this author in: * NPG journals * PubMed * Google Scholar * Akari Hagiwara3 Search for this author in: * NPG journals * PubMed * Google Scholar * Upinder S Bhalla2 Search for this author in: * NPG journals * PubMed * Google Scholar * Venkatesh N Murthy3vnmurthy@fas.harvard.edu Search for this author in: * NPG journals * PubMed * Google Scholar * Dinu F Albeanu1albeanu@cshl.edu Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 13 ,Pages:1404–1412Year published:(2010)DOI:doi:10.1038/nn.2673Received14 July 2010Accepted24 September 2010Published online17 October 2010 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Sensory inputs frequently converge on the brain in a spatially organized manner, often with overlapping inputs to multiple target neurons. Whether the responses of target neurons with common inputs become decorrelated depends on the contribution of local circuit interactions. We addressed this issue in the olfactory system using newly generated transgenic mice that express channelrhodopsin-2 in all of the olfactory sensory neurons. By selectively stimulating individual glomeruli with light, we identified mitral/tufted cells that receive common input (sister cells). Sister cells had highly correlated responses to odors, as measured by average spike rates, but their spike timing in relation to respiration was differentially altered. In contrast, non-sister cells correlated poorly on both of these measures. We suggest that sister mitral/tufted cells carry two different channels of information: average activity representing shared glomerular input and phase-specific information ! that refines odor representations and is substantially independent for sister cells. View full text Figures at a glance * Figure 1: ORC transgenic expression pattern. Laser-scanning photostimulation identified parent glomeruli for mitral cells in ORC mice olfactory bulb slices. () Confocal micrograph of olfactory bulb sagittal section from ORC mice showing EYFP fluorescence. A, anterior; AOB, accessory olfactory bulb; D, dorsal; GL, glomerular layer; MCL, mitral cell body layer; P, posterior; V, ventral. Scale bar represents 100 μm. Inset, higher magnification view, arrow indicates OSN axons. Scale bar represents 50 μm. () Bath application of glutamate receptor antagonists CNQX and AP5. The three traces for each of the conditions correspond to three adjacent photostimulation foci 50 μm apart (red trace, before drug application; black trace, during drug application; arrow indicates the time of photostimulation). () Phase (top left) and red fluorescence image (bottom left) of one mitral cell filled with Alexa 546; the box indicates the field of photostimulation. Top right, primary dendrite and tuft projecting to a glomerulus. Bottom righ! t, matching 2DLAM (16 × 16), inter-foci distance = 15 μm, photostimulation duration = 1 ms. Note the fiduciary circle on the two panels. Color represents the peak amplitude of the light-induced currents. ONL, olfactory nerve layer. Scale bar represents 100 μm. () Currents recorded in the mitral cell by laser-scanning photostimulation in are shown at locations corresponding to each point in the 16 × 16 grid. Traces were averaged across four repeats, 1.6-mW laser power was used. Scale bars represent 50 pA and 100 ms. * Figure 2: DMD patterned illumination in ORC mice maps the parent glomeruli of mitral/tufted cells in vivo. () Left, schematic of the DLP projector–based photostimulation setup. Top right, dorsal surface of the bulb with a tetrode positioned in the mitral cell layer. One square light spot can be seen projected onto the bulb surface. Scale bar represents 500 μm. Inset, cartoon schematic of glomeruli showing a subglomerular size light spot and dual-tetrodes positioned in the mitral cell layer. i, DLP projector; ii, focusing lens; iii, blue excitation filter; iv, dichroic mirror; v, emission filter; vi, CCD camera; vii, dual-tetrode; viii, olfactory bulb. () Top, raw voltage traces corresponding to the four channels of a tetrode during photostimulation. Center, raster plot of spikes from an isolated single unit. Bottom, peri-stimulus time histogram (PSTH) with 20-ms time bins. () Left, example spike waveform of a single unit across the eight channels of a dual-tetrode. Dark traces represent individual spikes and the white line represents the average waveform. Center, 2DLAM showing! the change in firing rate of the mitral/tufted unit during photostimulation over ten repeats. Scale bar represents 100 μm (light spot size, 50 μm). Right, 2DLAM re-sampled by interpolation. () 2DLAMs obtained at different stimulation intensities (spot size, 50 μm). All maps were normalized to the highest bin in the 20.8 mW mm−2 2DLAM. () Distribution of 2DLAM hotspot widths (FWHM) for all units (n = 40) obtained in a minimal photostimulation regime (black bars). The distribution of synaptopHluorin-labeled glomerular widths (FWHM) from OMP-spH mice (red line, n = 572) is shown. * Figure 3: Functional hotspots correspond to anatomically identified glomeruli. () Left, functional hotspot from representative 2DLAM. Center, z stack image projection of anatomical glomeruli from the same field of view as the 2DLAM obtained via multiphoton microscopy. Right, overlay of the 2DLAM and the z projection. Yellow dotted lines indicate the boundaries of the 2DLAM. () Hotspot FWHMs plotted against corresponding anatomical glomerular widths. () Normalized spatial jitter between the centroids of functional hotspots and the corresponding anatomical glomeruli plotted against anatomical glomerular widths. The spatial jitter was normalized by the mean width of the anatomical glomerulus and the hotspot (a value of 1 corresponds to jitter of 1 glomerular width). () Example z stack image projections of OMP-ChR2-YFP glomeruli obtained via multiphoton microscopy. Each image shown is a 20-μm thick projection, taken 20 μm apart in the z axis from the subsequent one. Drawing illustrates contours of the glomeruli in the field of view. Arrows indicate overs! tacked glomeruli. * Figure 4: Light mapping sorts mitral/tufted cells into sister and non-sister pairs. () Example spike waveforms on individual tetrode channels for two isolated non-sister mitral/tufted cell units. () 2DLAMs for the units shown in at different light intensities used for stimulation. The color scale to the right of the highest intensity maps indicates the range of firing rate changes with respect to baseline. All light maps for a particular unit are scaled to this