Shifts in plant foliar and floral metabolomes in response to the suppression of the associated microbiota.

PubMed

Gargallo-Garriga, Albert; Sardans, Jordi; Pérez-Trujillo, Míriam; Guenther, Alex; Llusià, Joan; Rico, Laura; Terradas, Jaume; Farré-Armengol, Gerard; Filella, Iolanda; Parella, Teodor; Peñuelas, Josep

2016-04-06

The phyllospheric microbiota is assumed to play a key role in the metabolism of host plants. Its role in determining the epiphytic and internal plant metabolome, however, remains to be investigated. We analyzed the Liquid Chromatography-Mass Spectrometry (LC-MS) profiles of the epiphytic and internal metabolomes of the leaves and flowers of Sambucus nigra with and without external antibiotic treatment application. The epiphytic metabolism showed a degree of complexity similar to that of the plant organs. The suppression of microbial communities by topical applications of antibiotics had a greater impact on the epiphytic metabolome than on the internal metabolomes of the plant organs, although even the latter changed significantly both in leaves and flowers. The application of antibiotics decreased the concentration of lactate in both epiphytic and organ metabolomes, and the concentrations of citraconic acid, acetyl-CoA, isoleucine, and several secondary compounds such as terpenes and phenols in the epiphytic extracts. The metabolite pyrogallol appeared in the floral epiphytic community only after the treatment. The concentrations of the amino acid precursors of the ketoglutarate-synthesis pathway tended to decrease in the leaves and to increase in the foliar epiphytic extracts. These results suggest that anaerobic and/or facultative anaerobic bacteria were present in high numbers in the phyllosphere and in the apoplasts of S. nigra. The results also show that microbial communities play a significant role in the metabolomes of plant organs and could have more complex and frequent mutualistic, saprophytic, and/or parasitic relationships with internal plant metabolism than currently assumed.

Long-term fertilization determines different metabolomic profiles and responses in saplings of three rainforest tree species with different adult canopy position

PubMed Central

Gargallo-Garriga, Albert; Wright, S. Joseph; Sardans, Jordi; Pérez-Trujillo, Míriam; Oravec, Michal; Večeřová, Kristýna; Urban, Otmar; Fernández-Martínez, Marcos; Parella, Teodor; Peñuelas, Josep

2017-01-01

Background Tropical rainforests are frequently limited by soil nutrient availability. However, the response of the metabolic phenotypic plasticity of trees to an increase of soil nutrient availabilities is poorly understood. We expected that increases in the ability of a nutrient that limits some plant processes should be detected by corresponding changes in plant metabolome profile related to such processes. Methodology/Principal findings We studied the foliar metabolome of saplings of three abundant tree species in a 15 year field NPK fertilization experiment in a Panamanian rainforest. The largest differences were among species and explained 75% of overall metabolome variation. The saplings of the large canopy species, Tetragastris panamensis, had the lowest concentrations of all identified amino acids and the highest concentrations of most identified secondary compounds. The saplings of the “mid canopy” species, Alseis blackiana, had the highest concentrations of amino acids coming from the biosynthesis pathways of glycerate-3P, oxaloacetate and α-ketoglutarate, and the saplings of the low canopy species, Heisteria concinna, had the highest concentrations of amino acids coming from the pyruvate synthesis pathways. Conclusions/Significance The changes in metabolome provided strong evidence that different nutrients limit different species in different ways. With increasing P availability, the two canopy species shifted their metabolome towards larger investment in protection mechanisms, whereas with increasing N availability, the sub-canopy species increased its primary metabolism. The results highlighted the proportional distinct use of different nutrients by different species and the resulting different metabolome profiles in this high diversity community are consistent with the ecological niche theory. PMID:28493911

Bio-effectors from waste materials as growth promoters, an agronomic and metabolomic study

NASA Astrophysics Data System (ADS)

Alwanney, Deaa; Chami, Ziad Al; Angelica De Pascali, Sandra; Cavoski, Ivana; Fanizzi, Francesco Paolo

2014-05-01

Nowadays, improving plant performance by providing growth promoters is a main concern of the organic agriculture. As a consequence of increased food demands, more efficient and alternatives of the current plant nutrition strategies are becoming urgent. Recently, a novel concept "bio-effectors" raised on to describe a group of products that are able to improve plant performance and do not belong to fertilizers or pesticides. Agro-Food processing residues are promising materials as bio-effector. Three plant-derived materials: brewers' spent grain (BSG), fennel processing residues (FPR) and lemon processing residues (LPR) were chosen as bio-effector candidates. Plant-derived materials were characterized in term of total macro and micronutrients content. Green extraction methodology and solvent choice (aqueous; ethanol; and aqueous: ethanol mixture 1:1) was based on the extraction yield as main factor. Optimum extracts, to be used on the tomato test plant, were determined using phytotoxicity test (seed germination test) as main constraint. Thereafter, selected extracts were characterized and secondary metabolites profiling were detected by NMR technique. Selected extracts were applied on tomato in a growth chamber at different doses in comparison to humic-like substances as positive control (Ctrl+) and to a Hoagland solution as negative control (Ctrl-). At the end of the experiment, agronomical parameters were determined and NMR-metabolomic profiling were conducted on tomato seedlings. Results are summarized as follow: (i) raw showed an interesting content, either at nutritional or biological level; (ii) aqueous extraction resulted higher yield than other used solvent; (iii) at high extraction ratio (1:25 for BSG; 1:100 for FPR; and 1:200 for LPR) aqueous extracts were not phytotoxic on the tomato test plant; (iv) all aqueous extract are differently rich in nutrients, aminoacids, sugars and low molecular weight molecules; (v) all extract exhibited a growth promotion at low application doses; (vi) regarding plant metabolomics study, all treatments showed a different metabolites in respect to Ctrl- treatment. BSG, LPR and Ctrl+ treatments had similar metabolic profile. Finally, Metabolomic study provided an efficient tool and a key reporter about bio-effectors impact on plants. The visible effect and measured agronomical parameters was emphasized and demonstrated by metabolic profiling which offer insights into the affected plant metabolic pathways. As conclusion, our results supported the prediction that plant derived materials may interfere again in plant production regardless their nutritional content. Keywords: Bio-effectors; Metabolomics; Nuclear Magnetic Resonance (NMR); Barley; Fennel; Lemon; Tomato.

Close and distant: Contrasting the metabolism of two closely related subspecies of Scots pine under the effects of folivory and summer drought

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rivas-Ubach, Albert; Sardans, Jordi; Hódar, José Antonio

The metabolome, the chemical phenotype of an organism, should be shaped by evolution. Metabolomes depend on genetic composition and expression, which can be sources of evolutionary inertia, so most aspects of metabolomes should be similar in closely related sympatric species. We examined the metabolomes of two sympatric subspecies of Pinus sylvestris in Sierra Nevada (southern Iberian Peninsula), one introduced (ssp. iberica) and one autochthonous (ssp. nevadensis), in summer and winter and exposed to folivory by the pine processionary moth. The overall metabolomes differed between the subspecies but both tended to respond more similarly to folivory. The metabolomes of the subspeciesmore » were more dissimilar in summer than in winter, and iberica trees had higher concentrations of metabolites directly related to drought stress. Our results suggest that certain plant metabolic responses associated with folivory have been conserved throughout evolutionary history. The larger divergence between subspecies metabolomes in summer is likely due to the warmer and drier conditions that the northern iberica subspecies experience in Sierra Nevada. Our results provide crucial insights into how iberica populations would respond to the predicted conditions of climate change under an increased defoliation, two recent severe issues in the Mediterranean Basin.« less

Metabolomics Suggests That Soil Inoculation with Arbuscular Mycorrhizal Fungi Decreased Free Amino Acid Content in Roots of Durum Wheat Grown under N-Limited, P-Rich Field Conditions

PubMed Central

Saia, Sergio; Ruisi, Paolo; Fileccia, Veronica; Di Miceli, Giuseppe; Amato, Gaetano; Martinelli, Federico

2015-01-01

Arbuscular mycorrhizal fungi (AMF) have a major impact on plant nutrition, defence against pathogens, a plant’s reaction to stressful environments, soil fertility, and a plant’s relationship with other microorganisms. Such effects imply a broad reprogramming of the plant’s metabolic activity. However, little information is available regarding the role of AMF and their relation to other soil plant growth—promoting microorganisms in the plant metabolome, especially under realistic field conditions. In the present experiment, we evaluated the effects of inoculation with AMF, either alone or in combination with plant growth–promoting rhizobacteria (PGPR), on the metabolome and changes in metabolic pathways in the roots of durum wheat (Triticum durum Desf.) grown under N-limited agronomic conditions in a P-rich environment. These two treatments were compared to infection by the natural AMF population (NAT). Soil inoculation with AMF almost doubled wheat root colonization by AMF and decreased the root concentrations of most compounds in all metabolic pathways, especially amino acids (AA) and saturated fatty acids, whereas inoculation with AMF+PGPR increased the concentrations of such compounds compared to inoculation with AMF alone. Enrichment metabolomics analyses showed that AA metabolic pathways were mostly changed by the treatments, with reduced amination activity in roots most likely due to a shift from the biosynthesis of common AA to γ-amino butyric acid. The root metabolome differed between AMF and NAT but not AMF+PGPR and AMF or NAT. Because the PGPR used were potent mineralisers, and AMF can retain most nitrogen (N) taken as organic compounds for their own growth, it is likely that this result was due to an increased concentration of mineral N in soil inoculated with AMF+PGPR compared to AMF alone. PMID:26067663

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sumner, Lloyd W.; Lei, Zhentian; Nikolau, Basil J.

Plant metabolomics has matured and modern plant metabolomics has accelerated gene discoveries and the elucidation of a variety of plant natural product biosynthetic pathways. This study highlights specific examples of the discovery and characterization of novel genes and enzymes associated with the biosynthesis of natural products such as flavonoids, glucosinolates, terpenoids, and alkaloids. Additional examples of the integration of metabolomics with genome-based functional characterizations of plant natural products that are important to modern pharmaceutical technology are also reviewed. This article also provides a substantial review of recent technical advances in mass spectrometry imaging, nuclear magnetic resonance imaging, integrated LC-MS-SPE-NMR formore » metabolite identifications, and x-ray crystallography of microgram quantities for structural determinations. The review closes with a discussion on the future prospects of metabolomics related to crop species and herbal medicine.« less

Mass spectrometry-based plant metabolomics: Metabolite responses to abiotic stress.

PubMed

Jorge, Tiago F; Rodrigues, João A; Caldana, Camila; Schmidt, Romy; van Dongen, Joost T; Thomas-Oates, Jane; António, Carla

2016-09-01

Metabolomics is one omics approach that can be used to acquire comprehensive information on the composition of a metabolite pool to provide a functional screen of the cellular state. Studies of the plant metabolome include analysis of a wide range of chemical species with diverse physical properties, from ionic inorganic compounds to biochemically derived hydrophilic carbohydrates, organic and amino acids, and a range of hydrophobic lipid-related compounds. This complexitiy brings huge challenges to the analytical technologies employed in current plant metabolomics programs, and powerful analytical tools are required for the separation and characterization of this extremely high compound diversity present in biological sample matrices. The use of mass spectrometry (MS)-based analytical platforms to profile stress-responsive metabolites that allow some plants to adapt to adverse environmental conditions is fundamental in current plant biotechnology research programs for the understanding and development of stress-tolerant plants. In this review, we describe recent applications of metabolomics and emphasize its increasing application to study plant responses to environmental (stress-) factors, including drought, salt, low oxygen caused by waterlogging or flooding of the soil, temperature, light and oxidative stress (or a combination of them). Advances in understanding the global changes occurring in plant metabolism under specific abiotic stress conditions are fundamental to enhance plant fitness and increase stress tolerance. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 35:620-649, 2016. © 2015 Wiley Periodicals, Inc.

REVIEW ARTICLE: Current trends and future requirements for the mass spectrometric investigation of microbial, mammalian and plant metabolomes

NASA Astrophysics Data System (ADS)

Dunn, Warwick B.

2008-03-01

The functional levels of biological cells or organisms can be separated into the genome, transcriptome, proteome and metabolome. Of these the metabolome offers specific advantages to the investigation of the phenotype of biological systems. The investigation of the metabolome (metabolomics) has only recently appeared as a mainstream scientific discipline and is currently developing rapidly for the study of microbial, plant and mammalian metabolomes. The metabolome pipeline or workflow encompasses the processes of sample collection and preparation, collection of analytical data, raw data pre-processing, data analysis and data storage. Of these processes the collection of analytical data will be discussed in this review with specific interest shown in the application of mass spectrometry in the metabolomics pipeline. The current developments in mass spectrometry platforms (GC-MS, LC-MS, DIMS and imaging MS) and applications of specific interest will be highlighted. The current limitations of these platforms and applications will be discussed with areas requiring further development also highlighted. These include the detectable coverage of the metabolome, the identification of metabolites and the process of converting raw data to biological knowledge.

Metabolomics for Plant Improvement: Status and Prospects

PubMed Central

Kumar, Rakesh; Bohra, Abhishek; Pandey, Arun K.; Pandey, Manish K.; Kumar, Anirudh

2017-01-01

Post-genomics era has witnessed the development of cutting-edge technologies that have offered cost-efficient and high-throughput ways for molecular characterization of the function of a cell or organism. Large-scale metabolite profiling assays have allowed researchers to access the global data sets of metabolites and the corresponding metabolic pathways in an unprecedented way. Recent efforts in metabolomics have been directed to improve the quality along with a major focus on yield related traits. Importantly, an integration of metabolomics with other approaches such as quantitative genetics, transcriptomics and genetic modification has established its immense relevance to plant improvement. An effective combination of these modern approaches guides researchers to pinpoint the functional gene(s) and the characterization of massive metabolites, in order to prioritize the candidate genes for downstream analyses and ultimately, offering trait specific markers to improve commercially important traits. This in turn will improve the ability of a plant breeder by allowing him to make more informed decisions. Given this, the present review captures the significant leads gained in the past decade in the field of plant metabolomics accompanied by a brief discussion on the current contribution and the future scope of metabolomics to accelerate plant improvement. PMID:28824660

The effects of mineral nitrogen limitation, competition, arbuscular mycorrhiza, and their respective interactions, on morphological and chemical plant traits of Plantago lanceolata.

PubMed

Pankoke, Helga; Höpfner, Ingo; Matuszak, Agnieszka; Beyschlag, Wolfram; Müller, Caroline

2015-10-01

Plants are sessile organisms that suffer from a multitude of challenges such as abiotic stress or the interactions with competitors, antagonists and symbionts, which influence their performance as well as their eco-physiological and biochemical responses in complex ways. In particular, the combination of different stressors and their impact on plant biomass production and the plant's ability to metabolically adjust to these challenges are less well understood. To study the effects of mineral nitrogen (N) availability, interspecific competition and the association with arbuscular mycorrhizal fungi (AMF) on biomass production, biomass allocation patterns (root/shoot ratio, specific leaf area) and metabolic responses, we chose the model organism Plantago lanceolata L. (Plantaginaceae). Plants were grown in a full factorial experiment. Biomass production and its allocation patterns were assessed at harvest, and the influence of the different treatments and their interactions on the plant metabolome were analysed using a metabolic fingerprinting approach with ultra-high performance liquid chromatography coupled with time-of-flight-mass spectrometry. Limited supply of mineral N caused the most pronounced changes with respect to plant biomass and biomass allocation patterns, and altered the concentrations of more than one third of the polar plant metabolome. Competition also impaired plant biomass production, yet affected the plant metabolome to a much lesser extent than limited mineral N supply. The interaction of competition and limited mineral N supply often caused additive changes on several traits. The association with AMF did not enhance biomass production, but altered biomass allocation patterns such as the root/shoot ratio and the specific leaf area. Interestingly, we did not find significant changes in the plant metabolome caused by AMF. A targeted analysis revealed that only limited mineral N supply reduced the concentrations of one of the main target defence compounds of P. lanceolata, the iridoid glycoside catalpol. In general, the interaction of competition and limited mineral N supply led to additive changes, while the association with AMF in any case alleviated the observed stress responses. Our results show that the joint analysis of biomass/allocation patterns and metabolic traits allows a more comprehensive interpretation of plant responses to different biotic and abiotic challenges; specifically, when multiple stresses interact. Copyright © 2015 Elsevier Ltd. All rights reserved.

A prominent role for the CBF cold response pathway in configuring the low-temperature metabolome of Arabidopsis

PubMed Central

Cook, Daniel; Fowler, Sarah; Fiehn, Oliver; Thomashow, Michael F.

2004-01-01

The Arabidopsis CBF cold response pathway has a central role in cold acclimation, the process whereby plants increase in freezing tolerance in response to low nonfreezing temperatures. Here we examined the changes that occur in the Arabidopsis metabolome in response to low temperature and assessed the role of the CBF cold response pathway in bringing about these modifications. Of 434 metabolites monitored by GC-time-of-flight MS, 325 (75%) were found to increase in Arabidopsis Wassilewskija-2 (Ws-2) plants in response to low temperature. Of these 325 metabolites, 256 (79%) also increased in nonacclimated Ws-2 plants in response to overexpression of C-repeat/dehydration responsive element-binding factor (CBF)3. Extensive cold-induced changes also occurred in the metabolome of Arabidopsis Cape Verde Islands-1 (Cvi-1) plants, which were found to be less freezing tolerant than Ws-2 plants. However, low-temperature-induced expression of CBF1, CBF2, CBF3, and CBF-targeted genes was much lower in Cvi-1 than in Ws-2 plants, and the low-temperature metabolome of Cvi-1 plants was depleted in metabolites affected by CBF3 overexpression. Taken together, the results indicate that the metabolome of Arabidopsis is extensively reconfigured in response to low temperature, and that the CBF cold response pathway has a prominent role in this process. PMID:15383661

Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches

PubMed Central

Beatty, Perrin H.; Klein, Matthias S.; Fischer, Jeffrey J.; Lewis, Ian A.; Muench, Douglas G.; Good, Allen G.

2016-01-01

A comprehensive understanding of plant metabolism could provide a direct mechanism for improving nitrogen use efficiency (NUE) in crops. One of the major barriers to achieving this outcome is our poor understanding of the complex metabolic networks, physiological factors, and signaling mechanisms that affect NUE in agricultural settings. However, an exciting collection of computational and experimental approaches has begun to elucidate whole-plant nitrogen usage and provides an avenue for connecting nitrogen-related phenotypes to genes. Herein, we describe how metabolomics, computational models of metabolism, and flux balance analysis have been harnessed to advance our understanding of plant nitrogen metabolism. We introduce a model describing the complex flow of nitrogen through crops in a real-world agricultural setting and describe how experimental metabolomics data, such as isotope labeling rates and analyses of nutrient uptake, can be used to refine these models. In summary, the metabolomics/computational approach offers an exciting mechanism for understanding NUE that may ultimately lead to more effective crop management and engineered plants with higher yields. PMID:27735856

Genetic transformation of rare Verbascum eriophorum Godr. plants and metabolic alterations revealed by NMR-based metabolomics.

PubMed

Marchev, Andrey; Yordanova, Zhenya; Alipieva, Kalina; Zahmanov, Georgi; Rusinova-Videva, Snezhana; Kapchina-Toteva, Veneta; Simova, Svetlana; Popova, Milena; Georgiev, Milen I

2016-09-01

To develop a protocol to transform Verbascum eriophorum and to study the metabolic differences between mother plants and hairy root culture by applying NMR and processing the datasets with chemometric tools. Verbascum eriophorum is a rare species with restricted distribution, which is poorly studied. Agrobacterium rhizogenes-mediated genetic transformation of V. eriophorum and hairy root culture induction are reported for the first time. To determine metabolic alterations, V. eriophorum mother plants and relevant hairy root culture were subjected to comprehensive metabolomic analyses, using NMR (1D and 2D). Metabolomics data, processed using chemometric tools (and principal component analysis in particular) allowed exploration of V. eriophorum metabolome and have enabled identification of verbascoside (by means of 2D-TOCSY NMR) as the most abundant compound in hairy root culture. Metabolomics data contribute to the elucidation of metabolic alterations after T-DNA transfer to the host V. eriophorum genome and the development of hairy root culture for sustainable bioproduction of high value verbascoside.

Decoding genes with coexpression networks and metabolomics - 'majority report by precogs'.

PubMed

Saito, Kazuki; Hirai, Masami Y; Yonekura-Sakakibara, Keiko

2008-01-01

Following the sequencing of whole genomes of model plants, high-throughput decoding of gene function is a major challenge in modern plant biology. In view of remarkable technical advances in transcriptomics and metabolomics, integrated analysis of these 'omics' by data-mining informatics is an excellent tool for prediction and identification of gene function, particularly for genes involved in complicated metabolic pathways. The availability of Arabidopsis public transcriptome datasets containing data of >1000 microarrays reinforces the potential for prediction of gene function by transcriptome coexpression analysis. Here, we review the strategy of combining transcriptome and metabolome as a powerful technology for studying the functional genomics of model plants and also crop and medicinal plants.

Topsoil depth substantially influences the responses to drought of the foliar metabolomes of Mediterranean forests

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rivas-Ubach, Albert; Barbeta, Adrià; Sardans, Jordi

Soils provide physical support, water, and nutrients to terrestrial plants. Upper soil layers are crucial for forest dynamics, especially under drought conditions, because many biological processes occur there and provide support, water and nutrients to terrestrial plants. We postulated that tree size and overall plant function manifested in the metabolome composition, the total set of metabolites, were dependent on the depth of upper soil layers and on water availability. We sampled leaves for stoichiometric and metabolomic analyses once per season from differently sized Quercus ilex trees under natural and experimental drought conditions as projected for the coming decades. Different sizedmore » trees had different metabolomes and plots with shallower soils had smaller trees. Soil moisture of the upper soil did not explain the tree size and smaller trees did not show higher concentrations of biomarker metabolites related to drought stress. However, the impact of drought treatment on metabolomes was higher in smaller trees in shallower soils. Our results suggested that tree size was more dependent on the depth of the upper soil layers, which indirectly affect the metabolomes of the trees, than on the moisture content of the upper soil layers. Metabolomic profiling of Q. ilex supported the premise that water availability in the upper soil layers was not necessarily correlated with tree size. The higher impact of drought on trees growing in shallower soils nevertheless indicates a higher vulnerability of small trees to the future increase in frequency, intensity, and duration of drought projected for the Mediterranean Basin and other areas. Metabolomics has proven to be an excellent tool detecting significant metabolic changes among differently sized individuals of the same species and it improves our understanding of the connection between plant metabolomes and environmental variables such as soil depth and moisture content.« less

The Chemistry of Plant–Microbe Interactions in the Rhizosphere and the Potential for Metabolomics to Reveal Signaling Related to Defense Priming and Induced Systemic Resistance

PubMed Central

Mhlongo, Msizi I.; Piater, Lizelle A.; Madala, Ntakadzeni E.; Labuschagne, Nico; Dubery, Ian A.

