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The metabolic networks of microorganisms are remarkably robust to genetic and environmental perturbations. This robustness stems from redundancies such as gene duplications, isoenzymes, alternative metabolic pathways, and also from non-enzymatic reactions. In the oxidative branch of the pentose phosphate pathway (oxPPP), 6-phosphogluconolactone hydrolysis into 6-phosphogluconate is catalysed by 6-phosphogluconolactonase (Pgl) but in the absence of the latter, the oxPPP flux is thought to be maintained by spontaneous hydrolysis. However, in Δpgl Escherichia coli, an extracellular pathway can also contribute to pentose phosphate synthesis. This raises question as to whether the intracellular non-enzymatic reaction can compensate for the absence of 6-phosphogluconolactonase and, ultimately, on the role of 6-phosphogluconolactonase in central metabolism. Our results validate that the bypass pathway is active in the absence of Pgl, specifically involving the extracellular spontaneous hydrolysis of gluconolactones to gluconate. Under these conditions, metabolic flux analysis reveals that this bypass pathway accounts for the entire flux into the oxPPP. This alternative metabolic route-partially extracellular-sustains the flux through the oxPPP necessary for cell growth, albeit at a reduced rate in the absence of Pgl. Importantly, these findings imply that intracellular non-enzymatic hydrolysis of 6-phosphogluconolactone does not compensate for the absence of Pgl. This underscores the crucial role of Pgl in ensuring the efficient functioning of the oxPPP.

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Even though they share many thematical overlaps, plant metabolomics and stable isotope ecology have been rather separate fields mainly due to different mass spectrometry demands. New high-resolution bioanalytical mass spectrometers are now not only offering high-throughput metabolite identification but are also suitable for compound- and intramolecular position-specific isotope analysis in the natural isotope abundance range. In plant metabolomics, label-free metabolic pathway and metabolic flux analysis might become possible when applying this new technology. This is because changes in the commitment of substrates to particular metabolic pathways and the activation or deactivation of others alter enzyme-specific isotope effects. This leads to differences in intramolecular and compound-specific isotope compositions. In plant isotope ecology, position-specific isotope analysis in plant archives informed by metabolic pathway analysis could be used to reconstruct and separate environmental impacts on complex metabolic processes. A technology-driven linkage between the two disciplines could allow us to extract information on environment-metabolism interaction from plant archives such as tree rings but also within ecosystems. This would contribute to a holistic understanding of how plants react to environmental drivers, thus also providing helpful information on the trajectories of the vegetation under the conditions to come.

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Among plant pathogens, the necrotrophic fungus Botrytis cinerea is one of the most prevalent, leading to severe crop damage. Studies related to its colonization of different plant species have reported variable host metabolic responses to infection. In tomato, high N availability leads to decreased susceptibility. Metabolic flux analysis can be used as an integrated method to better understand which metabolic adaptations lead to effective host defence and resistance. Here, we investigated the metabolic response of tomato infected by B. cinerea in symptomless stem tissues proximal to the lesions for 7 d post-inoculation, using a reconstructed metabolic model constrained by a large and consistent metabolic dataset acquired under four different N supplies. An overall comparison of 48 flux solution vectors of Botrytis- and mock-inoculated plants showed that fluxes were higher in Botrytis-inoculated plants, and the difference increased with a reduction in available N, accompanying an unexpected increase in radial growth. Despite higher fluxes, such as those involved in cell wall synthesis and other pathways, fluxes related to glycolysis, the tricarboxylic acid cycle, and amino acid and protein synthesis were limited under very low N, which might explain the enhanced susceptibility. Limiting starch synthesis and enhancing fluxes towards redox and specialized metabolism also contributed to defence independent of N supply.

