Green pathways: Metabolic network analysis of plant systems

Isotopically nonstationary 13C metabolic flux analysis in resting and activated human platelets

Platelet metabolism is linked to platelet hyper- and hypoactivity in numerous human diseases. Developing a detailed understanding of the link between metabolic shifts and platelet activation state is integral to improving human health. Here, we show the first application of isotopically nonstationary ¹³C metabolic flux analysis to quantitatively measure carbon fluxes in both resting and thrombin activated platelets. Metabolic flux analysis results show that resting platelets primarily metabolize glucose to lactate via glycolysis, while acetate is oxidized to fuel the tricarboxylic acid cycle. Upon activation with thrombin, a potent platelet agonist, platelets increase their uptake of glucose 3-fold. This results in an absolute increase in flux throughout central metabolism, but when compared to resting platelets they redistribute carbon dramatically. Activated platelets decrease relative flux to the oxidative pentose phosphate pathway and TCA cycle from glucose and increase relative flux to lactate. These results provide the first report of reaction-level carbon fluxes in platelets and allow us to distinguish metabolic fluxes with much higher resolution than previous studies.

Metabolomics and complementary techniques to investigate the plant phytochemical cosmos

Covering: up to 2021Plants and their associated microbial communities are known to produce millions of metabolites, a majority of which are still not characterized and are speculated to possess novel bioactive properties. In addition to their role in plant physiology, these metabolites are also relevant as existing and next-generation medicine candidates. Elucidation of the plant metabolite diversity is thus valuable for the successful exploitation of natural resources for humankind. Herein, we present a comprehensive review on recent metabolomics approaches to illuminate molecular networks in plants, including chemical isolation and enzymatic production as well as the modern metabolomics approaches such as stable isotope labeling, ultrahigh-resolution mass spectrometry, metabolome imaging (spatial metabolomics), single-cell analysis, cheminformatics, and computational mass spectrometry. Mass spectrometry-based strategies to characterize plant metabolomes through metabolite identification and annotation are described in detail. We also highlight the use of phytochemical genomics to mine genes associated with specialized metabolites' biosynthesis. Understanding the metabolic diversity through biotechnological advances is fundamental to elucidate the functions of the plant-derived specialized metabolome.

Multiscale computational models can guide experimentation and targeted measurements for crop improvement

Computational models of plants have identified gaps in our understanding of biological systems, and have revealed ways to optimize cellular processes or organ-level architecture to increase productivity. Thus, computational models are learning tools that help direct experimentation and measurements. Models are simplifications of complex systems, and often simulate specific processes at single scales (e.g. temporal, spatial, organizational, etc.). Consequently, single-scale models are unable to capture the critical cross-scale interactions that result in emergent properties of the system. In this perspective article, we contend that to accurately predict how a plant will respond in an untested environment, it is necessary to integrate mathematical models across biological scales. Computationally mimicking the flow of biological information from the genome to the phenome is an important step in discovering new experimental strategies to improve crops. A key challenge is to connect models across biological, temporal and computational (e.g. CPU versus GPU) scales, and then to visualize and interpret integrated model outputs. We address this challenge by describing the efforts of the international Crops in silico consortium.

Preparation of uniformly labelled 13C- and 15N-plants using customised growth chambers

BACKGROUND

Stable isotopically labelled organisms have found wide application in life science research including plant physiology, plant stress and defense as well as metabolism related sciences. Therefore, the reproducible production of plant material enriched with stable isotopes such as ¹³C and ¹⁵N is of considerable interest. A high degree of enrichment (> 96 atom %) with a uniformly distributed isotope (global labelling) is accomplished by a continuous substrate supply during plant growth/cultivation. In the case of plants, ¹³C-labelling can be achieved by growth in ¹³CO_2(g) atmosphere while global ¹⁵N-labelling needs ¹⁵N- containing salts in the watering/nutrient solution. Here, we present a method for the preparation of ¹³C and ¹⁵N-labelled plants by the use of closed growth chambers and hydroponic nutrient supply. The method is exemplified with durum wheat.

