Metabolic flux analysis of heterotrophic growth in Chlamydomonas reinhardtii

Model validation and selection in metabolic flux analysis and flux balance analysis

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 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. These fluxes can shed light on basic biology and have been successfully used to inform metabolic engineering strategies. Several approaches have been taken to test the reliability of estimates and predictions from constraint-based methods and to compare alternative model architectures. Despite advances in other areas of the statistical evaluation of metabolic models, such as the quantification of flux estimate uncertainty, 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 adopting 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.

Chlamydomonas mutants lacking chloroplast TRIOSE PHOSPHATE TRANSPORTER3 are metabolically compromised and light-sensitive

Modulation of photoassimilate export from the chloroplast is essential for controlling the distribution of fixed carbon in the cell and maintaining optimum photosynthetic rates. In this study we identified chloroplast TRIOSE PHOSPHATE/PHOSPHATE TRANSLOCATOR2 (CreTPT2) and CreTPT3 in the green alga Chlamydomonas (Chlamydomonas reinhardtii), which exhibit similar substrate specificities but whose encoding genes are differentially expressed over the diurnal cycle. We focused mostly on CreTPT3 because of its high level of expression and the severe phenotype exhibited by tpt3 relative to tpt2 mutants. Null mutants for CreTPT3 had a pleiotropic phenotype that affected growth, photosynthetic activities, metabolite profiles, carbon partitioning, and organelle-specific accumulation of H2O2. These analyses demonstrated that CreTPT3 is a dominant conduit on the chloroplast envelope for the transport of photoassimilates. In addition, CreTPT3 can serve as a safety valve that moves excess reductant out of the chloroplast and appears to be essential for preventing cells from experiencing oxidative stress and accumulating reactive oxygen species, even under low/moderate light intensities. Finally, our studies indicate subfunctionalization of the CreTPT transporters and suggest that there are differences in managing the export of photoassimilates from the chloroplasts of Chlamydomonas and vascular plants.

Model Validation and Selection in Metabolic Flux Analysis and Flux Balance Analysis

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.

The effects of acetate and glucose on carbon fixation and carbon utilization in mixotrophy of Haematococcus pluvialis

The culture method using sodium acetate and glucose, widely used as organic carbon sources in the mixotrophy of Haematococcus pluvialis, was compared with its autotrophy. In the 12-day culture, mixotrophy using sodium acetate and glucose increased by 40.4% and 77.1%, respectively, compared to autotrophy, but the mechanisms for the increasing biomass were different. The analysis of the mechanism was divided into autotrophic and heterotrophic metabolism. The mixotrophy with glucose increased the biomass by directly supplying the substrate and ATP to the TCA cycle while inhibiting photosynthesis. Gene expressions related to glycolysis and carbon fixation pathway were confirmed in autotrophy and mixotrophy with glucose and acetate. The metabolism predicted in the mixotrophy with acetate and glucose was proposed via autotrophic and heterotrophic metabolism analysis. The mechanism of Haematococcus pluvialis under mixotrophic conditions with high CO₂ concentration was confirmed through this study.

Proteomics unveil a central role for peroxisomes in butyrate assimilation of the heterotrophic Chlorophyte alga Polytomella sp

Volatile fatty acids found in effluents of the dark fermentation of biowastes can be used for mixotrophic growth of microalgae, improving productivity and reducing the cost of the feedstock. Microalgae can use the acetate in the effluents very well, but butyrate is poorly assimilated and can inhibit growth above 1 gC.L-1. The non-photosynthetic chlorophyte alga Polytomella sp. SAG 198.80 was found to be able to assimilate butyrate fast. To decipher the metabolic pathways implicated in butyrate assimilation, quantitative proteomics study was developed comparing Polytomella sp. cells grown on acetate and butyrate at 1 gC.L-1. After statistical analysis, a total of 1772 proteins were retained, of which 119 proteins were found to be overaccumulated on butyrate vs. only 46 on acetate, indicating that butyrate assimilation necessitates additional metabolic steps. The data show that butyrate assimilation occurs in the peroxisome via the β-oxidation pathway to produce acetyl-CoA and further tri/dicarboxylic acids in the glyoxylate cycle. Concomitantly, reactive oxygen species defense enzymes as well as the branched amino acid degradation pathway were strongly induced. Although no clear dedicated butyrate transport mechanism could be inferred, several membrane transporters induced on butyrate are identified as potential condidates. Metabolic responses correspond globally to the increased needs for central cofactors NAD, ATP and CoA, especially in the peroxisome and the cytosol.

