ELUCIDATING GENE SIGNATURES THAT CONTROL THE CIRCADIAN RHYTHM IN CYANOBACTERIA USING BIOINFORMATICS METHODS

poster abstractBackground: The daily light-dark cycle govern rhythmic changes in the behavior and physiology of most species. This circadian rhythm, or bi-ological “clock,” allows the organism to anticipate and prepare for the changes in the physical environment that are associated with day and night, thereby ensuring that the organism carry our specific processes at the right time of the day. Studies have found that the internal clock con-sists of an array of genes and the protein products they encode, which regulate various physiological processes throughout the body. Cyanothece sp. ATCC 51142 is an organism that has both photosynthetic (producing oxygen) and nitrogen fixing ability. The N2-fixing enzyme, nitrogenase, is highly sensitive to oxygen for which it has developed a temporal regula-tion in which N2 fixation and photosynthesis occur at different times throughout a diurnal cycle with very high levels of CO2 fixation during the light and high levels of N2 fixation in the dark. The mechanisms underly-ing the circadian rhythm and the signature genes elucidating this mecha-nism are addressed in this research. Objective: The objective is to integrate gene expression data with da-ta and knowledge from prior studies using bibliomics techniques, in the de novo construction of quasi-complete transcriptional regulatory networks to identify gene signatures in functional motifs and elucidate their role in circadian rhythms in cyanothece sp. ATCC 51142. Methodology: The sequence data of Transcription profiling time se-ries of cyanothece sp. ATCC 51142 grown in 12-hour light/12 hour dark then 24 h light from Array Express was used to construct the initial global regulatory network. Different network topological features (degree, betweeness and eccentricity) are used to identify the signature pathways during the day and night. The genes of the global regulatory network were used to construct networks of homologous species. The functions of the already known genes in well-studied homologous species were mapped to the function of the unannotated genes of cynaothece sp. ATCC 51142. Results: We have identified significant (p<0.05) signature pathways like photosynthesis, pantothenate and CoA biosynthesis and Glyoxylate and dicarboxylate metabolism that operate during the day. And during the night, pathways such as ribosome, riboflavin metabolism, and fatty acid biosynthesis sulfur metabolism were found to be significant (p<0.05). We will further investigate the genes that were already known to be significant using cyanobase database in a particular biological path-way and the novel genes that are identified by bibliomics approach

CLIQUES FOR IDENTIFICATION OF GENE SIGNATURES FOR COLORECTAL CANCER ACROSS POPULATION

poster abstractIntroduction: Colorectal cancer (CRC) is one of the most common cancers diagnosed worldwide. Studies have correlated CRC with dietary habits and environmental conditions. We developed a novel network based approach where cliques and their connectivity profiles explained the variation and similarity in CRC across four populations- China, Germany, Saudi Arabia and USA. Methods: Networks generated after data preprocessing were analyzed individually based on topological and biological features. Using greedy algorithm, cliques of various sizes were identified in each network and size 7 cliques were further analyzed based on their clique connectivity profile (CCP). Our algorithm considered the interaction of cliques based on two parameters: (i) Identification of common (links) genes; (ii) CliqueStrength. The cliques were evaluated by two conditions (a) Maximum number of common genes across cliques and highest CliqueStrength and (b) Minimum number of common genes across cliques and highest CliqueStrength. Results: Large numbers of genes are found to be common between USA, China and Germany. Highly scored nodes based on topological parameters are TP53, SRC, ESR1, SMAD3, GRB2, CREBBP, EGFR, SMAD2, and CSN2KA1. Signal transduction, protein phosphorylation etc., were found to be important GO biological processes. Number of unique size 7 cliques identified in all the population is 650. 49 common cliques identified included genes- EGFR, GRB2, PIK3R1, PTPN6, BRCA1, SMAD2, TP53, CSN2 etc. We found 20 cliques that are uniquely identified for USA, 10 for Germany and one for China. Cliques include genes that are both well studied, less-studied in CRC; but are targets in other cancers. Conclusion: With CCP, we were able to identify commonality, uniqueness and divergence among the populations. Furthermore, comparing all cliques (their CCP) as gene-signatures across populations can help to identify efficient drug targets. Results were consistent with other studies and demonstrate the power of cliques to study CRC across populations

