Cell-Autonomous TrkB Signaling in Presynaptic Retinal Ganglion Cells Mediates Axon Arbor Growth and Synapse Maturation during the Establishment of Retinotectal Synaptic Connectivity

Marshak, Sonya; Nikolakopoulou, Angeliki Maria; Dirks, Ron P.; Martens, Gerard J.M.; Cohen-Cory, Susana

doi:10.1523/jneurosci.4434-06.2007

Cited by 84 publications

(118 citation statements)

References 82 publications

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“…10), although more studies are required to clarify this issue. Similar intercellular competitive mechanisms have been reported for other synaptic cell adhesion molecules, such as ephrin-B3, neuroligin-1, and TrkB (Marshak et al, 2007;McClelland et al, 2010;Kwon et al, 2012). In the case of ephrin-B3 and neuroligin-1, binding to presynaptic EphB2 and neurexins, respectively, is required for the intercellular competition (McClelland et al, 2010;Kwon et al, 2012).…”

Section: Discussionsupporting

confidence: 64%

Neurotrophin-3 Regulates Synapse Development by Modulating TrkC-PTPσ Synaptic Adhesion and Intracellular Signaling Pathways

et al. 2016

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Neurotrophin-3 (NT-3) is a secreted neurotrophic factor that binds neurotrophin receptor tyrosine kinase C (TrkC), which in turn binds to presynaptic protein tyrosine phosphatase (PTP) to govern excitatory synapse development. However, whether and how NT-3 cooperates with the TrkC-PTP synaptic adhesion pathway and TrkC-mediated intracellular signaling pathways in rat cultured neurons has remained unclear. Here, we report that NT-3 enhances TrkC binding affinity for PTP. Strikingly, NT-3 treatment bidirectionally regulates the synaptogenic activity of TrkC: at concentrations of 10 -25 ng/ml, NT-3 further enhanced the increase in synapse density induced by TrkC overexpression, whereas at higher concentrations, NT-3 abrogated TrkC-induced increases in synapse density. Semiquantitative immunoblotting and optogenetics-based imaging showed that 25 ng/ml NT-3 or light stimulation at a power that produced a comparable level of NT-3 (6.25 W) activated only extracellular signal-regulated kinase (ERK) and Akt, whereas 100 ng/ml NT-3 (light intensity, 25 W) further triggered the activation of phospholipase C-␥1 and CREB independently of PTP. Notably, disruption of TrkC intracellular signaling pathways, extracellular ligand binding, or kinase activity by point mutations compromised TrkC-induced increases in synapse density. Furthermore, only sparse, but not global, TrkC knock-down in cultured rat neurons significantly decreased synapse density, suggesting that intercellular differences in TrkC expression level are critical for its synapse-promoting action. Together, our data demonstrate that NT-3 is a key factor in excitatory synapse development that may direct higher-order assembly of the TrkC/ PTP complex and activate distinct intracellular signaling cascades in a concentration-dependent manner to promote competitionbased synapse development processes.

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Section: Discussionsupporting

confidence: 64%

Neurotrophin-3 Regulates Synapse Development by Modulating TrkC-PTPσ Synaptic Adhesion and Intracellular Signaling Pathways

et al. 2016

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“…1996;Caton et al 2000). Even so, our current understanding suggests that the most general function of trophic factors is to promote the stabilization and survival of neurons and their processes once they have made connections with their appropriate targets (Reichardt 2006;Marshak et al 2007). …”

Section: Trophic Signalsmentioning

confidence: 99%

Cellular Strategies of Axonal Pathfinding

Raper

Mason

2010

Cold Spring Harbor Perspectives in Biology

157

130

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Axons follow highly stereotyped and reproducible trajectories to their targets. In this review we address the properties of the first pioneer neurons to grow in the developing nervous system and what has been learned over the past several decades about the extracellular and cell surface substrata on which axons grow. We then discuss the types of guidance cues and their receptors that influence axon extension, what determines where cues are expressed, and how axons respond to the cues they encounter in their environment.T his article provides an overview of how growth cones respond to the cellular substrata and molecular cues they encounter as they extend through the developing nervous system. It elaborates on the primer by Kolodkin and TessierLavigne (2010) and touches on many of the topics covered in greater detail in the articles that follow. The first sections describe how axons extend in a directed manner, the substrata on which they grow, interactions between pioneer and follower axons, and growth cone behaviors in emerging tracts and at decision points. The subsequent sections discuss examples of specific cues, their distributions, how their distributions are determined, and how growth cones integrate multiple cues during pathfinding. AXONS EXTEND IN VIVO IN A DIRECTED MANNERThe first person to visualize the growing tips of axons, Ramon y Cajal, recognized that axons for the most part grow very efficiently towards their ultimate targets. He was a strong advocate for axons finding their way in response to chemotactic cues:"If one admits that neuroblasts are endowed with chemotactic properties, then one might also imagine that they are capable of ameboid movements, initiated by factors secreted from epithelial, neural, or mesodermal elements. As a result, their processes may be oriented in the direction of chemical gradients, and thus guided to the secreting cells" (Ramon y Cajal 1892; trans. English, 1995).This surprisingly modern outlook emphasizing directed guidance was temporarily derailed by the views of Weiss during the 1920s and 1930s. He first argued that functional specificity did not arise as a consequence of specific axonal connections (Weiss 1936), and later argued that nonspecific mechanical guidance cues play a predominant role in guiding axons and organizing them into nerves and tracts

