Diese Arbeit wurde von der Intramural Research Program der National Institutes of Health, die Eunice Kennedy Shriver National Institute of Child Health und Human Development (Erteilungs HD008913 bis C-HL) und das Zentrum für Informationstechnologie (PGM, NP, ESM und MM).

<ol>
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Die Autoren haben nichts zu offenbaren.

Hier zeigen wir , wie man Bild und analysieren dendritischen Dorne von Drosophila Medulla Neuronen. Der erste Abschnitt, Dual-View-Bildgebung, beschreibt die Entfaltungs und Kombination von zwei Bildstapeln in einem hochauflösenden Bildstapel. Der zweite Abschnitt, Dendriten Verfolgung und Anmeldung, beschreibt die Verfolgung und Registrierung von Dendriten der Medulla Neuronen auf die Referenzspaltenanordnung. Der dritte Abschnitt, dendritische Analyse, beschreibt die Verwendung von benutzerdefinierten Skript...

Während der Entwicklung Neuronen aufwendige Dendriten in komplexen, aber klischee verzweigten Muster Synapsen mit ihren präsynaptischen Partnern zu bilden. Dendritische Verzweigungsmuster korrelieren mit neuronalen Identität und Funktionen. Die Standorte der dendritischen Dorne bestimmen die Art der präsynaptischen Eingänge sie erhalten, während die dendritischen Komplexität und Feldverzweigungsgrößen die Eingangsnummer regeln. Somit sind dendritische morphologischen Eigenschaften kritische Determinanten für die synaptische Verbindungen und neuronale Berechnung. In vielen Regionen der komplexen Gehirnen, wie beispielsweise die Fliegen optic Lappen und der wirbel Retina sind in Spalten und Schichten synaptischen Schaltungen organisiert Informationsverarbeitungs 1, 2 zu erleichtern. In einer solchen Spalte und Schicht Organisation, präsynaptischen Neuronen einer deutlichen Modalität Projekt Axone zu einer bestimmten Schicht zu beenden (sog Schicht-spezifisches Targeting) und eine geordnete zweidimensionale Anordnung zu bilden (so called topographische Karte), während postsynaptischen Neuronen Dendriten von geeigneter Größe in bestimmten Schichten erweitern präsynaptischen Eingänge der richtigen Typen und Zahlen zu erhalten. Während axonalen zu Schichten und Spalten Targeting gut 3 untersucht wurde, 4, ist viel weniger bekannt , wie Dendriten auf bestimmte Schichten geleitet werden und erweitern geeigneter Größe rezeptiven Felder 5 synaptischen Verbindungen mit den richtigen präsynaptischen Partnern zu bilden. Die Schwierigkeit der Bildgebung und Quantifizierung von dendritischen zu Schichten und Spalten Targeting hat die Studie von dendritischen Entwicklung in säulen und laminierten Hirnstrukturen behindert. Drosophila Medulla Neuronen sind ein ideales Modell für dendritische Routing und Schaltungsanordnung in Spalten und Schichten zu studieren. Die Fliege Medulla neuropil wird als 3D-Gitter aus 10 Schichten organisiert und etwa 750 Spalten. Jede Spalte ist durch einen Satz von Afferenzen innervated, einschließlich photoreceptors R7 / R8 und Lamina Neuronen L1 - L5, deren axonalen Terminals bilden topographische Karten in einem schichtspezifisch 6. Über 38 Arten von Medulla Neuronen sind in jedem Medulla Spalte und aufwendige Dendriten in bestimmten Schichten und mit entsprechenden Feldgrößen Eingänge aus diesen afferents 7 zu erhalten. Die synaptischen Schaltungen in der Medulla wurden bei der elektronenmikroskopischen Ebene rekonstruiert; Somit werden die synaptischen Partnerschaften gut 7 etabliert, 8. Darüber hinaus genetische Werkzeuge für verschiedene Arten von Medulla Neuronen Kennzeichnung sind vorhanden 9, 10, 11. Durch die Untersuchung drei Arten von transmedulla (Tm) Neuronen (Tm2, TM9 und TM20) haben wir bisher zwei identifizierten Zelltyp-spezifischen dendritischen Eigenschaften: (i) Tm Neuronen Dendriten in entweder der vorderen oder hinteren Richtung projizieren (planar projection Richtung) in Abhängigkeit von den Zelltypen und (ii) Dendriten der Medulla Neuronen enden in spezifischen medulla Schichten in einer zelltypspezifischen Weise (Schicht spezifische Terminierung) 12. Planar Projektionsrichtung und schichtspezifische Terminierung sind ausreichend, um diese drei Arten von Tm Neuronen zu differenzieren, während Mutationen, die Tm Antworten auf Schicht und Spalten Cues beeinflussen verschiedene Aspekte dieser Attribute stören. Hier präsentieren wir einen kompletten Workflow für die Prüfung des dendritischen Strukturierung von Drosophila Medulla Neuronen in Spalten und Schichten (Abbildung 1). Zuerst zeigen wir ein Dual-View-Bildgebungsverfahren, die kundenspezifische Software verwendet zwei konfokalen Bild zu kombinieren, stapelt hochwertige isotropen Bilder zu erzeugen. Diese Methode erfordert nur konventionelle konfokale Mikroskopie qualitativ hochwertige Bilder zu erzeugen, die für die zuverlässige Verfolgung von dendritischen Verzweigungen erlauben, ohne Mikroskopie mit Superauflösung zurückgreifen, wie eins STED (Stimulated Emission Depletion) oder strukturelle Beleuchtung. Zweitens stellen wir ein Verfahren zur dendritischen Dorne Tracing und zu einer Referenzspaltenanordnung der resultierenden Neuriten Spuren Registrierung. Drittens zeigen wir die Berechnungsmethoden für die Informationen auf der ebenen Projektionsrichtung und schichtspezifische Beendigung von Dendriten Extraktion sowie für Schätzungen für dendritischen Verzweigungen und Beendigung Frequenzen abzuleiten. Zusammen ermöglichen diese Verfahren für die Charakterisierung von dendritischen Muster in 3D, die Klassifizierung der Zelltypen auf dendritischen Morphologien basiert, und die Identifizierung von möglichen Defekten in Mutanten.

