Tracing metabolic flux through time and space with isotope labeling experiments

Exploring formation of turanose in honey via stable isotope labelling and high-resolution mass spectrometry analysis

Turanose, an isomer of sucrose, naturally exists in honey. Previous study indicated that turanose content increased gradually in acacia honey as honeybees brewed honey in the hive. However, it is unclear how turanose is generated in honey. We hypothesised that turanose was produced by enzymes from honeybees and performed a series of simulation experiments to prove this hypothesis. We found turanose in honey was produced by honeybees processing sucrose. Furthermore, we determined that sugar composition of simulated nectar influenced the turanose concentration in honey: when sucrose concentration was below 5%, turanose was difficult to form, whereas high concentration of fructose and limited glucose were beneficial in producing turanose. Using 13C-labelled sucrose tests combined with proteomics analysis, we identified that α-glucosidase converted sucrose to turanose through an intermolecular isomerisation process. This study reveals the formation mechanism of turanose in honey and assists in the scientific control and improvement of honey quality.

Advances in mass spectrometry imaging for plant metabolomics-Expanding the analytical toolbox

Mass spectrometry imaging (MSI) has become increasingly popular in plant science due to its ability to characterize complex chemical, spatial, and temporal aspects of plant metabolism. Over the past decade, as the emerging and unique features of various MSI techniques have continued to support new discoveries in studies of plant metabolism closely associated with various aspects of plant function and physiology, spatial metabolomics based on MSI techniques has positioned it at the forefront of plant metabolic studies, providing the opportunity for far higher resolution than was previously available. Despite these efforts, profound challenges at the levels of spatial resolution, sensitivity, quantitative ability, chemical confidence, isomer discrimination, and spatial multi-omics integration, undoubtedly remain. In this Perspective, we provide a contemporary overview of the emergent MSI techniques widely used in the plant sciences, with particular emphasis on recent advances in methodological breakthroughs. Having established the detailed context of MSI, we outline both the golden opportunities and key challenges currently facing plant metabolomics, presenting our vision as to how the enormous potential of MSI technologies will contribute to progress in plant science in the coming years.

Sucrose-Phosphate Synthase and Sucrose Synthase contribute to refoliation in ryegrass, a grassland fructan-accumulating species

The perennity of grassland species such as Lolium perenne greatly depends on their ability to regrow after cutting or grazing. Refoliation largely relies on the mobilization of fructans in the remaining tissues and on the associated sucrose synthesis and transport towards the basal leaf meristems. However, nothing is known yet about the sucrose synthesis pathway. Sucrose Phosphate Synthase (SPS) and Sucrose Synthase (SuS) activities, together with their transcripts, were monitored during the first hours after defoliation along the leaf axis of mature leaf sheaths and elongating leaf bases (ELB) where the leaf meristems are located. In leaf sheaths, which undergo a sink-source transition, fructan and sucrose contents declined while SPS and SuS activities increased, along with the expression of LpSPSA, LpSPSD.2, LpSuS1, LpSuS2, and LpSuS4. In ELB, which continue to act as a strong carbon sink, SPS and SuS activities increased to varying degrees while the expression of all the LpSPS and LpSuS genes decreased after defoliation. SPS and SuS both contribute to refoliation but are regulated differently depending on the source or sink status of the tissues. Together with fructan metabolism, they represent key determinants of ryegrass perennity and, more generally, of grassland sustainability.

Modeling lignin biosynthesis: a pathway to renewable chemicals

Plant biomass contains lignin that can be converted into high-value-added chemicals, fuels, and materials. The precise genetic manipulation of lignin content and composition in plant cells offers substantial environmental and economic benefits. However, the intricate regulatory mechanisms governing lignin formation challenge the development of crops with specific lignin profiles. Mathematical models and computational simulations have recently been employed to gain fundamental understanding of the metabolism of lignin and related phenolic compounds. This review article discusses the strategies used for modeling plant metabolic networks, focusing on the application of mathematical modeling for flux network analysis in monolignol biosynthesis. Furthermore, we highlight how current challenges might be overcome to optimize the use of metabolic modeling approaches for developing lignin-engineered plants.

The role of metabolomics in informing strategies for improving photosynthesis

Photosynthesis plays a vital role in acclimating to and mitigating climate change, providing food and energy security for a population that is constantly growing, and achieving an economy with zero carbon emissions. A thorough comprehension of the dynamics of photosynthesis, including its molecular regulatory network and limitations, is essential for utilizing it as a tool to boost plant growth, enhance crop yields, and support the production of plant biomass for carbon storage. Photorespiration constrains photosynthetic efficiency and contributes significantly to carbon loss. Therefore, modulating or circumventing photorespiration presents opportunities to enhance photosynthetic efficiency. Over the past eight decades, substantial progress has been made in elucidating the molecular basis of photosynthesis, photorespiration, and the key regulatory mechanisms involved, beginning with the discovery of the canonical Calvin-Benson-Bassham cycle. Advanced chromatographic and mass spectrometric technologies have allowed a comprehensive analysis of the metabolite patterns associated with photosynthesis, contributing to a deeper understanding of its regulation. In this review, we summarize the results of metabolomics studies that shed light on the molecular intricacies of photosynthetic metabolism. We also discuss the methodological requirements essential for effective analysis of photosynthetic metabolism, highlighting the value of this technology in supporting strategies aimed at enhancing photosynthesis.

