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plant metabolomics

Kazuyoshi Kitazaki, Atsushi Fukushima, Ryo Nakabayashi, Yozo Okazaki, Makoto Kobayashi, Tetsuya Mori, Tomoko Nishizawa, Sebastian Reyes-Chin-Wo, Richard W Michelmore, Kazuki Saito, Kazuhiro Shoji, Miyako Kusano
Light-emitting diodes (LEDs) are an artificial light source used in closed-type plant factories and provide a promising solution for a year-round supply of green leafy vegetables, such as lettuce (Lactuca sativa L.). Obtaining high-quality seedlings using controlled irradiation from LEDs is critical, as the seedling health affects the growth and yield of leaf lettuce after transplantation. Because key molecular pathways underlying plant responses to a specific light quality and intensity remain poorly characterised, we used a multi-omics-based approach to evaluate the metabolic and transcriptional reprogramming of leaf lettuce seedlings grown under narrow-band LED lighting...
May 21, 2018: Scientific Reports
Michael Scheunemann, Siobhan M Brady, Zoran Nikoloski
Plant organs consist of multiple cell types that do not operate in isolation, but communicate with each other to maintain proper functions. Here, we extract models specific to three developmental stages of eight root cell types or tissue layers in Arabidopsis thaliana based on a state-of-the-art constraint-based modeling approach with all publicly available transcriptomics and metabolomics data from this system to date. We integrate these models into a multi-cell root model which we investigate with respect to network structure, distribution of fluxes, and concordance to transcriptomics and proteomics data...
May 21, 2018: Scientific Reports
Martina Lardi, Gabriella Pessi
Biological nitrogen fixation gives legumes a pronounced growth advantage in nitrogen-deprived soils and is of considerable ecological and economic interest. In exchange for reduced atmospheric nitrogen, typically given to the plant in the form of amides or ureides, the legume provides nitrogen-fixing rhizobia with nutrients and highly specialised root structures called nodules. To elucidate the molecular basis underlying physiological adaptations on a genome-wide scale, functional genomics approaches, such as transcriptomics, proteomics, and metabolomics, have been used...
May 18, 2018: High-throughput
Vishakha Pandey, Manoj Singh, Dinesh Pandey, Anil Kumar
Tilletia indica incites Karnal bunt (KB) disease in wheat. To date, no KB resistant wheat cultivar could be developed due to non-availability of potential biomarkers related to pathogenicity/virulence for screening of resistant wheat genotypes. The present study was carried out to compare the proteomes of T. indica highly (TiK) and low (TiP) virulent isolates. Twenty one protein spots consistently observed as up-regulated/differential in the TiK proteome were selected for identification by MALDI-TOF/TOF. Identified sequences showed homology with fungal proteins playing essential role in plant infection and pathogen survival, including stress response, adhesion, fungal penetration, invasion, colonization, degradation of host cell wall, signal transduction pathway...
May 18, 2018: Scientific Reports
Alexandre Foito, Derek Stewart
Plants and crops contain a staggering diversity of compounds, many of which have pharmacological activity towards a variety of diseases. These properties have been exploited by traditional and modern medicine providing important sources of healthcare to this day. The contribution of natural products (such as plant-derived) to the modern pharmacopeia is indeed significant; however, the process of identifying novel bioactive compounds from biological sources has been a central challenge in the discovery of natural products...
May 15, 2018: Current Pharmaceutical Design
Lisa Fürtauer, Jakob Weiszmann, Wolfram Weckwerth, Thomas Nägele
The experimental analysis of a plant metabolome typically results in a comprehensive and multidimensional data set. To interpret metabolomics data in the context of biochemical regulation and environmental fluctuation, various approaches of mathematical modeling have been developed and have proven useful. In this chapter, a general introduction to mathematical modeling is presented and discussed in context of plant metabolism. A particular focus is laid on the suitability of mathematical approaches to functionally integrate plant metabolomics data in a metabolic network and combine it with other biochemical or physiological parameters...
