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

Spatio-Temporal Study of Galactolipid Biosynthesis in Duckweed Using Mass Spectrometry Imaging and in vivo Isotope Labeling

Isotope labeling coupled with mass spectrometry imaging (MSI) presents a potent strategy for elucidating the dynamics of metabolism at cellular resolution, yet its application to plant systems is scarce. It has the potential to reveal the spatio-temporal dynamics of lipid biosynthesis during plant development. In this study, we explore its application to galactolipid biosynthesis of an aquatic plant, Lemna minor, with D2O labeling. Specifically, matrix-assisted laser desorption/ionization-MSI data of two major galactolipids in L. minor, monogalactosyldiacylglycerol and digalactosyldiacylglycerol, were studied after growing in 50% D2O media over a 15-day time period. When they were partially labeled after 5 d, three distinct binomial isotopologue distributions were observed corresponding to the labeling of partial structural moieties: galactose only, galactose and a fatty acyl chain and the entire molecule. The temporal change in the relative abundance of these distributions follows the expected linear pathway of galactolipid biosynthesis. Notably, their mass spectrometry images revealed the localization of each isotopologue group to the old parent frond, the intermediate tissues and the newly grown daughter fronds. Besides, two additional labeling experiments, (i) 13CO2 labeling and (ii) backward labeling of completely 50% D2O-labeled L. minor in H2O media, confirm the observations in forward labeling. Furthermore, these experiments unveiled hidden isotopologue distributions indicative of membrane lipid restructuring. This study suggests the potential of isotope labeling using MSI to provide spatio-temporal details in lipid biosynthesis in plant development.

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.

Untargeted Plant Metabolomics: Evaluation of Lyophilization as a Sample Preparation Technique

Lyophilization is a common method used for stabilizing biological samples prior to storage or to concentrate extracts. However, it is possible that this process may alter the metabolic composition or lead to the loss of metabolites. In this study, the performance of lyophilization is investigated in the example of wheat roots. To this end, native and ¹³C-labelled, fresh or already lyophilized root samples, and (diluted) extracts with dilution factors up to 32 and authentic reference standards were investigated. All samples were analyzed using RP-LC-HRMS. Results show that using lyophilization for the stabilization of plant material altered the metabolic sample composition. Overall, 7% of all wheat metabolites detected in non-lyophilized samples were not detected in dried samples anymore, and up to 43% of the remaining metabolites exhibited significantly increased or decreased abundances. With respect to extract concentration, less than 5% of the expected metabolites were completely lost by lyophilization and the recovery rates of the remaining metabolites were slightly reduced with increasing concentration factors to an average of 85% at an enrichment factor of 32. Compound annotation did not indicate specific classes of wheat metabolites to be affected.

Measurement of True Indispensable Amino Acid Digestibility by the Dual Isotope Tracer Technique: A Methodological Review

The digestible indispensable amino acid score uses ileal digestibility of each indispensable amino acid (IAA) of a dietary protein to calculate its protein quality. However, true ileal digestibility, which is the exclusive sum of digestion and absorption of a dietary protein up to the terminal ileum, is difficult to measure in humans. It is traditionally measured using invasive oro-ileal balance methods but can be confounded by endogenous secreted protein in the intestinal lumen, although the use of intrinsically labeled protein corrects for this. A recent, minimally invasive dual isotope tracer technique is now available to measure true IAA digestibility of dietary protein sources. This method involves simultaneous ingestion of 2 intrinsically but differently (stable) isotopically labeled proteins, a (²H or ¹⁵N-labeled) test protein and (¹³C-labeled) reference protein whose true IAA digestibility is known. Using a plateau-feeding protocol, the true IAA digestibility is determined by comparing the steady state ratio of blood to meal test protein IAA enrichment to the similar reference protein IAA ratio. The use of intrinsically labeled protein also distinguishes between IAA of endogenous and dietary origin. The collection of blood samples makes this method minimally invasive. As the α-¹⁵N and α-²H atoms of AAs of the intrinsically labeled protein are prone to label loss because of transamination, underestimation of digestibility, appropriate correction factors need to be employed when using ¹⁵N or ²H labeled test protein. The true IAA digestibility values of highly digestible animal protein by the dual isotope tracer technique are comparable to that measured by direct oro-ileal balance measurements, but no data are yet available for proteins with lower digestibility. A major advantage is that the minimally invasive method allows for true IAA digestibility measurement in humans across different age groups and physiological conditions.