<table border="0" cellpadding="0" cellspacing="0" width="1632">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:464px;">Software</td>
			<td style="width:301px;"></td>
			<td style="width:227px;"></td>
			<td style="width:640px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Huygens Professional&#160;</td>
			<td>Scientific Volume Imaging</td>
			<td>version 16.05</td>
			<td>for image deconvolution (https://svi.nl).&#160; commercial software</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">MIPAV</td>
			<td></td>
			<td>version 7.3.0</td>
			<td>for image recombination and registration (http://mipav.cit.nih.gov/.).&#160; freeware</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">MIPAV plugin: PlugInDrosophilaRetinalRegistration.class</td>
			<td></td>
			<td></td>
			<td>freeware</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">MIPAV plugin: PlugInDrosophilaStandardColumnRegistration.class</td>
			<td></td>
			<td></td>
			<td>freeware</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Imaris</td>
			<td>Bitplane</td>
			<td></td>
			<td>for tracing neurites and assigning reference points for image registration (http://www.bitplane.com). commercial software</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Vaa3D</td>
			<td></td>
			<td></td>
			<td>for visualizing swc files (https://github.com/Vaa3D/release/releases/).&#160; freeware</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Matlab</td>
			<td>Mathworks</td>
			<td>R2014b</td>
			<td>for morphometric analysis of dendrites (http://www.mathworks.com).&#160; commercial software</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Matlab toolbox: TREES1.14</td>
			<td></td>
			<td>v1.14</td>
			<td>for analyzing dendritic morphometric parameters (http://www.treestoolbox.org/download.html).&#160; freeware</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Matlab toolbox: Dendritic_Tree_Toolbox</td>
			<td></td>
			<td>v1.0</td>
			<td>for calculating morphometric parameters (https://science.nichd.nih.gov/confluence/display/snc/Data+collections+for+imagines+combination+and+standardize+column+registration). Freeware</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Name</td>
			<td>Company</td>
			<td>Catalog number</td>
			<td>Comments</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Sample files</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">SWC file definition</td>
			<td></td>
			<td></td>
			<td>http://www.neuronland.org/NLMorphologyConverter/MorphologyFormats/SWC/Spec.html</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">The codes and sample files for image combination and registration</td>
			<td></td>
			<td></td>
			<td>https://science.nichd.nih.gov/confluence/display/snc/Data+collections+for+imagines+combination+and+standardize+column+registration</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Reference point example&#160;</td>
			<td></td>
			<td></td>
			<td>https://science.nichd.nih.gov/confluence/download/attachments/117216914/points.csv?version=1&#38;modificationDate=1471880596000&#38;api=v2</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Name</td>
			<td>Company</td>
			<td>Catalog number</td>
			<td>Comments</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Computer system</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">MS Windows Windows 7 x64 or Macintosh OS X 10.7 or later</td>
			<td></td>
			<td></td>
			<td>3GHz 64-bit quad-core processor, 16G RAM (minimal)</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Optional: Quadro4000&#160; (or above) graphic card</td>
			<td>Nvidia</td>
			<td></td>
			<td>for stereographic visualization of dendrites.</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Optional: NVIDIA 3D vision2</td>
			<td>Nvidia</td>
			<td></td>
			<td>http://www.nvidia.com/object/3d-vision-main.html</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Optional: 120 Hz LCD display for NVIDIA 3D vision2</td>
			<td></td>
			<td></td>
			<td>http://www.nvidia.com/object/3d-vision-system-requirements.html</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Name</td>
			<td>Company</td>
			<td>Catalog number</td>
			<td>Comments</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Reagents for imaging</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">24B10 antibody</td>
			<td>The Developmental Studies Hybridoma Bank</td>
			<td>24B10</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">GFP Tag Antibody</td>
			<td>Thermofisher Scientific</td>
			<td>G10362</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Goat anti-Rabbit (H+L), Alexa Fluor 488</td>
			<td>Thermofisher Scientific</td>
			<td>A11034</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Goat anti-Mouse (H+L), Alexa Fluor 568</td>
			<td>Thermofisher Scientific</td>
			<td>A21124</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">VECTASHIELD Antifade Mounting Medium</td>
			<td>Vector Laboratories</td>
			<td>H-1000</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Mounting&#160;Clay&#160;</td>
			<td>Fisher</td>
			<td>S04179</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">70% glycerol in 1X PBS</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Cover glasses, high performance, D=0.17mm</td>
			<td>Zeiss</td>
			<td>474030-9000-000</td>
			<td></td>
		</tr>
	</tbody>
</table>

