Modelling photosynthesis and its control

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.

Microbial reaction rate estimation using proteins and proteomes

Microbes transform their environments using diverse enzymatic reactions. However, it remains challenging to measure microbial reaction rates in natural environments. Despite advances in global quantification of enzyme abundances, the individual relationships between enzyme abundances and their reaction rates have not been systematically examined. Using matched proteomic and reaction rate data from microbial cultures, we show that enzyme abundance is often insufficient to predict its corresponding reaction rate. However, we discovered that global proteomic measurements can be used to make accurate rate predictions of individual reaction rates (median R 2 = 0.78). Accurate rate predictions required only a small number of proteins and they did not need explicit prior mechanistic knowledge or environmental context. These results indicate that proteomes are encoders of cellular reaction rates, potentially enabling proteomic measurements in situ to estimate the rates of microbially mediated reactions in natural systems.

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.

Rubisco is evolving for improved catalytic efficiency and CO2 assimilation in plants

Rubisco is the primary entry point for carbon into the biosphere. However, rubisco is widely regarded as inefficient leading many to question whether the enzyme can adapt to become a better catalyst. Through a phylogenetic investigation of the molecular and kinetic evolution of Form I rubisco we uncover the evolutionary trajectory of rubisco kinetic evolution in angiosperms. We show that rbcL is among the 1% of slowest-evolving genes and enzymes on Earth, accumulating one nucleotide substitution every 0.9 My and one amino acid mutation every 7.2 My. Despite this, rubisco catalysis has been continually evolving toward improved CO2/O2 specificity, carboxylase turnover, and carboxylation efficiency. Consistent with this kinetic adaptation, increased rubisco evolution has led to a concomitant improvement in leaf-level CO2 assimilation. Thus, rubisco has been slowly but continually evolving toward improved catalytic efficiency and CO2 assimilation in plants.

Machine learning predicts system-wide metabolic flux control in cyanobacteria

Metabolic fluxes and their control mechanisms are fundamental in cellular metabolism, offering insights for the study of biological systems and biotechnological applications. However, quantitative and predictive understanding of controlling biochemical reactions in microbial cell factories, especially at the system level, is limited. In this work, we present ARCTICA, a computational framework that integrates constraint-based modelling with machine learning tools to address this challenge. Using the model cyanobacterium Synechocystis sp. PCC 6803 as chassis, we demonstrate that ARCTICA effectively simulates global-scale metabolic flux control. Key findings are that (i) the photosynthetic bioproduction is mainly governed by enzymes within the Calvin-Benson-Bassham (CBB) cycle, rather than by those involve in the biosynthesis of the end-product, (ii) the catalytic capacity of the CBB cycle limits the photosynthetic activity and downstream pathways and (iii) ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) is a major, but not the most, limiting step within the CBB cycle. Predicted metabolic reactions qualitatively align with prior experimental observations, validating our modelling approach. ARCTICA serves as a valuable pipeline for understanding cellular physiology and predicting rate-limiting steps in genome-scale metabolic networks, and thus provides guidance for bioengineering of cyanobacteria.

Quantifying the impact of dynamic plant-environment interactions on metabolic regulation

A plant's genome encodes enzymes, transporters and many other proteins which constitute metabolism. Interactions of plants with their environment shape their growth, development and resilience towards adverse conditions. Although genome sequencing technologies and applications have experienced triumphantly rapid development during the last decades, enabling nowadays a fast and cheap sequencing of full genomes, prediction of metabolic phenotypes from genotype × environment interactions remains, at best, very incomplete. The main reasons are a lack of understanding of how different levels of molecular organisation depend on each other, and how they are constituted and expressed within a setup of growth conditions. Phenotypic plasticity, e.g., of the genetic model plant Arabidopsis thaliana, has provided important insights into plant-environment interactions and the resulting genotype x phenotype relationships. Here, we summarize previous and current findings about plant development in a changing environment and how this might be shaped and reflected in metabolism and its regulation. We identify current challenges in the study of plant development and metabolic regulation and provide an outlook of how methodological workflows might support the application of findings made in model systems to crops and their cultivation.

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.

Low light intensity elongates period and defers peak time of photosynthesis: a computational approach to circadian-clock-controlled photosynthesis in tomato

Photosynthesis is involved in the essential process of transforming light energy into chemical energy. Although the interaction between photosynthesis and the circadian clock has been confirmed, the mechanism of how light intensity affects photosynthesis through the circadian clock remains unclear. Here, we propose a first computational model for circadian-clock-controlled photosynthesis, which consists of the light-sensitive protein P, the core oscillator, photosynthetic genes, and parameters involved in the process of photosynthesis. The model parameters were determined by minimizing the cost function ( [Formula: see text]), which is defined by the errors of expression levels, periods, and phases of the clock genes (CCA1, PRR9, TOC1, ELF4, GI, and RVE8). The model recapitulates the expression pattern of the core oscillator under moderate light intensity (100 μmol m -2 s-1). Further simulation validated the dynamic behaviors of the circadian clock and photosynthetic outputs under low (62.5 μmol m-2 s-1) and normal (187.5 μmol m-2 s-1) intensities. When exposed to low light intensity, the peak times of clock and photosynthetic genes were shifted backward by 1-2 hours, the period was elongated by approximately the same length, and the photosynthetic parameters attained low values and showed delayed peak times, which confirmed our model predictions. Our study reveals a potential mechanism underlying the circadian regulation of photosynthesis by the clock under different light intensities in tomato.

