Acclimatisation of guard cell metabolism to long-term salinity.

Stomatal movements are enabled by changes in guard cell turgor facilitated via transient accumulation of inorganic and organic ions imported from the apoplast or biosynthesized within guard cells. Under salinity, excess salt ions accumulate within plant tissues resulting in osmotic and ionic stress. To elucidate whether (a) Na+ and Cl- concentrations increase in guard cells in response to long-term NaCl exposure and how (b) guard cell metabolism acclimates to the anticipated stress, we profiled the ions and primary metabolites of leaves, the apoplast and isolated guard cells at darkness and during light, that is, closed and fully opened stomata. In contrast to leaves, the primary metabolism of guard cell preparations remained predominantly unaffected by increased salt ion concentrations. Orchestrated reductions of stomatal aperture and guard cell osmolyte synthesis were found, but unlike in leaves, no increases of stress responsive metabolites or compatible solutes occurred. Diverging regulation of guard cell metabolism might be a prerequisite to facilitate the constant adjustment of turgor that affects aperture. Moreover, the photoperiod-dependent sucrose accumulation in the apoplast and guard cells changed to a permanently replete condition under NaCl, indicating that stress-related photosynthate accumulation in leaves contributes to the permanent closing response of stomata under stress.

Systems-wide analysis of acclimation responses to long-term heat stress and recovery in the photosynthetic model organism Chlamydomonas reinhardtii.

We applied a top-down systems biology approach to understand how Chlamydomonas reinhardtii acclimates to long-term heat stress (HS) and recovers from it. For this, we shifted cells from 25 to 42°C for 24 h and back to 25°C for ≥8 h and monitored abundances of 1856 proteins/protein groups, 99 polar and 185 lipophilic metabolites, and cytological and photosynthesis parameters. Our data indicate that acclimation of Chlamydomonas to long-term HS consists of a temporally ordered, orchestrated implementation of response elements at various system levels. These comprise (1) cell cycle arrest; (2) catabolism of larger molecules to generate compounds with roles in stress protection; (3) accumulation of molecular chaperones to restore protein homeostasis together with compatible solutes; (4) redirection of photosynthetic energy and reducing power from the Calvin cycle to the de novo synthesis of saturated fatty acids to replace polyunsaturated ones in membrane lipids, which are deposited in lipid bodies; and (5) when sinks for photosynthetic energy and reducing power are depleted, resumption of Calvin cycle activity associated with increased photorespiration, accumulation of reactive oxygen species scavengers, and throttling of linear electron flow by antenna uncoupling. During recovery from HS, cells appear to focus on processes allowing rapid resumption of growth rather than restoring pre-HS conditions.

Convergence and molecular evolution of floral fragrance after independent transitions to self-fertilization.

Studying the independent evolution of similar traits provides valuable insights into the ecological and genetic factors driving phenotypic evolution.1 The transition from outcrossing to self-fertilization is common in plant evolution2 and is often associated with a reduction in floral attractive features such as display size, chemical signals, and pollinator rewards.3 These changes are believed to result from the reallocation of the resources used for building attractive flowers, as the need to attract pollinators decreases.2,3 We investigated the similarities in the evolution of flower fragrance following independent transitions to self-fertilization in Capsella.4,5,6,7,8,9 We identified several compounds that exhibited similar changes in different selfer lineages, such that the flower scent composition reflects mating systems rather than evolutionary history within this genus. We further demonstrate that the repeated loss of ß-ocimene emission, one of the compounds most strongly affected by these transitions, was caused by mutations in different genes. In one of the Capsella selfing lineages, the loss of its emission was associated with a mutation altering subcellular localization of the ortholog of TERPENE SYNTHASE 2. This mutation appears to have been fixed early after the transition to selfing through the capture of variants segregating in the ancestral outcrossing population. The large extent of convergence in the independent evolution of flower scent, together with the evolutionary history and molecular consequences of a causal mutation, suggests that the emission of specific volatiles evolved as a response to changes in ecological pressures rather than resource limitation.

