Multilevel Analysis of Cortical Interneuron Dysfunction in Fragile X Syndrome

项目概要： 脆性X综合征（FXS）是一种常见的遗传性智力残疾， 有类似自闭症的临床特征它是由FMR 1基因的表观遗传沉默引起的，该基因编码 蛋白质FMRP是一种RNA结合蛋白，对突触中重要的mRNA具有强烈偏好 结构和功能。事实上，在这两个人类患者身上都观察到了有据可查的突触缺陷。 以及FXS小鼠模型（Fmr 1敲除）。在兴奋性锥体神经元中， 已经有很好的描述，但对剩下的20%的皮层神经元，抑制性皮层神经元， interneurons，in FXS.由于中间神经元功能障碍与精神分裂症以及 ASD，他们是一个有吸引力的细胞群体，在FXS的背景下研究。我们的中心假设是， 皮质中间神经元功能障碍在FXS病因学中起重要作用， 可以在细胞类型、数量、分布和突触水平上揭示。在这份提案中，我们将 使用一些新的方法对Fmr 1-/-小鼠中的中间神经元进行多水平分析， 开发这项工作非常重要，因为人们对中间神经元的了解很少。 尽管FXS在其他神经发育障碍的病因学中具有重要性，但它在FXS的背景下仍然存在。工作 也是高度创新的，因为它带来了许多新的方法来挖掘中间神经元 FXS中的表型：中间神经元分布的详细空间分析和机器学习策略， 在个体和群体水平上检查中间神经元突触。首先，我们将使用自动分割- 心理状态和位置登记，以研究中间神经元亚型的数量，分层和皮质分布， 在Fmr 1-/-和对照中的作用。第二，我们将采用一种新的机器学习管道来测量跨 在Fmr 1突变体和对照中的神经元突触靶特异性。第三，我们将以类似于 单细胞RNA-seq主成分分析-通过多维分析单个突触结- 空间特征分析这使我们能够对中间神经元的合成进行无监督的聚类分析。 突触终扣和显示群体水平之间的差异Fmr 1-/-和控制突触。综合起来看， 我们的数据将为FXS病因学中研究不足的细胞群--皮质中间神经元--提供新的线索 并为研究FXS和ASD背后的突触缺陷开辟了新的途径。

PROJECT SUMMARY: Fragile X Syndrome (FXS) is a common genetic form of intellectual disability that is frequently co-morbid with autism-like clinical features. It is caused by epigenetic silencing of the FMR1 gene, which encodes for the protein FMRP, an RNA binding protein with a strong preference for mRNAs important in synaptic structure and function. Indeed, there are well-documented synaptic defects observed in both human patients and in the mouse model for FXS (Fmr1 knockout). In excitatory pyramidal neurons, these synaptic defects are well-described but much less is known about the remaining 20% of cortical neurons, inhibitory cortical interneurons, in FXS. Since interneuron dysfunction has been implicated in both schizophrenia as well as ASD, they are an appealing cell population to study in the context of FXS. Our Central Hypothesis is that cortical interneurons dysfunction plays an important role in FXS etiology and that interneuron phenotypes can be revealed at the cell type numbers, distribution and synaptic levels. In this proposal, we will conduct a multi-level analysis of interneurons in Fmr1-/- mice using a number of novel approaches that we recently developed. The proposed work is Highly Significant in that interneurons are poorly understood in the context of FXS despite their importance in the etiology of other neurodevelopmental disorders. The work is also Highly Innovative because it brings to bear a number of novel approaches to unearth interneuron phenotypes in FXS: detailed spatial analysis of interneuron distribution and machine learning strategies to examine interneurons synapses at the individual and population level. First, we will use automated seg- mentation and positional registration to study interneuron subtype numbers, layering and cortical distribu- tion in Fmr1-/- and controls. Second, we will employ a novel machine learning pipeline to measure inter- neuron synaptic target specificity in Fmr1 mutant and controls. Third, we will - in a manner similar to single cell RNA-seq principle component analysis - analyze individual synaptic boutons by multidimen- sional spatial feature analysis. This allows us to perform unsupervised cluster analysis of interneuron syn- aptic boutons and reveal population level differences between Fmr1-/- and control synapses. Taken together, our data will shed new light on an understudied cell population – cortical interneurons - in FXS etiology and open new avenues of investigation into synaptic defects underlying FXS and ASD.