analyzing dendritic morphology in columns and layers

In vielen Regionen des zentralen Nervensystems, wie beispielsweise die Fliegen optic Lappen und der wirbel cortex werden in Schichten und Säulen synaptischen Schaltungen organisiert Gehirn Verdrahtung während der Entwicklung und der Informationsverarbeitung in den entwickelten Tieren erleichtern. Postsynaptischen Neuronen aufwendige Dendriten in typspezifische Muster in bestimmten Schichten mit entsprechenden präsynaptischen zu Synapse. Die Fliege medulla Neuropil besteht aus 10 Schichten und 750 Spalten; jede Spalte von Dendriten von mehr als 38 Arten von Medulla Neuronen innervated, die mit den axonalen Terminals einiger 7 Arten von Afferenzen in einem typspezifischen Art und Weise entsprechen. Dieser Bericht beschreibt die Verfahren zur Abbildung und Dendriten der Medulla Neuronen zu analysieren. Der Workflow besteht aus drei Abschnitten: (i) die Dual-View-Abbildungsabschnitt verbindet zwei konfokale Bildstapel in orthogonalen Richtungen in eine hochauflösende 3D-Bild von Dendriten gesammelt; (Ii) die Dendriten Verfolgung und Registrierung Abschnitt Spuren dendritischenDorne in 3D und registriert auf die Referenzspaltenanordnung dendritischen Spuren; (Iii) die dendritische Analyseabschnitt analysiert dendritische Muster in Bezug auf Spalten und Schichten, einschließlich der schichtspezifischen Termination und planar Projektionsrichtung dendritischer Dorne und leitet Schätzungen von dendritischen Verzweigungs und Termination Frequenzen. Die Protokolle verwenden benutzerdefinierte Plugins gebaut auf der Open-Source-MIPAV (Medical Imaging Verarbeitung, Analyse und Visualisierung) Plattform und benutzerdefinierte Toolboxen in der Matrix Laborsprache. Zusammen bieten diese Protokolle einen vollständigen Arbeitsablauf die dendritische Routing von Drosophila medulla Neuronen in Schichten und Säulen zur Analyse, Zelltypen zu identifizieren, und Defekte in Mutanten zu bestimmen.

