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. 相似文献
The cerebellum is a brain structure involved in the coordination, control and learning of movements, and elucidation of its function is an important issue. Japanese scholars have made seminal contributions in this field of neuroscience. Electrophysiological studies of the cerebellum have a long history in Japan since the pioneering works by Ito and Sasaki. Elucidation of the basic circuit diagram of the cerebellum in the 1960s was followed by the construction of cerebellar network theories and finding of their neural correlates in the 1970s. A theoretically predicted synaptic plasticity, long-term depression (LTD) at parallel fibre to Purkinje cell synapse, was demonstrated experimentally in 1982 by Ito and co-workers. Since then, Japanese neuroscientists from various disciplines participated in this field and have made major contributions to elucidate molecular mechanisms underlying LTD. An important pathway for LTD induction is type-1 metabotropic glutamate receptor (mGluR1) and its downstream signal transduction in Purkinje cells. Sugiyama and co-workers demonstrated the presence of mGluRs and Nakanishi and his pupils identified the molecular structures and functions of the mGluR family. Moreover, the authors contributed to the discovery and elucidation of several novel functions of mGluR1 in cerebellar Purkinje cells. mGluR1 turned out to be crucial for the release of endocannabinoid from Purkinje cells and the resultant retrograde suppression of transmitter release. It was also found that mGluR1 and its downstream signal transduction in Purkinje cells are indispensable for the elimination of redundant synapses during post-natal cerebellar development. This article overviews the seminal works by Japanese neuroscientists, focusing on mGluR1 signalling in cerebellar Purkinje cells. 相似文献
It has been suggested that information in the brain is encoded in temporal spike patterns which are decoded by a combination of time delays and coincidence detection. Here, we show how a multi-compartmental model of a cerebellar Purkinje cell can learn to recognise temporal parallel fibre activity patterns by adapting latencies of calcium responses after activation of metabotropic glutamate receptors (mGluRs). In each compartment of our model, the mGluR signalling cascade is represented by a set of differential equations that reflect the underlying biochemistry. Phosphorylation of the mGluRs changes the concentration of receptors which are available for activation by glutamate and thereby adjusts the time delay between mGluR stimulation and voltage response. The adaptation of a synaptic delay as opposed to a weight represents a novel non-Hebbian learning mechanism that can also implement the adaptive timing of the classically conditioned eye-blink response. 相似文献
Niemann Pick type C (NPC1) is a rare fatal hereditary cholesterol storage disease associated with a massive Purkinje cells loss. The mechanisms leading to neurodegeneration are still poorly understood. Different laboratories pointed to hypersensitivity to cytotoxic effects of statins (HMG‐CoA reductase inhibitors) in NPC1 and suggested an underlying lack of geranylgeranyl pyrophosphate (GGPP). GGPP is a non‐sterol isoprenoid essential for cell survival and differentiation. We measured GGPP levels in cerebella of a NPC1 mouse model and of wild‐type littermates and found a physiological increase of GGPP levels between post‐natal days 21 and 49 in wild‐type mice but not in NPC mice. This further supports the hypothesis that Purkinje cell loss may be due to an extremely low level of GGPP. The progressive Purkinje cell loss in NPC starts between p21 and p49. To test the hypothesis, we used long‐term organotypic slice cultures of NPC1 mice that display the natural history of NPC1 disease in vitro and tested if chronic administration of GGPP might prevent Purkinje cell loss. We did not see a beneficial effect. This suggests, in contrast to the expectations, that the relative lack of GGPP may not significantly contribute to mechanisms of Purkinje cell loss in NPC1.
