GenSensor Suite: A Web-Based Tool for the Analysis of Gene and Protein Interactions, Pathways, and Regulation

The GenSensor Suite consists of four web tools for elucidating relationships among genes and proteins. GenPath results show which biochemical, regulatory, or other gene set categories are over- or under-represented in an input list compared to a background list. All common gene sets are available for searching in GenPath, plus some specialized sets. Users can add custom background lists. GenInteract builds an interaction gene list from a single gene input and then analyzes this in GenPath. GenPubMed uses a PubMed query to identify a list of PubMed IDs, from which a gene list is extracted and queried in GenPath. GenViewer allows the user to query one gene set against another in GenPath. GenPath results are presented with relevant P- and q-values in an uncluttered, fully linked, and integrated table. Users can easily copy this table and paste it directly into a spreadsheet or document

Inflammation-Mediated Regulation of MicroRNA Expression in Transplanted Pancreatic Islets

Nonspecific inflammation in the transplant microenvironment results in β-cell dysfunction and death influencing negatively graft outcome. MicroRNA (miRNA) expression and gene target regulation in transplanted islets are not yet well characterized. We evaluated the impact of inflammation on miRNA expression in transplanted rat islets. Islets exposed in vitro to proinflammatory cytokines and explanted syngeneic islet grafts were evaluated by miRNA arrays. A subset of 26 islet miRNAs was affected by inflammation both in vivo and in vitro. Induction of miRNAs was dependent on NF-κB, a pathway linked with cytokine-mediated islet cell death. RT-PCR confirmed expression of 8 miRNAs. The association between these miRNAs and mRNA target-predicting algorithms in genome-wide RNA studies of β-cell inflammation identified 238 potential miRNA gene targets. Several genes were ontologically associated with regulation of insulin signaling and secretion, diabetes, and islet physiology. One of the most activated miRNAs was miR-21. Overexpression of miR-21 in insulin-secreting MIN6 cells downregulated endogenous expression of the tumor suppressor Pdcd4 and of Pclo, a Ca2+ sensor protein involved in insulin secretion. Bioinformatics identified both as potential targets. The integrated analysis of miRNA and mRNA expression profiles revealed potential targets that may identify molecular targets for therapeutic interventions

Comparative analysis of genome sequences from four strains of the Buchnera aphidicola Mp endosymbion of the green peach aphid, Myzus persicae

BACKGROUND: Myzus persicae, the green peach aphid, is a polyphagous herbivore that feeds from hundreds of species of mostly dicot crop plants. Like other phloem-feeding aphids, M. persicae rely on the endosymbiotic bacterium, Buchnera aphidicola (Buchnera Mp), for biosynthesis of essential amino acids and other nutrients that are not sufficiently abundant in their phloem sap diet. Tobacco-specialized M. persicae are typically red and somewhat distinct from other lineages of this species. To determine whether the endosymbiotic bacteria of M. persicae could play a role in tobacco adaptation, we sequenced the Buchnera Mp genomes from two tobacco-adapted and two non-tobacco M. persicae lineages. RESULTS: With a genome size of 643.5 kb and 579 predicted genes, Buchnera Mp is the largest Buchnera genome sequenced to date. No differences in gene content were found between the four sequenced Buchnera Mp strains. Compared to Buchnera APS from the well-studied pea aphid, Acyrthosiphon pisum, Buchnera Mp has 21 additional genes. These include genes encoding five enzymes required for biosynthesis of the modified nucleoside queosine, the heme pathway enzyme uroporphyrinogen III synthase, and asparaginase. Asparaginase, which is also encoded by the genome of the aphid host, may allow Buchnera Mp to synthesize essential amino acids from asparagine, a relatively abundant phloem amino acid. CONCLUSIONS: Together our results indicate that the obligate intracellular symbiont Buchnera aphidicola does not contribute to the adaptation of Myzus persicae to feeding on tobacco

