Biomedical Informatics Colloquium, BIO 4050, Course Outline

A seminar-based course that exposes students to current research topics in the fields of Bioinformatics and Medical Informatics. Weekly presentations by invited speakers and/or faculty introduce students to the broad diversity of research areas in both fields, and engages them in critical thinking and writing. Online lectures and reading activities will be given periodically

Bioinformatics II, BIO 3352, Course Outline

This course is a continuation of Bioinformatics I. Topics include gene expression, microarrays, next- generation sequencing methods, RNA-seq, large genomic projects, protein structure and stability, protein folding, and computational structure prediction of proteins; proteomics; and protein-nucleic acid interactions. The lab component includes R-based statistical data analysis on large datasets, introduction to big data analysis tools, protein visualization software, internet-based tools and high-level programming languages

Use of RNA sequencing to evaluate rheumatic disease patients

Studying the factors that control gene expression is of substantial importance for rheumatic diseases with poorly understood etiopathogenesis. In the past, gene expression microarrays have been used to measure transcript abundance on a genome-wide scale in a particular cell, tissue or organ. Microarray analysis has led to gene signatures that differentiate rheumatic diseases, and stages of a disease, as well as response to treatments. Nowadays, however, with the advent of next-generation sequencing methods, massive parallel sequencing of RNA tends to be the technology of choice for gene expression profiling, due to several advantages over microarrays, as well as for the detection of non-coding transcripts and alternative splicing events. In this review, we describe how RNA sequencing enables unbiased interrogation of the abundance and complexity of the transcriptome, and present a typical experimental workflow and bioinformatics tools that are often used for RNA sequencing analysis. We also discuss different uses of this next-generation sequencing technology to evaluate rheumatic disease patients and investigate the pathogenesis of rheumatic diseases such as rheumatoid arthritis, systemic lupus erythematosus, juvenile idiopathic arthritis and Sjögren\u27s syndrome

Visualizing Meta-Features in Proteomic Maps

<p>Abstract</p> <p>Background</p> <p>The steps of a high-throughput proteomics experiment include the separation, differential expression and mass spectrometry-based identification of proteins. However, the last and more challenging step is inferring the biological role of the identified proteins through their association with interaction networks, biological pathways, analysis of the effect of post-translational modifications, and other protein-related information.</p> <p>Results</p> <p>In this paper, we present an integrative visualization methodology that allows combining experimentally produced proteomic features with protein meta-features, typically coming from meta-analysis tools and databases, in synthetic Proteomic Feature Maps. Using three proteomics analysis scenarios, we show that the proposed visualization approach is effective in filtering, navigating and interacting with the proteomics data in order to address visually challenging biological questions. The novelty of our approach lies in the ease of integration of any user-defined proteomic features in easy-to-comprehend visual representations that resemble the familiar 2D-gel images, and can be adapted to the user's needs. The main capabilities of the developed VIP software, which implements the presented visualization methodology, are also highlighted and discussed.</p> <p>Conclusions</p> <p>By using this visualization and the associated VIP software, researchers can explore a complex heterogeneous proteomics dataset from different perspectives in order to address visually important biological queries and formulate new hypotheses for further investigation. VIP is freely available at <url>http://pelopas.uop.gr/~egian/VIP/index.html</url>.</p

The ​oestrogen receptor alpha-regulated lncRNA ​NEAT1 is a critical modulator of prostate cancer

The androgen receptor (AR) plays a central role in establishing an oncogenic cascade that drives prostate cancer progression. Some prostate cancers escape androgen dependence and are often associated with an aggressive phenotype. The oestrogen receptor alpha (ERα) is expressed in prostate cancers, independent of AR status. However, the role of ERα remains elusive. Using a combination of chromatin immunoprecipitation (ChIP) and RNA-sequencing data, we identified an ERα-specific non-coding transcriptome signature. Among putatively ERα-regulated intergenic long non-coding RNAs (lncRNAs), we identified nuclear enriched abundant transcript 1 (NEAT1) as the most significantly overexpressed lncRNA in prostate cancer. Analysis of two large clinical cohorts also revealed that NEAT1 expression is associated with prostate cancer progression. Prostate cancer cells expressing high levels of NEAT1 were recalcitrant to androgen or AR antagonists. Finally, we provide evidence that NEAT1 drives oncogenic growth by altering the epigenetic landscape of target gene promoters to favour transcription