Chlamydomonas reinhardtii Alternates Peroxisomal Contents in Response to Trophic Conditions

Chlamydomonas reinhardtii is a model green microalga capable of heterotrophic growth on acetic acid but not fatty acids, despite containing a full complement of genes for β-oxidation. Recent reports indicate that the alga preferentially sequesters, rather than breaks down, lipid acyl chains as a means to rebuild its membranes rapidly. Here, we assemble a list of potential Chlamydomonas peroxins (PEXs) required for peroxisomal biogenesis to suggest that C. reinhardtii has a complete set of peroxisome biogenesis factors. To determine involvements of the peroxisomes in the metabolism of exogenously added fatty acids, we examined transgenic C. reinhardtii expressing fluorescent proteins fused to N- or C-terminal peptide of peroxisomal proteins, concomitantly with fluorescently labeled palmitic acid under different trophic conditions. We used confocal microscopy to track the populations of the peroxisomes in illuminated and dark conditions, with and without acetic acid as a carbon source. In the cells, four major populations of compartments were identified, containing: (1) a glyoxylate cycle enzyme marker and a protein containing peroxisomal targeting signal 1 (PTS1) tripeptide but lacking the fatty acid marker, (2) the fatty acid marker alone, (3) the glyoxylate cycle enzyme marker alone, and (4) the PTS1 marker alone. Less than 5% of the compartments contained both fatty acid and peroxisomal markers. Statistical analysis on optically sectioned images found that C. reinhardtii simultaneously carries diverse populations of the peroxisomes in the cell and modulates peroxisomal contents based on light conditions. On the other hand, the ratio of the compartment containing both fatty acid and peroxisomal markers did not change significantly regardless of the culture conditions. The result indicates that β-oxidation may be only a minor occurrence in the peroxisomal population in C. reinhardtii, which supports the idea that lipid biosynthesis and not β-oxidation is the primary metabolic preference of fatty acids in the alga.

Multi-Objective Optimization of Microalgae Metabolism: An Evolutive Algorithm Based on FBA

Studies enabled by metabolic models of different species of microalgae have become significant since they allow us to understand changes in their metabolism and physiological stages. The most used method to study cell metabolism is FBA, which commonly focuses on optimizing a single objective function. However, recent studies have brought attention to the exploration of simultaneous optimization of multiple objectives. Such strategies have found application in optimizing biomass and several other bioproducts of interest; they usually use approaches such as multi-level models or enumerations schemes. This work proposes an alternative in silico multiobjective model based on an evolutionary algorithm that offers a broader approximation of the Pareto frontier, allowing a better angle for decision making in metabolic engineering. The proposed strategy is validated on a reduced metabolic network of the microalgae Chlamydomonas reinhardtii while optimizing for the production of protein, carbohydrates, and CO2 uptake. The results from the conducted experimental design show a favorable difference in the number of solutions achieved compared to a classic tool solving FBA.

Biosynthesis and biotechnological interventions for commercial production of microalgal pigments: A review

Microalgae are photosynthetic eukaryotes that serve as microbial cell factories for the production of useful biochemicals, including pigments. These pigments are eco-friendly alternatives to synthetic dyes and reduce environmental and health risks. They also exhibit excellent anti-oxidative properties, making them a useful commodity in the nutrition and pharmaceutical industries. Light-harvesting pigments such as chlorophylls and phycobilins, and photoprotective carotenoids are some of the most common microalgal pigments. The increasing demand for these pigments in industrial applications has prompted a need to improve their metabolic yield in microalgal cells. So far, expensive cultivation methods and sensitivity to microbial contamination remain the main obstacles to the large-scale production of these pigments. This review highlights current issues and future prospects related to the production of microalgal pigments. The review also emphasizes the use of engineering approaches such as genetic engineering, and optimization of media components and physical parameters to increase their commercial-scale production.

