Browsing by Author "Tawa, Gregory J"
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- ItemCharacterization of chemically induced liver injuries using gene co-expression modules.(2014-09-17) Tawa, Gregory J; AbdulHameed, Mohamed Diwan M; Yu, Xueping; Kumar, Kamal; Ippolito, Danielle L; Lewis, John A; Stallings, Jonathan D; Wallqvist, AndersLiver injuries due to ingestion or exposure to chemicals and industrial toxicants pose a serious health risk that may be hard to assess due to a lack of non invasive diagnostic tests Mapping chemical injuries to organ specific damage and clinical outcomes via biomarkers or biomarker panels will provide the foundation for highly specific and robust diagnostic tests Here we have used DrugMatrix a toxicogenomics database containing organ specific gene expression data matched to dose dependent chemical exposures and adverse clinical pathology assessments in Sprague Dawley rats to identify groups of co expressed genes modules specific to injury endpoints in the liver We identified 78 such gene co expression modules associated with 25 diverse injury endpoints categorized from clinical pathology organ weight changes and histopathology Using gene expression data associated with an injury condition we showed that these modules exhibited different patterns of activation characteristic of each injury We further showed that specific module genes mapped to 1 known biochemical pathways associated with liver injuries and 2 clinically used diagnostic tests for liver fibrosis As such the gene modules have characteristics of both generalized and specific toxic response pathways Using these results we proposed three gene signature sets characteristic of liver fibrosis steatosis and general liver injury based on genes from the co expression modules Out of all 92 identified genes 18 20 genes have well documented relationships with liver disease whereas the rest are novel and have not previously been associated with liver disease In conclusion identifying gene co expression modules associated with chemically induced liver injuries aids in generating testable hypotheses and has the potential to identify putative biomarkers of adverse health effects
- ItemExploiting large-scale drug-protein interaction information for computational drug repurposing.(2014-07-03) Liu, Ruifeng; Singh, Narender; Tawa, Gregory J; Wallqvist, Anders; Reifman, JaquesDespite increased investment in pharmaceutical research and development fewer and fewer new drugs are entering the marketplace This has prompted studies in repurposing existing drugs for use against diseases with unmet medical needs A popular approach is to develop a classification model based on drugs with and without a desired therapeutic effect For this approach to be statistically sound it requires a large number of drugs in both classes However given few or no approved drugs for the diseases of highest medical urgency and interest different strategies need to be investigated
- ItemIdentifying cytochrome p450 functional networks and their allosteric regulatory elements.(2013-12-06) Liu, Jin; Tawa, Gregory J; Wallqvist, AndersCytochrome P450 CYP enzymes play key roles in drug metabolism and adverse drug drug interactions Despite tremendous efforts in the past decades essential questions regarding the function and activity of CYPs remain unanswered Here we used a combination of sequence based co evolutionary analysis and structure based anisotropic thermal diffusion ATD molecular dynamics simulations to detect allosteric networks of amino acid residues and characterize their biological and molecular functions We investigated four CYP subfamilies CYP1A CYP2D CYP2C and CYP3A that are involved in 90 of all metabolic drug transformations and identified four amino acid interaction networks associated with specific CYP functionalities i e membrane binding heme binding catalytic activity and dimerization Interestingly we did not detect any co evolved substrate binding network suggesting that substrate recognition is specific for each subfamily Analysis of the membrane binding networks revealed that different CYP proteins adopt different membrane bound orientations consistent with the differing substrate preference for each isoform The catalytic networks were associated with conservation of catalytic function among CYP isoforms whereas the dimerization network was specific to different CYP isoforms We further applied low temperature ATD simulations to verify proposed allosteric sites associated with the heme binding network and their role in regulating metabolic fate Our approach allowed for a broad characterization of CYP properties such as membrane interactions catalytic mechanisms dimerization and linking these to groups of residues that can serve as allosteric regulators The presented combined co evolutionary analysis and ATD simulation approach is also generally applicable to other biological systems where allostery plays a role
- ItemA systems biology strategy to identify molecular mechanisms of action and protein indicators of traumatic brain injury.(2014-12-17) Yu, Chenggang; Boutté, Angela; Yu, Xueping; Dutta, Bhaskar; Feala, Jacob D; Schmid, Kara; Dave, Jitendra; Tawa, Gregory J; Wallqvist, Anders; Reifman, JaquesThe multifactorial nature of traumatic brain injury TBI especially the complex secondary tissue injury involving intertwined networks of molecular pathways that mediate cellular behavior has confounded attempts to elucidate the pathology underlying the progression of TBI Here systems biology strategies are exploited to identify novel molecular mechanisms and protein indicators of brain injury To this end we performed a meta analysis of four distinct high throughput gene expression studies involving different animal models of TBI By using canonical pathways and a large human protein interaction network as a scaffold we separately overlaid the gene expression data from each study to identify molecular signatures that were conserved across the different studies At 24 hr after injury the significantly activated molecular signatures were nonspecific to TBI whereas the significantly suppressed molecular signatures were specific to the nervous system In particular we identified a suppressed subnetwork consisting of 58 highly interacting coregulated proteins associated with synaptic function We selected three proteins from this subnetwork postsynaptic density protein 95 nitric oxide synthase 1 and disrupted in schizophrenia 1 and hypothesized that their abundance would be significantly reduced after TBI In a penetrating ballistic like brain injury rat model of severe TBI Western blot analysis confirmed our hypothesis In addition our analysis recovered 12 previously identified protein biomarkers of TBI The results suggest that systems biology may provide an efficient high yield approach to generate testable hypotheses that can be experimentally validated to identify novel mechanisms of action and molecular indicators of TBI
- ItemSystems level analysis and identification of pathways and networks associated with liver fibrosis.(2014-11-08) AbdulHameed, Mohamed Diwan M; Tawa, Gregory J; Kumar, Kamal; Ippolito, Danielle L; Lewis, John A; Stallings, Jonathan D; Wallqvist, AndersToxic liver injury causes necrosis and fibrosis which may lead to cirrhosis and liver failure Despite recent progress in understanding the mechanism of liver fibrosis our knowledge of the molecular level details of this disease is still incomplete The elucidation of networks and pathways associated with liver fibrosis can provide insight into the underlying molecular mechanisms of the disease as well as identify potential diagnostic or prognostic biomarkers Towards this end we analyzed rat gene expression data from a range of chemical exposures that produced observable periportal liver fibrosis as documented in DrugMatrix a publicly available toxicogenomics database We identified genes relevant to liver fibrosis using standard differential expression and co expression analyses and then used these genes in pathway enrichment and protein protein interaction PPI network analyses We identified a PPI network module associated with liver fibrosis that includes known liver fibrosis relevant genes such as tissue inhibitor of metalloproteinase 1 galectin 3 connective tissue growth factor and lipocalin 2 We also identified several new genes such as perilipin 3 legumain and myocilin which were associated with liver fibrosis We further analyzed the expression pattern of the genes in the PPI network module across a wide range of 640 chemical exposure conditions in DrugMatrix and identified early indications of liver fibrosis for carbon tetrachloride and lipopolysaccharide exposures Although it is well known that carbon tetrachloride and lipopolysaccharide can cause liver fibrosis our network analysis was able to link these compounds to potential fibrotic damage before histopathological changes associated with liver fibrosis appeared These results demonstrated that our approach is capable of identifying early stage indicators of liver fibrosis and underscore its potential to aid in predictive toxicity biomarker identification and to generally identify disease relevant pathways