Developing combinatorial multi-component therapies (CMCT) of drugs that are more specific and have fewer side effects than traditional one drug therapies

Drugs designed for a specific target are always found to have multiple effects. Rather than hope that one bullet can be designed to hit only one target, nonlinear interactions across genomic and proteomic networks could be used to design Combinatorial Multi-Component Therapies (CMCT) that are more targeted with fewer side effects. We show here how computational approaches can be used to predict which combinations of drugs would produce the best effects. Using a nonlinear model of how the output effect depends on multiple input drugs, we show that an artificial neural network can accurately predict the effect of all 215 = 32,768 combinations of drug inputs using only the limited data of the output effect of the drugs presented one-at-a-time and pairs-at-a-time

A comprehensive transcript index of the human genome generated using microarrays and computational approaches

BACKGROUND: Computational and microarray-based experimental approaches were used to generate a comprehensive transcript index for the human genome. Oligonucleotide probes designed from approximately 50,000 known and predicted transcript sequences from the human genome were used to survey transcription from a diverse set of 60 tissues and cell lines using ink-jet microarrays. Further, expression activity over at least six conditions was more generally assessed using genomic tiling arrays consisting of probes tiled through a repeat-masked version of the genomic sequence making up chromosomes 20 and 22. RESULTS: The combination of microarray data with extensive genome annotations resulted in a set of 28,456 experimentally supported transcripts. This set of high-confidence transcripts represents the first experimentally driven annotation of the human genome. In addition, the results from genomic tiling suggest that a large amount of transcription exists outside of annotated regions of the genome and serves as an example of how this activity could be measured on a genome-wide scale. CONCLUSIONS: These data represent one of the most comprehensive assessments of transcriptional activity in the human genome and provide an atlas of human gene expression over a unique set of gene predictions. Before the annotation of the human genome is considered complete, however, the previously unannotated transcriptional activity throughout the genome must be fully characterized

Identifying Consensus Disease Pathways in Parkinson's Disease Using an Integrative Systems Biology Approach

Parkinson's disease (PD) has had six genome-wide association studies (GWAS) conducted as well as several gene expression studies. However, only variants in MAPT and SNCA have been consistently replicated. To improve the utility of these approaches, we applied pathway analyses integrating both GWAS and gene expression. The top 5000 SNPs (p<0.01) from a joint analysis of three existing PD GWAS were identified and each assigned to a gene. For gene expression, rather than the traditional comparison of one anatomical region between sets of patients and controls, we identified differentially expressed genes between adjacent Braak regions in each individual and adjusted using average control expression profiles. Over-represented pathways were calculated using a hyper-geometric statistical comparison. An integrated, systems meta-analysis of the over-represented pathways combined the expression and GWAS results using a Fisher's combined probability test. Four of the top seven pathways from each approach were identical. The top three pathways in the meta-analysis, with their corrected p-values, were axonal guidance (p = 2.8E-07), focal adhesion (p = 7.7E-06) and calcium signaling (p = 2.9E-05). These results support that a systems biology (pathway) approach will provide additional insight into the genetic etiology of PD and that these pathways have both biological and statistical support to be important in PD

