Small RNA Deep Sequencing Identifies a Unique miRNA Signature Released in Serum Exosomes in a Mouse Model of Sjögren's Syndrome

Abstract

Sjögren's Syndrome (SS) is an autoimmune disease characterized by lymphocytic infiltration and loss of function of moisture-producing exocrine glands as well as systemic inflammation. SS diagnosis is cumbersome, subjective and complicated by manifestation of symptoms that overlap with those of other rheumatic and ocular diseases. Definitive diagnosis averages 4–5 years and this delay may lead to irreversible tissue damage. Thus, there is an urgent need for diagnostic biomarkers for earlier detection of SS. Extracellular vesicles called exosomes carry functional small non-coding RNAs which play a critical role in maintaining cellular homeostasis via transcriptional and translational regulation of mRNA. Alterations in levels of specific exosomal miRNAs may be predictive of disease status. Here, we have assessed serum exosomal RNA using next generation sequencing in a discovery cohort of the NOD mouse, a model of early-intermediate SS, to identify dysregulated miRNAs that may be indicative of SS. We found five miRNAs upregulated in serum exosomes of NOD mice with an adjusted p < 0.05—miRNA-127-3p, miRNA-409-3p, miRNA-410-3p, miRNA-541-5p, and miRNA-540-5p. miRNAs 127-3p and 541-5p were also statistically significantly upregulated in a validation cohort of NOD mice. Pathway analysis and existing literature indicates that differential expression of these miRNAs may dysregulate pathways involved in inflammation. Future studies will apply these findings in a human cohort to understand how they are correlated with manifestations of SS as well as understanding their functional role in systemic autoimmunity specific to SS.

Exosomes derived from human placental mesenchymal stem cells ameliorate myocardial infarction via anti-inflammation and restoring gut dysbiosis

“…Exosomal transfer of miRNAs from the bone marrow may promote breast cancer cell dormancy in a metastatic niche [ 63 ]. Moreover, a finding indicated that differential expression of miRNA-127-3p, miRNA-409-3p, miRNA-410-3p, miRNA-541-5p and miRNA-540-5p may result in the destruction of inflammation pathways in sicca syndrome mice [ 64 ]. Additionally, Exosomes miR-18b derived from cardiogenic cells improved ischemia–reperfusion injury in MI rats via inducing macrophage activation [ 65 ].…”

Research status and future prospects of extracellular vesicles in primary Sjögren’s syndrome

“…LC–MS analysis of saliva and tear EVs of pSS patients can screen new biomarkers that may contain saliva and lacrimal gland disease targets, which can improve the diagnostic accuracy of pSS and may also be used for disease staging and monitoring [ 45 , 46 ]. Recently, Kakan et al [ 47 ] used small RNA deep sequencing to identify the characteristics of serum exosome miRNA in early and middle autoimmune lacrimal gland inflammation and pSS mouse models. They found seven miRNAs with the most significant differences in expression.…”

Tear miRNAs Identified in a Murine Model of Sjögren’s Syndrome as Potential Diagnostic Biomarkers and Indicators of Disease Mechanism

“…In total, 13 samples were sent for RNA sequencing, and raw data was analyzed as follows: (A1) Quality assessment by FASTqc showed presence of 3' adapters in the reads; (B) Using cutadapt (33), 3' adapters were trimmed and reads with quality scores <20 or length <15 were removed; (C) Trimmed reads were aligned to mouse genome GRCm38 using Bowtie (34); and (D) Aligned reads were annotated using featureCounts (35). Additionally, (A2) raw FASTQ files were also run through our internal miRGrepp pipeline (36) and (E) miRNA counts were normalized, and plotted to assess the quality of the data with statistics on these read counts performed using R package, DESEq2 (37); (F) Shortlisted hits were validated by qPCR in a separate cohort of mice; and and (G) Pathway analysis of the hits was done in Ingenuity Pathway Analysis (Qiagen). Graphic created with BioRender.com.…”

“…Trimmed reads were aligned to mouse whole genome GENCODE GRCm38 using Bowtie and quantified using featureCounts. Raw reads were also aligned to miRbase v22.0 as described previously (36) using our in-house aligner miRGrep (36). miRNA read counts filtering, data normalization, and differential gene expression analysis was done using DESEq2 in RStudio with no data points excluded in the analysis.…”