range. Difference map refers to the difference between the normalized 2DLAMs of the two units, plotted for each of the light intensities used. Spatial scale bar represents 100 μm. () Example waveforms for two isolated sister mitral/tufted cell units. () 2DLAMs for the units shown in at different light intensities used for photostimulation. The color scale is as described in . The spatial scale bar represents 100 μm. () Cartoon schematic of parent glomerular connectivity for sister and non-sister mitral/tufted cells. () Separation of mitral/tufted cells into sisters and non-sisters based on Euclidea! n distance between the centers of light hotspots on 2DLAMs obtained in a minimal photostimulation regime. The distance between the centers of hotspots is expressed in units of the mean full width at half maximum (FWHM) of Gaussian fits to the two hotspots for each pair. Dotted line marks the separation between sister and non-sisters mitral/tufted cells and is placed at 1 FWHM. * Figure 5: Examples of similarities and differences in odor responses of sister mitral/tufted cells. () Example odor response of a mitral/tufted unit. Top, five odor stimulation trials are shown for this unit; vertical lines mark the time of a spike occurrence. Shadowed area indicates the odor presentation window (5 s). Bottom, respiration trace. One respiratory cycle (labeled 0 to 2π) was typically ~500 ms long. Inset, expanded traces showing three respiratory cycles during air and odor presentation periods for one trial. () Top, phase-time plot of the odor response of the same mitral/tufted unit in , shown over five repeats of allyl tiglate. Note the change in the preferred phase during odor stimulation (shadowed area). To the right of the phase-time plot are phase tuning curves calculated during air (dotted line) and odor (continuous line) presentation in which each respiratory cycle was divided into five time bins. Bottom, PSTH of the same unit showing a drop in firing rate triggered by odor onset (bin width, 500 ms; NSC, normalized spike count). () Example odor respon! ses to p-anis aldehyde, heptanal and 2-heptanone for two sister mitral/tufted cells (unit 1 and unit 2) shown as phase plots, PSTHs and phase tuning curves as in . Left, note the strong increase in firing, spread across all respiration cycle phases for both units. Center, the excitatory versus inhibitory response triggered by odor onset in the two units. Right, the change in preferred phase of unit 2 triggered by the odor onset. * Figure 6: Sister mitral/tufted cells have correlated changes in odor induced firing rates. (,) Examples of F-ORSs obtained using a set of 42 odors for three pairs of sister () and three pairs of non-sister mitral/tufted (M/T) cells (). Arrows in denote differential responses across pairs of sister units. () A scatter plot of the similarity (correlation coefficient) of odor-induced firing rate change against the Euclidean distance between the centers of the hotspots in the 2DLAMs for each pair of mitral/tufted units that we considered. Gray indicates non-sister mitral/tufted cells and black indicates sister mitral/tufted cells. The marginal distributions are shown as histograms on the top and right axes. Top, separation of units into sister and non-sister mitral/tufted cells, as shown in Figure 3f. Right, histograms of sister (n = 20) and non-sister pairs (n = 15) F-ORS correlations. () Average F-ORS correlations for sister and non-sister mitral/tufted cells; self refers to the same unit (n = 40) probed across different blocks of odor repeats by splitting the total! number of trials in two. #P < 0.05 for F-ORS correlations, across groups with respect to sister mitral/tufted pairs (for example, sister versus non-sister mitral/tufted units). Error bars represent s.e.m. * Figure 7: Odors disrupt phase correlations of sister and non-sister mitral/tufted cells. () Example phase tuning curves for two mitral/tufted units (unit 1 and unit 2) during air and odor. () Phase response spectra for one representative sister mitral/tufted unit pair. Arrows indicate example mismatches between the spectra. () Average phase response spectra correlations between sister and non-sister mitral/tufted pairs. () Example phase similarity spectra for two sister mitral/tufted cells during air (blue) and odor (red) for 42 stimuli. () Histograms of phase similarity during Air (blue) and Odor (red) for all sister (n = 20, top) and non-sister (n = 15, bottom) mitral/tufted unit pairs for 42 stimuli. () Average phase similarity for sister and non-sister mitral/tufted pairs. () Example phase tuning curves for two mitral/tufted units (unit 1 and unit 2, different from ) during air and light activation of single parent glomeruli. Note that light induced similar changes in phase for both units. () Left, average phase response between air and light for individual ! sister mitral/tufted units. Right, average phase similarity between sister mitral/tufted pairs during air (dotted line) and light (continuous line). Self refers to similarity between phase tuning curves generated from the same unit by splitting the number of trials into two. *P < 0.05 for comparisons within the same group (sister or non-sister mitral/tufted units) across conditions (odor versus air), #P < 0.05 for same condition (air or odor), across groups (sister versus non-sister mitral/tufted units) with respect to sister mitral/tufted pairs. * Figure 8: Odors trigger firing rate and phase changes in an independent manner. () Average number of odors that induced differential responses in units of the same pair, considered in terms of firing rate changes or phase similarity. Overlap refers to the number of odors that induced significant changes in both firing rate and phase between units. Expected overlap refers to the number of odors that would induce significant changes in both firing rate and phase if the two were independent. Data are shown for sister (left) and non-sister (right) mitral/tufted pairs (*P < 0.05). () Left, cartoon representation of the diversity of sister mitral/tufted cell surround fields. Right, example spike trains of two model sister mitral/tufted cells (red and blue) during air and odor periods with respect to the respiratory cycle (top trace). Stimulus 1 elicited different phase shifts between the two neurons, but their firing rates were unchanged. Stimulus 2 elicited similar firing rate changes in both neurons and their firing times remained correlated. Stimulus 3 eli! cited the same firing