The Role of Anti-dengue Virus NS-1 and Anti-protein Disulfide Isomerase Antibodies on Platelet Aggregation in Secondary Dengue Infection

Aim: to observe the correlation between anti-NS-1 and anti PDI antibodies against platelets function disorder on secondary dengue infection. Methods: 50 patients with secondary DV infection according to WHO criteria were observed by a cross sectional study. Patient’s blood was collected on day 3, 5 and 7 after fever onset. Platelets aggregation test was done to prove the possibility of platelets dysfunction. Anti-NS-1 and anti- PDI antibodies were determined by solid phase ELISA. Results: the inhibition of platelets aggregation was increased among day of observation. Means value of inhibition on day 3 is 46.6%, day 5 is 52.5% and day 7 is 56%. There is a significant difference (p0.05). Conclusion: the kinetics profile of NS1 and PDI antibodies responses, which were detected by the third day of symptoms. Dengue patients’ sera inhibited platelets aggregation. NS-1 antibodies and PDI antibodies might have a role on the platelets aggregation dysfunction; however, there is no correlation between them. It is possible that other mechanism involve in the inhibition of platelets aggregation.Key words: anti-NS-1 antibodies, anti PDI antibodies, inhibition platelets aggregation, secondary dengue infection

In silico study to breaking mystery of bioluminescence protein structure of bacterial luciferase and firefly luciferase

Bioluminescent proteins such as luciferase or green fluorescent protein become an interesting protein to be studied particularly on its structure, mechanism of light emission in certain wavelength and also its contribution in several applications. This study was conducted to understand more on the luciferase enzymes from bacteria and firefly based on in silico studies of their protein sequences, protein surface and interactions with different substrates. Protein crystal structures of bacterial luciferase and firefly luciferase that been deposited on Protein Data Bank (PDB) were used as model proteins for this study. Computer analysis of luciferase proteins such as pI prediction, multiple sequence alignment and molecular docking with different luciferase substrates (Flavin mononucleotide, L-luciferin, D-luciferin, vargulin, coelectrazine, Dinoflagellate luciferin, Latia luciferin) by using iGEMDOCK docking software had been conducted. Final analysis showed that, the bacterial luciferase prefers flavin mononucleotide and latia luciferin as its substrates and for firefly luciferase, it prefers dinoflagellate luciferin, L-luciferin and D-luciferin as the substrates. Bacterial luciferase and firefly luciferase shared very low protein sequence homology (&lt;30%) although they have similar catalyzing function. Prediction of pI by using ProtParam tool showed that bacterial luciferase and firefly luciferase has pI values of 4.95 and 6.42, respectively. In conclusion, bacterial and firefly luciferase can consider several different of luciferin in enzyme catalysis.</jats:p

Isolation and Characterization of A Heavy Metal-Tolerant Diesel Oil - Degrading Strain

&#x0D; A diesel-degrading bacterium has been isolated from a local university soil. The isolate was tentatively identified as Burkholderia sp. strain DRY27 based on the carbon utilization profiles using Biolog GN plates and partial 16S rDNA molecular phylogeny. Isolate 27 showed an increase cellular growth with respect to diesel concentrations from 0% until 3% where the optimum growth occurring at 3% (v/v) diesel concentration. Based on the optimization studies, sodium nitrate proved to be the best nitrogen source. Sodium nitrate was optimum at 7.7 gl-1 .The optimal temperature and optimal pH for this bacterium was between 10 to 40 oC and pH 7.5 to pH 8.5 respectively. Diesel components was proven to be completely removed from the reduction in the hydrocarbon peaks monitored by Solid Phase Microextraction Gas Chromatography analysis. These prove that this bacterium is the right bacterium for bioremediation of diesel spills and pollution in the tropics.&#x0D; </jats:p

Mathematical modelling of the degradation kinetics of Bacillus cereus grown on phenol

The mathematical modelling of the effect of substrate concentration on growth rate of bacteria is crucial in the understanding of the many phenomena in xenobiotics biodegradation. The rate constants obtained from this modeling allow the mathematical prediction of growth parameters. We remodelled a previously published work on phenol degradation by Bacillus cereus MTCC9817 strain AKG1 using several more growth kinetic models such as Monod, Teissier, Andrews and Noack, Hinshelwood, Moser, Aiba, Webb (Edward), Yano and Koga, Han and Levenspiel and Luong and evaluated the accuracy of the fitted model using statistical analysis such as Root Mean Square (RMSE), adjusted Coefficient of Determination (R2), corrected Akaike InformationCriterion (AICc), Bias Factor, Accuracy Factor and F-test. The calculated values for the best model- Luong’s such as maximal degradation rate, half saturation constant for maximal degradation, maximal concentration of substrate tolerated and curve parameter that defines the steepness of the growth rate decline from the maximum rate, symbolized by qmax, Ks, Sm, and n were 0.755 hr-1, 925.8 mg/L, 1859.3 mg/L and 0.329, respectively. The true value of qmaxdetermined as the value where the gradient for the slope is zero was 0.093 h-1 at 500 mg/L phenol. The results indicate that the exhaustive use of mathematical models on available published results could gleam new optimal models that can provide new knowledge on the way toxic substanceinhibit growth rate in microbes.</jats:p