Heterogeneous multimeric metabolite ion species observed in LC-MS based metabolomics data sets

Covalent or non-covalent heterogeneous multimerization of molecules associated with extracts from biological samples analyzed via LC-MS are quite difficult to recognize/annotate and therefore the prevalence of multimerization remains largely unknown. In this study, we utilized 13C labeled and unlabeled Pichia pastoris extracts to recognize heterogeneous multimers. More specifically, between 0.8% and 1.5% of the biologically-derived features detected in our experiments were confirmed to be heteromers, about half of which we could successfully annotate with monomeric partners. Interestingly, we found specific chemical classes such as nucleotides to disproportionately contribute to heteroadducts. Furthermore, we compiled these compounds into the first MS/MS library that included data from heteromultimers to provide a starting point for other labs to improve the annotation of such ions in other metabolomics data sets. Then, the detected heteromers were also searched in publicly accessible LC-MS datasets available in Metabolights, Metabolomics WB and GNPS/MassIVE to demonstrate that these newly annotated ions are also relevant to other public datasets. Furthermore, in additional datasets (Triticum aestivum, Fusarium graminearum, and Trichoderma reesei) our developed workflow also detected 0.5%-4.9% of metabolite features to originate from heterodimers, demonstrating heteroadducts to be present in metabolomics studies at a low percentage.

Design and fabrication of an improved dynamic flow cuvette for 13CO2 labeling in Arabidopsis plants

BACKGROUND

Stable isotope labeling is a non-invasive, sensitive means of monitoring metabolic flux in plants. The most physiologically meaningful information is obtained from experiments that take advantage of the natural photosynthetic carbon assimilation pathway to introduce a traceable marker with minimal effects on the physiology of the organism. The fundamental substrate in isotopic labeling experiments is ¹³CO₂, which can reveal the earliest events in carbon assimilation and realistically portray downstream metabolism when administered under conditions suitable for making kinetic inferences. Efforts to improve the accuracy and resolution of whole plant labeling techniques have focused on improvements in environmental control, air flow characteristics, and harvesting methods.

RESULTS

Here we present a dynamic flow cuvette designed for single Arabidopsis thaliana labeling experiments. We have also verified its suitability for labeling Nicotiana benthamiana and essential oils in Pelargonium graveolens. Complete plans for fabrication of this device are included. The design includes three important innovations. First, uniform, circular air flow over the rosette surface is accomplished by a fan and deflector that creates a mini-cyclone effect within the chamber interior. Second, a network of circulating canals connected to a water bath provides temperature control to within ± 0.1 ºC under variable irradiance, humidity, and air flow conditions. When photosynthetically active radiation (PAR) was varied over a range of 1000 μEinsteins m^-2 s^-1 with no adjustment to the external temperature control system, the abaxial leaf temperature changed by < 3 ºC/1000 PAR. Third, the device is fully compatible with liquid nitrogen quenching of metabolic activity without perturbation of the light environment. For short labeling experiments (< 10 s), the most critical variable is the half-life (t_1/2) of the atmosphere within the chamber, which determines the maximum resolution of the labeling system. Using an infrared gas analyzer, we monitored the atmospheric half-life during the transition from ¹²CO₂ to ¹³CO₂ air at different flow rates and determined that 3.5 L min^-1 is the optimal flow rate to initiate labeling (t_1/2 ~ 5 s). Under these conditions, we observed linear incorporation of ¹³C into triose phosphate with labeling times as short as 5 s.

CONCLUSIONS

Advances in our ability to conduct short term labeling experiments are critical to understanding of the rates and control of the earliest steps in plant metabolism. Precise kinetic measurements in whole plants using ¹³CO₂ inform metabolic models and reveal control points that can be exploited in agricultural or biotechnological contexts. The dynamic labeling cuvette presented here is suitable for studying early events in carbon assimilation and provides high resolution kinetic data for studies of metabolism in intact plants under physiologically realistic scenarios.

The TOR kinase pathway is relevant for nitrogen signaling and antagonism of the mycoparasite Trichoderma atroviride

Trichoderma atroviride (Ascomycota, Sordariomycetes) is a well-known mycoparasite applied for protecting plants against fungal pathogens. Its mycoparasitic activity involves processes shared with plant and human pathogenic fungi such as the production of cell wall degrading enzymes and secondary metabolites and is tightly regulated by environmental cues. In eukaryotes, the conserved Target of Rapamycin (TOR) kinase serves as a central regulator of cellular growth in response to nutrient availability. Here we describe how alteration of the activity of TOR1, the single and essential TOR kinase of T. atroviride, by treatment with chemical TOR inhibitors or by genetic manipulation of selected TOR pathway components affected various cellular functions. Loss of TSC1 and TSC2, that are negative regulators of TOR complex 1 (TORC1) in mammalian cells, resulted in altered nitrogen source-dependent growth of T. atroviride, reduced mycoparasitic overgrowth and, in the case of Δtsc1, a diminished production of numerous secondary metabolites. Deletion of the gene encoding the GTPase RHE2, whose mammalian orthologue activates mTORC1, led to rapamycin hypersensitivity and altered secondary metabolism, but had an only minor effect on vegetative growth and mycoparasitic overgrowth. The latter also applied to mutants missing the npr1-1 gene that encodes a fungus-specific kinase known as TOR target in yeast. Genome-wide transcriptome analysis confirmed TOR1 as a regulatory hub that governs T. atroviride metabolism and processes associated to ribosome biogenesis, gene expression and translation. In addition, mycoparasitism-relevant genes encoding terpenoid and polyketide synthases, peptidases, glycoside hydrolases, small secreted cysteine-rich proteins, and G protein coupled receptors emerged as TOR1 targets. Our results provide the first in-depth insights into TOR signaling in a fungal mycoparasite and emphasize its importance in the regulation of processes that critically contribute to the antagonistic activity of T. atroviride.