rate change in both neurons, but different phase shifts. Author information * Abstract * Author information * Supplementary information Affiliations * Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. * Ashesh K Dhawale & * Dinu F Albeanu * National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India. * Ashesh K Dhawale & * Upinder S Bhalla * Department of Molecular and Cellular Biology, and Center for Brain Science, Harvard University, Cambridge, Massachusetts, USA. * Akari Hagiwara & * Venkatesh N Murthy Contributions A.K.D. and D.F.A. designed the study. D.F.A. engineered the ORC transgenic mice in the laboratory of V.N.M. A.H. characterized the expression pattern of ORC mice and performed acute slice recordings. A.K.D. and D.F.A. built the DLP stimulation rig and performed in vivo experiments. A.K.D. wrote custom software for recording and analysis. A.K.D. and D.F.A. analyzed the data. U.S.B. and V.N.M. provided expert advice on data analysis and guidance with experimental design. A.K.D., U.S.B., V.N.M. and D.F.A. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Venkatesh N Murthy (vnmurthy@fas.harvard.edu) or * Dinu F Albeanu (albeanu@cshl.edu) Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–9, Supplementary Table 1 and Supplementary Notes 1–6 Additional data - The functional asymmetry of auditory cortex is reflected in the organization of local cortical circuits
- Nat Neurosci 13(11):1413-1420 (2010)
Nature Neuroscience | Article The functional asymmetry of auditory cortex is reflected in the organization of local cortical circuits * Hysell V Oviedo1 Search for this author in: * NPG journals * PubMed * Google Scholar * Ingrid Bureau2 Search for this author in: * NPG journals * PubMed * Google Scholar * Karel Svoboda3 Search for this author in: * NPG journals * PubMed * Google Scholar * Anthony M Zador1zador@cshl.edu Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 13 ,Pages:1413–1420Year published:(2010)DOI:doi:10.1038/nn.2659Received29 July 2010Accepted07 September 2010Published online17 October 2010 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The primary auditory cortex (A1) is organized tonotopically, with neurons sensitive to high and low frequencies arranged in a rostro-caudal gradient. We used laser scanning photostimulation in acute slices to study the organization of local excitatory connections onto layers 2 and 3 (L2/3) of the mouse A1. Consistent with the organization of other cortical regions, synaptic inputs along the isofrequency axis (orthogonal to the tonotopic axis) arose predominantly within a column. By contrast, we found that local connections along the tonotopic axis differed from those along the isofrequency axis: some input pathways to L3 (but not L2) arose predominantly out-of-column. In vivo cell-attached recordings revealed differences between the sound-responsiveness of neurons in L2 and L3. Our results are consistent with the hypothesis that auditory cortical microcircuitry is specialized to the one-dimensional representation of frequency in the auditory cortex. View full text Figures at a glance * Figure 1: Auditory cortex LSPS experimental preparation. () Coronal brain slice (cut along the lateral (L) to medial (M) axis) containing the primary auditory cortex and underlying subcortical area, used for studying the organization along the isofrequency axis. The white box outlines the stimulus grid, and the dashed lines represent the landmarks used to align the grid from mouse to mouse. For each cell, we measured the distance of the soma from the L1–L2 border and the middle of the grid. (The ventral and dorsal divisions of the lateral geniculate nucleus (VLG and DLG, respectively) are labeled as landmarks.) A, anterior; P, posterior; 40, 20 and 5 (in kHz) represent the spatial organization of tone frequency tuning (tonotopy) in A1. () Left, stimulus grid showing the 16 × 16 points of uncaging. Right, picture of a patched cell filled with Alexa and magnification of a dendritic branch (scale bar, 15 μm). () Left, examples of direct responses—those evoked by the direct activation of receptors by uncaged glutamate in the neu! ron under study. Right, examples of synaptic responses—EPSCs elicited by triggering action potentials in neurons presynaptic to the neuron under study. Note difference in scale between left and right. The vertical lines through the traces mark the time window to detect direct responses (first two vertical lines) and synaptic events (second and third vertical lines). * Figure 2: Synaptic input organization along the isofrequency axis. () Map of synaptic traces (left) used to generate the color map (middle) of a L2 neuron. Each trace on the left (and the corresponding pixel on the right) corresponds to a point on the uncaging grid (Fig. 1b). Pixels contaminated with a direct response are shown in black; for other pixels, the color indicates the charge transferred during the EPSC integration window defined in Figure 1c. The white square indicates the location of the soma. Right, interpolated average input map for all L2 neurons recorded (n = 11). Maps were realigned to place the somata on the center of the x axis of the map. Scale bars in and , 50 pA and 100 ms. () L3 single-cell trace map (left) and color map (middle), and interpolated population map (right) of all L3 neurons recorded (n = 15). () Interpolated map of all L2/3 neurons combined (n = 26). () Left, mean laminar input (n = 26) to L2/3 neurons (layers analyzed together). Local connections (within L2/3) provided most of the input for the populati! on of L2 and L3 neurons recorded (*P << 0.01, one-way analysis of variance). Right, summary of the mean laminar input to L2 and L3 (layers analyzed separately) arising from all cortical layers. Pre, presynaptic layer; post, postsynaptic. *P < 0.05, presynaptic laminar input for which the difference between L2 and L3 was significant (n = 26, t-test). Data are presented as mean ± s.e.m. Scale bars in synaptic traces (,), 50 pA and 100 ms. * Figure 3: Synaptic input organization along the tonotopic axis. () Horizontal slices used to capture the anterior-posterior (A↔P) representation of tonotopy in auditory cortex. Image of a horizontal slice depicts the anatomical landmarks used to align the stimulation grid (white box). The anterior (left) side of the slice corresponds to the putative high frequency (Hi F) portion of A1 and the posterior (right) side to putative low frequencies (Low F). M, medial; L, lateral. () Trace map of