Attempts to find the causality: Genes associated with Intellectual Disabilities; SORBS2, new molecular player regulates dendritic growth and its complexity.

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Dendrites can perform a gamut of operations, which involves sub-linear summation of inputs by filtering of synaptic inputs in a passive mode whilst generating supralinear spikes during active mode of information processing, there by acting as basic logical operation units (AND, OR, AND-NOT) to calculate complex operation on the incoming signals. Dendrite branching pattern and the dendritic field are involved in the normal functioning of many physiological processes. For instance, bi-tufted neurons modulate the temporal difference between sound input(Agmon-Snir et al., 1998). Amacrine cells and tangential cells confer directional selectivity by computing the direction of motion(Borst et al., 2010). Mitral cells with their functionally distinct apical and lateral dendrite use this particular organization for the specific processing of odor information and for odor discrimination(Dhawale et al., 2010). The area covered by the dendritic branching pattern governs the extent of the inputs the neuron can receive and compute, while the complexity of the branching of the dendrite determines its specialized task as mentioned in the examples above. The geometry of the dendritic branches, the number of synaptic sites, the distribution of different types of spines on the dendritic branches, the distribution of different voltage gated channels, and the history of the previous synaptic activity are all factors that determine how the dendrites integrate the incoming information, that the cell receives from multiple inputs spanning across the dendritic branches. Dendritic spines are the protrusions emanating from the dendritic shaft and they act as a specialized compartment for receiving the inputs from the boutons. With such a structured pattern all around the dendritic trees, spine enables the increase in connectivity, integrating the inputs and regulating the plasticity of specific inputs in a distributed circuit model (Yuste, 2011). Spines are rich with actin filaments and actin plays a prominent role in the growth and the shrinkage of spines by remodeling the cytoskeleton(Matus, 2000). Molecules such as Ca2+ regulate the actin dynamics in spines during synaptic activity via opening of NMDA receptors thereby in fluxing Ca2+ in the dendritic spines (Sabatini et al., 2001). Matsuzaki et al, provided evidence that spines obey hebbian plasticity. At the level of single synapses, input specific strong activation such as LTP (Long-term potentiation) creates rapid enlargement of small-stimulated spines that persist for longer time (Matsuzaki et al., 2004). It has been widely speculated that the variance in the size and the volume can be positively correlated with the strength of the synapses though this has not been still resolved very clearly.

Genome wide association studies, comparative genomics, transcriptome analysis, quantitative trait loci mapping studies combined with rigorous statistical and computational methods are helping us in gleaning information about cognitive disorders. SORBS2 gene is linked to intellectual disability in human patients (My blog on how Genome wide association studies and next generation sequencing helping us in understanding to translate genes to neurocognitive diseases, http://www.malikyousuf.com/nature-and-nurture-both-owns-zombies-in-the-brain-my-take-on-neurocognitive-disorders-such-as-autism-schizophrenia-etc-and-googles-foray-into-mental-disorders/ ) Guoping Feng and colleagues had now shown that the neuronal isoform of SORBS2 called nArgBP2 (For ease of reading, I will call nArgBP2 as SORBS2) is localized at the dendritic spines of the excitatory synapses but not at the inhibitory(Zhang et al., 2016). The spine localization of SORBS2 depends on the presence of the neuronal specific exon (NSE), as the deletion of NSE causes its relocalization to the dendritic shaft as well as in the soma. SORBS2 is highly localized in the cortex, amygdala and in the dentate gyrus, specifically they found an enriched expression of the protein in the dendrites in the outer molecular layer, which is preferentially innervated by axons from lateral entorhinal cortex. Sholl analysis in SORBS2 knock – out mice revealed a decrease in dendritic complexity as well as a reduction in the number of branch points. This is also functionally reflected in the decrease in the number of functional synapses as measured by the decrease in miniature EPSC ((Excitatory Postsynaptic current) frequency. Translating the morphological and functional changes to behavioural responses, the authors had performed a series of experiments, where they had concluded that the knock –out mice have defects in long-term object recognition but not the short-term. Moreover they also observed defects in contextual fear conditioning but not in toned test, thereby, drawing the conclusion that only specific form of learning and memory is compromised in the mutant. Taken together this work has shown the role of SORBS2 in regulating the dendritic development and its functional consequence in learning and memory tasks however this work posits interesting questions that need to be addressed in the future.

Outstanding Questions remain to be answered?