Interactions Between Carbon Metabolism and Photosynthetic Electron Transport in a Chlamydomonas reinhardtii Mutant Without CO2 Fixation by RuBisCO

A Chlamydomonas reinhardtii RuBisCO-less mutant, ΔrbcL, was used to study carbohydrate metabolism without fixation of atmospheric carbon. The regulatory mechanism(s) that control linear electron flow, known as "photosynthetic control," are amplified in ΔrbcL at the onset of illumination. With the aim to understand the metabolites that control this regulatory response, we have correlated the kinetics of primary carbon metabolites to chlorophyll fluorescence induction curves. We identify that ΔrbcL in the absence of acetate generates adenosine triphosphate (ATP) via photosynthetic electron transfer reactions. Also, metabolites of the Calvin Benson Bassham (CBB) cycle are responsive to the light. Indeed, ribulose 1,5-bisphosphate (RuBP), the last intermediate before carboxylation by Ribulose-1,5-bisphosphate carboxylase-oxygenase, accumulates significantly with time, and CBB cycle intermediates for RuBP regeneration, dihydroxyacetone phosphate (DHAP), pentose phosphates and ribose-5-phosphate (R5P) are rapidly accumulated in the first seconds of illumination, then consumed, showing that although the CBB is blocked, these enzymes are still transiently active. In opposition, in the presence of acetate, consumption of CBB cycle intermediates is strongly diminished, suggesting that the link between light and primary carbon metabolism is almost lost. Phosphorylated hexoses and starch accumulate significantly. We show that acetate uptake results in heterotrophic metabolism dominating phototrophic metabolism, with glyoxylate and tricarboxylic acid (TCA) cycle intermediates being the most highly represented metabolites, specifically succinate and malate. These findings allow us to hypothesize which metabolites and metabolic pathways are relevant to the upregulation of processes like cyclic electron flow that are implicated in photosynthetic control mechanisms.

Dynamic light- and acetate-dependent regulation of the proteome and lysine acetylome of Chlamydomonas

The green alga Chlamydomonas reinhardtii is one of the most studied microorganisms in photosynthesis research and for biofuel production. A detailed understanding of the dynamic regulation of its carbon metabolism is therefore crucial for metabolic engineering. Post-translational modifications can act as molecular switches for the control of protein function. Acetylation of the ɛ-amino group of lysine residues is a dynamic modification on proteins across organisms from all kingdoms. Here, we performed mass spectrometry-based profiling of proteome and lysine acetylome dynamics in Chlamydomonas under varying growth conditions. Chlamydomonas liquid cultures were transferred from mixotrophic (light and acetate as carbon source) to heterotrophic (dark and acetate) or photoautotrophic (light only) growth conditions for 30 h before harvest. In total, 5863 protein groups and 1376 lysine acetylation sites were identified with a false discovery rate of <1%. As a major result of this study, our data show that dynamic changes in the abundance of lysine acetylation on various enzymes involved in photosynthesis, fatty acid metabolism, and the glyoxylate cycle are dependent on acetate and light. Exemplary determination of acetylation site stoichiometries revealed particularly high occupancy levels on K175 of the large subunit of RuBisCO and K99 and K340 of peroxisomal citrate synthase under heterotrophic conditions. The lysine acetylation stoichiometries correlated with increased activities of cellular citrate synthase and the known inactivation of the Calvin-Benson cycle under heterotrophic conditions. In conclusion, the newly identified dynamic lysine acetylation sites may be of great value for genetic engineering of metabolic pathways in Chlamydomonas.