Metabolic profiling of Arabidopsis thaliana epidermal cells.

Metabolic phenotyping at cellular resolution may be considered one of the challenges in current plant physiology. A method is described which enables the cell type-specific metabolic analysis of epidermal cell types in Arabidopsis thaliana pavement, basal, and trichome cells. To achieve the required high spatial resolution, single cell sampling using microcapillaries was combined with routine gas chromatography-time of flight-mass spectrometry (GC-TOF-MS) based metabolite profiling. The identification and relative quantification of 117 mostly primary metabolites has been demonstrated. The majority, namely 90 compounds, were accessible without analytical background correction. Analyses were performed using cell type-specific pools of 200 microsampled individual cells. Moreover, among these identified metabolites, 38 exhibited differential pool sizes in trichomes, basal or pavement cells. The application of an independent component analysis confirmed the cell type-specific metabolic phenotypes. Significant pool size changes between individual cells were detectable within several classes of metabolites, namely amino acids, fatty acids and alcohols, alkanes, lipids, N-compounds, organic acids and polyhydroxy acids, polyols, sugars, sugar conjugates and phenylpropanoids. It is demonstrated here that the combination of microsampling and GC-MS based metabolite profiling provides a method to investigate the cellular metabolism of fully differentiated plant cell types in vivo.

Multiplexed Profiling and Data Processing Methods to Identify Temperature-Regulated Primary Metabolites Using Gas Chromatography Coupled to Mass Spectrometry.

This book chapter describes the analytical procedures required for the profiling of a metabolite fraction enriched for primary metabolites. The profiling is based on routine gas chromatography coupled to mass spectrometry (GC-MS). The generic profiling method is adapted to plant material, specifically to the analysis of plant material that was exposed to temperature stress. The method can be combined with stable isotope labeling and tracing experiments and is equally applicable to preparations of plant material and microbial photosynthetic organisms. The described methods are modular and can be multiplexed, that is, the same sample or a paired identical backup sample can be analyzed sequentially by more than one of the described procedures. The modules include rapid sampling and metabolic inactivation protocols for samples in a wide weight range, sample extraction procedures, chemical derivatization steps that are required to make the metabolite fraction amenable to gas chromatographic analysis, routine GC-MS methods, and procedures of data processing and data mining. A basic and extendable set of standardizations for metabolite recovery and retention index alignment of the resulting GC-MS chromatograms is included. The methods have two applications: (1) The rapid screening for changes of relative metabolite pools sizes under temperature stress and (2) the verification by exact quantification using GC-MS protocols that are extended by internal and external standardization.

Discovery of food identity markers by metabolomics and machine learning technology.

Verification of food authenticity establishes consumer trust in food ingredients and components of processed food. Next to genetic or protein markers, chemicals are unique identifiers of food components. Non-targeted metabolomics is ideally suited to screen food markers when coupled to efficient data analysis. This study explored feasibility of random forest (RF) machine learning, specifically its inherent feature extraction for non-targeted metabolic marker discovery. The distinction of chia, linseed, and sesame that have gained attention as "superfoods" served as test case. Chemical fractions of non-processed seeds and of wheat cookies with seed ingredients were profiled. RF technology classified original seeds unambiguously but appeared overdesigned for material with unique secondary metabolites, like sesamol or rosmarinic acid in the Lamiaceae, chia. Most unique metabolites were diluted or lost during cookie production but RF technology classified the presence of the seed ingredients in cookies with 6.7% overall error and revealed food processing markers, like 4-hydroxybenzaldehyde for chia and succinic acid monomethylester for linseed additions. RF based feature extraction was adequate for difficult classifications but marker selection should not be without human supervision. Combination with alternative data analysis technologies is advised and further testing of a wide range of seeds and food processing methods.

Acquisition of Volatile Compounds by Gas Chromatography-Mass Spectrometry (GC-MS).

