Combining Gas Exchange and Rapid Quenching of Leaf Tissue for Mass Spectrometry and NMR Analysis Using an External Chamber.

We describe here a method to study and manipulate photorespiration in intact illuminated leaves. When the CO2/O2 mole fraction ratio changes, instant sampling is critical, to quench leaf metabolism and thus trace rapid metabolic modification due to gaseous conditions. To do so, we combine 13CO2 labeling and gas exchange, using a large custom leaf chamber to facilitate fast sampling by direct liquid nitrogen spraying. Moreover, the use of a high chamber surface area (about 130 cm2) allows one to sample a large amount of leaf material to carry out 13C-nuclear magnetic resonance (NMR) analysis and complementary analyses, such as isotopic analyses by high-resolution mass spectrometry (by both GC and LC-MS). 13C-NMR gives access to absolute 13C amounts at the specific carbon atom position in the labeled molecules and thereby provides an estimate of 13C-flux of photorespiratory intermediates. Since NMR analysis is not very sensitive and can miss minor metabolites, GC or LC-MS analyses are useful to monitor metabolites at low concentrations. Furthermore, 13C-NMR and high-resolution LC-MS allow to estimate isotopologue distribution in response to 13CO2 labeling while modifying photorespiration activity.

Leaf day respiration involves multiple carbon sources and depends on previous dark metabolism.

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.

Phloem Sap Composition: What Have We Learnt from Metabolomics?

Phloem sap transport is essential for plant nutrition and development since it mediates redistribution of nutrients, metabolites and signaling molecules. However, its biochemical composition is not so well-known because phloem sap sampling is difficult and does not always allow extensive chemical analysis. In the past years, efforts have been devoted to metabolomics analyses of phloem sap using either liquid chromatography or gas chromatography coupled with mass spectrometry. Phloem sap metabolomics is of importance to understand how metabolites can be exchanged between plant organs and how metabolite allocation may impact plant growth and development. Here, we provide an overview of our current knowledge of phloem sap metabolome and physiological information obtained therefrom. Although metabolomics analyses of phloem sap are still not numerous, they show that metabolites present in sap are not just sugars and amino acids but that many more metabolic pathways are represented. They further suggest that metabolite exchange between source and sink organs is a general phenomenon, offering opportunities for metabolic cycles at the whole-plant scale. Such cycles reflect metabolic interdependence of plant organs and shoot-root coordination of plant growth and development.

Experimental Evidence for Seed Metabolic Allometry in Barrel Medic (Medicago truncatula Gaertn.).

Seed size is often considered to be an important trait for seed quality, i.e., vigour and germination performance. It is believed that seed size reflects the quantity of reserve material and thus the C and N sources available for post-germinative processes. However, mechanisms linking seed size and quality are poorly documented. In particular, specific metabolic changes when seed size varies are not well-known. To gain insight into this aspect, we examined seed size and composition across different accessions of barrel medic (Medicago truncatula Gaertn.) from the genetic core collection. We conducted multi-elemental analyses and isotope measurements, as well as exact mass GC-MS metabolomics. There was a systematic increase in N content (+0.17% N mg-1) and a decrease in H content (-0.14% H mg-1) with seed size, reflecting lower lipid and higher S-poor protein quantity. There was also a decrease in 2H natural abundance (δ2H), due to the lower prevalence of 2H-enriched lipid hydrogen atoms that underwent isotopic exchange with water during seed development. Metabolomics showed that seed size correlates with free amino acid and hexoses content, and anticorrelates with amino acid degradation products, disaccharides, malic acid and free fatty acids. All accessions followed the same trend, with insignificant differences in metabolic properties between them. Our results show that there is no general, proportional increase in metabolite pools with seed size. Seed size appears to be determined by metabolic balance (between sugar and amino acid degradation vs. utilisation for storage), which is in turn likely determined by phloem source metabolite delivery during seed development.

Exact mass GC-MS analysis: Protocol, database, advantages and application to plant metabolic profiling.

Plant metabolomics has been used widely in plant physiology, in particular to analyse metabolic responses to environmental parameters. Derivatization (via trimethylsilylation and methoximation) followed by GC-MS metabolic profiling is a major technique to quantify low molecular weight, common metabolites of primary carbon, sulphur and nitrogen metabolism. There are now excellent opportunities for new generation analyses, using high resolution, exact mass GC-MS spectrometers that are progressively becoming relatively cheap. However, exact mass GC-MS analyses for routine metabolic profiling are not common, since there is no dedicated available database. Also, exact mass GC-MS is usually dedicated to structural resolution of targeted secondary metabolites. Here, we present a curated database for exact mass metabolic profiling (made of 336 analytes, 1064 characteristic exact mass fragments) focused on molecules of primary metabolism. We show advantages of exact mass analyses, in particular to resolve isotopic patterns, localise S-containing metabolites, and avoid identification errors when analytes have common nominal mass peaks in their spectrum. We provide a practical example using leaves of different Arabidopsis ecotypes and show how exact mass GC-MS analysis can be applied to plant samples and identify metabolic profiles.