A 'wiring diagram' for source strength traits impacting wheat yield potential

Source traits are currently of great interest for the enhancement of yield potential; for example, much effort is being expended to find ways of modifying photosynthesis. However, photosynthesis is but one component of crop regulation, so sink activities and the coordination of diverse processes throughout the crop must be considered in an integrated, systems approach. A set of 'wiring diagrams' has been devised as a visual tool to integrate the interactions of component processes at different stages of wheat development. They enable the roles of chloroplast, leaf, and whole-canopy processes to be seen in the context of sink development and crop growth as a whole. In this review, we dissect source traits both anatomically (foliar and non-foliar) and temporally (pre- and post-anthesis), and consider the evidence for their regulation at local and whole-plant/crop levels. We consider how the formation of a canopy creates challenges (self-occlusion) and opportunities (dynamic photosynthesis) for components of photosynthesis. Lastly, we discuss the regulation of source activity by feedback regulation. The review is written in the framework of the wiring diagrams which, as integrated descriptors of traits underpinning grain yield, are designed to provide a potential workspace for breeders and other crop scientists that, along with high-throughput and precision phenotyping data, genetics, and bioinformatics, will help build future dynamic models of trait and gene interactions to achieve yield gains in wheat and other field crops.

From Soil Amendments to Controlling Autophagy: Supporting Plant Metabolism under Conditions of Water Shortage and Salinity

Crop resistance to environmental stress is a major issue. The globally increasing land degradation and desertification enhance the demand on management practices to balance both food and environmental objectives, including strategies that tighten nutrient cycles and maintain yields. Agriculture needs to provide, among other things, future additional ecosystem services, such as water quantity and quality, runoff control, soil fertility maintenance, carbon storage, climate regulation, and biodiversity. Numerous research projects have focused on the food–soil–climate nexus, and results were summarized in several reviews during the last decades. Based on this impressive piece of information, we have selected only a few aspects with the intention of studying plant–soil interactions and methods for optimization. In the short term, the use of soil amendments is currently attracting great interest to cover the current demand in agriculture. We will discuss the impact of biochar at water shortage, and plant growth promoting bacteria (PGPB) at improving nutrient supply to plants. In this review, our focus is on the interplay of both soil amendments on primary reactions of photosynthesis, plant growth conditions, and signaling during adaptation to environmental stress. Moreover, we aim at providing a general overview of how dehydration and salinity affect signaling in cells. With the use of the example of abscisic acid (ABA) and ethylene, we discuss the effects that can be observed when biochar and PGPB are used in the presence of stress. The stress response of plants is a multifactorial trait. Nevertheless, we will show that plants follow a general concept to adapt to unfavorable environmental conditions in the short and long term. However, plant species differ in the upper and lower regulatory limits of gene expression. Therefore, the presented data may help in the identification of traits for future breeding of stress-resistant crops. One target for breeding could be the removal and efficient recycling of damaged as well as needless compounds and structures. Furthermore, in this context, we will show that autophagy can be a useful goal of breeding measures, since the recycling of building blocks helps the cells to overcome a period of imbalanced substrate supply during stress adjustment.

A hybrid kinetic and constraint-based model of leaf metabolism allows predictions of metabolic fluxes in different environments

While flux balance analysis (FBA) provides a framework for predicting steady-state leaf metabolic network fluxes, it does not readily capture the response to environmental variables without being coupled to other modelling formulations. To address this, we coupled an FBA model of 903 reactions of soybean (Glycine max) leaf metabolism with e-photosynthesis, a dynamic model that captures the kinetics of 126 reactions of photosynthesis and associated chloroplast carbon metabolism. Successful coupling was achieved in an iterative formulation in which fluxes from e-photosynthesis were used to constrain the FBA model and then, in turn, fluxes computed from the FBA model used to update parameters in e-photosynthesis. This process was repeated until common fluxes in the two models converged. Coupling did not hamper the ability of the kinetic module to accurately predict the carbon assimilation rate, photosystem II electron flux, and starch accumulation of field-grown soybean at two CO2 concentrations. The coupled model also allowed accurate predictions of additional parameters such as nocturnal respiration, as well as analysis of the effect of light intensity and elevated CO2 on leaf metabolism. Predictions included an unexpected decrease in the rate of export of sucrose from the leaf at high light, due to altered starch-sucrose partitioning, and altered daytime flux modes in the tricarboxylic acid cycle at elevated CO2 . Mitochondrial fluxes were notably different between growing and mature leaves, with greater anaplerotic, tricarboxylic acid cycle and mitochondrial ATP synthase fluxes predicted in the former, primarily to provide carbon skeletons and energy for protein synthesis.

Potential metabolic mechanisms for inhibited chloroplast nitrogen assimilation under high CO2

Improving photosynthesis is considered a major and feasible option to dramatically increase crop yield potential. Increased atmospheric CO2 concentration often stimulates both photosynthesis and crop yield, but decreases protein content in the main C3 cereal crops. This decreased protein content in crops constrains the benefits of elevated CO2 on crop yield and affects their nutritional value for humans. To support studies of photosynthetic nitrogen assimilation and its complex interaction with photosynthetic carbon metabolism for crop improvement, we developed a dynamic systems model of plant primary metabolism, which includes the Calvin-Benson cycle, the photorespiration pathway, starch synthesis, glycolysis-gluconeogenesis, the tricarboxylic acid cycle, and chloroplastic nitrogen assimilation. This model successfully captures responses of net photosynthetic CO2 uptake rate (A), respiration rate, and nitrogen assimilation rate to different irradiance and CO2 levels. We then used this model to predict inhibition of nitrogen assimilation under elevated CO2. The potential mechanisms underlying inhibited nitrogen assimilation under elevated CO2 were further explored with this model. Simulations suggest that enhancing the supply of α-ketoglutarate is a potential strategy to maintain high rates of nitrogen assimilation under elevated CO2. This model can be used as a heuristic tool to support research on interactions between photosynthesis, respiration, and nitrogen assimilation. It also provides a basic framework to support the design and engineering of C3 plant primary metabolism for enhanced photosynthetic efficiency and nitrogen assimilation in the coming high-CO2 world.

