Genome-wide expression links the electron transfer pathway of Shewanella oneidensis to chemotaxis

<p>Abstract</p> <p>Background</p> <p>By coupling the oxidation of organic substrates to a broad range of terminal electron acceptors (such as nitrate, metals and radionuclides), <it>Shewanella oneidensis </it>MR-1 has the ability to produce current in microbial fuel cells (MFCs). <it>omcA</it>, <it>mtrA</it>, <it>omcB </it>(also known as <it>mtrC</it>), <it>mtrB</it>, and <it>gspF </it>are some known genes of <it>S. oneidensis </it>MR-1 that participate in the process of electron transfer. How does the cell coordinate the expression of these genes? To shed light on this problem, we obtain the gene expression datasets of MR-1 that are recently public-accessible in Gene Expression Omnibus. We utilize the novel statistical method, liquid association (LA), to investigate the complex pattern of gene regulation.</p> <p>Results</p> <p>Through a web of information obtained by our data analysis, a network of transcriptional regulatory relationship between chemotaxis and electron transfer pathways is revealed, highlighting the important roles of the chemotaxis gene <it>cheA-1</it>, the magnesium transporter gene <it>mgtE-1</it>, and a triheme <it>c</it>-type cytochrome gene SO4572.</p> <p>Conclusion</p> <p>We found previously unknown relationship between chemotaxis and electron transfer using LA system. The study has the potential of helping researchers to overcome the intrinsic metabolic limitation of the microorganisms for improving power density output of an MFC.</p

Tissue-specific gene expression templates for accurate molecular characterization of the normal physiological states of multiple human tissues with implication in development and cancer studies

<p>Abstract</p> <p>Background</p> <p>To elucidate the molecular complications in many complex diseases, we argue for the priority to construct a model representing the normal physiological state of a cell/tissue.</p> <p>Results</p> <p>By analyzing three independent microarray datasets on normal human tissues, we established a quantitative molecular model GET, which consists of 24 tissue-specific <it>G</it>ene <it>E</it>xpression <it>T</it>emplates constructed from a set of 56 genes, for predicting 24 distinct tissue types under disease-free condition. 99.2% correctness was reached when a large-scale validation was performed on 61 new datasets to test the tissue-prediction power of GET. Network analysis based on molecular interactions suggests a potential role of these 56 genes in tissue differentiation and carcinogenesis.</p> <p>Applying GET to transcriptomic datasets produced from tissue development studies the results correlated well with developmental stages. Cancerous tissues and cell lines yielded significantly lower correlation with GET than the normal tissues. GET distinguished melanoma from normal skin tissue or benign skin tumor with 96% sensitivity and 89% specificity.</p> <p>Conclusions</p> <p>These results strongly suggest that a normal tissue or cell may uphold its normal functioning and morphology by maintaining specific chemical stoichiometry among genes. The state of stoichiometry can be depicted by a compact set of representative genes such as the 56 genes obtained here. A significant deviation from normal stoichiometry may result in malfunction or abnormal growth of the cells.</p

Contributions to Structured and Unstructured Data Analysis: Liquid Association Computation Acceleration and Word Similarity via Folksonomy

In this thesis, I organize two independent projects into five chapters. The first chapter introduces Liquid Association and our proposed method to accelerate its computation. The second chapter is related to the design of the computational structure for Liquid Association website (LAP3). The third chapter is regarding the application of Liquid Association to Global Health Observatory (GHO) data. The fourth chapter describes a novel method to model the distribution of human ratings on word-similarity. The last chapter focuses on the analysis of the relationship between the knowledge-based approach and the corpus-based approach

Novel Synthetic, Host-defense Peptide Protects Against Organ Injury/Dysfunction in a Rat Model of Severe Hemorrhagic Shock.

OBJECTIVE: To evaluate (1) levels of the host-defense/antimicrobial peptide LL-37 in patients with trauma and hemorrhagic shock (HS) and (2) the effects of a synthetic host-defense peptide; Pep19-4LF on multiple organ failure (MOF) associated with HS. BACKGROUND: HS is a common cause of death in severely injured patients. There is no specific therapy that reduces HS-associated MOF. METHODS: (1) LL-37 was measured in 47 trauma/HS patients admitted to an urban major trauma center. (2) Male Wistar rats were submitted to HS (90 min, target mean arterial pressure: 27-32 mm Hg) or sham operation. Rats were treated with Pep19-4LF [66 (n = 8) or 333 μg/kg · h (n = 8)] or vehicle (n = 12) for 4 hours following resuscitation. RESULTS: Plasma LL-37 was 12-fold higher in patients with trauma/HS compared to healthy volunteers. HS rats treated with Pep19-4LF (high dose) had a higher mean arterial pressure at the end of the 4-hour resuscitation period (79 ± 4 vs 54 ± 5 mm Hg) and less renal dysfunction, liver injury, and lung inflammation than HS rats treated with vehicle. Pep19-4LF enhanced (kidney/liver) the phosphorylation of (1) protein kinase B and (2) endothelial nitric oxide synthase. Pep19-4LF attenuated the HS-induced (1) translocation of p65 from cytosol to nucleus, (2) phosphorylation of IκB kinase on Ser, and (3) phosphorylation of IκBα on Ser resulting in inhibition of nuclear factor kappa B and formation of proinflammatory cytokines. Pep19-4LF prevented the release of tumor necrosis factor alpha caused by heparan sulfate in human mononuclear cells by binding to this damage-associated molecular pattern. CONCLUSIONS: Trauma-associated HS results in release of LL-37. The synthetic host-defense/antimicrobial peptide Pep19-4LF attenuates the organ injury/dysfunction associated with HS