|Commenced in January 2007||Frequency: Monthly||Edition: International||Paper Count: 5|
Hyphal growth and the transcriptional regulation to the host environment are key issues during the pathogenesis of C. albicans. Tec1p is the C. albicans homolog of a TEA transcription factor family, which share a conserved DNA-binding TEA domain in their N-terminal. In order to define a structure-function relationship of the C. albicans Tec1p protein, we constructed several mutations on the N terminal, C terminal or in the TEA binding domain itself by homologous recombination technology. The modifications in the open reading frame of TEC1 were tested for reconstitution of the morphogenetic development of the tec1/tec1 mutant strain CaAS12. Mutation in the TEA consensus sequence did not confer transition to hyphae whereas the reconstitution of the full-length Tec1p has reconstituted hyphal development. A deletion in one of glutamine-rich regions either in the Tec1p N-terminal or the C-terminal in regions of 53-212 or 637–744 aa, respectively, did not restore morphological development in mutant CaAS12 strain. Whereas, the reconstitution with Tec1p mutants other than the glutamate-rich region has restored the morphogenetic switch. Additionally, the deletion of the glutamine-rich region has attenuated the invasive growth and the heat shock resistance of C. albicans. In conclusion, we show that a glutamine-rich region of Tec1p is essential for the hyphal development and mediating adaptation to the host environment of C. albicans.
Kigelia africana (Lam.) Benth. (Bignoniaceae) is a reputed traditional remedy for various human ailments such as skin diseases, microbial infections, melanoma, stomach troubles, metabolic disorders, malaria and general pains. In spite of the fruit being widely used for purposes related to its antibacterial and antifungal properties, the chemical constituents associated with the activity have not been fully identified. To elucidate the active principles, we evaluated the antimicrobial activity of fruit extracts and purified fractions against Staphylococcus aureus, Enterococcus faecalis, Moraxella catarrhalis, Escherichia coli, Candida albicans and Candida tropicalis. Shade-dried fruits were powdered and extracted with hydroalcoholic (1:1) mixture by soaking at room temperature for 72 h. The crude extract was further fractionated by column chromatography, with successive elution using hexane, dichloromethane, ethyl acetate, acetone and methanol. The dichloromethane and ethyl acetate fractions were combined and subjected to column chromatography to furnish a wax and oil from the eluates of 20% and 40% ethyl acetate in hexane, respectively. The GC-MS and GC×GC-MS results revealed that linoleic acid, linolenic acid, palmitic acid, arachidic acid and stearic acid were the major constituents in both oil and wax. The crude hydroalcoholic extract exhibited the strongest activity with MICs of 0.125-0.5 mg/mL, followed by the ethyl acetate (MICs = 0.125-1.0 mg/mL), dichloromethane (MICs = 0.250-2.0 mg/mL), hexane (MICs = 0.25- 2.0 mg/mL), acetone (MICs = 0.5-2.0 mg/mL) and methanol (MICs = 1.0-2.0 mg/mL), whereas the wax (MICs = 2.0-4.0 mg/mL) and oil (MICs = 4.0-8.0 mg/mL) showed poor activity. The study concludes that synergistic interactions of chemical constituents could be responsible for the antimicrobial activity of K. africana fruits, which needs a more holistic approach to understand the mechanism of its antimicrobial activity.
Reverse engineering of full-genomic interaction networks based on compendia of expression data has been successfully applied for a number of model organisms. This study adapts these approaches for an important non-model organism: The major human fungal pathogen Candida albicans. During the infection process, the pathogen can adapt to a wide range of environmental niches and reversibly changes its growth form. Given the importance of these processes, it is important to know how they are regulated. This study presents a reverse engineering strategy able to infer fullgenomic interaction networks for C. albicans based on a linear regression, utilizing the sparseness criterion (LASSO). To overcome the limited amount of expression data and small number of known interactions, we utilize different prior-knowledge sources guiding the network inference to a knowledge driven solution. Since, no database of known interactions for C. albicans exists, we use a textmining system which utilizes full-text research papers to identify known regulatory interactions. By comparing with these known regulatory interactions, we find an optimal value for global modelling parameters weighting the influence of the sparseness criterion and the prior-knowledge. Furthermore, we show that soft integration of prior-knowledge additionally improves the performance. Finally, we compare the performance of our approach to state of the art network inference approaches.
Candida albicans ATCC 10231 had low endogenous activity of the alternative oxidase compared with that of C. albicans ATCC 10261. In C. albicans ATCC 10231 the endogenous activity declined as the cultures aged. Alternative oxidase activity could be induced in C. albicans ATCC 10231 by treatment with cyanide, but the induction of this activity required the presence of oxygen which could be replaced, at least in part, with high concentrations of potassium ferricyanide. We infer from this that the expression of the gene encoding the alternative oxidase is under the control of a redoxsensitive transcription factor.