Computational Analysis of Alternative Photosynthetic Electron Flows Linked With Oxidative Stress

During photosynthesis, organisms respond to their energy demand and ensure the supply of energy and redox equivalents that sustain metabolism. Hence, the photosynthetic apparatus can, and in fact should, be treated as an integrated supply-demand system. Any imbalance in the energy produced and consumed can lead to adverse reactions, such as the production of reactive oxygen species (ROS). Reaction centres of both photosystems are known sites of ROS production. Here, we investigate in particular the central role of Photosystem I (PSI) in this tightly regulated system. Using a computational approach we have expanded a previously published mechanistic model of C3 photosynthesis by including ROS producing and scavenging reactions around PSI. These include two water to water reactions mediated by Plastid terminal oxidase (PTOX) and Mehler and the ascorbate-glutathione (ASC-GSH) cycle, as a main non-enzymatic antioxidant. We have used this model to predict flux distributions through alternative electron pathways under various environmental stress conditions by systematically varying light intensity and enzymatic activity of key reactions. In particular, we studied the link between ROS formation and activation of pathways around PSI as potential scavenging mechanisms. This work shines light on the role of alternative electron pathways in photosynthetic acclimation and investigates the effect of environmental perturbations on PSI activity in the context of metabolic productivity.

A Holistic Approach to Study Photosynthetic Acclimation Responses of Plants to Fluctuating Light

Plants in natural environments receive light through sunflecks, the duration and distribution of these being highly variable across the day. Consequently, plants need to adjust their photosynthetic processes to avoid photoinhibition and maximize yield. Changes in the composition of the photosynthetic apparatus in response to sustained changes in the environment are referred to as photosynthetic acclimation, a process that involves changes in protein content and composition. Considering this definition, acclimation differs from regulation, which involves processes that alter the activity of individual proteins over short-time periods, without changing the abundance of those proteins. The interconnection and overlapping of the short- and long-term photosynthetic responses, which can occur simultaneously or/and sequentially over time, make the study of long-term acclimation to fluctuating light in plants challenging. In this review we identify short-term responses of plants to fluctuating light that could act as sensors and signals for acclimation responses, with the aim of understanding how plants integrate environmental fluctuations over time and tailor their responses accordingly. Mathematical modeling has the potential to integrate physiological processes over different timescales and to help disentangle short-term regulatory responses from long-term acclimation responses. We review existing mathematical modeling techniques for studying photosynthetic responses to fluctuating light and propose new methods for addressing the topic from a holistic point of view.

SiFBA5, a cold-responsive factor from Saussurea involucrata promotes cold resilience and biomass increase in transgenic tomato plants under cold stress

BACKGROUND

Saussurea involucrata survives in extreme arctic conditions and is very cold-resistant. This species grows in rocky, mountainous areas with elevations of 2400-4100 m, which are snow-covered year-round and are subject to freezing temperatures. S. involucrata's ability to survive in an extreme low-temperature environment suggests that it has particularly high photosynthetic efficiency, providing a magnificent model, and rich gene pool, for the analysis of plant cold stress response. Fructose-1, 6-bisphosphate aldolase (FBA) is a key enzyme in the photosynthesis process and also mediates the conversion of fructose 1, 6-bisphosphate (FBP) into dihydroxyacetone phosphate (DHAP) and glycerol triphosphate (GAP) during glycolysis and gluconeogenesis. The molecular mechanisms underlying S. involucrata's cold tolerance are still unclear; therefore, our work aims to investigate the role of FBA in plant cold-stress response.

RESULTS

In this study, we identified a cold-responsive gene, SiFBA5, based on a preliminary low-temperature, genome-wide transcriptional profiling of S. involucrata. Expression analysis indicated that cold temperatures rapidly induced transcriptional expression of SiFBA5, suggesting that SiFBA5 participates in the initial stress response. Subcellular localization analysis revealed that SiFBA5 is localized to the chloroplast. Transgenic tomato plants that overexpressed SiFBA5 were generated using a CaMV 35S promoter. Phenotypic observation suggested that the transgenic plants displayed increased cold tolerance and photosynthetic efficiency in comparison with wild-type plants.

CONCLUSION

Cold stress has a detrimental impact on crop yield. Our results demonstrated that SiFBA5 positively regulates plant response to cold stress, which is of great significance for increasing crop yield under cold stress conditions.

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.

Stimulating photosynthetic processes increases productivity and water-use efficiency in the field

Previous studies have demonstrated that the independent stimulation of either electron transport or RuBP regeneration can increase the rate of photosynthetic carbon assimilation and plant biomass. In this paper, we present evidence that a multigene approach to simultaneously manipulate these two processes provides a further stimulation of photosynthesis. We report on the introduction of the cyanobacterial bifunctional enzyme fructose-1,6-bisphosphatase/sedoheptulose-1,7-bisphosphatase or the overexpression of the plant enzyme sedoheptulose-1,7-bisphosphatase, together with the expression of the red algal protein cytochrome c6, and show that a further increase in biomass accumulation under both glasshouse and field conditions can be achieved. Furthermore, we provide evidence that the stimulation of both electron transport and RuBP regeneration can lead to enhanced intrinsic water-use efficiency under field conditions.

Dynamics of Plant Metabolism during Cold Acclimation

Plants have evolved strategies to tightly regulate metabolism during acclimation to a changing environment. Low temperature significantly constrains distribution, growth and yield of many temperate plant species. Exposing plants to low but non-freezing temperature induces a multigenic processes termed cold acclimation, which eventually results in an increased freezing tolerance. Cold acclimation comprises reprogramming of the transcriptome, proteome and metabolome and affects communication and signaling between subcellular organelles. Carbohydrates play a central role in this metabolic reprogramming. This review summarizes current knowledge about the role of carbohydrate metabolism in plant cold acclimation with a focus on subcellular metabolic reprogramming, its thermodynamic constraints under low temperature and mathematical modelling of metabolism.