2018: Methods in Molecular Biology
Francisco de Abreu E Lima, Lydia Leifels, Zoran Nikoloski
Bridging metabolomics with plant phenotypic responses is challenging. Multivariate analyses account for the existing dependencies among metabolites, and regression models in particular capture such dependencies in search for association with a given trait. However, special care should be undertaken with metabolomics data. Here we propose a modeling workflow that considers all caveats imposed by such large data sets.
2018: Methods in Molecular Biology
Isabel Orf
As part of a systems biology approach, metabolomics often aim at broadening our understanding of the functionality of biological systems as a whole. Observations from stand-alone experiments may reveal interesting changes in metabolites of a specific pathway or metabolite class. However, bringing these observations into context with more general biological processes requires the integration and comparison of different datasets. This chapter aims at introducing and explaining methods of comparative data analysis for plant metabolomics using the statistical software framework R...
2018: Methods in Molecular Biology
Nadine Töpfer, Samuel M D Seaver, Asaph Aharoni
In the last decade, plant genome-scale modeling has developed rapidly and modeling efforts have advanced from representing metabolic behavior of plant heterotrophic cell suspensions to studying the complex interplay of cell types, tissues, and organs. A crucial driving force for such developments is the availability and integration of "omics" data (e.g., transcriptomics, proteomics, and metabolomics) which enable the reconstruction, extraction, and application of context-specific metabolic networks...
2018: Methods in Molecular Biology
Carsten Jaeger, Jan Lisec
Raw data from metabolomics experiments are initially subjected to peak identification and signal deconvolution to generate raw data matrices m × n, where m are samples and n are metabolites. We describe here simple statistical procedures on such multivariate data matrices, all provided as functions in the programming environment R, useful to normalize data, detect biomarkers, and perform sample classification.
2018: Methods in Molecular Biology
Keiko Masuda, Yasmine Abouleila, Ahmed Ali, Toshio Yanagida, Tsutomu Masujima
Live single-cell mass spectrometry (LSC-MS) allows for the detection of hundreds to thousands of metabolite peaks acquired from a single plant cell within a few minutes. Plant cells are first observed under a stereomicroscope, a cell of interest is chosen, and then sampled using a metal-coated glass microcapillary for subsequent analysis. A few microliters of ionization solvent is then added to the rear end of the capillary followed by the introduction of the capillary's content directly into the mass spectrometer...
2018: Methods in Molecular Biology
Desalegn W Etalo, Carmen Díez-Simón, Ric C H de Vos, Robert D Hall
There is increasing demand to bring the level of metabolomics analyses down to the tissue or cell level. Significant progress has been made involving the use of in situ metabolomics imaging techniques where no tissue collection or extraction is needed prior to analysis. In this chapter we describe a relatively new method which is simple and easy to use. No ectopic matrix or vacuum is required, and analyses are performed with living plant materials directly from (or even still attached to) the plant. Although relatively straightforward, there are still a few caveats as regards this method which are described at the end of the chapter...
2018: Methods in Molecular Biology
Berin A Boughton, Dinaiz Thinagaran
Mass spectrometry imaging (MSI) is a developing technique to measure the spatiotemporal distribution of many biomolecules in tissues. Over the preceding decade MSI has been adopted by plant biologists and applied in a broad range of areas including: primary metabolism, natural products, plant defense, plant responses to abiotic and biotic stress, plant lipids, and the developing field of spatial metabolomics. This methods chapter covers preparation of plant tissues for matrix-assisted laser desorption ionization (MALDI)-MSI, including sample embedding and freezing, sectioning, mounting, and matrix deposition using both sublimation and spray deposition prior to MSI analysis...
2018: Methods in Molecular Biology
Nir Shahaf, Asaph Aharoni, Ilana Rogachev
Databases containing mass spectrometry (MS) spectral data (i.e., MS reference libraries) are currently the most reliable and widely accepted approach to annotate unknown features in MS-based metabolomics. While for gas chromatography (GC)-MS data, a strategy for collecting, storing, and comparing to raw data has been established, this is not the case for liquid chromatography (LC)-MS data. Here, we present our approach for high-throughput data collection and automated MS reference library generation, as applied recently in the WEIZMASS library of plant metabolites...