Unter Verwendung des Dual-View-Bildgebungsverfahren hier vorgestellten ein Gehirn fly dünn markiertem TM20 Neuronen enthält, wurde in zwei orthogonalen Richtungen abgebildet. Vor der Bildgebung wurde das Gehirn mit den entsprechenden primären und sekundären Antikörper zur Visualisierung von membran tethered GFP und Photorezeptor Axone gefärbt. Für die Bildgebung wurde das Gehirn zuerst in der horizontalen Ausrichtung montiert (2A, B). Ein GFP-markiertem TM20 Neuro...

Watch this Scientific Journal Video about Analyzing Dendritic Morphology in Columns and Layers at JoVE.com

Analyzing Dendritic Morphology in Columns and Layers

Hier zeigen wir , wie dendritische Routing von Drosophila Medulla Neuronen in Spalten und Schichten zu analysieren. Der Workflow enthält einen Dual-View-Imaging-Technik, um die Bildqualität und Computational Tools für das Aufspüren, Registrierung dendritischen Dorne auf die Referenzspaltenanordnung und für die Analyse der dendritischen Strukturen in 3D-Raum zu verbessern.

Analyse dendritischer Morphologie in Spalten und Schichten

In many regions of the central nervous systems, such as the fly optic lobes and the vertebrate cortex, synaptic circuits are organized in layers and ...

analyzing-dendritic-morphology-in-columns-and-layers

Research

JoVE Journal

Neuroscience

9.2K Aufrufe.  National Institutes of Health (NIH).  Hier zeigen wir , wie dendritische Routing von Drosophila Medulla Neuronen in Spalten und Schichten zu analysieren. Der Workflow enthält einen Dual-View-Imaging-Technik, um die Bildqualität und Computational Tools für das Aufspüren, Registrierung dendritischen Dorne auf die Referenzspaltenanordnung und für die Analyse der dendritischen Strukturen in 3D-Raum zu verbessern. 

Serie: Analyzing Dendritic Morphology in Columns and Layers

Automated Sholl Analysis of Digitized Neuronal Morphology at Multiple Scales

Neuronal morphology plays a significant role in determining how neurons function and communicate1-3. Specifically, it affects the ability of neurons to receive inputs from other cells2 and contributes to the propagation of action potentials4,5. The morphology of the neurites also affects how information is processed. The diversity of dendrite morphologies facilitate local and long range signaling and allow individual neurons or groups of neurons to carry out specialized functions within the neuronal network6,7. Alterations in dendrite morphology, including fragmentation of dendrites and changes in branching patterns, have been observed in a number of disease states, including Alzheimer's disease8, schizophrenia9,10, and mental retardation11. The ability to both understand the factors that shape dendrite morphologies and to identify changes in dendrite morphologies is essential in the understanding of nervous system function and dysfunction.
Neurite morphology is often analyzed by Sholl analysis and by counting the number of neurites and the number of branch tips. This analysis is generally applied to dendrites, but it can also be applied to axons. Performing this analysis by hand is both time consuming and inevitably introduces variability due to experimenter bias and inconsistency. The Bonfire program is a semi-automated approach to the analysis of dendrite and axon morphology that builds upon available open-source morphological analysis tools. Our program enables the detection of local changes in dendrite and axon branching behaviors by performing Sholl analysis on subregions of the neuritic arbor. For example, Sholl analysis is performed on both the neuron as a whole as well as on each subset of processes (primary, secondary, terminal, root, etc.) Dendrite and axon patterning is influenced by a number of intracellular and extracellular factors, many acting locally. Thus, the resulting arbor morphology is a result of specific processes acting on specific neurites, making it necessary to perform morphological analysis on a smaller scale in order to observe these local variations12.
The Bonfire program requires the use of two open-source analysis tools, the NeuronJ plugin to ImageJ and NeuronStudio. Neurons are traced in ImageJ, and NeuronStudio is used to define the connectivity between neurites. Bonfire contains a number of custom scripts written in MATLAB (MathWorks) that are used to convert the data into the appropriate format for further analysis, check for user errors, and ultimately perform Sholl analysis. Finally, data are exported into Excel for statistical analysis. A flow chart of the Bonfire program is shown in Figure 1.

We have developed a computer program to analyze neuronal morphology. In combination with two existing open source analysis tools, our program performs Sholl analysis and determines the number of neurites, branch points, and neurite tips. The analyses are performed so that local changes in neurite morphology can be observed.

