IntroductionPlants employ the Calvin-Benson cycle (CBC) to fix atmospheric CO2 for the production of biomass. The flux of carbon through the CBC is limited by the activity and selectivity of Ribulose-1,5-Bisphosphate Carboxylase/Oxygenase (RuBisCO). Alternative CO2 fixation pathways that do not use RuBisCO to fix CO2 have evolved in some anaerobic, autotrophic microorganisms.MethodsRather than modifying existing routes of carbon metabolism in plants, we have developed a synthetic carbon fixation cycle that does not exist in nature but is inspired by metabolisms of bacterial autotrophs. In this work, we build and characterize a condensed, reverse tricarboxylic acid (crTCA) cycle in vitro and in planta.ResultsWe demonstrate that a simple, synthetic cycle can be used to fix carbon in vitro under aerobic and mesophilic conditions and that these enzymes retain activity whenexpressed transiently in planta. We then evaluate stable transgenic lines of Camelina sativa that have both phenotypic and physiologic changes. Transgenic C. sativa are shorter than controls with increased rates of photosynthetic CO2 assimilation and changes in photorespiratory metabolism.DiscussionThis first iteration of a build-test-learn phase of the crTCA cycle provides promising evidence that this pathway can be used to increase photosynthetic capacity in plants.

In the future, plants may encounter increased light and elevated CO 2 levels. How consequent alterations in photosynthetic rates will impact fluxes in photosynthetic carbon metabolism remains uncertain. Respiration in light ( R L ) is pivotal in plant carbon balance and a key parameter in photosynthesis models. Understanding the dynamics of photosynthetic metabolism and R L under varying environmental conditions is essential for optimizing plant growth and agricultural productivity. However, measuring R L under high light and high CO 2 (HLHC) conditions poses challenges using traditional gas exchange methods. In this study, we employed isotopically nonstationary metabolic flux analysis (INST-MFA) to estimate R L and investigate photosynthetic carbon flux, unveiling nuanced adjustments in Camelina sativa under HLHC. Despite numerous flux alterations in HLHC, R L remained stable. HLHC affects several factors influencing R L , such as starch and sucrose partitioning, v o / v c ratio, triose phosphate partitioning, and hexose kinase activity. Analysis of A/C i curve operational points reveals that HLHC's major changes primarily stem from CO 2 suppressing photorespiration. Integration of these fluxes into a simplified model predicts changes in CBC labeling under HLHC. This study extends our prior discovery that incomplete CBC labeling is due to unlabeled carbon reimported during R L , offering insights into manipulating labeling through adjustments in photosynthetic rates.

Camelina sativa has considerable promise as a dedicated industrial oilseed crop. Its oil-based blends have been tested and approved as liquid transportation fuels. Previously, we utilized metabolomic and transcriptomic profiling approaches and identified metabolic bottlenecks that control oil production and accumulation in seeds. Accordingly, we selected candidate genes for the metabolic engineering of Camelina. Here we targeted the overexpression of Camelina PDCT gene, which encodes the phosphatidylcholine: diacylglycerol cholinephosphotransferase enzyme. PDCT is proposed as a gatekeeper responsible for the interconversions of diacylglycerol (DAG) and phosphatidylcholine (PC) pools and has the potential to increase the levels of TAG in seeds. To confirm whether increased CsPDCT activity in developing Camelina seeds would enhance carbon flux toward increased levels of TAG and alter oil composition, we overexpressed the CsPDCT gene under the control of the seed-specific phaseolin promoter. Camelina transgenics exhibited significant increases in seed yield (19-56%), seed oil content (9-13%), oil yields per plant (32-76%), and altered polyunsaturated fatty acid (PUFA) content compared to their parental wild-type (WT) plants. Results from [14C] acetate labeling of Camelina developing embryos expressing CsPDCT in culture indicated increased rates of radiolabeled fatty acid incorporation into glycerolipids (up to 64%, 59%, and 43% higher in TAG, DAG, and PC, respectively), relative to WT embryos. We conclude that overexpression of PDCT appears to be a positive strategy to achieve a synergistic effect on the flux through the TAG synthesis pathway, thereby further increasing oil yields in Camelina.