Leafamine®, a Free Amino Acid-Rich Biostimulant, Promotes Growth Performance of Deficit-Irrigated Lettuce.

Water deficit causes substantial yield losses that climate change is going to make even more problematic. Sustainable agricultural practices are increasingly developed to improve plant tolerance to abiotic stresses. One innovative solution amongst others is the integration of plant biostimulants in agriculture. In this work, we investigate for the first time the effects of the biostimulant -Leafamine®-a protein hydrolysate on greenhouse lettuce (Lactuca sativa L.) grown under well-watered and water-deficit conditions. We examined the physiological and metabolomic water deficit responses of lettuce treated with Leafamine® (0.585 g/pot) or not. Root application of Leafamine® increased the shoot fresh biomass of both well-watered (+40%) and deficit-irrigated (+20%) lettuce plants because the projected leaf area increased. Our results also indicate that Leafamine® application could adjust the nitrogen metabolism by enhancing the total nitrogen content, amino acid (proline) contents and the total protein level in lettuce leaves, irrespective of the water condition. Osmolytes such as soluble sugars and polyols, also increased in Leafamine®-treated lettuce. Our findings suggest that the protective effect of Leafamine is a widespread change in plant metabolism and could involve ABA, putrescine and raffinose.

Compound-Specific 14N/15N Analysis of Amino Acid Trimethylsilylated Derivatives from Plant Seed Proteins.

Isotopic analyses of plant samples are now of considerable importance for food certification and plant physiology. In fact, the natural nitrogen isotope composition (δ15N) is extremely useful to examine metabolic pathways of N nutrition involving isotope fractionations. However, δ15N analysis of amino acids is not straightforward and involves specific derivatization procedures to yield volatile derivatives that can be analysed by gas chromatography coupled to isotope ratio mass spectrometry (GC-C-IRMS). Derivatizations other than trimethylsilylation are commonly used since they are believed to be more reliable and accurate. Their major drawback is that they are not associated with metabolite databases allowing identification of derivatives and by-products. Here, we revisit the potential of trimethylsilylated derivatives via concurrent analysis of δ15N and exact mass GC-MS of plant seed protein samples, allowing facile identification of derivatives using a database used for metabolomics. When multiple silylated derivatives of several amino acids are accounted for, there is a good agreement between theoretical and observed N mole fractions, and δ15N values are satisfactory, with little fractionation during derivatization. Overall, this technique may be suitable for compound-specific δ15N analysis, with pros and cons.

Grain carbon isotope composition is a marker for allocation and harvest index in wheat.

The natural 13 C abundance (δ13 C) in plant leaves has been used for decades with great success in agronomy to monitor water-use efficiency and select modern cultivars adapted to dry conditions. However, in wheat, it is also important to find genotypes with high carbon allocation to spikes and grains, and thus with a high harvest index (HI) and/or low carbon losses via respiration. Finding isotope-based markers of carbon partitioning to grains would be extremely useful since isotope analyses are inexpensive and can be performed routinely at high throughput. Here, we took the advantage of a set of field trials made of more than 600 plots with several wheat cultivars and measured agronomic parameters as well as δ13 C values in leaves and grains. We find a linear relationship between the apparent isotope discrimination between leaves and grain (denoted as Δδcorr ), and the respiration use efficiency-to-HI ratio. It means that overall, efficient carbon allocation to grains is associated with a small isotopic difference between leaves and grains. This effect is explained by postphotosynthetic isotope fractionations, and we show that this can be modelled by equations describing the carbon isotope composition in grains along the wheat growth cycle. Our results show that 13 C natural abundance in grains could be useful to find genotypes with better carbon allocation properties and assist current wheat breeding technologies.

Non-targeted 13 C metabolite analysis demonstrates broad re-orchestration of leaf metabolism when gas exchange conditions vary.

It is common practice to manipulate CO2 and O2 mole fraction during gas-exchange experiments to suppress or exacerbate photorespiration, or simply carry out CO2 response curves. In doing so, it is implicitly assumed that metabolic pathways other than carboxylation and oxygenation are altered minimally. In the past few years, targeted metabolic analyses have shown that this assumption is incorrect, with changes in the tricarboxylic acid cycle, anaplerosis (phosphoenolpyruvate carboxylation), and nitrogen or sulphur assimilation. However, this problem has never been tackled systematically using non-targeted analyses to embrace all possible affected metabolic pathways. Here, we exploited combined NMR, GC-MS, and LC-MS data and conducted non-targeted analyses on sunflower leaves sampled at different O2 /CO2 ratios in a gas exchange system. The statistical analysis of nearly 4,500 metabolic features not only confirms previous findings on anaplerosis or S assimilation, but also reveals significant changes in branched chain amino acids, phenylpropanoid metabolism, or adenosine turn-over. Noteworthy, all of these pathways involve CO2 assimilation or liberation and thus affect net CO2 exchange. We conclude that manipulating CO2 and O2 mole fraction has a broad effect on metabolism, and this must be taken into account to better understand variations in carboxylation (anaplerotic fixation) or apparent day respiration.

Consequences of blunting the mevalonate pathway in cancer identified by a pluri-omics approach.

