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theses

Photosynthetic molecular machinery is the primary source of energy in the biosphere of the earth. Plants, algae, and cyanobacteria have evolved over billions of years to harness the light energy of the sun and convert it to chemical energy to produce biomass and perform all the required cellular processes. Light energy is used to extract electrons from water as well as generate a proton gradient along the thylakoid membrane, the energy in which is ultimately used to fix carbon (mainly in the form of CO2 and HCO3+) through the Calvin Benson Bassham (CBB) cycle. Human civilization is dependent on this biomass to generate food, feed, as well as a variety of value-added chemicals such as biofuels. In order to meet the needs of the continuously growing global population, there is a need to better understand the biological processes that enable carbon fixation. In the photosynthetic research community, these processes have primarily been monitored through O2 evolution and Chlorophyll Fluorescence yield, both arising from the light-dependent water-splitting protein, Photosystem II (PSII). The water oxidation cycle is a four-step process, releasing O2 once every cycle. This process has been traditionally modeled using Kok-type Hidden Markov Chain models (HMMs) that include 3 parameters: misses, double hits, and backward transitions. However, these models do not offer any insight into the underlying mechanisms for any of these processes. The first objective of this thesis was to extract that mechanistic knowledge from these models. To do so, I built an ordinary differential equation (ODE)-based model of PSII, namely RODE1, and developed a framework to discretize the solutions of the ODEs to connect them to the parameters calculated in the Kok-type HMM models. This work showed that the efficiency of charge separation in the donor side of PSII, where electrons are extracted from water utilizing photons is tightly controlled by the acceptor side of PSII, where electrons are transferred to Plastoquinone (PQ), a loosely bound 2 e- carrier which shuttles the electrons downstream to the Photosynthetic Electron Transport Chain (PETC). Even though our approach could accurately predict forward electron transfer within PSII, it lacked the prediction of backward transitions, a process where electrons are moved from the acceptor side to the donor side. Exploring the mechanistic process of backward transitions was the second objective of this thesis. This was achieved by expanding the model to include the appropriate reactions and applying it to O2 evolution data acquired from C. ohadii, a desert crust alga, which has been previously shown to have uncharacteristically high backward transitions. This study showed that the process of backward transitions is again regulated by the donor and the acceptor side. We showed that the PSII microstates that allow for backward transitions were the ones where the loosely bound PQ at the donor side (QB) would carry a single electron in the form of a semiquinone, rather than being fully oxidized (0 e-) or fully reduced (2 e-). The proposed mechanism for backward transitions is a potential pathway for Cyclic Electron Flow around PSII (PSII-CEF) which is a mechanism that can be used for photoprotection (dissipative PSII-CEF) or to increase the proton gradient across the thylakoid membrane (generative PSII-CEF). The last objective of this thesis was to develop a method to study the PETC from water to CO2, which are the primary source, and the terminal acceptor of electrons respectively. The developed method utilizes Fast Repetition Rate fluorometry (FRRf) to monitor changes in charge separation efficiency in multiple time scales, from μs to minutes. We showed how the kinetic features observed in our method respond to altering photosynthetic electron transport through multiple treatments and identified the redox events that each kinetic feature corresponds to. Among other redox events, we identified how Cyclic Electron Flow around PSI (PSI-CEF) appears in our measurements and how the PETC is connected to dark metabolism.

http://dissertations.umi.com/gsnb.rutgers:12283

Ph.D.

Includes bibliographical references

doi:10.7282/t3-6thj-0869

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