RESULTS: A total of 75,350,240 sequence reads were obtained via Hi-seq 2500 sequencing technology. A total of 5473 significant differentially expressed genes were called. Gene ontology functional categorisation showed that cellular process, catalytic activity, and cell part categories had the highest number of expressed genes, while the metabolic pathways category possessed the highest number of expressed genes in the KEGG pathway analysis. The additional sequence dataset will further enrich existing M. fascicularis transcriptome assemblies, and provide a dataset for further downstream studies.
RESULTS: Key biological processes linked to upregulated genes (n = 214) included 'response to endoplasmic reticulum stress' and 'lipid metabolism', and processes representing downregulated genes (n = 357) included 'DNA-conformation change' and 'cellular lipid metabolism'.
CONCLUSIONS: Exposure of C. elegans to Pf-fraction 5 induces significant changes in the transcriptome. Gene ontology analysis suggests that Pf-fraction 5 induces endoplasmic reticulum and mitochondrial stress, and the changes in gene expression are either a direct or indirect consequence of this. Further work is required to assess specific responses to sub-fractions of Pf-fraction 5 in time-course experiments in C. elegans, to define the chemical(s) with potent anthelmintic properties, to attempt to unravel their mode(s) of action and to assess their selectivity against nematodes.
Methods: In this study, comparative genome analysis was carried out using the G. boninense NJ3 genome to identify and characterize carbohydrate-active enzyme (CAZymes) including CWDE in the fungal genome. Augustus pipeline was employed for gene identification in G. boninense NJ3 and the produced protein sequences were analyzed via dbCAN pipeline and PhiBase 4.5 database annotation for CAZymes and plant-host interaction (PHI) gene analysis, respectively. Comparison of CAZymes from G. boninense NJ3 was made against G. lucidum, a well-studied model Ganoderma sp. and five selected pathogenic fungi for CAZymes characterization. Functional annotation of PHI genes was carried out using Web Gene Ontology Annotation Plot (WEGO) and was used for selecting candidate PHI genes related to cell wall degradation of G. boninense NJ3.
Results: G. boninense was enriched with CAZymes and CWDEs in a similar fashion to G. lucidum that corroborate with the lignocellulolytic abilities of both closely-related fungal strains. The role of polysaccharide and cell wall degrading enzymes in the hemibiotrophic mode of infection of G. boninense was investigated by analyzing the fungal CAZymes with necrotrophic Armillaria solidipes, A. mellea, biotrophic Ustilago maydis, Melampsora larici-populina and hemibiotrophic Moniliophthora perniciosa. Profiles of the selected pathogenic fungi demonstrated that necrotizing pathogens including G. boninense NJ3 exhibited an extensive set of CAZymes as compared to the more CAZymes-limited biotrophic pathogens. Following PHI analysis, several candidate genes including polygalacturonase, endo β-1,3-xylanase, β-glucanase and laccase were identified as potential CWDEs that contribute to the plant host interaction and pathogenesis.
Discussion: This study employed bioinformatics tools for providing a greater understanding of the biological mechanisms underlying the production of CAZymes in G. boninense NJ3. Identification and profiling of the fungal polysaccharide- and lignocellulosic-degrading enzymes would further facilitate in elucidating the infection mechanisms through the production of CWDEs by G. boninense. Identification of CAZymes and CWDE-related PHI genes in G. boninense would serve as the basis for functional studies of genes associated with the fungal virulence and pathogenicity using systems biology and genetic engineering approaches.
Methods: Microarray expression dataset GSE22255 was retrieved from the Gene Expression Omnibus (GEO) database. It includes messenger ribonucleic acid (mRNA) expression data for the peripheral blood mononuclear cells of 20 controls and 20 IS patients. The bioconductor-package 'affy' was used to calculate expression and a pairwise t-test was applied to screen DEGs (P < 0.01). Further, GSEA was used to determine the enrichment of DEGs specific to gene ontology (GO) annotations.
Results: GSEA analysis revealed 21 genes to be significantly plausible gene markers, enriched in multiple pathways among all the DEGs (n = 881). Ten gene sets were found to be core enriched in specific GO annotations. JunD, NCX3 and fibroblast growth factor receptor 4 (FGFR4) were under-represented and glycoprotein M6-B (GPM6B) was persistently over-represented.
Conclusion: The identified genes are either associated with the pathophysiology of IS or they affect post-IS neuronal regeneration, thereby influencing clinical outcome. These genes should, therefore, be evaluated for their utility as suitable markers for predicting IS in clinical scenarios.