Plants synthesize and emit a large range of volatile organic compounds (VOCs) that play important roles in their interactions with the environment, from attracting pollinators and seed dispersers to protectants such as repellants and pathogen inhibitors. As such, the development of techniques for headspace collection of volatiles in combination with gas chromatography-mass spectrometry (GC-MS) has an important impact on our understanding of the biosynthesis of plant VOCs. Furthermore, knowledge of the plant VOCs can be valuable in relation to plant breeding for improving fruit flavor or enhancing resistance to insects or pathogens. This chapter describes a reliable method for extracting volatile compounds by headspace solid-phase microextraction (HS-SPME), and separate and detect them by GC-MS.

Rationales and approaches for studying metabolism in eukaryotic microalgae.

The generation of efficient production strains is essential for the use of eukaryotic microalgae for biofuel production. Systems biology approaches including metabolite profiling on promising microalgal strains, will provide a better understanding of their metabolic networks, which is crucial for metabolic engineering efforts. Chlamydomonas reinhardtii represents a suited model system for this purpose. We give an overview to genetically amenable microalgal strains with the potential for biofuel production and provide a critical review of currently used protocols for metabolite profiling on Chlamydomonas. We provide our own experimental data to underpin the validity of the conclusions drawn.

Profiling methods to identify cold-regulated primary metabolites using gas chromatography coupled to mass spectrometry.

This book chapter describes the analytical procedures required for the profiling of a metabolite fraction enriched for primary metabolites. The profiling is based on routine gas chromatography coupled to mass spectrometry (GC-MS). The generic profiling method is adapted to plant material, specifically to the analysis of single leaves from plants that were exposed to temperature stress experiments. The described method is modular. The modules include a rapid sampling and metabolic inactivation protocol for samples in a wide size range, a sample extraction procedure, a chemical derivatization step that is required to make the metabolite fraction amenable to gas chromatographic analysis, a routine GC-MS method, and finally the procedures of data processing and data mining. A basic and extendable set of standardizations for metabolite recovery and retention index alignment of the resulting GC-MS chromatograms is included. The method has two applications: (1) the rapid screening for changes of relative metabolite pools sizes under temperature stress and (2) the verification of cold-regulated metabolites by exact quantification using a GC-MS protocol with extended internal and external standardization.

Downregulation of cinnamoyl-coenzyme A reductase in poplar: multiple-level phenotyping reveals effects on cell wall polymer metabolism and structure.

Cinnamoyl-CoA reductase (CCR) catalyzes the penultimate step in monolignol biosynthesis. We show that downregulation of CCR in transgenic poplar (Populus tremula x Populus alba) was associated with up to 50% reduced lignin content and an orange-brown, often patchy, coloration of the outer xylem. Thioacidolysis, nuclear magnetic resonance (NMR), immunocytochemistry of lignin epitopes, and oligolignol profiling indicated that lignin was relatively more reduced in syringyl than in guaiacyl units. The cohesion of the walls was affected, particularly at sites that are generally richer in syringyl units in wild-type poplar. Ferulic acid was incorporated into the lignin via ether bonds, as evidenced independently by thioacidolysis and by NMR. A synthetic lignin incorporating ferulic acid had a red-brown coloration, suggesting that the xylem coloration was due to the presence of ferulic acid during lignification. Elevated ferulic acid levels were also observed in the form of esters. Transcript and metabolite profiling were used as comprehensive phenotyping tools to investigate how CCR downregulation impacted metabolism and the biosynthesis of other cell wall polymers. Both methods suggested reduced biosynthesis and increased breakdown or remodeling of noncellulosic cell wall polymers, which was further supported by Fourier transform infrared spectroscopy and wet chemistry analysis. The reduced levels of lignin and hemicellulose were associated with an increased proportion of cellulose. Furthermore, the transcript and metabolite profiling data pointed toward a stress response induced by the altered cell wall structure. Finally, chemical pulping of wood derived from 5-year-old, field-grown transgenic lines revealed improved pulping characteristics, but growth was affected in all transgenic lines tested.