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Day respiration (Rd) is the metabolic, nonphotorespiratory process by which illuminated leaves liberate CO2 during photosynthesis. Rd is used routinely in photosynthetic models and is thus critical for calculations. However, metabolic details associated with Rd are poorly known, and this can be problematic to predict how Rd changes with environmental conditions and relates to night respiration. It is often assumed that day respiratory CO2 release just reflects 'ordinary' catabolism (glycolysis and Krebs 'cycle'). Here, we carried out a pulse-chase experiment, whereby a 13CO2 pulse in the light was followed by a chase period in darkness and then in the light. We took advantage of nontargeted, isotope-assisted metabolomics to determine non-'ordinary' metabolism, detect carbon remobilisation and compare light and dark 13C utilisation. We found that several concurrent metabolic pathways ('ordinary' catabolism, oxidative pentose phosphates pathway, amino acid production, nucleotide biosynthesis and secondary metabolism) took place in the light and participated in net CO2 efflux associated with day respiration. Flux reconstruction from metabolomics leads to an underestimation of Rd, further suggesting the contribution of a variety of CO2-evolving processes. Also, the cornerstone of the Krebs 'cycle', citrate, is synthetised de novo from photosynthates mostly in darkness, and remobilised or synthesised from stored material in the light. Collectively, our data provides direct evidence that leaf day respiration (i) involves several CO2-producing reactions and (ii) is fed by different carbon sources, including stored carbon disconnected from current photosynthates.

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The accurate prediction of phenotypes in microorganisms is a main challenge for systems biology. Genome-scale models (GEMs) are a widely used mathematical formalism for predicting metabolic fluxes using constraint-based modeling methods such as flux balance analysis (FBA). However, they require prior knowledge of the metabolic network of an organism and appropriate objective functions, often hampering the prediction of metabolic fluxes under different conditions. Moreover, the integration of omics data to improve the accuracy of phenotype predictions in different physiological states is still in its infancy. Here, we present a novel approach for predicting fluxes under various conditions. We explore the use of supervised machine learning (ML) models using transcriptomics and/or proteomics data and compare their performance against the standard parsimonious FBA (pFBA) approach using case studies of Escherichia coli organism as an example. Our results show that the proposed omics-based ML approach is promising to predict both internal and external metabolic fluxes with smaller prediction errors in comparison to the pFBA approach. The code, data, and detailed results are available at the project's repository[1].

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Catabolite control protein A (CcpA) is a critical regulator in Gram-positive bacteria that orchestrates carbon metabolism by coordinating the utilization of different carbon sources. Although it has been widely proved that CcpA helps prioritize the utilization of glucose over other carbon sources, this global regulator's precise mechanism of action remains unclear. In this study, a mutant Bacillus licheniformis deleted for CcpA was constructed. Cell growth, carbon utilization, metabolites and the transcription of key enzymes of the mutant strain were compared with that of the wild-type one. It was found that CcpA is involved in the regulation of glucose concentration metabolism in Bacillus. At the same time, CcpA regulates glucose metabolism by inhibiting acetic acid synthesis and pentose phosphate pathway key gene zwF. The conversion rate of acetic acid is increased by about 3.5 times after ccpA is deleted. The present study provides a new mechanism of carbon metabolism and acetic acid balance regulated by CcpA. On the one hand, this work deepens the understanding of the regulatory function of CcpA and provides a new view on the regulation of glucose metabolism. On the other hand, it is helpful to the transformation of B. licheniformis chassis microorganisms.

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Although primary metabolism is well conserved across species, it is useful to explore the specificity of its network to assess the extent to which some pathways may contribute to particular outcomes. Constraint-based metabolic modelling is an established framework for predicting metabolic fluxes and phenotypes and helps to explore how the plant metabolic network delivers specific outcomes from temporal series. After describing the main physiological traits during fruit development, we confirmed the correlations between fruit relative growth rate (RGR), protein content and time to maturity. Then a constraint-based method is applied to a panel of eight fruit species with a knowledge-based metabolic model of heterotrophic cells describing a generic metabolic network of primary metabolism. The metabolic fluxes are estimated by constraining the model using a large set of metabolites and compounds quantified throughout fruit development. Multivariate analyses showed a clear common pattern of flux distribution during fruit development with differences between fast- and slow-growing fruits. Only the latter fruits mobilise the tricarboxylic acid cycle in addition to glycolysis, leading to a higher rate of respiration. More surprisingly, to balance nitrogen, the model suggests, on the one hand, nitrogen uptake by nitrate reductase to support a high RGR at early stages of cucumber and, on the other hand, the accumulation of alkaloids during ripening of pepper and eggplant. Finally, building virtual fruits by combining 12 biomass compounds shows that the growth-defence trade-off is supported mainly by cell wall synthesis for fast-growing fruits and by total polyphenols accumulation for slow-growing fruits.