2018-01-01

Plant roots communicate with microbes in a sophisticated manner through chemical communication within the rhizosphere, thereby leading to biofilm formation of beneficial microbes and, in the case of plant growth-promoting rhizomicrobes/-bacteria (PGPR), resulting in priming of defense, or induced resistance in the plant host. The knowledge of plant–plant and plant–microbe interactions have been greatly extended over recent years; however, the chemical communication leading to priming is far from being well understood. Furthermore, linkage between below- and above-ground plant physiological processes adds to the complexity. In metabolomics studies, the main aim is to profile and annotate all exo- and endo-metabolites in a biological system that drive and participate in physiological processes. Recent advances in this field has enabled researchers to analyze 100s of compounds in one sample over a short time period. Here, from a metabolomics viewpoint, we review the interactions within the rhizosphere and subsequent above-ground ‘signalomics’, and emphasize the contributions that mass spectrometric-based metabolomic approaches can bring to the study of plant-beneficial – and priming events. PMID:29479360

Metabolome analysis of 20 taxonomically related benzylisoquinoline alkaloid-producing plants.

PubMed

Hagel, Jillian M; Mandal, Rupasri; Han, Beomsoo; Han, Jun; Dinsmore, Donald R; Borchers, Christoph H; Wishart, David S; Facchini, Peter J

2015-09-15

Recent progress toward the elucidation of benzylisoquinoline alkaloid (BIA) metabolism has focused on a small number of model plant species. Current understanding of BIA metabolism in plants such as opium poppy, which accumulates important pharmacological agents such as codeine and morphine, has relied on a combination of genomics and metabolomics to facilitate gene discovery. Metabolomics studies provide important insight into the primary biochemical networks underpinning specialized metabolism, and serve as a key resource for metabolic engineering, gene discovery, and elucidation of governing regulatory mechanisms. Beyond model plants, few broad-scope metabolomics reports are available for the vast number of plant species known to produce an estimated 2500 structurally diverse BIAs, many of which exhibit promising medicinal properties. We applied a multi-platform approach incorporating four different analytical methods to examine 20 non-model, BIA-accumulating plant species. Plants representing four families in the Ranunculales were chosen based on reported BIA content, taxonomic distribution and importance in modern/traditional medicine. One-dimensional (1)H NMR-based profiling quantified 91 metabolites and revealed significant species- and tissue-specific variation in sugar, amino acid and organic acid content. Mono- and disaccharide sugars were generally lower in roots and rhizomes compared with stems, and a variety of metabolites distinguished callus tissue from intact plant organs. Direct flow infusion tandem mass spectrometry provided a broad survey of 110 lipid derivatives including phosphatidylcholines and acylcarnitines, and high-performance liquid chromatography coupled with UV detection quantified 15 phenolic compounds including flavonoids, benzoic acid derivatives and hydroxycinnamic acids. Ultra-performance liquid chromatography coupled with high-resolution Fourier transform mass spectrometry generated extensive mass lists for all species, which were mined for metabolites putatively corresponding to BIAs. Different alkaloids profiles, including both ubiquitous and potentially rare compounds, were observed. Extensive metabolite profiling combining multiple analytical platforms enabled a more complete picture of overall metabolism occurring in selected plant species. This study represents the first time a metabolomics approach has been applied to most of these species, despite their importance in modern and traditional medicine. Coupled with genomics data, these metabolomics resources serve as a key resource for the investigation of BIA biosynthesis in non-model plant species.

Bridging the gap: basic metabolomics methods for natural product chemistry.

PubMed

Jones, Oliver A H; Hügel, Helmut M

2013-01-01

Natural products and their derivatives often have potent physiological activities and therefore play important roles as both frontline treatments for many diseases and as the inspiration for chemically synthesized therapeutics. However, the detection and synthesis of new therapeutic compounds derived from, or inspired by natural compounds has declined in recent years due to the increased difficulty of identifying and isolating novel active compounds. A new strategy is therefore necessary to jumpstart this field of research. Metabolomics, including both targeted and global metabolite profiling strategies, has the potential to be instrumental in this effort since it allows a systematic study of complex mixtures (such as plant extracts) without the need for prior isolation of active ingredients (or mixtures thereof). Here we describe the basic steps for conducting metabolomics experiments and analyzing the results using some of the more commonly used analytical and statistical methodologies.

Mass spectrometry in plant metabolomics strategies: from analytical platforms to data acquisition and processing.

PubMed

Ernst, Madeleine; Silva, Denise Brentan; Silva, Ricardo Roberto; Vêncio, Ricardo Z N; Lopes, Norberto Peporine

2014-06-01

Covering: up to 2013. Plant metabolomics is a relatively recent research field that has gained increasing interest in the past few years. Up to the present day numerous review articles and guide books on the subject have been published. This review article focuses on the current applications and limitations of the modern mass spectrometry techniques, especially in combination with electrospray ionisation (ESI), an ionisation method which is most commonly applied in metabolomics studies. As a possible alternative to ESI, perspectives on matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS) in metabolomics studies are introduced, a method which still is not widespread in the field. In metabolomics studies the results must always be interpreted in the context of the applied sampling procedures as well as data analysis. Different sampling strategies are introduced and the importance of data analysis is illustrated in the example of metabolic network modelling.

Food metabolomics: from farm to human.

PubMed

Kim, Sooah; Kim, Jungyeon; Yun, Eun Ju; Kim, Kyoung Heon

2016-02-01

Metabolomics, one of the latest components in the suite of systems biology, has been used to understand the metabolism and physiology of living systems, including microorganisms, plants, animals and humans. Food metabolomics can be defined as the application of metabolomics in food systems, including food resources, food processing and diet for humans. The study of food metabolomics has increased gradually in the recent years, because food systems are directly related to nutrition and human health. This review describes the recent trends and applications of metabolomics to food systems, from farm to human, including food resource production, industrial food processing and food intake by humans. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparative Metabolome Profile between Tobacco and Soybean Grown under Water-Stressed Conditions.

PubMed

Rabara, Roel C; Tripathi, Prateek; Rushton, Paul J

2017-01-01

Understanding how plants respond to water deficit is important in order to develop crops tolerant to drought. In this study, we compare two large metabolomics datasets where we employed a nontargeted metabolomics approach to elucidate metabolic pathways perturbed by progressive dehydration in tobacco and soybean plants. The two datasets were created using the same strategy to create water deficit conditions and an identical metabolomics pipeline. Comparisons between the two datasets therefore reveal common responses between the two species, responses specific to one of the species, responses that occur in both root and leaf tissues, and responses that are specific to one tissue. Stomatal closure is the immediate response of the plant and this did not coincide with accumulation of abscisic acid. A total of 116 and 140 metabolites were observed in tobacco leaves and roots, respectively, while 241 and 207 were observed in soybean leaves and roots, respectively. Accumulation of metabolites is significantly correlated with the extent of dehydration in both species. Among the metabolites that show increases that are restricted to just one plant, 4-hydroxy-2-oxoglutaric acid (KHG) in tobacco roots and coumestrol in soybean roots show the highest tissue-specific accumulation. The comparisons of these two large nontargeted metabolomics datasets provide novel information and suggest that KHG will be a useful marker for drought stress for some members of Solanaceae and coumestrol for some legume species.

Automatic differential analysis of NMR experiments in complex samples.

PubMed

Margueritte, Laure; Markov, Petar; Chiron, Lionel; Starck, Jean-Philippe; Vonthron-Sénécheau, Catherine; Bourjot, Mélanie; Delsuc, Marc-André

2018-06-01

Liquid state nuclear magnetic resonance (NMR) is a powerful tool for the analysis of complex mixtures of unknown molecules. This capacity has been used in many analytical approaches: metabolomics, identification of active compounds in natural extracts, and characterization of species, and such studies require the acquisition of many diverse NMR measurements on series of samples. Although acquisition can easily be performed automatically, the number of NMR experiments involved in these studies increases very rapidly, and this data avalanche requires to resort to automatic processing and analysis. We present here a program that allows the autonomous, unsupervised processing of a large corpus of 1D, 2D, and diffusion-ordered spectroscopy experiments from a series of samples acquired in different conditions. The program provides all the signal processing steps, as well as peak-picking and bucketing of 1D and 2D spectra, the program and its components are fully available. In an experiment mimicking the search of a bioactive species in a natural extract, we use it for the automatic detection of small amounts of artemisinin added to a series of plant extracts and for the generation of the spectral fingerprint of this molecule. This program called Plasmodesma is a novel tool that should be useful to decipher complex mixtures, particularly in the discovery of biologically active natural products from plants extracts but can also in drug discovery or metabolomics studies. Copyright © 2017 John Wiley & Sons, Ltd.

Assessing the impact of transcriptomics, proteomics and metabolomics on fungal phytopathology.

PubMed

Tan, Kar-Chun; Ipcho, Simon V S; Trengove, Robert D; Oliver, Richard P; Solomon, Peter S

2009-09-01

SUMMARY Peer-reviewed literature is today littered with exciting new tools and techniques that are being used in all areas of biology and medicine. Transcriptomics, proteomics and, more recently, metabolomics are three of these techniques that have impacted on fungal plant pathology. Used individually, each of these techniques can generate a plethora of data that could occupy a laboratory for years. When used in combination, they have the potential to comprehensively dissect a system at the transcriptional and translational level. Transcriptomics, or quantitative gene expression profiling, is arguably the most familiar to researchers in the field of fungal plant pathology. Microarrays have been the primary technique for the last decade, but others are now emerging. Proteomics has also been exploited by the fungal phytopathogen community, but perhaps not to its potential. A lack of genome sequence information has frustrated proteomics researchers and has largely contributed to this technique not fulfilling its potential. The coming of the genome sequencing era has partially alleviated this problem. Metabolomics is the most recent of these techniques to emerge and is concerned with the non-targeted profiling of all metabolites in a given system. Metabolomics studies on fungal plant pathogens are only just beginning to appear, although its potential to dissect many facets of the pathogen and disease will see its popularity increase quickly. This review assesses the impact of transcriptomics, proteomics and metabolomics on fungal plant pathology over the last decade and discusses their futures. Each of the techniques is described briefly with further reading recommended. Key examples highlighting the application of these technologies to fungal plant pathogens are also reviewed.

Proteomics and Metabolomics: Two Emerging Areas for Legume Improvement

PubMed Central

Ramalingam, Abirami; Kudapa, Himabindu; Pazhamala, Lekha T.; Weckwerth, Wolfram; Varshney, Rajeev K.

2015-01-01

The crop legumes such as chickpea, common bean, cowpea, peanut, pigeonpea, soybean, etc. are important sources of nutrition and contribute to a significant amount of biological nitrogen fixation (>20 million tons of fixed nitrogen) in agriculture. However, the production of legumes is constrained due to abiotic and biotic stresses. It is therefore imperative to understand the molecular mechanisms of plant response to different stresses and identify key candidate genes regulating tolerance which can be deployed in breeding programs. The information obtained from transcriptomics has facilitated the identification of candidate genes for the given trait of interest and utilizing them in crop breeding programs to improve stress tolerance. However, the mechanisms of stress tolerance are complex due to the influence of multi-genes and post-transcriptional regulations. Furthermore, stress conditions greatly affect gene expression which in turn causes modifications in the composition of plant proteomes and metabolomes. Therefore, functional genomics involving various proteomics and metabolomics approaches have been obligatory for understanding plant stress tolerance. These approaches have also been found useful to unravel different pathways related to plant and seed development as well as symbiosis. Proteome and metabolome profiling using high-throughput based systems have been extensively applied in the model legume species, Medicago truncatula and Lotus japonicus, as well as in the model crop legume, soybean, to examine stress signaling pathways, cellular and developmental processes and nodule symbiosis. Moreover, the availability of protein reference maps as well as proteomics and metabolomics databases greatly support research and understanding of various biological processes in legumes. Protein-protein interaction techniques, particularly the yeast two-hybrid system have been advantageous for studying symbiosis and stress signaling in legumes. In this review, several studies on proteomics and metabolomics in model and crop legumes have been discussed. Additionally, applications of advanced proteomics and metabolomics approaches have also been included in this review for future applications in legume research. The integration of these “omics” approaches will greatly support the identification of accurate biomarkers in legume smart breeding programs. PMID:26734026

Chemical Composition and Seasonality of Aromatic Mediterranean Plant Species by NMR-Based Metabolomics

PubMed Central

Scognamiglio, Monica; D'Abrosca, Brigida; Esposito, Assunta; Fiorentino, Antonio

2015-01-01

An NMR-based metabolomic approach has been applied to analyse seven aromatic Mediterranean plant species used in traditional cuisine. Based on the ethnobotanical use of these plants, the approach has been employed in order to study the metabolic changes during different seasons. Primary and secondary metabolites have been detected and quantified. Flavonoids (apigenin, quercetin, and kaempferol derivatives) and phenylpropanoid derivatives (e.g., chlorogenic and rosmarinic acid) are the main identified polyphenols. The richness in these metabolites could explain the biological properties ascribed to these plant species. PMID:25785229

Current Challenges in Plant Eco-Metabolomics

PubMed Central

Peters, Kristian; Worrich, Anja; Alka, Oliver; Balcke, Gerd; Bruelheide, Helge; Dietz, Sophie; Dührkop, Kai; Heinig, Uwe; Kücklich, Marlen; Müller, Caroline; Poeschl, Yvonne; Pohnert, Georg; Ruttkies, Christoph; Schweiger, Rabea; Shahaf, Nir; Tortosa, Maria; Ueberschaar, Nico; Velasco, Pablo; Weiß, Brigitte M.; van Dam, Nicole M.

2018-01-01

The relatively new research discipline of Eco-Metabolomics is the application of metabolomics techniques to ecology with the aim to characterise biochemical interactions of organisms across different spatial and temporal scales. Metabolomics is an untargeted biochemical approach to measure many thousands of metabolites in different species, including plants and animals. Changes in metabolite concentrations can provide mechanistic evidence for biochemical processes that are relevant at ecological scales. These include physiological, phenotypic and morphological responses of plants and communities to environmental changes and also interactions with other organisms. Traditionally, research in biochemistry and ecology comes from two different directions and is performed at distinct spatiotemporal scales. Biochemical studies most often focus on intrinsic processes in individuals at physiological and cellular scales. Generally, they take a bottom-up approach scaling up cellular processes from spatiotemporally fine to coarser scales. Ecological studies usually focus on extrinsic processes acting upon organisms at population and community scales and typically study top-down and bottom-up processes in combination. Eco-Metabolomics is a transdisciplinary research discipline that links biochemistry and ecology and connects the distinct spatiotemporal scales. In this review, we focus on approaches to study chemical and biochemical interactions of plants at various ecological levels, mainly plant–organismal interactions, and discuss related examples from other domains. We present recent developments and highlight advancements in Eco-Metabolomics over the last decade from various angles. We further address the five key challenges: (1) complex experimental designs and large variation of metabolite profiles; (2) feature extraction; (3) metabolite identification; (4) statistical analyses; and (5) bioinformatics software tools and workflows. The presented solutions to these challenges will advance connecting the distinct spatiotemporal scales and bridging biochemistry and ecology. PMID:29734799

Towards a scientific interpretation of the terroir concept: plasticity of the grape berry metabolome.

PubMed

Anesi, Andrea; Stocchero, Matteo; Dal Santo, Silvia; Commisso, Mauro; Zenoni, Sara; Ceoldo, Stefania; Tornielli, Giovanni Battista; Siebert, Tracey E; Herderich, Markus; Pezzotti, Mario; Guzzo, Flavia

2015-08-07

The definition of the terroir concept is one of the most debated issues in oenology and viticulture. The dynamic interaction among diverse factors including the environment, the grapevine plant and the imposed viticultural techniques means that the wine produced in a given terroir is unique. However, there is an increasing interest to define and quantify the contribution of individual factors to a specific terroir objectively. Here, we characterized the metabolome and transcriptome of berries from a single clone of the Corvina variety cultivated in seven different vineyards, located in three macrozones, over a 3-year trial period. To overcome the anticipated strong vintage effect, we developed statistical tools that allowed us to identify distinct terroir signatures in the metabolic composition of berries from each macrozone, and from different vineyards within each macrozone. We also identified non-volatile and volatile components of the metabolome which are more plastic and therefore respond differently to terroir diversity. We observed some relationships between the plasticity of the metabolome and transcriptome, allowing a multifaceted scientific interpretation of the terroir concept. Our experiments with a single Corvina clone in different vineyards have revealed the existence of a clear terroir-specific effect on the transcriptome and metabolome which persists over several vintages and allows each vineyard to be characterized by the unique profile of specific metabolites.

Impact of Soil Warming on the Plant Metabolome of Icelandic Grasslands.

PubMed

Gargallo-Garriga, Albert; Ayala-Roque, Marta; Sardans, Jordi; Bartrons, Mireia; Granda, Victor; Sigurdsson, Bjarni D; Leblans, Niki I W; Oravec, Michal; Urban, Otmar; Janssens, Ivan A; Peñuelas, Josep

2017-08-23

Climate change is stronger at high than at temperate and tropical latitudes. The natural geothermal conditions in southern Iceland provide an opportunity to study the impact of warming on plants, because of the geothermal bedrock channels that induce stable gradients of soil temperature. We studied two valleys, one where such gradients have been present for centuries (long-term treatment), and another where new gradients were created in 2008 after a shallow crustal earthquake (short-term treatment). We studied the impact of soil warming (0 to +15 °C) on the foliar metabolomes of two common plant species of high northern latitudes: Agrostis capillaris , a monocotyledon grass; and Ranunculus acris , a dicotyledonous herb, and evaluated the dependence of shifts in their metabolomes on the length of the warming treatment. The two species responded differently to warming, depending on the length of exposure. The grass metabolome clearly shifted at the site of long-term warming, but the herb metabolome did not. The main up-regulated compounds at the highest temperatures at the long-term site were saccharides and amino acids, both involved in heat-shock metabolic pathways. Moreover, some secondary metabolites, such as phenolic acids and terpenes, associated with a wide array of stresses, were also up-regulated. Most current climatic models predict an increase in annual average temperature between 2-8 °C over land masses in the Arctic towards the end of this century. The metabolomes of A. capillaris and R. acris shifted abruptly and nonlinearly to soil warming >5 °C above the control temperature for the coming decades. These results thus suggest that a slight warming increase may not imply substantial changes in plant function, but if the temperature rises more than 5 °C, warming may end up triggering metabolic pathways associated with heat stress in some plant species currently dominant in this region.

Impact of Soil Warming on the Plant Metabolome of Icelandic Grasslands

PubMed Central

Gargallo-Garriga, Albert; Ayala-Roque, Marta; Granda, Victor; Sigurdsson, Bjarni D.; Leblans, Niki I. W.; Oravec, Michal; Urban, Otmar; Janssens, Ivan A.

2017-01-01

Climate change is stronger at high than at temperate and tropical latitudes. The natural geothermal conditions in southern Iceland provide an opportunity to study the impact of warming on plants, because of the geothermal bedrock channels that induce stable gradients of soil temperature. We studied two valleys, one where such gradients have been present for centuries (long-term treatment), and another where new gradients were created in 2008 after a shallow crustal earthquake (short-term treatment). We studied the impact of soil warming (0 to +15 °C) on the foliar metabolomes of two common plant species of high northern latitudes: Agrostis capillaris, a monocotyledon grass; and Ranunculus acris, a dicotyledonous herb, and evaluated the dependence of shifts in their metabolomes on the length of the warming treatment. The two species responded differently to warming, depending on the length of exposure. The grass metabolome clearly shifted at the site of long-term warming, but the herb metabolome did not. The main up-regulated compounds at the highest temperatures at the long-term site were saccharides and amino acids, both involved in heat-shock metabolic pathways. Moreover, some secondary metabolites, such as phenolic acids and terpenes, associated with a wide array of stresses, were also up-regulated. Most current climatic models predict an increase in annual average temperature between 2–8 °C over land masses in the Arctic towards the end of this century. The metabolomes of A. capillaris and R. acris shifted abruptly and nonlinearly to soil warming >5 °C above the control temperature for the coming decades. These results thus suggest that a slight warming increase may not imply substantial changes in plant function, but if the temperature rises more than 5 °C, warming may end up triggering metabolic pathways associated with heat stress in some plant species currently dominant in this region. PMID:28832555

Integration of Plant Metabolomics Data with Metabolic Networks: Progresses and Challenges.

PubMed

Töpfer, Nadine; Seaver, Samuel M D; Aharoni, Asaph

2018-01-01

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. In this chapter, we demonstrate a workflow to integrate gas chromatography coupled to mass spectrometry (GC-MS)-based metabolomics data of tomato fruit pericarp (flesh) tissue, at five developmental stages, with a genome-scale reconstruction of tomato metabolism. This method allows for the extraction of context-specific networks reflecting changing activities of metabolic pathways throughout fruit development and maturation.

From chromatogram to analyte to metabolite. How to pick horses for courses from the massive web resources for mass spectral plant metabolomics

PubMed Central

Perez de Souza, Leonardo; Naake, Thomas; Tohge, Takayuki; Fernie, Alisdair R

2017-01-01

Abstract The grand challenge currently facing metabolomics is the expansion of the coverage of the metabolome from a minor percentage of the metabolic complement of the cell toward the level of coverage afforded by other post-genomic technologies such as transcriptomics and proteomics. In plants, this problem is exacerbated by the sheer diversity of chemicals that constitute the metabolome, with the number of metabolites in the plant kingdom generally considered to be in excess of 200 000. In this review, we focus on web resources that can be exploited in order to improve analyte and ultimately metabolite identification and quantification. There is a wide range of available software that not only aids in this but also in the related area of peak alignment; however, for the uninitiated, choosing which program to use is a daunting task. For this reason, we provide an overview of the pros and cons of the software as well as comments regarding the level of programing skills required to effectively exploit their basic functions. In addition, the torrent of available genome and transcriptome sequences that followed the advent of next-generation sequencing has opened up further valuable resources for metabolite identification. All things considered, we posit that only via a continued communal sharing of information such as that deposited in the databases described within the article are we likely to be able to make significant headway toward improving our coverage of the plant metabolome. PMID:28520864

Lipidome and metabolome analysis of fresh tobacco leaves in different geographical regions using liquid chromatography-mass spectrometry.

PubMed

Li, Lili; Lu, Xin; Zhao, Jieyu; Zhang, Junjie; Zhao, Yanni; Zhao, Chunxia; Xu, Guowang

2015-07-01

The combination of the lipidome and the metabolome can provide much more information in plant metabolomics studies. A method for the simultaneous extraction of the lipidome and the metabolome of fresh tobacco leaves was developed. Method validation was performed on the basis of the optimal ratio of methanol to methyl tert-butyl ether to water (37:45:68) from the design of experiments. Good repeatability was obtained. We found that 92.2% and 91.6% of the peaks for the lipidome and the metabolome were within a relative standard deviation of 20%, accounting for 94.6% and 94.6% of the total abundance, respectively. The intraday and interday precisions were also satisfactory. A total of 230 metabolites, including 129 lipids, were identified. Significant differences were found in lipidomic and metabolomic profiles of fresh tobacco leaves in different geographical regions. Highly unsaturated galactolipids, phosphatidylethanolamines, predominant phosphatidylcholines, most of the polyphenols, amino acids, and polyamines had a higher content in Yunnan province, and low-unsaturation-degree galactolipids, triacylglycerols, glucosylceramides with trihydroxy long-chain bases, acylated sterol glucosides, and some organic acids were more abundant in Henan province. Correlation analysis between differential metabolites and climatic factors indicated the vital importance of temperature. The fatty acid unsaturation degree of galactolipids could be influenced by temperature. Accumulation of polyphenols and decreases in the ratios of stigmasterols to sitosterols and glucosylstigmasterols to glucosylsitosterols were also correlated with lower temperature in Yunnan province. Furthermore, lipids were more sensitive to climatic variations than other metabolites.

