NMJ-Analyser identifies subtle early changes in mouse models of neuromuscular disease.

NMJ-Analyser identifies subtle early changes in mouse models of neuromuscular disease.
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DOI:
10.1038/s41598-021-91094-6
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发表时间:
2021-06-10
期刊:
影响因子:
4.6
通讯作者:
Sudre CH
Sudre CH
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Mejia Maza A;Jarvis S;Lee WC;Cunningham TJ;Schiavo G;Secrier M;Fratta P;Sleigh JN;Fisher EMC;Sudre CH

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神经肌肉接头(NMJ)是运动神经元轴突末端和肌纤维之间形成的外周突触。 NMJ 被认为是许多神经肌肉疾病中外周病理学的主要部位,但神经支配/去神经支配状态的定性评估通常在研究中缺乏系统标准,并且与 3D 形态结构分开。在这里,我们描述了“NMJ-Analyser”的开发,以自动全面筛选NMJ的形态及其相应的神经支配状态。 NMJ-Analyser 生成 29 个生物学相关特征,以定量定义健康和异常的神经肌肉突触,并应用机器学习来诊断 NMJ 退化。我们在野生型小鼠的纵向分析以及四种不同的神经肌肉疾病模型中验证了这一框架:三种用于肌萎缩侧索硬化症(ALS),一种用于周围神经病。我们发现,NMJ 的结构变化最初发生在突变 TDP43 和 FUS ALS 模型的神经末梢中。使用机器学习算法,可以以 95% 的准确度、88% 的灵敏度和 97% 的特异性识别健康和异常的神经肌肉突触。我们的结果验证了 NMJ-Analyser 作为 NMJ 系统和结构筛选的强大平台,并为神经肌肉疾病的可转移、交叉比较和高通量研究铺平了道路。
The neuromuscular junction (NMJ) is the peripheral synapse formed between a motor neuron axon terminal and a muscle fibre. NMJs are thought to be the primary site of peripheral pathology in many neuromuscular diseases, but innervation/denervation status is often assessed qualitatively with poor systematic criteria across studies, and separately from 3D morphological structure. Here, we describe the development of ‘NMJ-Analyser’, to comprehensively screen the morphology of NMJs and their corresponding innervation status automatically. NMJ-Analyser generates 29 biologically relevant features to quantitatively define healthy and aberrant neuromuscular synapses and applies machine learning to diagnose NMJ degeneration. We validated this framework in longitudinal analyses of wildtype mice, as well as in four different neuromuscular disease models: three for amyotrophic lateral sclerosis (ALS) and one for peripheral neuropathy. We showed that structural changes at the NMJ initially occur in the nerve terminal of mutant TDP43 and FUS ALS models. Using a machine learning algorithm, healthy and aberrant neuromuscular synapses are identified with 95% accuracy, with 88% sensitivity and 97% specificity. Our results validate NMJ-Analyser as a robust platform for systematic and structural screening of NMJs, and pave the way for transferrable, and cross-comparison and high-throughput studies in neuromuscular diseases.
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