The thermoacidophilic red alga Cyanidioschyzon merolae survives its challenging environment likely in part by operating a carbon-concentrating mechanism (CCM). Here, we demonstrated that C. merolae's cellular affinity for CO2 is stronger than the affinity of its rubisco for CO2. This finding provided additional evidence that C. merolae operates a CCM while lacking the structures and functions characteristic of CCMs in other organisms. To test how such a CCM could function, we created a mathematical compartmental model of a simple CCM, distinct from those we have seen previously described in detail. The results of our modeling supported the feasibility of this proposed minimal and non-canonical CCM in C. merolae. To facilitate the robust modeling of this process, we measured and incorporated physiological and enzymatic parameters into the model. Additionally, we trained a surrogate machine-learning model to emulate the mechanistic model and characterized the effects of model parameters on key outputs. This parameter exploration enabled us to identify model features that influenced whether the model met the experimentally derived criteria for functional carbon concentration and efficient energy usage. Such parameters included cytosolic pH, bicarbonate pumping cost and kinetics, cell radius, carboxylation velocity, number of thylakoid membranes, and CO2 membrane permeability. Our exploration thus suggested that a non-canonical CCM could exist in C. merolae and illuminated the essential features generally necessary for CCMs to function. The thermoacidophilic red alga Cyanidioschyzon merolae possesses a unique carbon-concentrating mechanism (CCM), and a model illuminates the essential features generally required for CCM function.

Carbon-concentrating mechanisms (CCMs) have evolved numerous times in photosynthetic organisms. They elevate the concentration of CO2 around the carbon-fixing enzyme rubisco, thereby increasing CO2 assimilatory flux and reducing photorespiration. Biophysical CCMs, like the pyrenoid-based CCM (PCCM) of Chlamydomonas reinhardtii or carboxysome systems of cyanobacteria, are common in aquatic photosynthetic microbes, but in land plants appear only among the hornworts. To predict the likely efficiency of biophysical CCMs in C3 plants, we used spatially resolved reaction-diffusion models to predict rubisco saturation and light use efficiency. We found that the energy efficiency of adding individual CCM components to a C3 land plant is highly dependent on the permeability of lipid membranes to CO2, with values in the range reported in the literature that are higher than those used in previous modeling studies resulting in low light use efficiency. Adding a complete PCCM into the leaf cells of a C3 land plant was predicted to boost net CO2 fixation, but at higher energetic costs than those incurred by photorespiratory losses without a CCM. Two notable exceptions were when substomatal CO2 levels are as low as those found in land plants that already use biochemical CCMs and when gas exchange is limited, such as with hornworts, making the use of a biophysical CCM necessary to achieve net positive CO2 fixation under atmospheric CO2 levels. This provides an explanation for the uniqueness of hornworts' CCM among land plants and the evolution of pyrenoids multiple times.

Acyl editing refers to a deacylation and reacylation cycle on a lipid, which allows for fatty acid desaturation and modification prior to being removed and incorporated into other pools. Acyl editing is an important determinant of glycerolipid synthesis and has been well-characterized in land plants, thus this review begins with an overview of acyl editing in plants. Much less is known about acyl editing in algae, including the extent to which acyl editing impacts lipid synthesis and on which lipid substrate(s) it occurs. This review compares what is known about acyl editing on its major hub phosphatidylcholine (PC) in land plants with the evidence for acyl editing of betaine lipids such as diacylglyceryltrimethylhomoserine (DGTS), the structural analog that replaces PC in several species of microalgae. In land plants, PC is also known to be a major source of fatty acids and diacylglycerol (DAG) for synthesis of the neutral lipid triacylglycerol (TAG). We review the evidence that DGTS contributes substantially to TAG accumulation in algae as a source of fatty acids, but not as a precursor to DAG. We conclude with evidence of acyl editing on other membrane lipid substrates in plants and algae apart from PC or DGTS, and discuss future analyses to elucidate the role of DGTS and other betaine lipids in acyl editing in microalgae.