Relationship between irradiance and levels of Calvin-Benson cycle and other intermediates in the model eudicot Arabidopsis and the model monocot rice

Metabolite profiles provide a top-down overview of the balance between the reactions in a pathway. We compared Calvin-Benson cycle (CBC) intermediate profiles in different conditions in Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa) to learn which features of CBC regulation differ and which are shared between these model eudicot and monocot C3 species. Principal component analysis revealed that CBC intermediate profiles follow different trajectories in Arabidopsis and rice as irradiance increases. The balance between subprocesses or reactions differed, with 3-phosphoglycerate reduction being favoured in Arabidopsis and ribulose 1,5-bisphosphate regeneration in rice, and sedoheptulose-1,7-bisphosphatase being favoured in Arabidopsis compared with fructose-1,6-bisphosphatase in rice. Photosynthesis rates rose in parallel with ribulose 1,5-bisphosphate levels in Arabidopsis, but not in rice. Nevertheless, some responses were shared between Arabidopsis and rice. Fructose 1,6-bisphosphate and sedoheptulose-1,7-bisphosphate were high or peaked at very low irradiance in both species. Incomplete activation of fructose-1,6-bisphosphatase and sedoheptulose-1,7-bisphosphatase may prevent wasteful futile cycles in low irradiance. End-product synthesis is inhibited and high levels of CBC intermediates are maintained in low light or in low CO2 in both species. This may improve photosynthetic efficiency in fluctuating irradiance, and facilitate rapid CBC flux to support photorespiration and energy dissipation in low CO2.

Metabolic acclimation-a key to enhancing photosynthesis in changing environments?

Plants adjust their photosynthetic capacity in response to their environment in a way that optimizes their yield and fitness. There is growing evidence that this acclimation is a response to changes in the leaf metabolome, but the extent to which these are linked and how this is optimized remain poorly understood. Using as an example the metabolic perturbations occurring in response to cold, we define the different stages required for acclimation, discuss the evidence for a metabolic temperature sensor, and suggest further work towards designing climate-smart crops. In particular, we discuss how constraint-based and kinetic metabolic modelling approaches can be used to generate targeted hypotheses about relevant pathways, and argue that a stronger integration of experimental and in silico studies will help us to understand the tightly regulated interplay of carbon partitioning and resource allocation required for photosynthetic acclimation to different environmental conditions.

Balancing energy supply during photosynthesis - a theoretical perspective

The photosynthetic electron transport chain (PETC) provides energy and redox equivalents for carbon fixation by the Calvin-Benson-Bassham (CBB) cycle. Both of these processes have been thoroughly investigated and the underlying molecular mechanisms are well known. However, it is far from understood by which mechanisms it is ensured that energy and redox supply by photosynthesis matches the demand of the downstream processes. Here, we deliver a theoretical analysis to quantitatively study the supply-demand regulation in photosynthesis. For this, we connect two previously developed models, one describing the PETC, originally developed to study non-photochemical quenching, and one providing a dynamic description of the photosynthetic carbon fixation in C3 plants, the CBB Cycle. The merged model explains how a tight regulation of supply and demand reactions leads to efficient carbon fixation. The model further illustrates that a stand-by mode is necessary in the dark to ensure that the carbon fixation cycle can be restarted after dark-light transitions, and it supports hypotheses, which reactions are responsible to generate such mode in vivo.

Feeding the world: improving photosynthetic efficiency for sustainable crop production

A number of recent studies have provided strong support demonstrating that improving the photosynthetic processes through genetic engineering can provide an avenue to improve yield potential. The major focus of this review is on improvement of the Calvin-Benson cycle and electron transport. Consideration is also given to how altering regulatory process may provide an additional route to increase photosynthetic efficiency. Here we summarize some of the recent successes that have been observed through genetic manipulation of photosynthesis, showing that, in both the glasshouse and the field, yield can be increased by >40%. These results provide a clear demonstration of the potential for increasing yield through improvements in photosynthesis. In the final section, we consider the need to stack improvement in photosynthetic traits with traits that target the yield gap in order to provide robust germplasm for different crops across the globe.

Kinetic modeling of the Calvin cycle identifies flux control and stable metabolomes in Synechocystis carbon fixation

Biological fixation of atmospheric CO2 via the Calvin-Benson-Bassham cycle has massive ecological impact and offers potential for industrial exploitation, either by improving carbon fixation in plants and autotrophic bacteria, or by installation into new hosts. A kinetic model of the Calvin-Benson-Bassham cycle embedded in the central carbon metabolism of the cyanobacterium Synechocystis sp. PCC 6803 was developed to investigate its stability and underlying control mechanisms. To reduce the uncertainty associated with a single parameter set, random sampling of the steady-state metabolite concentrations and the enzyme kinetic parameters was employed, resulting in millions of parameterized models which were analyzed for flux control and stability against perturbation. Our results show that the Calvin cycle had an overall high intrinsic stability, but a high concentration of ribulose 1,5-bisphosphate was associated with unstable states. Low substrate saturation and high product saturation of enzymes involved in highly interconnected reactions correlated with increased network stability. Flux control, that is the effect that a change in one reaction rate has on the other reactions in the network, was distributed and mostly exerted by energy supply (ATP), but also by cofactor supply (NADPH). Sedoheptulose 1,7-bisphosphatase/fructose 1,6-bisphosphatase, fructose-bisphosphate aldolase, and transketolase had a weak but positive effect on overall network flux, in agreement with published observations. The identified flux control and relationships between metabolite concentrations and system stability can guide metabolic engineering. The kinetic model structure and parameterizing framework can be expanded for analysis of metabolic systems beyond the Calvin cycle.

