Computational Analysis of Alternative Photosynthetic Electron Flows Linked With Oxidative Stress

Alternatives to photorespiration: A system-level analysis reveals mechanisms of enhanced plant productivity

Photorespiration causes a substantial decrease in crop yield because of mitochondrial decarboxylation. Alternative pathways (APs) have been designed to relocate the decarboxylation step or even fix additional carbon. To improve the success of transferring those engineered APs from model species to crops, we must understand how they will interact with metabolism and how plant physiology affects their performance. Here, we used multiple mathematical modeling techniques to analyze and compare existing AP designs. We show that carbon-fixing APs are the most promising candidates to replace native photorespiration in major crop species. Our results demonstrate the different metabolic routes that APs use to increase yield and which plant physiology can profit the most from them. We anticipate our results to guide the design of new APs and to help improve existing ones.

New avenues in photosynthesis: from light harvesting to global modeling

Photosynthesis underpins life on Earth, serving as the primary energy source while regulating global carbon and water cycles, thereby shaping climate and vegetation. Advancing photosynthesis research is essential for improving crop productivity and refining photosynthesis models across scales, ultimately addressing critical global challenges such as food security and environmental sustainability. This minireview synthesizes a selection of recent advancements presented at the 2nd European Congress of Photosynthesis Research, focusing on improving photosynthesis efficiency and modelling across the scales. We explore strategies to optimize light harvesting and carbon fixation, leading to canopy level improvements. Alongside synthetic biology, we examine recent advances in harnessing natural variability in key photosynthetic traits, considering both methodological innovations and the vast reservoir of opportunities they present. Additionally, we highlight unique insights gained from plants adapted to extreme environments, offering pathways to improve photosynthetic efficiency and resilience simultaneously. We emphasize the importance of a holistic approach, integrating dynamic modeling of metabolic processes to bridge these advancements. Beyond photosynthesis improvements, we discuss the progress of improving photosynthesis simulations, particularly through improved parametrization of mesophyll conductance, crucial for enhancing leaf-to-global scale simulations. Recognizing the need for greater interdisciplinary collaboration to tackle the grand challenges put on photosynthesis research, we highlight two initiatives launched at the congress-an open science platform and a dedicated journal for plant ecophysiology. We conclude this minireview with a forward-looking outline, highlighting key next steps toward achieving meaningful improvements in photosynthesis, yield, resilience and modeling.

From leaf to multiscale models of photosynthesis: applications and challenges for crop improvement

To keep up with the growth of human population and to circumvent deleterious effects of global climate change, it is essential to enhance crop yield to achieve higher production. Here we review mathematical models of oxygenic photosynthesis that are extensively used, and discuss in depth a subset that accounts for diverse approaches providing solutions to our objective. These include models (1) to study different ways to enhance photosynthesis, such as fine-tuning antenna size, photoprotection and electron transport; (2) to bioengineer carbon metabolism; and (3) to evaluate the interactions between the process of photosynthesis and the seasonal crop dynamics, or those that have included statistical whole-genome prediction methods to quantify the impact of photosynthesis traits on the improvement of crop yield. We conclude by emphasizing that the results obtained in these studies clearly demonstrate that mathematical modelling is a key tool to examine different approaches to improve photosynthesis for better productivity, while effective multiscale crop models, especially those that also include remote sensing data, are indispensable to verify different strategies to obtain maximized crop yields.

Reaction-Kinetic Modeling of Photorespiration Using Modelbase

Plant science has become more and more complex. With the introduction of new experimental techniques and technologies, it is now possible to explore the fine details of plant metabolism. Besides steady-state measurements often applied in gas-exchange or metabolomic analyses, new approaches, e.g., based on 13C labeling, are now available to understand the changes in metabolic concentrations under fluctuating environmental conditions in the field or laboratory. To explore those transient phenomena of metabolite concentrations, kinetic models are a valuable tool. In this chapter, we describe ways to implement and build kinetic models of plant metabolism with the Python software package modelbase. As an example, we use a part of the photorespiratory pathway. Moreover, we show additional functionalities of modelbase that help to explore kinetic models and thus can reveal information about a biological system that is not easily accessible to experiments. In addition, we will point to extra information on the mathematical background of kinetic models to give an impetus for further self-study.