Systems biology approach to obtain significant modules of immune therapy and colorectal cancer

poster abstractColorectal cancer (CRC) is the second leading cause of cancer death in the United States. There has been a lot of research around genes influencing CRC, despite its extensive understanding on the genetic perspective and the emergence of drugs targeting these genes, the tumor progression could be hardly mitigated. However, immune therapy has recently been observed to be effective in CRC treatment and diagnosis. This study focuses on developing a statistically validated multi-feature analytical approach to identify immuno-oncology targets. The features considered in this study were gene expression, DNA methylation, concepts from literature and immuno-cancer pathways. The network algorithm will identify the potentially relevant immuno-oncology modules of CRC. For the study level-3 data (7.2 gigabytes) of gene expression and DNA methylation was obtained from The Cancer Genome Atlas. Around 13000 genes were identified to be significant from the gene expression data analysis and 19000 genes significant in DNA methylation data. The CRC and Immuno-oncology concepts were manually annotated from 50 peer reviewed articles. The output of the preliminary analysis could predict 95 concepts annotated to the 1587 significant genes and were integrated into the network. The top rank concepts in terms of genes associated were ‘apoptosis’, ‘transforming growth factor’, ‘protein arginine methyltransferase’, ‘carcinoembryonic antigen’ and ‘methyl binding protein’. The gene annotated with highest number of concepts was ‘PRMT5’, ‘CSF2’, ‘CFLAR’ and ‘MLH1’. These genes were observed in the literature as targets of CRC

Network based transcription factor analysis of regenerating axolotl limbs

<p>Abstract</p> <p>Background</p> <p>Studies on amphibian limb regeneration began in the early 1700's but we still do not completely understand the cellular and molecular events of this unique process. Understanding a complex biological process such as limb regeneration is more complicated than the knowledge of the individual genes or proteins involved. Here we followed a systems biology approach in an effort to construct the networks and pathways of protein interactions involved in formation of the accumulation blastema in regenerating axolotl limbs.</p> <p>Results</p> <p>We used the human orthologs of proteins previously identified by our research team as bait to identify the transcription factor (TF) pathways and networks that regulate blastema formation in amputated axolotl limbs. The five most connected factors, c-Myc, SP1, HNF4A, ESR1 and p53 regulate ~50% of the proteins in our data. Among these, c-Myc and SP1 regulate 36.2% of the proteins. c-Myc was the most highly connected TF (71 targets). Network analysis showed that TGF-β1 and fibronectin (FN) lead to the activation of these TFs. We found that other TFs known to be involved in epigenetic reprogramming, such as Klf4, Oct4, and Lin28 are also connected to c-Myc and SP1.</p> <p>Conclusions</p> <p>Our study provides a systems biology approach to how different molecular entities inter-connect with each other during the formation of an accumulation blastema in regenerating axolotl limbs. This approach provides an in silico methodology to identify proteins that are not detected by experimental methods such as proteomics but are potentially important to blastema formation. We found that the TFs, c-Myc and SP1 and their target genes could potentially play a central role in limb regeneration. Systems biology has the potential to map out numerous other pathways that are crucial to blastema formation in regeneration-competent limbs, to compare these to the pathways that characterize regeneration-deficient limbs and finally, to identify stem cell markers in regeneration.</p

Proteomic analysis of blastema formation in regenerating axolotl limbs

BACKGROUND: Following amputation, urodele salamander limbs reprogram somatic cells to form a blastema that self-organizes into the missing limb parts to restore the structure and function of the limb. To help understand the molecular basis of blastema formation, we used quantitative label-free liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS)-based methods to analyze changes in the proteome that occurred 1, 4 and 7 days post amputation (dpa) through the mid-tibia/fibula of axolotl hind limbs. RESULTS: We identified 309 unique proteins with significant fold change relative to controls (0 dpa), representing 10 biological process categories: (1) signaling, (2) Ca2+ binding and translocation, (3) transcription, (4) translation, (5) cytoskeleton, (6) extracellular matrix (ECM), (7) metabolism, (8) cell protection, (9) degradation, and (10) cell cycle. In all, 43 proteins exhibited exceptionally high fold changes. Of these, the ecotropic viral integrative factor 5 (EVI5), a cell cycle-related oncoprotein that prevents cells from entering the mitotic phase of the cell cycle prematurely, was of special interest because its fold change was exceptionally high throughout blastema formation. CONCLUSION: Our data were consistent with previous studies indicating the importance of inositol triphosphate and Ca2+ signaling in initiating the ECM and cytoskeletal remodeling characteristic of histolysis and cell dedifferentiation. In addition, the data suggested that blastema formation requires several mechanisms to avoid apoptosis, including reduced metabolism, differential regulation of proapoptotic and antiapoptotic proteins, and initiation of an unfolded protein response (UPR). Since there is virtually no mitosis during blastema formation, we propose that high levels of EVI5 function to arrest dedifferentiated cells somewhere in the G1/S/G2 phases of the cell cycle until they have accumulated under the wound epidermis and enter mitosis in response to neural and epidermal factors. Our findings indicate the general value of quantitative proteomic analysis in understanding the regeneration of complex structures