Automatisierte Sholl Analyse digitalisierter neuronale Morphologie bei Multiple Scales

Neuronal morphology plays a significant role in determining how neurons function and communicate1-3.  Specifically, it affects the ability of neurons to ...

Forschung

Neurowissenschaften

Analysis of Dendritic Spine Morphology in Cultured CNS Neurons

Dendritic spines are the sites of the majority of excitatory connections within the brain, and form the post-synaptic 
compartment of synapses. These structures are rich in actin and have been shown to be highly dynamic. In response to classical Hebbian plasticity 
as well as neuromodulatory signals, dendritic spines can change shape and number, which is thought to be critical for the refinement of neural 
circuits and the processing and storage of information within the brain. Within dendritic spines, a complex network of proteins link extracellular 
signals with the actin cyctoskeleton allowing for control of dendritic spine morphology and number. Neuropathological studies have demonstrated that 
a number of disease states, ranging from schizophrenia to autism spectrum disorders, display abnormal dendritic spine morphology or numbers. 
Moreover, recent genetic studies have identified mutations in numerous genes that encode synaptic proteins, leading to suggestions that these 
proteins may contribute to aberrant spine plasticity that, in part, underlie the pathophysiology of these disorders. In order to study the potential 
role of these proteins in controlling dendritic spine morphologies/number, the use of cultured cortical neurons offers several advantages. Firstly, 
this system allows for high-resolution imaging of dendritic spines in fixed cells as well as time-lapse imaging of live cells. Secondly, this in 
vitro system allows for easy manipulation of protein function by expression of mutant proteins, knockdown by shRNA constructs, or pharmacological 
treatments. These techniques allow researchers to begin to dissect the role of disease-associated proteins and to predict how mutations of these 
proteins may function in vivo.

Numerous recent studies have identified mutations in synaptic proteins associated with brain pathologies. Primary cultured cortical neurons offer great flexibility in examining the effects of these disease-associated proteins on dendritic spine morphology and motility.

Die Analyse der dendritischen Spine Morphologie in Cultured ZNS-Neuronen

Dendritic spines are the sites of the majority of excitatory connections within the brain, and form the post-synaptic 
compartment of synapses. These ...

Inducing Dendritic Growth in Cultured Sympathetic Neurons

The shape of the dendritic arbor determines the total synaptic input a neuron can receive 1-3, and influences the types and distribution of these inputs 4-6. Altered patterns of dendritic growth and plasticity are associated with impaired neurobehavioral function in experimental models 7, and are thought to contribute to clinical symptoms observed in both neurodevelopmental disorders 8-10 and neurodegenerative diseases 11-13. Such observations underscore the functional importance of precisely regulating dendritic morphology, and suggest that identifying mechanisms that control dendritic growth will not only advance understanding of how neuronal connectivity is regulated during normal development, but may also provide insight on novel therapeutic strategies for diverse neurological diseases.
Mechanistic studies of dendritic growth would be greatly facilitated by the availability of a model system that allows neurons to be experimentally switched from a state in which they do not extend dendrites to one in which they elaborate a dendritic arbor comparable to that of their in vivo counterparts. Primary cultures of sympathetic neurons dissociated from the superior cervical ganglia (SCG) of perinatal rodents provide such a model. When cultured in defined medium in the absence of serum and ganglionic glial cells, sympathetic neurons extend a single process which is axonal, and this unipolar state persists for weeks to months in culture 14,15. However, the addition of either bone morphogenetic protein-7 (BMP-7) 16,17 or Matrigel 18 to the culture medium triggers these neurons to extend multiple processes that meet the morphologic, biochemical and functional criteria for dendrites. Sympathetic neurons dissociated from the SCG of perinatal rodents and grown under defined conditions are a homogenous population of neurons 19 that respond uniformly to the dendrite-promoting activity of Matrigel, BMP-7 and other BMPs of the decapentaplegic (dpp) and 60A subfamilies 17,18,20,21. Importantly, Matrigel- and BMP-induced dendrite formation occurs in the absence of changes in cell survival or axonal growth 17,18.
Here, we describe how to set up dissociated cultures of sympathetic neurons derived from the SCG of perinatal rats so that they are responsive to the selective dendrite-promoting activity of Matrigel or BMPs.