Non-targeted Metabolomics in Diverse Sorghum Breeding Lines Indicates Primary and Secondary Metabolite Profiles Are Associated with Plant Biomass Accumulation and Photosynthesis

DOE PAGES

Turner, Marie F.; Heuberger, Adam L.; Kirkwood, Jay S.; ...

2016-07-11

Metabolomics is an emerging method to improve our understanding of how genetic diversity affects phenotypic variation in plants. Recent studies have demonstrated that genotype has a major influence on biochemical variation in several types of plant tissues, however, the association between metabolic variation and variation in morphological and physiological traits is largely unknown. Sorghum bicolor (L.) is an important food and fuel crop with extensive genetic and phenotypic variation. Sorghum lines have been bred for differing phenotypes beneficial for production of grain (food), stem sugar (food, fuel), and cellulosic biomass (forage, fuel), and these varying phenotypes are the end productsmore » of innate metabolic programming which determines how carbon is allocated during plant growth and development. Further, sorghum has been adapted among highly diverse environments. Because of this geographic and phenotypic variation, the sorghum metabolome is expected to be highly divergent; however, metabolite variation in sorghum has not been characterized. Here, we utilize a phenotypically diverse panel of sorghum breeding lines to identify associations between leaf metabolites and morpho-physiological traits. The panel (11 lines) exhibited significant variation for 21 morpho-physiological traits, as well as broader trends in variation by sorghum type (grain vs. biomass types). Variation was also observed for cell wall constituents (glucan, xylan, lignin, ash). Non-targeted metabolomics analysis of leaf tissue showed that 956 of 1181 metabolites varied among the lines (81%, ANOVA, FDR adjusted p < 0.05). Both univariate and multivariate analyses determined relationships between metabolites and morpho-physiological traits, and 384 metabolites correlated with at least one trait (32%, p < 0.05), including many secondary metabolites such as glycosylated flavonoids and chlorogenic acids. The use of metabolomics to explain relationships between two or more morpho-physiological traits was explored and showed chlorogenic and shikimic acid to be associated with photosynthesis, early plant growth and final biomass measures in sorghum. In conclusion, taken together, this study demonstrates the integration of metabolomics with morpho-physiological datasets to elucidate links between plant metabolism, growth, and architecture.« less

Non-targeted Metabolomics in Diverse Sorghum Breeding Lines Indicates Primary and Secondary Metabolite Profiles Are Associated with Plant Biomass Accumulation and Photosynthesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Turner, Marie F.; Heuberger, Adam L.; Kirkwood, Jay S.

Metabolomics is an emerging method to improve our understanding of how genetic diversity affects phenotypic variation in plants. Recent studies have demonstrated that genotype has a major influence on biochemical variation in several types of plant tissues, however, the association between metabolic variation and variation in morphological and physiological traits is largely unknown. Sorghum bicolor (L.) is an important food and fuel crop with extensive genetic and phenotypic variation. Sorghum lines have been bred for differing phenotypes beneficial for production of grain (food), stem sugar (food, fuel), and cellulosic biomass (forage, fuel), and these varying phenotypes are the end productsmore » of innate metabolic programming which determines how carbon is allocated during plant growth and development. Further, sorghum has been adapted among highly diverse environments. Because of this geographic and phenotypic variation, the sorghum metabolome is expected to be highly divergent; however, metabolite variation in sorghum has not been characterized. Here, we utilize a phenotypically diverse panel of sorghum breeding lines to identify associations between leaf metabolites and morpho-physiological traits. The panel (11 lines) exhibited significant variation for 21 morpho-physiological traits, as well as broader trends in variation by sorghum type (grain vs. biomass types). Variation was also observed for cell wall constituents (glucan, xylan, lignin, ash). Non-targeted metabolomics analysis of leaf tissue showed that 956 of 1181 metabolites varied among the lines (81%, ANOVA, FDR adjusted p < 0.05). Both univariate and multivariate analyses determined relationships between metabolites and morpho-physiological traits, and 384 metabolites correlated with at least one trait (32%, p < 0.05), including many secondary metabolites such as glycosylated flavonoids and chlorogenic acids. The use of metabolomics to explain relationships between two or more morpho-physiological traits was explored and showed chlorogenic and shikimic acid to be associated with photosynthesis, early plant growth and final biomass measures in sorghum. In conclusion, taken together, this study demonstrates the integration of metabolomics with morpho-physiological datasets to elucidate links between plant metabolism, growth, and architecture.« less

NMR metabolomics of thrips (Frankliniella occidentalis) resistance in Senecio hybrids.

PubMed

Leiss, Kirsten A; Choi, Young H; Abdel-Farid, Ibrahim B; Verpoorte, Robert; Klinkhamer, Peter G L

2009-02-01

Western flower thrips (Frankliniella occidentalis) has become a key insect pest of agricultural and horticultural crops worldwide. Little is known about host plant resistance to thrips. In this study, we investigated thrips resistance in F (2) hybrids of Senecio jacobaea and Senecio aquaticus. We identified thrips-resistant hybrids applying three different bioassays. Subsequently, we compared the metabolomic profiles of these hybrids applying nuclear magnetic resonance spectroscopy (NMR). The new developments of NMR facilitate a wide range coverage of the metabolome. This makes NMR especially suitable if there is no a priori knowledge of the compounds related to herbivore resistance and allows a holistic approach analyzing different chemical compounds simultaneously. We show that the metabolomes of thrips-resistant and -susceptible hybrids differed considerably. Thrips-resistant hybrids contained higher amounts of the pyrrolizidine alkaloids (PA), jacobine, and jaconine, especially in younger leaves. Also, a flavanoid, kaempferol glucoside, accumulated in the resistant plants. Both PAs and kaempferol are known for their inhibitory effect on herbivores. In resistant and susceptible F (2) hybrids, young leaves showed less thrips damage than old leaves. Consistent with the optimal plant defense theory, young leaves contained increased levels of primary metabolites such as sucrose, raffinose, and stachyose, but also accumulated jacaranone as a secondary plant defense compound. Our results prove NMR as a promising tool to identify different metabolites involved in herbivore resistance. It constitutes a significant advance in the study of plant-insect relationships, providing key information on the implementation of herbivore resistance breeding strategies in plants.

Establishing Substantial Equivalence: Metabolomics

NASA Astrophysics Data System (ADS)

Beale, Michael H.; Ward, Jane L.; Baker, John M.

Modern ‘metabolomic’ methods allow us to compare levels of many structurally diverse compounds in an automated fashion across a large number of samples. This technology is ideally suited to screening of populations of plants, including trials where the aim is the determination of unintended effects introduced by GM. A number of metabolomic methods have been devised for the determination of substantial equivalence. We have developed a methodology, using [1H]-NMR fingerprinting, for metabolomic screening of plants and have applied it to the study of substantial equivalence of field-grown GM wheat. We describe here the principles and detail of that protocol as applied to the analysis of flour generated from field plots of wheat. Particular emphasis is given to the downstream data processing and comparison of spectra by multivariate analysis, from which conclusions regarding metabolome changes due to the GM can be assessed against the background of natural variation due to environment.

Compliance with minimum information guidelines in public metabolomics repositories

PubMed Central

Spicer, Rachel A.; Salek, Reza; Steinbeck, Christoph

2017-01-01

The Metabolomics Standards Initiative (MSI) guidelines were first published in 2007. These guidelines provided reporting standards for all stages of metabolomics analysis: experimental design, biological context, chemical analysis and data processing. Since 2012, a series of public metabolomics databases and repositories, which accept the deposition of metabolomic datasets, have arisen. In this study, the compliance of 399 public data sets, from four major metabolomics data repositories, to the biological context MSI reporting standards was evaluated. None of the reporting standards were complied with in every publicly available study, although adherence rates varied greatly, from 0 to 97%. The plant minimum reporting standards were the most complied with and the microbial and in vitro were the least. Our results indicate the need for reassessment and revision of the existing MSI reporting standards. PMID:28949328

Compliance with minimum information guidelines in public metabolomics repositories.

PubMed

Spicer, Rachel A; Salek, Reza; Steinbeck, Christoph

2017-09-26

The Metabolomics Standards Initiative (MSI) guidelines were first published in 2007. These guidelines provided reporting standards for all stages of metabolomics analysis: experimental design, biological context, chemical analysis and data processing. Since 2012, a series of public metabolomics databases and repositories, which accept the deposition of metabolomic datasets, have arisen. In this study, the compliance of 399 public data sets, from four major metabolomics data repositories, to the biological context MSI reporting standards was evaluated. None of the reporting standards were complied with in every publicly available study, although adherence rates varied greatly, from 0 to 97%. The plant minimum reporting standards were the most complied with and the microbial and in vitro were the least. Our results indicate the need for reassessment and revision of the existing MSI reporting standards.

From chromatogram to analyte to metabolite. How to pick horses for courses from the massive web resources for mass spectral plant metabolomics.

PubMed

Perez de Souza, Leonardo; Naake, Thomas; Tohge, Takayuki; Fernie, Alisdair R

2017-07-01

The grand challenge currently facing metabolomics is the expansion of the coverage of the metabolome from a minor percentage of the metabolic complement of the cell toward the level of coverage afforded by other post-genomic technologies such as transcriptomics and proteomics. In plants, this problem is exacerbated by the sheer diversity of chemicals that constitute the metabolome, with the number of metabolites in the plant kingdom generally considered to be in excess of 200 000. In this review, we focus on web resources that can be exploited in order to improve analyte and ultimately metabolite identification and quantification. There is a wide range of available software that not only aids in this but also in the related area of peak alignment; however, for the uninitiated, choosing which program to use is a daunting task. For this reason, we provide an overview of the pros and cons of the software as well as comments regarding the level of programing skills required to effectively exploit their basic functions. In addition, the torrent of available genome and transcriptome sequences that followed the advent of next-generation sequencing has opened up further valuable resources for metabolite identification. All things considered, we posit that only via a continued communal sharing of information such as that deposited in the databases described within the article are we likely to be able to make significant headway toward improving our coverage of the plant metabolome. © The Authors 2017. Published by Oxford University Press.

Heavy Metal Tolerance in Plants: Role of Transcriptomics, Proteomics, Metabolomics, and Ionomics

PubMed Central

Singh, Samiksha; Parihar, Parul; Singh, Rachana; Singh, Vijay P.; Prasad, Sheo M.

2016-01-01

Heavy metal contamination of soil and water causing toxicity/stress has become one important constraint to crop productivity and quality. This situation has further worsened by the increasing population growth and inherent food demand. It has been reported in several studies that counterbalancing toxicity due to heavy metal requires complex mechanisms at molecular, biochemical, physiological, cellular, tissue, and whole plant level, which might manifest in terms of improved crop productivity. Recent advances in various disciplines of biological sciences such as metabolomics, transcriptomics, proteomics, etc., have assisted in the characterization of metabolites, transcription factors, and stress-inducible proteins involved in heavy metal tolerance, which in turn can be utilized for generating heavy metal-tolerant crops. This review summarizes various tolerance strategies of plants under heavy metal toxicity covering the role of metabolites (metabolomics), trace elements (ionomics), transcription factors (transcriptomics), various stress-inducible proteins (proteomics) as well as the role of plant hormones. We also provide a glance of some strategies adopted by metal-accumulating plants, also known as “metallophytes.” PMID:26904030

Enzyme-driven metabolomic screening: a proof-of-principle method for discovery of plant defence compounds targeted by pathogens.

PubMed

Carere, Jason; Colgrave, Michelle L; Stiller, Jiri; Liu, Chunji; Manners, John M; Kazan, Kemal; Gardiner, Donald M

2016-11-01

Plants produce a variety of secondary metabolites to defend themselves from pathogen attack, while pathogens have evolved to overcome plant defences by producing enzymes that degrade or modify these defence compounds. However, many compounds targeted by pathogen enzymes currently remain enigmatic. Identifying host compounds targeted by pathogen enzymes would enable us to understand the potential importance of such compounds in plant defence and modify them to make them insensitive to pathogen enzymes. Here, a proof of concept metabolomics-based method was developed to discover plant defence compounds modified by pathogens using two pathogen enzymes with known targets in wheat and tomato. Plant extracts treated with purified pathogen enzymes were subjected to LC-MS, and the relative abundance of metabolites before and after treatment were comparatively analysed. Using two enzymes from different pathogens the in planta targets could be found by combining relatively simple enzymology with the power of untargeted metabolomics. Key to the method is dataset simplification based on natural isotope occurrence and statistical filtering, which can be scripted. The method presented here will aid in our understanding of plant-pathogen interactions and may lead to the development of new plant protection strategies. © 2016 CSIRO. New Phytologist © 2016 New Phytologist Trust.

Comprehensive transcriptome analyses correlated with untargeted metabolome reveal differentially expressed pathways in response to cell wall alterations.

PubMed

Reem, Nathan T; Chen, Han-Yi; Hur, Manhoi; Zhao, Xuefeng; Wurtele, Eve Syrkin; Li, Xu; Li, Ling; Zabotina, Olga

2018-03-01

This research provides new insights into plant response to cell wall perturbations through correlation of transcriptome and metabolome datasets obtained from transgenic plants expressing cell wall-modifying enzymes. Plants respond to changes in their cell walls in order to protect themselves from pathogens and other stresses. Cell wall modifications in Arabidopsis thaliana have profound effects on gene expression and defense response, but the cell signaling mechanisms underlying these responses are not well understood. Three transgenic Arabidopsis lines, two with reduced cell wall acetylation (AnAXE and AnRAE) and one with reduced feruloylation (AnFAE), were used in this study to investigate the plant responses to cell wall modifications. RNA-Seq in combination with untargeted metabolome was employed to assess differential gene expression and metabolite abundance. RNA-Seq results were correlated with metabolite abundances to determine the pathways involved in response to cell wall modifications introduced in each line. The resulting pathway enrichments revealed the deacetylation events in AnAXE and AnRAE plants induced similar responses, notably, upregulation of aromatic amino acid biosynthesis and changes in regulation of primary metabolic pathways that supply substrates to specialized metabolism, particularly those related to defense responses. In contrast, genes and metabolites of lipid biosynthetic pathways and peroxidases involved in lignin polymerization were downregulated in AnFAE plants. These results elucidate how primary metabolism responds to extracellular stimuli. Combining the transcriptomics and metabolomics datasets increased the power of pathway prediction, and demonstrated the complexity of pathways involved in cell wall-mediated signaling.

Holistic Analysis Enhances the Description of Metabolic Complexity in Dietary Natural Products1234

PubMed Central

Kulakowski, Daniel; Lankin, David C; McAlpine, James B; Chen, Shao-Nong

2016-01-01

In the field of food and nutrition, complex natural products (NPs) are typically obtained from cells/tissues of diverse organisms such as plants, mushrooms, and animals. Among them, edible fruits, grains, and vegetables represent most of the human diet. Because of an important dietary dependence, the comprehensive metabolomic analysis of dietary NPs, performed holistically via the assessment of as many metabolites as possible, constitutes a fundamental building block for understanding the human diet. Both mass spectrometry (MS) and nuclear magnetic resonance (NMR) are important complementary analytic techniques, covering a wide range of metabolites at different concentrations. Particularly, 1-dimensional 1H-NMR offers an unbiased overview of all metabolites present in a sample without prior knowledge of its composition, thereby leading to an untargeted analysis. In the past decade, NMR-based metabolomics in plant and food analyses has evolved considerably. The scope of the present review, covering literature of the past 5 y, is to address the relevance of 1H-NMR–based metabolomics in food plant studies, including a comparison with MS-based techniques. Major applications of NMR-based metabolomics for the quality control of dietary NPs and assessment of their nutritional values are presented. PMID:27180381

Advances in metabolomic applications in plant genetics and breeding

USDA-ARS?s Scientific Manuscript database

Metabolomics is a systems biology discipline wherein abundances of endogenous metabolites from biological samples are identified and quantitatively measured across a large range of metabolites and/or a large number of samples. Since all developmental, physiological and response to the environment ph...

Linking Ecological, Environmental and Biogeochemical Data with Multi'omics Analysis

NASA Astrophysics Data System (ADS)

Hasler-Sheetal, H.; Castorani, M. C.; Fragner, L.; Zeng, Y.; Holmer, M.; Glud, R. N.; Weckwerth, W.; Canfield, D. E.

2016-02-01

The integrated analysis of multi'omics and environmental data provides a holistic understanding of biological processes and has been proven to be challenging. Here we present our research concept for conducting multi-omics experiments and linking them to environmental data. Hypoxia, reduced light availability and species interaction - all amplified by global warming - cause a global decline of seagrasses. Metabolic mechanisms for coping with these global threats are largely unknown and multi'omics approaches can be an important approach for generating this insight. We applied GC, LC-qTOF-MS and bioinformatics to investigate the effects of environmental pressure on metabolites present in seagrasses. In a first experiment we assessed the metabolomics response of the seagrass Zostera marina towards anoxia and showed that photosynthetically derived oxygen could satisfy the oxygen demand in the leaves. But accumulation of fermentation products in the roots showed that the rhizosphere was under anoxic stress. In contrast nocturnal anoxia caused a biphasic shift in the metabolome of roots and leaves. This nocturnal reprogramming of the metabolome under anoxia indicates a mitigation mechanism to avoid the toxic effects. A pathway enrichment analysis proposes the alanine shunt, the GABA shunt and the 2-oxoglutarate shunt as such mitigation mechanisms that alleviate pyruvate levels and lead to carbon and nitrogen storage during anoxia. In a second experiment, varying light exposure and species interaction of Z. marina with the blue mussel Mytilus edulis - a co-occurring species in seagrass systems - resulted in treatment specific metabolic fingerprints in seagrass. Light modified the metabolic fingerprint expressed in Z. marina to the presence of mussels, indicating varying physiological responses to mussels in normal and low light regimes. Multivariate data-analysis indicated light exposure as main driver (45%) and mussel presence as minor driver (13%) for the metabolic responses. Traditional plant performance parameters exhibited light dependent variation but in contrast to the metabolome none of these parameters were dependent on the presence of M. edulis. This demonstrates the applicability of metabolomics to reveal hidden effects of environmental pressure on seagrasses.

Integrated work-flow for quantitative metabolome profiling of plants, Peucedani Radix as a case.

PubMed

Song, Yuelin; Song, Qingqing; Liu, Yao; Li, Jun; Wan, Jian-Bo; Wang, Yitao; Jiang, Yong; Tu, Pengfei

2017-02-08

Universal acquisition of reliable information regarding the qualitative and quantitative properties of complicated matrices is the premise for the success of metabolomics study. Liquid chromatography-mass spectrometry (LC-MS) is now serving as a workhorse for metabolomics; however, LC-MS-based non-targeted metabolomics is suffering from some shortcomings, even some cutting-edge techniques have been introduced. Aiming to tackle, to some extent, the drawbacks of the conventional approaches, such as redundant information, detector saturation, low sensitivity, and inconstant signal number among different runs, herein, a novel and flexible work-flow consisting of three progressive steps was proposed to profile in depth the quantitative metabolome of plants. The roots of Peucedanum praeruptorum Dunn (Peucedani Radix, PR) that are rich in various coumarin isomers, were employed as a case study to verify the applicability. First, offline two dimensional LC-MS was utilized for in-depth detection of metabolites in a pooled PR extract namely universal metabolome standard (UMS). Second, mass fragmentation rules, notably concerning angular-type pyranocoumarins that are the primary chemical homologues in PR, and available databases were integrated for signal assignment and structural annotation. Third, optimum collision energy (OCE) as well as ion transition for multiple monitoring reaction measurement was online optimized with a reference compound-free strategy for each annotated component and large-scale relative quantification of all annotated components was accomplished by plotting calibration curves via serially diluting UMS. It is worthwhile to highlight that the potential of OCE for isomer discrimination was described and the linearity ranges of those primary ingredients were extended by suppressing their responses. The integrated workflow is expected to be qualified as a promising pipeline to clarify the quantitative metabolome of plants because it could not only holistically provide qualitative information, but also straightforwardly generate accurate quantitative dataset. Copyright © 2016 Elsevier B.V. All rights reserved.

Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools

PubMed Central

Sud, Manish; Fahy, Eoin; Cotter, Dawn; Azam, Kenan; Vadivelu, Ilango; Burant, Charles; Edison, Arthur; Fiehn, Oliver; Higashi, Richard; Nair, K. Sreekumaran; Sumner, Susan; Subramaniam, Shankar

2016-01-01

The Metabolomics Workbench, available at www.metabolomicsworkbench.org, is a public repository for metabolomics metadata and experimental data spanning various species and experimental platforms, metabolite standards, metabolite structures, protocols, tutorials, and training material and other educational resources. It provides a computational platform to integrate, analyze, track, deposit and disseminate large volumes of heterogeneous data from a wide variety of metabolomics studies including mass spectrometry (MS) and nuclear magnetic resonance spectrometry (NMR) data spanning over 20 different species covering all the major taxonomic categories including humans and other mammals, plants, insects, invertebrates and microorganisms. Additionally, a number of protocols are provided for a range of metabolite classes, sample types, and both MS and NMR-based studies, along with a metabolite structure database. The metabolites characterized in the studies available on the Metabolomics Workbench are linked to chemical structures in the metabolite structure database to facilitate comparative analysis across studies. The Metabolomics Workbench, part of the data coordinating effort of the National Institute of Health (NIH) Common Fund's Metabolomics Program, provides data from the Common Fund's Metabolomics Resource Cores, metabolite standards, and analysis tools to the wider metabolomics community and seeks data depositions from metabolomics researchers across the world. PMID:26467476

Chemical interactions between plants in Mediterranean vegetation: the influence of selected plant extracts on Aegilops geniculata metabolome.