synaptic input map to a L2 neuron (top) and its color map (middle). Interpolated population map of all L2 neurons recorded (bottom, n = 15). () L3 single-cell trace map (top) and color map (middle), and interpolated population map (bottom) of all L3 neurons recorded (n = 15). () Summary of the mean laminar input to L2 and L3 arising from all cortical layers. Asterisk indicates laminar input where the difference in synaptic input between L2 and L3 was significantly different (P < 0.05, n = 30, t-test). () Grand summary and comparison of the mean lamin! ar input to L2/3 along the isofrequency (IF) and tonotopic (TT) axes. Asterisk indicates laminar input where the difference in synaptic input between the tonotopic and isofrequency axes was significantly different (P << 0.01, t-test). Data are presented as mean ± s.e.m. Scale bars in synaptic traces (,) 50 pA and 100 ms. * Figure 4: Along tonotopic but not isofrequency axis, inputs to L3 arise asymmetrically out-of-column. (,) L5/6 input to L3, but not L2, arose out-of-column preferentially from putative high-frequency (Hi F) neurons in tonotopic slices. Top panels show the distribution of the horizontal distances between the soma and its hotspot (ds–h) of presynaptic input along the tonotopic (n = 39) and isofrequency (n = 22) axes for each L2 and L3 neuron. The square points show the mean (± s.e.m.) of the L2 and L3 distributions. Bottom panels show columnar average of L5/6 input. Asterisks indicate columns where input to L2 was significantly different from input to L3. The insets show the uncaging grids and the relative positions of the cortical area where inputs were averaged (dashed rectangles). () Local L3 input to L3 arose preferentially from putative high-frequency neurons in tonotopic slices. Relative contribution of local input (within L3) arising from the anterior and posterior (putative higher and lower frequency, respectively) input sites of the L3 cells mapped in the tonotopic! slice. The plots show the mean charge transfer along columns. Input arising from the higher-frequency sites was greater than from lower frequency sites in the tonotopic slice (left), but not the isofrequency (right). Inputs arising from posterior and medial sites were reflected on the x axis for display purposes. Insets show the uncaging grid and the relative position of the cortical area where inputs were averaged (dashed rectangles to the left and right of L3 somata). Data are presented as mean ± s.e.m. * Figure 5: Synaptic input correlation between pairs of auditory cortical neurons. Plot shows the relationship between the correlations of input maps in pairs of cells in the same slice as a function of their intersomatic horizontal distance. We compared population correlation along the tonotopic and isofrequency axes. The gray line is the exponential fit (0.37e−x/159). Square points showing the correlation of maps obtained for the same cell represent the theoretical upper limit of correlation given the experimental variability. * Figure 6: L3 neurons are less responsive to simple auditory stimuli than L2 neurons. () Frequency-response plot (right) for a L2 neuron (left) assessed using cell-attached recording. () Frequency-response plot (left) for a L3 neuron (right) assessed using cell-attached recording. Scale bars in and , 25 μm. () Summary of the differences in evoked firing rate between the L2 and L3 neurons recovered (n = 20). For each intensity, we found the octave bin with the maximum firing rate in the 150 ms post-stimulus epoch; we then averaged over the maximum for intensities 20, 50 and 80. The difference in firing rates was insensitive to outliers (for example, removing the three highest firing rates from each group increased significance from P < 10−4 to P < 10−5, n = 20, t-test). () Locations of neurons characterized in . () Labeling in the left auditory cortex after injection of a retrograde tracer (cholera toxin) into the right auditory cortex, showing that L3 but not L2 neurons project to the contralateral auditory cortex. Data are presented as mean ± s.e.m. Author information * Abstract * Author information * Supplementary information Affiliations * Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. * Hysell V Oviedo & * Anthony M Zador * Institut National de la Santé et de la Recherche Médicale (INSERM), Unité 901, Institut de Neurobiologie de la Méditerranée, Marseille, France. * Ingrid Bureau * Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA. * Karel Svoboda Contributions H.V.O. and A.M.Z. conceived the experiments, analyzed the data and wrote the paper. H.V.O. performed all the experiments. I.B. and K.S. provided expert advice and LSPS experimental set-up. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Anthony M Zador (zador@cshl.edu) Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (8M) Supplementary Figures 1–12 Additional data - Cross-modal plasticity in specific auditory cortices underlies visual compensations in the deaf
- Nat Neurosci 13(11):1421-1427 (2010)
Nature Neuroscience | Article Cross-modal plasticity in specific auditory cortices underlies visual compensations in the deaf * Stephen G Lomber1steve.lomber@uwo.ca Search for this author in: * NPG journals * PubMed * Google Scholar * M Alex Meredith2 Search for this author in: * NPG journals * PubMed * Google Scholar * Andrej Kral3 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorJournal name:Nature NeuroscienceVolume: 13 ,Pages:1421–1427Year published:(2010)DOI:doi:10.1038/nn.2653Received02 July 2010Accepted24 August 2010Published online10 October 2010 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg When the brain is deprived of input from one sensory modality, it often compensates with supranormal performance in one or more of the intact sensory systems. In the absence of acoustic input, it has been proposed that cross-modal reorganization of deaf auditory cortex may provide the neural substrate mediating compensatory visual function. We tested this hypothesis using a battery of visual psychophysical tasks and found that congenitally deaf cats, compared with hearing cats, have superior localization in the peripheral field and lower visual movement detection thresholds. In the deaf cats, reversible deactivation of posterior auditory cortex selectively eliminated superior visual localization abilities, whereas deactivation of the dorsal auditory cortex eliminated superior visual motion detection. Our results indicate that enhanced visual performance in the deaf