REACTIVE OXYGEN SPECIES AS POSSIBLE MEDIATOR OF ANTIBACTERIAL ACTIVITY OF PARKIA JAVANICA, AGAINST BACTERIAL SPECIES PREDOMINANTLY FOUND IN CHRONIC WOUND.

The crude methanol extract of Parkia javanica was screened for antibacterial activity. against bacterial species predominantly found in chronic wound, by serial dilution technique. Growth kinetics study was performed and percentage of ROS production was measured by NBT reduction assay. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were obtained with a range of IC100 5-40 mg/ml in case of standard bacterial strains. The lag phase of all extract treated bacteria is extended compared to untreated cells. The normalized % of ROS is increased in presence of crude extract. This study suggests that the crude methanol extract of Parkia javanica possesses promising antimicrobial substances which are having activity against Standard ATCC bacterial species and ROS induced DNA damage could be the possible mediator of its antimicrobial activity. Keywords: Parkia javanica, antibacterial activity, standard ATCC bacterial strains, growth curve, ROS, DNA damag

Impact of safety-related dose reductions or discontinuations on sustained virologic response in HCV-infected patients: Results from the GUARD-C Cohort

BACKGROUND: Despite the introduction of direct-acting antiviral agents for chronic hepatitis C virus (HCV) infection, peginterferon alfa/ribavirin remains relevant in many resource-constrained settings. The non-randomized GUARD-C cohort investigated baseline predictors of safety-related dose reductions or discontinuations (sr-RD) and their impact on sustained virologic response (SVR) in patients receiving peginterferon alfa/ribavirin in routine practice. METHODS: A total of 3181 HCV-mono-infected treatment-naive patients were assigned to 24 or 48 weeks of peginterferon alfa/ribavirin by their physician. Patients were categorized by time-to-first sr-RD (Week 4/12). Detailed analyses of the impact of sr-RD on SVR24 (HCV RNA <50 IU/mL) were conducted in 951 Caucasian, noncirrhotic genotype (G)1 patients assigned to peginterferon alfa-2a/ribavirin for 48 weeks. The probability of SVR24 was identified by a baseline scoring system (range: 0-9 points) on which scores of 5 to 9 and <5 represent high and low probability of SVR24, respectively. RESULTS: SVR24 rates were 46.1% (754/1634), 77.1% (279/362), 68.0% (514/756), and 51.3% (203/396), respectively, in G1, 2, 3, and 4 patients. Overall, 16.9% and 21.8% patients experienced 651 sr-RD for peginterferon alfa and ribavirin, respectively. Among Caucasian noncirrhotic G1 patients: female sex, lower body mass index, pre-existing cardiovascular/pulmonary disease, and low hematological indices were prognostic factors of sr-RD; SVR24 was lower in patients with 651 vs. no sr-RD by Week 4 (37.9% vs. 54.4%; P = 0.0046) and Week 12 (41.7% vs. 55.3%; P = 0.0016); sr-RD by Week 4/12 significantly reduced SVR24 in patients with scores <5 but not 655. CONCLUSIONS: In conclusion, sr-RD to peginterferon alfa-2a/ribavirin significantly impacts on SVR24 rates in treatment-naive G1 noncirrhotic Caucasian patients. Baseline characteristics can help select patients with a high probability of SVR24 and a low probability of sr-RD with peginterferon alfa-2a/ribavirin