Imaging plant metabolism in situ

Mass spectrometry imaging (MSI) has emerged as an invaluable analytical technique for investigating the spatial distribution of molecules within biological systems. In the realm of plant science, MSI is increasingly employed to explore metabolic processes across a wide array of plant tissues, including those in leaves, fruits, stems, roots, and seeds, spanning various plant systems such as model species, staple and energy crops, and medicinal plants. By generating spatial maps of metabolites, MSI has elucidated the distribution patterns of diverse metabolites and phytochemicals, encompassing lipids, carbohydrates, amino acids, organic acids, phenolics, terpenes, alkaloids, vitamins, pigments, and others, thereby providing insights into their metabolic pathways and functional roles. In this review, we present recent MSI studies that demonstrate the advances made in visualizing the plant spatial metabolome. Moreover, we emphasize the technical progress that enhances the identification and interpretation of spatial metabolite maps. Within a mere decade since the inception of plant MSI studies, this robust technology is poised to continue as a vital tool for tackling complex challenges in plant metabolism.

SIMPEL: using stable isotopes to elucidate dynamics of context specific metabolism

The capacity to leverage high resolution mass spectrometry (HRMS) with transient isotope labeling experiments is an untapped opportunity to derive insights on context-specific metabolism, that is difficult to assess quantitatively. Tools are needed to comprehensively mine isotopologue information in an automated, high-throughput way without errors. We describe a tool, Stable Isotope-assisted Metabolomics for Pathway Elucidation (SIMPEL), to simplify analysis and interpretation of isotope-enriched HRMS datasets. The efficacy of SIMPEL is demonstrated through examples of central carbon and lipid metabolism. In the first description, a dual-isotope labeling experiment is paired with SIMPEL and isotopically nonstationary metabolic flux analysis (INST-MFA) to resolve fluxes in central metabolism that would be otherwise challenging to quantify. In the second example, SIMPEL was paired with HRMS-based lipidomics data to describe lipid metabolism based on a single labeling experiment. Available as an R package, SIMPEL extends metabolomics analyses to include isotopologue signatures necessary to quantify metabolic flux.

Diversity and function of viral AMGs associated with DNA biosynthesis in the Napahai plateau wetland

Viruses play an important role in microbial community structure and biodiversity by lysing host cells, and can also affect host metabolic pathways by expressing auxiliary metabolic genes (AMGs). As a unique low-latitude, high-altitude seasonal plateau wetland in China, Napahai has high research value. However, studies on the genetic diversity of AMGs and viruses associated with DNA biosynthesis have not been reported. Based on metagenomics, with the phylogenetic tree, PCoA, and α diversity analysis, we found that three DNA biosynthesis-related viral AMGs (cobS, mazG, and purM) in the Napahai plateau wetland were rich in genetic diversity, uniqueness, and differences compared with other habitats and host sources. Through the KEGG metabolic pathway and metabolic flow analysis of Pseudomonas mandelii (SW-3) and phage (VSW-3), the AMGs (cobS, mazG, and purM) genes of the three related viruses involved in DNA biosynthesis were upregulated and their expression increased significantly. In general, we systematically described the genetic diversity of AMGs associated with DNA biosynthesis in plateau wetland ecosystems and clarified the contribution of viral AMGs in the Napahai plateau wetland to DNA biosynthesis, as well as the changes of metabolites and genes. It further expands the understanding of phage-host interactions, which is of great significance for further revealing the role of viral AMGs in the biological evolution and biogeochemical cycle of wetland ecosystems.

Quantitative Dynamic Analysis of de novo Sphingolipid Biosynthesis in Arabidopsis thaliana

Sphingolipids are pivotal for plant development and stress responses. Growing interest has been directed towards fully comprehending the regulatory mechanisms of the sphingolipid pathway. We explore its de novo biosynthesis and homeostasis in Arabidopsis thaliana cell cultures, shedding light on fundamental metabolic mechanisms. Employing 15N isotope labeling and quantitative dynamic modeling approach, we developed a regularized and constraint-based Dynamic Metabolic Flux Analysis (r-DMFA) framework to predict metabolic shifts due to enzymatic changes. Our analysis revealed key enzymes such as sphingoid-base hydroxylase (SBH) and long-chain-base kinase (LCBK) to be critical for maintaining sphingolipid homeostasis. Disruptions in these enzymes were found to affect cellular viability and increase the potential for programmed cell death (PCD). Thus, this work enhances our understanding of sphingolipid metabolism and demonstrates the utility of dynamic modeling in analyzing complex metabolic pathways.

A role for fermentation in aerobic conditions as revealed by computational analysis of maize root metabolism during growth by cell elongation

The root is a well-studied example of cell specialisation, yet little is known about the metabolism that supports the transport functions and growth of different root cell types. To address this, we used computational modelling to study metabolism in the elongation zone of a maize lateral root. A functional-structural model captured the cell-anatomical features of the root and modelled how they changed as the root elongated. From these data, we derived constraints for a flux balance analysis model that predicted metabolic fluxes of the 11 concentric rings of cells in the root. We discovered a distinct metabolic flux pattern in the cortical cell rings, endodermis and pericycle (but absent in the epidermis) that involved a high rate of glycolysis and production of the fermentation end-products lactate and ethanol. This aerobic fermentation was confirmed experimentally by metabolite analysis. The use of fermentation in the model was not obligatory but was the most efficient way to meet the specific demands for energy, reducing power and carbon skeletons of expanding cells. Cytosolic acidification was avoided in the fermentative mode due to the substantial consumption of protons by lipid synthesis. These results expand our understanding of fermentative metabolism beyond that of hypoxic niches and suggest that fermentation could play an important role in the metabolism of aerobic tissues.