is caused by cross-modal reorganization of deaf auditory cortex and it is possible to localize individual visua! l functions in discrete portions of reorganized auditory cortex. View full text Figures at a glance * Figure 1: Performance of hearing and deaf cats on seven visual psychophysical tasks. () Polar plot of the visual localization responses of hearing cats (light gray bars) and the superior performance of deaf cats (dark gray bars). The two concentric semicircles represent 50% and 100% correct response levels and the length of each colored line corresponds to the percentage of correct responses at each location tested. For both the hearing and deaf cats, data represent mean performance for 200 stimulus presentations at each peripheral target location and 400 stimulus presentations for the central target. () Histograms of combined data from left and right hemifields showing mean ± s.e.m. performance for the hearing (light gray) and deaf (dark gray) cats at each of the tested positions in the visual localization task. For both hearing and deaf cats, data represent mean performance for 400 stimulus presentations at each peripheral target location and 800 stimulus presentations for the central target (0°). (–) Mean threshold ± s.e.m. for the hearing and deaf c! ats on the movement detection (), grating acuity (), Vernier acuity (), orientation () and direction of motion () discrimination tasks. () Performance of the hearing and deaf cats on the velocity discrimination task. Data are presented as Weber fractions for six different stimulus velocities. *P < 0.01 between the hearing and deaf conditions. Sample stimuli are shown for each task. * Figure 2: Cortical areas deactivated in deaf auditory cortex. () Schematic illustration of the left hemisphere of the cat cerebrum showing all of the auditory areas (lateral view). The areas that we examined are highlighted in gray. A, anterior; A2, second auditory cortex; aes, anterior ectosylvian; D, dorsal; dPE, dorsal posterior ectosylvian area; FAES, auditory field of the anterior ectosylvian sulcus; IN, insular region; iPE, intermediate posterior ectosylvian area; P, posterior; pes, posterior ectosylvian; ss, suprasylvian; T, temporal region; V, ventral; VAF, ventral auditory field; VPAF, ventral posterior auditory field; vPE, ventral posterior ectosylvian area. The areal borders shown in this figure are based on a compilation of electrophysiological mapping and cytoarchitectonic studies. () Cooling loops in contact with areas AAF, DZ, A1 and PAF of the left hemisphere of a congenitally deaf cat at the time of implantation. Left is anterior. The areal borders presented in this figure are based on the post-mortem analysis of SMI-3! 2 processed tissue from the brain shown here. * Figure 3: Visual localization task data from deaf cats during bilateral reversible deactivation of PAF, DZ, A1 and AAF. () Polar plot of the visual localization responses of deaf cats while cortex was warm (dark gray) and active and during simultaneous cooling deactivation of PAF, DZ, A1, and AAF (black). (–) Histogram of combined data from the left and right hemifields showing mean ± s.e.m. performance for deaf cats while cortex was warm (dark gray) and active and while it was cooled (black) and deactivated. Asterisks indicate a significant difference (P < 0.01) between the warm and cool conditions. () Data from the simultaneous deactivation of PAF, DZ, A1 and AAF. (–) Data from individual area deactivations. () Visual localization data comparing performance at each position for hearing cats (light gray), deaf cats while PAF was warm (dark gray), and deaf cats while PAF was cooled (black). *P < 0.01 from the hearing and deaf PAF cool conditions. * Figure 4: Motion detection thresholds for the deaf cats before and after cooling deactivation and during bilateral reversible deactivation. (–) Histograms showing mean ± s.e.m. motion detection thresholds for deaf cats while cortex was warm (dark gray) and active and while it was cooled (black) and deactivated. *P < 0.01 between the warm and cool conditions. Motion detection thresholds from deaf cats during bilateral reversible deactivation of PAF, DZ, A1 and AAF are shown in . Data from individual area deactivations are shown in –. () Motion detection thresholds to compare performance of hearing cats (light gray), deaf cats while DZ was warm (dark gray) and deaf cats while DZ was cooled (black). *P < 0.01 from the hearing and deaf DZ cool conditions. * Figure 5: Performance of hearing cats on seven visual psychophysical tasks during simultaneous bilateral deactivation of PAF, DZ, A1 and AAF. () Polar plot of the visual localization responses of the hearing cats (light gray bars) and during bilateral deactivation of all four cortical areas (black bars). The two concentric semicircles represent 50% and 100% correct response levels and the length of each bold line corresponds to the percentage of correct responses at each location tested. () Histograms of combined data from the left and right hemifields showing mean ± s.e.m. performance for the hearing cats when cortex was warm and active (light gray) and when all four areas were bilateraly cooled and deactivated (black). (–) Mean threshold ± s.e.m. on the movement detection (), grating acuity (), Vernier acuity (), orientation () and direction of motion () discrimination tasks for the hearing cats when cortex was warm and active (light gray) and when all four areas were bilateraly cooled and deactivated (black). Sample stimuli are shown for each task. () Performance on the velocity discrimination task. Data ar! e presented as Weber fractions for six different stimulus velocities. * Figure 6: Thermal cortical maps constructed by generating Voronoi tessellations21 from 335 temperature recording sites during deactivation of each individual cooling loop. Each image is a dorsolateral view of dorsal auditory cortex from the same brain pictured in Figure 2b. A color-coded temperature scale is provided on the right. () Line drawing showing the locations of the four cooling loops (wide black lines) on the cortical surface and the positions of the 335 temperature recording sites. At each site temperature was recorded 500 μm below the pial surface. () Cortical temperatures before cooling. (–) Thermal profiles during cooling of each individual cryoloop to 3 °C. Sulci are indicated by thick black lines. * Figure 7: Summary diagram illustrating the double-dissociation of visual functions in auditory cortex