Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, Tennessee.
Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, Tennessee
J Neurosci. 2024 Mar 20;44(12):e1078232023. doi: 10.1523/JNEUROSCI.1078-23.2023.
Regression is a key feature of neurodevelopmental disorders such as autism spectrum disorder, Fragile X syndrome, and Rett syndrome (RTT). RTT is caused by mutations in the X-linked gene methyl-CpG-binding protein 2 (). It is characterized by an early period of typical development with subsequent regression of previously acquired motor and speech skills in girls. The syndromic phenotypes are individualistic and dynamic over time. Thus far, it has been difficult to capture these dynamics and syndromic heterogeneity in the preclinical -heterozygous female mouse model (Het). The emergence of computational neuroethology tools allows for robust analysis of complex and dynamic behaviors to model endophenotypes in preclinical models. Toward this first step, we utilized DeepLabCut, a marker-less pose estimation software to quantify trajectory kinematics and multidimensional analysis to characterize behavioral heterogeneity in Het in the previously benchmarked, ethologically relevant social cognition task of pup retrieval. We report the identification of two distinct phenotypes of adult Het: Het that display a delay in efficiency in early days and then improve over days like wild-type mice and Het that regress and perform worse in later days. Furthermore, regression is dependent on age and behavioral context and can be detected in the initial days of retrieval. Together, the novel identification of two populations of Het suggests differential effects on neural circuitry, opens new avenues to investigate the underlying molecular and cellular mechanisms of heterogeneity, and designs better studies for stratifying therapeutics.
回归是自闭症谱系障碍、脆性 X 综合征和雷特综合征 (RTT) 等神经发育障碍的一个关键特征。RTT 是由 X 连锁基因甲基化CpG 结合蛋白 2 () 的突变引起的。其特征是女孩在典型的早期发育阶段后,先前获得的运动和言语技能出现退化。综合征表型具有个体性和随时间的动态变化。到目前为止,在临床前 -杂合雌性小鼠模型 (Het) 中很难捕捉到这些动态变化和综合征异质性。计算神经行为学工具的出现允许对复杂和动态行为进行稳健分析,以在临床前模型中模拟表型。为此,我们首先利用无标记姿态估计软件 DeepLabCut 来量化轨迹运动学和多维分析,以在以前经过基准测试的、与行为相关的社会认知任务(幼崽取回)中描述 Het 中的行为异质性。我们报告了成年 Het 的两种不同表型的鉴定:一种是在早期几天内效率延迟,然后像野生型小鼠一样在几天内提高;另一种是在后期退化并表现更差。此外,退化依赖于年龄和行为背景,可以在取回的最初几天检测到。总之,Het 的两种群体的新识别表明对神经回路有不同的影响,为研究异质性的潜在分子和细胞机制开辟了新途径,并为分层治疗设计了更好的研究。