Oilomics: An important branch of foodomics dealing with oil science and technology

Oil is one of three nutritious elements. The application of omics techniques in the field of oil science and technology is attracted increasing attention. Oilomics, which emerged as an important branch of foodomics, has been widely used in various aspects of oil science and technology. However, there are currently no articles systematically reviewing the application of oilomics. This paper aims to provide a critical overview of the advantages and value of oilomics technology compared to traditional techniques in various aspects of oil science and technology, including oil nutrition, oil processing, oil quality, safety, and traceability. Moreover, this article intends to review major issues in oilomics and give a comprehensive, critical overview of the current state of the art, future challenges and trends in oilomics, with a view to promoting the optimal application and development of oilomics technology in oil science and technology.

13CO2-labelling and Sampling in Algae for Flux Analysis of Photosynthetic and Central Carbon Metabolism

The flux in photosynthesis can be studied by performing 13CO2 pulse labelling and analysing the temporal labelling kinetics of metabolic intermediates using gas or liquid chromatography linked to mass spectrometry. Metabolic flux analysis (MFA) is the primary approach for analysing metabolic network function and quantifying intracellular metabolic fluxes. Different MFA approaches differ based on the metabolic state (steady vs. non-steady state) and the use of stable isotope tracers. The main methodology used to investigate metabolic systems is metabolite steady state associated with stable isotope labelling experiments. Specifically, in biological systems like photoautotrophic organisms, isotopic non-stationary 113C metabolic flux analysis at metabolic steady state with transient isotopic labelling (13C-INST-MFA) is required. The common requirement for metabolic steady state, alongside its very short half-timed reactions, complicates robust MFA of photosynthetic metabolism. While custom gas chambers design has addressed these challenges in various model plants, no similar tools were developed for liquid photosynthetic cultures (e.g., algae, cyanobacteria), where diffusion and equilibration of inorganic carbon species in the medium entails a new dimension of complexity. Recently, a novel tailor-made microfluidics labelling system has been introduced, supplying short 13CO2 pulses at steady state, and resolving fluxes across most photosynthetic metabolic pathways in algae. The system involves injecting algal cultures and medium containing pre-equilibrated inorganic 13C into a microfluidic mixer, followed by rapid metabolic quenching, enabling precise seconds-level label pulses. This was complemented by a 13CO2-bubbling-based open labelling system (photobioreactor), allowing long pulses (minutes-hours) required for investigating fluxes into central C metabolism and major products. This combined labelling procedure provides a comprehensive fluxome cover for most algal photosynthetic and central C metabolism pathways, thus allowing comparative flux analyses across algae and plants.

Time-resolved, deuterium-based fluxomics uncovers the hierarchy and dynamics of sugar processing by Pseudomonas putida

Pseudomonas putida, a microbial host widely adopted for metabolic engineering, processes glucose through convergent peripheral pathways that ultimately yield 6-phosphogluconate. The periplasmic gluconate shunt (PGS), composed by glucose and gluconate dehydrogenases, sequentially transforms glucose into gluconate and 2-ketogluconate. Although the secretion of these organic acids by P. putida has been extensively recognized, the mechanism and spatiotemporal regulation of the PGS remained elusive thus far. To address this challenge, we adopted a dynamic 13C- and 2H-metabolic flux analysis strategy, termed D-fluxomics. D-fluxomics demonstrated that the PGS underscores a highly dynamic metabolic architecture in glucose-dependent batch cultures of P. putida, characterized by hierarchical carbon uptake by the PGS throughout the cultivation. Additionally, we show that gluconate and 2-ketogluconate accumulation and consumption can be solely explained as a result of the interplay between growth rate-coupled and decoupled metabolic fluxes. As a consequence, the formation of these acids in the PGS is inversely correlated to the bacterial growth rate-unlike the widely studied overflow metabolism of Escherichia coli and yeast. Our findings, which underline survival strategies of soil bacteria thriving in their natural environments, open new avenues for engineering P. putida towards efficient, sugar-based bioprocesses.

Monitoring and modelling the glutamine metabolic pathway: a review and future perspectives

BACKGROUND

Analysis of the glutamine metabolic pathway has taken a special place in metabolomics research in recent years, given its important role in cell biosynthesis and bioenergetics across several disorders, especially in cancer cell survival. The science of metabolomics addresses the intricate intracellular metabolic network by exploring and understanding how cells function and respond to external or internal perturbations to identify potential therapeutic targets. However, despite recent advances in metabolomics, monitoring the kinetics of a metabolic pathway in a living cell in situ, real-time and holistically remains a significant challenge.

AIM

This review paper explores the range of analytical approaches for monitoring metabolic pathways, as well as physicochemical modeling techniques, with a focus on glutamine metabolism. We discuss the advantages and disadvantages of each method and explore the potential of label-free Raman microspectroscopy, in conjunction with kinetic modeling, to enable real-time and in situ monitoring of the cellular kinetics of the glutamine metabolic pathway.

KEY SCIENTIFIC CONCEPTS

Given its important role in cell metabolism, the ability to monitor and model the glutamine metabolic pathways are highlighted. Novel, label free approaches have the potential to revolutionise metabolic biosensing, laying the foundation for a new paradigm in metabolomics research and addressing the challenges in monitoring metabolic pathways in living cells.