We have previously shown that the combination of statins and taxanes was a powerful trigger of HGT-1 human gastric cancer cells' apoptosis1. Importantly, several genes involved in the "Central carbon metabolism pathway in cancer", as reported in the Kyoto Encyclopedia of Genes and Genomes, were either up- (ACLY, ERBB2, GCK, MYC, PGM, PKFB2, SLC1A5, SLC7A5, SLC16A3,) or down- (IDH, MDH1, OGDH, P53, PDK) regulated in response to the drug association. In the present study, we conducted non-targeted metabolomics and lipidomics analyses by complementary methods and cross-platform initiatives, namely mass spectrometry (GC-MS, LC-MS) and nuclear magnetic resonance (NMR), to analyze the changes resulting from these treatments. We identified several altered biochemical pathways involved in the anabolism and disposition of amino acids, sugars, and lipids. Using the Cytoscape environment with, as an input, the identified biochemical marker changes, we distinguished the functional links between pathways. Finally, looking at the overlap between metabolomics/lipidomics and transcriptome changes, we identified correlations between gene expression modifications and changes in metabolites/lipids. Among the metabolites commonly detected by all types of platforms, glutamine was the most induced (6-7-fold), pointing to an important metabolic adaptation of cancer cells. Taken together, our results demonstrated that combining robust biochemical and molecular approaches was efficient to identify both altered metabolic pathways and overlapping gene expression alterations in human gastric cancer cells engaging into apoptosis following blunting the cholesterol synthesis pathway.

13C and 15N natural isotope abundance reflects breast cancer cell metabolism.

Breast cancer is the most common cancer in women worldwide. Despite the information provided by anatomopathological assessment and molecular markers (such as receptor expression ER, PR, HER2), breast cancer therapies and prognostics depend on the metabolic properties of tumor cells. However, metabolomics have not provided a robust and congruent biomarker yet, likely because individual metabolite contents are insufficient to encapsulate all of the alterations in metabolic fluxes. Here, we took advantage of natural 13C and 15N isotope abundance to show there are isotopic differences between healthy and cancer biopsy tissues or between healthy and malignant cultured cell lines. Isotope mass balance further suggests that these differences are mostly related to lipid metabolism, anaplerosis and urea cycle, three pathways known to be impacted in malignant cells. Our results demonstrate that the isotope signature is a good descriptor of metabolism since it integrates modifications in C partitioning and N excretion altogether. Our present study is thus a starting point to possible clinical applications such as patient screening and biopsy characterization in every cancer that is associated with metabolic changes.

Multi-element, multi-compound isotope profiling as a means to distinguish the geographical and varietal origin of fermented cocoa (Theobroma cacao L.) beans.

Multi-element stable isotope ratios have been assessed as a means to distinguish between fermented cocoa beans from different geographical and varietal origins. Isotope ratios and percentage composition for C and N were measured in different tissues (cotyledons, shells) and extracts (pure theobromine, defatted cocoa solids, protein, lipids) obtained from fermented cocoa bean samples. Sixty-one samples from 24 different geographical origins covering all four continental areas producing cocoa were analyzed. Treatment of the data with unsupervised (Principal Component Analysis) and supervised (Partial Least Squares Discriminant Analysis) multiparametric statistical methods allowed the cocoa beans from different origins to be distinguished. The most discriminant variables identified as responsible for geographical and varietal differences were the δ(15)N and δ(13)C values of cocoa beans and some extracts and tissues. It can be shown that the isotope ratios are correlated with the altitude and precipitation conditions found in the different cocoa-growing regions.

1H NMR metabolomic signatures in five brain regions of the AßPPswe Tg2576 mouse model of Alzheimer's disease at four ages.

In the quest for biomarkers of onset and progression of Alzheimer's disease, a 1H NMR-based metabolomic study was performed on the simple single-transgenic Tg2576 mouse model. These mice develop a slow cognitive decline starting by 6 months and express amyloid plaques from 10 months of age. The metabolic profiles of extracts from five brain regions (frontal cortex, rhinal cortex, hippocampus, midbrain, and cerebellum) of Tg2576 male mice were compared to those of controls, at 1, 3, 6 and 11 months of age. The most obvious differences were due to brain regions. Age was also a discriminating parameter. Metabolic perturbations were already detected in the hippocampus and the rhinal cortex of transgenic mice as early as 1 month of age with decreased concentrations of glutamate (Glu) and N-acetylaspartate (NAA) compared to those in wild-type animals. Metabolic changes were more numerous in the hippocampus and the rhinal cortex of 3 month-old transgenic mice and involved Glu, NAA, myo-inositol, creatine, phosphocholine, and γ-aminobutyric acid (only in the hippocampus) whose concentrations decreased. A metabolic disruption characterized by an increase in the hippocampal concentrations of Glu, creatine, and taurine was detected in 6 month-old transgenic mice. At this time point, the chemical profile of the cerebellum was slightly affected. At 11 months, all the brain regions analyzed (except the frontal cortex) were metabolically altered, with mainly a marked increase in the formation of the neuroprotective metabolites creatine and taurine. Our findings demonstrate that metabolic modifications occur long before the onset of behavioral impairment.