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Deuterium metabolic imaging (DMI) is a promising molecular MRI approach, which follows the administration of deuterated substrates and their metabolization. [6,6'-2 H2 ]-glucose for instance is preferentially converted in tumors to [3,3'-2 H2 ]-lactate as a result of the Warburg effect, providing a distinct resonance whose mapping using time-resolved spectroscopic imaging can diagnose cancer. The MR detection of low-concentration metabolites such as lactate, however, is challenging. It has been recently shown that multi-echo balanced steady-state free precession (ME-bSSFP) increases the signal-to-noise ratio (SNR) of these experiments approximately threefold over regular chemical shift imaging; the present study examines how DMI's sensitivity can be increased further by advanced processing methods. Some of these, such as compressed sensing multiplicative denoising and block-matching/3D filtering, can be applied to any spectroscopic/imaging methods. Sensitivity-enhancing approaches were also specifically tailored to ME-bSSFP DMI, by relying on priors related to the resonances' positions and to features of the metabolic kinetics. Two new methods are thus proposed that use these constraints for enhancing the sensitivity of both the spectral images and the metabolic kinetics. The ability of these methods to improve DMI is evidenced in pancreatic cancer studies carried at 15.2 T, where suitable implementations of the proposals imparted eightfold or more SNR improvement over the original ME-bSSFP data, at no informational cost. Comparisons with other propositions in the literature are briefly discussed.

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Recent studies have demonstrated that plankton can be a key pathway for the uptake and transfer of contaminants entering the marine environment up to top predators. The plankton-contaminant MERITE-HIPPOCAMPE cruise was devoted to quantifying contaminants in water and the whole plankton size range (10 size fractions) at 10 stations along a north-south transect in the western Mediterranean Sea from the French to the Tunisian coasts through the Provençal and Algerian basins. Pumping and filtering devices and net sampling have been used for collecting very high amounts of small particles and planktonic organisms in the chlorophyll maximum layer (CML). The present paper characterizes the zooplankton components for which the contaminant measurements were carried out. At each station, a horizontal towed Hydro-Bios net with a 60 µm mesh-size net was used to discriminate 5 size-fractions from 60 µm to a few mm. For each size-fraction, one part of the sample was used for dry weight measurements and the other one for estimating the contribution to biomass of detritus, phytoplankton, and among zooplankton of the major taxonomic groups based on the imagery tools ZOOSCAN and FLOWCAM. In each zooplankton size fraction, metabolic rates were calculated from the size spectrum to estimate trophic and excretion fluxes flowing through this fraction. These observations were compared to a similar analysis of tows in the upper layer (vertical) and the surface layer (horizontal). The total sampled biomass concentration at the CML was higher than in the water column (COL) and much higher than at the surface (SURF) in most of the stations, but in the CML and COL a substantial contribution was due to detritus mostly concentrated in the smallest size-fractions (60-200 µm and 200-500 µm). Absolute values of zooplankton biomass show neither a clear spatial pattern nor a significant difference between strata. The CML layer was dominated by copepods similarly to COL and SURF, but presented a higher contribution of nauplii and a near absence of appendicularians. At some stations, crustaceans and gelatinous plankton could be important contributors to CML. The zooplankton biomass composition of the two smallest fractions (<500 µm) was dominated by nauplii, small copepods and, occasionally, by small miscellaneous organisms (mostly pteropodes). In contrast, clear differences between stations appeared for the largest fractions (>500 µm) due to large crustaceans, gelatinous organisms, and chaetognaths. These changes in biomass composition according to size fractions suggest a progressive trophic shift from dominant herbivory in the smallest fractions to more contrasted trophic structure (including carnivory) in the largest fractions. The daily carbon demand and the N and P excretion of zooplankton were on average higher at the CML but with no significant difference with COL. The zooplankton grazing represented 2.7 to 22.7 % of the phytoplankton stock per day, whereas its excretion represented a daily N and P recycling compared to dissolved inorganic nitrogen and phosphorus stocks ranging respectively from 0.2 to 19 % and from 0 to 21 %. This information should help in the interpretation of the content of various contaminants in zooplankton fractions.