PubMed

Scognamiglio, Monica; Fiumano, Vittorio; D'Abrosca, Brigida; Esposito, Assunta; Choi, Young Hae; Verpoorte, Robert; Fiorentino, Antonio

2014-10-01

Allelopathy is the chemical mediated communication among plants. While on one hand there is growing interest in the field, on the other hand it is still debated as doubts exist at different levels. A number of compounds have been reported for their ability to influence plant growth, but the existence of this phenomenon in the field has rarely been demonstrated. Furthermore, only few studies have reported the uptake and the effects at molecular level of the allelochemicals. Allelopathy has been reported on some plants of Mediterranean vegetation and could contribute to structuring this ecosystem. Sixteen plants of Mediterranean vegetation have been selected and studied by an NMR-based metabolomics approach. The extracts of these donor plants have been characterized in terms of chemical composition and the effects on a selected receiving plant, Aegilops geniculata, have been studied both at the morphological and at the metabolic level. Most of the plant extracts employed in this study were found to have an activity, which could be correlated with the presence of flavonoids and hydroxycinnamate derivatives. These plant extracts affected the receiving plant in different ways, with different rates of growth inhibition at morphological level. The results of metabolomic analysis of treated plants suggested the induction of oxidative stress in all the receiving plants treated with active donor plant extracts, although differences were observed among the responses. Finally, the uptake and transport into receiving plant leaves of different metabolites present in the extracts added to the culture medium were observed. Copyright © 2014 Elsevier Ltd. All rights reserved.

(1)H NMR and GC-MS Based Metabolomics Reveal Defense and Detoxification Mechanism of Cucumber Plant under Nano-Cu Stress.

PubMed

Zhao, Lijuan; Huang, Yuxiong; Hu, Jerry; Zhou, Hongjun; Adeleye, Adeyemi S; Keller, Arturo A

2016-02-16

Because copper nanoparticles are being increasingly used in agriculture as pesticides, it is important to assess their potential implications for agriculture. Concerns have been raised about the bioaccumulation of nano-Cu and their toxicity to crop plants. Here, the response of cucumber plants in hydroponic culture at early development stages to two concentrations of nano-Cu (10 and 20 mg/L) was evaluated by proton nuclear magnetic resonance spectroscopy ((1)H NMR) and gas chromatography-mass spectrometry (GC-MS) based metabolomics. Changes in mineral nutrient metabolism induced by nano-Cu were determined by inductively coupled plasma-mass spectrometry (ICP-MS). Results showed that nano-Cu at both concentrations interferes with the uptake of a number of micro- and macro-nutrients, such as Na, P, S, Mo, Zn, and Fe. Metabolomics data revealed that nano-Cu at both levels triggered significant metabolic changes in cucumber leaves and root exudates. The root exudate metabolic changes revealed an active defense mechanism against nano-Cu stress: up-regulation of amino acids to sequester/exclude Cu/nano-Cu; down-regulation of citric acid to reduce the mobilization of Cu ions; ascorbic acid up-regulation to combat reactive oxygen species; and up-regulation of phenolic compounds to improve antioxidant system. Thus, we demonstrate that nontargeted (1)H NMR and GC-MS based metabolomics can successfully identify physiological responses induced by nanoparticles. Root exudates metabolomics revealed important detoxification mechanisms.

Proteome and metabolome profiling of cytokinin action in Arabidopsis identifying both distinct and similar responses to cytokinin down- and up-regulation.

PubMed

Černý, Martin; Kuklová, Alena; Hoehenwarter, Wolfgang; Fragner, Lena; Novák, Ondrej; Rotková, Gabriela; Jedelsky, Petr L; Žáková, Katerina; Šmehilová, Mária; Strnad, Miroslav; Weckwerth, Wolfram; Brzobohaty, Bretislav

2013-11-01

In plants, numerous developmental processes are controlled by cytokinin (CK) levels and their ratios to levels of other hormones. While molecular mechanisms underlying the regulatory roles of CKs have been intensely researched, proteomic and metabolomic responses to CK deficiency are unknown. Transgenic Arabidopsis seedlings carrying inducible barley cytokinin oxidase/dehydrogenase (CaMV35S>GR>HvCKX2) and agrobacterial isopentenyl transferase (CaMV35S>GR>ipt) constructs were profiled to elucidate proteome- and metabolome-wide responses to down- and up-regulation of CK levels, respectively. Proteome profiling identified >1100 proteins, 155 of which responded to HvCKX2 and/or ipt activation, mostly involved in growth, development, and/or hormone and light signalling. The metabolome profiling covered 79 metabolites, 33 of which responded to HvCKX2 and/or ipt activation, mostly amino acids, carbohydrates, and organic acids. Comparison of the data sets obtained from activated CaMV35S>GR>HvCKX2 and CaMV35S>GR>ipt plants revealed unexpectedly extensive overlaps. Integration of the proteomic and metabolomic data sets revealed: (i) novel components of molecular circuits involved in CK action (e.g. ribosomal proteins); (ii) previously unrecognized links to redox regulation and stress hormone signalling networks; and (iii) CK content markers. The striking overlaps in profiles observed in CK-deficient and CK-overproducing seedlings might explain surprising previously reported similarities between plants with down- and up-regulated CK levels.

Advances in computational metabolomics and databases deepen the understanding of metabolisms.

PubMed

Tsugawa, Hiroshi

2018-01-29

Mass spectrometry (MS)-based metabolomics is the popular platform for metabolome analyses. Computational techniques for the processing of MS raw data, for example, feature detection, peak alignment, and the exclusion of false-positive peaks, have been established. The next stage of untargeted metabolomics would be to decipher the mass fragmentation of small molecules for the global identification of human-, animal-, plant-, and microbiota metabolomes, resulting in a deeper understanding of metabolisms. This review is an update on the latest computational metabolomics including known/expected structure databases, chemical ontology classifications, and mass spectrometry cheminformatics for the interpretation of mass fragmentations and for the elucidation of unknown metabolites. The importance of metabolome 'databases' and 'repositories' is also discussed because novel biological discoveries are often attributable to the accumulation of data, to relational databases, and to their statistics. Lastly, a practical guide for metabolite annotations is presented as the summary of this review. Copyright © 2018 Elsevier Ltd. All rights reserved.

Tools for the functional interpretation of metabolomic experiments.

PubMed

Chagoyen, Monica; Pazos, Florencio

2013-11-01

The so-called 'omics' approaches used in modern biology aim at massively characterizing the molecular repertories of living systems at different levels. Metabolomics is one of the last additions to the 'omics' family and it deals with the characterization of the set of metabolites in a given biological system. As metabolomic techniques become more massive and allow characterizing larger sets of metabolites, automatic methods for analyzing these sets in order to obtain meaningful biological information are required. Only recently the first tools specifically designed for this task in metabolomics appeared. They are based on approaches previously used in transcriptomics and other 'omics', such as annotation enrichment analysis. These, together with generic tools for metabolic analysis and visualization not specifically designed for metabolomics will for sure be in the toolbox of the researches doing metabolomic experiments in the near future.

Untargeted Metabolomics Strategies—Challenges and Emerging Directions

NASA Astrophysics Data System (ADS)

Schrimpe-Rutledge, Alexandra C.; Codreanu, Simona G.; Sherrod, Stacy D.; McLean, John A.

2016-12-01

Metabolites are building blocks of cellular function. These species are involved in enzyme-catalyzed chemical reactions and are essential for cellular function. Upstream biological disruptions result in a series of metabolomic changes and, as such, the metabolome holds a wealth of information that is thought to be most predictive of phenotype. Uncovering this knowledge is a work in progress. The field of metabolomics is still maturing; the community has leveraged proteomics experience when applicable and developed a range of sample preparation and instrument methodology along with myriad data processing and analysis approaches. Research focuses have now shifted toward a fundamental understanding of the biology responsible for metabolomic changes. There are several types of metabolomics experiments including both targeted and untargeted analyses. While untargeted, hypothesis generating workflows exhibit many valuable attributes, challenges inherent to the approach remain. This Critical Insight comments on these challenges, focusing on the identification process of LC-MS-based untargeted metabolomics studies—specifically in mammalian systems. Biological interpretation of metabolomics data hinges on the ability to accurately identify metabolites. The range of confidence associated with identifications that is often overlooked is reviewed, and opportunities for advancing the metabolomics field are described.

Metabolomics for Biomarker Discovery in Gastroenterological Cancer

PubMed Central

Nishiumi, Shin; Suzuki, Makoto; Kobayashi, Takashi; Matsubara, Atsuki; Azuma, Takeshi; Yoshida, Masaru

2014-01-01

The study of the omics cascade, which involves comprehensive investigations based on genomics, transcriptomics, proteomics, metabolomics, etc., has developed rapidly and now plays an important role in life science research. Among such analyses, metabolome analysis, in which the concentrations of low molecular weight metabolites are comprehensively analyzed, has rapidly developed along with improvements in analytical technology, and hence, has been applied to a variety of research fields including the clinical, cell biology, and plant/food science fields. The metabolome represents the endpoint of the omics cascade and is also the closest point in the cascade to the phenotype. Moreover, it is affected by variations in not only the expression but also the enzymatic activity of several proteins. Therefore, metabolome analysis can be a useful approach for finding effective diagnostic markers and examining unknown pathological conditions. The number of studies involving metabolome analysis has recently been increasing year-on-year. Here, we describe the findings of studies that used metabolome analysis to attempt to discover biomarker candidates for gastroenterological cancer and discuss metabolome analysis-based disease diagnosis. PMID:25003943

Isoprene emission by poplar is not important for the feeding behaviour of poplar leaf beetles.

PubMed

Müller, Anna; Kaling, Moritz; Faubert, Patrick; Gort, Gerrit; Smid, Hans M; Van Loon, Joop J A; Dicke, Marcel; Kanawati, Basem; Schmitt-Kopplin, Philippe; Polle, Andrea; Schnitzler, Jörg-Peter; Rosenkranz, Maaria

2015-06-30

Chrysomela populi (poplar leaf beetle) is a common herbivore in poplar plantations whose infestation causes major economic losses. Because plant volatiles act as infochemicals, we tested whether isoprene, the main volatile organic compound (VOC) produced by poplars (Populus x canescens), affects the performance of C. populi employing isoprene emitting (IE) and transgenic isoprene non-emitting (NE) plants. Our hypothesis was that isoprene is sensed and affects beetle orientation or that the lack of isoprene affects plant VOC profiles and metabolome with consequences for C. populi feeding. Electroantennographic analysis revealed that C. populi can detect higher terpenes, but not isoprene. In accordance to the inability to detect isoprene, C. populi showed no clear preference for IE or NE poplar genotypes in the choice experiments, however, the beetles consumed a little bit less leaf mass and laid fewer eggs on NE poplar trees in field experiments. Slight differences in the profiles of volatile terpenoids between IE and NE genotypes were detected by gas chromatography - mass spectrometry. Non-targeted metabolomics analysis by Fourier Transform Ion Cyclotron Resonance Mass Spectrometer revealed genotype-, time- and herbivore feeding-dependent metabolic changes both in the infested and adjacent undamaged leaves under field conditions. We show for the first time that C. populi is unable to sense isoprene. The detected minor differences in insect feeding in choice experiments and field bioassays may be related to the revealed changes in leaf volatile emission and metabolite composition between the IE and NE poplars. Overall our results indicate that lacking isoprene emission is of minor importance for C. populi herbivory under natural conditions, and that the lack of isoprene is not expected to change the economic losses in poplar plantations caused by C. populi infestation.

Arsenomics: omics of arsenic metabolism in plants

PubMed Central

Tripathi, Rudra Deo; Tripathi, Preeti; Dwivedi, Sanjay; Dubey, Sonali; Chatterjee, Sandipan; Chakrabarty, Debasis; Trivedi, Prabodh K.

2012-01-01

Arsenic (As) contamination of drinking water and groundwater used for irrigation can lead to contamination of the food chain and poses serious health risk to people worldwide. To reduce As intake through the consumption of contaminated food, identification of the mechanisms for As accumulation and detoxification in plant is a prerequisite to develop efficient phytoremediation methods and safer crops with reduced As levels. Transcriptome, proteome, and metabolome analysis of any organism reflects the total biological activities at any given time which are responsible for the adaptation of the organism to the surrounding environmental conditions. As these approaches are very important in analyzing plant As transport and accumulation, we termed “Arsenomics” as approach which deals transcriptome, proteome, and metabolome alterations during As exposure. Although, various studies have been performed to understand modulation in transcriptome in response to As, many important questions need to be addressed regarding the translated proteins of plants at proteomic and metabolomic level, resulting in various ecophysiological responses. In this review, the comprehensive knowledge generated in this area has been compiled and analyzed. There is a need to strengthen Arsenomics which will lead to build up tools to develop As-free plants for safe consumption. PMID:22934029

Structured plant metabolomics for the simultaneous exploration of multiple factors.

PubMed

Vasilev, Nikolay; Boccard, Julien; Lang, Gerhard; Grömping, Ulrike; Fischer, Rainer; Goepfert, Simon; Rudaz, Serge; Schillberg, Stefan

2016-11-17

Multiple factors act simultaneously on plants to establish complex interaction networks involving nutrients, elicitors and metabolites. Metabolomics offers a better understanding of complex biological systems, but evaluating the simultaneous impact of different parameters on metabolic pathways that have many components is a challenging task. We therefore developed a novel approach that combines experimental design, untargeted metabolic profiling based on multiple chromatography systems and ionization modes, and multiblock data analysis, facilitating the systematic analysis of metabolic changes in plants caused by different factors acting at the same time. Using this method, target geraniol compounds produced in transgenic tobacco cell cultures were grouped into clusters based on their response to different factors. We hypothesized that our novel approach may provide more robust data for process optimization in plant cell cultures producing any target secondary metabolite, based on the simultaneous exploration of multiple factors rather than varying one factor each time. The suitability of our approach was verified by confirming several previously reported examples of elicitor-metabolite crosstalk. However, unravelling all factor-metabolite networks remains challenging because it requires the identification of all biochemically significant metabolites in the metabolomics dataset.

Metabolomics by Proton High-Resolution Magic-Angle-Spinning Nuclear Magnetic Resonance of Tomato Plants Treated with Two Secondary Metabolites Isolated from Trichoderma.

PubMed

Mazzei, Pierluigi; Vinale, Francesco; Woo, Sheridan Lois; Pascale, Alberto; Lorito, Matteo; Piccolo, Alessandro

2016-05-11

Trichoderma fungi release 6-pentyl-2H-pyran-2-one (1) and harzianic acid (2) secondary metabolites to improve plant growth and health protection. We isolated metabolites 1 and 2 from Trichoderma strains, whose different concentrations were used to treat seeds of Solanum lycopersicum. The metabolic profile in the resulting 15 day old tomato leaves was studied by high-resolution magic-angle-spinning nuclear magnetic resonance (HRMAS NMR) spectroscopy directly on the whole samples without any preliminary extraction. Principal component analysis (PCA) of HRMAS NMR showed significantly enhanced acetylcholine and γ-aminobutyric acid (GABA) content accompanied by variable amount of amino acids in samples treated with both Trichoderma secondary metabolites. Seed germination rates, seedling fresh weight, and the metabolome of tomato leaves were also dependent upon doses of metabolites 1 and 2 treatments. HRMAS NMR spectroscopy was proven to represent a rapid and reliable technique for evaluating specific changes in the metabolome of plant leaves and calibrating the best concentration of bioactive compounds required to stimulate plant growth.

Potential impact of soil microbiomes on the leaf metabolome and on herbivore feeding behavior

USDA-ARS?s Scientific Manuscript database

: It is known that environmental factors can affect the biosynthesis of leaf metabolites. Similarly, specific pairwise plant-microbe interactions modulate specifically the plant’s metabolome by stimulating production of phytoalexins and other defense-related compounds. However, there is no informati...

Metabolome of Vanilla planifolia (Orchidaceae) and related species under Cymbidium mosaic virus (CymMV) infection.

PubMed

Palama, Tony Lionel; Grisoni, Michel; Fock-Bastide, Isabelle; Jade, Katia; Bartet, Laetitia; Choi, Young Hae; Verpoorte, Robert; Kodja, Hippolyte

2012-11-01

The genus Vanilla which belongs to the Orchidaceae family comprises more than 110 species of which two are commercially cultivated (Vanilla planifolia and Vanilla xtahitensis). The cured pods of these species are the source of natural vanilla flavor. In intensive cultivation systems the vines are threatened by viruses such as Cymbidium mosaic virus (CymMV). In order to investigate the effect of CymMV on the growth and metabolome of vanilla plants, four accessions grown in intensive cultivation systems under shadehouse, CR01 (V. planifolia), CR17 (V. xtahitensis), CR03 (V. planifolia × V. xtahitensis) and CR18 (Vanilla pompona), were challenged with an isolate of CymMV. CymMV infected plants of CR01, CR03 and CR17 had a reduced growth compared to healthy plants, while there was no significant difference in the growth of CR18 vines. Interestingly, CR18 had qualitatively more phenolic compounds in leaves and a virus titre that diminished over time. No differences in the metabolomic profiles of the shadehouse samples obtained by nuclear magnetic resonance (NMR) were observed between the virus infected vs. healthy plants. However, using in- vitro V. planifolia plants, the metabolomic profiles were affected by virus infection. Under these controlled conditions the levels of amino acids and sugars present in the leaves were increased in CymMV infected plants, compared to uninfected ones, whereas the levels of phenolic compounds and malic acid were decreased. The metabolism, growth and viral status of V. pompona accession CR18 contrasted from that of the other species suggesting the existence of partial resistance to CymMV in the vanilla germplasm. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

Design of experiments for amino acid extraction from tobacco leaves and their subsequent determination by capillary zone electrophoresis.

PubMed

Hodek, Ondřej; Křížek, Tomáš; Coufal, Pavel; Ryšlavá, Helena

2017-03-01

In this study, we optimized a method for the determination of free amino acids in Nicotiana tabacum leaves. Capillary electrophoresis with contactless conductivity detector was used for the separation of 20 proteinogenic amino acids in acidic background electrolyte. Subsequently, the conditions of extraction with HCl were optimized for the highest extraction yield of the amino acids because sample treatment of plant materials brings some specific challenges. Central composite face-centered design with fractional factorial design was used in order to evaluate the significance of selected factors (HCl volume, HCl concentration, sonication, shaking) on the extraction process. In addition, the composite design helped us to find the optimal values for each factor using the response surface method. The limits of detection and limits of quantification for the 20 proteinogenic amino acids were found to be in the order of 10 -5 and 10 -4  mol l -1 , respectively. Addition of acetonitrile to the sample was tested as a method commonly used to decrease limits of detection. Ambiguous results of this experiment pointed out some features of plant extract samples, which often required specific approaches. Suitability of the method for metabolomic studies was tested by analysis of a real sample, in which all amino acids, except for L-methionine and L-cysteine, were successfully detected. The optimized extraction process together with the capillary electrophoresis method can be used for the determination of proteinogenic amino acids in plant materials. The resulting inexpensive, simple, and robust method is well suited for various metabolomic studies in plants. As such, the method represents a valuable tool for research and practical application in the fields of biology, biochemistry, and agriculture.

Metabolomics as a Hypothesis-Generating Functional Genomics Tool for the Annotation of Arabidopsis thaliana Genes of “Unknown Function”

PubMed Central

Quanbeck, Stephanie M.; Brachova, Libuse; Campbell, Alexis A.; Guan, Xin; Perera, Ann; He, Kun; Rhee, Seung Y.; Bais, Preeti; Dickerson, Julie A.; Dixon, Philip; Wohlgemuth, Gert; Fiehn, Oliver; Barkan, Lenore; Lange, Iris; Lange, B. Markus; Lee, Insuk; Cortes, Diego; Salazar, Carolina; Shuman, Joel; Shulaev, Vladimir; Huhman, David V.; Sumner, Lloyd W.; Roth, Mary R.; Welti, Ruth; Ilarslan, Hilal; Wurtele, Eve S.; Nikolau, Basil J.

2012-01-01

Metabolomics is the methodology that identifies and measures global pools of small molecules (of less than about 1,000 Da) of a biological sample, which are collectively called the metabolome. Metabolomics can therefore reveal the metabolic outcome of a genetic or environmental perturbation of a metabolic regulatory network, and thus provide insights into the structure and regulation of that network. Because of the chemical complexity of the metabolome and limitations associated with individual analytical platforms for determining the metabolome, it is currently difficult to capture the complete metabolome of an organism or tissue, which is in contrast to genomics and transcriptomics. This paper describes the analysis of Arabidopsis metabolomics data sets acquired by a consortium that includes five analytical laboratories, bioinformaticists, and biostatisticians, which aims to develop and validate metabolomics as a hypothesis-generating functional genomics tool. The consortium is determining the metabolomes of Arabidopsis T-DNA mutant stocks, grown in standardized controlled environment optimized to minimize environmental impacts on the metabolomes. Metabolomics data were generated with seven analytical platforms, and the combined data is being provided to the research community to formulate initial hypotheses about genes of unknown function (GUFs). A public database (www.PlantMetabolomics.org) has been developed to provide the scientific community with access to the data along with tools to allow for its interactive analysis. Exemplary datasets are discussed to validate the approach, which illustrate how initial hypotheses can be generated from the consortium-produced metabolomics data, integrated with prior knowledge to provide a testable hypothesis concerning the functionality of GUFs. PMID:22645570

Zinc stress affects ionome and metabolome in tea plants.

PubMed

Zhang, Yinfei; Wang, Yu; Ding, Zhaotang; Wang, Hui; Song, Lubin; Jia, Sisi; Ma, Dexin

2017-02-01

The research of physiological responses to Zn stress in plants has been extensively studied. However, the ionomics and metabolomics responses of plants to Zn stress remain largely unknown. In present study, the nutrient elements were identified involved in ion homeostasis and metabolomics changes related to Zn deficiency or excess in tea plants. Nutrient element analysis demonstrated that the concentrations of Zn affected the ion-uptake in roots and the nutrient element transportation to leaves, leading to the different distribution of P, S, Al, Ca, Fe and Cu in the tea leaves or roots. Metabolomics analysis revealed that Zn deficiency or excess differentially influenced the metabolic pathways in the tea leaves. More specifically, Zn deficiency affected the metabolism of carbohydrates, and Zn excess affected flavonoids metabolism. Additionally, the results showed that both Zn deficiency and Zn excess led to reduced nicotinamide levels, which speeded up NAD + degradation and thus reduced energy metabolism. Furthermore, element-metabolite correlation analysis illustrated that Zn contents in the tea leaves were positively correlated with organic acids, nitrogenous metabolites and some carbohydrate metabolites, and negatively correlated with the metabolites involved in secondary metabolism and some other carbohydrate metabolites. Meanwhile, metabolite-metabolite correlation analysis demonstrated that organic acids, sugars, amino acids and flavonoids played dominant roles in the regulation of the tea leaf metabolism under Zn stress. Therefore, the conclusion should be drawn that the tea plants responded to Zn stress by coordinating ion-uptake and regulation of metabolism of carbohydrates, nitrogenous metabolites, and flavonoids. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools.

