E-photosynthesis: web-based platform for modeling of complex photosynthetic processes

Appropriate time interval of PPFD measurement to estimate daily photosynthetic gain

Photosynthetic models sometimes incorporate meteorological elements typically recorded at a time interval of 10 min or 1 h. Because these data are calculated by averaging instantaneous values over time, short-term environmental fluctuations are concealed, which may affect outputs of the model. To assess an appropriate time interval of photosynthetic photon flux density (PPFD) measurement for accurate estimation of photosynthetic gain under open field conditions, we simulated the daily integral net photosynthetic gain using photosynthetic models with or without considering induction kinetics in response to changes in PPFD. Compared with the daily gain calculated from 60-min-interval PPFD data using a steady-state model that ignored the induction kinetics (i.e. a baseline gain), the gains simulated using higher-resolution PPFD data (10-s, 1-min, and 10-min intervals) and using a dynamic model that considered slow induction kinetics were both smaller by ~2%. The gain estimated by the slow dynamic model with 10-s-interval PPFD data was smaller than the baseline gain by more than 5% with a probability of 66%. Thus, the use of low-resolution PPFD data causes overestimation of daily photosynthetic gain in open fields. An appropriate time interval for PPFD measurement is 1 min or shorter to ensure accuracy of the estimates.

Photosynthesis: basics, history and modelling

BACKGROUND

With limited agricultural land and increasing human population, it is essential to enhance overall photosynthesis and thus productivity. Oxygenic photosynthesis begins with light absorption, followed by excitation energy transfer to the reaction centres, primary photochemistry, electron and proton transport, NADPH and ATP synthesis, and then CO2 fixation (Calvin-Benson cycle, as well as Hatch-Slack cycle). Here we cover some of the discoveries related to this process, such as the existence of two light reactions and two photosystems connected by an electron transport 'chain' (the Z-scheme), chemiosmotic hypothesis for ATP synthesis, water oxidation clock for oxygen evolution, steps for carbon fixation, and finally the diverse mechanisms of regulatory processes, such as 'state transitions' and 'non-photochemical quenching' of the excited state of chlorophyll a.

SCOPE

In this review, we emphasize that mathematical modelling is a highly valuable tool in understanding and making predictions regarding photosynthesis. Different mathematical models have been used to examine current theories on diverse photosynthetic processes; these have been validated through simulation(s) of available experimental data, such as chlorophyll a fluorescence induction, measured with fluorometers using continuous (or modulated) exciting light, and absorbance changes at 820 nm (ΔA820) related to redox changes in P700, the reaction centre of photosystem I.

CONCLUSIONS

We highlight here the important role of modelling in deciphering and untangling complex photosynthesis processes taking place simultaneously, as well as in predicting possible ways to obtain higher biomass and productivity in plants, algae and cyanobacteria.

Synthetic biology as it relates to CAM photosynthesis: challenges and opportunities

To meet future food and energy security needs, which are amplified by increasing population growth and reduced natural resource availability, metabolic engineering efforts have moved from manipulating single genes/proteins to introducing multiple genes and novel pathways to improve photosynthetic efficiency in a more comprehensive manner. Biochemical carbon-concentrating mechanisms such as crassulacean acid metabolism (CAM), which improves photosynthetic, water-use, and possibly nutrient-use efficiency, represent a strategic target for synthetic biology to engineer more productive C3 crops for a warmer and drier world. One key challenge for introducing multigene traits like CAM onto a background of C3 photosynthesis is to gain a better understanding of the dynamic spatial and temporal regulatory events that underpin photosynthetic metabolism. With the aid of systems and computational biology, vast amounts of experimental data encompassing transcriptomics, proteomics, and metabolomics can be related in a network to create dynamic models. Such models can undergo simulations to discover key regulatory elements in metabolism and suggest strategic substitution or augmentation by synthetic components to improve photosynthetic performance and water-use efficiency in C3 crops. Another key challenge in the application of synthetic biology to photosynthesis research is to develop efficient systems for multigene assembly and stacking. Here, we review recent progress in computational modelling as applied to plant photosynthesis, with attention to the requirements for CAM, and recent advances in synthetic biology tool development. Lastly, we discuss possible options for multigene pathway construction in plants with an emphasis on CAM-into-C3 engineering.