Unravelling Plant Responses to Stress-The Importance of Targeted and Untargeted Metabolomics

Climate change and an increasing population, present a massive global challenge with respect to environmentally sustainable nutritious food production. Crop yield enhancements, through breeding, are decreasing, whilst agricultural intensification is constrained by emerging, re-emerging, and endemic pests and pathogens, accounting for ~30% of global crop losses, as well as mounting abiotic stress pressures, due to climate change. Metabolomics approaches have previously contributed to our knowledge within the fields of molecular plant pathology and plant-insect interactions. However, these remain incredibly challenging targets, due to the vast diversity in metabolite volatility and polarity, heterogeneous mixtures of pathogen and plant cells, as well as rapid rates of metabolite turn-over. Unravelling the systematic biochemical responses of plants to various individual and combined stresses, involves monitoring signaling compounds, secondary messengers, phytohormones, and defensive and protective chemicals. This demands both targeted and untargeted metabolomics approaches, as well as a range of enzymatic assays, protein assays, and proteomic and transcriptomic technologies. In this review, we focus upon the technical and biological challenges of measuring the metabolome associated with plant stress. We illustrate the challenges, with relevant examples from bacterial and fungal molecular pathologies, plant-insect interactions, and abiotic and combined stress in the environment. We also discuss future prospects from both the perspective of key innovative metabolomic technologies and their deployment in breeding for stress resistance.

Bringing New Methods to the Seed Proteomics Platform: Challenges and Perspectives

For centuries, crop plants have represented the basis of the daily human diet. Among them, cereals and legumes, accumulating oils, proteins, and carbohydrates in their seeds, distinctly dominate modern agriculture, thus play an essential role in food industry and fuel production. Therefore, seeds of crop plants are intensively studied by food chemists, biologists, biochemists, and nutritional physiologists. Accordingly, seed development and germination as well as age- and stress-related alterations in seed vigor, longevity, nutritional value, and safety can be addressed by a broad panel of analytical, biochemical, and physiological methods. Currently, functional genomics is one of the most powerful tools, giving direct access to characteristic metabolic changes accompanying plant development, senescence, and response to biotic or abiotic stress. Among individual post-genomic methodological platforms, proteomics represents one of the most effective ones, giving access to cellular metabolism at the level of proteins. During the recent decades, multiple methodological advances were introduced in different branches of life science, although only some of them were established in seed proteomics so far. Therefore, here we discuss main methodological approaches already employed in seed proteomics, as well as those still waiting for implementation in this field of plant research, with a special emphasis on sample preparation, data acquisition, processing, and post-processing. Thereby, the overall goal of this review is to bring new methodologies emerging in different areas of proteomics research (clinical, food, ecological, microbial, and plant proteomics) to the broad society of seed biologists.

Enhanced Metabolome Coverage and Evaluation of Matrix Effects by the Use of Experimental-Condition-Matched 13C-Labeled Biological Samples in Isotope-Assisted LC-HRMS Metabolomics

Stable isotope-assisted approaches can improve untargeted liquid chromatography-high resolution mass spectrometry (LC-HRMS) metabolomics studies. Here, we demonstrate at the example of chemically stressed wheat that metabolome-wide internal standardization by globally ¹³C-labeled metabolite extract (GLMe-IS) of experimental-condition-matched biological samples can help to improve the detection of treatment-relevant metabolites and can aid in the post-acquisition assessment of putative matrix effects in samples obtained upon different treatments. For this, native extracts of toxin- and mock-treated (control) wheat ears were standardized by the addition of uniformly ¹³C-labeled wheat ear extracts that were cultivated under similar experimental conditions (toxin-treatment and control) and measured with LC-HRMS. The results show that 996 wheat-derived metabolites were detected with the non-condition-matched ¹³C-labeled metabolite extract, while another 68 were only covered by the experimental-condition-matched GLMe-IS. Additional testing is performed with the assumption that GLMe-IS enables compensation for matrix effects. Although on average no severe matrix differences between both experimental conditions were found, individual metabolites may be affected as is demonstrated by wrong decisions with respect to the classification of significantly altered metabolites. When GLMe-IS was applied to compensate for matrix effects, 272 metabolites showed significantly altered levels between treated and control samples, 42 of which would not have been classified as such without GLMe-IS.