PubMed

Sud, Manish; Fahy, Eoin; Cotter, Dawn; Azam, Kenan; Vadivelu, Ilango; Burant, Charles; Edison, Arthur; Fiehn, Oliver; Higashi, Richard; Nair, K Sreekumaran; Sumner, Susan; Subramaniam, Shankar

2016-01-04

The Metabolomics Workbench, available at www.metabolomicsworkbench.org, is a public repository for metabolomics metadata and experimental data spanning various species and experimental platforms, metabolite standards, metabolite structures, protocols, tutorials, and training material and other educational resources. It provides a computational platform to integrate, analyze, track, deposit and disseminate large volumes of heterogeneous data from a wide variety of metabolomics studies including mass spectrometry (MS) and nuclear magnetic resonance spectrometry (NMR) data spanning over 20 different species covering all the major taxonomic categories including humans and other mammals, plants, insects, invertebrates and microorganisms. Additionally, a number of protocols are provided for a range of metabolite classes, sample types, and both MS and NMR-based studies, along with a metabolite structure database. The metabolites characterized in the studies available on the Metabolomics Workbench are linked to chemical structures in the metabolite structure database to facilitate comparative analysis across studies. The Metabolomics Workbench, part of the data coordinating effort of the National Institute of Health (NIH) Common Fund's Metabolomics Program, provides data from the Common Fund's Metabolomics Resource Cores, metabolite standards, and analysis tools to the wider metabolomics community and seeks data depositions from metabolomics researchers across the world. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Jasmonate-mediated stomatal closure under elevated CO2 revealed by time-resolved metabolomics

USDA-ARS?s Scientific Manuscript database

Foliar stomatal movements are critical for regulating plant water status and gas exchange. Elevated carbon dioxide (CO2) concentrations are known to induce stomatal closure. However, current knowledge on CO2 signal transduction in stomatal guard cells is limited. Here we report the metabolomic respo...

High-Resolution Magic-Angle-Spinning NMR and Magnetic Resonance Imaging Spectroscopies Distinguish Metabolome and Structural Properties of Maize Seeds from Plants Treated with Different Fertilizers and Arbuscular mycorrhizal fungi.

PubMed

Mazzei, Pierluigi; Cozzolino, Vincenza; Piccolo, Alessandro

2018-03-21

Both high-resolution magic-angle-spinning (HRMAS) and magnetic resonance imaging (MRI) NMR spectroscopies were applied here to identify the changes of metabolome, morphology, and structural properties induced in seeds (caryopses) of maize plants grown at field level under either mineral or compost fertilization in combination with the inoculation by arbuscular mycorrhizal fungi (AMF). The metabolome of intact caryopses was examined by HRMAS-NMR, while the morphological aspects, endosperm properties and seed water distribution were investigated by MRI. Principal component analysis (PCA) was applied to evaluate 1 H CPMG (Carr-Purcel-Meiboom-Gill) HRMAS spectra as well as several MRI-derived parameters ( T 1 , T 2 , and self-diffusion coefficients) of intact maize caryopses. PCA score-plots from spectral results indicated that both seeds metabolome and structural properties depended on the specific field treatment undergone by maize plants. Our findings show that a combination of multivariate statistical analyses with advanced and nondestructive NMR techniques, such as HRMAS and MRI, enables the evaluation of the effects induced on maize caryopses by different fertilization and management practices at field level. The spectroscopic approach adopted here may become useful for the objective appraisal of the quality of seeds produced under a sustainable agriculture.

Metabolomic evaluation of ginsenosides distribution in Panax genus (Panax ginseng and Panax quinquefolius) using multivariate statistical analysis.

PubMed

Pace, Roberto; Martinelli, Ernesto Marco; Sardone, Nicola; D E Combarieu, Eric

2015-03-01

Ginseng is any one of the eleven species belonging to the genus Panax of the family Araliaceae and is found in North America and in eastern Asia. Ginseng is characterized by the presence of ginsenosides. Principally Panax ginseng and Panax quinquefolius are the adaptogenic herbs and are commonly distributed as health food markets. In the present study high performance liquid chromatography has been used to identify and quantify ginsenosides in the two subject species and the different parts of the plant (roots, neck, leaves, flowers, fruits). The power of this chromatographic technique to evaluate the identity of botanical material and to distinguishing different part of the plants has been investigated with metabolomic technique such as principal component analysis. Metabolomics provide a good opportunity for mining useful chemical information from the chromatographic data set resulting an important tool for quality evaluation of medicinal plants in the authenticity, consistency and efficacy. Copyright © 2015 Elsevier B.V. All rights reserved.

Binary similarity measures for fingerprint analysis of qualitative metabolomic profiles.

PubMed

Rácz, Anita; Andrić, Filip; Bajusz, Dávid; Héberger, Károly

2018-01-01

Contemporary metabolomic fingerprinting is based on multiple spectrometric and chromatographic signals, used either alone or combined with structural and chemical information of metabolic markers at the qualitative and semiquantitative level. However, signal shifting, convolution, and matrix effects may compromise metabolomic patterns. Recent increase in the use of qualitative metabolomic data, described by the presence (1) or absence (0) of particular metabolites, demonstrates great potential in the field of metabolomic profiling and fingerprint analysis. The aim of this study is a comprehensive evaluation of binary similarity measures for the elucidation of patterns among samples of different botanical origin and various metabolomic profiles. Nine qualitative metabolomic data sets covering a wide range of natural products and metabolomic profiles were applied to assess 44 binary similarity measures for the fingerprinting of plant extracts and natural products. The measures were analyzed by the novel sum of ranking differences method (SRD), searching for the most promising candidates. Baroni-Urbani-Buser (BUB) and Hawkins-Dotson (HD) similarity coefficients were selected as the best measures by SRD and analysis of variance (ANOVA), while Dice (Di1), Yule, Russel-Rao, and Consonni-Todeschini 3 ranked the worst. ANOVA revealed that concordantly and intermediately symmetric similarity coefficients are better candidates for metabolomic fingerprinting than the asymmetric and correlation based ones. The fingerprint analysis based on the BUB and HD coefficients and qualitative metabolomic data performed equally well as the quantitative metabolomic profile analysis. Fingerprint analysis based on the qualitative metabolomic profiles and binary similarity measures proved to be a reliable way in finding the same/similar patterns in metabolomic data as that extracted from quantitative data.

Metabolomic Responses of Guard Cells and Mesophyll Cells to Bicarbonate

PubMed Central

Misra, Biswapriya B.; de Armas, Evaldo; Tong, Zhaohui; Chen, Sixue

2015-01-01

Anthropogenic CO2 presently at 400 ppm is expected to reach 550 ppm in 2050, an increment expected to affect plant growth and productivity. Paired stomatal guard cells (GCs) are the gate-way for water, CO2, and pathogen, while mesophyll cells (MCs) represent the bulk cell-type of green leaves mainly for photosynthesis. We used the two different cell types, i.e., GCs and MCs from canola (Brassica napus) to profile metabolomic changes upon increased CO2 through supplementation with bicarbonate (HCO3 -). Two metabolomics platforms enabled quantification of 268 metabolites in a time-course study to reveal short-term responses. The HCO3 - responsive metabolomes of the cell types differed in their responsiveness. The MCs demonstrated increased amino acids, phenylpropanoids, redox metabolites, auxins and cytokinins, all of which were decreased in GCs in response to HCO3 -. In addition, the GCs showed differential increases of primary C-metabolites, N-metabolites (e.g., purines and amino acids), and defense-responsive pathways (e.g., alkaloids, phenolics, and flavonoids) as compared to the MCs, indicating differential C/N homeostasis in the cell-types. The metabolomics results provide insights into plant responses and crop productivity under future climatic changes where elevated CO2 conditions are to take center-stage. PMID:26641455

A detailed view on sulphur metabolism at the cellular and whole-plant level illustrates challenges in metabolite flux analyses.

PubMed

Rennenberg, Heinz; Herschbach, Cornelia

2014-11-01

Understanding the dynamics of physiological process in the systems biology era requires approaches at the genome, transcriptome, proteome, and metabolome levels. In this context, metabolite flux experiments have been used in mapping metabolite pathways and analysing metabolic control. In the present review, sulphur metabolism was taken to illustrate current challenges of metabolic flux analyses. At the cellular level, restrictions in metabolite flux analyses originate from incomplete knowledge of the compartmentation network of metabolic pathways. Transport of metabolites through membranes is usually not considered in flux experiments but may be involved in controlling the whole pathway. Hence, steady-state and snapshot readings need to be expanded to time-course studies in combination with compartment-specific metabolite analyses. Because of species-specific differences, differences between tissues, and stress-related responses, the quantitative significance of different sulphur sinks has to be elucidated; this requires the development of methods for whole-sulphur metabolome approaches. Different cell types can contribute to metabolite fluxes to different extents at the tissue and organ level. Cell type-specific analyses are needed to characterize these contributions. Based on such approaches, metabolite flux analyses can be expanded to the whole-plant level by considering long-distance transport and, thus, the interaction of roots and the shoot in metabolite fluxes. However, whole-plant studies need detailed empirical and mathematical modelling that have to be validated by experimental analyses. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Application of a Smartphone Metabolomics Platform to the Authentication of Schisandra sinensis.

PubMed

Kwon, Hyuk Nam; Phan, Hong-Duc; Xu, Wen Jun; Ko, Yoon-Joo; Park, Sunghyouk

2016-05-01

Herbal medicines have been used for a long time all around the world. Since the quality of herbal preparations depends on the source of herbal materials, there has been a strong need to develop methods to correctly identify the origin of materials. To develop a smartphone metabolomics platform as a simpler and low-cost alternative for the identification of herbal material source. Schisandra sinensis extracts from Korea and China were prepared. The visible spectra of all samples were measured by a smartphone spectrometer platform. This platform included all the necessary measures built-in for the metabolomics research: data acquisition, processing, chemometric analysis and visualisation of the results. The result of the smartphone metabolomics platform was compared to that of NMR-based metabolomics, suggesting the feasibility of smartphone platform in metabolomics research. The smartphone metabolomics platform gave similar results to the NMR method, showing good separation between Korean and Chinese materials and correct predictability for all test samples. With its accuracy and advantages of affordability, user-friendliness, and portability, the smartphone metabolomics platform could be applied to the authentication of other medicinal plants. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Standard Reporting Requirements for Biological Samples in Metabolomics Experiments: Environmental Context

EPA Science Inventory

Metabolomic technologies are increasingly being applied to study biological questions in a range of different settings from clinical through to environmental. As with other high-throughput technologies, such as those used in transcriptomics and proteomics, metabolomics continues...

Metabolome analysis for discovering biomarkers of gastroenterological cancer.

PubMed

Suzuki, Makoto; Nishiumi, Shin; Matsubara, Atsuki; Azuma, Takeshi; Yoshida, Masaru

2014-09-01

Improvements in analytical technologies have made it possible to rapidly determine the concentrations of thousands of metabolites in any biological sample, which has resulted in metabolome analysis being applied to various types of research, such as clinical, cell biology, and plant/food science studies. The metabolome represents all of the end products and by-products of the numerous complex metabolic pathways operating in a biological system. Thus, metabolome analysis allows one to survey the global changes in an organism's metabolic profile and gain a holistic understanding of the changes that occur in organisms during various biological processes, e.g., during disease development. In clinical metabolomic studies, there is a strong possibility that differences in the metabolic profiles of human specimens reflect disease-specific states. Recently, metabolome analysis of biofluids, e.g., blood, urine, or saliva, has been increasingly used for biomarker discovery and disease diagnosis. Mass spectrometry-based techniques have been extensively used for metabolome analysis because they exhibit high selectivity and sensitivity during the identification and quantification of metabolites. Here, we describe metabolome analysis using liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and capillary electrophoresis-mass spectrometry. Furthermore, the findings of studies that attempted to discover biomarkers of gastroenterological cancer are also outlined. Finally, we discuss metabolome analysis-based disease diagnosis. Copyright © 2014 Elsevier B.V. All rights reserved.

Metabolomics for in situ environmental monitoring of surface waters impacted by contaminants from both point and non-point sources

EPA Science Inventory

We investigated the efficacy of metabolomics for field-monitoring of fish exposed to waste water treatment plant (WWTP) effluents and non-point sources of chemical contamination. Lab-reared male fathead minnows (Pimephales promelas, FHM) were held in mobile monitoring units and e...

Monitoring Ecological Impacts of Environmental Surface ...

EPA Pesticide Factsheets

Optimized cell-based metabolomics has been used to study the impacts of contaminants in surface waters on human and fish metabolomes. This method has proven to be resource- and time-effective, as well as sustainable for long term and large scale studies. In the current study, cell-based metabolomics is used to investigate the impacts of contaminants in surface waters on biological pathways in human and ecologically relevant cell lines. Water samples were collected from stream sites nationwide, where significant impacts have been estimated from the most potentially contaminated sources (i.e. waste water treatment plants, concentrated animal feeding operations, mining operations, and plant-based agricultural operations that use intensive chemical applications). Zebrafish liver cells (ZFL) were used to study exposure impacts on in vitro metabolomes. In addition, a small number of water samples were studied using two human cell lines (liver cells, HepG2 and brain cells, LN229). The cellular metabolites were profiled by nuclear magnetic resonance (NMR) spectroscopy and gas chromatography mass spectrometry (GC-MS). Detailed methods and results will be reported. Presented at SETAC North America 37th Annual Meeting

A comparative UPLC-Q/TOF-MS-based metabolomics approach for distinguishing Zingiber officinale Roscoe of two geographical origins.

PubMed

Mais, Enos; Alolga, Raphael N; Wang, Shi-Lei; Linus, Loveth O; Yin, Xiaojin; Qi, Lian-Wen

2018-02-01

Ginger, the rhizome of Zingiber officinale Roscoe, is a popular spice used in the food, beverage and confectionary industries. In this study, we report an untargeted UPLC-Q/TOF-MS-based metabolomics approach for comprehensively discriminating between ginger from two geographical locations, Ghana in West Africa and China. Forty batches of fresh ginger from both countries were discriminated using principal component analysis and orthogonal partial least squares discrimination analysis. Sixteen differential metabolites were identified between the gingers from the two geographical locations, six of which were identified as the marker compounds responsible for the discrimination. Our study highlights the essence and predictive power of metabolomics in detecting minute differences in same varieties of plants/plant samples based on the levels and composition of their metabolites. Copyright © 2017 Elsevier Ltd. All rights reserved.

Classification using NMR-based metabolomics of Sophora flavescens grown in Japan and China.

PubMed

Suzuki, Ryuichiro; Ikeda, Yuriko; Yamamoto, Akari; Saima, Toyoe; Fujita, Tatsuya; Fukuda, Tatsuo; Fukuda, Eriko; Baba, Masaki; Okada, Yoshihito; Shirataki, Yoshiaki

2012-11-01

We demonstrate that NMR-based metabolomics can be used to identify the country of growth (Japan or China) of Sophora flavescens plants. Principle Component Analysis (PCA) conducted on extracts of S. flavescens grown in China provided data distinct from that of extracts of plants grown in Japan. Loading plot analysis showed signals characteristic of Japanese S. flavescens. NMR analyses showed these signals to be due to kurarinol (1) and kushenol H (2). These compounds were confirmed by HPLC analysis to be distinctive markers for Japanese S. flavescens.

LC-MS metabolic profiling of Arabidopsis thaliana plant leaves and cell cultures: optimization of pre-LC-MS procedure parameters.

PubMed

t'Kindt, Ruben; De Veylder, Lieven; Storme, Michael; Deforce, Dieter; Van Bocxlaer, Jan

2008-08-01

This study treats the optimization of methods for homogenizing Arabidopsis thaliana plant leaves as well as cell cultures, and extracting their metabolites for metabolomics analysis by conventional liquid chromatography electrospray ionization mass spectrometry (LC-ESI/MS). Absolute recovery, process efficiency and procedure repeatability have been compared between different pre-LC-MS homogenization/extraction procedures through the use of samples fortified before extraction with a range of representative metabolites. Hereby, the magnitude of the matrix effect observed in the ensuing LC-MS based metabolomics analysis was evaluated. Based on relative recovery and repeatability of key metabolites, comprehensiveness of extraction (number of m/z-retention time pairs) and clean-up potential of the approach (minimum matrix effects), the most appropriate sample pre-treatment was adopted. It combines liquid nitrogen homogenization for plant leaves with thermomixer based extraction using MeOH/H(2)O 80/20. As such, an efficient and highly reproducible LC-MS plant metabolomics set-up is achieved, as illustrated by the obtained results for both LC-MS (8.88%+/-5.16 versus 7.05%+/-4.45) and technical variability (12.53%+/-11.21 versus 9.31%+/-6.65) data in a comparative investigation of A. thaliana plant leaves and cell cultures, respectively.

CAMERA: An integrated strategy for compound spectra extraction and annotation of LC/MS data sets

PubMed Central

Kuhl, Carsten; Tautenhahn, Ralf; Böttcher, Christoph; Larson, Tony R.; Neumann, Steffen

2013-01-01

Liquid chromatography coupled to mass spectrometry is routinely used for metabolomics experiments. In contrast to the fairly routine and automated data acquisition steps, subsequent compound annotation and identification require extensive manual analysis and thus form a major bottle neck in data interpretation. Here we present CAMERA, a Bioconductor package integrating algorithms to extract compound spectra, annotate isotope and adduct peaks, and propose the accurate compound mass even in highly complex data. To evaluate the algorithms, we compared the annotation of CAMERA against a manually defined annotation for a mixture of known compounds spiked into a complex matrix at different concentrations. CAMERA successfully extracted accurate masses for 89.7% and 90.3% of the annotatable compounds in positive and negative ion mode, respectively. Furthermore, we present a novel annotation approach that combines spectral information of data acquired in opposite ion modes to further improve the annotation rate. We demonstrate the utility of CAMERA in two different, easily adoptable plant metabolomics experiments, where the application of CAMERA drastically reduced the amount of manual analysis. PMID:22111785

Novel chemistry of invasive plants: exotic species have more unique metabolomic profiles than native congeners.

PubMed

Macel, Mirka; de Vos, Ric C H; Jansen, Jeroen J; van der Putten, Wim H; van Dam, Nicole M

2014-07-01

It is often assumed that exotic plants can become invasive when they possess novel secondary chemistry compared with native plants in the introduced range. Using untargeted metabolomic fingerprinting, we compared a broad range of metabolites of six successful exotic plant species and their native congeners of the family Asteraceae. Our results showed that plant chemistry is highly species-specific and diverse among both exotic and native species. Nonetheless, the exotic species had on average a higher total number of metabolites and more species-unique metabolites compared with their native congeners. Herbivory led to an overall increase in metabolites in all plant species. Generalist herbivore performance was lower on most of the exotic species compared with the native species. We conclude that high chemical diversity and large phytochemical uniqueness of the exotic species could be indicative of biological invasion potential.

Plants' Metabolites as Potential Antiobesity Agents

PubMed Central

Gooda Sahib, Najla; Saari, Nazamid; Ismail, Amin; Khatib, Alfi; Mahomoodally, Fawzi; Abdul Hamid, Azizah

2012-01-01

Obesity and obesity-related complications are on the increase both in the developed and developing world. Since existing pharmaceuticals fail to come up with long-term solutions to address this issue, there is an ever-pressing need to find and develop new drugs and alternatives. Natural products, particularly medicinal plants, are believed to harbor potential antiobesity agents that can act through various mechanisms either by preventing weight gain or promoting weight loss amongst others. The inhibition of key lipid and carbohydrate hydrolyzing and metabolizing enzymes, disruption of adipogenesis, and modulation of its factors or appetite suppression are some of the plethora of targeted approaches to probe the antiobesity potential of medicinal plants. A new technology such as metabolomics, which deals with the study of the whole metabolome, has been identified to be a promising technique to probe the progression of diseases, elucidate their pathologies, and assess the effects of natural health products on certain pathological conditions. This has been applied to drug research, bone health, and to a limited extent to obesity research. This paper thus endeavors to give an overview of those plants, which have been reported to have antiobesity effects and highlight the potential and relevance of metabolomics in obesity research. PMID:22666121

Linking the morphological and metabolomic response of Lactuca sativa L exposed to emerging contaminants using GC × GC-MS and chemometric tools.

PubMed

Hurtado, Carlos; Parastar, Hadi; Matamoros, Víctor; Piña, Benjamín; Tauler, Romà; Bayona, Josep M

2017-07-26

The occurrence of contaminants of emerging concern (CECs) in irrigation waters (up to low μg L -1 ) and irrigated crops (ng g -1 in dry weight) has been reported, but the linkage between plant morphological changes and plant metabolomic response has not yet been addressed. In this study, a non-targeted metabolomic analysis was performed on lettuce (Lactuca sativa L) exposed to 11 CECs (pharmaceuticals, personal care products, anticorrosive agents and surfactants) by irrigation. The plants were watered with different CEC concentrations (0-50 µg L -1 ) for 34 days under controlled conditions and then harvested, extracted, derivatised and analysed by comprehensive two-dimensional gas chromatography coupled to a time-of-flight mass spectrometer (GC × GC-TOFMS). The resulting raw data were analysed using multivariate curve resolution (MCR) and partial least squares (PLS) methods. The metabolic response indicates that exposure to CECs at environmentally relevant concentrations (0.05 µg L -1 ) can cause significant metabolic alterations in plants (carbohydrate metabolism, the citric acid cycle, pentose phosphate pathway and glutathione pathway) linked to changes in morphological parameters (leaf height, stem width) and chlorophyll content.

Plant defense compounds: systems approaches to metabolic analysis.

PubMed

Kliebenstein, Daniel J

2012-01-01

Systems biology attempts to answer biological questions by integrating across diverse genomic data sets. With the increasing ability to conduct genomics experiments, this integrative approach is being rapidly applied across numerous biological research communities. One of these research communities investigates how plants utilize secondary metabolites or defense metabolites to defend against attack by pathogens and other biotic organisms. This use of systems biology to integrate across transcriptomics, metabolomics, and genomics is significantly enhancing the rate of discovery of genes, metabolites, and bioactivities for plant defense compounds as well as extending our knowledge of how these compounds are regulated. Plant defense compounds are also providing a unique proving platform to develop new approaches that enhance the ability to conduct systems biology with existing and previously unforseen genomics data sets. This review attempts to illustrate both how systems biology is helping the study of plant defense compounds and vice versa.

Opposite metabolic responses of shoots and roots to drought

NASA Astrophysics Data System (ADS)

Gargallo-Garriga, Albert; Sardans, Jordi; Pérez-Trujillo, Míriam; Rivas-Ubach, Albert; Oravec, Michal; Vecerova, Kristyna; Urban, Otmar; Jentsch, Anke; Kreyling, Juergen; Beierkuhnlein, Carl; Parella, Teodor; Peñuelas, Josep

2014-10-01

Shoots and roots are autotrophic and heterotrophic organs of plants with different physiological functions. Do they have different metabolomes? Do their metabolisms respond differently to environmental changes such as drought? We used metabolomics and elemental analyses to answer these questions. First, we show that shoots and roots have different metabolomes and nutrient and elemental stoichiometries. Second, we show that the shoot metabolome is much more variable among species and seasons than is the root metabolome. Third, we show that the metabolic response of shoots to drought contrasts with that of roots; shoots decrease their growth metabolism (lower concentrations of sugars, amino acids, nucleosides, N, P, and K), and roots increase it in a mirrored response. Shoots are metabolically deactivated during drought to reduce the consumption of water and nutrients, whereas roots are metabolically activated to enhance the uptake of water and nutrients, together buffering the effects of drought, at least at the short term.

