10 research outputs found

    Hair cell maturation is differentially regulated along the tonotopic axis of the mammalian cochlea

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    Sound amplification within the mammalian cochlea depends upon specialized hair cells, the outer hair cells (OHCs), which possess both sensory and motile capabilities. In various altricial rodents, OHCs become functionally competent from around postnatal day 7 (P7), before the primary sensory inner hair cells (IHCs), which become competent at about the onset of hearing (P12). The mechanisms responsible for the maturation of OHCs and their synaptic specialization remain poorly understood. We report that spontaneous Ca2+ activity in the immature cochlea, which is generated by CaV1.3 Ca2+ channels, differentially regulates the maturation of hair cells along the cochlea. Under near‐physiological recording conditions we found that, similar to IHCs, immature OHCs elicited spontaneous Ca2+ action potentials (APs), but only during the first few postnatal days. Genetic ablation of these APs in vivo, using CaV1.3−/− mice, prevented the normal developmental acquisition of mature‐like basolateral membrane currents in low‐frequency (apical) hair cells, such as IK,n (carried by KCNQ4 channels), ISK2 and IACh (α9α10nAChRs) in OHCs and IK,n and IK,f (BK channels) in IHCs. Electromotility and prestin expression in OHCs were normal in CaV1.3−/− mice. The maturation of high‐frequency (basal) hair cells was also affected in CaV1.3−/− mice, but to a much lesser extent than apical cells. However, a characteristic feature in CaV1.3−/− mice was the reduced hair cell size irrespective of their cochlear location. We conclude that the development of low‐ and high‐frequency hair cells is differentially regulated during development, with apical cells being more strongly dependent on experience‐independent Ca2+ APs

    Geniculo-Cortical Projection Diversity Revealed within the Mouse Visual Thalamus.

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    The mouse dorsal lateral geniculate nucleus (dLGN) is an intermediary between retina and primary visual cortex (V1). Recent investigations are beginning to reveal regional complexity in mouse dLGN. Using local injections of retrograde tracers into V1 of adult and neonatal mice, we examined the developing organisation of geniculate projection columns: the population of dLGN-V1 projection neurons that converge in cortex. Serial sectioning of the dLGN enabled the distribution of labelled projection neurons to be reconstructed and collated within a common standardised space. This enabled us to determine: the organisation of cells within the dLGN-V1 projection columns; their internal organisation (topology); and their order relative to V1 (topography). Here, we report parameters of projection columns that are highly variable in young animals and refined in the adult, exhibiting profiles consistent with shell and core zones of the dLGN. Additionally, such profiles are disrupted in adult animals with reduced correlated spontaneous activity during development. Assessing the variability between groups with partial least squares regression suggests that 4-6 cryptic lamina may exist along the length of the projection column. Our findings further spotlight the diversity of the mouse dLGN--an increasingly important model system for understanding the pre-cortical organisation and processing of visual information. Furthermore, our approach of using standardised spaces and pooling information across many animals will enhance future functional studies of the dLGN.Funding was provided by a Wellcome Trust grant jointly awarded to IDT and SJE (083205, www.wellcome.ac.uk), and by MRC PhD Studentships awarded to MNL and ACH (http://www.mrc.ac.uk/).This is the final version of the article. It was first available from PLOS via http://dx.doi.org/10.1371/journal.pone.014484

    Coordinated calcium signalling in cochlear sensory and non‐sensory cells refines afferent innervation of outer hair cells

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    Outer hair cells (OHCs) are highly specialized sensory cells conferring the fine‐tuning and high sensitivity of the mammalian cochlea to acoustic stimuli. Here, by genetically manipulating spontaneous Ca2+ signalling in mice in vivo, through a period of early postnatal development, we find that the refinement of OHC afferent innervation is regulated by complementary spontaneous Ca2+ signals originating in OHCs and non‐sensory cells. OHCs fire spontaneous Ca2+ action potentials during a narrow period of neonatal development. Simultaneously, waves of Ca2+ activity in the non‐sensory cells of the greater epithelial ridge cause, via ATP‐induced activation of P2X3 receptors, the increase and synchronization of the Ca2+ activity in nearby OHCs. This synchronization is required for the refinement of their immature afferent innervation. In the absence of connexin channels, Ca2+ waves are impaired, leading to a reduction in the number of ribbon synapses and afferent fibres on OHCs. We propose that the correct maturation of the afferent connectivity of OHCs requires experience‐independent Ca2+ signals from sensory and non‐sensory cells

    Axon guidance in the developing ocular motor system and Duane retraction syndrome depends on Semaphorin signaling via alpha2-chimaerin