Ultrasensitive enzyme immunoassay method for the measurement of rat brain-type creatine kinase BB (CK-BB) was developed by use of purified antibodies specific to the B subunit of creatine kinase. The antibody immunoglobulin G was purified with immunoaffinity chromatography of the antiserum raised in rabbits by injecting the purified rat CK-BB. The assay system consisted of polystyrene balls with immobilized antibody F(ab')2 fragments and the same antibody Fab' fragments labeled with beta-D-galactosidase from Escherichia coli. The assay was specific to the B subunit of CK (CK-B), showing about 10% cross-reactivity with CK-MB, but it did not cross-react with CK-MM and neuron-specific gamma gamma enolase. The minimum detection limit of the assay was 0.1 pg or 1 amol CK-BB, being sufficiently sensitive for the measurement of CK-B contents in the isolated Purkinje cell bodies at the level of single cells. The average content of CK-B in a single Purkinje cell was 1.64 pg. The CK-B concentration in rat cerebellum (about 22 micrograms/mg protein) was about twofold higher than that (about 13 micrograms/mg protein) in the cerebrum. High levels (greater than 5 micrograms/mg protein) of CK-B were also found in the peripheral tissues such as gastrointestinal tract and urinary bladder, all of which are composed of smooth muscle. Immunohistochemical localization of CK-B antigens in the CNS revealed that the antigens is distributed not only in the neurons but also in the glial cells. 相似文献
Pyramidal cells in the electrosensory lateral line lobe (ELL) of weakly electric fish have been observed to produce high-frequency burst discharge with constant depolarizing current (Turner et al., 1994). We present a two-compartment model of an ELL pyramidal cell that produces burst discharges similar to those seen in experiments. The burst mechanism involves a slowly changing interaction between the somatic and dendritic action potentials. Burst termination occurs when the trajectory of the system is reinjected in phase space near the ghost of a saddle-node bifurcation of fixed points. The burst trajectory reinjection is studied using quasi-static bifurcation theory, that shows a period doubling transition in the fast subsystem as the cause of burst termination. As the applied depolarization is increased, the model exhibits first resting, then tonic firing, and finally chaotic bursting behavior, in contrast with many other burst models. The transition between tonic firing and burst firing is due to a saddle-node bifurcation of limit cycles. Analysis of this bifurcation shows that the route to chaos in these neurons is type I intermittency, and we present experimental analysis of ELL pyramidal cell burst trains that support this model prediction. By varying parameters in a way that changes the positions of both saddle-node bifurcations in parameter space, we produce a wide gallery of burst patterns, which span a significant range of burst time scales. 相似文献
We use a mathematical model to investigate how climbing fiber-dependent plasticity at granule cell to Purkinje cell (grPkj) synapses in the cerebellar cortex is influenced by the synaptic organization of the cerebellar-olivary system. Based on empirical studies, grPkj synapses are assumed to decrease in strength when active during a climbing fiber input (LTD) and increase in strength when active without a climbing fiber input (LTP). Results suggest that the inhibition of climbing fibers by cerebellar output combines with LTD/P to self-regulate spontaneous climbing fiber activity to an equilibrium level at which LTP and LTD balance and the expected net change in grPkj synaptic weights is zero. The synaptic weight vector is asymptotically confined to an equilibrium hyperplane defining the set of all possible combinations of synaptic weights consistent with climbing fiber equilibrium. Results also suggest restrictions on LTP/D at grPkj synapses required to produce synaptic weights that do not drift spontaneously. 相似文献
Abstract. To determine whether the p75 neurotrophin receptor (p75NTR) plays a role in naturally occurring neuronal death, we examined neonatal sympathetic neurons that express both the TrkA tyrosine kinase receptor and p75NTR. When sympathetic neuron survival is maintained with low quantities of NGF or KCl, the neurotrophin brain-derived neurotrophic factor (BDNF), which does not activate Trk receptors on sympathetic neurons, causes neuronal apoptosis and increased phosphorylation of c-jun. Function-blocking antibody studies indicate that this apoptosis is due to BDNF-mediated activation of p75NTR. To determine the physiological relevance of these culture findings, we examined sympathetic neurons in BDNF−/− and p75NTR−/− mice. In BDNF−/− mice, sympathetic neuron number is increased relative to BDNF+/+ littermates, and in p75NTR−/− mice, the normal period of sympathetic neuron death does not occur, with neuronal attrition occurring later in life. This deficit in apoptosis is intrinsic to sympathetic neurons, since cultured p75NTR−/− neurons die more slowly than do their wild-type counterparts. Together, these data indicate that p75NTR can signal to mediate apoptosis, and that this mechanism is essential for naturally occurring sympathetic neuron death. 相似文献
To study the behaviour of a living cell exposed to radiations we investigate a stochastic model, employing for its analysis the theory of semi-Markov and Markov renewal processes. Four states of the cell namely, normal state, damaged state 1, damaged state 2 and altered state are defined and various characteristics of interest pertaining to the cell behaviour are studied. 相似文献
