Introduction
Single cell analysis is a recent, fast expanding technology that allows a deep characterization of cellular diversity in tissues (Kulkarni et al., 2019; Ståhlberg & Kubista, 2018). This method has led to the identification of new cell types as well as to the discovery of cell-specific functions and the recognition of their maturation state (Perchet et al., 2017; Ståhlberg & Kubista, 2018). It is useful for studying heterogeneous cell populations, especially in diseases with genetic variability (Rantalainen, 2018; Ren et al., 2018). In these cases, indeed, an in-depth understanding of all the cell populations that form an affected organ/tissue and of their characteristics and interactions are important issues in the context of personalized medicine.
One of the disorders that can be studied using single cell analysis is myotonic dystrophy type I (DM1). This autosomal dominant genetic condition is characterized by genetic instability and is caused by a CTG repeat expansion in the non-coding 3’ untranslated (UTR) region of the myotonic dystrophy protein kinase (DMPK ) gene (Bird, 1993). More than 50 CTG repeats are considered pathogenic and repeat length can vary from 50 to thousands of repeats in affected patients (Bird, 1993). Furthermore, the size of the CTG repeat also varies between tissues within the same patient (Ashizawa et al., 1993; Lavedan et al., 1993; Mahadevan et al., 1992) as well as during a patient’s lifetime(Wong et al., 1995), and produces anticipation(Harper et al., 1992).
CTG repeat expansions produce toxic RNAs that trigger some of the patient’s symptoms. When the pathological repeats are transcribedDMPK transcripts carry CUG expansions that sequester important cellular proteins, altering their levels and functionalities (Miller et al., 2000). These RNA and protein complexes are known as “RNA foci” and they are located in the nucleus of DM1 cells (Mykowska et al., 2011). One of the proteins sequestered by the RNA foci is the splicing regulator muscleblind-like 1 (MBNL1 ). Proteins aberrantly spliced due to MBNL1 sequestration include insulin receptor (INSR), sarcoplasmic reticulum Ca(2+)-ATPase 1 (ATP2A1), chloride channel 1 (CLCN1), and MBNL1 – which regulates its own splicing (Konieczny et al., 2017). The altered transcription of these genes in DM1 has been related to several symptoms of the disease. Thus, INSR and CLCN1 misregulation are associated with insulin resistance (Renna et al., 2019) and myotonia (Charlet-B. et al., 2002), respectively, and ATP2A1 might impair calcium homeostasis in skeletal muscle (Kimura et al., 2005).
The skeletal muscle is one of the most affected tissues in patients with DM1, but their clinical manifestations are highly heterogeneous (Bundey, 1982). Muscle impairment can be assessed using several scales: the muscle research council (MRC) scale, which evaluates muscle power (Compston, 2010), muscle impairment rating (MIRS) scale (which assesses the degree of distal to proximal muscle involvement) (Mathieu et al., 2001), the 6-minute walking distance (6MWD, an index of endurance [or ‘aerobic’] capacity (Butland et al., 1982)), or the modified Rankin Scale (mRS, an indicator of disability in patients (Van Swieten et al., 1988)).
In DM1 there is a need for single cell data. Scientific evidence indicates that every DM1 muscle cell may contain a different number of CTG repeats in its genome, and therefore could potentially behave differently. In this study, we aimed to analyze the diversity of the muscle cells that compose the DM1 muscle, and analyze how frequently alterations such as RNA foci and splicing occur, and if they can be correlated with the muscle tissue function in patients. By doing so, we attempted to answer the following questions: are all the cells in the muscle tissue affected equally? Is there a correlation between RNA foci and splicing alteration at the single-cell level? Can the average of single-cell data in a patient be correlated with the severity of muscle-related symptoms?