We describe a protocol for using bone morphogenetic protein-7 (BMP-7) or Matrigel to selectively induce dendritic growth in primary sympathetic neurons dissociated from the superior cervical ganglia (SCG) of perinatal rats.

Induktion von dendritischen Wachstums in Cultured sympathischen Neuronen

The shape of the dendritic arbor determines the total synaptic input a neuron can receive 1-3, and influences the types and distribution of these inputs ...

The Analysis of Purkinje Cell Dendritic Morphology in Organotypic Slice Cultures

Purkinje cells are an attractive model system for studying dendritic development, because they have an impressive dendritic tree which is strictly oriented in the sagittal plane and develops mostly in the postnatal period in small rodents 3. Furthermore, several antibodies are available which selectively and intensively label Purkinje cells including all processes, with anti-Calbindin D28K being the most widely used. For viewing of dendrites in living cells, mice expressing EGFP selectively in Purkinje cells 11 are available through Jackson labs. Organotypic cerebellar slice cultures cells allow easy experimental manipulation of Purkinje cell dendritic development because most of the dendritic expansion of the Purkinje cell dendritic tree is actually taking place during the culture period 4. We present here a short, reliable and easy protocol for viewing and analyzing the dendritic morphology of Purkinje cells grown in organotypic cerebellar slice cultures. For many purposes, a quantitative evaluation of the Purkinje cell dendritic tree is desirable. We focus here on two parameters, dendritic tree size and branch point numbers, which can be rapidly and easily determined from anti-calbindin stained cerebellar slice cultures. These two parameters yield a reliable and sensitive measure of changes of the Purkinje cell dendritic tree. Using the example of treatments with the protein kinase C (PKC) activator PMA and the metabotropic glutamate receptor 1 (mGluR1) we demonstrate how differences in the dendritic development are visualized and quantitatively assessed. The combination of the presence of an extensive dendritic tree, selective and intense immunostaining methods, organotypic slice cultures which cover the period of dendritic growth and a mouse model with Purkinje cell specific EGFP expression make Purkinje cells a powerful model system for revealing the mechanisms of dendritic development.

We present a protocol that permits to view and to quantitatively asses the morphology of the dendritic tree of individual Purkinje cells grown in organotypic cerebellar slice cultures. This protocol is intended to promote studies on the mechanisms of Purkinje cell dendritic development.

Die Analyse von Purkinje Zelle Dendritische Morphologie in organotypischen Kulturen

Purkinje cells are an attractive model system for studying dendritic development, because they have an impressive dendritic tree which is strictly ...

Visualizing the Effects of a Positive Early Experience, Tactile Stimulation, on Dendritic Morphology and Synaptic Connectivity with Golgi-Cox Staining

To generate longer-term changes in behavior, experiences must be producing stable changes in neuronal morphology and synaptic connectivity. Tactile stimulation is a positive early experience that mimics maternal licking and grooming in the rat. Exposing rat pups to this positive experience can be completed easily and cost-effectively by using highly accessible materials such as a household duster. Using a cross-litter design, pups are either stroked or left undisturbed, for 15 min, three times per day throughout the perinatal period. To measure the neuroplastic changes related to this positive early experience, Golgi-Cox staining of brain tissue is utilized. Owing to the fact that Golgi-Cox impregnation stains a discrete number of neurons rather than all of the cells, staining of the rodent brain with Golgi-Cox solution permits the visualization of entire neuronal elements, including the cell body, dendrites, axons, and dendritic spines. The staining procedure is carried out over several days and requires that the researcher pay close attention to detail. However, once staining is completed, the entire brain has been impregnated and can be preserved indefinitely for ongoing analysis. Therefore, Golgi-Cox staining is a valuable resource for studying experience-dependent plasticity.

This paper describes the procedures for tactile stimulation of rat pups and subsequent Golgi-Cox staining of neuronal morphology. Tactile stimulation is a positive experience that is administered in the perinatal period by stroking pups with a household duster. Golgi-cox staining is a reliable procedure permitting the visualization of entire neurons.

Visualisierung der Auswirkungen einer Früh Positive Erfahrung, taktile Stimulation, auf dendritischen Morphologie und synaptische Verbindungen mit Golgi-Cox Färbung

To generate longer-term changes in behavior, experiences must be producing stable changes in neuronal morphology and synaptic connectivity. Tactile ...