Lymph nodes are meeting points for circulating immune cells. A network of reticular cells that ensheathe a mesh of collagen fibers crisscrosses the tissue in each lymph node. This reticular cell network distributes key molecules and provides a structure for immune cells to move around on. During infections, the network can suffer damage. A new study has now investigated the network’s structure in detail, using methods from graph theory. The study showed that the network is remarkably robust to damage: it can still support immune responses even when half of the reticular cells are destroyed. This is a further important example of how network connectivity achieves tolerance to failure, a property shared with other important biological and nonbiological networks.Lymph nodes are critical sites for immune cells to connect, exchange information, and initiate responses to foreign invaders. More than 90% of the cells in each lymph node—the T and B lymphocytes of the adaptive immune system—only reside there temporarily and are constantly moving around as they search for foreign substances (antigen). When there is no infection, T and B cells migrate within distinct regions. But lymph node architecture changes dramatically when antigen is found, and an immune response is mounted. New blood vessels grow and recruit vast numbers of lymphocytes from the blood circulation. Antigen-specific cells divide and mature into “effector” immune cells. The combination of these two processes—increased influx of cells from outside and proliferation within—can make a lymph node grow 10-fold within only a few days [1]. Accordingly, the structural backbone supporting lymph node function cannot be too rigid; otherwise, it would impede this rapid organ expansion. This structural backbone is provided by a network of fibroblastic reticular cells (FRCs) [2], which secrete a form of collagen (type III alpha 1) that produces reticular fibers—thin, threadlike structures with a diameter of less than 1 μm. Reticular fibers cross-link and form a spider web–like structure. The FRCs surrounding this structure form the reticular cell network (Fig 1), which was first observed in the 1930s [3]. Interestingly, experiments in which the FRCs were destroyed showed that the collagen fiber network remained intact [4].Open in a separate windowFig 1Structure of the reticular cell network.The reticular cell network is formed by fibroblastic reticular cells (FRCs) whose cell membranes ensheathe a core of collagen fibers that acts as a conduit system for the distribution of small molecules [5]. In most other tissues, collagen fibers instead reside outside cell membranes, where they form the extracellular matrix. Inset: graph structure representing the FRCs in the depicted network as “nodes” (circles) and the direct connections between them as “edges” (lines). Shape and length of the fibers are not represented in the graph.Reticular cell networks do not only support lymph node structure; they are also important players in the immune response. Small molecules from the tissue environment or from pathogens, such as viral protein fragments, can be distributed within the lymph node through the conduit system formed by the reticular fibers [5]. Some cytokines and chemokines that are vital for effective T cell migration—and the nitric oxide that inhibits T cell proliferation [6]—are even produced by the FRCs themselves. Moreover, the network is thought of as a “road system” for lymphocyte migration [7]: in 2006, a seminal study found that lymphocytes roaming through lymph nodes were in contact with network fibers most of the time [8]. A few years before, it had become possible to observe lymphocyte migration in vivo by means of two-photon microscopy [9]. Movies from these experiments strikingly demonstrated that individual cells were taking very different paths, engaging in what appeared to be a “random walk.” But these movies did not show the structures surrounding the migrating cells, which created an impression of motion in empty space. Appreciating the role of the reticular cell network in this pattern of motion [8] suggested that the complex cell trajectories reflect the architecture of the network along which the cells walk.Given its important functions, it is surprising how little we know about the structure of the reticular cell network—compared to, for instance, our wealth of knowledge on neuron connectivity in the brain. In part this is because the reticular cells are hard to visualize. In vivo techniques like two-photon imaging do not provide sufficient resolution to reliably capture the fine-threaded mesh. Instead, thin tissue sections are stained with fluorescent antibodies that bind to the reticular fibers and are imaged with high-resolution confocal microscopy to reveal the network structure. One study [10] applied this method to determine basic parameters such as branch length and the size of gaps between fibers. Here, we discuss a recent study by Novkovic et al. [11] that took a different approach to investigating properties of the reticular cell network structure: they applied methods from graph theory.Graph theory is a classic subject in mathematics that is often traced back to Leonhard Euler’s stroll through 18th-century Königsberg, Prussia. Euler could not find a circular route that crossed each of the city’s seven bridges exactly once, and wondered how he could prove that such a route does not exist. He realized that this problem could be phrased in terms of a simple diagram containing points (parts of the city) and lines between them (bridges). Further detail, such as the layout of city’s streets, was irrelevant. This was the birth of graph theory—the study of objects consisting of points (nodes) connected by lines (edges). Graph theory has diverse applications ranging from logistics to molecular biology. Since the beginning of this century, there has been a strong interest in applying graph theory to understand the structure of networks that occur in nature—including biological networks, such as neurons in the brain, and more recently, social networks like friendships on Facebook. Various mathematical models of network structures have been developed in an attempt to understand network properties that are relevant in different contexts, such as the speed at which information spreads or the amount of damage that a network can tolerate before breaking into disconnected parts. Three well-known network topologies are random, small-world, and scale-free networks (Box 1). Novkovic et al. modeled reticular cell networks as graphs by considering each FRC to be a node and the fiber connections between FRCs to be edges (Fig 1).
