Analysis of Annotated and Unannotated Long Noncoding RNAs from Exosome Subtypes Using Next-Generation RNA Sequencing

Long noncoding RNAs (lncRNAs) contain >200 nucleotides and act as regulatory molecules in transcription and translation processes in both normal and pathological conditions. LncRNAs have been reported to localize in nuclei, cytoplasm, and, more recently, extracellular vesicles such as exosomes. Exosomal lncRNAs have gained much attention as exosomes secreted from one cell type can transfer their cargo (e.g., protein, RNA species, and lipids) to recipient cells and mediate phenotypic changes in the recipient cell. In recent years, many exosomal lncRNAs have been discovered and annotated and are attracting much attention as potential markers for disease diagnosis and prognosis. It is expected that many exosomal lncRNAs are yet to be identified. However, characterization of unannotated exosomal RNAs with non-protein-coding sequences from massive RNA sequencing data is technically challenging. Here, we describe a method for the discovery of annotated and unannotated exosomal lncRNA. This method includes a large-scale isolation and purification strategy for exosome subtypes, using the human colorectal cancer cell line (LIM1863) as a model. The method inputs RNA sequencing clean reads and performs transcript assembly to identify annotated and unannotated exosomal lncRNAs. Cutoffs (length, number of exon, classification code, and human protein-coding probability) are used to identify potentially novel exosomal lncRNAs. Raw read count calculation and differential expression analysis are also introduced for downstream analysis and candidate selection. Exosomal lncRNA candidates are validated using RT-qPCR. This method provides a template for exosomal lncRNA discovery and analysis from next-generation RNA sequencing.

Molecular signature of different lesion types in the brain white matter of patients with progressive multiple sclerosis

To identify pathogenetic markers and potential drivers of different lesion types in the white matter (WM) of patients with progressive multiple sclerosis (PMS), we sequenced RNA from 73 different WM areas. Compared to 25 WM controls, 6713 out of 18,609 genes were significantly differentially expressed in MS tissues (FDR < 0.05). A computational systems medicine analysis was performed to describe the MS lesion endophenotypes. The cellular source of specific molecules was examined by RNAscope, immunohistochemistry, and immunofluorescence. To examine common lesion specific mechanisms, we performed de novo network enrichment based on shared differentially expressed genes (DEGs), and found TGFβ-R2 as a central hub. RNAscope revealed astrocytes as the cellular source of TGFβ-R2 in remyelinating lesions. Since lesion-specific unique DEGs were more common than shared signatures, we examined lesion-specific pathways and de novo networks enriched with unique DEGs. Such network analysis indicated classic inflammatory responses in active lesions; catabolic and heat shock protein responses in inactive lesions; neuronal/axonal specific processes in chronic active lesions. In remyelinating lesions, de novo analyses identified axonal transport responses and adaptive immune markers, which was also supported by the most heterogeneous immunoglobulin gene expression. The signature of the normal-appearing white matter (NAWM) was more similar to control WM than to lesions: only 465 DEGs differentiated NAWM from controls, and 16 were unique. The upregulated marker CD26/DPP4 was expressed by microglia in the NAWM but by mononuclear cells in active lesions, which may indicate a special subset of microglia before the lesion develops, but also emphasizes that omics related to MS lesions should be interpreted in the context of different lesions types. While chronic active lesions were the most distinct from control WM based on the highest number of unique DEGs (n = 2213), remyelinating lesions had the highest gene expression levels, and the most different molecular map from chronic active lesions. This may suggest that these two lesion types represent two ends of the spectrum of lesion evolution in PMS. The profound changes in chronic active lesions, the predominance of synaptic/neural/axonal signatures coupled with minor inflammation may indicate end-stage irreversible molecular events responsible for this less treatable phase.

Unique RNA signature of different lesion types in the brain white matter in progressive multiple sclerosis

The heterogeneity of multiple sclerosis is reflected by dynamic changes of different lesion types in the brain white matter (WM). To identify potential drivers of this process, we RNA-sequenced 73 WM areas from patients with progressive MS (PMS) and 25 control WM. Lesion endophenotypes were described by a computational systems medicine analysis combined with RNAscope, immunohistochemistry, and immunofluorescence. The signature of the normal-appearing WM (NAWM) was more similar to control WM than to lesions: one of the six upregulated genes in NAWM was CD26/DPP4 expressed by microglia. Chronic active lesions that become prominent in PMS had a signature that were different from all other lesion types, and were differentiated from them by two clusters of 62 differentially expressed genes (DEGs). An upcoming MS biomarker, CHI3L1 was among the top ten upregulated genes in chronic active lesions expressed by astrocytes in the rim. TGFβ-R2 was the central hub in a remyelination-related protein interaction network, and was expressed there by astrocytes. We used de novo networks enriched by unique DEGs to determine lesion-specific pathway regulation, i.e. cellular trafficking and activation in active lesions; healing and immune responses in remyelinating lesions characterized by the most heterogeneous immunoglobulin gene expression; coagulation and ion balance in inactive lesions; and metabolic changes in chronic active lesions. Because we found inverse differential regulation of particular genes among different lesion types, our data emphasize that omics related to MS lesions should be interpreted in the context of lesion pathology. Our data indicate that the impact of molecular pathways is substantially changing as different lesions develop. This was also reflected by the high number of unique DEGs that were more common than shared signatures. A special microglia subset characterized by CD26 may play a role in early lesion development, while astrocyte-derived TGFβ-R2 and TGFβ pathways may be drivers of repair in contrast to chronic tissue damage. The highly specific mechanistic signature of chronic active lesions indicates that as these lesions develop in PMS, the molecular changes are substantially skewed: the unique mitochondrial/metabolic changes and specific downregulation of molecules involved in tissue repair may reflect a stage of exhaustion.