Metabolomic Analysis of Alfalfa (Medicago sativa L.) Root-Symbiotic Rhizobia Responses under Alkali Stress.

PubMed

Song, Tingting; Xu, Huihui; Sun, Na; Jiang, Liu; Tian, Pu; Yong, Yueyuan; Yang, Weiwei; Cai, Hua; Cui, Guowen

2017-01-01

Alkaline salts (e.g., NaHCO 3 and Na 2 CO 3 ) causes more severe morphological and physiological damage to plants than neutral salts (e.g., NaCl and Na 2 SO 4 ) due to differences in pH. The mechanism by which plants respond to alkali stress is not fully understood, especially in plants having symbotic relationships such as alfalfa ( Medicago sativa L.). Therefore, a study was designed to evaluate the metabolic response of the root-nodule symbiosis in alfalfa under alkali stress using comparative metabolomics. Rhizobium-nodulized (RI group) and non-nodulized (NI group) alfalfa roots were treated with 200 mmol/L NaHCO 3 and, roots samples were analyzed for malondialdehydyde (MDA), proline, glutathione (GSH), superoxide dismutase (SOD), and peroxidase (POD) content. Additionally, metabolite profiling was conducted using gas chromatography combined with time-of-flight mass spectrometry (GC/TOF-MS). Phenotypically, the RI alfalfa exhibited a greater resistance to alkali stress than the NI plants examined. Physiological analysis and metabolic profiling revealed that RI plants accumulated more antioxidants (SOD, POD, GSH), osmolytes (sugar, glycols, proline), organic acids (succinic acid, fumaric acid, and alpha-ketoglutaric acid), and metabolites that are involved in nitrogen fixation. Our pairwise metabolomics comparisons revealed that RI alfalfa plants exhibited a distinct metabolic profile associated with alkali putative tolerance relative to NI alfalfa plants. Data provide new information about the relationship between non-nodulized, rhizobium-nodulized alfalfa and alkali resistance.

Metabolomic Analysis of Alfalfa (Medicago sativa L.) Root-Symbiotic Rhizobia Responses under Alkali Stress

PubMed Central

Song, Tingting; Xu, Huihui; Sun, Na; Jiang, Liu; Tian, Pu; Yong, Yueyuan; Yang, Weiwei; Cai, Hua; Cui, Guowen

2017-01-01

Alkaline salts (e.g., NaHCO3 and Na2CO3) causes more severe morphological and physiological damage to plants than neutral salts (e.g., NaCl and Na2SO4) due to differences in pH. The mechanism by which plants respond to alkali stress is not fully understood, especially in plants having symbotic relationships such as alfalfa (Medicago sativa L.). Therefore, a study was designed to evaluate the metabolic response of the root-nodule symbiosis in alfalfa under alkali stress using comparative metabolomics. Rhizobium-nodulized (RI group) and non-nodulized (NI group) alfalfa roots were treated with 200 mmol/L NaHCO3 and, roots samples were analyzed for malondialdehydyde (MDA), proline, glutathione (GSH), superoxide dismutase (SOD), and peroxidase (POD) content. Additionally, metabolite profiling was conducted using gas chromatography combined with time-of-flight mass spectrometry (GC/TOF-MS). Phenotypically, the RI alfalfa exhibited a greater resistance to alkali stress than the NI plants examined. Physiological analysis and metabolic profiling revealed that RI plants accumulated more antioxidants (SOD, POD, GSH), osmolytes (sugar, glycols, proline), organic acids (succinic acid, fumaric acid, and alpha-ketoglutaric acid), and metabolites that are involved in nitrogen fixation. Our pairwise metabolomics comparisons revealed that RI alfalfa plants exhibited a distinct metabolic profile associated with alkali putative tolerance relative to NI alfalfa plants. Data provide new information about the relationship between non-nodulized, rhizobium-nodulized alfalfa and alkali resistance. PMID:28744296

Metabolomic response of Calotropis procera growing in the desert to changes in water availability.

PubMed

Ramadan, Ahmed; Sabir, Jamal S M; Alakilli, Saleha Y M; Shokry, Ahmed M; Gadalla, Nour O; Edris, Sherif; Al-Kordy, Magdy A; Al-Zahrani, Hassan S; El-Domyati, Fotouh M; Bahieldin, Ahmed; Baker, Neil R; Willmitzer, Lothar; Irgang, Susann

2014-01-01

Water availability is a major limitation for agricultural productivity. Plants growing in severe arid climates such as deserts provide tools for studying plant growth and performance under extreme drought conditions. The perennial species Calotropis procera used in this study is a shrub growing in many arid areas which has an exceptional ability to adapt and be productive in severe arid conditions. We describe the results of studying the metabolomic response of wild C procera plants growing in the desert to a one time water supply. Leaves of C. procera plants were taken at three time points before and 1 hour, 6 hours and 12 hours after watering and subjected to a metabolomics and lipidomics analysis. Analysis of the data reveals that within one hour after watering C. procera has already responded on the metabolic level to the sudden water availability as evidenced by major changes such as increased levels of most amino acids, a decrease in sucrose, raffinose and maltitol, a decrease in storage lipids (triacylglycerols) and an increase in membrane lipids including photosynthetic membranes. These changes still prevail at the 6 hour time point after watering however 12 hours after watering the metabolomics data are essentially indistinguishable from the prewatering state thus demonstrating not only a rapid response to water availability but also a rapid response to loss of water. Taken together these data suggest that the ability of C. procera to survive under the very harsh drought conditions prevailing in the desert might be associated with its rapid adjustments to water availability and losses.

Metabolomic Response of Calotropis procera Growing in the Desert to Changes in Water Availability

PubMed Central

Ramadan, Ahmed; Sabir, Jamal S. M.; Alakilli, Saleha Y. M.; Shokry, Ahmed M.; Gadalla, Nour O.; Edris, Sherif; Al-Kordy, Magdy A.; Al-Zahrani, Hassan S.; El-Domyati, Fotouh M.; Bahieldin, Ahmed; Baker, Neil R.; Willmitzer, Lothar; Irgang, Susann

2014-01-01

Water availability is a major limitation for agricultural productivity. Plants growing in severe arid climates such as deserts provide tools for studying plant growth and performance under extreme drought conditions. The perennial species Calotropis procera used in this study is a shrub growing in many arid areas which has an exceptional ability to adapt and be productive in severe arid conditions. We describe the results of studying the metabolomic response of wild C procera plants growing in the desert to a one time water supply. Leaves of C. procera plants were taken at three time points before and 1 hour, 6 hours and 12 hours after watering and subjected to a metabolomics and lipidomics analysis. Analysis of the data reveals that within one hour after watering C. procera has already responded on the metabolic level to the sudden water availability as evidenced by major changes such as increased levels of most amino acids, a decrease in sucrose, raffinose and maltitol, a decrease in storage lipids (triacylglycerols) and an increase in membrane lipids including photosynthetic membranes. These changes still prevail at the 6 hour time point after watering however 12 hours after watering the metabolomics data are essentially indistinguishable from the prewatering state thus demonstrating not only a rapid response to water availability but also a rapid response to loss of water. Taken together these data suggest that the ability of C. procera to survive under the very harsh drought conditions prevailing in the desert might be associated with its rapid adjustments to water availability and losses. PMID:24520340

An introduction to metabolomics and its potential application in veterinary science.

PubMed

Jones, Oliver A H; Cheung, Victoria L

2007-10-01

Metabolomics has been found to be applicable to a wide range of fields, including the study of gene function, toxicology, plant sciences, environmental analysis, clinical diagnostics, nutrition, and the discrimination of organism genotypes. This approach combines high-throughput sample analysis with computer-assisted multivariate pattern-recognition techniques. It is increasingly being deployed in toxico- and pharmacokinetic studies in the pharmaceutical industry, especially during the safety assessment of candidate drugs in human medicine. However, despite the potential of this technique to reduce both costs and the numbers of animals used for research, examples of the application of metabolomics in veterinary research are, thus far, rare. Here we give an introduction to metabolomics and discuss its potential in the field of veterinary science.

Transcriptional and metabolomic analysis of Ascophyllum nodosum mediated freezing tolerance in Arabidopsis thaliana

PubMed Central

2012-01-01

Background We have previously shown that lipophilic components (LPC) of the brown seaweed Ascophyllum nodosum (ANE) improved freezing tolerance in Arabidopsis thaliana. However, the mechanism(s) of this induced freezing stress tolerance is largely unknown. Here, we investigated LPC induced changes in the transcriptome and metabolome of A. thaliana undergoing freezing stress. Results Gene expression studies revealed that the accumulation of proline was mediated by an increase in the expression of the proline synthesis genes P5CS1 and P5CS2 and a marginal reduction in the expression of the proline dehydrogenase (ProDH) gene. Moreover, LPC application significantly increased the concentration of total soluble sugars in the cytosol in response to freezing stress. Arabidopsis sfr4 mutant plants, defective in the accumulation of free sugars, treated with LPC, exhibited freezing sensitivity similar to that of untreated controls. The 1H NMR metabolite profile of LPC-treated Arabidopsis plants exposed to freezing stress revealed a spectrum dominated by chemical shifts (δ) representing soluble sugars, sugar alcohols, organic acids and lipophilic components like fatty acids, as compared to control plants. Additionally, 2D NMR spectra suggested an increase in the degree of unsaturation of fatty acids in LPC treated plants under freezing stress. These results were supported by global transcriptome analysis. Transcriptome analysis revealed that LPC treatment altered the expression of 1113 genes (5%) in comparison with untreated plants. A total of 463 genes (2%) were up regulated while 650 genes (3%) were down regulated. Conclusion Taken together, the results of the experiments presented in this paper provide evidence to support LPC mediated freezing tolerance enhancement through a combination of the priming of plants for the increased accumulation of osmoprotectants and alteration of cellular fatty acid composition. PMID:23171218

Web-based resources for mass-spectrometry-based metabolomics: a user's guide.

PubMed

Tohge, Takayuki; Fernie, Alisdair R

2009-03-01

In recent years, a plethora of web-based tools aimed at supporting mass-spectrometry-based metabolite profiling and metabolomics applications have appeared. Given the huge hurdles presented by the chemical diversity and dynamic range of the metabolites present in the plant kingdom, profiling the levels of a broad range of metabolites is highly challenging. Given the scale and costs involved in defining the plant metabolome, it is imperative that data are effectively shared between laboratories pursuing this goal. However, ensuring accurate comparison of samples run on the same machine within the same laboratory, let alone cross-machine and cross-laboratory comparisons, requires both careful experimentation and data interpretation. In this review, we present an overview of currently available software that aids either in peak identification or in the related field of peak alignment as well as those with utility in defining structural information of compounds and metabolic pathways.

Livestock metabolomics and the livestock metabolome: A systematic review

PubMed Central

Guo, An Chi; Sajed, Tanvir; Steele, Michael A.; Plastow, Graham S.; Wishart, David S.

2017-01-01

Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular “omics” approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed. PMID:28531195

Livestock metabolomics and the livestock metabolome: A systematic review.

PubMed

Goldansaz, Seyed Ali; Guo, An Chi; Sajed, Tanvir; Steele, Michael A; Plastow, Graham S; Wishart, David S

2017-01-01

Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular "omics" approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed.

Metabolomics for undergraduates: Identification and pathway assignment of mitochondrial metabolites.

PubMed

Marques, Ana Patrícia; Serralheiro, Maria Luisa; Ferreira, António E N; Freire, Ana Ponces; Cordeiro, Carlos; Silva, Marta Sousa

2016-01-01

Metabolomics is a key discipline in systems biology, together with genomics, transcriptomics, and proteomics. In this omics cascade, the metabolome represents the biochemical products that arise from cellular processes and is often regarded as the final response of a biological system to environmental or genetic changes. The overall screening approach to identify all the metabolites in a given biological system is called metabolic fingerprinting. Using high-resolution and high-mass accuracy mass spectrometry, large metabolome coverage, sensitivity, and specificity can be attained. Although the theoretical concepts of this methodology are usually provided in life-science programs, hands-on laboratory experiments are not usually accessible to undergraduate students. Even if the instruments are available, there are not simple laboratory protocols created specifically for teaching metabolomics. We designed a straightforward hands-on laboratory experiment to introduce students to this methodology, relating it to biochemical knowledge through metabolic pathway mapping of the identified metabolites. This study focuses on mitochondrial metabolomics since mitochondria have a well-known, medium-sized cellular sub-metabolome. These features facilitate both data processing and pathway mapping. In this experiment, students isolate mitochondria from potatoes, extract the metabolites, and analyze them by high-resolution mass spectrometry (using an FT-ICR mass spectrometer). The resulting mass list is submitted to an online program for metabolite identification, and compounds associated with mitochondrial pathways can be highlighted in a metabolic network map. © 2015 The International Union of Biochemistry and Molecular Biology.

A Unique Model Platform for C4 Plant Systems and Synthetic Biology

DTIC Science & Technology

2015-12-10

International Conference in Bioinformatics , Sydney, Australia, July 31 - August 2, 2014.  Nielsen LK (2015) Genome scale metabolic and regulatory...the comparison of transcriptome proteome and central metabolome in mature and immature tissue. Preliminary data were obtained suggesting successful...guide the comparison of transcriptome, proteome and central metabolome in mature and immature tissue. Preliminary data were obtained suggesting

Phytochemical genomics--a new trend.

PubMed

Saito, Kazuki

2013-06-01

Phytochemical genomics is a recently emerging field, which investigates the genomic basis of the synthesis and function of phytochemicals (plant metabolites), particularly based on advanced metabolomics. The chemical diversity of the model plant Arabidopsis thaliana is larger than previously expected, and the gene-to-metabolite correlations have been elucidated mostly by an integrated analysis of transcriptomes and metabolomes. For example, most genes involved in the biosynthesis of flavonoids in Arabidopsis have been characterized by this method. A similar approach has been applied to the functional genomics for production of phytochemicals in crops and medicinal plants. Great promise is seen in metabolic quantitative loci analysis in major crops such as rice and tomato, and identification of novel genes involved in the biosynthesis of bioactive specialized metabolites in medicinal plants. Copyright © 2013 The Author. Published by Elsevier Ltd.. All rights reserved.

Acclimation to UV-B radiation and visible light in Lactuca sativa involves up-regulation of photosynthetic performance and orchestration of metabolome-wide responses.

PubMed

Wargent, J J; Nelson, B C W; McGhie, T K; Barnes, P W

2015-05-01

UV-B radiation is often viewed as a source of stress for higher plants. In particular, photosynthetic function has been described as a common target for UV-B impairment; yet as our understanding of UV-B photomorphogenesis increases, there are opportunities to expand the emerging paradigm of regulatory UV response. Lactuca sativa is an important dietary crop species and is often subjected to rapid sunlight exposure at field transfer. Acclimation to UV-B and visible light conditions in L. sativa was dissected using gas exchange and chlorophyll fluorescence measurements, in addition to non-destructive assessments of UV epidermal shielding (SUV ). After UV-B treatment, seedlings were subjected to wide-range metabolomic analysis using liquid chromatography hybrid quadrupole time-of-flight high-resolution mass spectrometry (LC-QTOF-HRMS). During the acclimation period, net photosynthetic rate increased in UV-treated plants, epidermal UV shielding increased in both subsets of plants transferred to the acclimatory conditions (UV+/UV- plants) and Fv /Fm declined slightly in UV+/UV- plants. Metabolomic analysis revealed that a key group of secondary compounds was up-regulated by higher light conditions, yet several of these compounds were elevated further by UV-B radiation. In conclusion, acclimation to UV-B radiation involves co-protection from the effects of visible light, and responses to UV-B radiation at a photosynthetic level may not be consistently viewed as damaging to plant development. © 2014 John Wiley & Sons Ltd.

Profiling of Altered Metabolomic States in Nicotiana tabacum Cells Induced by Priming Agents

PubMed Central

Mhlongo, Msizi I.; Steenkamp, Paul A.; Piater, Lizelle A.; Madala, Ntakadzeni E.; Dubery, Ian A.

2016-01-01

Metabolomics has developed into a valuable tool for advancing our understanding of plant metabolism. Plant innate immune defenses can be activated and enhanced so that, subsequent to being pre-sensitized, plants are able to launch a stronger and faster defense response upon exposure to pathogenic microorganisms, a phenomenon known as priming. Here, three contrasting chemical activators, namely acibenzolar-S-methyl, azelaic acid and riboflavin, were used to induce a primed state in Nicotiana tabacum cells. Identified biomarkers were then compared to responses induced by three phytohormones—abscisic acid, methyljasmonate, and salicylic acid. Altered metabolomes were studied using a metabolite fingerprinting approach based on liquid chromatography and mass spectrometry. Multivariate data models indicated that these inducers cause time-dependent metabolic perturbations in the cultured cells and revealed biomarkers of which the levels are affected by these agents. A total of 34 metabolites were annotated from the mass spectral data and online databases. Venn diagrams were used to identify common biomarkers as well as those unique to a specific agent. Results implicate 20 cinnamic acid derivatives conjugated to (i) quinic acid (chlorogenic acids), (ii) tyramine, (iii) polyamines, or (iv) glucose as discriminatory biomarkers of priming in tobacco cells. Functional roles for most of these metabolites in plant defense responses could thus be proposed. Metabolites induced by the activators belong to the early phenylpropanoid pathway, which indicates that different stimuli can activate similar pathways but with different metabolite fingerprints. Possible linkages to phytohormone-dependent pathways at a metabolomic level were indicated in the case of cells treated with salicylic acid and methyljasmonate. The results contribute to a better understanding of the priming phenomenon and advance our knowledge of cinnamic acid derivatives as versatile defense metabolites. PMID:27803705

Recent breakthroughs in metabolomics promise to reveal the cryptic chemical traits that mediate plant community composition, character evolution and lineage diversification.

PubMed

Sedio, Brian E

2017-05-01

Contents 952 I. 952 II. 953 III. 955 IV. 956 V. 957 957 References 957 SUMMARY: Much of our understanding of the mechanisms by which biotic interactions shape plant communities has been constrained by the methods available to study the diverse secondary chemistry that defines plant relationships with other organisms. Recent innovations in analytical chemistry and bioinformatics promise to reveal the cryptic chemical traits that mediate plant ecology and evolution by facilitating simultaneous structural comparisons of hundreds of unknown molecules to each other and to libraries of known compounds. Here, I explore the potential for mass spectrometry and nuclear magnetic resonance metabolomics to enable unprecedented tests of seminal, but largely untested hypotheses that propose a fundamental role for plant chemical defenses against herbivores and pathogens in the evolutionary origins and ecological coexistence of plant species diversity. © 2017 The Author. New Phytologist © 2017 New Phytologist Trust.

Metabolomics: A Primer.

PubMed

Liu, Xiaojing; Locasale, Jason W

2017-04-01

Metabolomics generates a profile of small molecules that are derived from cellular metabolism and can directly reflect the outcome of complex networks of biochemical reactions, thus providing insights into multiple aspects of cellular physiology. Technological advances have enabled rapid and increasingly expansive data acquisition with samples as small as single cells; however, substantial challenges in the field remain. In this primer we provide an overview of metabolomics, especially mass spectrometry (MS)-based metabolomics, which uses liquid chromatography (LC) for separation, and discuss its utilities and limitations. We identify and discuss several areas at the frontier of metabolomics. Our goal is to give the reader a sense of what might be accomplished when conducting a metabolomics experiment, now and in the near future. Copyright © 2017 Elsevier Ltd. All rights reserved.

The plant ontology as a tool for comparative plant anatomy and genomic analyses

USDA-ARS?s Scientific Manuscript database

Plant science is now a major player in the fields of genomics, gene expression analysis, phenomics and metabolomics. Recent advances in sequencing technologies have led to a windfall of data, with new species being added rapidly to the list of species whose genomes have been decoded. The Plant Ontol...

Challenges in integrating component level technology and system level information from Ayurveda: Insights from NMR phytometabolomics and anti-HIV potential of select Ayurvedic medicinal plants.

PubMed

Jayasundar, Rama; Ghatak, Somenath; Makhdoomi, Muzamil Ashraf; Luthra, Kalpana; Singh, Aruna; Velpandian, Thirumurthy

2018-01-03

Information from Ayurveda meeting the analytical challenges of modern technology is an area of immense relevance. Apart from the cerebral task of bringing together two different viewpoints, the question at the pragmatic level remains 'who benefits whom'. The aim is to highlight the challenges in integration of information (Ayurvedic) and technology using test examples of Nuclear Magnetic Resonance (NMR) metabolomics and anti-HIV-1 potential of select Ayurvedic medicinal plants. The other value added objective is implications and relevance of such work for Ayurveda. Six medicinal plants (Azadirachta indica, Tinospora cordifolia, Swertia chirata, Terminalia bellerica, Zingiber officinale and Symplocos racemosa) were studied using high resolution proton NMR spectroscopy based metabolomics and also evaluated for anti-HIV-1 activity on three pseudoviruses (ZM53 M.PB12, ZM109F.PB4, RHPA 4259.7). Of the six plants, T.bellerica and Z.officinale showed minimum cell cytotoxicity and maximum anti-HIV-1 potential. T.bellerica was effective against all the three HIV-1 pseudoviruses. Untargeted NMR profiling and multivariate analyses demonstrated that the six plants, all of which had different Ayurvedic pharmacological properties, showed maximum differences in the aromatic region of the spectra. The work adds onto the list of potential plants for anti-HIV-1 drug molecules. At the same time, it has drawn attention to the different perspectives of Ayurveda and Western medicine underscoring the inherent limitations of conceptual bilinguism between the two systems, especially in the context of medicinal plants. The study has also highlighted the potential of NMR metabolomics in study of plant extracts as used in Ayurveda. Copyright © 2017 Transdisciplinary University, Bangalore and World Ayurveda Foundation. Published by Elsevier B.V. All rights reserved.

MVAPACK: A Complete Data Handling Package for NMR Metabolomics

PubMed Central

2015-01-01

Data handling in the field of NMR metabolomics has historically been reliant on either in-house mathematical routines or long chains of expensive commercial software. Thus, while the relatively simple biochemical protocols of metabolomics maintain a low barrier to entry, new practitioners of metabolomics experiments are forced to either purchase expensive software packages or craft their own data handling solutions from scratch. This inevitably complicates the standardization and communication of data handling protocols in the field. We report a newly developed open-source platform for complete NMR metabolomics data handling, MVAPACK, and describe its application on an example metabolic fingerprinting data set. PMID:24576144

Effects of MeJA on Arabidopsis metabolome under endogenous JA deficiency

NASA Astrophysics Data System (ADS)

Cao, Jingjing; Li, Mengya; Chen, Jian; Liu, Pei; Li, Zhen

2016-11-01

Jasmonates (JAs) play important roles in plant growth, development and defense. Comprehensive metabolomics profiling of plants under JA treatment provides insights into the interaction and regulation network of plant hormones. Here we applied high resolution mass spectrometry based metabolomics approach on Arabidopsis wild type and JA synthesis deficiency mutant opr3. The effects of exogenous MeJA treatment on the metabolites of opr3 were investigated. More than 10000 ion signals were detected and more than 2000 signals showed significant variation in different genotypes and treatment groups. Multivariate statistic analyses (PCA and PLS-DA) were performed and a differential compound library containing 174 metabolites with high resolution precursor ion-product ions pairs was obtained. Classification and pathway analysis of 109 identified compounds in this library showed that glucosinolates and tryptophan metabolism, amino acids and small peptides metabolism, lipid metabolism, especially fatty acyls metabolism, were impacted by endogenous JA deficiency and exogenous MeJA treatment. These results were further verified by quantitative reverse transcription PCR (RT-qPCR) analysis of 21 related genes involved in the metabolism of glucosinolates, tryptophan and α-linolenic acid pathways. The results would greatly enhance our understanding of the biological functions of JA.

