Transcriptional profiling of proliferative skeletal muscle mononucleated cells coupled with broadband electrical cytometry towards diagnosis of myalgic encephalomyelitis/chronic fatigue syndrome

Transcriptional profiling of proliferative skeletal muscle mononucleated cells coupled with broadband electrical cytometry towards diagnosis of myalgic encephalomyelitis/chronic fatigue syndrome PROJECT SUMMARY / ABSTRACT Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating, acquired disease affecting up

to 2.5 million Americans. With increasing evidence that a proportion of patients with COVID-19 experience prolonged convalescence and chronic symptoms similar to ME/CFS, it is suggested that the incidence of ME/CFS will increase significantly. Currently, no single biomarkers or pathognomonic signs have been identified

for diagnostic measures. Instead, diagnosis is based on clinical symptoms after exclusion of other possible etiologies known to cause fatigue, a method that does not prescribe adequate sensitivity or specificity. Since clinical symptoms suggest that skeletal muscle is a major and consistent target of the pathology, and proliferative

skeletal mononucleated cells (SMMCs) are excellent indicators of muscle disorders, we hypothesize that proliferative SMMCs from of ME/CFS patients are distinguishable from those of healthy individuals on the molecular and cellular level. Proposed work will investigate gene expression, functional pathways and electrical

characteristics of single SMMCs from ME/CFS and healthy donors to identify a matrix of molecular and biophysical markers to enable future development of diagnostics. Single-cell mRNA profiling will identify differential gene expression describing alterations that occur in ME/CFS samples. Using differential biomarkers

identified by scRNA-seq, subpopulations of SMMCs unique to ME/CFS will be sorted to study changes in protein expression and cell function. Furthermore, an impedance cytometer recently developed by our team will be used to measure single cell electrical spectra, and disease-specific signatures will be identified by machine learning.

The molecular, cellular and electrical characteristics will be further correlated with each other to provide a comprehensive understanding of the SMMC pathology in ME/CFS, an untapped subject. The proposed single- cell transcriptome analysis of SMMCs from ME/CFS patients represents the first study of its kind and will greatly

contribute to the fundamental knowledge of the role of proliferative SMMCs in ME/CFS dysfunctions. Compared to molecular approaches, proposed impedance cytometry captures a ‘big picture’ of the multitude of changes contributing to abnormalities in ME/CFS SMMCs. As specific molecular markers have not been identified for

diagnostic measures, the holistic electrical characteristics of single cells offer a unique perspective of global changes in SMMCs and hold great diagnostic potential in the future. Integration of electrical and biological studies of SMMCs will further allow interpretation of the impedance spectra to promote sensing specificity.