Dissecting pathology in mouse models in Amyotrophic Lateral Sclerosis and Charcot-Marie-Tooth disease

Neuromuscular junctions (NMJs) are the synapses connecting motor neurons to muscle fibres. Dysfunction of the NMJ has been implicated in the pathology of amyotrophic lateral sclerosis (ALS) and Charcot-Marie- Tooth (CMT) disease, partly due to the progressive loss of skeletal muscle control in these disorders, and due to the common final NMJ phenotype, regardless of the genetic mutation. These motor system diseases are associated with skeletal muscle fibre and protein pathologies in the central or peripheral nervous system. Modelling NMJ dysfunction using mouse models is important for us to investigate pathological mechanisms and to identify how gene mutations involved in diverse biological functions lead to a common NMJ phenotype. However, NMJ structural studies are based mostly on manual analysis with potential intra- and inter-rater variability, limiting reproducibility. Methods: Mouse models of ALS and CMT were investigated, each containing a single mutation caused by transgenic or knock-in technology or chemical mutagenesis. We carried out an extensive pathological analysis in the nervous tissues and hindlimb muscles in the ALS mice and NMJ studies in both ALS and CMT mice. The NMJ studies were further developed by creating a python- script coupled to a machine learning algorithm. Results and discussion: To address the subjective nature of manual NMJ analysis, we developed a novel high-throughput screening method for NMJ structural analysis and a machine learning system for automatic identification of NMJ innervation status. Using this system, ‘NMJ analyser’ we have identified changes in multiple morphological parameters across ALS and CMT mouse strains supporting the idea that the NMJ denervation process seems to be different in these models. Furthermore, within FUS-ALS mice, we did not find upper motor neuron loss and gliosis in the motor cortex nor fibretype pathology at multiple timepoints analysed. Our results lead to a 1) more comprehensive and precise study of NMJ pathology, 2) systematic study of NMJs in mice and 3) precise identification of NMJ morphological changes across different mouse models with NMJ pathology. Further understanding of NMJ denervation process could lead to novel and earlier therapeutic interventions in patients where NMJ pathology is observed

Mice with endogenous TDP-43 mutations exhibit gain of splicing function and characteristics of amyotrophic lateral sclerosis

TDP-43 (encoded by the gene TARDBP) is an RNA binding protein central to the pathogenesis of amyotrophic lateral sclerosis (ALS). However, how TARDBP mutations trigger pathogenesis remains unknown. Here, we use novel mouse mutants carrying point mutations in endogenous Tardbp to dissect TDP-43 function at physiological levels both in vitro and in vivo Interestingly, we find that mutations within the C-terminal domain of TDP-43 lead to a gain of splicing function. Using two different strains, we are able to separate TDP-43 loss- and gain-of-function effects. TDP-43 gain-of-function effects in these mice reveal a novel category of splicing events controlled by TDP-43, referred to as "skiptic" exons, in which skipping of constitutive exons causes changes in gene expression. In vivo, this gain-of-function mutation in endogenous Tardbp causes an adult-onset neuromuscular phenotype accompanied by motor neuron loss and neurodegenerative changes. Furthermore, we have validated the splicing gain-of-function and skiptic exons in ALS patient-derived cells. Our findings provide a novel pathogenic mechanism and highlight how TDP-43 gain of function and loss of function affect RNA processing differently, suggesting they may act at different disease stages

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

Abstract 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