of the deaf cat. Bilateral deactivation of PAF, but not DZ, resulted in the loss of enhanced visual localization in the far periphery. On the other hand, bilateral deactivation of DZ, but not PAF, resulted in higher movement detection thresholds. The lower panel shows a lateral view of the cat cerebrum highlighting the locations of PAF and DZ. Author information * Abstract * Author information * Supplementary information Affiliations * Centre for Brain and Mind, Department of Physiology and Pharmacology, Department of Psychology, University of Western Ontario, London, Ontario, Canada. * Stephen G Lomber * Department of Anatomy and Neurobiology, School of Medicine, Virginia Commonwealth University, Richmond, Virginia, USA. * M Alex Meredith * Department of Experimental Otology, Institute of Audioneurotechnology, Medical University Hannover, Hannover, Germany. * Andrej Kral Contributions S.G.L. and A.K. conceived and designed the project. A.K. bred and provided the cats. All psychophysical work was performed or supervised by S.G.L. M.A.M. provided assistance with data analysis and interpretation. The manuscript was written and edited by all of the authors. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Stephen G Lomber (steve.lomber@uwo.ca) Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–6 Additional data - Categorical speech representation in human superior temporal gyrus
- Nat Neurosci 13(11):1428-1432 (2010)
Nature Neuroscience | Article Categorical speech representation in human superior temporal gyrus * Edward F Chang1, 2, 6changed@neurosurg.ucsf.edu Search for this author in: * NPG journals * PubMed * Google Scholar * Jochem W Rieger2, 3, 6jochem.rieger@med.ovgu.de Search for this author in: * NPG journals * PubMed * Google Scholar * Keith Johnson4 Search for this author in: * NPG journals * PubMed * Google Scholar * Mitchel S Berger1 Search for this author in: * NPG journals * PubMed * Google Scholar * Nicholas M Barbaro1 Search for this author in: * NPG journals * PubMed * Google Scholar * Robert T Knight1, 2, 5 Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 13 ,Pages:1428–1432Year published:(2010)DOI:doi:10.1038/nn.2641Received12 March 2010Accepted12 August 2010Published online03 October 2010 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Speech perception requires the rapid and effortless extraction of meaningful phonetic information from a highly variable acoustic signal. A powerful example of this phenomenon is categorical speech perception, in which a continuum of acoustically varying sounds is transformed into perceptually distinct phoneme categories. We found that the neural representation of speech sounds is categorically organized in the human posterior superior temporal gyrus. Using intracranial high-density cortical surface arrays, we found that listening to synthesized speech stimuli varying in small and acoustically equal steps evoked distinct and invariant cortical population response patterns that were organized by their sensitivities to critical acoustic features. Phonetic category boundaries were similar between neurometric and psychometric functions. Although speech-sound responses were distributed, spatially discrete cortical loci were found to underlie specific phonetic discrimination. Our ! results provide direct evidence for acoustic-to–higher order phonetic level encoding of speech sounds in human language receptive cortex. View full text Figures at a glance * Figure 1: Psychophysics of categorical speech perception and speech-evoked responses during intraoperative human cortical recordings. () Wide-band spectrograms of the stimulus token continuum, synthesized with equal parametric changes in the F2 starting frequency (from 800–2,100 Hz). Top, full spectrogram of a single token with an 800-Hz starting frequency (stimulus 1, duration = 250 ms). Bottom, first 50 ms for each of the 14 stimulus tokens. () Psychometric identification function with percentage reporting /ba/, /da/ or /ga/. () Psychometric discrimination function (two step). The percentages of responses judged as different versus same are shown. The category boundaries located at peak discrimination are at stimuli 4 and 5 and at 9 and 10. () Three-dimensional surface reconstruction of representative brain magnetic resonance imaging with superimposed electrode positions over pSTG. () Grand average rooted mean square (RMS) evoked potentials recorded over pSTG for sound stimuli reliably categorized as /ba/ (tokens 1–4), /da/ (tokens 6–9) and /ga/ (tokens 10–14). The average evoked potentials (RMS,! solid line) and standard errors of evoked potential amplitudes (shaded) are shown. Potentials peaked at approximately 110 ms after stimulus onset. () Topographic plots of evoked potentials at 110 ms for each prototype sound stimulus revealed distributed cortical activation pattern, with some sharply localized differences between stimuli. * Figure 2: Categorical organization of neural response patterns to a speech-stimulus continuum. () Rapid and transient neural representation for speech stimulus discriminability. Time series of the total normalized neural pattern dissimilarity derived from classifier performance aggregated across all pair-wise stimulus comparisons are shown. Peak dissimilarity occurred at the same time as peak of evoked potential magnitude in Figure 1e. () Structured neural dissimilarity. Shown are neural confusion matrices for three time intervals: 0–40 ms (1), 110–150 ms (2) and 180–220 ms (3) (group average data). Color bar scaling corresponds to the classifier performance for each pair-wise stimulus comparison shown in individual matrix pixels. In the 110–150-ms interval, responses to some stimulus pairs, for example, 1 versus 4, 8 versus 5 or 10 versus 13, were nearly indiscriminable, whereas other stimulus pairs elicited responses that were much easier to discriminate, such as 7 versus 11 or 3 versus 9. () Relational organization of neural pattern response dissimilarity u! sing MDS. Neural pattern dissimilarity was proportional to the Euclidean distance (that is, similar response patterns are grouped closely together, whereas dissimilar patterns are positioned far apart). K-means clustering results for group membership are denoted by stimulus coloring (red = /ba/ sounds, green = /da/ sounds, blue = /ga/ sounds, k = 3). Zero cluster errors were found at time interval 110–150 ms (that is, same clustering as in psychophysical results), six errors at 0–40 ms and five errors at 180–220 