RESULTS

In total, 330 g of globally ¹³C- and 295 g of ¹⁵N-labelled Triticum durum wheat was produced during 87 cultivation days. For this, a total of 3.88 mol of ¹³CO_2(g) and 58 mmol of ¹⁵N were consumed. The degree of enrichment was determined by LC-HRMS and ranged between 96 and 98 atom % for ¹³C and 95-99 atom % for ¹⁵N, respectively. Additionally, the isotopically labelled plant extracts were successfully used for metabolome-wide internal standardisation of native T.durum plants. Application of an isotope-assisted LC-HRMS workflow enabled the detection of 652 truly wheat-derived metabolites out of which 143 contain N.

CONCLUSION

A reproducible cultivation which makes use of climate chambers and hydroponics was successfully adapted to produce highly enriched, uniformly ¹³C- and ¹⁵N-labelled wheat. The obtained plant material is suitable to be used in all kinds of isotope-assisted research. The described technical equipment and protocol can easily be applied to other plants to produce ¹³C-enriched biological samples when the necessary specific adaptations e.g. temperature and light regime, as well as nutrient supply are considered. Additionally, the ¹⁵N-labelling method can also be carried out under regular glasshouse conditions without the need for customised atmosphere.

A strategy for quality evaluation of salt-treated Apocyni Veneti Folium and discovery of efficacy-associated markers by fingerprint-activity relationship modeling

In this study, a fingerprint-activity relationship between chemical fingerprints and hepatoprotective activity was established to evaluate the quality of salt-treated Apocyni Veneti Folium (AVF). Characteristic fingerprints of AVF samples exposed to different concentrations of salt were generated by ultrafast liquid chromatography tandem triple time-of-flight mass/mass spectrometry (UFLC-Triple TOF-MS/MS), and a similarity analysis was performed based on common characteristic peaks by hierarchical clustering analysis (HCA). Then, the hepatoprotective activity of AVF against CCl₄-induced acute liver damage in mice was investigated by assessing biochemical markers and histopathology, which showed that a high dose of AVF exposed to low levels of salt stress produced a marked amelioration of hepatic damage compared with the other salt-treated AVF. Finally, fingerprint-activity relationship modeling, which was capable of discovering the bioactive markers used in the quality evaluation, was investigated by the chemical fingerprints and the hepatoprotective activities utilizing multivariate statistical analysis, gray correlation analysis (GCA) and bivariate correlation analysis (BCA). The results showed that the accumulation of polyphenols, such as flavonoids and phenolic acids, in AVF subjected to low levels of salt stress could result in the effective scavenging of free radicals. Therefore, the present study may provide a powerful strategy to holistically evaluate the quality of salt-treated AVF in combination with chemical fingerprint and bioactivity evaluation.

Metabolomics characterizes metabolic changes of Apocyni Veneti Folium in response to salt stress

Apocyni Veneti Folium (AVF) has been raised great interest in the antioxidant properties recently for the preservation of human health. However, little research was found on the integrate metabolites except our previous investigation on the variations of the bioactive constituents. To understand the salt-tolerant mechanisms of the halophyte, metabolomic platform based on ultra-fast liquid chromatography tandem triple time-of-flight mass/mass spectrometer was applied in this study. The results showed that metabolic profiles were separated and differentiated among groups based on multivariate statistical analysis; different metabolites belonged to various chemical classes. Besides, phenylpropanoid pathway and terpenoid biosynthesis were disturbed in all salt-stressed AVF and low salt-treated group appeared to be better than other samples in terms of relative contents (peak areas) of the wide variety of bioactive components and physiological variations of photosynthetic pigments, osmotic homeostasis, lipid peroxidation product and antioxidative enzymes. This study may provide additional insight into the salt-tolerant mechanisms and the quality assessment of AVF in a holistic level based on the plant metabolomics.

Shoot tip culture: a step towards 13C metabolite flux analysis of sink leaf metabolism

BACKGROUND

Better understanding of the physiological and metabolic status of plants can only be obtained when metabolic fluxes are accurately assessed in a growing plant. Steady state ¹³C-MFA has been established as a routine method for analysis of fluxes in plant primary metabolism. However, the experimental system needs to be improved for continuous carbon enrichment from labelled sugars into metabolites for longer periods until complex secondary metabolism reaches steady state.