Contributions of polysaccharides to arsenate resistance in Chlamydomonas reinhardtii

Polysaccharides supply energy for various metabolic processes in cells. However, their roles in the arsenate (As(V)) resistance in microalgae remain largely unknown. Here, we explored the synthesis and transformation of polysaccharides in Chlamydomonas reinhardtii upon various levels of As(V) stress, using a number of physiological indexes along with transmission electron microscopic (TEM) and proteomic analyses. When exposed to low concentration of As(V) (0-20 μg/L), C. reinhardtii accumulated starch and produced more extracellular polysaccharides. At 50 μg/L As(V) treatment, starch accumulation gradually shifted to polysaccharides decomposition in the algal cells. Under higher As(V) concentration (500 μg/L), significantly more proteins in fatty acid metabolic pathway were differentially expressed, indicating that cells redirected carbon flux and transformed lipids into polysaccharides. The findings of this study demonstrate that polysaccharides may be critically involved in the As(V) resistance of C. reinhardtii.

Subcellular Localizations of Catalase and Exogenously Added Fatty Acid in Chlamydomonas reinhardtii

Fatty acids are important biological components, yet the metabolism of fatty acids in microalgae is not clearly understood. Previous studies found that Chlamydomonas reinhardtii, the model microalga, incorporates exogenously added fatty acids but metabolizes them differently from animals and yeast. Furthermore, a recent metabolic flux analysis found that the majority of lipid turnover in C. reinhardtii is the recycling of acyl chains from and to membranes, rather than β -oxidation. This indicates that for the alga, the maintenance of existing acyl chains may be more valuable than their breakdown for energy. To gain cell-biological knowledge of fatty acid metabolism in C. reinhardtii, we conducted microscopy analysis with fluorescent probes. First, we found that CAT1 (catalase isoform 1) is in the peroxisomes while CAT2 (catalase isoform 2) is localized in the endoplasmic reticulum, indicating the alga is capable of detoxifying hydrogen peroxide that would be produced during β-oxidation in the peroxisomes. Second, we compared the localization of exogenously added FL-C16 (fluorescently labelled palmitic acid) with fluorescently marked endosomes, mitochondria, peroxisomes, lysosomes, and lipid droplets. We found that exogenously added FL-C16 are incorporated and compartmentalized via a non-endocytic route within 10 min. However, the fluorescence signals from FL-C16 did not colocalize with any marked organelles, including peroxisomes. During triacylglycerol accumulation, the fluorescence signals from FL-C16 were localized in lipid droplets. These results support the idea that membrane turnover is favored over β-oxidation in C. reinhardtii. The knowledge gained in these analyses would aid further studies of the fatty acid metabolism.

Towards model-driven characterization and manipulation of plant lipid metabolism

Plant lipids have versatile applications and provide essential fatty acids in human diet. Therefore, there has been a growing interest to better characterize the genetic basis, regulatory networks, and metabolic pathways that shape lipid quantity and composition. Addressing these issues is challenging due to context-specificity of lipid metabolism integrating environmental, developmental, and tissue-specific cues. Here we systematically review the known metabolic pathways and regulatory interactions that modulate the levels of storage lipids in oilseeds. We argue that the current understanding of lipid metabolism provides the basis for its study in the context of genome-wide plant metabolic networks with the help of approaches from constraint-based modeling and metabolic flux analysis. The focus is on providing a comprehensive summary of the state-of-the-art of modeling plant lipid metabolic pathways, which we then contrast with the existing modeling efforts in yeast and microalgae. We then point out the gaps in knowledge of lipid metabolism, and enumerate the recent advances of using genome-wide association and quantitative trait loci mapping studies to unravel the genetic regulations of lipid metabolism. Finally, we offer a perspective on how advances in the constraint-based modeling framework can propel further characterization of plant lipid metabolism and its rational manipulation.

Tracing metabolic flux through time and space with isotope labeling experiments

Metabolism is dynamic and must function in context-specific ways to adjust to changes in the surrounding cellular and ecological environment. When isotopic tracers are used, metabolite flow (i.e. metabolic flux) can be quantified through biochemical networks to assess metabolic pathway operation. The cellular activities considered across multiple tissues and organs result in the observed phenotype and can be analyzed to discover emergent, whole-system properties of biology and elucidate misconceptions about network operation. However, temporal and spatial challenges remain significant hurdles and require novel approaches and creative solutions. We survey current investigations in higher plant and animal systems focused on dynamic isotope labeling experiments, spatially resolved measurement strategies, and observations from re-analysis of our own studies that suggest prospects for future work. Related discoveries will be necessary to push the frontier of our understanding of metabolism to suggest novel solutions to cure disease and feed a growing future world population.

