From light to dark: mapping fluxes of model cyanobacteria for biofuel applications

Cyanobacteria are a diverse class of prokaryotes that are the simplest oxygenic photoautotrophs. They harvest light energy during the daytime to assimilate inorganic carbon (predominately CO2 and HCO3-) from the environment. Photosynthetically fixed carbons are used to synthesize the majority of cellular components, including proteins, lipids, carbohydrates, nucleic acids, pigments, etc. that are used for diverse functions. Among these, proteins are the major carbon products formed during growth in excess nutrients and light, when cell division is fastest. By contrast, carbohydrates, typically glycogen, accumulate during periods of nutrient limitation in sufficient light and CO2. They serve as carbon and energy storage components for dark periods when light energy is low (no photophosphorylation) or carbon is scarce. These two biomass components together may account for up to 85% of the cellular dry weight. Now, scientists are using technologies to try to make cyanobacterial “cell factories” that produce valuable chemicals and biofuel. Accomplishing such ambitious redesign requires a comprehensive understanding of cyanobacterial metabolism at a system level picture under various conditions. The objective of the first part of this thesis was to quantitatively measure and predict the carbon flux distributions in a model cyanobacterium Synechococcus sp. PCC 7002 under various light and nutrient conditions. For this, I employed two different approaches, flux balance analysis (FBA) and metabolic flux analysis (MFA), to map carbon flux distributions under different growth conditions. The FBA approach is simplest to apply but more primitive. It relies upon a steady-state (non-kinetic) representation of enzymatic fluxes between metabolites inferred to exist based on the presence in the genome of encoded enzymes and from comparison to classical pathways. FBA was able to simulate one important metabolic transition: from active carbon allocation (growth) to carbon and energy storage mode that occurs as light intensity increases. Integration of transcriptomic information with the FBA modeling further enabled the prediction of steady-state carbon flux distribution under nitrogen deprivation. The relative flux of fixed carbon into storage carbohydrates under nitrogen deprivation was predicted to increase by 200%, compared to a predicted 30% decrease of carbon flux through the lower glycolytic pathway and into the TCA cycle. This prediction was validated by the experimental-based MFA approach that measures metabolic flux directly using 13C-labelled precursors. In addition to quantifying the carbon fluxes into different terminal products, the FBA and MFA approaches together illustrated several important metabolic routes that were overlooked by scientists in the past. The FBA approach predicted a hybrid gluconeogenesis-pentose phosphate (hGPP) pathway was equally possible to convert fixed CO2 intermediates into glycogen, rather than the conventional gluconeogenesis-only pathway. Using the MFA approach, I provided quantitative experimental proof showing the alternative hGPP pathway to be the major pathway under nitrogen deprivation, 4.4-fold more active than conventional gluconeogenesis. Again using 13C-labelling and the MFA approach, I generated quantitative results proving that the newly discovered pair of enzymes of the succinic semialdehyde (SSA) shunt, previously postulated to complete the TCA cycle of cyanobacteria (AKG SSA SUCC), actually operate to catalyze these reactions during photosynthesis. Furthermore, deletion of one or both of these enzymes led to a 10~15% reduction of the photosynthetic growth rate, and 50~80% reduction of the pool size of the downstream product, succinate. The MFA results showed the flux through the SSA shunt accounts for > 6.4% of the corresponding RuBisCO carboxylation flux under photoautotrophic conditions. Lastly using the MFA approach, I showed: 1) the dominant role of a cyclic route (PEP OXA MAL PYR PEP) via the malic enzyme for generating PYR and OXA needed for photoautotrophic biosynthesis; and 2) the increased synthesis of glycogen that occurs under nitrogen deprivation results from the combination of two pathways at the 3PG and G6P branching points that contribute precursors. The goal of the second part of the thesis was to construct a Synechococcus 7002 mutant capable of producing H2 in the dark at high rates by anaerobic fermentation in the presence of nitrate. Cyanobacteria catabolize the storage carbohydrates (glycogen) synthesized during photosynthesis under dark anaerobic conditions (denoted auto-fermentation). Synechococcus 7002 bears a H2-producing enzyme, Hox hydrogenase, which produces H2 during auto-fermentation by consuming reductant generated through glycogen catabolism. A knockout mutant of the reductant consuming nitrate reductase, ΔnarB, showed a 6-fold higher dark fermentative H2 evolution rate than the WT when fermenting on nitrate. Combining the mutation with a “milking” strategy, which continuously removes H2 from the fermentation medium, resulted in a 49-fold combined increase in the net H2 evolution rate during 2 days of fermentation compared to the WT. In summary, my dissertation quantitatively maps the carbon flux distribution, using a combination of computational and experimental approaches, under both photoautotrophic growth at different light intensities and nutrient conditions and under dark autofermentation in the model cyanobacterium Synechococcus 7002. These studies reveal the capacity for using cyanobacteria as cell factories for carbon and solar energy storage and H2 production, respectively.Ph.D.Includes bibliographical referencesby Xiao Qia