MicroRNAs modulate schwann cell response to nerve injury by reinforcing transcriptional silencing of dedifferentiation-related genes

In the peripheral nervous system, Schwann cells (SCs) surrounding damaged axons undergo an injury response that is driven by an intricate transcriptional program and is critical for nerve regeneration. To examine whether these injury-induced changes in SCs are also regulated posttranscriptionally by miRNAs, we performed miRNA expression profiling of mouse sciatic nerve distal segment after crush injury. We also characterized the SC injury response in mice containing SCs with disrupted miRNA processing due to loss of Dicer. We identified 87 miRNAs that were expressed in mouse adult peripheral nerve, 48 of which were dynamically regulated after nerve injury. Most of these injury-regulated SC miRNAs were computationally predicted to inhibit drivers of SC dedifferentiation/proliferation and thereby re-enforce the transcriptional program driving SC remyelination. SCs deficient in miRNAs manifested a delay in the transition between the distinct differentiation states required to support peripheral nerve regeneration. Among the miRNAs expressed in adult mouse SCs, miR-34a and miR-140 were identified as functional regulators of SC dedifferentiation/proliferation and remyelination, respectively. We found that miR-34a interacted with positive regulators of dedifferentiation and proliferation such as Notch1 and Ccnd1 to control cell cycle dynamics in SCs. miR-140 targeted the transcription factor Egr2, a master regulator of myelination, and modulated myelination in DRG/SC cocultures. Together, these results demonstrate that SC miRNAs are important modulators of the SC regenerative response after nerve damage

A systematic model to predict transcriptional regulatory mechanisms based on overrepresentation of transcription factor binding profiles

An important aspect of understanding a biological pathway is to delineate the transcriptional regulatory mechanisms of the genes involved. Two important tasks are often encountered when studying transcription regulation, i.e., (1) the identification of common transcriptional regulators of a set of coexpressed genes; (2) the identification of genes that are regulated by one or several transcription factors. In this study, a systematic and statistical approach was taken to accomplish these tasks by establishing an integrated model considering all of the promoters and characterized transcription factors (TFs) in the genome. A promoter analysis pipeline (PAP) was developed to implement this approach. PAP was tested using coregulated gene clusters collected from the literature. In most test cases, PAP identified the transcription regulators of the input genes accurately. When compared with chromatin immunoprecipitation experiment data, PAP's predictions are consistent with the experimental observations. When PAP was used to analyze one published expression-profiling data set and two novel coregulated gene sets, PAP was able to generate biologically meaningful hypotheses. Therefore, by taking a systematic approach of considering all promoters and characterized TFs in our model, we were able to make more reliable predictions about the regulation of gene expression in mammalian organisms

Identification of transcriptional regulatory networks specific to pilocytic astrocytoma.

BackgroundPilocytic Astrocytomas (PAs) are common low-grade central nervous system malignancies for which few recurrent and specific genetic alterations have been identified. In an effort to better understand the molecular biology underlying the pathogenesis of these pediatric brain tumors, we performed higher-order transcriptional network analysis of a large gene expression dataset to identify gene regulatory pathways that are specific to this tumor type, relative to other, more aggressive glial or histologically distinct brain tumours.MethodsRNA derived from frozen human PA tumours was subjected to microarray-based gene expression profiling, using Affymetrix U133Plus2 GeneChip microarrays. This data set was compared to similar data sets previously generated from non-malignant human brain tissue and other brain tumour types, after appropriate normalization.ResultsIn this study, we examined gene expression in 66 PA tumors compared to 15 non-malignant cortical brain tissues, and identified 792 genes that demonstrated consistent differential expression between independent sets of PA and non-malignant specimens. From this entire 792 gene set, we used the previously described PAP tool to assemble a core transcriptional regulatory network composed of 6 transcription factor genes (TFs) and 24 target genes, for a total of 55 interactions. A similar analysis of oligodendroglioma and glioblastoma multiforme (GBM) gene expression data sets identified distinct, but overlapping, networks. Most importantly, comparison of each of the brain tumor type-specific networks revealed a network unique to PA that included repressed expression of ONECUT2, a gene frequently methylated in other tumor types, and 13 other uniquely predicted TF-gene interactions.ConclusionsThese results suggest specific transcriptional pathways that may operate to create the unique molecular phenotype of PA and thus opportunities for corresponding targeted therapeutic intervention. Moreover, this study also demonstrates how integration of gene expression data with TF-gene and TF-TF interaction data is a powerful approach to generating testable hypotheses to better understand cell-type specific genetic programs relevant to cancer

Standardized Extract of Bacopa monniera

The aim of the present study is to investigate the effect of standardized extract of Bacopa monnieri (memory enhancer) and Melatonin (an antioxidant) on nuclear factor erythroid 2 related factor 2 (Nrf2) pathway in Okadaic acid induced memory impaired rats. OKA (200 ng) was administered intracerebroventricularly (ICV) to induce memory impairment in rats. Bacopa monnieri (BM-40 and 80 mg/kg) and Melatonin (20 mg/kg) were administered 1 hr before OKA injection and continued daily up to day 13. Memory functions were assessed by Morris water maze test on days 13–15. Rats were sacrificed for biochemical estimations of oxidative stress, neuroinflammation, apoptosis, and molecular studies of Nrf2, HO1, and GCLC expressions in cerebral cortex and hippocampus brain regions. OKA caused a significant memory deficit with oxidative stress, neuroinflammation, and neuronal loss which was concomitant with attenuated expression of Nrf2, HO1, and GCLC. Treatment with BM and Melatonin significantly improved memory dysfunction in OKA rats as shown by decreased latency time and path length. The treatments also restored Nrf2, HO1, and GCLC expressions and decreased oxidative stress, neuroinflammation, and neuronal loss. Thus strengthening the endogenous defense through Nrf2 modulation plays a key role in the protective effect of BM and Melatonin in OKA induced memory impairment in rats

PAP: a comprehensive workbench for mammalian transcriptional regulatory sequence analysis

Given the recent explosion of publications that employ microarray technology to monitor genome-wide expression and that correlate these expression changes to biological processes or to disease states, the determination of the transcriptional regulation of these co-expressed genes is the next major step toward deciphering the genetic network governing the pathway or disease under study. Although computational approaches have been proposed for this purpose, there is no integrated and user-friendly software application that allows experimental biologists to tackle this problem in higher eukaryotes. We have previously reported a systematic, statistical model of mammalian transcriptional regulatory sequence analysis. We have now made crucial extensions to this model and have developed a comprehensive, user-friendly web application suite termed the Promoter Analysis Pipeline (PAP). PAP is available at: http://bioinformatics.wustl.edu/webTools/portalModule/PromoterSearch.d