Isotopic Tracing of Nucleotide Sugar Metabolism in Human Pluripotent Stem Cells

Metabolism not only produces energy necessary for the cell but is also a key regulator of several cellular functions, including pluripotency and self-renewal. Nucleotide sugars (NSs) are activated sugars that link glucose metabolism with cellular functions via protein N-glycosylation and O-GlcNAcylation. Thus, understanding how different metabolic pathways converge in the synthesis of NSs is critical to explore new opportunities for metabolic interference and modulation of stem cell functions. Tracer-based metabolomics is suited for this challenge, however chemically-defined, customizable media for stem cell culture in which nutrients can be replaced with isotopically labeled analogs are scarcely available. Here, we established a customizable flux-conditioned E8 (FC-E8) medium that enables stem cell culture with stable isotopes for metabolic tracing, and a dedicated liquid chromatography mass-spectrometry (LC-MS/MS) method targeting metabolic pathways converging in NS biosynthesis. By 13C6-glucose feeding, we successfully traced the time-course of carbon incorporation into NSs directly via glucose, and indirectly via other pathways, such as glycolysis and pentose phosphate pathways, in induced pluripotent stem cells (hiPSCs) and embryonic stem cells. Then, we applied these tools to investigate the NS biosynthesis in hiPSC lines from a patient affected by deficiency of phosphoglucomutase 1 (PGM1), an enzyme regulating the synthesis of the two most abundant NSs, UDP-glucose and UDP-galactose.

Expression of malic enzyme reveals subcellular carbon partitioning for storage reserve production in soybeans

Central metabolism produces amino and fatty acids for protein and lipids that establish seed value. Biosynthesis of storage reserves occurs in multiple organelles that exchange central intermediates including two essential metabolites, malate, and pyruvate that are linked by malic enzyme. Malic enzyme can be active in multiple subcellular compartments, partitioning carbon and reducing equivalents for anabolic and catabolic requirements. Prior studies based on isotopic labeling and steady-state metabolic flux analyses indicated malic enzyme provides carbon for fatty acid biosynthesis in plants, though genetic evidence confirming this role is lacking. We hypothesized that increasing malic enzyme flux would alter carbon partitioning and result in increased lipid levels in soybeans. Homozygous transgenic soybean plants expressing Arabidopsis malic enzyme alleles, targeting the translational products to plastid or outside the plastid during seed development, were verified by transcript and enzyme activity analyses, organelle proteomics, and transient expression assays. Protein, oil, central metabolites, cofactors, and acyl-acyl carrier protein (ACPs) levels were quantified overdevelopment. Amino and fatty acid levels were altered resulting in an increase in lipids by 0.5-2% of seed biomass (i.e. 2-9% change in oil). Subcellular targeting of a single gene product in central metabolism impacts carbon and reducing equivalent partitioning for seed storage reserves in soybeans.

Isotopically non-stationary metabolic flux analysis of heterotrophic Arabidopsis thaliana cell cultures

Fluxes are the ultimate phenotype of metabolism and their accurate quantification is fundamental to any understanding of metabolic networks. Steady state metabolic flux analysis has been the method of choice for quantifying fluxes in heterotrophic cells, but it is unable to measure fluxes during short-lived metabolic states, such as a transient oxidative load. Isotopically non-stationary metabolic flux analysis (INST-MFA) can be performed over shorter timescales (minutes - hours) and might overcome this limitation. INST-MFA has recently been applied to photosynthesising leaves, but agriculturally important tissues such as roots and storage organs, or plants during the night are heterotrophic. Here we outline the application of INST-MFA to heterotrophic plant cells. Using INST-MFA we were able to identify changes in the fluxes supported by phosphoenolpyruvate carboxylase and malic enzyme under oxidative load, highlighting the potential of INST-MFA to measure fluxes during short-lived metabolic states. We discuss the challenges in applying INST-MFA, and highlight further development required before it can be routinely used to quantify fluxes in heterotrophic plant cells.

Stochastic simulation algorithm for isotope-based dynamic flux analysis

Carbon isotope labeling method is a standard metabolic engineering tool for flux quantification in living cells. To cope with the high dimensionality of isotope labeling systems, diverse algorithms have been developed to reduce the number of variables or operations in metabolic flux analysis (MFA), but lacks generalizability to non-stationary metabolic conditions. In this study, we present a stochastic simulation algorithm (SSA) derived from the chemical master equation of the isotope labeling system. This algorithm allows to compute the time evolution of isotopomer concentrations in non-stationary conditions, with the valuable property that computational time does not scale with the number of isotopomers. The efficiency and limitations of the algorithm is benchmarked for the forward and inverse problems of 13C-DMFA in the pentose phosphate pathways, and is compared with EMU-based methods for NMFA and MFA including the central carbon metabolism. Overall, SSA constitutes an alternative class to deterministic approaches for metabolic flux analysis that is well adapted to comprehensive dataset including parallel labeling experiments, and whose limitations associated to the sampling size can be overcome by using Monte Carlo sampling approaches.

Glutaraldehyde and uranyl acetate dual fixation combined sputtering/unroofing enables intracellular fatty acids TOF-SIMS imaging with organelle-corresponding subcellular distribution

Fatty acids (FAs) have diverse functions in cellular activities. The intracellular distribution of FAs is critical for their functions. Imaging of FAs by time-of-flight secondary ion mass spectrometry (TOF-SIMS) has been achieved. However, TOF-SIMS images of FAs so far do not have subcellular distribution due to inadequate sample preparation methods. In this study, we developed a chemical fixation method using glutaraldehyde (GA) with uranyl acetate (UA), which preserved cellular structure and intracellular FA distribution well. Combining GA+UA fixation with sputtering-based methods and unroofing-based methods, respectively, we successfully imaged intracellular lipids with the subcellular distribution.