Using a Multi-compartmental Metabolic Model to Predict Carbon Allocation in Arabidopsis thaliana

The molecular mechanism of loading/unloading of sucrose into/from the phloem plays an important role in sucrose translocation among plant tissues. Perturbation of this mechanism results in growth phenotypes of a plant. In order to better understand the coupling of sucrose translocation with metabolic processes a multi-compartmental metabolic network of Arabidopsis thaliana was reconstructed and optimized with respect to biomass growth, both in light and in dark conditions. The model can be used to perform flux balance analysis of metabolic fluxes through the central carbon metabolism and catabolic and anabolic pathways. Balances and turnover of energy (ATP/ADP) and redox metabolites (NAD(P)H/NAD(P)) as well as proton concentrations in different compartments can be estimated. Importantly, the model can be used to quantify the translocation of sucrose from source to sink tissues through phloem in association with an integral balance of protons, which in turn is defined by the operational modes of the energy metabolism (light and dark conditions). This chapter describes how a multi-compartmental model to predict carbon allocation is constructed and used.

Increased SBPase activity improves photosynthesis and grain yield in wheat grown in greenhouse conditions

To meet the growing demand for food, substantial improvements in yields are needed. This is particularly the case for wheat, where global yield has stagnated in recent years. Increasing photosynthesis has been identified as a primary target to achieve yield improvements. To increase leaf photosynthesis in wheat, the level of the Calvin-Benson cycle enzyme sedoheptulose-1,7-biphosphatase (SBPase) has been increased through transformation and expression of a Brachypodium distachyon SBPase gene construct. Transgenic lines with increased SBPase protein levels and activity were grown under greenhouse conditions and showed enhanced leaf photosynthesis and increased total biomass and dry seed yield. This showed the potential of improving yield potential by increasing leaf photosynthesis in a crop species such as wheat. The results are discussed with regard to future strategies for further improvement of photosynthesis in wheat.This article is part of the themed issue 'Enhancing photosynthesis in crop plants: targets for improvement'.

Formulation, construction and analysis of kinetic models of metabolism: A review of modelling frameworks

Kinetic models are critical to predict the dynamic behaviour of metabolic networks. Mechanistic kinetic models for large networks remain uncommon due to the difficulty of fitting their parameters. Recent modelling frameworks promise new ways to overcome this obstacle while retaining predictive capabilities. In this review, we present an overview of the relevant mathematical frameworks for kinetic formulation, construction and analysis. Starting with kinetic formalisms, we next review statistical methods for parameter inference, as well as recent computational frameworks applied to the construction and analysis of kinetic models. Finally, we discuss opportunities and limitations hindering the development of larger kinetic reconstructions.

Simultaneous stimulation of sedoheptulose 1,7-bisphosphatase, fructose 1,6-bisphophate aldolase and the photorespiratory glycine decarboxylase-H protein increases CO2 assimilation, vegetative biomass and seed yield in Arabidopsis

In this article, we have altered the levels of three different enzymes involved in the Calvin-Benson cycle and photorespiratory pathway. We have generated transgenic Arabidopsis plants with altered combinations of sedoheptulose 1,7-bisphosphatase (SBPase), fructose 1,6-bisphophate aldolase (FBPA) and the glycine decarboxylase-H protein (GDC-H) gene identified as targets to improve photosynthesis based on previous studies. Here, we show that increasing the levels of the three corresponding proteins, either independently or in combination, significantly increases the quantum efficiency of PSII. Furthermore, photosynthetic measurements demonstrated an increase in the maximum efficiency of CO₂ fixation in lines over-expressing SBPase and FBPA. Moreover, the co-expression of GDC-H with SBPase and FBPA resulted in a cumulative positive impact on leaf area and biomass. Finally, further analysis of transgenic lines revealed a cumulative increase of seed yield in SFH lines grown in high light. These results demonstrate the potential of multigene stacking for improving the productivity of food and energy crops.

Metabolic model of central carbon and energy metabolisms of growing Arabidopsis thaliana in relation to sucrose translocation

BACKGROUND

Sucrose translocation between plant tissues is crucial for growth, development and reproduction of plants. Systemic analysis of these metabolic and underlying regulatory processes allow a detailed understanding of carbon distribution within the plant and the formation of associated phenotypic traits. Sucrose translocation from 'source' tissues (e.g. mesophyll) to 'sink' tissues (e.g. root) is tightly bound to the proton gradient across the membranes. The plant sucrose transporters are grouped into efflux exporters (SWEET family) and proton-symport importers (SUC, STP families). To better understand regulation of sucrose export from source tissues and sucrose import into sink tissues, there is a need for a metabolic model that takes in account the tissue organisation of Arabidopsis thaliana with corresponding metabolic specificities of respective tissues in terms of sucrose and proton production/utilization. An ability of the model to operate under different light modes ('light' and 'dark') and correspondingly in different energy producing modes is particularly important in understanding regulatory modules.

RESULTS

Here, we describe a multi-compartmental model consisting of a mesophyll cell with plastid and mitochondrion, a phloem cell, as well as a root cell with mitochondrion. In this model, the phloem was considered as a non-growing transport compartment, the mesophyll compartment was considered as both autotrophic (growing on CO₂ under light) and heterotrophic (growing on starch in darkness), and the root was always considered as heterotrophic tissue dependent on sucrose supply from the mesophyll compartment. In total, the model includes 413 balanced compounds interconnected by 400 transformers. The structured metabolic model accounts for central carbon metabolism, photosynthesis, photorespiration, carbohydrate metabolism, energy and redox metabolisms, proton metabolism, biomass growth, nutrients uptake, proton gradient generation and sucrose translocation between tissues. Biochemical processes in the model were associated with gene-products (742 ORFs). Flux Balance Analysis (FBA) of the model resulted in balanced carbon, nitrogen, proton, energy and redox states under both light and dark conditions. The main H⁺-fluxes were reconstructed and their directions matched with proton-dependent sucrose translocation from 'source' to 'sink' under any light condition.