Bioinformatics Challenges in Translational Research Invited Keynote Talk

The basic goal of translational research, from a boinformatics perspective, is to relate data acquired from basic research to an outcome in a patient. The relation of data may be following the drug discovery process, where biochemical and protein structure data is linked all the way through to data collected during the clinical trial process and onward. The relation of data can also be associate with better patient care, through techniques like data mining, where data from the research environment is combined with data from the clinical environment and used for hypothesis generation, testing and potential outcomes are implemented. Translation research also requires collaboration between various clinical investigators, physicians, scientists and teams, creating a need for secure data sharing. Inherent to the nature of translational research is the integration of data from multiple systems. Data used for research resides in EMRs, LIMSs, CTMS, and other source systems. For example at the University of Miami, The Miller school and its affiliate Institutes (e.g., Jackson Hospital), have established a number of information systems to support various operational needs. These current systems include Velos (for clinical trials management) Cerner (the Jackson EMR), MetaDatach, (UMH) and IDX. The Miller School is also in the process of implementing a EPIC EMR system. We are developing a system to address the above outlined needs and challenges. It is an integration infrastructure to support translational research, but may also be applied to other data sharing and integration needs throughout UM. The system is currently referred to as UTRIX (UM Translational Research Information eXchange). More specifically, UTRIX features a utility data storage environment (FUSE), a service oriented architecture (SOA), an organization currently referred to as the ”honest broker” (HB) to control access to data, and standard tools and educational programs to support data analysis. FUSE (Flexible Utility Storage Environment) is intended to meet the data storage needs described above. The SOA and HB together address the challenges posed by data access and authorization. FUSE, the SOA and HB together provide a context in which to make available tools and educational programs to enable the data analysis and advance data mining of research data

Viral expression associated with gastrointestinal adenocarcinomas in TCGA high-throughput sequencing data

Up to 20% of cancers worldwide are thought to be associated with microbial pathogens, including bacteria and viruses. The widely used methods of viral infection detection are usually limited to a few a priori suspected viruses in one cancer type. To our knowledge, there have not been many broad screening approaches to address this problem more comprehensively. In this study, we performed a comprehensive screening for viruses in nine common cancers using a multistep computational approach. Tumor transcriptome and genome sequencing data were available from The Cancer Genome Atlas (TCGA). Nine hundred fifty eight primary tumors in nine common cancers with poor prognosis were screened against a non-redundant database of virus sequences. DNA sequences from normal matched tissue specimens were used as controls to test whether each virus is associated with tumors. We identified human papilloma virus type 18 (HPV-18) and four human herpes viruses (HHV) types 4, 5, 6B, and 8, also known as EBV, CMV, roseola virus, and KSHV, in colon, rectal, and stomach adenocarcinomas. In total, 59% of screened gastrointestinal adenocarcinomas (GIA) were positive for at least one virus: 26% for EBV, 21% for CMV, 7% for HHV-6B, and 20% for HPV-18. Over 20% of tumors were co-infected with multiple viruses. Two viruses (EBV and CMV) were statistically significantly associated with colorectal cancers when compared to the matched healthy tissues from the same individuals (p = 0.02 and 0.03, respectively). HPV-18 was not detected in DNA, and thus, no association testing was possible. Nevertheless, HPV-18 expression patterns suggest viral integration in the host genome, consistent with the potentially oncogenic nature of HPV-18 in colorectal adenocarcinomas. The estimated counts of viral copies were below one per cell for all identified viruses and approached the detection limit. Our comprehensive screening for viruses in multiple cancer types using next-generation sequencing data clearly demonstrates the presence of viral sequences in GIA. EBV, CMV, and HPV-18 are potentially causal for GIA, although their oncogenic role is yet to be established

An unusual gene arrangement for the putative chromosome replication origin and circadian expression of dnaN in Synechococcus sp. strain PCC 7942

In eubacteria, the clustering of DnaA boxes around the dnaN (β subunit of DNA polymerase III) and dnaA genes usually defines the chromosome replication origin ( oriC). In this study, the dnaN locus from the cyanobacterium Synechococcus sp. strain PCC 7942 was sequenced. The gene order in this region is cbbZp-dnaN-orf288-purL-purF which contrasts with other eubacteria. A cluster of eleven DnaA boxes (consensus sequence: TTTTCCACA) was found in the intergenic region between dnaN and cbbZp. We also found a 41-bp sequence within this region that is 80% identical to the proposed oriC of Streptomyces coelicolor. Therefore, we propose that this intergenic region may serve as an oriC in Synechococcus. Using bacterial luciferase as a reporter, we also showed that dnaN is rhythmically expressed, suggesting that DNA replication could be under circadian control in this organism