Metabolic synergy in Camelina reproductive tissues for seed development

Photosynthesis in fruits is well documented, but its contribution to seed development and yield remains largely unquantified. In oilseeds, the pods are green and elevated with direct access to sunlight. With ¹³C labeling in planta and through an intact pod labeling system, a unique multi-tissue comprehensive flux model mechanistically described how pods assimilate up to one-half (33 to 45%) of seed carbon by proximal photosynthesis in Camelina sativa. By capturing integrated tissue metabolism, the studies reveal the contribution of plant architecture beyond leaves, to enable seed filling and maximize the number of viable seeds. The latent capacity of the pod wall in the absence of leaves contributes approximately 79% of seed biomass, supporting greater seed sink capacity and higher theoretical yields that suggest an opportunity for crop productivity gains.

Recent metabolomic developments for antimalarial drug discovery

Malaria is a parasitic disease that remains a global health issue, responsible for a significant death and morbidity toll. Various factors have impacted the use and delayed the development of antimalarial therapies, such as the associated financial cost and parasitic resistance. In order to discover new drugs and validate parasitic targets, a powerful omics tool, metabolomics, emerged as a reliable approach. However, as a fairly recent method in malaria, new findings are timely and original practices emerge frequently. This review aims to discuss recent research towards the development of new metabolomic methods in the context of uncovering antiplasmodial mechanisms of action in vitro and to point out innovative metabolic pathways that can revitalize the antimalarial pipeline.

13CO2 labeling kinetics in maize reveal impaired efficiency of C4 photosynthesis under low irradiance

C4 photosynthesis allows faster photosynthetic rates and higher water and nitrogen use efficiency than C3 photosynthesis, but at the cost of lower quantum yield due to the energy requirement of its biochemical carbon concentration mechanism. It has also been suspected that its operation may be impaired in low irradiance. To investigate fluxes under moderate and low irradiance, maize (Zea mays) was grown at 550 µmol photons m-2 s-l and 13CO2 pulse-labeling was performed at growth irradiance or several hours after transfer to 160 µmol photons m-2 s-1. Analysis by liquid chromatography/tandem mass spectrometry or gas chromatography/mass spectrometry provided information about pool size and labeling kinetics for 32 metabolites and allowed estimation of flux at many steps in C4 photosynthesis. The results highlighted several sources of inefficiency in low light. These included excess flux at phosphoenolpyruvate carboxylase, restriction of decarboxylation by NADP-malic enzyme, and a shift to increased CO2 incorporation into aspartate, less effective use of metabolite pools to drive intercellular shuttles, and higher relative and absolute rates of photorespiration. The latter provides evidence for a lower bundle sheath CO2 concentration in low irradiance, implying that operation of the CO2 concentration mechanism is impaired in this condition. The analyses also revealed rapid exchange of carbon between the Calvin-Benson cycle and the CO2-concentration shuttle, which allows rapid adjustment of the balance between CO2 concentration and assimilation, and accumulation of large amounts of photorespiratory intermediates in low light that provides a major carbon reservoir to build up C4 metabolite pools when irradiance increases.

13C-labeling reveals how membrane lipid components contribute to triacylglycerol accumulation in Chlamydomonas

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.

An efficient LC-MS method for isomer separation and detection of sugars, phosphorylated sugars, and organic acids

Assessing central carbon metabolism in plants can be challenging due to the dynamic range in pool sizes, with low levels of important phosphorylated sugars relative to more abundant sugars and organic acids. Here, we report a sensitive liquid chromatography-mass spectrometry method for analysing central metabolites on a hybrid column, where both anion-exchange and hydrophilic interaction chromatography (HILIC) ligands are embedded in the stationary phase. The liquid chromatography method was developed for enhanced selectivity of 27 central metabolites in a single run with sensitivity at femtomole levels observed for most phosphorylated sugars. The method resolved phosphorylated hexose, pentose, and triose isomers that are otherwise challenging. Compared with a standard HILIC approach, these metabolites had improved peak areas using our approach due to ion enhancement or low ion suppression in the biological sample matrix. The approach was applied to investigate metabolism in high lipid-producing tobacco leaves that exhibited increased levels of acetyl-CoA, a precursor for oil biosynthesis. The application of the method to isotopologue detection and quantification was considered through evaluating 13C-labeled seeds from Camelina sativa. The method provides a means to analyse intermediates more comprehensively in central metabolism of plant tissues.

A negative-solvatochromic fluorescent probe for visualizing intracellular distributions of fatty acid metabolites

Metabolic distribution of fatty acid to organelles is an essential biological process for energy homeostasis as well as for the maintenance of membrane integrity, and the metabolic pathways are strictly regulated in response to environmental stimuli. Herein, we report a fluorescent fatty acid probe, which bears an azapyrene dye that changes its absorption and emission features depending on the microenvironment polarity of the organelle into which it is transported. Owing to the environmental sensitivity of this dye, the distribution of the metabolically incorporated probe in non-polar lipid droplets, medium-polarity membranes, and the polar aqueous regions, can be visualized in different colors. Based on density scatter plots of the fluorophore, we demonstrate that the degradation of triacylglycerols in lipid droplets occurs predominantly via lipolysis rather than lipophagy in nutrition-starved hepatocytes. This tool can thus be expected to significantly advance our understanding of the lipid metabolism in living organisms.