ms. * Figure 3: Correlation of neurometric and psychometric category boundaries. Peak encoding at 110–150 ms. () Left, comparison of neuronal-derived (dark) and psychophysical-derived (light/dashed) identification functions. Neurometric identification functions were determined using the MDS distance between each stimulus position and the three cluster means. Middle, correlation between neurometric and psychometric identification functions (Pearson's correlation, 0.92 for /ba/, 0.98 for /da/ and 0.92 for the /ga/ category; dotted line, threshold of corrected P value at 0.05). Right, comparison of neural (red) and psychophysical (black/dashed) discrimination functions. The neurometric discrimination functions were derived from the distance of the stimulus responses in MDS space. At 110 ms, both the position of the maxima and the general shape of the neurometric function correlated well with the psychometric function (r = 0.66, P < 0.05). Early (0–40 ms, ) and late (180–220 ms, ) epoch field potentials indicated poor correlation between neural and psy! chophysical results (insets). * Figure 4: Topography of discriminative cortical sites in the pSTG underlying categorical speech perception. () The degree of separability of the various evoked activations at each electrode position is shown as classifier weights. The spatial patterns indicate that discriminative neuronal activation was not distributed over the pSTG, but was instead concentrated in few cortical sites. () The informative loci overlapped very little between comparisons of the features (on average 3.9 ± 0.88%; indicated by mixed colors such as magenta, cyan or orange in ), suggesting that the neuronal categorization is not accomplished by simply scaling the responses in the same network, but is instead a function of spatially discrete and local selectivity. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Edward F Chang & * Jochem W Rieger Affiliations * Department of Neurological Surgery, University of California San Francisco, San Francisco, California, USA. * Edward F Chang, * Mitchel S Berger, * Nicholas M Barbaro & * Robert T Knight * Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California, USA. * Edward F Chang, * Jochem W Rieger & * Robert T Knight * Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany. * Jochem W Rieger * Department of Linguistics, University of California Berkeley, Berkeley, California, USA. * Keith Johnson * Department of Psychology, University of California, Berkeley, Berkeley, California, USA. * Robert T Knight Contributions E.F.C. designed the experiments, collected the data and wrote the manuscript. E.F.C. and J.W.R. analyzed the data, evaluated results and edited the manuscript. J.W.R., N.M.B. and M.S.B. helped with data collection. K.J. and R.T.K. reviewed the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Edward F Chang (changed@neurosurg.ucsf.edu) or * Jochem W Rieger (jochem.rieger@med.ovgu.de) Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (224K) Supplementary Figures 1–4, Supplementary Table 1 and Supplementary Results Additional data - Functional imaging of hippocampal place cells at cellular resolution during virtual navigation
- Nat Neurosci 13(11):1433-1440 (2010)
Nature Neuroscience | Technical Report Functional imaging of hippocampal place cells at cellular resolution during virtual navigation * Daniel A Dombeck1ddombeck@princeton.edu Search for this author in: * NPG journals * PubMed * Google Scholar * Christopher D Harvey1 Search for this author in: * NPG journals * PubMed * Google Scholar * Lin Tian2 Search for this author in: * NPG journals * PubMed * Google Scholar * Loren L Looger2 Search for this author in: * NPG journals * PubMed * Google Scholar * David W Tank1dwtank@princeton.edu Search for this author in: * NPG journals * PubMed * Google Scholar * Affiliations * Contributions * Corresponding authorsJournal name:Nature NeuroscienceVolume: 13 ,Pages:1433–1440Year published:(2010)DOI:doi:10.1038/nn.2648Received03 May 2010Accepted01 September 2010Published online03 October 2010 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Spatial navigation is often used as a behavioral task in studies of the neuronal circuits that underlie cognition, learning and memory in rodents. The combination of in vivo microscopy with genetically encoded indicators has provided an important new tool for studying neuronal circuits, but has been technically difficult to apply during navigation. Here we describe methods for imaging the activity of neurons in the CA1 region of the hippocampus with subcellular resolution in behaving mice. Neurons that expressed the genetically encoded calcium indicator GCaMP3 were imaged through a chronic hippocampal window. Head-restrained mice performed spatial behaviors in a setup combining a virtual reality system and a custom-built two-photon microscope. We optically identified populations of place cells and determined the correlation between the location of their place fields in the virtual environment and their anatomical location in the local circuit. The combination of virtual real! ity and high-resolution functional imaging should allow a new generation of studies to investigate neuronal circuit dynamics during behavior. View full text Figures at a glance * Figure 1: Experimental setup. () The experimental apparatus, consisting of a spherical treadmill, a virtual reality apparatus (projector, reflecting mirror (RM), angular amplification mirror (AAM), toroidal screen and optical computer mouse to record ball rotation) and a custom two-photon microscope (titanium:sapphire laser (Ti:S), long-pass filter (LP), galvanometers (X-Y), scan lens (SL), mirror (M), tube lens (TL), dichroic mirror (DM), collection lens (CL), biconcave lens (L), bandpass filter (BP), focusing lens (FL), photomultiplier tube (PMT), sliding stage (used to move microscope for treadmill access), X-Y translation (moves treadmill and mouse), Z-translation (objective focus control) and rubber tube (shown in cross-section, for light shielding)). () Photograph of experimental setup. () Top, view from one end of the virtual linear track. Bottom, top view of the linear track. () View of materials used to block background light from entering the microscope objective hole. Hippocampal imaging windo! w can also be seen. () Detailed view of hippocampal imaging window (from boxed region in ). () In vivo two-photon images at different depths through the hippocampal window. * Figure 2: Imaging CA1 place