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?