Metabolic distribution of fatty acids to organelles is an essential biological process for energy homeostasis. Here the authors report a fluorescent probe that allows multicolour visualisation of the intracellular distribution of exogenous fatty acids, metabolically incorporated as lipid components.

Reimport of carbon from cytosolic and vacuolar sugar pools into the Calvin-Benson cycle explains photosynthesis labeling anomalies

SignificancePhotosynthesis 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.

Metabolic profiles in C3, C3-C4 intermediate, C4-like, and C4 species in the genus Flaveria

C4 photosynthesis concentrates CO2 around Rubisco in the bundle sheath, favouring carboxylation over oxygenation and decreasing photorespiration. This complex trait evolved independently in >60 angiosperm lineages. Its evolution can be investigated in genera such as Flaveria (Asteraceae) that contain species representing intermediate stages between C3 and C4 photosynthesis. Previous studies have indicated that the first major change in metabolism probably involved relocation of glycine decarboxylase and photorespiratory CO2 release to the bundle sheath and establishment of intercellular shuttles to maintain nitrogen stoichiometry. This was followed by selection for a CO2-concentrating cycle between phosphoenolpyruvate carboxylase in the mesophyll and decarboxylases in the bundle sheath, and relocation of Rubisco to the latter. We have profiled 52 metabolites in nine Flaveria species and analysed 13CO2 labelling patterns for four species. Our results point to operation of multiple shuttles, including movement of aspartate in C3-C4 intermediates and a switch towards a malate/pyruvate shuttle in C4-like species. The malate/pyruvate shuttle increases from C4-like to complete C4 species, accompanied by a rise in ancillary organic acid pools. Our findings support current models and uncover further modifications of metabolism along the evolutionary path to C4 photosynthesis in the genus Flaveria.

INTEGRATE: Model-based multi-omics data integration to characterize multi-level metabolic regulation

Metabolism is directly and indirectly fine-tuned by a complex web of interacting regulatory mechanisms that fall into two major classes. On the one hand, the expression level of the catalyzing enzyme sets the maximal theoretical flux level (i.e., the net rate of the reaction) for each enzyme-controlled reaction. On the other hand, metabolic regulation controls the metabolic flux through the interactions of metabolites (substrates, cofactors, allosteric modulators) with the responsible enzyme. High-throughput data, such as metabolomics and transcriptomics data, if analyzed separately, do not accurately characterize the hierarchical regulation of metabolism outlined above. They must be integrated to disassemble the interdependence between different regulatory layers controlling metabolism. To this aim, we propose INTEGRATE, a computational pipeline that integrates metabolomics and transcriptomics data, using constraint-based stoichiometric metabolic models as a scaffold. We compute differential reaction expression from transcriptomics data and use constraint-based modeling to predict if the differential expression of metabolic enzymes directly originates differences in metabolic fluxes. In parallel, we use metabolomics to predict how differences in substrate availability translate into differences in metabolic fluxes. We discriminate fluxes regulated at the metabolic and/or gene expression level by intersecting these two output datasets. We demonstrate the pipeline using a set of immortalized normal and cancer breast cell lines. In a clinical setting, knowing the regulatory level at which a given metabolic reaction is controlled will be valuable to inform targeted, truly personalized therapies in cancer patients.

Cardiac stem cells: Current knowledge and future prospects

Regenerative medicine is the field concerned with the repair and restoration of the integrity of damaged human tissues as well as whole organs. Since the inception of the field several decades ago, regenerative medicine therapies, namely stem cells, have received significant attention in preclinical studies and clinical trials. Apart from their known potential for differentiation into the various body cells, stem cells enhance the organ's intrinsic regenerative capacity by altering its environment, whether by exogenous injection or introducing their products that modulate endogenous stem cell function and fate for the sake of regeneration. Recently, research in cardiology has highlighted the evidence for the existence of cardiac stem and progenitor cells (CSCs/CPCs). The global burden of cardiovascular diseases’ morbidity and mortality has demanded an in-depth understanding of the biology of CSCs/CPCs aiming at improving the outcome for an innovative therapeutic strategy. This review will discuss the nature of each of the CSCs/CPCs, their environment, their interplay with other cells, and their metabolism. In addition, important issues are tackled concerning the potency of CSCs/CPCs in relation to their secretome for mediating the ability to influence other cells. Moreover, the review will throw the light on the clinical trials and the preclinical studies using CSCs/CPCs and combined therapy for cardiac regeneration. Finally, the novel role of nanotechnology in cardiac regeneration will be explored.

Cardiac stem cells: Current knowledge and future prospects

Regenerative medicine is the field concerned with the repair and restoration of the integrity of damaged human tissues as well as whole organs. Since the inception of the field several decades ago, regenerative medicine therapies, namely stem cells, have received significant attention in preclinical studies and clinical trials. Apart from their known potential for differentiation into the various body cells, stem cells enhance the organ's intrinsic regenerative capacity by altering its environment, whether by exogenous injection or introducing their products that modulate endogenous stem cell function and fate for the sake of regeneration. Recently, research in cardiology has highlighted the evidence for the existence of cardiac stem and progenitor cells (CSCs/CPCs). The global burden of cardiovascular diseases' morbidity and mortality has demanded an in-depth understanding of the biology of CSCs/CPCs aiming at improving the outcome for an innovative therapeutic strategy. This review will discuss the nature of each of the CSCs/CPCs, their environment, their interplay with other cells, and their metabolism. In addition, important issues are tackled concerning the potency of CSCs/CPCs in relation to their secretome for mediating the ability to influence other cells. Moreover, the review will throw the light on the clinical trials and the preclinical studies using CSCs/CPCs and combined therapy for cardiac regeneration. Finally, the novel role of nanotechnology in cardiac regeneration will be explored.