RESULTS

We developed an in vitro plant culture strategy by using peppermint as a model plant with minimizing unlabelled carbon fixation where growing shoot tip was strongly dependent on labelled glucose for their carbon necessity. We optimized the light condition and detected the satisfactory phenotypical growth under the lower light intensity. Total volatile terpenes were also highest at the same light. Analysis of label incorporation into pulegone monoterpene after continuous U-¹³C₆ glucose feeding revealed nearly 100% ¹³C, even at 15 days after first leaf visibility (DALV). Label enrichment was gradually scrambled with increasing light intensity and leaf age. This study was validated by showing similar levels of label enrichment in proteinogenic amino acids. The efficiency of this method was also verified in oregano.

CONCLUSIONS

Our shoot tip culture depicted a method in achieving long term, stable and a high percentage of label accumulation in secondary metabolites within a fully functional growing plant system. It recommends the potential application for the investigations of various facets of plant metabolism by steady state ¹³C-MFA. The system also provides a greater potential to study sink leaf metabolism. Overall, we propose a system to accurately describe complex metabolic phenotypes in a growing plant.

Using metabolome data for mathematical modeling of plant metabolic systems

Plant metabolism is characterized by a wide diversity of metabolites, with systems far more complicated than those of microorganisms. Mathematical modeling is useful for understanding dynamic behaviors of plant metabolic systems for metabolic engineering. Time-series metabolome data has great potential for estimating kinetic model parameters to construct a genome-wide metabolic network model. However, data obtained by current metabolomics techniques does not meet the requirement for constructing accurate models. In this article, we highlight novel strategies and algorithms to handle the underlying difficulties and construct dynamic in vivo models for large-scale plant metabolic systems. The coarse but efficient modeling enables the prediction of unknown mechanisms regulating plant metabolism.

Comparative Metabolomic Analysis of the Cambium Tissue of Non-transgenic and Multi-Gene Transgenic Poplar (Populus × euramericana 'Guariento')

Poplar, a model for woody plant research, is the most widely distributed tree species in the world. Metabolites are the basis of phenotypes, allowing an intuitive and effective understanding of biological processes and their mechanisms. However, metabolites in non-transgenic and multi-gene transgenic poplar remains poorly characterized, especially in regards of the influences on quantity and in the analysis of the relative abundance of metabolites after the introduction of multi stress-related genes. In this study, we investigated the cambium metabolomes of one non-transgenic (D5-0) and two multi-gene (vgb, SacB, ERF36, BtCry3A, and OC-I) transgenic lines (D5-20 and D5-21) of hybrid poplar (Populus × euramericana 'Guariento') using both gas chromatography-mass spectrometry (GC-MS) and ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). We aimed to explore the effects of the exogenous genes on metabolite composition and to screen out metabolites with important biological functions. Finally, we identified 239 named metabolites and determined their relative abundance. Among these, 197 metabolites had a different abundance across the three lines. These methabolites spanned nine primary and 44 secondary metabolism pathways. Arginine and glutamate, as substrates and intermediates in nitrogen metabolism, and important in growth and stress-related processes, as well as sucrose, uridine diphosphate glucose, and their derivatives, precursors in cell wall pathways, and catechol, relevant to insect resistance, differed greatly between the genetically modified and non-transgenic poplar. These findings may provide a basis for further study of cambium metabolism, and fully understand metabolites associated with stress response.

Modeling the Metabolism of Arabidopsis thaliana: Application of Network Decomposition and Network Reduction in the Context of Petri Nets

Motivation:Arabidopsis thaliana is a well-established model system for the analysis of the basic physiological and metabolic pathways of plants. Nevertheless, the system is not yet fully understood, although many mechanisms are described, and information for many processes exists. However, the combination and interpretation of the large amount of biological data remain a big challenge, not only because data sets for metabolic paths are still incomplete. Moreover, they are often inconsistent, because they are coming from different experiments of various scales, regarding, for example, accuracy and/or significance. Here, theoretical modeling is powerful to formulate hypotheses for pathways and the dynamics of the metabolism, even if the biological data are incomplete. To develop reliable mathematical models they have to be proven for consistency. This is still a challenging task because many verification techniques fail already for middle-sized models. Consequently, new methods, like decomposition methods or reduction approaches, are developed to circumvent this problem. Methods: We present a new semi-quantitative mathematical model of the metabolism of Arabidopsis thaliana. We used the Petri net formalism to express the complex reaction system in a mathematically unique manner. To verify the model for correctness and consistency we applied concepts of network decomposition and network reduction such as transition invariants, common transition pairs, and invariant transition pairs. Results: We formulated the core metabolism of Arabidopsis thaliana based on recent knowledge from literature, including the Calvin cycle, glycolysis and citric acid cycle, glyoxylate cycle, urea cycle, sucrose synthesis, and the starch metabolism. By applying network decomposition and reduction techniques at steady-state conditions, we suggest a straightforward mathematical modeling process. We demonstrate that potential steady-state pathways exist, which provide the fixed carbon to nearly all parts of the network, especially to the citric acid cycle. There is a close cooperation of important metabolic pathways, e.g., the de novo synthesis of uridine-5-monophosphate, the γ-aminobutyric acid shunt, and the urea cycle. The presented approach extends the established methods for a feasible interpretation of biological network models, in particular of large and complex models.

