RESULTS: Targeted and non-targeted metabolomics for both polar and semi-polar metabolites of Phialemonium curvatum AWO2 (DSM 23903) cultivated in MSM with palm oil (MSM-P) or glucose (MSM-G) as carbon sources were obtained. Targeted metabolomics on central carbon metabolism of tricarboxylic acid (TCA) cycle and glyoxylate cycle were analysed using LC-MS/MS-TripleQ and GC-MS, while untargeted metabolite profiling was performed using LC-MS/MS-QTOF followed by multivariate analysis. Targeted metabolomics analysis showed that glyoxylate pathway and TCA cycle were recruited at central carbon metabolism for triglyceride and glucose catabolism, respectively. Significant differences in organic acids concentration of about 4- to 8-fold were observed for citric acid, succinic acid, malic acid, and oxaloacetic acid. Correlation of organic acids concentration and key enzymes involved in the central carbon metabolism was further determined by enzymatic assays. On the other hand, the untargeted profiling revealed seven metabolites undergoing significant changes between MSM-P and MSM-G cultures.
CONCLUSIONS: Overall, this study has provided insights on the understanding on the effect of triglycerides and sugar as carbon source in fungi global metabolic pathway, which might become important for future optimization of carbon flux engineering in fungi to improve organic acids production when vegetable oil is applied as the sole carbon source.
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: We therefore conducted a cluster analysis of the Autism Diagnostic Interview-Revised (ADI-R) scores from 85 individuals with ASD to predict subgroups and subsequently identified dysregulated genes by reanalyzing the transcriptome profiles of individuals with ASD and unaffected individuals. Proteome profiling of lymphoblastoid cell lines from these individuals was performed via 2D-gel electrophoresis, and then mass spectrometry. Disrupted proteins were identified and compared to the dysregulated transcripts and reported dysregulated proteins from previous proteome studies. Biological functions were predicted using the Ingenuity Pathway Analysis (IPA) program. Selected proteins were also analyzed by Western blotting.
RESULTS: The cluster analysis of ADI-R data revealed four ASD subgroups, including ASD with severe language impairment, and transcriptome profiling identified dysregulated genes in each subgroup. Screening via proteome analysis revealed 82 altered proteins in the ASD subgroup with severe language impairment. Eighteen of these proteins were further identified by nano-LC-MS/MS. Among these proteins, fourteen were predicted by IPA to be associated with neurological functions and inflammation. Among these proteins, diazepam-binding inhibitor (DBI) protein was confirmed by Western blot analysis to be expressed at significantly decreased levels in the ASD subgroup with severe language impairment, and the DBI expression levels were correlated with the scores of several ADI-R items.
CONCLUSIONS: By subgrouping individuals with ASD based on clinical phenotypes, and then performing an integrated transcriptome-proteome analysis, we identified DBI as a novel candidate protein for ASD with severe language impairment. The mechanisms of this protein and its potential use as an ASD biomarker warrant further study.