Metabolic flux analysis of the non-transitory starch tradeoff for lipid production in mature tobacco leaves

The metabolic plasticity of tobacco leaves has been demonstrated via the generation of transgenic plants that can accumulate over 30% dry weight as triacylglycerols. In investigating the changes in carbon partitioning in these high lipid-producing (HLP) leaves, foliar lipids accumulated stepwise over development. Interestingly, non-transient starch was observed to accumulate with plant age in WT but not HLP leaves, with a drop in foliar starch concurrent with an increase in lipid content. The metabolic carbon tradeoff between starch and lipid was studied using 13CO2-labeling experiments and isotopically nonstationary metabolic flux analysis, not previously applied to the mature leaves of a crop. Fatty acid synthesis was investigated through assessment of acyl-acyl carrier proteins using a recently derived quantification method that was extended to accommodate isotopic labeling. Analysis of labeling patterns and flux modeling indicated the continued production of unlabeled starch, sucrose cycling, and a significant contribution of NADP-malic enzyme to plastidic pyruvate production for the production of lipids in HLP leaves, with the latter verified by enzyme activity assays. The results suggest an inherent capacity for a developmentally regulated carbon sink in tobacco leaves and may in part explain the uniquely successful leaf lipid engineering efforts in this crop.

Validation of carbon isotopologue distribution measurements by GC-MS and application to 13C-metabolic flux analysis of the tricarboxylic acid cycle in Brassica napus leaves

The estimation of metabolic fluxes in photosynthetic organisms represents an important challenge that has gained interest over the last decade with the development of ¹³C-Metabolic Flux Analysis at isotopically non-stationary steady-state. This approach requires a high level of accuracy for the measurement of Carbon Isotopologue Distribution in plant metabolites. But this accuracy has still not been evaluated at the isotopologue level for GC-MS, leading to uncertainties for the metabolic fluxes calculated based on these fragments. Here, we developed a workflow to validate the measurements of CIDs from plant metabolites with GC-MS by producing tailor-made E. coli standard extracts harboring a predictable binomial CID for some organic and amino acids. Overall, most of our TMS-derivatives mass fragments were validated with these standards and at natural isotope abundance in plant matrices. Then, we applied this validated MS method to investigate the light/dark regulation of plant TCA cycle by incorporating U-¹³C-pyruvate to Brassica napus leaf discs. We took advantage of pathway-specific isotopologues/isotopomers observed between two and six hours of labeling to show that the TCA cycle can operate in a cyclic manner under both light and dark conditions. Interestingly, this forward cyclic flux mode has a nearly four-fold higher contribution for pyruvate-to-citrate and pyruvate-to-malate fluxes than the phosphoenolpyruvate carboxylase (PEPc) flux reassimilating carbon derived from some mitochondrial enzymes. The contribution of stored citrate to the mitochondrial TCA cycle activity was also questioned based on dynamics of ¹³C-enrichment in citrate, glutamate and succinate and variations of citrate total amounts under light and dark conditions. Interestingly, there was a light-dependent ¹³C-incorporation into glycine and serine showing that decarboxylations from pyruvate dehydrogenase complex and TCA cycle enzymes were actively reassimilated and could represent up to 5% to net photosynthesis.

Liquid Chromatography-Mass Spectrometry for Clinical Metabolomics: An Overview

Metabolomics is a discipline that offers a comprehensive analysis of metabolites in biological samples. In the last decades, the notable evolution in liquid chromatography and mass spectrometry technologies has driven an exponential progress in LC-MS-based metabolomics. Targeted and untargeted metabolomics strategies are important tools in health and medical science, especially in the study of disease-related biomarkers, drug discovery and development, toxicology, diet, physical exercise, and precision medicine. Clinical and biological problems can now be understood in terms of metabolic phenotyping. This overview highlights the current approaches to LC-MS-based metabolomics analysis and its applications in the clinical research.

Biophysical characterization of melanoma cell phenotype markers during metastatic progression

Melanoma is the most fatal form of skin cancer, with increasing prevalence worldwide. The most common melanoma genetic driver is mutation of the proto-oncogene serine/threonine kinase BRAF; thus, the inhibition of its MAP kinase pathway by specific inhibitors is a commonly applied therapy. However, many patients are resistant, or develop resistance to this type of monotherapy, and therefore combined therapies which target other signaling pathways through various molecular mechanisms are required. A possible strategy may involve targeting cellular energy metabolism, which has been recognized as crucial for cancer development and progression and which connects through glycolysis to cell surface glycan biosynthetic pathways. Protein glycosylation is a hallmark of more than 50% of the human proteome and it has been recognized that altered glycosylation occurs during the metastatic progression of melanoma cells which, in turn facilitates their migration. This review provides a description of recent advances in the search for factors able to remodel cell metabolism between glycolysis and oxidative phosphorylation, and of changes in specific markers and in the biophysical properties of cells during melanoma development from a nevus to metastasis. This development is accompanied by changes in the expression of surface glycans, with corresponding changes in ligand-receptor affinity, giving rise to structural features and viscoelastic parameters particularly well suited to study by label-free biophysical methods.