1) Does the recruitment of SORBS2 to the dendritic spines is regulated by activity? Inducing Chemical LTP experiments with glycine (Lu et al., 2001) in dissociated neuronal cultures will be able to address this question. 2) How are they been recruited from the shaft and from the cell body to the spines? 3) Is there an enrichment of SORBS2 in potentiated spines? 4) What is the turn over of SORBS2 in the potentiated spines? 5) How does the actin dynamics as well as the turnover of actin changes in the spines of wild type and in the knockout model of SORBS2? Given the NSE region is important for the localization of SORBS2 to the spines, 6) what are the effectors binding to this region for their recruitment to the spines? 7) Does the reduced dendritic complexity, total length as well as the branch points phenotypes seen in dentate gyrus also holds true in other regions such as cortex, amygdala as SORBS2 is highly enriched in the above mentioned regions? Sholl analysis measured the extent of dendritic complexity and dendritic arborization. The geometry of the dendritic branching pattern (e.g. the number of branches or the branching points plays a pivotal role in the propagation of action potentials in both forward and backward directions(Hausser et al., 2000) . Decrease in the number of Sholl intersections and decrease in the number of branch points in the mutant might change the computational properties of the network, where the neuron is part. This is interesting in the light of the finding that SORBS2 is highly enriched in layer I – III of the neocortex and in the layer I of the piriform cortex. Recently, it has been shown that the apical tufts in the layer 1 produced dendritic spikes by back propagating action potential thereby rendering a non-linear integration of signal processing during an active task (Xu et al., 2012). One of the interesting question that came out from this studies will be 8) whether the dendritic complexity as well as dendrite length has been changed in the pyramidal neurons in the upper later of the cortex? 9) If so, how would they be affecting the functional properties of these neurons? Physiological experiments will further help in understanding in detail some key questions such as to 10) what extent does the dendritic excitability of the pyramidal neurons in the mutant contribute to plasticity, input integration and computation of information in neural networks? 11) What’s the measure or magnitude of the forward and backward propagation of EPSPs (Excitatory Postsynaptic Potential) and APs (Action Potential) invading the soma and dendrites, respectively, in the mutant? 12) To what extent does the linear and non – linear summation happen during dendritic spiking? 13) How ion channels on the dendrites in the mutant is adjusted to the altered length of dendrites in comparison to wild type mice? It is very plausible that the connectivity matrix/ axon arborization of SORBS2 mouse mice is changed and the integration of synaptic input changing the matrix of synaptic weight will be different from wild type mice. This will be an interesting proposition to test.

From a developmental neuroscience perspective, this work has shown that SORBS2 mutant has a reduced dendritic growth and they are involved in dendritogenesis. This raises some interesting questions with regard to the molecular function of SORBS2 in dendritogenesis. 14) To what extent is the tiling and scaling of dendrites affected in the mutant in comparison to wild type? 15) Which key molecules and what signaling pathway is perturbed in the mutant so that the growth of the dendrite, it’s scaling, and its maintenance is affected? Another interesting question that emanates from this study is 16) whether the decrease in the dendrite complexity and reduced dendrite growth as observed by the decrease in the dendritic length is due to the effect of SORBS2 during developmental stages or in the later stages where SORBS2 is needed for the maintenance of the dendritic tree? In this scenario, it will also be very important to understand how regulators of actin such as the Rho family of GTPases are acting on the growth and the maintenance of dendritic branches in the mutant (Lee et al., 2003, Scott et al., 2003).

The discovery of the function of SORBS2 in regulating dendritic complexity and the knock-out models showing learning and memory deficit shall be refined to understand the causality of the role of SORBS2 in intellectual disability. Experiments understanding the pathways upstream as well as downstream of SORBS2 combining with physiological and anatomical approaches such as the connectomics will not only helps in refining our understanding of the function of this protein but also prove the causality of the link of SORBS2 to intellectual disability.

p.s: The pictures are taken from Google images.

References:

Agmon-Snir H, Carr CE, Rinzel J (1998) The role of dendrites in auditory coincidence detection. Nature 393:268-272.

Borst A, Haag J, Reiff DF (2010) Fly motion vision. Annual review of neuroscience 33:49-70.

Dhawale AK, Hagiwara A, Bhalla US, Murthy VN, Albeanu DF (2010) Non-redundant odor coding by sister mitral cells revealed by light addressable glomeruli in the mouse. Nature neuroscience 13:1404-1412.

Hausser M, Spruston N, Stuart GJ (2000) Diversity and dynamics of dendritic signaling. Science (New York, NY) 290:739-744.

Lee A, Li W, Xu K, Bogert BA, Su K, Gao FB (2003) Control of dendritic development by the Drosophila fragile X-related gene involves the small GTPase Rac1. Development (Cambridge, England) 130:5543-5552.

Lu W, Man H, Ju W, Trimble WS, MacDonald JF, Wang YT (2001) Activation of synaptic NMDA receptors induces membrane insertion of new AMPA receptors and LTP in cultured hippocampal neurons. Neuron 29:243-254.

Matsuzaki M, Honkura N, Ellis-Davies GC, Kasai H (2004) Structural basis of long-term potentiation in single dendritic spines. Nature 429:761-766.

Matus A (2000) Actin-based plasticity in dendritic spines. Science (New York, NY) 290:754-758.

Sabatini BL, Maravall M, Svoboda K (2001) Ca (2+) signaling in dendritic spines. Current opinion in neurobiology 11:349-356.

Scott EK, Reuter JE, Luo L (2003) Small GTPase Cdc42 is required for multiple aspects of dendritic morphogenesis. The Journal of neuroscience: the official journal of the Society for Neuroscience 23:3118-3123.

Xu NL, Harnett MT, Williams SR, Huber D, O’Connor DH, Svoboda K, Magee JC (2012) Nonlinear dendritic integration of sensory and motor input during an active sensing task. Nature 492:247-251.

Yuste R (2011) Dendritic spines and distributed circuits. Neuron 71:772-781.

Zhang Q, Gao X, Li C, Feliciano C, Wang D, Zhou D, Mei Y, Monteiro P, Anand M, Itohara S, Dong X, Fu Z, Feng G (2016) Impaired Dendritic Development and Memory in Sorbs2 Knock-Out Mice. The Journal of neuroscience: the official journal of the Society for Neuroscience 36:2247-2260.

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