Gene expression patterns following unilateral traumatic brain injury reveals a local pro-inflammatory and remote anti-inflammatory response.

BackgroundTraumatic brain injury (TBI) results in irreversible damage at the site of impact and initiates cellular and molecular processes that lead to secondary neural injury in the surrounding tissue. We used microarray analysis to determine which genes, pathways and networks were significantly altered using a rat model of TBI. Adult rats received a unilateral controlled cortical impact (CCI) and were sacrificed 24 h post-injury. The ipsilateral hemi-brain tissue at the site of the injury, the corresponding contralateral hemi-brain tissue, and naïve (control) brain tissue were used for microarray analysis. Ingenuity Pathway Analysis (IPA) software was used to identify molecular pathways and networks that were associated with the altered gene expression in brain tissues following TBI.ResultsInspection of the top fifteen biological functions in IPA associated with TBI in the ipsilateral tissues revealed that all had an inflammatory component. IPA analysis also indicated that inflammatory genes were altered on the contralateral side, but many of the genes were inversely expressed compared to the ipsilateral side. The contralateral gene expression pattern suggests a remote anti-inflammatory molecular response. We created a network of the inversely expressed common (i.e., same gene changed on both sides of the brain) inflammatory response (IR) genes and those IR genes included in pathways and networks identified by IPA that changed on only one side. We ranked the genes by the number of direct connections each had in the network, creating a gene interaction hierarchy (GIH). Two well characterized signaling pathways, toll-like receptor/NF-kappaB signaling and JAK/STAT signaling, were prominent in our GIH.ConclusionsBioinformatic analysis of microarray data following TBI identified key molecular pathways and networks associated with neural injury following TBI. The GIH created here provides a starting point for investigating therapeutic targets in a ranked order that is somewhat different than what has been presented previously. In addition to being a vehicle for identifying potential targets for post-TBI therapeutic strategies, our findings can also provide a context for evaluating the potential of therapeutic agents currently in development

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Transcriptomic analysis of neuregulin-1 regulated genes following ischemic stroke by computational identification of promoter binding sites: A role for the ETS-1 transcription factor.

Ischemic stroke is a major cause of mortality in the United States. We previously showed that neuregulin-1 (NRG1) was neuroprotective in rat models of ischemic stroke. We used gene expression profiling to understand the early cellular and molecular mechanisms of NRG1's effects after the induction of ischemia. Ischemic stroke was induced by middle cerebral artery occlusion (MCAO). Rats were allocated to 3 groups: (1) control, (2) MCAO and (3) MCAO + NRG1. Cortical brain tissues were collected three hours following MCAO and NRG1 treatment and subjected to microarray analysis. Data and statistical analyses were performed using R/Bioconductor platform alongside Genesis, Ingenuity Pathway Analysis and Enrichr software packages. There were 2693 genes differentially regulated following ischemia and NRG1 treatment. These genes were organized by expression patterns into clusters using a K-means clustering algorithm. We further analyzed genes in clusters where ischemia altered gene expression, which was reversed by NRG1 (clusters 4 and 10). NRG1, IRS1, OPA3, and POU6F1 were central linking (node) genes in cluster 4. Conserved Transcription Factor Binding Site Finder (CONFAC) identified ETS-1 as a potential transcriptional regulator of NRG1 suppressed genes following ischemia. A transcription factor activity array showed that ETS-1 activity was increased 2-fold, 3 hours following ischemia and this activity was attenuated by NRG1. These findings reveal key early transcriptional mechanisms associated with neuroprotection by NRG1 in the ischemic penumbra

Representing Normal and Abnormal Physiology as Routes of Flow in ApiNATOMY.

We present (i) the ApiNATOMY workflow to build knowledge models of biological connectivity, as well as (ii) the ApiNATOMY TOO map, a topological scaffold to organize and visually inspect these connectivity models in the context of a canonical architecture of body compartments. In this work, we outline the implementation of ApiNATOMY's knowledge representation in the context of a large-scale effort, SPARC, to map the autonomic nervous system. Within SPARC, the ApiNATOMY modeling effort has generated the SCKAN knowledge graph that combines connectivity models and TOO map. This knowledge graph models flow routes for a number of normal and disease scenarios in physiology. Calculations over SCKAN to infer routes are being leveraged to classify, navigate and search for semantically-linked metadata of multimodal experimental datasets for a number of cross-scale, cross-disciplinary projects

Regulation of inflammatory responses by neuregulin-1 in brain ischemia and microglial cells in vitro involves the NF-kappa B pathway.

BackgroundWe previously demonstrated that neuregulin-1 (NRG-1) was neuroprotective in rats following ischemic stroke. Neuroprotection by NRG-1 was associated with the suppression of pro-inflammatory gene expression in brain tissues. Over-activation of brain microglia can induce pro-inflammatory gene expression by activation of transcriptional regulators following stroke. Here, we examined how NRG-1 transcriptionally regulates inflammatory gene expression by computational bioinformatics and in vitro using microglial cells.MethodsTo identify transcriptional regulators involved in ischemia-induced inflammatory gene expression, rats were sacrificed 24 h after middle cerebral artery occlusion (MCAO) and NRG-1 treatment. Gene expression profiles of brain tissues following ischemia and NRG-1 treatment were examined by microarray technology. The Conserved Transcription Factor-Binding Site Finder (CONFAC) bioinformatics software package was used to predict transcription factors associated with inflammatory genes induced following stroke and suppressed by NRG-1 treatment. NF-kappa B (NF-kB) was identified as a potential transcriptional regulator of NRG-1-suppressed genes following ischemia. The involvement of specific NF-kB subunits in NRG-1-mediated inflammatory responses was examined using N9 microglial cells pre-treated with NRG-1 (100 ng/ml) followed by lipopolysaccharide (LPS; 10 μg/ml) stimulation. The effects of NRG-1 on cytokine production were investigated using Luminex technology. The levels of the p65, p52, and RelB subunits of NF-kB and IkB-α were determined by western blot analysis and ELISA. Phosphorylation of IkB-α was investigated by ELISA.ResultsCONFAC identified 12 statistically over-represented transcription factor-binding sites (TFBS) in our dataset, including NF-kBP65. Using N9 microglial cells, we observed that NRG-1 significantly inhibited LPS-induced TNFα and IL-6 release. LPS increased the phosphorylation and degradation of IkB-α which was blocked by NRG-1. NRG-1 also prevented the nuclear translocation of the NF-kB p65 subunit following LPS administration. However, NRG-1 increased production of the neuroprotective cytokine granulocyte colony-stimulating factor (G-CSF) and the nuclear translocation of the NF-kB p52 subunit, which is associated with the induction of anti-apoptotic and suppression of pro-inflammatory gene expression.ConclusionsNeuroprotective and anti-inflammatory effects of NRG-1 are associated with the differential regulation of NF-kB signaling pathways in microglia. Taken together, these findings suggest that NRG-1 may be a potential therapeutic treatment for treating stroke and other neuroinflammatory disorders

Transcriptomic analysis of neuregulin-1 regulated genes following ischemic stroke by computational identification of promoter binding sites: A role for the ETS-1 transcription factor - Fig 3

<p>A heat map visualized the expression intensities for significant statistical genes in (a) cluster 4, decreased following MCAO and returned to baseline by NRG1, while genes in (b) cluster 10 had the opposite expression profile. High signal (red) to low signal (green) intensities.</p