CONCLUSIONS

The model quantified the translocation of sucrose between plant tissues in association with an integral balance of protons, which in turn is defined by operational modes of the energy metabolism.

Toward Multiscale Models of Cyanobacterial Growth: A Modular Approach

Oxygenic photosynthesis dominates global primary productivity ever since its evolution more than three billion years ago. While many aspects of phototrophic growth are well understood, it remains a considerable challenge to elucidate the manifold dependencies and interconnections between the diverse cellular processes that together facilitate the synthesis of new cells. Phototrophic growth involves the coordinated action of several layers of cellular functioning, ranging from the photosynthetic light reactions and the electron transport chain, to carbon-concentrating mechanisms and the assimilation of inorganic carbon. It requires the synthesis of new building blocks by cellular metabolism, protection against excessive light, as well as diurnal regulation by a circadian clock and the orchestration of gene expression and cell division. Computational modeling allows us to quantitatively describe these cellular functions and processes relevant for phototrophic growth. As yet, however, computational models are mostly confined to the inner workings of individual cellular processes, rather than describing the manifold interactions between them in the context of a living cell. Using cyanobacteria as model organisms, this contribution seeks to summarize existing computational models that are relevant to describe phototrophic growth and seeks to outline their interactions and dependencies. Our ultimate aim is to understand cellular functioning and growth as the outcome of a coordinated operation of diverse yet interconnected cellular processes.

The influence of leaf anatomy on the internal light environment and photosynthetic electron transport rate: exploration with a new leaf ray tracing model

Leaf photosynthesis is determined by biochemical properties and anatomical features. Here we developed a three-dimensional leaf model that can be used to evaluate the internal light environment of a leaf and its implications for whole-leaf electron transport rates (J). This model includes (i) the basic components of a leaf, such as the epidermis, palisade and spongy tissues, as well as the physical dimensions and arrangements of cell walls, vacuoles and chloroplasts; and (ii) an efficient forward ray-tracing algorithm, predicting the internal light environment for light of wavelengths between 400 and 2500nm. We studied the influence of leaf anatomy and ambient light on internal light conditions and J The results show that (i) different chloroplasts can experience drastically different light conditions, even when they are located at the same distance from the leaf surface; (ii) bundle sheath extensions, which are strips of parenchyma, collenchyma or sclerenchyma cells connecting the vascular bundles with the epidermis, can influence photosynthetic light-use efficiency of leaves; and (iii) chloroplast positioning can also influence the light-use efficiency of leaves. Mechanisms underlying leaf internal light heterogeneity and implications of the heterogeneity for photoprotection and for the convexity of the light response curves are discussed.

A Method of Accounting for Enzyme Costs in Flux Balance Analysis Reveals Alternative Pathways and Metabolite Stores in an Illuminated Arabidopsis Leaf

Flux balance analysis of plant metabolism is an established method for predicting metabolic flux phenotypes and for exploring the way in which the plant metabolic network delivers specific outcomes in different cell types, tissues, and temporal phases. A recurring theme is the need to explore the flexibility of the network in meeting its objectives and, in particular, to establish the extent to which alternative pathways can contribute to achieving specific outcomes. Unfortunately, predictions from conventional flux balance analysis minimize the simultaneous operation of alternative pathways, but by introducing flux-weighting factors to allow for the variable intrinsic cost of supporting each flux, it is possible to activate different pathways in individual simulations and, thus, to explore alternative pathways by averaging thousands of simulations. This new method has been applied to a diel genome-scale model of Arabidopsis (Arabidopsis thaliana) leaf metabolism to explore the flexibility of the network in meeting the metabolic requirements of the leaf in the light. This identified alternative flux modes in the Calvin-Benson cycle revealed the potential for alternative transitory carbon stores in leaves and led to predictions about the light-dependent contribution of alternative electron flow pathways and futile cycles in energy rebalancing. Notable features of the analysis include the light-dependent tradeoff between the use of carbohydrates and four-carbon organic acids as transitory storage forms and the way in which multiple pathways for the consumption of ATP and NADPH can contribute to the balancing of the requirements of photosynthetic metabolism with the energy available from photon capture.

Multigene manipulation of photosynthetic carbon assimilation increases CO2 fixation and biomass yield in tobacco

Over the next 40 years it has been estimated that a 50% increase in the yield of grain crops such as wheat and rice will be required to meet the food and fuel demands of the increasing world population. Transgenic tobacco plants have been generated with altered combinations of sedoheptulose-1,7-bisphosphatase, fructose-1,6-bisphosphate aldolase, and the cyanobacterial putative-inorganic carbon transporter B, ictB, of which have all been identified as targets to improve photosynthesis based on empirical studies. It is shown here that increasing the levels of the three proteins individually significantly increases the rate of photosynthetic carbon assimilation, leaf area, and biomass yield. Furthermore, the daily integrated measurements of photosynthesis showed that mature plants fixed between 12-19% more CO2 than the equivalent wild-type plants. Further enhancement of photosynthesis and yield was observed when sedoheptulose-1,7-bisphosphatase, fructose-1,6-bisphosphate aldolase, and ictB were over-expressed together in the same plant. These results demonstrate the potential for the manipulation of photosynthesis, using multigene-stacking approaches, to increase crop yields.