Systems Analysis of Eukaryotic Proteomic Regulatory Mechanisms

I studied three biological problems in my dissertation research. The problems involved flow of information into the cells from outside, the regulation of information flow by the ribosomes in protein synthesis, and the disruption of information flow due to microsatellite repeat expansions leading to a human disease myotonic dystrophy. In the first study, I built a conceptual basis for interpreting and understanding the cellular responses to multiple concurrent stimuli. A gene represents the inherent information of the cells while a stimulus represents the information outside their boundary. Since a gene and a stimulus are both packets of information, they can be considered analogues. Therefore, the concepts of gene interactions can be applied to the study of modulation of cellular processes by stimuli. This assumption allowed me to define the concepts of environmental interactions and environmental epistasis in terms of gene interactions and genetic epistasis. I used proteomic and transcriptomic changes in Saccharomyces cerevisiae to test the conceptual framework. In the second study, I designed and performed experiments to test the ribosome filter hypothesis. The ribosome filter hypothesis says that the amount of information flow from a transcript to a protein is regulated by the compositions of the subpopulations of ribosomes in a cell. The composition of a ribosome determines its interactions with the mRNA and accessory factors, which in turn determine the efficiency of translation of a transcript. Therefore, to efficiently translate the proteome required for growing in one environmental condition would require a specific complement of ribosomes with different compositions. The required complement of ribosomes will be different for a cell growing in a different environmental condition. A difference in the protein composition of ribosomes from cells growing in two different conditions would be evidence supporting the ribosome filter hypothesis. It would allow identification of candidate ribosomal proteins, or their post-translation modifications that regulate information flow from specific transcripts. I used growth of S. cerevisiae with fermentable carbon source, glucose, and non-fermentable carbon source, glycerol, as two conditions. I used iTRAQ labeling based quantitative proteomics as well as, in collaboration with the Joachim Frank lab, cryo-electron microscopy to measure the changes in protein composition of ribosomes. I used yeast genetics and polysome profiling to measure the effect of loss of function of a candidate ribosomal protein, Rpl8a or Rpl8b, on translation. In the third project, I studied the changes introduced in the skeletal muscle proteome of myotonic dystrophy patients, both type 1 and 2, due to the disruption of information flow by microsatellite repeat expansions in the non-coding regions of mRNA transcripts. I used iTRAQ labeling based quantitative proteomics analysis to quantitate the changes in the skeletal muscle proteome of DM patients compared to healthy volunteers. I identified differentially present proteins and used pathway analysis to understand their role in the pathogenesis. I have identified a number of candidate proteins that are interesting targets for more in depth genetic and biochemical studies including a ribosomal protein RPL13A, previously implicated in regulating information flow by translational inhibition of transcripts containing the GAIT sequence motif. In summary, I have studied three different ways the information content of cells and tissues are affected

DEAD/H-Box Helicases in Immunity, Inflammation, Cell Differentiation, and Cell Death and Disease

DEAD/H-box proteins are the largest family of RNA helicases in mammalian genomes, and they are present in all kingdoms of life. Since their discovery in the late 1980s, DEAD/H-box family proteins have been a major focus of study. They have been found to play central roles in RNA metabolism, gene expression, signal transduction, programmed cell death, and the immune response to bacterial and viral infections. Aberrant functions of DEAD/H-box proteins have been implicated in a wide range of human diseases that include cancer, neurodegeneration, and inherited genetic disorders. In this review, we provide a historical context and discuss the molecular functions of DEAD/H-box proteins, highlighting the recent discoveries linking their dysregulation to human diseases. We will also discuss the state of knowledge regarding two specific DEAD/H-box proteins that have critical roles in immune responses and programmed cell death, DDX3X and DDX58, also known as RIG-I. Given their importance in homeostasis and disease, an improved understanding of DEAD/H-box protein biology and protein–protein interactions will be critical for informing strategies to counteract the pathogenesis associated with several human diseases

Proteins in different environmental interaction classes and the corresponding enriched pathways after concurrent G and HT stimuli.

<p>The color bar shows the range of fold changes. Pathway analysis was done using <i>GeneMANIA</i> Cytoscape plugin[<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0134099#pone.0134099.ref042" target="_blank">42</a>]. Bar graphs were generated in <i>Graphpad Prism</i>. A) Non-specific environmental response (NER) proteins to individual and concurrent HT and G environmental stimuli. The theoretical expression patterns are shown in the top panel. The fold changes of 175 NER proteins are shown as a heatmap. B) The theoretical expression patterns for discordant environmental interaction are shown in the top panel. The fold changes of 41 proteins are shown as a heatmap. C) The theoretical expression patterns for suppression environmental interaction are shown in the top panel. The fold changes of the 58 proteins affected by suppression are shown as a heatmap. D) Bar graph shows the–log q-value of enrichments for the top 5 pathways for the non-specific environmental response proteins. E) Bar graph shows the–log q-value of enrichments for the top 5 pathways in the list of proteins affected by discordant environmental interaction. F) Bar graph shows the–log q-value of enrichments for the top 5 pathways in the list of proteins affected by suppression environmental interaction.</p

Proteomic responses to complex environmental stimuli.