13C metabolic flux analysis on roles of malate transporter in lipid accumulation of Mucor circinelloides

Background

Mitochondrial and cytoplasmic malate transporter proteins are responsible for transmembrane transport of malate, thereby linking malate metabolism in various subcellular regions of the cell. These transporters play an important role in fatty acid biosynthesis of oleaginous microorganisms. Our previous studies have found that lipid content of the recombinant Mucor circinelloides (M. circinelloides) strain with mitochondrial malate transporter (mt) gene overexpression was increased by 70%, while that of strain with mt gene knockout was decreased by 27%. However, the mechanism of malate transporter promoting the transport of mitochondrial malate and citrate related to lipid accumulation is not clear. Therefore, ¹³C-labeled glucose metabolic flux analysis was carried out to identify the metabolic network topology and estimate intracellular fluxes of genetically engineered M. circinelloides strains for the purpose of better understanding the roles of malate transporters in citrate transport systems and lipid accumulation.

Results

The metabolic flux distribution analysis suggested that tricarboxylic acid (TCA) cycle flux ratio of mt-overexpression strains was decreased compared to that of the control strain, but in contrast, glyoxylic acid (GOX) cycle flux ratio was increased. Accordingly, the mt-knockout strain showed an opposite phenomenon with a higher TCA cycle flux ratio and a lower GOX cycle flux ratio than the control strain. GOX cycle might be more effective than TCA cycle in producing malate and oxaloacetate replenishment. Moreover, a relatively higher flux ratio of the pentose phosphate (PP) pathway was obtained in mt-overexpression strains, but no significant difference in the malic enzyme flux between recombinant strains and the control strain. Our results confirmed that PP pathway might play an important role for supplying NADPH and malic enzyme is not a limiting factor for fatty acid synthesis in oleaginous fungus M. circinelloides strains.

Conclusion

Intracellular metabolic flux information suggested that mt-overexpression strains had higher flux in PP pathway and GOX cycle, lower flux in TCA cycle, and no difference in malic enzyme cycle. Together, the role of malate transporter was assumed to further participate in transporting cycle of acetyl-CoA and drive PP pathway to supply NADPH required for lipid accumulation in recombinant M. circinelloides strains.

Flux sampling is a powerful tool to study metabolism under changing environmental conditions

The development of high-throughput 'omic techniques has sparked a rising interest in genome-scale metabolic models, with applications ranging from disease diagnostics to crop adaptation. Efficient and accurate methods are required to analyze large metabolic networks. Flux sampling can be used to explore the feasible flux solutions in metabolic networks by generating probability distributions of steady-state reaction fluxes. Unlike other methods, flux sampling can be used without assuming a particular cellular objective. We have undertaken a rigorous comparison of several sampling algorithms and concluded that the coordinate hit-and-run with rounding (CHRR) algorithm is the most efficient based on both run-time and multiple convergence diagnostics. We demonstrate the power of CHRR by using it to study the metabolic changes that underlie photosynthetic acclimation to cold of Arabidopsis thaliana plant leaves. In combination with experimental measurements, we show how the regulated interplay between diurnal starch and organic acid accumulation defines the plant acclimation process. We confirm fumarate accumulation as a requirement for cold acclimation and further predict γ-aminobutyric acid to have a key role in metabolic signaling under cold conditions. These results demonstrate how flux sampling can be used to analyze the feasible flux solutions across changing environmental conditions, whereas eliminating the need to make assumptions which introduce observer bias.

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.

