Molecular regulation of flowering induction in Quercus suber

Dissertação de mestrado em Plant Molecular Biology, Biotechnology and Bioentrepeneurship

Impact of mutated KRAS signalling on autophagy regulation in colorectal carcinoma

Programa Doutoral em Biologia Molecular e Ambiental

Lower NPAS3 expression during the later stages of abnormal lung development in rat congenital diaphragmatic hernia

Purpose Congenital diaphragmatic hernia (CDH) is characterized by a developmental defect in the diaphragm, pulmonary hypoplasia and pulmonary hypertension. NPAS3 is a PAS domain transcription factor regulating Drosophila tracheogenesis. NPAS3 null mice develop pulmonary hypoplasia in utero and die after birth due to respiratory failure. We aimed to evaluate NPAS3 expres- sion during normal and abnormal lung development due to CDH. Methods CDH was induced by administering 100 mg/ml nitrofen to time-pregnant dams on embryonic day (E) 9 of gestation. Lungs were isolated on E15, E18 and E21 and NPAS3 localization was determined by immunohisto- chemistry and quantified using Western blotting. Results We found that only E21 hypoplastic CDH lungs have reduced expression of NPAS3 in the terminal sac- cules. Western blotting confirmed the down-regulation of NPAS3 protein in the nitrofen-induced hypoplastic lungs. Conclusions We demonstrate for the first time that ni- trofen-induced hypoplastic CDH lungs have reduced NPAS3 expression in the terminal saccules during the later stages of abnormal lung development. Our findings suggest that NPAS3 is associated with pulmonary hypoplasia in CDH.

Metabolic engineering with multi-objective optimization of kinetic models

Kinetic models have a great potential for metabolic engineering applications. They can be used for testing which genetic and regulatory modifications can increase the production of metabolites of interest, while simultaneously monitoring other key functions of the host organism. This work presents a methodology for increasing productivity in biotechnological processes exploiting dynamic models. It uses multi-objective dynamic optimization to identify the combination of targets (enzymatic modifications) and the degree of up- or down-regulation that must be performed in order to optimize a set of pre-defined performance metrics subject to process constraints. The capabilities of the approach are demonstrated on a realistic and computationally challenging application: a large-scale metabolic model of Chinese Hamster Ovary cells (CHO), which are used for antibody production in a fed-batch process. The proposed methodology manages to provide a sustained and robust growth in CHO cells, increasing productivity while simultaneously increasing biomass production, product titer, and keeping the concentrations of lactate and ammonia at low values. The approach presented here can be used for optimizing metabolic models by finding the best combination of targets and their optimal level of up/down-regulation. Furthermore, it can accommodate additional trade-offs and constraints with great flexibility.