<p>Diploid <i>S</i>. <i>cerevisiae</i> (BY4743) cells were grown in rich media under 4 conditions: 1) glucose as the carbon source at 30°C, 2) glycerol as the carbon source at 30°C, 3) glucose at 37°C, and 4) glycerol at 37°C. Three biological replicates for each growth conditions were performed. Fold changes were calculated from iTRAQ reporter ion intensities using reporter ion intensities from the pooled replicates of growth in glucose as the carbon source at 30°C as the baseline. The fold changes were log₂ transformed for downstream analysis. The color bar shows the fold change range. A) Complete filtered proteomic dataset for high temperature stimulus (HT), glycerol stimulus (G), and concurrent glycerol and high temperature stimuli (HT+G) (Red: Up, Green: Down, Black: No change). The heatmap represents the fold changes of 466 proteins. B) Fold changes of 283 proteins differentially expressed in response to HT stimulus. C) Bar graph shows the–log q-value of enrichments of the top 5 pathways in the list of proteins differentially expressed after the HT stimulus. D) Fold changes of 379 proteins differentially expressed in response to the G stimulus. E) Bar graph shows the–log q-value of enrichments of the top 5 pathways in the list of proteins differentially expressed after the G stimulus.</p

Environmental epistasis in the proteomic response to concurrent stimuli.

<p>Pathway analysis was done using the <i>GeneMANIA</i> Cytoscape plugin[<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0134099#pone.0134099.ref042" target="_blank">42</a>]. Bar graphs were generated in <i>Graphpad Prism</i>. A) Bar graph shows the–log q-value of enrichments of the top 10 pathways in the list of proteins affected by epistasis (purple) and their–log q-value in the list of proteins not affected by epistasis (orange). B) Bar graph shows the–log q-value of enrichments of the top 10 pathways in the list of proteins not affected by epistasis (orange) and their–log q-value in the list of proteins affected by epistasis (purple).</p

Environmental interactions affect transcriptomic profiles as well.

<p>Normalized expression data from <i>Knijnenburg et</i>. <i>al</i>. <i>2009</i> was used for the analyses. The transcriptomic data used in the study used haploid <i>S</i>. <i>cerevisiae</i> cells (CEN.PK113-7D MATa) grown in carbon limited chemostat cultures under 4 conditions – 1) ammonium sulfate as nitrogen source (n = 5), 2) methionine as nitrogen source, NS stimulus (n = 3), 3) Anaerobic condition, AN stimulus (n = 4), and 4) methionine as nitrogen source under anaerobic conditions NS+AN stimulus (n = 3) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0134099#pone.0134099.ref013" target="_blank">13</a>]. Fold changes were calculated from normalized expression data using average normalized expression data from the five replicates of growth with ammonium sulfate as the baseline. The color bar shows the range of fold changes. Pathway analysis was done using <i>GeneMANIA</i> Cytoscape plugin[<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0134099#pone.0134099.ref042" target="_blank">42</a>]. Bar graphs were generated in <i>Graphpad Prism</i>. A) A heatmap of fold changes of the complete transcriptomics dataset consisting of 6551 transcripts. B) A heatmap showing the fold changes for 281 transcripts for which NS stimulus is dominant. C) The–log q-value of enrichment for the top 5 pathways enriched in the list of transcripts for which NS stimulus is dominant. As anticipated, pathways expected to be involved in metabolization of methionine are enriched. D) A heatmap showing the fold changes for 938 transcripts for which AN stimulus is dominant. E) The–log q-value of enrichment for the top 5 pathways enriched in the list of transcripts for which AN stimulus is dominant. As anticipated, pathways expected to be involved in energy production are enriched.</p