Cyanobacterial carboxysome mutant analysis reveals the influence of enzyme compartmentalization on cellular metabolism and metabolic network rigidity

Cyanobacterial carboxysomes encapsulate carbonic anhydrase and ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO). Genetic deletion of the major structural proteins encoded within the ccm operon in Synechococcus sp. PCC 7002 (ΔccmKLMN) disrupts carboxysome formation and significantly affects cellular physiology. Here we employed both metabolite pool size analysis and isotopically nonstationary metabolic flux analysis (INST-MFA) to examine metabolic regulation in cells lacking carboxysomes. Under high CO₂ environments (1%), the ΔccmKLMN mutant could recover growth and had a similar central flux distribution as the control strain, with the exceptions of moderately decreased photosynthesis and elevated biomass protein content and photorespiration activity. Metabolite analyses indicated that the ΔccmKLMN strain had significantly larger pool sizes of pyruvate (>18 folds), UDPG (uridine diphosphate glucose), and aspartate as well as higher levels of secreted organic acids (e.g., malate and succinate). These results suggest that the ΔccmKLMN mutant is able to largely maintain a fluxome similar to the control strain by changing in intracellular metabolite concentrations and metabolite overflows under optimal growth conditions. When CO₂ was insufficient (0.2%), provision of acetate moderately promoted mutant growth. Interestingly, the removal of microcompartments may loosen the flux network and promote RuBisCO side-reactions, facilitating redirection of central metabolites to competing pathways (i.e., pyruvate to heterologous lactate production). This study provides important insights into metabolic regulation via enzyme compartmentation and cyanobacterial compensatory responses.

Overproduction of recombinant E. coli malate synthase enhances Chlamydomonas reinhardtii biomass by upregulating heterotrophic metabolism

High uptake of malate and efficient distribution of intracellular malate to organelles contributed to biomass increase, reducing maintenance energy. In this study, transgenic Chlamydomonas reinhardtii was developed that stably expresses malate synthase in the chloroplast. The strains under glyoxylate treatment showed 19% more increase in microalgal biomass than wild-type. By RNA analysis, transcript levels of malate dehydrogenase (MDH4) and acetyl-CoA synthetase (ACS3), isocitrate lyase (ICL1) and malate synthase (MAS1), were significantly more expressed (17%, 42%, 24%, and 18% respectively), which was consistent with reported heterotrophic metabolism flux analysis with the objective function maximizing biomass. Photosynthetic F_v/F_m was slightly reduced. A more meticulous analysis is necessary, but, in the transgenic microalgae with malate synthase overexpression, the metabolism is likely to more rely on heterotrophic energy production via TCA cycle and glyoxylate shunt than on photosynthesis, resulting in the increase in microalgal biomass.

The challenge and potential of photosynthesis: unique considerations for metabolic flux measurements in photosynthetic microorganisms

Photosynthetic microorganisms have the potential for sustainable production of chemical feedstocks and products but have had limited success due to a lack of tools and deeper understanding of metabolic pathway regulation. The application of instationary metabolic flux analysis (INST-MFA) to photosynthetic microorganisms has allowed researchers to quantify fluxes and identify bottlenecks and metabolic inefficiencies to improve strain performance or gain insight into cellular physiology. Additionally, flux measurements can also highlight deviations between measured and predicted fluxes, revealing weaknesses in metabolic models and highlighting areas where a lack of understanding still exists. In this review, we outline the experimental steps necessary to successfully perform photosynthetic flux experiments and analysis. We also discuss the challenges unique to photosynthetic microorganisms and how to account for them, including: light supply, quenching, concentration, extraction, analysis, and flux calculation. We hope that this will enable a larger number of researchers to successfully apply isotope assisted metabolic flux analysis (¹³C-MFA) to their favorite photosynthetic organism.

Modeling and Simulating the Aerobic Carbon Metabolism of a Green Microalga Using Petri Nets and New Concepts of VANESA

In this work we present new concepts of VANESA, a tool for modeling and simulation in systems biology. We provide a convenient way to handle mathematical expressions and take physical units into account. Simulation and result management has been improved, and syntax and consistency checks, based on physical units, reduce modeling errors. As a proof of concept, essential components of the aerobic carbon metabolism of the green microalga Chlamydomonas reinhardtii are modeled and simulated. The modeling process is based on xHPN Petri net formalism and simulation is performed with OpenModelica, a powerful environment and compiler for Modelica. VANESA, as well as OpenModelica, is open source, free-of-charge for non-commercial use, and is available at: http://agbi.techfak.uni-bielefeld.de/vanesa.

