Nicholas Matigian

MicroRNAs and their isomiRs function cooperatively to target common biological pathways

BackgroundVariants of microRNAs (miRNAs), called isomiRs, are commonly reported in deep-sequencing studies; however, the functional significance of these variants remains controversial. Observational studies show that isomiR patterns are non-random, hinting that these molecules could be regulated and therefore functional, although no conclusive biological role has been demonstrated for these molecules.ResultsTo assess the biological relevance of isomiRs, we have performed ultra-deep miRNA-seq on ten adult human tissues, and created an analysis pipeline called miRNA-MATE to align, annotate, and analyze miRNAs and their isomiRs. We find that isomiRs share sequence and expression characteristics with canonical miRNAs, and are generally strongly correlated with canonical miRNA expression. A large proportion of isomiRs potentially derive from AGO2 cleavage independent of Dicer. We isolated polyribosome-associated mRNA, captured the mRNA-bound miRNAs, and found that isomiRs and canonical miRNAs are equally associated with translational machinery. Finally, we transfected cells with biotinylated RNA duplexes encoding isomiRs or their canonical counterparts and directly assayed their mRNA targets. These studies allow us to experimentally determine genome-wide mRNA targets, and these experiments showed substantial overlap in functional mRNA networks suppressed by both canonical miRNAs and their isomiRs.ConclusionsTogether, these results find isomiRs to be biologically relevant and functionally cooperative partners of canonical miRNAs that act coordinately to target pathways of functionally related genes. This work exposes the complexity of the miRNA-transcriptome, and helps explain a major miRNA paradox: how specific regulation of biological processes can occur when the specificity of miRNA targeting is mediated by only 6 to 11 nucleotides.

Disease-specific, neurosphere-derived cells as models for brain disorders

SUMMARY There is a pressing need for patient-derived cell models of brain diseases that are relevant and robust enough to produce the large quantities of cells required for molecular and functional analyses. We describe here a new cell model based on patient-derived cells from the human olfactory mucosa, the organ of smell, which regenerates throughout life from neural stem cells. Olfactory mucosa biopsies were obtained from healthy controls and patients with either schizophrenia, a neurodevelopmental psychiatric disorder, or Parkinson’s disease, a neurodegenerative disease. Biopsies were dissociated and grown as neurospheres in defined medium. Neurosphere-derived cell lines were grown in serum-containing medium as adherent monolayers and stored frozen. By comparing 42 patient and control cell lines we demonstrated significant disease-specific alterations in gene expression, protein expression and cell function, including dysregulated neurodevelopmental pathways in schizophrenia and dysregulated mitochondrial function, oxidative stress and xenobiotic metabolism in Parkinson’s disease. The study has identified new candidate genes and cell pathways for future investigation. Fibroblasts from schizophrenia patients did not show these differences. Olfactory neurosphere-derived cells have many advantages over embryonic stem cells and induced pluripotent stem cells as models for brain diseases. They do not require genetic reprogramming and they can be obtained from adults with complex genetic diseases. They will be useful for understanding disease aetiology, for diagnostics and for drug discovery.

Cell cycle alterations in biopsied olfactory neuroepithelium in schizophrenia and bipolar I disorder using cell culture and gene expression analyses

We previously demonstrated that olfactory cultures from individuals with schizophrenia had increased cell proliferation compared to cultures from healthy controls. The aims of this study were to (a) replicate this observation in a new group of individuals with schizophrenia, (b) examine the specificity of these findings by including individuals with bipolar I disorder and (c) explore gene expression differences that may underlie cell cycle differences in these diseases. Compared to controls (n = 10), there was significantly more mitosis in schizophrenia patient cultures (n = 8) and significantly more cell death in the bipolar I disorder patient cultures (n = 8). Microarray data showed alterations to the cell cycle and phosphatidylinositol signalling pathways in schizophrenia and bipolar I disorder, respectively. Whilst caution is required in the interpretation of the array results, the study provides evidence indicating that cell proliferation and cell death in olfactory neuroepithelial cultures is differentially altered in schizophrenia and bipolar disorder.