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Genome-scale metabolic models (GEMs) have found numerous applications in different domains, ranging from biotechnology to systems medicine. Herein, we overview the most popular algorithms for the automated reconstruction of context-specific GEMs using high-throughput experimental data. Moreover, we describe different datasets applied in the process, and protocols that can be used to further automate the model reconstruction and validation. Finally, we describe recent COVID-19 applications of context-specific GEMs, focusing on the analysis of metabolic implications, identification of biomarkers and potential drug targets.

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The metabolic fluxes throughout the tricarboxylic acid cycle (TCAC) are inhibited in the light by the mitochondrial thioredoxin (TRX) system. However, it is unclear how this system orchestrates the fluxes throughout the TCAC and associated pathways in the dark. Here we carried out a13C-HCO3 labelling experiment in Arabidopsis leaves from wild type (WT) and mutants lacking TRX o1 (trxo1), TRX h2 (trxh2), or both NADPH-dependent TRX reductase A and B (ntra ntrb) exposed to 0, 30 and 60 min of dark or light conditions. No 13C-enrichment in TCAC metabolites in illuminated WT leaves was observed. However, increased succinate content was found in parallel to reductions in Ala in the light, suggesting the latter operates as an alternative carbon source for succinate synthesis. By contrast to WT, all mutants showed substantial changes in the content and 13C-enrichment in TCAC metabolites under both dark and light conditions. Increased 13C-enrichment in glutamine in illuminated trxo1 leaves was also observed, strengthening the idea that TRX o1 restricts in vivo carbon fluxes from glycolysis and the TCAC to glutamine. We further demonstrated that both photosynthetic and gluconeogenic fluxes toward glucose are increased in trxo1 and that the phosphoenolpyruvate carboxylase (PEPc)-mediated 13C-incorporation into malate is higher in trxh2 mutants, as compared to WT. Our results collectively provide evidence that TRX h2 and the mitochondrial NTR/TRX system regulate the metabolic fluxes throughout the TCAC and associated pathways, including glycolysis, gluconeogenesis and the synthesis of glutamine in a light-independent manner.

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Cancer represents a global health concern, imposing a severe burden both from a societal and clinical perspective. Despite the latest advancements and achievements in the treatment and management of malignancy, cancer still imposes a dramatically high burden worldwide. Different theories (biophysical or biochemical, genetic or epigenetic) related to the origin of tumor cells have been put forth. These theories can also be subdivided into reductionist and emergentist/holistic theories. In the current overview, we will focus only on the cancer metabolic theory, one of the emergentist/holistic theories: it is holistic in that maintains that pathways, cascades and networks controlling energy metabolism, as well as those devoted to cell growth, cell cycle, replication, division and other cellular processes are highly interwoven and interconnected, and cannot be understood if not assuming a systems biology perspective. Cells should be seen as metabolic factories, in which metabolic fluxes and circuits (anabolic and catabolic) are plastically re-wired on the basis of the internal/external stimuli (cell make-up and genetic determinants, micro-environment, etc.). Complex regulatory and meta-regulatory systems exist that finely tune the functioning of cell, cell-cell communication and its interaction with the surrounding environment. At the tissue level, not all tissues share the same degree of metabolic plasticity (metabolic rigidity vs. metabolic flexibility), even though some metabolic coupling systems exist in order to guarantee an overall minimum extent of metabolic plasticity. The same broad picture of molecular events is necessary when describing the impairment and dysregulation of these processes, leading to multi-stage phenomena, including carcinogenesis.

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Metabolic engineering (ME) aims to develop efficient microbial cell factories that can produce a wide variety of valuable compounds, ideally at the highest yield and from various feedstocks. We summarize recent developments in ME methods for tailoring different yeast cell factories (YCFs). In particular, we highlight the most timely and cutting-edge molecular tools and strategies for biosynthetic pathway optimization (including genome-editing tools), combinatorial transcriptional and post-transcriptional engineering (cis/trans regulators), dynamic control of metabolic fluxes (e.g., rewiring of primary metabolism), and spatial reconfiguration of metabolic pathways. Finally, we discuss challenges and perspectives for adaptive laboratory evolution (ALE) of yeast to advance ME of microbial cell factories.