cells in the dorsal hippocampus. () Two-photon image of neuron cell bodies in stratum pyramidale of CA1 labeled with GCaMP3. The indicator is excluded from the nucleus13. ROIs for example cells are shown in red (right). () GCaMP3 baseline subtracted ΔF/F traces are shown in black for a subset of the cells labeled in (right). Red traces indicate significant calcium transients with <5% false positive error rates (see Online Methods). The position of the mouse along the virtual linear track and reward times are shown at the bottom. () Expanded view of boxed region in . () Mean ΔF/F versus linear track position for a subset of the cells labeled in (right). () A plot of mean ΔF/F versus linear track position for all of the cells labeled in (right). () Place cells are colored according to the location of their place fields along the virtual linear track. Only place cells with significant place fields during running in the positive direction are shown. * Figure 3: Place cells differ depending on the running direction in the linear track. () An example imaging field in which the place cells are colored according to the location of their place fields along the virtual linear track. Significant place fields during running in the positive (left panel) and negative (right panel) directions are shown. Example place cells with different place fields or no place fields depending on the running direction are highlighted with closed arrowheads or open arrowheads, respectively. () A plot of mean ΔF/F versus linear track position for the positive direction place cells labeled in (left) during running in the positive (left) and negative (right) directions. () Histogram of directionality index for all place fields. * Figure 4: Characterization of place cell calcium transients and place fields. Histograms of place cell transient widths () and transient peak ΔF/F () are shown for periods of mouse movement along the virtual track. Histograms of place field position along the linear track () and place field widths () are also shown. * Figure 5: Place cell activity variability in place fields. () Temporal activity pattern versus virtual linear track position traces for a subset of the cells shown in Figure 2a (right). Each of the 21 positive running direction track traversals is shown for each of the cells. () Mean and s.d. of ΔF/F versus linear track position for the traces shown in . () Histogram of the probability that a place cell is active during traversals through the place field. () Histogram of the percentage of place field traversal time for which the cell had a significant calcium transient. * Figure 6: Spatial organization of place cells in dorsal CA1. () Example images from different fields of view in which the place cells are colored according to the location of their place fields along the virtual linear track. Each image shows place cells with significant place fields during running in either the positive or negative direction. () Plot of mean distance between place cells in the hippocampus versus the mean distance between their place fields along the track averaged over all 47 time series. The error bars represent s.e.m. () Plot of mean distance between cells in the hippocampus versus the mean correlation between their temporal activity patterns averaged over all 47 time series for all place cells (gray) and all neurons (black). The error bars represent s.e.m. * Figure 7: Imaging place-related activity in dendrites and putative interneurons. (,) A two-photon image () of a field of view ~75 μm ventral to the stratum pyramidale cell body layer (dashed line in ). Bright spots in are a cross-section through the apical dendrites from the overlying CA1 neurons. O-LM, oriens lacunosum molecular; S-O, stratum oriens; S-P, stratum pyramidale; S-R, stratum radiatum. () Mean ΔF/F versus linear track position for the dendrites labeled in . (,) A two-photon image () of a field of view ~50 μm dorsal to the stratum pyramidale cell body layer (dashed line in ). Sparsely distributed cell bodies in are assumed interneurons. () Mean ΔF/F versus linear track position for the interneurons labeled in the image in . Author information * Abstract * Author information * Supplementary information Affiliations * Department of Molecular Biology and Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey, USA. * Daniel A Dombeck, * Christopher D Harvey & * David W Tank * Howard Hughes Medical Institute, Janelia Farm Research Campus, Ashburn, Virginia, USA. * Lin Tian & * Loren L Looger Contributions D.A.D. and D.W.T. designed the research. D.A.D. performed the imaging experiments and developed the chronic hippocampal window system and surgery/training sequences. D.W.T. designed and implemented the combined two-photon microscope and virtual reality instrumentation. D.A.D. and C.D.H. performed extracellular recording and optimized virtual reality training procedures. L.T. and L.L.L. provided AAV2/1-synapsin-1-GCaMP3. D.A.D. analyzed the data. D.A.D. and D.W.T. wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * David W Tank (dwtank@princeton.edu) or * Daniel A Dombeck (ddombeck@princeton.edu) Supplementary information * Abstract * Author information * Supplementary information Movies * Supplementary Movie 1 (824K) Z-series movie of the hippocampal region labeled with GCaMP3 virus infection. Movie begins in the external capsule/alveus (dense plexus of fibers) and then steps ventral in 5 micron increments through stratum oriens, stratum pyramidale and then ends in stratum radiatum (~350 microns below the external capsule surface). The field is ~200×100 microns. * Supplementary Movie 2 (4M) Functional two-photon movie of a field of CA1 neurons in a mouse running back and forth along a virtual linear track. The two-photon time-series was acquired at ~15fps and the movie is displayed at 30fps. The virtual linear track is shown at the bottom of the movie and a "^" indicates the position of the mouse along the linear track. This movie corresponds to the data shown in Fig. 2 (the ~2 minute time period shown in Fig. 2b). The two-photon movie was made by coloring all of the pixels within a neuron's ROI a red intensity proportional to the value of the significant transient only trace corresponding to each frame (the red color was saturated at 35% changes). This red intensity was added to the still grey-scale image. PDF files * Supplementary Text and Figures (1M) Supplementary Figures 1–5 Additional data
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