Expression profiling in monozygotic twins discordant for bipolar disorder reveals dysregulation of the WNT signalling pathway

To identify genes dysregulated in bipolar disorder (BD1), we carried out global gene expression profiling using whole-genome microarrays. To minimize genetic variation in gene expression levels between cases and controls, we compared expression profiles in lymphoblastoid cell lines from monozygotic twin pairs discordant for the disease. We identified 82 genes that were differentially expressed by ⩾1.3-fold in three BD1 cases compared to their co-twins, and which were statistically (P⩽0.05) differentially expressed between the groups of BD1 cases and controls. Using quantitative reverse transcriptase-polymerase chain reaction, we confirmed the differential expression of some of these genes, including: KCNK1, MAL, PFN2, TCF7, PGK1 and PI4KCB, in at least two of the twin pairs. In contrast to the findings of a previous study by Kakiuchi and colleagues with similar discordant BD1 twin design, our data do not support the dysregulation of XBP1 and HSPA5. From pathway and gene ontology analysis, we identified upregulation of the WNT signalling pathway and the biological process of apoptosis. The differentially regulated genes and pathways identified in this study may provide insights into the biology of BD1.

Variance of gene expression identifies altered network constraints in neurological disease

Gene expression analysis has become a ubiquitous tool for studying a wide range of human diseases. In a typical analysis we compare distinct phenotypic groups and attempt to identify genes that are, on average, significantly different between them. Here we describe an innovative approach to the analysis of gene expression data, one that identifies differences in expression variance between groups as an informative metric of the group phenotype. We find that genes with different expression variance profiles are not randomly distributed across cell signaling networks. Genes with low-expression variance, or higher constraint, are significantly more connected to other network members and tend to function as core members of signal transduction pathways. Genes with higher expression variance have fewer network connections and also tend to sit on the periphery of the cell. Using neural stem cells derived from patients suffering from Schizophrenia (SZ), Parkinsons disease (PD), and a healthy control group, we find marked differences in expression variance in cell signaling pathways that shed new light on potential mechanisms associated with these diverse neurological disorders. In particular, we find that expression variance of core networks in the SZ patient group was considerably constrained, while in contrast the PD patient group demonstrated much greater variance than expected. One hypothesis is that diminished variance in SZ patients corresponds to an increased degree of constraint in these pathways and a corresponding reduction in robustness of the stem cell networks. These results underscore the role that variation plays in biological systems and suggest that analysis of expression variance is far more important in disease than previously recognized. Furthermore, modeling patterns of variability in gene expression could fundamentally alter the way in which we think about how cellular networks are affected by disease processes.

A Cross-Study Transcriptional Analysis of Parkinson's Disease

The study of Parkinsons disease (PD), like other complex neurodegenerative disorders, is limited by access to brain tissue from patients with a confirmed diagnosis. Alternatively the study of peripheral tissues may offer some insight into the molecular basis of disease susceptibility and progression, but this approach still relies on brain tissue to benchmark relevant molecular changes against. Several studies have reported whole-genome expression profiling in post-mortem brain but reported concordance between these analyses is lacking. Here we apply a standardised pathway analysis to seven independent case-control studies, and demonstrate increased concordance between data sets. Moreover data convergence increased when the analysis was limited to the five substantia nigra (SN) data sets; this highlighted the down regulation of dopamine receptor signaling and insulin-like growth factor 1 (IGF1) signaling pathways. We also show that case-control comparisons of affected post mortem brain tissue are more likely to reflect terminal cytoarchitectural differences rather than primary pathogenic mechanisms. The implementation of a correction factor for dopaminergic neuronal loss predictably resulted in the loss of significance of the dopamine signaling pathway while axon guidance pathways increased in significance. Interestingly the IGF1 signaling pathway was also over-represented when data from non-SN areas, unaffected or only terminally affected in PD, were considered. Our findings suggest that there is greater concordance in PD whole-genome expression profiling when standardised pathway membership rather than ranked gene list is used for comparison.

NRF2 Activation Restores Disease Related Metabolic Deficiencies in Olfactory Neurosphere-Derived Cells from Patients with Sporadic Parkinson's Disease

Background Without appropriate cellular models the etiology of idiopathic Parkinsons disease remains unknown. We recently reported a novel patient-derived cellular model generated from biopsies of the olfactory mucosa (termed olfactory neurosphere-derived (hONS) cells) which express functional and genetic differences in a disease-specific manner. Transcriptomic analysis of Patient and Control hONS cells identified the NRF2 transcription factor signalling pathway as the most differentially expressed in Parkinsons disease. Results We tested the robustness of our initial findings by including additional cell lines and confirmed that hONS cells from Patients had 20% reductions in reduced glutathione levels and MTS [3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium, inner salt] metabolism compared to cultures from healthy Control donors. We also confirmed that Patient hONS cells are in a state of oxidative stress due to higher production of H2O2 than Control cultures. siRNA-mediated ablation of NRF2 in Control donor cells decreased both total glutathione content and MTS metabolism to levels detected in cells from Parkinsons Disease patients. Conversely, and more importantly, we showed that activation of the NRF2 pathway in Parkinsons disease hONS cultures restored glutathione levels and MTS metabolism to Control levels. Paradoxically, transcriptomic analysis after NRF2 pathway activation revealed an increased number of differentially expressed mRNAs within the NRF2 pathway in L-SUL treated Patient-derived hONS cells compared to L-SUL treated Controls, even though their metabolism was restored to normal. We also identified differential expression of the PI3K/AKT signalling pathway, but only post-treatment. Conclusions Our results confirmed NRF2 as a potential therapeutic target for Parkinsons disease and provided the first demonstration that NRF2 function was inducible in Patient-derived cells from donors with uniquely varied genetic backgrounds. However, our results also demonstrated that the response of PD patient-derived cells was not co-ordinated in the same way as in Control cells. This may be an important factor when developing new therapeutics.