Fast Micro-iontophoresis of Glutamate and GABA: A Useful Tool to Investigate Synaptic Integration

One of the fundamental interests in neuroscience is to understand the integration of excitatory and inhibitory inputs along the very complex structure of the dendritic tree, which eventually leads to neuronal output of action potentials at the axon. The influence of diverse spatial and temporal parameters of specific synaptic input on neuronal output is currently under investigation, e.g. the distance-dependent attenuation of dendritic inputs, the location-dependent interaction of spatially segregated inputs, the influence of GABAergig inhibition on excitatory integration, linear and non-linear integration modes, and many more.
With fast micro-iontophoresis of glutamate and GABA it is possible to precisely investigate the spatial and temporal integration of glutamatergic excitation and GABAergic inhibition. Critical technical requirements are either a triggered fluorescent lamp, light-emitting diode (LED), or a two-photon scanning microscope to visualize dendritic branches without introducing significant photo-damage of the tissue. Furthermore, it is very important to have a micro-iontophoresis amplifier that allows for fast capacitance compensation of high resistance pipettes. Another crucial point is that no transmitter is involuntarily released by the pipette during the experiment.
Once established, this technique will give reliable and reproducible signals with a high neurotransmitter and location specificity. Compared to glutamate and GABA uncaging, fast iontophoresis allows using both transmitters at the same time but at very distant locations without limitation to the field of view. There are also advantages compared to focal electrical stimulation of axons: with micro-iontophoresis the location of the input site is definitely known and it is sure that only the neurotransmitter of interest is released. However it has to be considered that with micro-iontophoresis only the postsynapse is activated and presynaptic aspects of neurotransmitter release are not resolved. In this article we demonstrate how to set up micro-iontophoresis in brain slice experiments.

In this article we introduce fast micro-iontophoresis of neurotransmitters as a technique to investigate integration of postsynaptic signals with high spatial and temporal precision.

Schnelle Micro-Iontophorese von Glutamat und GABA: Ein nützliches Tool, um Synaptic Integration Untersuchen

One of the fundamental interests in neuroscience is to understand the integration of excitatory and inhibitory inputs along the very complex structure of ...

Genetic Manipulation of Cerebellar Granule Neurons In Vitro and In Vivo to Study Neuronal Morphology and Migration

Developmental events in the brain including neuronal morphogenesis and migration are highly orchestrated processes. In vitro and in vivo analyses allow for an in-depth characterization to identify pathways involved in these events. Cerebellar granule neurons (CGNs) that are derived from the developing cerebellum are an ideal model system that allows for morphological analyses. Here, we describe a method of how to genetically manipulate CGNs and how to study axono- and dendritogenesis of individual neurons. With this method the effects of RNA interference, overexpression or small molecules can be compared to control neurons. In addition, the rodent cerebellar cortex is an easily accessible in vivo system owing to its predominant postnatal development. We also present an in vivo electroporation technique to genetically manipulate the developing cerebella and describe subsequent cerebellar analyses to assess neuronal morphology and migration.

Genetic Manipulation of Cerebellar Granule Neurons In Vitro and In Vivo to Study Neuronal Morphology and Migration

Neuronal morphogenesis and migration are crucial events underlying proper brain development. Here, we describe methods to genetically manipulate cultured cerebellar granule neurons and the developing cerebellum for the assessment of morphology and migratory characteristics of neurons.

Genetische Manipulation von Kleinhirnkörnerzellen<em&gt; In-vitro-</em&gt; Und<em&gt; In Vivo</em&gt;, Um neuronale Morphologie und Migration Studieren

Developmental events in the brain including neuronal morphogenesis and migration are highly orchestrated processes. In vitro and in vivo analyses allow ...

The Indirect Neuron-astrocyte Coculture Assay: An In Vitro Set-up for the Detailed Investigation of Neuron-glia Interactions

Proper neuronal development and function is the prerequisite of the developing and the adult brain. However, the mechanisms underlying the highly controlled formation and maintenance of complex neuronal networks are not completely understood thus far. The open questions concerning neurons in health and disease are diverse and reaching from understanding the basic development to investigating human related pathologies, e.g.,&#160;Alzheimer&#39;s disease and&#160;Schizophrenia. The most detailed analysis of neurons can be performed in vitro. However, neurons are demanding cells and need the additional support of astrocytes for their long-term survival. This cellular heterogeneity is in conflict with the aim to dissect the analysis of neurons and astrocytes. We present here a cell-culture assay that allows for the long-term cocultivation of pure primary neurons and astrocytes, which share the same chemically defined medium, while being physically separated. In this setup, the cultures survive for up to four weeks and the assay is suitable for a diversity of investigations concerning neuron-glia interaction.