Source of 12C in Calvin-Benson cycle intermediates and isoprene emitted from plant leaves fed with 13CO2

Feeding 14CO2 was crucial to uncovering the path of carbon in photosynthesis. Feeding 13CO2 to photosynthesizing leaves emitting isoprene has been used to develop hypotheses about the sources of carbon for the methylerythritol 4-phosphate pathway, which makes the precursors for terpene synthesis in chloroplasts and bacteria. Both photosynthesis and isoprene studies found that products label very quickly (<10 min) up to 80-90% but the last 10-20% of labeling requires hours indicating a source of 12C during photosynthesis and isoprene emission. Furthermore, studies with isoprene showed that the proportion of slow label could vary significantly. This was interpreted as a variable contribution of carbon from sources other than the Calvin-Benson cycle (CBC) feeding the methylerythritol 4-phosphate pathway. Here, we measured the degree of label in isoprene and photosynthetic metabolites 20 min after beginning to feed 13CO2. Isoprene labeling was the same as labeling of photosynthesis intermediates. High temperature reduced the label in isoprene and photosynthesis intermediates by the same amount indicating no role for alternative carbon sources for isoprene. A model assuming glucose, fructose, and/or sucrose reenters the CBC as ribulose 5-phosphate through a cytosolic shunt involving glucose 6-phosphate dehydrogenase was consistent with the observations.

A guide to metabolic flux analysis in metabolic engineering: Methods, tools and applications

The field of metabolic engineering is primarily concerned with improving the biological production of value-added chemicals, fuels and pharmaceuticals through the design, construction and optimization of metabolic pathways, redirection of intracellular fluxes, and refinement of cellular properties relevant for industrial bioprocess implementation. Metabolic network models and metabolic fluxes are central concepts in metabolic engineering, as was emphasized in the first paper published in this journal, "Metabolic fluxes and metabolic engineering" (Metabolic Engineering, 1: 1-11, 1999). In the past two decades, a wide range of computational, analytical and experimental approaches have been developed to interrogate the capabilities of biological systems through analysis of metabolic network models using techniques such as flux balance analysis (FBA), and quantify metabolic fluxes using constrained-based modeling approaches such as metabolic flux analysis (MFA) and more advanced experimental techniques based on the use of stable-isotope tracers, i.e. ¹³C-metabolic flux analysis (¹³C-MFA). In this review, we describe the basic principles of metabolic flux analysis, discuss current best practices in flux quantification, highlight potential pitfalls and alternative approaches in the application of these tools, and give a broad overview of pragmatic applications of flux analysis in metabolic engineering practice.

Sterile Spikelets Contribute to Yield in Sorghum and Related Grasses

Sorghum (Sorghum bicolor) and its relatives in the grass tribe Andropogoneae bear their flowers in pairs of spikelets in which one spikelet (seed-bearing or sessile spikelet [SS]) of the pair produces a seed and the other is sterile or male (staminate). This division of function does not occur in other major cereals such as wheat (Triticum aestivum) or rice (Oryza sativa). Additionally, one bract of the SS spikelet often produces a long extension, the awn, that is in the same position as, but independently derived from, that of wheat and rice. The function of the sterile spikelet is unknown and that of the awn has not been tested in Andropogoneae. We used radioactive and stable isotopes of carbon, RNA sequencing of metabolically important enzymes, and immunolocalization of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) to show that the sterile spikelet assimilates carbon, which is translocated to the largely heterotrophic SS. The awn shows no evidence of photosynthesis. These results apply to distantly related species of Andropogoneae. Removal of sterile spikelets in sorghum significantly decreases seed weight (yield) by ∼9%. Thus, the sterile spikelet, but not the awn, affects yield in the cultivated species and fitness in the wild species.

Multi-omics systems toxicology study of mouse lung assessing the effects of aerosols from two heat-not-burn tobacco products and cigarette smoke

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Multi-omics systems toxicology study, comprising five omics data modalities.

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Multi-Omics Factor Analysis and multi-modality functional network interpretation.

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Cigarettes smoke (CS) induced complex immunoregulatory interactions across molecular layers.

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Aerosols from two heat-not-burn tobacco products had less impact on lungs than CS.

Cigarette smoke (CS) causes adverse health effects and, for smoker who do not quit, modified risk tobacco products (MRTPs) can be an alternative to reduce the risk of developing smoking-related diseases. Standard toxicological endpoints can lack sensitivity, with systems toxicology approaches yielding broader insights into toxicological mechanisms. In a 6-month systems toxicology study on ApoE^−/− mice, we conducted an integrative multi-omics analysis to assess the effects of aerosols from the Carbon Heated Tobacco Product (CHTP) 1.2 and Tobacco Heating System (THS) 2.2—a potential and a candidate MRTP based on the heat-not-burn (HnB) principle—compared with CS at matched nicotine concentrations. Molecular exposure effects in the lungs were measured by mRNA/microRNA transcriptomics, proteomics, metabolomics, and lipidomics. Integrative data analysis included Multi-Omics Factor Analysis and multi-modality functional network interpretation. Across all five data modalities, CS exposure was associated with an increased inflammatory and oxidative stress response, and lipid/surfactant alterations. Upon HnB aerosol exposure these effects were much more limited or absent, with reversal of CS-induced effects upon cessation and switching to CHTP 1.2. Functional network analysis revealed CS-induced complex immunoregulatory interactions across the investigated molecular layers (e.g., itaconate, quinolinate, and miR-146) and highlighted the engagement of the heme–Hmox–bilirubin oxidative stress axis by CS. This work exemplifies how multi-omics approaches can be leveraged within systems toxicology studies and the generated multi-omics data set can facilitate the development of analysis methods and can yield further insights into the effects of toxicological exposures on the lung of mice.