Fibroblast and Lymphoblast Gene Expression Profiles in Schizophrenia: Are Non-Neural Cells Informative?

Lymphoblastoid cell lines (LCLs) and fibroblasts provide conveniently derived non-neuronal samples in which to investigate the aetiology of schizophrenia (SZ) using gene expression profiling. This assumes that heritable mechanisms associated with risk of SZ have systemic effects and result in changes to gene expression in all tissues. The broad aim of this and other similar studies is that comparison of the transcriptomes of non-neuronal tissues from SZ patients and healthy controls may identify gene/pathway dysregulation underpinning the neurobiological defects associated with SZ. Using microarrays consisting of 18,664 probes we compared gene expression profiles of LCLs from SZ cases and healthy controls. To identify robust associations with SZ that were not patient or tissue specific, we also examined fibroblasts from an independent series of SZ cases and controls using the same microarrays. In both tissue types ANOVA analysis returned approximately the number of differentially expressed genes expected by chance. No genes were significantly differentially expressed in either tissue when corrected for multiple testing. Even using relaxed parameters (p≤0.05, without multiple testing correction) there were still no differentially expressed genes that also displayed ≥2-fold change between the groups of SZ cases and controls common to both LCLs and fibroblasts. We conclude that despite encouraging data from previous microarray studies assessing non-neural tissues, the lack of a convergent set of differentially expressed genes associated with SZ using fibroblasts and LCLs indicates the utility of non-neuronal tissues for detection of gene expression differences and/or pathways associated with SZ remains to be demonstrated.

Stemformatics: visualisation and sharing of stem cell gene expression.

Genome-scale technologies are increasingly adopted by the stem cell research community, because of the potential to uncover the molecular events most informative about a stem cell state. These technologies also present enormous challenges around the sharing and visualisation of data derived from different laboratories or under different experimental conditions. Stemformatics is an easy to use, publicly accessible portal that hosts a large collection of exemplar stem cell data. It provides fast visualisation of gene expression across a range of mouse and human datasets, with transparent links back to the original studies. One difficulty in the analysis of stem cell signatures is the paucity of public pathways/gene lists relevant to stem cell or developmental biology. Stemformatics provides a simple mechanism to create, share and analyse gene sets, providing a repository of community-annotated stem cell gene lists that are informative about pathways, lineage commitment, and common technical artefacts. Stemformatics can be accessed at stemformatics.org.

Variability in the Generation of Induced Pluripotent Stem Cells: Importance for Disease Modeling

In the field of disease modeling, induced pluripotent stem cells (iPSCs) have become an appealing choice, especially for diseases that do not have an animal model. They can be generated from patients with known clinical features and compared with cells from healthy controls to identify the biological bases of disease. This study was undertaken to determine the variability in iPSC lines derived from different individuals, with the aim of determining criteria for selecting iPSC lines for disease models. We generated and characterized 18 iPSC lines from eight donors and considered variability at three levels: (a) variability in the criteria that define iPSC lines as pluripotent cells, (b) variability in cell lines from different donors, and (c) variability in cell lines from the same donor. We found that variability in transgene expression and pluripotency marker levels did not prevent iPSCs from fulfilling all other criteria for pluripotency, including teratoma formation. We found low interindividual and interclonal variability in iPSCs that fulfilled the most stringent criteria for pluripotency, with very high correlation in their gene expression profiles. Interestingly, some cell lines exhibited reprogramming instability, spontaneously regressing from a fully to a partially reprogrammed state. This was associated with a low percentage of cells expressing the pluripotency marker stage‐specific embryonic antigen‐4. Our study shows that it is possible to define a similar “ground state” for each cell line as the basis for making patient versus control comparisons, an essential step in order to identify disease‐associated variability above individual and cell line variability.