The Indirect Neuron-astrocyte Coculture Assay: An In Vitro Set-up for the Detailed Investigation of Neuron-glia Interactions

This protocol describes the indirect neuron-astrocyte coculture for compartmentalized analysis of neuron-glia interactions.

Die indirekte Neuron-Astrozyten Cokultur Assay: Ein<em&gt; In Vitro</em&gt; Für die detaillierte Untersuchung von Neuron-Glia Interaktionen Set-up

Proper neuronal development and function is the prerequisite of the developing and the adult brain. However, the mechanisms underlying the highly ...

Quantitative Analysis of Neuronal Dendritic Arborization Complexity in Drosophila

Dendrites are the branched projections of a neuron, and dendritic morphology reflects synaptic organization during the development of the nervous system. Drosophila larval neuronal dendritic arborization (da) is an ideal model for studying morphogenesis of neural dendrites and gene function in the development of nervous system. There are four classes of da neurons. Class IV is the most complex with a branching pattern that covers almost the entire area of the larval body wall. We have previously characterized the effect of silencing the Drosophila ortholog of SOX5 on class IV neuronal dendritic arborization complexity (NDAC) using four parameters: the length of dendrites, the surface area of dendrite coverage, the total number of branches, and the branching structure. This protocol presents the workflow of NDAC quantitative analysis, consisting of larval dissection, confocal microscopy, and image analysis procedures using ImageJ software. Further insight into da neuronal development and its underlying mechanisms will improve the understanding of neuronal function and provide clues about the fundamental causes of neurological and neurodevelopmental disorders.

Quantitative Analysis of Neuronal Dendritic Arborization Complexity in Drosophila

This protocol focuses on quantitative analysis of neuronal dendritic arborization complexity (NDAC) in Drosophila, which can be used for studies of dendritic morphogenesis.

Quantitative Analyse der neuronalen dendritischen Arborization Komplexität in Drosophila

Dendrites are the branched projections of a neuron, and dendritic morphology reflects synaptic organization during the development of the nervous system. ...

Visualizing and Analyzing Intracellular Transport of Organelles and Other Cargos in Astrocytes

Astrocytes are among the most abundant cell types in the adult brain, where they play key roles in a multiplicity of functions. As a central player in brain homeostasis, astrocytes supply neurons with vital metabolites and buffer extracellular water, ions, and glutamate. An integral component of the &#8220;tri-partite&#8221; synapse, astrocytes are also critical in the formation, pruning, maintenance, and modulation of synapses. To enable these highly interactive functions, astrocytes communicate among themselves and with other glial cells, neurons, the brain vasculature, and the extracellular environment through a multitude of specialized membrane proteins that include cell adhesion molecules, aquaporins, ion channels, neurotransmitter transporters, and gap junction molecules. To support this dynamic flux, astrocytes, like neurons, rely on tightly coordinated and efficient intracellular transport. Unlike neurons,&#160;where intracellular trafficking has been extensively delineated, microtubule-based transport in astrocytes has been less studied. Nonetheless, exo- and endocytic trafficking of cell membrane proteins and intracellular organelle transport orchestrates astrocytes&#8217; normal biology, and these processes are often affected in disease or in response to injury. Here we present a straightforward protocol to culture high quality murine astrocytes, to fluorescently label astrocytic proteins and organelles of interest, and to record their intracellular transport dynamics using time-lapse confocal microscopy. We also demonstrate how to extract and quantify relevant transport parameters from the acquired movies using available image analysis software (i.e., ImageJ/FIJI) plugins.

Here we describe an in vitro live-imaging method to visualize intracellular transport of organelles and trafficking of plasma membrane proteins in murine astrocytes. This protocol also presents an image analysis methodology to determine cargo transport itineraries and kinetics.

Visualisierung und Analyse des intrazellulären Transports von Organellen und anderen Ladungen in Astrozyten

Astrocytes are among the most abundant cell types in the adult brain, where they play key roles in a multiplicity of functions. As a central player in ...