Cyanidioschyzon merolae is an extremophilic red microalga which grows in low-pH, high-temperature environments. The basis of C. merolae's environmental resilience is not fully characterized, including whether this alga uses a carbon-concentrating mechanism (CCM). To determine if C. merolae uses a CCM, we measured CO2 uptake parameters using an open-path infra-red gas analyzer and compared them to values expected in the absence of a CCM. These measurements and analysis indicated that C. merolae had the gas-exchange characteristics of a CCM-operating organism: low CO2 compensation point, high affinity for external CO2, and minimized rubisco oxygenation. The biomass δ13C of C. merolae was also consistent with a CCM. The apparent presence of a CCM in C. merolae suggests the use of an unusual mechanism for carbon concentration, as C. merolae is thought to lack a pyrenoid and gas-exchange measurements indicated that C. merolae primarily takes up inorganic carbon as carbon dioxide, rather than bicarbonate. We use homology to known CCM components to propose a model of a pH-gradient-based CCM, and we discuss how this CCM can be further investigated.

13C-Metabolic Flux Analysis (13C-MFA) and Flux Balance Analysis (FBA) are widely used to investigate the operation of biochemical networks in both biological and biotechnological research. Both of these methods use metabolic reaction network models of metabolism operating at steady state, so that reaction rates (fluxes) and the levels of metabolic intermediates are constrained to be invariant. They provide estimated (MFA) or predicted (FBA) values of the fluxes through the network in vivo, which cannot be measured directly. A number of approaches have been taken to test the reliability of estimates and predictions from constraint-based methods and to decide on and/or discriminate between alternative model architectures. Despite advances in other areas of the statistical evaluation of metabolic models, validation and model selection methods have been underappreciated and underexplored. We review the history and state-of-the-art in constraint-based metabolic model validation and model selection. Applications and limitations of the χ2-test of goodness-of-fit, the most widely used quantitative validation and selection approach in 13C-MFA, are discussed, and complementary and alternative forms of validation and selection are proposed. A combined model validation and selection framework for 13C-MFA incorporating metabolite pool size information that leverages new developments in the field is presented and advocated for. Finally, we discuss how the adoption of robust validation and selection procedures can enhance confidence in constraint-based modeling as a whole and ultimately facilitate more widespread use of FBA in biotechnology in particular.

Daylength, a seasonal and latitudinal variable, exerts a substantial impact on plant growth. However, the relationship between daylength and growth is nonproportional, suggesting the existence of adaptive mechanisms. Thus, our study aimed to comprehensively investigate the adaptive strategies employed by plants in response to daylength variation. We grew false flax (Camelina sativa) plants, a model oilseed crop, under long-day (LD) and short-day (SD) conditions and used growth measurements, gas exchange measurements, and isotopic labeling techniques, including 13C, 14C, and 2H2O, to determine responses to different daylengths. Our findings revealed that daylength influences various growth parameters, photosynthetic physiology, carbon partitioning, metabolic fluxes, and metabolite levels. SD plants employed diverse mechanisms to compensate for reduced CO2 fixation in the shorter photoperiod. These mechanisms included enhanced photosynthetic rates and reduced respiration in the light (RL), leading to increased shoot investment. Additionally, SD plants exhibited reduced rates of the glucose 6-phosphate (G6P) shunt and greater partitioning of sugars into starch, thereby sustaining carbon availability during the longer night. Isotopic labeling results further demonstrated substantial alterations in the partitioning of amino acids and TCA cycle intermediates between rapidly and slowly turning over pools. Overall, the results point to multiple developmental, physiological, and metabolic ways in which plants adapt to different daylengths to maintain growth.