Natural variation in photosynthetic capacity, growth, and yield in 64 field-grown wheat genotypes

Increasing photosynthesis in wheat has been identified as an approach to enhance crop yield, with manipulation of key genes involved in electron transport and the Calvin cycle as one avenue currently being explored. However, natural variation in photosynthetic capacity is a currently unexploited genetic resource for potential crop improvement. Using gas-exchange analysis and protein analysis, the existing natural variation in photosynthetic capacity in a diverse panel of 64 elite wheat cultivars grown in the field was examined relative to growth traits, including biomass and harvest index. Significant variations in photosynthetic capacity, biomass, and yield were observed, although no consistent correlation was found between photosynthetic capacity of the flag leaf and grain yield when all cultivars were compared. The majority of the variation in photosynthesis could be explained by components related to maximum capacity and operational rates of CO2 assimilation, and to CO2 diffusion. Cluster analysis revealed that cultivars may have been bred unintentionally for desirable traits at the expense of photosynthetic capacity. These findings suggest that there is significant underutilized photosynthetic capacity among existing wheat varieties. Our observations are discussed in the context of exploiting existing natural variation in physiological processes for the improvement of photosynthesis in wheat.

Hierarchical modularization of biochemical pathways using fuzzy-c means clustering

Biological systems that are representative of regulatory, metabolic, or signaling pathways can be highly complex. Mathematical models that describe such systems inherit this complexity. As a result, these models can often fail to provide a path toward the intuitive comprehension of these systems. More coarse information that allows a perceptive insight of the system is sometimes needed in combination with the model to understand control hierarchies or lower level functional relationships. In this paper, we present a method to identify relationships between components of dynamic models of biochemical pathways that reside in different functional groups. We find primary relationships and secondary relationships. The secondary relationships reveal connections that are present in the system, which current techniques that only identify primary relationships are unable to show. We also identify how relationships between components dynamically change over time. This results in a method that provides the hierarchy of the relationships among components, which can help us to understand the low level functional structure of the system and to elucidate potential hierarchical control. As a proof of concept, we apply the algorithm to the epidermal growth factor signal transduction pathway, and to the C3 photosynthesis pathway. We identify primary relationships among components that are in agreement with previous computational decomposition studies, and identify secondary relationships that uncover connections among components that current computational approaches were unable to reveal.

Model-assisted analysis of sugar metabolism throughout tomato fruit development reveals enzyme and carrier properties in relation to vacuole expansion

A kinetic model combining enzyme activity measurements and subcellular compartmentation was parameterized to fit the sucrose, hexose, and glucose-6-P contents of pericarp throughout tomato (Solanum lycopersicum) fruit development. The model was further validated using independent data obtained from domesticated and wild tomato species and on transgenic lines. A hierarchical clustering analysis of the calculated fluxes and enzyme capacities together revealed stage-dependent features. Cell division was characterized by a high sucrolytic activity of the vacuole, whereas sucrose cleavage during expansion was sustained by both sucrose synthase and neutral invertase, associated with minimal futile cycling. Most importantly, a tight correlation between flux rate and enzyme capacity was found for fructokinase and PPi-dependent phosphofructokinase during cell division and for sucrose synthase, UDP-glucopyrophosphorylase, and phosphoglucomutase during expansion, thus suggesting an adaptation of enzyme abundance to metabolic needs. In contrast, for most enzymes, flux rates varied irrespectively of enzyme capacities, and most enzymes functioned at <5% of their maximal catalytic capacity. One of the major findings with the model was the high accumulation of soluble sugars within the vacuole together with organic acids, thus enabling the osmotic-driven vacuole expansion that was found during cell division.

Elements required for an efficient NADP-malic enzyme type C4 photosynthesis

C4 photosynthesis has higher light, nitrogen, and water use efficiencies than C3 photosynthesis. Although the basic anatomical, cellular, and biochemical features of C4 photosynthesis are well understood, the quantitative significance of each element of C4 photosynthesis to the high photosynthetic efficiency are not well defined. Here, we addressed this question by developing and using a systems model of C4 photosynthesis, which includes not only the Calvin-Benson cycle, starch synthesis, sucrose synthesis, C4 shuttle, and CO₂ leakage, but also photorespiration and metabolite transport between the bundle sheath cells and mesophyll cells. The model effectively simulated the CO₂ uptake rates, and the changes of metabolite concentrations under varied CO₂ and light levels. Analyses show that triose phosphate transport and CO₂ leakage can help maintain a high photosynthetic rate by balancing ATP and NADPH amounts in bundle sheath cells and mesophyll cells. Finally, we used the model to define the optimal enzyme properties and a blueprint for C4 engineering. As such, this model provides a theoretical framework for guiding C4 engineering and studying C4 photosynthesis in general.

Regulatory principles and experimental approaches to the circadian control of starch turnover

In many plants, starch is synthesized during the day and degraded during the night to avoid carbohydrate starvation in darkness. The circadian clock participates in a dynamic adjustment of starch turnover to changing environmental condition through unknown mechanisms. We used mathematical modelling to explore the possible scenarios for the control of starch turnover by the molecular components of the plant circadian clock. Several classes of plausible models were capable of describing the starch dynamics observed in a range of clock mutant plants and light conditions, including discriminating circadian protocols. Three example models of these classes are studied in detail, differing in several important ways. First, the clock components directly responsible for regulating starch degradation are different in each model. Second, the intermediate species in the pathway may play either an activating or inhibiting role on starch degradation. Third, the system may include a light-dependent interaction between the clock and downstream processes. Finally, the clock may be involved in the regulation of starch synthesis. We discuss the differences among the models’ predictions for diel starch profiles and the properties of the circadian regulators. These suggest additional experiments to elucidate the pathway structure, avoid confounding results and identify the molecular components involved.

e-Photosynthesis: a comprehensive dynamic mechanistic model of C3 photosynthesis: from light capture to sucrose synthesis

