Non-stationary 13C-Metabolic flux analysis of cyanobacteria.
13C-MFA technique has been extremely helpful to quantify intracellular reaction rates. The technique requires recursive fitting of experimentally observed patterns of 13C labeling of metabolites. Non stationary 13C-MFA specifically makes the use of systems that are in metabolic steady state but in a state of transition in terms of isotope labeling. Although more challenging, the non-stationary 13C-MFA is a preferred tool to probe cellular metabolism and provides better perspective to reaction rates. In our group, we have developed a novel pipeline for the collection of labelling data for over 100 metabolites and fragments using LC/MS/MS. The proposed work involves improvement of this pipeline and 13C-MFA of non-model organisms such as cyanobacteria. The work will provide insights into efficiency of the metabolic network and flexibility at crucial node points. The work becomes a guide for classical metabolic engineering. The student will be involved in experimental as well as computational part of work. During the initial years of PhD, the student will be expected to learn the various computational aspects such as metabolic modeling and flux analysis. Basic proficiency in mathematics and programming is expected.