IUPUI Imaging Research Council

poster abstractAbstract The IUPUI Imaging Research Council was created by the IUPUI Vice Chancellor for Research to provide guidance and direction for expansion of research imaging initiatives across all Schools and Departments within IUPUI. The specific goals of the council are: • To encourage and coordinate collaboration among IUPUI researchers from different disciplines • To provide advice and guidance in the realization of highly competitive large grant proposals that will support and grow the IUPUI imaging efforts into major nationally and internationally recognized programs • To develop a strategic plan that will enable IUPUI to become nationally and internationally known as the place for imaging research and its applications • To determine strategic areas of strength and growth • To determine available and needed resources • To determine strategic external partnerships Activities organized by the council to date include sponsoring an IUPUI Imaging Research Workshop on November 17, 2011. This workshop consisted of invited presentations, a poster session, and working group breakout sessions. Working groups explored research opportunities and needs in four priority areas (neuroscience, cancer, cardiovascular disease, and remote sensing). The council has recently initiated a monthly seminar series and is actively developing an IUPUI research imaging strategic plan. For more information visit the IUPUI Imaging Research Initiative website at www.imaging.iupui.edu

Identification of a gene signature in cell cycle pathway for breast cancer prognosis using gene expression profiling data

<p>Abstract</p> <p>Background</p> <p>Numerous studies have used microarrays to identify gene signatures for predicting cancer patient clinical outcome and responses to chemotherapy. However, the potential impact of gene expression profiling in cancer diagnosis, prognosis and development of personalized treatment may not be fully exploited due to the lack of consensus gene signatures and poor understanding of the underlying molecular mechanisms.</p> <p>Methods</p> <p>We developed a novel approach to derive gene signatures for breast cancer prognosis in the context of known biological pathways. Using unsupervised methods, cancer patients were separated into distinct groups based on gene expression patterns in one of the following pathways: apoptosis, cell cycle, angiogenesis, metastasis, p53, DNA repair, and several receptor-mediated signaling pathways including chemokines, EGF, FGF, HIF, MAP kinase, JAK and NF-κB. The survival probabilities were then compared between the patient groups to determine if differential gene expression in a specific pathway is correlated with differential survival.</p> <p>Results</p> <p>Our results revealed expression of cell cycle genes is strongly predictive of breast cancer outcomes. We further confirmed this observation by building a cell cycle gene signature model using supervised methods. Validated in multiple independent datasets, the cell cycle gene signature is a more accurate predictor for breast cancer clinical outcome than the previously identified Amsterdam 70-gene signature that has been developed into a FDA approved clinical test MammaPrint^®.</p> <p>Conclusion</p> <p>Taken together, the gene expression signature model we developed from well defined pathways is not only a consistently powerful prognosticator but also mechanistically linked to cancer biology. Our approach provides an alternative to the current methodology of identifying gene expression markers for cancer prognosis and drug responses using the whole genome gene expression data.</p

Cliques for the identification of gene signatures for colorectal cancer across population

<p>Abstract</p> <p>Background</p> <p>Colorectal cancer (CRC) is one of the most commonly diagnosed cancers worldwide. Studies have correlated risk of CRC development with dietary habits and environmental conditions. Gene signatures for any disease can identify the key biological processes, which is especially useful in studying cancer development. Such processes can be used to evaluate potential drug targets. Though recognition of CRC gene-signatures across populations is crucial to better understanding potential novel treatment options for CRC, it remains a challenging task.</p> <p>Results</p> <p>We developed a topological and biological feature-based network approach for identifying the gene signatures across populations. In this work, we propose a novel approach of using cliques to understand the variability within population. Cliques are more conserved and co-expressed, therefore allowing identification and comparison of cliques across a population which can help researchers study gene variations. Our study was based on four publicly available expression datasets belonging to four different populations across the world. We identified cliques of various sizes (0 to 7) across the four population networks. Cliques of size seven were further analyzed across populations for their commonality and uniqueness. Forty-nine common cliques of size seven were identified. These cliques were further analyzed based on their connectivity profiles. We found associations between the cliques and their connectivity profiles across networks. With these clique connectivity profiles (CCPs), we were able to identify the divergence among the populations, important biological processes (cell cycle, signal transduction, and cell differentiation), and related gene pathways. Therefore the genes identified in these cliques and their connectivity profiles can be defined as the gene-signatures across populations. In this work we demonstrate the power and effectiveness of cliques to study CRC across populations.</p> <p>Conclusions</p> <p>We developed a new approach where cliques and their connectivity profiles helped elucidate the variation and similarity in CRC gene profiles across four populations with unique dietary habits.</p