2018: Methods in Molecular Biology
Takafumi Shimizu, Mutsumi Watanabe, Alisdair R Fernie, Takayuki Tohge
Recent technological developments and methodological advances of both liquid chromatography (LC) and mass spectrometry (MS) have allowed LC-MS-based plant metabolomics to become a common tool for investigating quantity, quality, and chemical diversity of plant metabolites. Targeted LC-MS metabolite analysis focuses on the detection and quantitation of the researcher's target metabolites. Whilst the word "target analysis" has been used for the analytical measurement to obtain the absolute concentrations evaluated by authentic and/or stable-isotope-labeled standards, over time the phrase came to be also used in a broad sense for the measurement of annotatable metabolites by structural information obtained from the combination of different strategies such as MS/MS analysis, reference extracts, mutant analysis and database search...
2018: Methods in Molecular Biology
Camille Bénard, Sébastien Acket, Yannick Rossez, Olivier Fernandez, Thierry Berton, Yves Gibon, Cécile Cabasson
The way plants are grown and samples are harvested, prepared, and extracted has a profound impact on the output of a metabolomics experiment. In this chapter, we detail the experimental procedures from plant cultivation to extract preparation, in order to avoid difficulties that could result in contamination or undesired changes of the analytes. Two plant organs are mentioned as examples: tomato fruits (Solanum lycopersicum) and flax seeds (Linum usitatissimum). Extractions designed for the untargeted analysis of semipolar compounds by liquid chromatography-mass spectrometry (LC-MS) and targeted analysis of fatty acids by gas chromatography-mass spectrometry (GC-MS) or gas chromatography with flame ionization detector (GC-FID) are described...
2018: Methods in Molecular Biology
Leonardo Perez de Souza, Alisdair R Fernie, Takayuki Tohge
Stable-isotope-labeling experiments have become a frequently used tool to investigate different metabolic systems. They have been recently applied to several comprehensive studies in plant metabolomics providing interesting insights into metabolic dynamics and regulation. However, the complexity of mass spectrometry data originating from such experiments is rarely fully explored. Data analysis often considers metabolites in their entirety which obscures important information at the atomic level. Recently, the use of mass spectrometry fragmentation for obtaining positional-labeling information was described for a few specific metabolites...
2018: Methods in Molecular Biology
Valéria F Lima, Leonardo Perez de Souza, Thomas C R Williams, Alisdair R Fernie, Danilo M Daloso
Stable-isotope labeling analysis has been used to discover new metabolic pathways and their key regulatory points in a wide range of organisms. Given the complexity of the plant metabolic network, this analysis provides information complementary to that obtained from metabolite profiling that can be used to understand how plants cope with adverse conditions, and how metabolism varies between different cells, tissues, and organs. Here we describe the experimental procedures from sample harvesting and extraction to mass spectral analysis and interpretation that allow the researcher to perform 13 C-labeling experiments...
2018: Methods in Molecular Biology
Saleh Alseekh, Si Wu, Yariv Brotman, Alisdair R Fernie
Recent methodological advances in both liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) have facilitated the profiling highly complex mixtures of primary and secondary metabolites in order to investigate a diverse range of biological questions. These techniques usually face a large number of potential sources of technical and biological variation. In this chapter we describe guidelines and normalization procedures to reduce the analytical variation, which are essential for the high-throughput evaluation of metabolic variance used in broad genetic populations which commonly entail the evaluation of hundreds or thousands of samples...
2018: Methods in Molecular Biology
Ana Margarida Rodrigues, Carla António
Studies of the plant metabolome include the analysis of a wide range of chemical species with very diverse physicochemical properties requiring powerful analytical tools for the separation, characterization, and quantification of this vast compound diversity present in plant matrices. In quantitative metabolomics studies, major efforts are put into optimizing sample extraction and separation as well as instrument conditions to measure specific plant metabolites. Here, challenges in the use of mass spectrometry (MS) as a quantitative tool in plant metabolomics experiments are discussed, and an overview of the most critical steps in the development and validation of MS-based analytical methods is presented...
2018: Methods in Molecular Biology
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