Advances in metabolic modeling of oleaginous microalgae

Production of biofuels and bioenergy precursors by phototrophic microorganisms, such as microalgae and cyanobacteria, is a promising alternative to conventional fuels obtained from non-renewable resources. Several species of microalgae have been investigated as potential candidates for the production of biofuels, for the most part due to their exceptional metabolic capability to accumulate large quantities of lipids. Constraint-based modeling, a systems biology approach that accurately predicts the metabolic phenotype of phototrophs, has been deployed to identify suitable culture conditions as well as to explore genetic enhancement strategies for bioproduction. Core metabolic models were employed to gain insight into the central carbon metabolism in photosynthetic microorganisms. More recently, comprehensive genome-scale models, including organelle-specific information at high resolution, have been developed to gain new insight into the metabolism of phototrophic cell factories. Here, we review the current state of the art of constraint-based modeling and computational method development and discuss how advanced models led to increased prediction accuracy and thus improved lipid production in microalgae.

Systems protobiology: origin of life in lipid catalytic networks

Life is that which replicates and evolves, but there is no consensus on how life emerged. We advocate a systems protobiology view, whereby the first replicators were assemblies of spontaneously accreting, heterogeneous and mostly non-canonical amphiphiles. This view is substantiated by rigorous chemical kinetics simulations of the graded autocatalysis replication domain (GARD) model, based on the notion that the replication or reproduction of compositional information predated that of sequence information. GARD reveals the emergence of privileged non-equilibrium assemblies (composomes), which portray catalysis-based homeostatic (concentration-preserving) growth. Such a process, along with occasional assembly fission, embodies cell-like reproduction. GARD pre-RNA evolution is evidenced in the selection of different composomes within a sparse fitness landscape, in response to environmental chemical changes. These observations refute claims that GARD assemblies (or other mutually catalytic networks in the metabolism first scenario) cannot evolve. Composomes represent both a genotype and a selectable phenotype, anteceding present-day biology in which the two are mostly separated. Detailed GARD analyses show attractor-like transitions from random assemblies to self-organized composomes, with negative entropy change, thus establishing composomes as dissipative systems-hallmarks of life. We show a preliminary new version of our model, metabolic GARD (M-GARD), in which lipid covalent modifications are orchestrated by non-enzymatic lipid catalysts, themselves compositionally reproduced. M-GARD fills the gap of the lack of true metabolism in basic GARD, and is rewardingly supported by a published experimental instance of a lipid-based mutually catalytic network. Anticipating near-future far-reaching progress of molecular dynamics, M-GARD is slated to quantitatively depict elaborate protocells, with orchestrated reproduction of both lipid bilayer and lumenal content. Finally, a GARD analysis in a whole-planet context offers the potential for estimating the probability of life's emergence. The invigorated GARD scrutiny presented in this review enhances the validity of autocatalytic sets as a bona fide early evolution scenario and provides essential infrastructure for a paradigm shift towards a systems protobiology view of life's origin.

Cell-Type Specific Metabolic Flux Analysis: A Challenge for Metabolic Phenotyping and a Potential Solution in Plants

Stable isotope labelling experiments are used routinely in metabolic flux analysis (MFA) to determine the metabolic phenotype of cells and tissues. A complication arises in multicellular systems because single cell measurements of transcriptomes, proteomes and metabolomes in multicellular organisms suggest that the metabolic phenotype will differ between cell types. In silico analysis of simulated metabolite isotopomer datasets shows that cellular heterogeneity confounds conventional MFA because labelling data averaged over multiple cell types does not necessarily yield averaged flux values. A potential solution to this problem—the use of cell-type specific reporter proteins as a source of cell-type specific labelling data—is proposed and the practicality of implementing this strategy in the roots of Arabidopsis thaliana seedlings is explored. A protocol for the immunopurification of ectopically expressed green fluorescent protein (GFP) from Arabidopsis thaliana seedlings using a GFP-binding nanobody is developed, and through GC-MS analysis of protein hydrolysates it is established that constitutively expressed GFP reports accurately on the labelling of total protein in root tissues. It is also demonstrated that the constitutive expression of GFP does not perturb metabolism. The principal obstacle to the implementation of the method in tissues with cell-type specific GFP expression is the sensitivity of the GC-MS system.