Epigenetic profiles signify cell fate plasticity in unipotent spermatogonial stem and progenitor cells

Spermatogonial stem and progenitor cells (SSCs) generate adult male gametes. During in vitro expansion, these unipotent murine cells spontaneously convert to multipotent adult spermatogonial-derived stem cells (MASCs). Here we investigate this conversion process through integrative transcriptomic and epigenomic analyses. We find in SSCs that promoters essential to maintenance and differentiation of embryonic stem cells (ESCs) are enriched with histone H3-lysine4 and -lysine 27 trimethylations. These bivalent modifications are maintained at most somatic promoters after conversion, bestowing MASCs an ESC-like promoter chromatin. At enhancers, the core pluripotency circuitry is activated partially in SSCs and completely in MASCs, concomitant with loss of germ cell-specific gene expression and initiation of embryonic-like programs. Furthermore, SSCs in vitro maintain the epigenomic characteristics of germ cells in vivo. Our observations suggest that SSCs encode innate plasticity through the epigenome and that both conversion of promoter chromatin states and activation of cell type-specific enhancers are prominent features of reprogramming

IFN-g Induces Histone 3 Lysine 27 Trimethylation in a Small Subset of Promoters to Stably Silence Gene Expression in Human Macrophages

The mechanisms by which IFN-g activates expression of interferon-stimulated genes that have inflammatory and host defense functions are well understood. In contrast, little is known about how IFN-g represses gene expression. By using transcriptomic and epigenomic analysis, we found that stable repression of a small group of genes by IFN-g is associated with recruitment of the histone methyltransferase EZH2 and deposition of the negative mark histone 3 lysine 27 trimethylation (H3K27me3) at their promoters. Repressed genes included MERTK, PPARG, and RANK, which have anti-inflammatory functions and promote osteoclast differentiation. Gene repression and H3K27me3 persisted after IFN-g signaling was terminated, and these silenced genes were no longer responsive to glucocorticoids, IL-4, and M-CSF. These results identify cytokineinduced H3K27 trimethylation as a mechanism that stabilizes gene silencing in macrophages. IFN-ginduced macrophage activation is thus reinforced by a chromatin-based mechanism that blocks antiinflammatory and opposing pathways

Type I IFNs and TNF cooperatively reprogram the macrophage epigenome to promote inflammatory activation

Cross-regulation of Toll-like receptor responses by cytokines is essential for effective host defense, avoidance of toxicity, and homeostasis, but the underlying mechanisms are not well understood. A comprehensive epigenomic approach in human macrophages showed that the proinflammatory cytokines TNF and type I IFNs induce transcriptional cascades that alter chromatin states to broadly reprogram TLR4-induced responses. TNF tolerized inflammatory genes to prevent toxicity, while preserving antiviral and metabolic gene induction. Type I IFNs potentiated TNF inflammatory function by priming chromatin to prevent silencing of inflammatory NF-κB target genes. Priming of chromatin enabled robust transcriptional responses to weak upstream signals. Similar chromatin regulation occurred in human diseases. Our findings reveal that signaling crosstalk between IFNs and TNF is integrated at the level of chromatin to reprogram inflammatory responses, and identify new functions and mechanisms of action of these cytokines

Interferon-γ Regulates Cellular Metabolism and mRNA Translation to Potentiate Macrophage Activation

Interferon-γ (IFN-γ) primes macrophages for enhanced inflammatory activation by Toll-like receptors (TLRs) and microbial killing, but little is known about the regulation of cell metabolism or mRNA translation during priming. We found that IFN-γ regulates human macrophage metabolism and translation by targeting the kinases mTORC1 and MNK that both converge on the selective regulator of translation initiation eIF4E. Physiological downregulation of mTORC1 by IFN-γ was associated with autophagy and translational suppression of repressors of inflammation such as HES1. Genome-wide ribosome profiling in TLR2-stimulated macrophages revealed that IFN-γ selectively modulates the macrophage translatome to promote inflammation, further reprogram metabolic pathways, and modulate protein synthesis. These results add IFN-γ-mediated metabolic reprogramming and translational regulation as key components of classical inflammatory macrophage activation