In silico metabolic network analysis of Arabidopsis leaves

Background

During the last decades, we face an increasing interest in superior plants to supply growing demands for human and animal nutrition and for the developing bio-based economy. Presently, our limited understanding of their metabolism and its regulation hampers the targeted development of desired plant phenotypes. In this regard, systems biology, in particular the integration of metabolic and regulatory networks, is promising to broaden our knowledge and to further explore the biotechnological potential of plants.

Results

The thale cress Arabidopsis thaliana provides an ideal model to understand plant primary metabolism. To obtain insight into its functional properties, we constructed a large-scale metabolic network of the leaf of A. thaliana. It represented 511 reactions with spatial separation into compartments. Systematic analysis of this network, utilizing elementary flux modes, investigates metabolic capabilities of the plant and predicts relevant properties on the systems level: optimum pathway use for maximum growth and flux re-arrangement in response to environmental perturbation. Our computational model indicates that the A. thaliana leaf operates near its theoretical optimum flux state in the light, however, only in a narrow range of photon usage. The simulations further demonstrate that the natural day-night shift requires substantial re-arrangement of pathway flux between compartments: 89 reactions, involving redox and energy metabolism, substantially change the extent of flux, whereas 19 reactions even invert flux direction. The optimum set of anabolic pathways differs between day and night and is partly shifted between compartments. The integration with experimental transcriptome data pinpoints selected transcriptional changes that mediate the diurnal adaptation of the plant and superimpose the flux response.

Conclusions

The successful application of predictive modelling in Arabidopsis thaliana can bring systems-biological interpretation of plant systems forward. Using the gained knowledge, metabolic engineering strategies to engage plants as biotechnological factories can be developed.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-016-0347-3) contains supplementary material, which is available to authorized users.

Non-targeted Metabolite Profiling and Scavenging Activity Unveil the Nutraceutical Potential of Psyllium (Plantago ovata Forsk)

Non-targeted metabolomics implies that psyllium (Plantago ovata) is a rich source of natural antioxidants, PUFAs (ω-3 and ω-6 fatty acids) and essential and sulfur-rich amino acids, as recommended by the FAO for human health. Psyllium contains phenolics and flavonoids that possess reducing capacity and reactive oxygen species (ROS) scavenging activities. In leaves, seeds, and husks, about 76, 78, 58% polyunsaturated, 21, 15, 20% saturated, and 3, 7, 22% monounsaturated fatty acids were found, respectively. A range of FAs (C12 to C24) was detected in psyllium and among different plant parts, a high content of the nutritive indicators ω-3 alpha-linolenic acid CPS (57%) and ω-6 linoleic acid CPS (18%) was detected in leaves. Similarly, total content of phenolics and the essential amino acid valine were also detected utmost in leaves followed by sulfur-rich amino acids and flavonoids. In total, 36 different metabolites were identified in psyllium, out of which 26 (13 each) metabolites were detected in leaves and seeds, whereas the remaining 10 were found in the husk. Most of the metabolites are natural antioxidants, phenolics, flavonoids, or alkaloids and can be used as nutrient supplements. Moreover, these metabolites have been reported to have several pharmaceutical applications, including anti-cancer activity. Natural plant ROS scavengers, saponins, were also detected. Based on metabolomic data, the probable presence of a flavonoid biosynthesis pathway was inferred, which provides useful insight for metabolic engineering in the future. Non-targeted metabolomics, antioxidants and scavenging activities reveal the nutraceutical potential of the plant and also suggest that psyllium leaves can be used as a green salad as a dietary supplement to daily food.