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Plants, as biological systems, are organized and regulated by a complex network of interactions from the genetic to the morphological level and suffer substantial influence from the environment. Reductionist approaches have been widely used in plant biology but have failed to reveal the mechanisms by which plants can growth under adverse conditions. It seems likely, therefore, that to understand the complexity of plant metabolic responses it is necessary to adopt non-reductionist approaches such as those from systems biology. Although such approaches seem methodologically complex to perform and difficult to interpret, they have been successfully applied in both metabolic and gene expression networks in a wide range of microorganisms and more recently in plants. Given the advance of techniques that allow complex analysis of plant cells, high quantities of data are currently generated and are available for in silico analysis and mathematical modeling. It is increasingly recognized, therefore, that the use of different methods such as graph analysis and dynamic network modeling are needed to better understand this abundance of information. However, before these practical advances, one of the main challenges currently in plant biology is to change the paradigm from the classical reductionism to the systemic level, which requires not only scientific but also educational changes.

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Anthocyanins and PAs are the two most common flavonoids, which are widely present among diverse species. Great progress has been made in their synthesis and regulation. In this study, we analyzed the metabolic fluxes from their synthetic precursor leucoanthocyanins, which were obtained by overexpression of dihydroflavonol 4-reductase (DFR) in vitro and in vivo. The unstable product leucocyanidin generated in the CsDFRa enzymatic reaction was easily converted into C-type carbocations under weak acidic conditions, which could be further involved in the synthesis of C-type PAs in vitro. Additionally, the metabolites in tobacco overexpressing CsDFRa and Arabidopsis thaliana DFR and anthocyanidin synthase (ANS) mutants were investigated. In CsDFRa transgenic tobacco, the content of anthocyanins in the petals was greatly increased, but no catechin or PA was detected. In A. thaliana, EC-type carbocation was mainly accumulated in the wild type (WT), and the C-type carbocation was only detected in the ans mutant. In tea plant, the accumulation of C-type PAs is strong positively correlated with the expression of CsDFRa. In summary, leucocyanidin is not only involved in the synthesis of downstream anthocyanin and epicatechin but also can be converted into C-type carbocation to participate in the synthesis of C-type PAs. Hence, from leucocyanidin, three metabolic fluxes were formed toward catechin, cyanidin, and C-type carbocation. These results enriched the metabolic fluxes of leucoanthocyanins and further elaborated the roles of DFR in the process of C-type PA formation.

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Biosynthesis of poly-3-hydroxybutyrate (PHB) as a fermentation product enables the coupling of growth and product generation. Moreover, the reduction of oxygen supply should reduce operative cost and increase product yield. Generation of PHB as a fermentation product depends on the in vivo activity of an NADH-preferring acetoacetyl-CoA reductase. Proof of this concept requires (i) quantification of the cofactor preference, in physiologically relevant conditions, of a putative NADH-preferring acetoacetyl-CoA reductase and (ii) verification of PHB accumulation using an NADH-preferring acetoacetyl-CoA reductase in a species naturally incapable of doing so, for example, Escherichia coli. This dataset contains kinetic data obtained by spectrophotometry and data from a continuous culture of an engineered E. coli strain accumulating PHB under oxygen-limiting conditions. In this dataset it is possible to find (1) enzyme stability assays; (2) initial rates and progress curves from reactions catalyzed by two acetoacetyl-CoA reductases; (3) estimations of the relative use of NADH and NADPH by two acetoacetyl-CoA reductases; (4) estimations of the flux capacity of the reaction catalyzed by an acetoacetyl-CoA reductase; (5) biomass composition of an engineered E. coli strain transformed with a plasmid; (6) calculation of reconciled specific rates of this engineered strain growing on sucrose as the sole carbon source under oxygen limitation and (7) metabolic fluxes distributions during the continuous growth of this engineered strain. Because a relatively small number of acetoacetyl-CoA reductases have been kinetically characterized, data and scripts here provided could be useful for further kinetic characterizations. Moreover, the procedure described to estimate biomass composition could be interesting to estimate plasmid and protein burden in other strains. Application of data reconciliation to fermentations should help to obtain specific rates consistent with the principle of mass and electron conservation. All the required data and scripts to perform these analyses are deposited in a Mendeley Data repository. This article was co-submitted with the manuscript entitled "An NADH preferring acetoacetyl-CoA reductase is engaged in poly-3-hydroxybutyrate accumulation in Escherichiasia. coli".