The modeling of rates of biochemical reactions-fluxes-in metabolic networks is widely used for both basic biological research and biotechnological applications. A number of different modeling methods have been developed to estimate and predict fluxes, including kinetic and constraint-based (Metabolic Flux Analysis and flux balance analysis) approaches. Although different resources exist for teaching these methods individually, to-date no resources have been developed to teach these approaches in an integrative way that equips learners with an understanding of each modeling paradigm, how they relate to one another, and the information that can be gleaned from each. We have developed a series of modeling simulations in Python to teach kinetic modeling, metabolic control analysis, 13C-metabolic flux analysis, and flux balance analysis. These simulations are presented in a series of interactive notebooks with guided lesson plans and associated lecture notes. Learners assimilate key principles using models of simple metabolic networks by running simulations, generating and using data, and making and validating predictions about the effects of modifying model parameters. We used these simulations as the hands-on computer laboratory component of a four-day metabolic modeling workshop and participant survey results showed improvements in learners' self-assessed competence and confidence in understanding and applying metabolic modeling techniques after having attended the workshop. The resources provided can be incorporated in their entirety or individually into courses and workshops on bioengineering and metabolic modeling at the undergraduate, graduate, or postgraduate level.

Motivation The accurate prediction of complex phenotypes such as metabolic fluxes in living systems is a grand challenge for systems biology and central to efficiently identifying biotechnological interventions that can address pressing industrial needs. The application of gene expression data to improve the accuracy of metabolic flux predictions using mechanistic modeling methods such as Flux Balance Analysis (FBA) has not been previously demonstrated in multi-tissue systems, despite their biotechnological importance. We hypothesized that a method for generating metabolic flux predictions informed by relative expression levels between tissues would improve prediction accuracy. Results Relative gene expression levels derived from multiple transcriptomic and proteomic datasets were integrated into Flux Balance Analysis predictions of a multi-tissue, diel model of Arabidopsis thaliana’s central metabolism. This integration dramatically improved the agreement of flux predictions with experimentally based flux maps from 13C Metabolic Flux Analysis (MFA) compared with a standard parsimonious FBA approach. Disagreement between FBA predictions and MFA flux maps, as measured by weighted averaged percent error values, dropped from between 169-180% and 94-103% in high light and low light conditions, respectively, to between 10-12% and 9-11%, depending on the gene expression dataset used. The incorporation of gene expression data into the modeling process also substantially altered the predicted carbon and energy economy of the plant. Availability Code is available from https://github.com/Gibberella/ArabidopsisGeneExpressionWeights Contact yairhill@msu.edu

Lipid metabolism in microalgae has attracted much interest due to potential utilization of lipids as feedstocks for biofuels, nutraceuticals, and other high-value compounds. Chlamydomonas reinhardtii is a model organism for characterizing the synthesis of the neutral lipid triacylglycerol (TAG), from which biodiesel is made. While much of TAG accumulation under N-deprivation is the result of de novo fatty acid (FA) synthesis, recent work has revealed that approximately one-third of FAs, especially polyunsaturated FAs (PUFAs), come from preexisting membrane lipids. Here, we used 13C isotopic labeling and mass spectrometry to analyze the turnover of glycerol backbones, headgroups, FAs, whole molecules, and molecular fragments of individual lipids. About one-third of the glyceryl backbones in TAG are derived from preexisting membrane lipids, as are approximately one-third of FAs. The different moieties of the major galactolipids turn over synchronously, while the FAs of diacylglyceryltrimethylhomoserine (DGTS), the most abundant extraplastidial lipid, turn over independently of the rest of the molecule. The major plastidic lipid monogalactosyldiacylglycerol (MGDG), whose predominant species is 18:3α/16:4, was previously shown to be a major source of PUFAs for TAG synthesis. This study reveals that MGDG turns over as whole molecules, the 18:3α/16:4 species is present in both DAG and TAG, and the positional distribution of these PUFAs is identical in MGDG, DAG, and TAG. We conclude that headgroup removal with subsequent acylation is the mechanism by which the major MGDG species is converted to TAG during N-deprivation. This has noteworthy implications for engineering the composition of microalgal TAG for food, fuel, and other applications.