Box 1. Graph Theory and the Robustness of Real Networks
After the publication of several landmark papers on network topology at the end of the previous century, the science of complex networks has grown explosively. One of these papers described “small-world” networks [16] and demonstrated that several natural networks have the amazing property that the average length of shortest paths between arbitrary nodes is unexpectedly small (making it a “small world”), even if most of the network nodes are clustered (that is, when neighbors of neighbors tend to be neighbors). The Barabasi group published a series of papers describing “scale-free” networks [17,18] and demonstrated that scale-free networks are extremely robust to random deletions of nodes—the vast majority of the nodes can be deleted before the network falls apart [15]. In scale-free networks, the number of edges per node is distributed according to a power law, implying that most nodes have very few connections, and a few nodes are hubs having very many connections. Thus, the topology of complex networks can be scale-free, small-world, or neither, such as with random networks [19]. Novkovic et al. [11] describe the clustering of the edges of neighbors and the average shortest path–length between arbitrary nodes, finding that reticular cell networks have small-world properties. Whether or not these networks have scale-free properties is not explicitly examined in the paper, but given that they are embedded in a three-dimensional space, that they “already” lose functionality when about 50% of the FRCs are ablated, and that the number of connected protrusions per FRC is not distributed according to a power law (see the data underlying their Figure 2g), reticular cell networks are not likely to be scale-free. Thus, the enhanced robustness of reticular cell networks is most likely due to their high local connectivity: Networks lose functionality when they fall apart in disconnected components, and high clustering means that the graph is unlikely to split apart when a single node is removed, because the neighbors of that node tend to stay connected [14]. Additionally, since the reticular cell network has a spatial structure (unlike the internet or the Facebook social network), its high degree of clustering is probably due to the preferential attachment to nearby FRCs when the network develops, which agrees well with Novkovic et al.’s recent classification as a small-world network with lattice-like properties [11].Some virus infections are known to damage reticular cell networks [12], either through infection of the FRCs or as a bystander effect of inflammation. It is therefore important to understand to what extent the network structure is able to survive partial destruction. Novkovic et al. first approached this question by performing computer simulations, in which they randomly removed FRC nodes from the networks they had reconstructed from microscopy images. They found that they had to remove at least half of the nodes to break the network apart into disconnected parts. To study the effect of damage on the reticular cell network in vivo rather than in silico, Novkovic et al. used an experimental technique called conditional cell ablation. In this technique, a gene encoding the diphtheria toxin receptor (DTR) is inserted after a specific promoter that leads it to be expressed in a particular cell type of interest. Administration of diphtheria toxin kills DTR-expressing cells, leaving other cells unaffected. By expressing DTR under the control of the FRC-specific Ccl19 promoter, Novkovic et al. were able to selectively destroy the reticular cell network and then watch it grow back over time. Regrowth took about four weeks, and the resulting network properties were no different from a network formed naturally during development. Thus, it seems that the reticular cell network structure is imprinted and reemerges even after severe damage. This finding ties in nicely with previous data from the same group [13], showing that reticular cell networks form even in the absence of lymphotoxin-beta receptor, an otherwise key player in many aspects of lymphoid tissue development. Together, these data make a compelling case that network formation is a robust fundamental trait of FRCs.Next, Novkovic et al. varied the dose of diphtheria toxin such that only a fraction of FRCs were destroyed, effectively removing a random subset of the network nodes. They measured in two ways how FRC loss affects the immune system: they tracked T cell migration using two-photon microscopy and they determined the amount of antiviral T cells produced by the mice after an infection. Remarkably, as predicted by their computer simulations, lymph nodes appeared capable of tolerating the loss of up to half of FRCs with little effect on either T cell migration or the numbers of activated antiviral T cells. Only when more than half of the FRCs were destroyed did T cell motion slow down significantly and the mice were no longer able to mount effective antiviral immune responses. Such a tolerance of damage is impressive—for comparison, consider what would