Kinetics of Bacterial Colony Growth by Laser Induced Fluorescence

The growth kinetics of an aerial bacterial colony on solid agar media was studied using laser induced fluorescence technique. Fluorescence quenching of Rhodamin B by the bacterial colony was utilized for the study. The lag phase, log phase, and stationary phase of growth curve of bacterial colony was identified by measuring peak fluorescence intensity of dye doped bacterial colony.

Studies on Production of Bacterial Xylanases

Xylanases with hydrolytic activity on xylan, one of the hemicellulosic materials present in plant cell walls, have been identified long back and the applicability of this enzyme is constantly growing. All these applications especially the pulp and paper industries require novel enzymes. There has been lot of documentation on microbial xylanases, however, none meeting all the required characteristics. The characters being sought are: higher production, higher pH and temperature optima, good stabilities under these conditions and finally the low associated cellulase and protease production. The present study analyses various facets of xylanase biotechnology giving emphasis on bacterial xylanases. Fungal xylanases are having problems like low pH values for both enzyme activity and growth. Moreover, the associated production of cellulases at significant levels make fungal xylanases less suitable for application in paper and pulp industries.Bacillus SSP-34 selected from 200 isolates was clearly having xylan catabolizing nature distinct from earlier reports. The stabilities at higher temperatures and pH values along with the optimum conditions for pH and temperature is rendering Bacillus SSP-34 xylanase more suitable than many of the previous reports for application in pulp and paper industries.Bacillus SSP-34 is an alkalophilic thertmotolerant bacteria which under optimal cultural conditions as mentioned earlier, can produce 2.5 times more xylanase than the basal medium.The 0.5% xylan concentration in the medium was found to the best carbon source resulting in 366 IU/ml of xylanase activity. This induction was subjected to catabolite repression by glucose. Xylose was a good inducer for xylanase production. The combination of yeast extract and peptone selected from several nitrogen sources resulted in the highest enzyme production (379+-0.2 IU/ml) at the optimum final concentration of 0.5%. All the cultural and nutritional parameters were compiled and comparative study showed that the modified medium resulted in xylanase activity of 506 IU/ml, 5 folds higher than the basal medium.The novel combination of purification techniques like ultrafiltraton, ammonium sulphate fractionation, DEAE Sepharose anion exchange chromatography, CM Sephadex cation exchange chromatography and Gel permeation chromatography resulted in the purified xylanase having a specific activity of 1723 U/mg protein with 33.3% yield. The enzyme was having a molecular weight of 20-22 kDa. The Km of the purified xylanase was 6.5 mg of oat spelts xylan per ml and Vmax 1233 µ mol/min/mg protein.Bacillus SSP-34 xylanase resulted in the ISO brightness increase from 41.1% to 48.5%. The hydrolytic nature of the xylanase was in the endo-form.Thus the organism Bacillus SSP-34 was having interesting biotechnological and physiological aspects. The SSP-34 xylanase having desired characters seems to be suited for application in paper and pulp industries.

“Reconstruction of Gene Regulatory Network from Expression Profile of Plasma RNA Data of Colorectal Cancer Patients using Soft Computing Techniques”

Microarray data analysis is one of data mining tool which is used to extract meaningful information hidden in biological data. One of the major focuses on microarray data analysis is the reconstruction of gene regulatory network that may be used to provide a broader understanding on the functioning of complex cellular systems. Since cancer is a genetic disease arising from the abnormal gene function, the identification of cancerous genes and the regulatory pathways they control will provide a better platform for understanding the tumor formation and development. The major focus of this thesis is to understand the regulation of genes responsible for the development of cancer, particularly colorectal cancer by analyzing the microarray expression data. In this thesis, four computational algorithms namely fuzzy logic algorithm, modified genetic algorithm, dynamic neural fuzzy network and Takagi Sugeno Kang-type recurrent neural fuzzy network are used to extract cancer specific gene regulatory network from plasma RNA dataset of colorectal cancer patients. Plasma RNA is highly attractive for cancer analysis since it requires a collection of small amount of blood and it can be obtained at any time in repetitive fashion allowing the analysis of disease progression and treatment response.

Development and Validation of Bacterial Consortia for Bioremediation of Detritus in Aquaculture Systems

Cochin University Of Science And Technology