Analyzing Gene Expression Profiles from Ataxia and Spasticity Phenotypes to Reveal Spastic Ataxia Related Pathways

PathIN: an integrated tool for the visualization of pathway interaction networks

PathIN is a web-service that provides an easy and flexible way for rapidly creating pathway-based networks at several functional biological levels: genes, compounds and reactions. The tool is supported by a database repository of reference pathway networks across a large set of species, developed through the freely available information included in the KEGG, Reactome and Wiki Pathways database repositories. PathIN provides networks by means of five diverse methodologies: (a) direct connections between pathways of interest, (b) direct connections as well as the first neighbours of the given pathways, (c) direct connections, the first neighbours and the connections in between them, and (d) two additional methodologies for creating complementary pathway-to-pathway networks that involve additional (missing) pathways that interfere in-between pathways of interest. PathIN is expected to be used as a simple yet informative reference tool for understanding networks of molecular mechanisms related to specific diseases.

Transcriptomic characterization of tissues from patients and subsequent pathway analyses reveal biological pathways that are implicated in spastic ataxia

BACKGROUND

Spastic ataxias (SAs) encompass a group of rare and severe neurodegenerative diseases, characterized by an overlap between ataxia and spastic paraplegia clinical features. They have been associated with pathogenic variants in a number of genes, including GBA2. This gene codes for the non-lysososomal β-glucosylceramidase, which is involved in sphingolipid metabolism through its catalytic role in the degradation of glucosylceramide. However, the mechanism by which GBA2 variants lead to the development of SA is still unclear.

METHODS

In this work, we perform next-generation RNA-sequencing (RNA-seq), in an attempt to discover differentially expressed genes (DEGs) in lymphoblastoid, fibroblast cell lines and induced pluripotent stem cell-derived neurons derived from patients with SA, homozygous for the GBA2 c.1780G > C missense variant. We further exploit DEGs in pathway analyses in order to elucidate candidate molecular mechanisms that are implicated in the development of the GBA2 gene-associated SA.

RESULTS

Our data reveal a total of 5217 genes with significantly altered expression between patient and control tested tissues. Furthermore, the most significant extracted pathways are presented and discussed for their possible role in the pathogenesis of the disease. Among them are the oxidative stress, neuroinflammation, sphingolipid signaling and metabolism, PI3K-Akt and MAPK signaling pathways.

CONCLUSIONS

Overall, our work examines for the first time the transcriptome profiles of GBA2-associated SA patients and suggests pathways and pathway synergies that could possibly have a role in SA pathogenesis. Lastly, it provides a list of DEGs and pathways that could be further validated towards the discovery of disease biomarkers.

PathExNET: A tool for extracting pathway expression networks from gene expression statistics

A fundamental issue related to the understanding of the molecular mechanisms, is the way in which common pathways act across different biological experiments related to complex diseases. Using network-based approaches, this work aims to provide a numeric characterization of pathways across different biological experiments, in the prospect to create unique footprints that may characterise a specific disease under study at a pathway network level. In this line we propose PathExNET, a web service that allows the creation of pathway-to-pathway expression networks that hold the over- and under expression information obtained from differential gene expression analyses. The unique numeric characterization of pathway expression status related to a specific biological experiment (or disease), as well as the creation of diverse combination of pathway networks generated by PathExNET, is expected to provide a concrete contribution towards the individualization of disease, and further lead to a more precise personalised medicine and management of treatment. PathExNET is available at: https://bioinformatics.cing.ac.cy/PathExNET and at https://pathexnet.cing-big.hpcf.cyi.ac.cy/.

Signaling pathways of genetic variants and miRNAs in the pathogenesis of myasthenia gravis

BACKGROUND

Myasthenia gravis (MG) is a chronic autoimmune neuromuscular disorder causing muscle weakness and characterized by a defect in synaptic transmission at the neuromuscular junction. The pathogenesis of this disease remains unclear. We aimed to predict the key signaling pathways of genetic variants and miRNAs in the pathogenesis of MG, and identify the key genes among them.

METHODS

We searched published information regarding associated single nucleotide polymorphisms (SNPs) and differentially-expressed miRNAs in MG cases. We search of SNPs and miRNAs in literature databases about MG, then we used bioinformatic tools to predict target genes of miRNAs. Moreover, functional enrichment analysis for key genes was carried out utilizing the Cytoscape-plugin, known as ClueGO. These key genes were mapped to STRING database to construct a protein-protein interaction (PPI) network. Then a miRNA-target gene regulatory network was established to screen key genes.

RESULTS

Five genes containing SNPs associated with MG risk were involved in the inflammatory bowel disease (IBD) signaling pathway, and FoxP3 was the key gene. MAPK1, SMAD4, SMAD2 and BCL2 were predicted to be targeted by the 18 miRNAs and to act as the key genes in adherens, junctions, apoptosis, or cancer-related pathways respectively. These five key genes containing SNPs or targeted by miRNAs were found to be involved in negative regulation of T cell differentiation.

CONCLUSIONS

We speculate that SNPs cause the genes to be defective or the miRNAs to downregulate the factors that subsequently negatively regulate regulatory T cells and trigger the onset of MG.

Effect of Expression of Human Glucosylceramidase 2 Isoforms on Lipid Profiles in COS-7 Cells

Glucosylceramide (GlcCer) is a major membrane lipid and the precursor of gangliosides. GlcCer is mainly degraded by two enzymes, lysosomal acid β-glucosidase (GBA) and nonlysosomal β-glucosidase (GBA2), which may have different isoforms because of alternative splicing. To understand which GBA2 isoforms are active and how they affect glycosphingolipid levels in cells, we expressed nine human GBA2 isoforms in COS-7 cells, confirmed their expression by qRT-PCR and Western blotting, and assayed their activity to hydrolyze 4-methylumbelliferyl-β-D-glucopyranoside (4MUG) in cell extracts. Human GBA2 isoform 1 showed high activity, while the other isoforms had activity similar to the background. Comparison of sphingolipid levels by ultra-high resolution/accurate mass spectrometry (UHRAMS) analysis showed that isoform 1 overexpression increased ceramide and decreased hexosylceramide levels. Comparison of ratios of glucosylceramides to the corresponding ceramides in the extracts indicated that GBA2 isoform 1 has broad specificity for the lipid component of glucosylceramide, suggesting that only one GBA2 isoform 1 is active and affects sphingolipid levels in the cell. Our study provides new insights into how increased breakdown of GlcCer affects cellular lipid metabolic networks.