Photosynthesis is arguably the most researched of all plant processes. A dynamic model of leaf photosynthesis that includes each discrete process from light capture to carbohydrate synthesis, e-photosynthesis, is described. It was developed by linking and extending our previous models of photosystem II (PSII) energy transfer and photosynthetic C3 carbon metabolism to include electron transfer processes around photosystem I (PSI), ion transfer between the lumen and stroma, ATP synthesis and NADP reduction to provide a complete representation. Different regulatory processes linking the light and dark reactions are also included: Rubisco activation via Rubisco activase, pH and xanthophyll cycle-dependent non-photochemical quenching mechanisms, as well as the regulation of enzyme activities via the ferredoxin-theoredoxin system. Although many further feedback and feedforward controls undoubtedly exist, it is shown that e-photosynthesis effectively mimics the typical kinetics of leaf CO₂ uptake, O₂ evolution, chlorophyll fluorescence emission, lumen and stromal pH, and membrane potential following perturbations in light, [CO₂] and [O₂] observed in intact C3 leaves. The model provides a framework for guiding engineering of improved photosynthetic efficiency, for evaluating multiple non-invasive measures used in emerging phenomics facilities, and for quantitative assessment of strengths and weaknesses within the understanding of photosynthesis as an integrated process.

Identification of a metabolic bottleneck for cold acclimation in Arabidopsis thaliana

Central carbohydrate metabolism of Arabidopsis thaliana is known to play a crucial role during cold acclimation and the acquisition of freezing tolerance. During cold exposure, many carbohydrates accumulate and a new metabolic homeostasis evolves. In the present study, we analyse the diurnal dynamics of carbohydrate homeostasis before and after cold exposure in three natural accessions showing distinct cold acclimation capacity. Diurnal dynamics of soluble carbohydrates were found to be significantly different in cold-sensitive and cold-tolerant accessions. Although experimentally determined maximum turnover rates for sucrose phosphate synthase in cold-acclimated leaves were higher for cold-tolerant accessions, model simulations of diurnal carbohydrate dynamics revealed similar fluxes. This implied a significantly higher capacity for sucrose synthesis in cold-tolerant than cold-sensitive accessions. Based on this implication resulting from mathematical model simulation, a critical temperature for sucrose synthesis was calculated using the Arrhenius equation and experimentally validated in the cold-sensitive accession C24. At the critical temperature suggested by model simulation, an imbalance in photosynthetic carbon fixation ultimately resulting in oxidative stress was observed. It is therefore concluded that metabolic capacities at least in part determine the ability of accessions of Arabidopsis thaliana to cope with changes in environmental conditions.

Thermodynamic constraints shape the structure of carbon fixation pathways

Thermodynamics impose a major constraint on the structure of metabolic pathways. Here, we use carbon fixation pathways to demonstrate how thermodynamics shape the structure of pathways and determine the cellular resources they consume. We analyze the energetic profile of prototypical reactions and show that each reaction type displays a characteristic change in Gibbs energy. Specifically, although carbon fixation pathways display a considerable structural variability, they are all energetically constrained by two types of reactions: carboxylation and carboxyl reduction. In fact, all adenosine triphosphate (ATP) molecules consumed by carbon fixation pathways - with a single exception - are used, directly or indirectly, to power one of these unfavorable reactions. When an indirect coupling is employed, the energy released by ATP hydrolysis is used to establish another chemical bond with high energy of hydrolysis, e.g. a thioester. This bond is cleaved by a downstream enzyme to energize an unfavorable reaction. Notably, many pathways exhibit reduced ATP requirement as they couple unfavorable carboxylation or carboxyl reduction reactions to exergonic reactions other than ATP hydrolysis. In the most extreme example, the reductive acetyl coenzyme A (acetyl-CoA) pathway bypasses almost all ATP-consuming reactions. On the other hand, the reductive pentose phosphate pathway appears to be the least ATP-efficient because it is the only carbon fixation pathway that invests ATP in metabolic aims other than carboxylation and carboxyl reduction. Altogether, our analysis indicates that basic thermodynamic considerations accurately predict the resource investment required to support a metabolic pathway and further identifies biochemical mechanisms that can decrease this requirement.

Understanding biological timing using mechanistic and black-box models

The use of mathematical modelling in understanding and dissecting physiological mechanisms in plants has seen many successes. Notably, studies of the component interactions of the Arabidopsis circadian clock have yielded multiple insights into the roles of specific regulators at the transcriptional and post-transcriptional level. In this article, I review the use of mathematical techniques in dissecting the Arabidopsis clock mechanism, covering first the well-established use of mechanistic models implemented as systems of nonlinear ordinary differential equations. In situations where mechanistic models are not appropriate, I describe how linear time-invariant (LTI) systems, a type of black-box model, can offer quantitative descriptions of biological systems that provide a systems-level understanding without detailed descriptions of the underlying mechanism. A comparison of the two approaches is provided to exemplify when LTI systems modelling might offer advantages for interpreting biological measurements. In particular, formal analysis of large datasets with LTI systems can offer genome-scale inferences, which is of timely relevance as novel experimental techniques are generating increasingly large quantities of data.

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.

A survey of carbon fixation pathways through a quantitative lens

While the reductive pentose phosphate cycle is responsible for the fixation of most of the carbon in the biosphere, it has several natural substitutes. In fact, due to the characterization of three new carbon fixation pathways in the last decade, the diversity of known metabolic solutions for autotrophic growth has doubled. In this review, the different pathways are analysed and compared according to various criteria, trying to connect each of the different metabolic alternatives to suitable environments or metabolic goals. The different roles of carbon fixation are discussed; in addition to sustaining autotrophic growth it can also be used for energy conservation and as an electron sink for the recycling of reduced electron carriers. Our main focus in this review is on thermodynamic and kinetic aspects, including thermodynamically challenging reactions, the ATP requirement of each pathway, energetic constraints on carbon fixation, and factors that are expected to limit the rate of the pathways. Finally, possible metabolic structures of yet unknown carbon fixation pathways are suggested and discussed.