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Stable isotope-resolved metabolomics (SIRM), based on the analysis of biological samples from living cells incubated with artificial isotope enriched substrates, enables mapping the rates of biochemical reactions (metabolic fluxes). We developed software supporting a workflow of analysis of SIRM data obtained with mass spectrometry (MS). The evaluation of fluxes starting from raw MS recordings requires at least three steps of computer support: first, extraction of mass spectra of metabolites of interest, then correction of the spectra for natural isotope abundance, and finally, evaluation of fluxes by simulation of the corrected spectra using a corresponding mathematical model. A kinetic model based on ordinary differential equations (ODEs) for isotopomers of metabolites of the corresponding biochemical network supports the final part of the analysis, which provides a dynamic flux map.

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A comprehensive description of the phenotypic changes during cellular aging is key towards unraveling its causal forces. Previously, we mapped age-related changes in the proteome and transcriptome (Janssens et al., 2015). Here, employing the same experimental procedure and model-based inference, we generate a comprehensive account of metabolic changes during the replicative life of Saccharomyces cerevisiae. With age, we found decreasing metabolite levels, decreasing growth and substrate uptake rates accompanied by a switch from aerobic fermentation to respiration, with glycerol and acetate production. The identified metabolic fluxes revealed an increase in redox cofactor turnover, likely to combat increased production of reactive oxygen species. The metabolic changes are possibly a result of the age-associated decrease in surface area per cell volume. With metabolism being an important factor of the cellular phenotype, this work complements our recent mapping of the transcriptomic and proteomic changes towards a holistic description of the cellular phenotype during aging.

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Carbon isotope (13C) fractionations occurring during and after photosynthetic CO2 fixation shape the carbon isotope composition (δ13C) of plant material and respired CO2. However, responses of 13C fractionations to diel variation in starch metabolism in the leaf are not fully understood. Here we measured δ13C of organic matter (δ13COM), concentrations and δ13C of potential respiratory substrates, δ13C of dark-respired CO2 (δ13CR), and gas exchange in leaves of starch-deficient plastidial phosphoglucomutase (pgm) mutants and wild-type plants of four species (Arabidopsis thaliana, Mesembryanthemum crystallinum, Nicotiana sylvestris, and Pisum sativum). The strongest δ13C response to the pgm-induced starch deficiency was observed in N. sylvestris, with more negative δ13COM, δ13CR, and δ13C values for assimilates (i.e. sugars and starch) and organic acids (i.e. malate and citrate) in pgm mutants than in wild-type plants during a diel cycle. The genotype differences in δ13C values could be largely explained by differences in leaf gas exchange. In contrast, the PGM-knockout effect on post-photosynthetic 13C fractionations via the plastidic fructose-1,6-bisphosphate aldolase reaction or during respiration was small. Taken together, our results show that the δ13C variations in starch-deficient mutants are primarily explained by photosynthetic 13C fractionations and that the combination of knockout mutants and isotope analyses allows additional insights into plant metabolism.

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Cyclin-dependent kinases (CDKs) are the central regulators of the eukaryotic cell cycle, and are conserved across eukaryotes. Their main and well-studied function lies in the regulation and the time-keeping of cell cycle entry and progression. Additionally, more and more non canonical functions of CDKs are being uncovered. One fairly recently discovered role of CDKs is the coordination of carbon and energy metabolism with proliferation. Evidence from different model organisms is accumulating that CDKs can directly and indirectly control fluxes through metabolism, for example by phosphorylating metabolic enzymes. In this mini-review, we summarize the emerging role of CDKs in regulating carbon and energy metabolism and discuss examples in different models from yeast to cancer cells.