Carbon-neutral production of valuable bioproducts is critical to sustainable development but remains limited by the slow engineering of photosynthetic organisms. Improving existing synthetic biology tools to engineer model organisms to fix carbon dioxide is one route to overcoming the limitations of photosynthetic organisms. In this work, we describe a pipeline that enabled the deletion of a conditionally essential gene from the Shewanella oneidensis MR-1 genome. S. oneidensis is a simple bacterial host that could be used for electricity-driven conversion of carbon dioxide in the future with further genetic engineering. We used Flux Balance Analysis (FBA) to model carbon and energy flows in central metabolism and assess the effects of single and double gene deletions. We modeled the growth of deletion strains under several alternative conditions to identify substrates that restore viability to an otherwise lethal gene knockout. These predictions were tested in vivo using a Mobile-CRISPRi gene knockdown system. The information learned from FBA and knockdown experiments informed our strategy for gene deletion, allowing us to successfully delete an "expected essential" gene, gpmA. FBA predicted, knockdown experiments supported, and deletion confirmed that the "essential" gene gpmA is not needed for survival, dependent on the medium used. Removal of gpmA is a first step toward driving electrode-powered CO2 fixation via RuBisCO. This work demonstrates the potential for broadening the scope of genetic engineering in S. oneidensis as a synthetic biology chassis. By combining computational analysis with a CRISPRi knockdown system in this way, one can systematically assess the impact of conditionally essential genes and use this knowledge to generate mutations previously thought unachievable.

Significance Photosynthesis metabolites are quickly labeled when 13CO2 is fed to leaves, but the time course of labeling reveals additional contributing processes involved in the metabolic dynamics of photosynthesis. The existence of three such processes is demonstrated, and a metabolic flux model is developed to explore and characterize them. The model is consistent with a slow return of carbon from cytosolic and vacuolar sugars into the Calvin–Benson cycle through the oxidative pentose phosphate pathway. Our results provide insight into how carbon assimilation is integrated into the metabolic network of photosynthetic cells with implications for global carbon fluxes.

Plants employ the Calvin-Benson cycle (CBC) to fix atmospheric CO 2 for the production of biomass. The flux of carbon through the CBC is limited by the activity and selectivity of ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO). Alternative pathways that do not use RuBisCO to fix CO 2 exist but occur only in anaerobic microorganisms. Rather than modifying existing routes of carbon metabolism in plants, we have developed a synthetic carbon fixation cycle that does not exist in nature, but is inspired by metabolisms of bacterial autotrophs. This synthetic cycle uses endogenous plant metabolites to fix CO 2 and yield glyoxylate as a product. In this work, we build and characterize a condensed, reverse tricarboxylic acid (crTCA) cycle in vitro and in planta . We demonstrate that a simple, synthetic cycle can be used to fix carbon in vitro under aerobic and mesophilic conditions and that these enzymes retain activity when expressed transiently in planta . We then evaluate stable transgenic lines of Camelina sativa that have both phenotypic and physiologic changes. Transgenic C. sativa are shorter than controls with increased rates of photosynthetic CO 2 assimilation and changes in photorespiratory metabolism. This first iteration of a build-test-learn phase of the crTCA cycle provides promising evidence that this pathway can be used to increase photosynthetic capacity in plants.