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“…Morphometric measurement further defines the quantitative and statistical relationships between the cell dynamics that underlie morphogenesis (Kim and Davidson 2011;Marshak et al, 2007;Elul et al, 1997;Witte et al, 1996). Mathematical decomposition of cell dynamics additionally facilitates the computational modeling of cellular mechanisms that drive morphogenesis (Satulovsky et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

“…A powerful technique for elucidating the dynamic cellular mechanisms of morphogenesis is time-lapse videomicroscopic imaging of cells in embryonic tissues undergoing morphogenesis (Elul and Keller 2000;Elul et al, 1997;Harris et al, 1987). The mechanisms underlying morphogenetic processes can be clarified by observation of cell dynamics from these time-lapse video sequences.Morphometric measurement further defines the quantitative and statistical relationships between the cell dynamics that underlie morphogenesis (Kim and Davidson 2011;Marshak et al, 2007;Elul et al, 1997;Witte et al, 1996). Mathematical decomposition of cell dynamics additionally facilitates the computational modeling of cellular mechanisms that drive morphogenesis (Satulovsky et al, 2008).…”

mentioning

confidence: 99%

Visualizing Morphogenesis with the Processing Programming Language

Patel¹,

Bains²,

Miller³

et al. 2017

JBC

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We used Processing, a visual artists' programming language developed at MIT Media Lab, to IntroductionProcessing is a Java based software language and environment created at MIT Media Laboratory in 2001 for visual modeling (www.processing.org). Processing has grown into a popular tool and online community for programming within the visual arts and data visualization fields. Several artists have used Processing to model or simulate various biological phenomena. One artist animated a matrix of biological cells switching between two states (Polyptic by George Legrady), while another simulated fungal hyphae growth using images as food (Mycelium by Ryan Alexander). A textbook further describes how Processing can animate dynamic processes in nature using diverse underlying theoretical models (Shiffman 2012). However, Processing has yet to make its full mark in modeling of biological phenomena. One potential area of application for Processing is computational visualization of morphogenesis in developmental biology.Morphogenesis -the generation of shape and form in embryonic tissues -is a critical process in developmental biology (Gilbert 2013). Morphogenesis is responsible for elongating the body axis, forming the organs in the body, and establishing neuronal circuitry in the brain, among other processes. A central issue in the study of morphogenesis is determining the cell behaviors (e.g. motility, rearrangement, shape change, and division) that are responsible for changing tissue shapes. A powerful technique for elucidating the dynamic cellular mechanisms of morphogenesis is time-lapse videomicroscopic imaging of cells in embryonic tissues undergoing morphogenesis (Elul and Keller 2000;Elul et al., 1997;Harris et al., 1987). The mechanisms underlying morphogenetic processes can be clarified by observation of cell dynamics from these time-lapse video sequences.Morphometric measurement further defines the quantitative and statistical relationships between the cell dynamics that underlie morphogenesis (Kim and Davidson 2011;Marshak et al., 2007;Elul et al., 1997;Witte et al., 1996). Mathematical decomposition of cell dynamics additionally facilitates the computational modeling of cellular mechanisms that drive morphogenesis (Satulovsky et al., 2008). MethodsIn this paper, we use the Processing programming language to visualize dynamic cell behaviors driving morphogenesis in the developing nervous system. Based on in vivo time-lapse image sequences, we created models of cell dynamics underlying two morphogenetic processes in the developing nervous system. We first computationally modeled the cell motility that drives neural tube formation and spinal cord elongation in vertebrate embryos. The terminal branching of optic axonal arbors that establish synaptic connectivity in the primary visual projection was then simulated. These visualizations highlight the process of computational decomposition of the dynamic cell behaviors that shape the developing nervous system, which may be useful for artists seeking to illustrate ...

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Cell-Autonomous TrkB Signaling in Presynaptic Retinal Ganglion Cells Mediates Axon Arbor Growth and Synapse Maturation during the Establishment of Retinotectal Synaptic Connectivity

Cited by 84 publications

References 82 publications

Neurotrophin-3 Regulates Synapse Development by Modulating TrkC-PTPσ Synaptic Adhesion and Intracellular Signaling Pathways

Neurotrophin-3 Regulates Synapse Development by Modulating TrkC-PTPσ Synaptic Adhesion and Intracellular Signaling Pathways

Cellular Strategies of Axonal Pathfinding

Visualizing Morphogenesis with the Processing Programming Language

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