2005) and isolated complexes (Ahn et al. 2008; Avenson et al. 2008). Moving forward, it seems likely that correlating the amplitudes and dynamics of TA experiments with qE in vivo will be necessary for differentiating between different qE mechanisms. New tools for characterizing qE in vivo Since the first discovery of qE quenching, a great deal of information has been revealed about the triggers, components, and spectroscopic signatures associated with qE. Measurements of chloroplasts, isolated thylakoids, and isolated proteins have

yielded numerous hypotheses regarding the trigger, site, and photophysical mechanisms of qE. In our view, resolving the many hypotheses that have been proposed based on isolated systems requires the development of techniques to study qE in intact living systems such as whole leaves and live algae. Because qE is a dynamic SBI-0206965 order process, a full understanding requires knowledge of the timescales of constituent processes. Interpretation of results in intact systems is complicated because the events leading up to qE occur on many timescales and are affected by a large number of dynamic processes. Figure 8 illustrates the range of timescales involved in qE. In particular, the timescale of the appearance of qE quenching, as observed by fluorescence measurements,

is a combination of the formation BTSA1 mouse of the triggers (the lumen pH and \(\Updelta\hboxpH\)) and the timescale and set Rapamycin clinical trial points of the membrane rearrangements (e.g., protein activations, protein aggregation) that give rise to the formation of qE. The lumen pH is itself determined by four processes: (1) water splitting at PSII, (2) proton pumping at cytochrome b 6 f, (3) proton efflux through ATP synthesis, and (4) parsing of the proton

motive 3-mercaptopyruvate sulfurtransferase force into a \(\Updelta\hboxpH\) and a \(\Updelta \psi\) component by the motion of ions across the thylakoid membrane. Fig. 8 Schematic of feedback loop governing qE (solid black rectangles), and the broad range of timescales of processes giving rise to qE (dashed colored rectangles) The multitude of interconnected processes that give rise to a qE quenching state makes it difficult to differentiate between mechanistic hypotheses. To address this difficulty, we have developed a kinetic model of the processes in photosynthesis that give rise to qE. Our model, which is inspired by state-space models of engineering control theory analysis (Eberhard et al. 2008), calculates the lumen pH and simulates the induction and relaxation of qE in low and high light intensity (Zaks et al. 2012). The model currently consists of 24 non-linear differential equations that calculate the pH in the lumen on timescales ranging from microseconds to minutes. We tested the effectiveness of the model by calculating chlorophyll fluorescence yields and comparing those predictions to PAM fluorescence measurements.