Chlorophyll a fluorescence induction: a personal perspective of the thermal phase, the J-I-P rise

The fast (up to 1 s) chlorophyll (Chl) a fluorescence induction (FI) curve, measured under saturating continuous light, has a photochemical phase, the O-J rise, related mainly to the reduction of Q(A), the primary electron acceptor plastoquinone of Photosystem II (PSII); here, the fluorescence rise depends strongly on the number of photons absorbed. This is followed by a thermal phase, the J-I-P rise, which disappears at subfreezing temperatures. According to the mainstream interpretation of the fast FI, the variable fluorescence originates from PSII antenna, and the oxidized Q(A) is the most important quencher influencing the O-J-I-P curve. As the reaction centers of PSII are gradually closed by the photochemical reduction of Q(A), Chl fluorescence, F, rises from the O level (the minimal level) to the P level (the peak); yet, the relationship between F and [Q(A) (-)] is not linear, due to the presence of other quenchers and modifiers. Several alternative theories have been proposed, which give different interpretations of the O-J-I-P transient. The main idea in these alternative theories is that in saturating light, Q(A) is almost completely reduced already at the end of the photochemical phase O-J, but the fluorescence yield is lower than its maximum value due to the presence of either a second quencher besides Q(A), or there is an another process quenching the fluorescence; in the second quencher hypothesis, this quencher is consumed (or the process of quenching the fluorescence is reversed) during the thermal phase J-I-P. In this review, we discuss these theories. Based on our critical examination, that includes pros and cons of each theory, as well mathematical modeling, we conclude that the mainstream interpretation of the O-J-I-P transient is the most credible one, as none of the alternative ideas provide adequate explanation or experimental proof for the almost complete reduction of Q(A) at the end of the O-J phase, and for the origin of the fluorescence rise during the thermal phase. However, we suggest that some of the factors influencing the fluorescence yield that have been proposed in these newer theories, as e.g., the membrane potential ΔΨ, as suggested by Vredenberg and his associates, can potentially contribute to modulate the O-J-I-P transient in parallel with the reduction of Q(A), through changes at the PSII antenna and/or at the reaction center, or, possibly, through the control of the oxidation-reduction of the PQ-pool, including proton transfer into the lumen, as suggested by Rubin and his associates. We present in this review our personal perspective mainly on our understanding of the thermal phase, the J-I-P rise during Chl a FI in plants and algae.

Modelling cyanobacteria: from metabolism to integrative models of phototrophic growth

Cyanobacteria are phototrophic microorganisms of global importance and have recently attracted increasing attention due to their capability to convert sunlight and atmospheric CO(2) directly into organic compounds, including carbon-based biofuels. The utilization of cyanobacteria as a biological chassis to generate third-generation biofuels would greatly benefit from an increased understanding of cyanobacterial metabolism and its interplay with other cellular processes. In this respect, metabolic modelling has been proposed as a way to overcome the traditional trial and error methodology that is often employed to introduce novel pathways. In particular, flux balance analysis and related methods have proved to be powerful tools to investigate the organization of large-scale metabolic networks-with the prospect of predicting modifications that are likely to increase the yield of a desired product and thereby to streamline the experimental progress and avoid futile avenues. This contribution seeks to describe the utilization of metabolic modelling as a research tool to understand the metabolism and phototrophic growth of cyanobacteria. The focus of the contribution is on a mathematical description of the metabolic network of Synechocystis sp. PCC 6803 and its analysis using constraint-based methods. A particular challenge is to integrate the description of the metabolic network with other cellular processes, such as the circadian clock, the photosynthetic light reactions, carbon concentration mechanism, and transcriptional regulation-aiming at a predictive model of a cyanobacterium in silico.

Modeling the Calvin-Benson cycle

BACKGROUND

Modeling the Calvin-Benson cycle has a history in the field of theoretical biology. Anyone who intends to model this system will look at existing models to adapt, refine and improve them. With the goal to study the regulation of carbon metabolism, we investigated a broad range of relevant models for their suitability to provide the basis for further modeling efforts. Beyond a critical analysis of existing models, we furthermore investigated the question how adjacent metabolic pathways, for instance photorespiration, can be integrated in such models.

RESULTS

Our analysis reveals serious problems with a range of models that are publicly available and widely used. The problems include the irreproducibility of the published results or significant differences between the equations in the published description of the model and model itself in the supplementary material. In addition to and based on the discussion of existing models, we furthermore analyzed approaches in PGA sink implementation and confirmed a weak relationship between the level of its regulation and efficiency of PGA export, in contrast to significant changes in the content of metabolic pool within the Calvin-Benson cycle.

CONCLUSIONS

In our study we show that the existing models that have been investigated are not suitable for reuse without substantial modifications. We furthermore show that the minor adjacent pathways of the carbon metabolism, neglected in all kinetic models of Calvin-Benson cycle, cannot be substituted without consequences in the mass production dynamics. We further show that photorespiration or at least its first step (O2 fixation) has to be implemented in the model if this model is aimed for analyses out of the steady state.