happen if one were to close half of London’s subway stations!Robustness to damage is of interest for many different networks, from power grids to the internet [14]. In particular, the “scale-free” architecture that features rare, strongly connected “hub” nodes is highly robust to random damage [15]. Novkovic et al. did not address whether the reticular cell network is scale-free, but it is likely that it isn’t (Box 1). Instead, the network’s robustness probably arises from its high degree of clustering, which means that the neighbors of each node are likely to be themselves also neighbors. If a node is removed from a clustered network, then there is still likely a short detour available by going through two of the neighbors. Therefore, one would have to randomly remove a large fraction of the nodes before the network structure breaks down. High clustering in the network could be a consequence of the fact that multiple fibers extend from each FRC and establish connections to many FRCs in its vicinity. A question not yet addressed by Novkovic et al. is how robust reticular cell networks would be to nonrandom damage, such as a locally spreading viral infection. In fact, scale-free networks are drastically more vulnerable to targeted rather than random damage: the United States flight network can come to a grinding halt by closing a few hub airports [15]. Less is known about the robustness to nonrandom damage for other network architectures, and the findings by Novkovic et al. motivate future research in this direction.Novkovic et al. did not yet explicitly identify all mechanisms that hamper T cell responses when more than half of the FRCs are depleted. But given the reticular cell network’s many different functions, this could occur in several ways. For instance, severe depletion might prevent the secretion of important molecules, halt the migration of T cells, prevent the anchoring of antigen-presenting dendritic cells (DCs) on the network, or cause structural disarray in the tissue. In addition to the effects on T cell migration, Novkovic et al. also showed that the amount of DCs in fact decreased when FRCs were depleted, emphasizing that several mechanisms are likely at play. Disentangling these mechanisms will require substantial additional research efforts.The current reticular cell network reconstruction by Novkovic et al. is based on thin tissue slices. It will be exciting to study the network architecture when it can be visualized in the whole organ. Some aspects of the network may then look different. For instance, those FRCs that are near the border of a slice will have their degree of connectivity underestimated, as not all of their neighbors in the network can be seen. Further refinements of the network analysis may also consider that reticular fibers are real physical objects situated in a three-dimensional space (unlike abstract connections such as friendships). Migrating T cells may travel quicker via a short, straight fiber than on a long, curved one, but the network graph does not make this distinction. More generally, it would be interesting to understand conceptually how reticular cell networks help foster immune cell migration. While at first it appears obvious that having a “road system” should make it easier for cells to roam lymph node tissue, three different theoretical studies have in fact all concluded that effective T cell migration should also be possible in the absence of a network [20–22]. A related question is whether T cells are constrained to move only on the network or are merely using it for loose guidance. For instance, could migrating T cells be in contact with two or more network fibers at once or with none at all? This would make the relationship between cell migration and network structure more complex than the graph structure alone suggests.There is also some evidence that T cells can migrate according to what is called a Lévy walk [23]—a kind of random walk where frequent short steps are interspersed with few very long steps, a search strategy that appears to occur frequently in nature (though this is debated [24]). While there is so far no evidence that T cells perform a Lévy walk when roaming the lymph node [25], this may be in part due to limitations of two-photon imaging, and one could speculate that reticular cell networks might in fact be constructed in a way that facilitates this or another efficient kind of “search strategy.” Resolving this question will require substantial improvements in imaging technology, allowing individual T cells to be tracked across an entire lymph node.No doubt further studies will address these and other questions, and provide further insights on how reticular cell networks benefit immune responses. Such advances may help us design better treatments against infections that damage the network. It may also help us understand how we can best administer vaccines or tumor immune therapy treatments in a way that ensures optimal delivery to immune cells in the lymph node. As is nicely illustrated by the study of Novkovic et al., mathematical methods may well play key roles in this quest. 相似文献
下载免费PDF全文