Quantitative flux maps describing glycerolipid synthesis can be important tools for rational engineering of lipid content and composition in oilseeds. Lipid accumulation in cultured embryos of Camelina sativa is known to mimic that of seeds in terms of rate of lipid synthesis and composition. To assess the kinetic complexity of the glycerolipid flux network, cultured embryos were incubated with [14C/13C]glycerol, and initial and steady state rates of [14C/13Cglyceryl] lipid accumulation were measured. At steady state, the linear accumulations of labeled lipid classes matched those expected from mass compositions. The system showed an apparently simple kinetic precursor-product relationship between the intermediate pool, dominated by diacylglycerol (DAG) and phosphatidylcholine (PC), and the triacylglycerol (TAG) product. We also conducted isotopomer analyses on hydrogenated lipid class species. [13C3glyceryl] labeling of DAG and PC, together with estimates of endogenous [12C3glyceryl] dilution, showed that each biosynthetically active lipid pool is ∼30% of the total by moles. This validates the concept that lipid sub-pools can describe lipid biosynthetic networks. By tracking the kinetics of [13C3glyceryl] and [13C2acyl] labeling, we observed two distinct TAG synthesis components. The major TAG synthesis flux (∼75%) was associated with >95% of the DAG/PC intermediate pool, with little glycerol being metabolized to fatty acids, and with little dilution from endogenous glycerol; a smaller flux exhibited converse characteristics. This kinetic heterogeneity was further explored using postlabeling embryo dissection and differential lipid extractions. The minor flux was tentatively localized to surface cells across the whole embryo. Such heterogeneity must be recognized in order to construct accurate gene expression patterns and metabolic networks describing lipid biosynthesis in developing embryos.

The microalga Chlorella sorokiniana has attracted much attention for lipid production and wastewater treatment. It can perform photosynthesis and organic carbon utilization concurrently. To understand its phototrophic metabolism, a biomass compositional analysis, a 13C metabolic flux analysis, and metabolite pool size analyses were performed. Under dark condition, the oxidative pentose phosphate pathway (OPP) was the major route for glucose catabolism (88% carbon flux) and a cyclic OPP–glycolytic route for glucose catabolism was formed. Under light condition, fluxes in the glucose catabolism, tricarboxylic acid (TCA) cycle, and anaplerotic reaction (CO2 fixation via phosphoenolpyruvate carboxylase) were all suppressed. Meanwhile, the RuBisCO reaction became active and the ratio of its carbon fixation to glucose carbon utilization was determined as 7:100. Moreover, light condition significantly reduced the pool sizes of sugar phosphate metabolites (such as E4P, F6P, and S7P) and promoted biomass synthesis (which reached 0.155 h−1). In addition, light condition increased glucose consumption rates, leading to higher ATP and NADPH production and a higher protein content (43% vs. 30%) in the biomass during the exponential growth phase.

Respiration in the light (RL) releases CO2 in photosynthesizing leaves and is a phenomenon that occurs independently from photorespiration. Since RL lowers net carbon fixation, understanding RL could help improve plant carbon-use efficiency and models of crop photosynthesis. Although RL was identified more than 75 years ago, its biochemical mechanisms remain unclear. To identify reactions contributing to RL, we mapped metabolic fluxes in photosynthesizing source leaves of the oilseed crop and model plant camelina (Camelina sativa). We performed a flux analysis using isotopic labeling patterns of central metabolites during 13CO2 labeling time course, gas exchange, and carbohydrate production rate experiments. To quantify the contributions of multiple potential CO2 sources with statistical and biological confidence, we increased the number of metabolites measured and reduced biological and technical heterogeneity by using single mature source leaves and quickly quenching metabolism by directly injecting liquid N2; we then compared the goodness-of-fit between these data and data from models with alternative metabolic network structures and constraints. Our analysis predicted that RL releases 5.2 μmol CO2 g-1 FW h-1 of CO2, which is relatively consistent with a value of 9.3 μmol CO2 g-1 FW h-1 measured by CO2 gas exchange. The results indicated that ≤10% of RL results from TCA cycle reactions, which are widely considered to dominate RL. Further analysis of the results indicated that oxidation of glucose-6-phosphate to pentose phosphate via 6-phosphogluconate (the G6P/OPP shunt) can account for >93% of CO2 released by RL.