Functional metabolomics as a tool to analyze Mediator function and structure in plants.

PubMed

Davoine, Celine; Abreu, Ilka N; Khajeh, Khalil; Blomberg, Jeanette; Kidd, Brendan N; Kazan, Kemal; Schenk, Peer M; Gerber, Lorenz; Nilsson, Ove; Moritz, Thomas; Björklund, Stefan

2017-01-01

Mediator is a multiprotein transcriptional co-regulator complex composed of four modules; Head, Middle, Tail, and Kinase. It conveys signals from promoter-bound transcriptional regulators to RNA polymerase II and thus plays an essential role in eukaryotic gene regulation. We describe subunit localization and activities of Mediator in Arabidopsis through metabolome and transcriptome analyses from a set of Mediator mutants. Functional metabolomic analysis based on the metabolite profiles of Mediator mutants using multivariate statistical analysis and heat-map visualization shows that different subunit mutants display distinct metabolite profiles, which cluster according to the reported localization of the corresponding subunits in yeast. Based on these results, we suggest localization of previously unassigned plant Mediator subunits to specific modules. We also describe novel roles for individual subunits in development, and demonstrate changes in gene expression patterns and specific metabolite levels in med18 and med25, which can explain their phenotypes. We find that med18 displays levels of phytoalexins normally found in wild type plants only after exposure to pathogens. Our results indicate that different Mediator subunits are involved in specific signaling pathways that control developmental processes and tolerance to pathogen infections.

The WEIZMASS spectral library for high-confidence metabolite identification

NASA Astrophysics Data System (ADS)

Shahaf, Nir; Rogachev, Ilana; Heinig, Uwe; Meir, Sagit; Malitsky, Sergey; Battat, Maor; Wyner, Hilary; Zheng, Shuning; Wehrens, Ron; Aharoni, Asaph

2016-08-01

Annotation of metabolites is an essential, yet problematic, aspect of mass spectrometry (MS)-based metabolomics assays. The current repertoire of definitive annotations of metabolite spectra in public MS databases is limited and suffers from lack of chemical and taxonomic diversity. Furthermore, the heterogeneity of the data prevents the development of universally applicable metabolite annotation tools. Here we present a combined experimental and computational platform to advance this key issue in metabolomics. WEIZMASS is a unique reference metabolite spectral library developed from high-resolution MS data acquired from a structurally diverse set of 3,540 plant metabolites. We also present MatchWeiz, a multi-module strategy using a probabilistic approach to match library and experimental data. This strategy allows efficient and high-confidence identification of dozens of metabolites in model and exotic plants, including metabolites not previously reported in plants or found in few plant species to date.

Metabolome-genome-wide association study dissects genetic architecture for generating natural variation in rice secondary metabolism

PubMed Central

Matsuda, Fumio; Nakabayashi, Ryo; Yang, Zhigang; Okazaki, Yozo; Yonemaru, Jun-ichi; Ebana, Kaworu; Yano, Masahiro; Saito, Kazuki

2015-01-01

Plants produce structurally diverse secondary (specialized) metabolites to increase their fitness for survival under adverse environments. Several bioactive compounds for new drugs have been identified through screening of plant extracts. In this study, genome-wide association studies (GWAS) were conducted to investigate the genetic architecture behind the natural variation of rice secondary metabolites. GWAS using the metabolome data of 175 rice accessions successfully identified 323 associations among 143 single nucleotide polymorphisms (SNPs) and 89 metabolites. The data analysis highlighted that levels of many metabolites are tightly associated with a small number of strong quantitative trait loci (QTLs). The tight association may be a mechanism generating strains with distinct metabolic composition through the crossing of two different strains. The results indicate that one plant species produces more diverse phytochemicals than previously expected, and plants still contain many useful compounds for human applications. PMID:25267402

MetaboLights: towards a new COSMOS of metabolomics data management.

PubMed

Steinbeck, Christoph; Conesa, Pablo; Haug, Kenneth; Mahendraker, Tejasvi; Williams, Mark; Maguire, Eamonn; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Salek, Reza M; Griffin, Julian L

2012-10-01

Exciting funding initiatives are emerging in Europe and the US for metabolomics data production, storage, dissemination and analysis. This is based on a rich ecosystem of resources around the world, which has been build during the past ten years, including but not limited to resources such as MassBank in Japan and the Human Metabolome Database in Canada. Now, the European Bioinformatics Institute has launched MetaboLights, a database for metabolomics experiments and the associated metadata (http://www.ebi.ac.uk/metabolights). It is the first comprehensive, cross-species, cross-platform metabolomics database maintained by one of the major open access data providers in molecular biology. In October, the European COSMOS consortium will start its work on Metabolomics data standardization, publication and dissemination workflows. The NIH in the US is establishing 6-8 metabolomics services cores as well as a national metabolomics repository. This communication reports about MetaboLights as a new resource for Metabolomics research, summarises the related developments and outlines how they may consolidate the knowledge management in this third large omics field next to proteomics and genomics.

Metabolome analysis of food-chain between plants and insects

USDA-ARS?s Scientific Manuscript database

Evolution has shown the co-dependency of host plants-predators (insects), especially inevitable dependency of predators on plant biomass for securing their energy sources. In this respect, it had been believed that NAD+ source used for major energy producing pathway in insects is a glycerol-3-phosph...

Metabolomic profiling of the nectars of Aquilegia pubescens and A. canadensis

USDA-ARS?s Scientific Manuscript database

To date, variation in nectar chemistry of flowering plants has not been studied in detail. Such variation exerts considerable influence on pollinator–plant interactions, as well as on flower traits that play important roles in the selection of a plant for visitation by specific pollinators. Over the...

Proposed minimum reporting standards for chemical analysis Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI)

PubMed Central

Amberg, Alexander; Barrett, Dave; Beale, Michael H.; Beger, Richard; Daykin, Clare A.; Fan, Teresa W.-M.; Fiehn, Oliver; Goodacre, Royston; Griffin, Julian L.; Hankemeier, Thomas; Hardy, Nigel; Harnly, James; Higashi, Richard; Kopka, Joachim; Lane, Andrew N.; Lindon, John C.; Marriott, Philip; Nicholls, Andrew W.; Reily, Michael D.; Thaden, John J.; Viant, Mark R.

2013-01-01

There is a general consensus that supports the need for standardized reporting of metadata or information describing large-scale metabolomics and other functional genomics data sets. Reporting of standard metadata provides a biological and empirical context for the data, facilitates experimental replication, and enables the re-interrogation and comparison of data by others. Accordingly, the Metabolomics Standards Initiative is building a general consensus concerning the minimum reporting standards for metabolomics experiments of which the Chemical Analysis Working Group (CAWG) is a member of this community effort. This article proposes the minimum reporting standards related to the chemical analysis aspects of metabolomics experiments including: sample preparation, experimental analysis, quality control, metabolite identification, and data pre-processing. These minimum standards currently focus mostly upon mass spectrometry and nuclear magnetic resonance spectroscopy due to the popularity of these techniques in metabolomics. However, additional input concerning other techniques is welcomed and can be provided via the CAWG on-line discussion forum at http://msi-workgroups.sourceforge.net/ or http://Msi-workgroups-feedback@lists.sourceforge.net. Further, community input related to this document can also be provided via this electronic forum. PMID:24039616

Omics Approaches for the Engineering of Pathogen Resistant Plants.

PubMed

Gomez-Casati, Diego F; Pagani, María A; Busi, María V; Bhadauria, Vijai

2016-01-01

The attack of different pathogens, such as bacteria, fungi and viruses has a negative impact on crop production. In counter such attacks, plants have developed different strategies involving the modification of gene expression, activation of several metabolic pathways and post-translational modification of proteins, which culminate into the accumulation of primary and secondary metabolites implicated in plant defense responses. The recent advancement in omics techniques allows the increase coverage of plants transcriptomes, proteomes and metabolomes during pathogen attack, and the modulation of the response after the infection. Omics techniques also allow us to learn more about the biological cycle of the pathogens in addition to the identification of novel virulence factors in pathogens and their host targets. Both approaches become important to decipher the mechanism underlying pathogen attacks and to develop strategies for improving disease-resistant plants. In this review, we summarize some of the contribution of genomics, transcriptomics, proteomics, metabolomics and metallomics in devising the strategies to obtain plants with increased resistance to pathogens. These approaches constitute important research tools in the development of new technologies for the protection against diseases and increase plant production.

MeRy-B, a metabolomic database and knowledge base for exploring plant primary metabolism.

PubMed

Deborde, Catherine; Jacob, Daniel

2014-01-01

Plant primary metabolites are organic compounds that are common to all or most plant species and are essential for plant growth, development, and reproduction. They are intermediates and products of metabolism involved in photosynthesis and other biosynthetic processes. Primary metabolites belong to different compound families, mainly carbohydrates, organic acids, amino acids, nucleotides, fatty acids, steroids, or lipids. Until recently, unlike the Human Metabolome Database ( http://www.hmdb.ca ) dedicated to human metabolism, there was no centralized database or repository dedicated exclusively to the plant kingdom that contained information on metabolites and their concentrations in a detailed experimental context. MeRy-B is the first platform for plant (1)H-NMR metabolomic profiles (MeRy-B, http://bit.ly/meryb ), designed to provide a knowledge base of curated plant profiles and metabolites obtained by NMR, together with the corresponding experimental and analytical metadata. MeRy-B contains lists of plant metabolites, mostly primary metabolites and unknown compounds, with information about experimental conditions, the factors studied, and metabolite concentrations for 19 different plant species (Arabidopsis, broccoli, daphne, grape, maize, barrel clover, melon, Ostreococcus tauri, palm date, palm tree, peach, pine tree, eucalyptus, plantain rice, strawberry, sugar beet, tomato, vanilla), compiled from more than 2,300 annotated NMR profiles for various organs or tissues deposited by 30 different private or public contributors in September 2013. Currently, about half of the data deposited in MeRy-B is publicly available. In this chapter, readers will be shown how to (1) navigate through and retrieve data of publicly available projects on MeRy-B website; (2) visualize lists of experimentally identified metabolites and their concentrations in all plant species present in MeRy-B; (3) get primary metabolite list for a particular plant species in MeRy-B; and for a particular tissue (4) find information on a primary metabolite regardless of the species.

Microbial symbionts affect Pisum sativum proteome and metabolome under Didymella pinodes infection.

PubMed

Desalegn, G; Turetschek, R; Kaul, H-P; Wienkoop, S

2016-06-30

The long cultivation of field pea led to an enormous diversity which, however, seems to hold just little resistance against the ascochyta blight disease complex. The potential of below ground microbial symbiosis to prime the immune system of Pisum for an upcoming pathogen attack has hitherto received little attention. This study investigates the effect of beneficial microbes on the leaf proteome and metabolome as well as phenotype characteristics of plants in various symbiont interactions (mycorrhiza, rhizobia, co-inoculation, non-symbiotic) after infestation by Didymella pinodes. In healthy plants, mycorrhiza and rhizobia induced changes in RNA metabolism and protein synthesis. Furthermore, metal handling and ROS dampening was affected in all mycorrhiza treatments. The co-inoculation caused the synthesis of stress related proteins with concomitant adjustment of proteins involved in lipid biosynthesis. The plant's disease infection response included hormonal adjustment, ROS scavenging as well as synthesis of proteins related to secondary metabolism. The regulation of the TCA, amino acid and secondary metabolism including the pisatin pathway, was most pronounced in rhizobia associated plants which had the lowest infection rate and the slowest disease progression. A most comprehensive study of the Pisum sativum proteome and metabolome infection response to Didymella pinodes is provided. Several distinct patterns of microbial symbioses on the plant metabolism are presented for the first time. Upon D. pinodes infection, rhizobial symbiosis revealed induced systemic resistance e.g. by an enhanced level of proteins involved in pisatin biosynthesis. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Metabolomic assessment of key maize resources: GC-MS and NMR profiling of grain from B73 hybrids of the nested association mapping (NAM) founders and of geographically diverse landraces

USDA-ARS?s Scientific Manuscript database

The present study expands metabolomic assessments of maize beyond commercial elite lines to include two sets of publicly available lines used extensively in the scientific community to investigate the genetic basis of complex plant traits or that may serve as a source of new alleles for improving mo...

An automated growth enclosure for metabolic labeling of Arabidopsis thaliana with 13C-carbon dioxide - an in vivo labeling system for proteomics and metabolomics research

PubMed Central

2011-01-01

Background Labeling whole Arabidopsis (Arabidopsis thaliana) plants to high enrichment with 13C for proteomics and metabolomics applications would facilitate experimental approaches not possible by conventional methods. Such a system would use the plant's native capacity for carbon fixation to ubiquitously incorporate 13C from 13CO2 gas. Because of the high cost of 13CO2 it is critical that the design conserve the labeled gas. Results A fully enclosed automated plant growth enclosure has been designed and assembled where the system simultaneously monitors humidity, temperature, pressure and 13CO2 concentration with continuous adjustment of humidity, pressure and 13CO2 levels controlled by a computer running LabView software. The enclosure is mounted on a movable cart for mobility among growth environments. Arabidopsis was grown in the enclosure for up to 8 weeks and obtained on average >95 atom% enrichment for small metabolites, such as amino acids and >91 atom% for large metabolites, including proteins and peptides. Conclusion The capability of this labeling system for isotope dilution experiments was demonstrated by evaluation of amino acid turnover using GC-MS as well as protein turnover using LC-MS/MS. Because this 'open source' Arabidopsis 13C-labeling growth environment was built using readily available materials and software, it can be adapted easily to accommodate many different experimental designs. PMID:21310072

Introduction to metabolomics and its applications in ophthalmology

PubMed Central

Tan, S Z; Begley, P; Mullard, G; Hollywood, K A; Bishop, P N

2016-01-01

Metabolomics is the study of endogenous and exogenous metabolites in biological systems, which aims to provide comparative semi-quantitative information about all metabolites in the system. Metabolomics is an emerging and potentially powerful tool in ophthalmology research. It is therefore important for health professionals and researchers involved in the speciality to understand the basic principles of metabolomics experiments. This article provides an overview of the experimental workflow and examples of its use in ophthalmology research from the study of disease metabolism and pathogenesis to identification of biomarkers. PMID:26987591

Metabolomics Reveals the Origins of Antimicrobial Plant Resins Collected by Honey Bees

PubMed Central

Wilson, Michael B.; Spivak, Marla; Hegeman, Adrian D.; Rendahl, Aaron; Cohen, Jerry D.

2013-01-01

The deposition of antimicrobial plant resins in honey bee, Apis mellifera, nests has important physiological benefits. Resin foraging is difficult to approach experimentally because resin composition is highly variable among and between plant families, the environmental and plant-genotypic effects on resins are unknown, and resin foragers are relatively rare and often forage in unobservable tree canopies. Subsequently, little is known about the botanical origins of resins in many regions or the benefits of specific resins to bees. We used metabolomic methods as a type of environmental forensics to track individual resin forager behavior through comparisons of global resin metabolite patterns. The resin from the corbiculae of a single bee was sufficient to identify that resin's botanical source without prior knowledge of resin composition. Bees from our apiary discriminately foraged for resin from eastern cottonwood (Populus deltoides), and balsam poplar (P. balsamifera) among many available, even closely related, resinous plants. Cottonwood and balsam poplar resin composition did not show significant seasonal or regional changes in composition. Metabolomic analysis of resin from 6 North American Populus spp. and 5 hybrids revealed peaks characteristic to taxonomic nodes within Populus, while antimicrobial analysis revealed that resin from different species varied in inhibition of the bee bacterial pathogen, Paenibacillus larvae. We conclude that honey bees make discrete choices among many resinous plant species, even among closely related species. Bees also maintained fidelity to a single source during a foraging trip. Furthermore, the differential inhibition of P. larvae by Populus spp., thought to be preferential for resin collection in temperate regions, suggests that resins from closely related plant species many have different benefits to bees. PMID:24204850

Cardioprotective and Metabolomic Profiling of Selected Medicinal Plants against Oxidative Stress

PubMed Central

Afsheen, Nadia; Jahan, Nazish; Ijaz, Misbah; Manzoor, Asad; Khan, Khalid Mahmood; Hina, Saman

2018-01-01

In this research work, the antioxidant and metabolomic profiling of seven selected medicinally important herbs including Rauvolfia serpentina, Terminalia arjuna, Coriandrum sativum, Elettaria cardamom, Piper nigrum, Allium sativum, and Crataegus oxyacantha was performed. The in vivo cardioprotective potential of these medicinal plants was evaluated against surgically induced oxidative stress through left anterior descending coronary artery ligation (LADCA) in dogs. The antioxidant profiling of these plants was done through DPPH and DNA protection assay. The C. oxyacantha and T. arjuna showed maximum antioxidant potential, while the E. cardamom showed poor antioxidative strength even at its high concentration. Different concentrations of extracts of the said plants exhibited the protection of plasmid DNA against H2O2 damage as compared to the plasmid DNA merely treated with H2O2. The metabolomic profiling through LC-MS analysis of these antioxidants revealed the presence of active secondary metabolites responsible for their antioxidant potential. During in vivo analysis, blood samples of all treatment groups were drawn at different time intervals to analyze the cardiac and hemodynamic parameters. The results depicted that the group pretreated with HC4 significantly sustained the level of CK-MB, SGOT, and LDH as well as hemodynamic parameters near to normal. The histopathological examination also confirmed the cardioprotective potential of HC4. Thus, the HC4 being safe and inexpensive cardioprotective herbal combination could be considered as an alternate of synthetic drugs. PMID:29576858

Metabolome Integrated Analysis of High-Temperature Response in Pinus radiata.

PubMed

Escandón, Mónica; Meijón, Mónica; Valledor, Luis; Pascual, Jesús; Pinto, Gloria; Cañal, María Jesús

2018-01-01

The integrative omics approach is crucial to identify the molecular mechanisms underlying high-temperature response in non-model species. Based on future scenarios of heat increase, Pinus radiata plants were exposed to a temperature of 40°C for a period of 5 days, including recovered plants (30 days after last exposure to 40°C) in the analysis. The analysis of the metabolome using complementary mass spectrometry techniques (GC-MS and LC-Orbitrap-MS) allowed the reliable quantification of 2,287 metabolites. The analysis of identified metabolites and highlighter metabolic pathways across heat time exposure reveal the dynamism of the metabolome in relation to high-temperature response in P. radiata , identifying the existence of a turning point (on day 3) at which P. radiata plants changed from an initial stress response program (shorter-term response) to an acclimation one (longer-term response). Furthermore, the integration of metabolome and physiological measurements, which cover from the photosynthetic state to hormonal profile, suggests a complex metabolic pathway interaction network related to heat-stress response. Cytokinins (CKs), fatty acid metabolism and flavonoid and terpenoid biosynthesis were revealed as the most important pathways involved in heat-stress response in P. radiata , with zeatin riboside (ZR) and isopentenyl adenosine (iPA) as the key hormones coordinating these multiple and complex interactions. On the other hand, the integrative approach allowed elucidation of crucial metabolic mechanisms involved in heat response in P. radiata , as well as the identification of thermotolerance metabolic biomarkers (L-phenylalanine, hexadecanoic acid, and dihydromyricetin), crucial metabolites which can reschedule the metabolic strategy to adapt to high temperature.

Metabolome Integrated Analysis of High-Temperature Response in Pinus radiata

PubMed Central

Escandón, Mónica; Meijón, Mónica; Valledor, Luis; Pascual, Jesús; Pinto, Gloria; Cañal, María Jesús

2018-01-01

The integrative omics approach is crucial to identify the molecular mechanisms underlying high-temperature response in non-model species. Based on future scenarios of heat increase, Pinus radiata plants were exposed to a temperature of 40°C for a period of 5 days, including recovered plants (30 days after last exposure to 40°C) in the analysis. The analysis of the metabolome using complementary mass spectrometry techniques (GC-MS and LC-Orbitrap-MS) allowed the reliable quantification of 2,287 metabolites. The analysis of identified metabolites and highlighter metabolic pathways across heat time exposure reveal the dynamism of the metabolome in relation to high-temperature response in P. radiata, identifying the existence of a turning point (on day 3) at which P. radiata plants changed from an initial stress response program (shorter-term response) to an acclimation one (longer-term response). Furthermore, the integration of metabolome and physiological measurements, which cover from the photosynthetic state to hormonal profile, suggests a complex metabolic pathway interaction network related to heat-stress response. Cytokinins (CKs), fatty acid metabolism and flavonoid and terpenoid biosynthesis were revealed as the most important pathways involved in heat-stress response in P. radiata, with zeatin riboside (ZR) and isopentenyl adenosine (iPA) as the key hormones coordinating these multiple and complex interactions. On the other hand, the integrative approach allowed elucidation of crucial metabolic mechanisms involved in heat response in P. radiata, as well as the identification of thermotolerance metabolic biomarkers (L-phenylalanine, hexadecanoic acid, and dihydromyricetin), crucial metabolites which can reschedule the metabolic strategy to adapt to high temperature. PMID:29719546

Application of mathematical models and computation in plant metabolomics

USDA-ARS?s Scientific Manuscript database

The investigation and reporting of plants’ chemical constituents has greatly evolved over the centuries of natural products and phytochemical research. Starting from the extraction and identification of plant-based bioactive components, such as historical salicin or more recent paclitaxel, phytochem...

CE-MS for metabolomics: Developments and applications in the period 2014-2016.

PubMed

Ramautar, Rawi; Somsen, Govert W; de Jong, Gerhardus J

2017-01-01

CE-MS can be considered a useful analytical technique for the global profiling of (highly) polar and charged metabolites in various samples. Over the past few years, significant advancements have been made in CE-MS approaches for metabolomics studies. In this paper, which is a follow-up of a previous review paper covering the years 2012-2014 (Electrophoresis 2015, 36, 212-224), recent CE-MS strategies developed for metabolomics covering the literature from July 2014 to June 2016 are outlined. Attention will be paid to new CE-MS approaches for the profiling of anionic metabolites and the potential of SPE coupled to CE-MS is also demonstrated. Representative examples illustrate the applicability of CE-MS in the fields of biomedical, clinical, microbial, plant, and food metabolomics. A complete overview of recent CE-MS-based metabolomics studies is given in a table, which provides information on sample type and pretreatment, capillary coatings, and MS detection mode. Finally, general conclusions and perspectives are given. © 2016 The Authors ELECTROPHORESIS Published by Wiley-VCH Verlag GmbH & Co. KGaA.