Improving photosynthetic efficiency toward food security: Strategies, advances, and perspectives

Photosynthesis in crops and natural vegetation allows light energy to be converted into chemical energy and thus forms the foundation for almost all terrestrial trophic networks on Earth. The efficiency of photosynthetic energy conversion plays a crucial role in determining the portion of incident solar radiation that can be used to generate plant biomass throughout a growth season. Consequently, alongside the factors such as resource availability, crop management, crop selection, maintenance costs, and intrinsic yield potential, photosynthetic energy use efficiency significantly influences crop yield. Photosynthetic efficiency is relevant to sustainability and food security because it affects water use efficiency, nutrient use efficiency, and land use efficiency. This review focuses specifically on the potential for improvements in photosynthetic efficiency to drive a sustainable increase in crop yields. We discuss bypassing photorespiration, enhancing light use efficiency, harnessing natural variation in photosynthetic parameters for breeding purposes, and adopting new-to-nature approaches that show promise for achieving unprecedented gains in photosynthetic efficiency.

What controls carbon sequestration in plants under which conditions?

Photosynthetic organisms use photosynthesis to harvest sunlight and convert the solar energy into chemical energy, which is then used to reduce atmospheric carbon dioxide into organic molecules. This process forms the basis of all life on Earth, and stands at the beginning of the food chain which feeds the world population. Not surprisingly, many research efforts are currently ongoing aiming at improving growth and product yield of photosynthetic organisms, and several of these activities directly target the photosynthetic pathways. Metabolic Control Analysis (MCA) shows that, in general, the control over a metabolic flux, such as carbon fixation, is distributed among several steps and highly dependent on the external conditions. Therefore, the concept of a single 'rate-limiting' step is hardly ever applicable, and as a consequence, any strategy relying on improving a single molecular process in a complex metabolic system is bound to fail to yield the expected results. In photosynthesis, reports on which processes exert the highest control over carbon fixation are contradictory. This refers to both the photosynthetic 'light' reactions harvesting photons and the 'dark' reactions of the Calvin-Benson-Bassham Cycle (CBB cycle). Here, we employ a recently developed mathematical model, which describes photosynthesis as an interacting supply-demand system, to systematically study how external conditions affect the control over carbon fixation fluxes.

Molecular, Brownian, kinetic and stochastic models of the processes in photosynthetic membrane of green plants and microalgae

The paper presents the results of recent work at the Department of Biophysics of the Biological Faculty, Lomonosov Moscow State University on the kinetic and multiparticle modeling of processes in the photosynthetic membrane. The detailed kinetic models and the rule-based kinetic Monte Carlo models allow to reproduce the fluorescence induction curves and redox transformations of the photoactive pigment P700 in the time range from 100 ns to dozens of seconds and make it possible to reveal the role of individual carriers in their formation for different types of photosynthetic organisms under different illumination regimes, in the presence of inhibitors, under stress conditions. The fitting of the model curves to the experimental data quantifies the reaction rate constants that cannot be directly measured experimentally, including the non-radiative thermal relaxation reactions. We use the direct multiparticle models to explicitly describe the interactions of mobile photosynthetic carrier proteins with multienzyme complexes both in solution and in the biomembrane interior. An analysis of these models reveals the role of diffusion and electrostatic factors in the regulation of electron transport, the influence of ionic strength and pH of the cellular environment on the rate of electron transport reactions between carrier proteins. To describe the conformational intramolecular processes of formation of the final complex, in which the actual electron transfer occurs, we use the methods of molecular dynamics. The results obtained using kinetic and molecular models supplement our knowledge of the mechanisms of organization of the photosynthetic electron transport processes at the cellular and molecular levels.