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    Eye movements depend on correct patterns of connectivity between cranial motor axons and the extraocular muscles. Despite the clinical importance of the ocular motor system, little is known of the molecular mechanisms underlying its development. We have recently shown that mutations in the Chimaerin-1 gene encoding the signaling protein α2-chimaerin (α2-chn) perturb axon guidance in the ocular motor system and lead to the human eye movement disorder, Duane retraction syndrome (DRS). The axon guidance cues that lie upstream of α2-chn are unknown; here we identify candidates to be the Semaphorins (Sema) 3A and 3C, acting via the PlexinA receptors. Sema3A/C are expressed in and around the developing extraocular muscles and cause growth cone collapse of oculomotor neurons in vitro. Furthermore, RNAi knockdown of α2-chn or PlexinAs in oculomotor neurons abrogates Sema3A/C-dependent growth cone collapse. In vivo knockdown of endogenous PlexinAs or α2-chn function results in stereotypical oculomotor axon guidance defects, which are reminiscent of DRS, whereas expression of α2-chn gain-of-function constructs can rescue PlexinA loss of function. These data suggest that α2-chn mediates Sema3–PlexinA repellent signaling. We further show that α2-chn is required for oculomotor neurons to respond to CXCL12 and hepatocyte growth factor (HGF), which are growth promoting and chemoattractant during oculomotor axon guidance. α2-chn is therefore a potential integrator of different types of guidance information to orchestrate ocular motor pathfinding. DRS phenotypes can result from incorrect regulation of this signaling pathway

    Three dimensional reconstruction of dLGN-to-V1 projection columns.

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    <p>(A) Fluorescent <i>RetroBeads</i> were injected into V1 and transported into thalamo-cortical projection neurons within the dLGN. (B) Bright-field images of sections registered to 3D standardized space (MRI). Cross-hairs are colour-coded for each orthogonal view. Yellow dashed lines outline the boundary of the dLGN. (C) Reconstructed locations of labelled somas within the boundaries of the standardized dLGN space (mesh). Left inset: summarised trajectory of the dLGN projection column that extends from the pial surface (⭕) to the ventral boundary of the dLGN (●). Right inset: spread of cells along normalised columns (based on boundary positions: ⭕->●). Scale bars are 250ÎŒm.</p

    PLS Regression Suggests Complex Cryptic Organisation.

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    <p>(A) Normalised profiles (zero mean and unit variance) representing the numbers of cells; spread of cells and normalised P<sub>t</sub> representing topological and topographical order for all groups (WT, P6, P12 and ÎČ2<sup>-/-</sup>). Colour coding is arbitrary except that the ÎČ2<sup>-/-</sup> group are dashed lines. (B) PLS regression; the degree of variance within A is increasingly explained by an increasing number of latents. Curves represent the explained variance for the combined WT, P6 and P12 groups (solid line) and all groups combined together (dashed). (C) Cross-validation error (Mean Squared Error—MSE) as a function of the number of latents retained in the model. WT, P6 and P12 groups (solid line) and all groups (dashed).</p

    Dynamic Topological and Topographical Order in Geniculo-Cortical Projection Columns.

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    <p>Generating maps of dLGN columns for each 5<sup>th</sup> percentile along its length enables estimations of organisation and order. (A) Example of a best-fit plane (normal vector: blue-line) for WT projection columns at 10<sup>th</sup> percentile (0.1) position. Inset: collapsed view orthogonal to the plane–end on normal vector. Scale bar is 100ÎŒm. (B) Example of registration (expansion—E; rotation - Ξ) between neighbouring (0.1 and 0.05) WT planes. (C) Cumulative rotation and (D) expansion of each 5<sup>th</sup> percentile map aligned to the pial plane (0). (E) Internal topological order within each group compared to the preceding 5<sup>th</sup> percentile position. Note, a normalised P<sub>t</sub> of 1 represents complete disorder while 0 is perfect order. (F) Degree of topological order between the pial and ventral maps of the dLGN. Monte Carlo permutation tests: * (p<0.05)—statistically significant order. (G) Schematic: correspondence of WT V1 injection sites to dLGN pial plane (0). (H) Degree of topographical order between V1 and the dLGN at each 5<sup>th</sup> percentile. Monte Carlo permutation tests: * (p<0.05)—statistically significant order.</p

    Form and Features of dLGN-V1 Projection Columns.

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    <p>(A-D) Location of V1 injections (mm relative to Lambda) and positions of the labelled column on the pial surface (scale bar 200ÎŒm) for four groups: Adult Wild Type (WT), n = 16; Adult ÎČ2<sup>-/-</sup>, n = 9; P6 WT, n = 14, P12 WT, n = 13. Coordinates are relative to lambda. (E-G) Reconstructed paths of dLGN-V1 projection columns collapsed onto coronal (E), horizontal (F), and sagittal (G). Columns extend from the pial surface (⭕) to the ventral boundary of the dLGN (●). (H) Distribution of injection volumes in each group, Kruskal Wallis test, with Dunn’s Multiple Comparison Post Hoc Tests, *p<0.05, ** p<0.01. (I) Column lengths. (J) Number of cells per column. (I & J) One-way ANOVA with Bonferroni post-hoc tests: * p<0.05; ** p<0.01; *** p<0.001. (K) Number of cells per 5<sup>th</sup> percentile of unit column. Data presented as mean ±SEM. Grey shading in this and subsequent figures indicate the shell core boundary at approximately 30% of the projection column. Two-way ANOVA with Bonferroni post-hoc tests relative to pial end: *** p<0.001. (L) Spread of cells from the centre of mass of each column per 5<sup>th</sup> percentile. Data presented as mean ±SEM. Values are corrected for different sized dLGNs by scaling to the WT dLGN. (M) Cumulative histogram illustrating the numbers of cells of a given spread (see L). Kruskal Wallis test, with Dunn’s Multiple Comparison Post-hoc tests compared to WT: ** p<0.01. (N) Fitted Rayleigh distributions to cumulative data in M, normalised to the area under each curve.</p
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