MetaboLights: An Open-Access Database Repository for Metabolomics Data.

PubMed

Kale, Namrata S; Haug, Kenneth; Conesa, Pablo; Jayseelan, Kalaivani; Moreno, Pablo; Rocca-Serra, Philippe; Nainala, Venkata Chandrasekhar; Spicer, Rachel A; Williams, Mark; Li, Xuefei; Salek, Reza M; Griffin, Julian L; Steinbeck, Christoph

2016-03-24

MetaboLights is the first general purpose, open-access database repository for cross-platform and cross-species metabolomics research at the European Bioinformatics Institute (EMBL-EBI). Based upon the open-source ISA framework, MetaboLights provides Metabolomics Standard Initiative (MSI) compliant metadata and raw experimental data associated with metabolomics experiments. Users can upload their study datasets into the MetaboLights Repository. These studies are then automatically assigned a stable and unique identifier (e.g., MTBLS1) that can be used for publication reference. The MetaboLights Reference Layer associates metabolites with metabolomics studies in the archive and is extensively annotated with data fields such as structural and chemical information, NMR and MS spectra, target species, metabolic pathways, and reactions. The database is manually curated with no specific release schedules. MetaboLights is also recommended by journals for metabolomics data deposition. This unit provides a guide to using MetaboLights, downloading experimental data, and depositing metabolomics datasets using user-friendly submission tools. Copyright © 2016 John Wiley & Sons, Inc.

Metabolic responses of Quercus ilex seedlings to wounding analysed with nuclear magnetic resonance profiling.

PubMed

Sardans, J; Gargallo-Garriga, A; Pérez-Trujillo, M; Parella, T J; Seco, R; Filella, I; Peñuelas, J

2014-03-01

Plants defend themselves against herbivory at several levels. One of these is the synthesis of inducible chemical defences. Using NMR metabolomic techniques, we studied the metabolic changes of plant leaves after a wounding treatment simulating herbivore attack in the Mediterranean sclerophyllous tree Quercus ilex. First, an increase in glucose content was observed in wounded plants. There was also an increase in the content of C-rich secondary metabolites such as quinic acid and quercitol, both related to the shikimic acid pathway and linked to defence against biotic stress. There was also a shift in N-storing amino acids, from leucine and isoleucine to asparagine and choline. The observed higher content of asparagine is related to the higher content of choline through serine that was proved to be the precursor of choline. Choline is a general anti-herbivore and pathogen deterrent. The study shows the rapid metabolic response of Q. ilex in defending its leaves, based on a rapid increase in the production of quinic acid, quercitol and choline. The results also confirm the suitability of (1)H NMR-based metabolomic profiling studies to detect global metabolome shifts after wounding stress in tree leaves, and therefore its suitability in ecometabolomic studies. © 2013 German Botanical Society and The Royal Botanical Society of the Netherlands.

Zinc Excess Triggered Polyamines Accumulation in Lettuce Root Metabolome, As Compared to Osmotic Stress under High Salinity

PubMed Central

Rouphael, Youssef; Colla, Giuseppe; Bernardo, Letizia; Kane, David; Trevisan, Marco; Lucini, Luigi

2016-01-01

Abiotic stresses such as salinity and metal contaminations are the major environmental stresses that adversely affect crop productivity worldwide. Crop responses and tolerance to abiotic stress are complex processes for which “-omic” approaches such as metabolomics is giving us a newest view of biological systems. The aim of the current research was to assess metabolic changes in lettuce (Lactuca sativa L.), by specifically probing the root metabolome of plants exposed to elevated isomolar concentrations of NaCl and ZnSO4. Most of the metabolites that were differentially accumulated in roots were identified for stress conditions, however the response was more intense in plants exposed to NaCl. Compounds identified in either NaCl or ZnSO4 conditions were: carbohydrates, phenolics, hormones, glucosinolates, and lipids. Our findings suggest that osmotic stress and the consequent redox imbalance play a major role in determining lettuce root metabolic response. In addition, it was identified that polyamines and polyamine conjugates were triggered as a specific response to ZnSO4. These findings help improve understanding of how plants cope with abiotic stresses. This information can be used to assist decision-making in breeding programs for improving crop tolerance to salinity and heavy metal contaminations. PMID:27375675

Meta-analysis of pathway enrichment: combining independent and dependent omics data sets.

PubMed

Kaever, Alexander; Landesfeind, Manuel; Feussner, Kirstin; Morgenstern, Burkhard; Feussner, Ivo; Meinicke, Peter

2014-01-01

A major challenge in current systems biology is the combination and integrative analysis of large data sets obtained from different high-throughput omics platforms, such as mass spectrometry based Metabolomics and Proteomics or DNA microarray or RNA-seq-based Transcriptomics. Especially in the case of non-targeted Metabolomics experiments, where it is often impossible to unambiguously map ion features from mass spectrometry analysis to metabolites, the integration of more reliable omics technologies is highly desirable. A popular method for the knowledge-based interpretation of single data sets is the (Gene) Set Enrichment Analysis. In order to combine the results from different analyses, we introduce a methodical framework for the meta-analysis of p-values obtained from Pathway Enrichment Analysis (Set Enrichment Analysis based on pathways) of multiple dependent or independent data sets from different omics platforms. For dependent data sets, e.g. obtained from the same biological samples, the framework utilizes a covariance estimation procedure based on the nonsignificant pathways in single data set enrichment analysis. The framework is evaluated and applied in the joint analysis of Metabolomics mass spectrometry and Transcriptomics DNA microarray data in the context of plant wounding. In extensive studies of simulated data set dependence, the introduced correlation could be fully reconstructed by means of the covariance estimation based on pathway enrichment. By restricting the range of p-values of pathways considered in the estimation, the overestimation of correlation, which is introduced by the significant pathways, could be reduced. When applying the proposed methods to the real data sets, the meta-analysis was shown not only to be a powerful tool to investigate the correlation between different data sets and summarize the results of multiple analyses but also to distinguish experiment-specific key pathways.

CE-MS for metabolomics: developments and applications in the period 2012-2014.

PubMed

Ramautar, Rawi; Somsen, Govert W; de Jong, Gerhardus J

2015-01-01

In the field of metabolomics, CE-MS is now regarded as a useful complementary analytical technique for the profiling of (highly) polar ionogenic metabolites in biological samples. Over the past few years, significant advancements have been made in CE-MS approaches for metabolic profiling studies. This paper, which is a follow-up of three previous review papers covering the years 2000-2012 [Electrophoresis 2009, 30, 276-291; Electrophoresis 2011, 32, 52-65; Electrophoresis 2013, 34, 86-98], provides an update of these developments covering the scientific literature from July 2012 to June 2014. Attention will be paid to novel interfacing techniques for coupling CE to MS and their implications for metabolomics studies. The potential of CEC-MS and MEKC-MS are also considered, and CE-MS systems for high-throughput metabolic profiling are discussed. The applicability of CE-MS for metabolomics studies is demonstrated by representative examples in the fields of biomedical, clinical, microbial, plant, environmental, and food metabolomics. An overview of recent CE-MS-based metabolomics studies is given in a table, which provides information on sample type and pretreatment, capillary coatings, and MS detection mode. Finally, general conclusions and perspectives are given. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Experimental design and reporting standards for metabolomics studies of mammalian cell lines.

PubMed

Hayton, Sarah; Maker, Garth L; Mullaney, Ian; Trengove, Robert D

2017-12-01

Metabolomics is an analytical technique that investigates the small biochemical molecules present within a biological sample isolated from a plant, animal, or cultured cells. It can be an extremely powerful tool in elucidating the specific metabolic changes within a biological system in response to an environmental challenge such as disease, infection, drugs, or toxins. A historically difficult step in the metabolomics pipeline is in data interpretation to a meaningful biological context, for such high-variability biological samples and in untargeted metabolomics studies that are hypothesis-generating by design. One way to achieve stronger biological context of metabolomic data is via the use of cultured cell models, particularly for mammalian biological systems. The benefits of in vitro metabolomics include a much greater control of external variables and no ethical concerns. The current concerns are with inconsistencies in experimental procedures and level of reporting standards between different studies. This review discusses some of these discrepancies between recent studies, such as metabolite extraction and data normalisation. The aim of this review is to highlight the importance of a standardised experimental approach to any cultured cell metabolomics study and suggests an example procedure fully inclusive of information that should be disclosed in regard to the cell type/s used and their culture conditions. Metabolomics of cultured cells has the potential to uncover previously unknown information about cell biology, functions and response mechanisms, and so the accurate biological interpretation of the data produced and its ability to be compared to other studies should be considered vitally important.

Metabolomic profiling from leaves and roots of tomato (Solanum lycopersicum L.) plants grown under nitrogen, phosphorus or potassium-deficient condition

USDA-ARS?s Scientific Manuscript database

Nitrogen (N), phosphorus (P) and potassium (K) are essential macronutrients that are required in large quantities by growing plants. Deficiency of N, P or K can strongly affect metabolites in plant tissues. However, specific metabolic network responses to nutrient deficiencies are not well-defined. ...

Metabolomic Responses of Arabidopsis Suspension Cells to Bicarbonate under Light and Dark Conditions

PubMed Central

Misra, Biswapriya B.; Yin, Zepeng; Geng, Sisi; de Armas, Evaldo; Chen, Sixue

2016-01-01

Global CO2 level presently recorded at 400 ppm is expected to reach 550 ppm in 2050, an increment likely to impact plant growth and productivity. Using targeted LC-MS and GC-MS platforms we quantified 229 and 29 metabolites, respectively in a time-course study to reveal short-term responses to different concentrations (1, 3, and 10 mM) of bicarbonate (HCO3−) under light and dark conditions. Results indicate that HCO3− treatment responsive metabolomic changes depend on the HCO3− concentration, time of treatment, and light/dark. Interestingly, 3 mM HCO3− concentration treatment induced more significantly changed metabolites than either lower or higher concentrations used. Flavonoid biosynthesis and glutathione metabolism were common to both light and dark-mediated responses in addition to showing concentration-dependent changes. Our metabolomics results provide insights into short-term plant cellular responses to elevated HCO3− concentrations as a result of ambient increases in CO2 under light and dark. PMID:27762345

Bio-effectors from waste materials as growth promoters for tomato plants, an agronomic and metabolomic study

NASA Astrophysics Data System (ADS)

Abou Chehade, Lara; Chami, Ziad Al; De Pascali, Sandra; Cavoski, Ivana; Fanizzi, Francesco Paolo

2015-04-01

In organic farming, where nutrient management is constrained and sustainability is claimed, bio-effectors pave their way. Considering selected bio-effectors, this study integrates metabolomics to agronomy in depicting induced relevant phenomena. Extracts of three agro-industrial wastes (Lemon processing residues, Fennel processing residues and Brewer's spent grain) are being investigated as sources of bio-effectors for the third trial consequently. Corresponding individual and mixture aqueous extracts are assessed for their synergistic and/or single agronomic and qualitative performances on soil-grown tomato, compared to both a control and humic acid treatments. A metabolomic profiling of tomato fruits via the Proton Nuclear Magnetic Resonance (NMR) spectroscopy, as holistic indicator of fruit quality and extract-induced responses, complements crop productivity and organoleptic/nutritional qualitative analyses. Results are expected to show mainly an enhancement of the fruit qualitative traits, and to confirm partly the previous results of better crop productivity and metabolism enhancement. Waste-derived bio-effectors could be, accordingly, demonstrated as potential candidates of plant-enhancing substances. Keywords: bio-effectors, organic farming, agro-industrial wastes, nuclear magnetic resonance (NMR), tomato.

METABOLOMICS IN MEDICAL SCIENCES--TRENDS, CHALLENGES AND PERSPECTIVES.

PubMed

Klupczyńska, Agnieszka; Dereziński, Paweł; Kokot, Zenon J

2015-01-01

Metabolomics is the latest of the "omic" technologies that involves comprehensive analysis of small molecule metabolites of an organism or a specific biological sample. Metabolomics provides an insight into the cell status and describes an actual health condition of organisms. Analysis of metabolome offers a unique opportunity to study the influence of genetic variation, disease, applied treatment or diet on endogenous metabolic state of organisms. There are many areas that might benefit from metabolomic research. In the article some applications of this novel "omic" technology in the field of medical sciences are presented. One of the most popular aims of metabolomic studies is biomarker discovery. Despite using the state-of-art analytical techniques along with advanced bioinformatic tools, metabolomic experiments encounter numerous difficulties and pitfalls. Challenges that researchers in the field of analysis of metabolome have to face include i.a., technical limitations, bioinformatic challenges and integration with other "omic" sciences. One of the grand challenges for studies in the field of metabolomics is to tackle the problem of data analysis, which is probably the most time consuming stage of metabolomic workflow and requires close collaboration between analysts, clinicians and experts in chemometric analysis. Implementation of metabolomics into clinical practice will be dependent on establishment of standardized protocols in analytical performance and data analysis and development of fit-for-purpose biomarker method validation. Metabolomics allows to achieve a sophisticated level of information about biological systems and opens up new perspectives in many fields of medicine, especially in oncology. Apart from its extensive cognitive significance, metabolomics manifests also a practical importance as it may lead to design of new non-invasive, sensitive and specific diagnostic techniques and development of new therapies.

Updates in metabolomics tools and resources: 2014-2015.

PubMed

Misra, Biswapriya B; van der Hooft, Justin J J

2016-01-01

Data processing and interpretation represent the most challenging and time-consuming steps in high-throughput metabolomic experiments, regardless of the analytical platforms (MS or NMR spectroscopy based) used for data acquisition. Improved machinery in metabolomics generates increasingly complex datasets that create the need for more and better processing and analysis software and in silico approaches to understand the resulting data. However, a comprehensive source of information describing the utility of the most recently developed and released metabolomics resources--in the form of tools, software, and databases--is currently lacking. Thus, here we provide an overview of freely-available, and open-source, tools, algorithms, and frameworks to make both upcoming and established metabolomics researchers aware of the recent developments in an attempt to advance and facilitate data processing workflows in their metabolomics research. The major topics include tools and researches for data processing, data annotation, and data visualization in MS and NMR-based metabolomics. Most in this review described tools are dedicated to untargeted metabolomics workflows; however, some more specialist tools are described as well. All tools and resources described including their analytical and computational platform dependencies are summarized in an overview Table. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Metadata description of the data in "A metabolomic comparison of urinary changes in type 2 diabetes in mouse, rat, and human."

PubMed Central

2011-01-01

Background Metabolomics is a rapidly developing functional genomic tool that has a wide range of applications in diverse fields in biology and medicine. However, unlike transcriptomics and proteomics there is currently no central repository for the depositing of data despite efforts by the Metabolomics Standard Initiative (MSI) to develop a standardised description of a metabolomic experiment. Findings In this manuscript we describe how the MSI description has been applied to a published dataset involving the identification of cross-species metabolic biomarkers associated with type II diabetes. The study describes sample collection of urine from mice, rats and human volunteers, and the subsequent acquisition of data by high resolution 1H NMR spectroscopy. The metadata is described to demonstrate how the MSI descriptions could be applied in a manuscript and the spectra have also been made available for the mouse and rat studies to allow others to process the data. Conclusions The intention of this manuscript is to stimulate discussion as to whether the MSI description is sufficient to describe the metadata associated with metabolomic experiments and encourage others to make their data available to other researchers. PMID:21801423

Evaluation of Normalization Methods to Pave the Way Towards Large-Scale LC-MS-Based Metabolomics Profiling Experiments

PubMed Central

Valkenborg, Dirk; Baggerman, Geert; Vanaerschot, Manu; Witters, Erwin; Dujardin, Jean-Claude; Burzykowski, Tomasz; Berg, Maya

2013-01-01

Abstract Combining liquid chromatography-mass spectrometry (LC-MS)-based metabolomics experiments that were collected over a long period of time remains problematic due to systematic variability between LC-MS measurements. Until now, most normalization methods for LC-MS data are model-driven, based on internal standards or intermediate quality control runs, where an external model is extrapolated to the dataset of interest. In the first part of this article, we evaluate several existing data-driven normalization approaches on LC-MS metabolomics experiments, which do not require the use of internal standards. According to variability measures, each normalization method performs relatively well, showing that the use of any normalization method will greatly improve data-analysis originating from multiple experimental runs. In the second part, we apply cyclic-Loess normalization to a Leishmania sample. This normalization method allows the removal of systematic variability between two measurement blocks over time and maintains the differential metabolites. In conclusion, normalization allows for pooling datasets from different measurement blocks over time and increases the statistical power of the analysis, hence paving the way to increase the scale of LC-MS metabolomics experiments. From our investigation, we recommend data-driven normalization methods over model-driven normalization methods, if only a few internal standards were used. Moreover, data-driven normalization methods are the best option to normalize datasets from untargeted LC-MS experiments. PMID:23808607

Fecal metabolome of the Hadza hunter-gatherers: a host-microbiome integrative view

PubMed Central

Turroni, Silvia; Fiori, Jessica; Rampelli, Simone; Schnorr, Stephanie L.; Consolandi, Clarissa; Barone, Monica; Biagi, Elena; Fanelli, Flaminia; Mezzullo, Marco; Crittenden, Alyssa N.; Henry, Amanda G.; Brigidi, Patrizia; Candela, Marco

2016-01-01

The recent characterization of the gut microbiome of traditional rural and foraging societies allowed us to appreciate the essential co-adaptive role of the microbiome in complementing our physiology, opening up significant questions on how the microbiota changes that have occurred in industrialized urban populations may have altered the microbiota-host co-metabolic network, contributing to the growing list of Western diseases. Here, we applied a targeted metabolomics approach to profile the fecal metabolome of the Hadza of Tanzania, one of the world’s few remaining foraging populations, and compared them to the profiles of urban living Italians, as representative of people in the post-industrialized West. Data analysis shows that during the rainy season, when the diet is primarily plant-based, Hadza are characterized by a distinctive enrichment in hexoses, glycerophospholipids, sphingolipids, and acylcarnitines, while deplete in the most common natural amino acids and derivatives. Complementary to the documented unique metagenomic features of their gut microbiome, our findings on the Hadza metabolome lend support to the notion of an alternate microbiome configuration befitting of a nomadic forager lifestyle, which helps maintain metabolic homeostasis through an overall scarcity of inflammatory factors, which are instead highly represented in the Italian metabolome. PMID:27624970

Comprehensive Optimization of LC-MS Metabolomics Methods Using Design of Experiments (COLMeD).

PubMed

Rhoades, Seth D; Weljie, Aalim M

2016-12-01

Both reverse-phase and HILIC chemistries are deployed for liquid-chromatography mass spectrometry (LC-MS) metabolomics analyses, however HILIC methods lag behind reverse-phase methods in reproducibility and versatility. Comprehensive metabolomics analysis is additionally complicated by the physiochemical diversity of metabolites and array of tunable analytical parameters. Our aim was to rationally and efficiently design complementary HILIC-based polar metabolomics methods on multiple instruments using Design of Experiments (DoE). We iteratively tuned LC and MS conditions on ion-switching triple quadrupole (QqQ) and quadrupole-time-of-flight (qTOF) mass spectrometers through multiple rounds of a workflow we term COLMeD (Comprehensive optimization of LC-MS metabolomics methods using design of experiments). Multivariate statistical analysis guided our decision process in the method optimizations. LC-MS/MS tuning for the QqQ method on serum metabolites yielded a median response increase of 161.5% (p<0.0001) over initial conditions with a 13.3% increase in metabolite coverage. The COLMeD output was benchmarked against two widely used polar metabolomics methods, demonstrating total ion current increases of 105.8% and 57.3%, with median metabolite response increases of 106.1% and 10.3% (p<0.0001 and p<0.05 respectively). For our optimized qTOF method, 22 solvent systems were compared on a standard mix of physiochemically diverse metabolites, followed by COLMeD optimization, yielding a median 29.8% response increase (p<0.0001) over initial conditions. The COLMeD process elucidated response tradeoffs, facilitating improved chromatography and MS response without compromising separation of isobars. COLMeD is efficient, requiring no more than 20 injections in a given DoE round, and flexible, capable of class-specific optimization as demonstrated through acylcarnitine optimization within the QqQ method.

Comprehensive Optimization of LC-MS Metabolomics Methods Using Design of Experiments (COLMeD)

PubMed Central

Rhoades, Seth D.

2017-01-01

Introduction Both reverse-phase and HILIC chemistries are deployed for liquid-chromatography mass spectrometry (LC-MS) metabolomics analyses, however HILIC methods lag behind reverse-phase methods in reproducibility and versatility. Comprehensive metabolomics analysis is additionally complicated by the physiochemical diversity of metabolites and array of tunable analytical parameters. Objective Our aim was to rationally and efficiently design complementary HILIC-based polar metabolomics methods on multiple instruments using Design of Experiments (DoE). Methods We iteratively tuned LC and MS conditions on ion-switching triple quadrupole (QqQ) and quadrupole-time-of-flight (qTOF) mass spectrometers through multiple rounds of a workflow we term COLMeD (Comprehensive optimization of LC-MS metabolomics methods using design of experiments). Multivariate statistical analysis guided our decision process in the method optimizations. Results LC-MS/MS tuning for the QqQ method on serum metabolites yielded a median response increase of 161.5% (p<0.0001) over initial conditions with a 13.3% increase in metabolite coverage. The COLMeD output was benchmarked against two widely used polar metabolomics methods, demonstrating total ion current increases of 105.8% and 57.3%, with median metabolite response increases of 106.1% and 10.3% (p<0.0001 and p<0.05 respectively). For our optimized qTOF method, 22 solvent systems were compared on a standard mix of physiochemically diverse metabolites, followed by COLMeD optimization, yielding a median 29.8% response increase (p<0.0001) over initial conditions. Conclusions The COLMeD process elucidated response tradeoffs, facilitating improved chromatography and MS response without compromising separation of isobars. COLMeD is efficient, requiring no more than 20 injections in a given DoE round, and flexible, capable of class-specific optimization as demonstrated through acylcarnitine optimization within the QqQ method. PMID:28348510

Cell-based metabolomics approach for assessing the impact of wastewater treatment plant effluent on downstream water quality

EPA Science Inventory

Wastewater treatment plants (WWTP) are a known source of various types of chemicals including pharmaceuticals and personal care products (PPCPs), naturally occurring hormones, and pesticides. There is great concern regarding their adverse effects on human and ecological health th...

Elucidating induced plant defenses: the use of targeted metabolomics as a bridge from elicitation to response

USDA-ARS?s Scientific Manuscript database

Dynamic plant defense responses to biotic attack involve the perception of specific biochemical elicitors associated with the offending agent, activation of signaling cascades, and the production of small molecules with complex protective roles. Chemical analyses are essential empirical tools for el...

UPLC-Q-TOF-HDMS analysis of constituents in the root of two kinds of Aconitum using a metabolomics approach.

PubMed

Sun, Hui; Wang, Mo; Zhang, Aihua; Ni, Bei; Dong, Hui; Wang, Xijun

2013-01-01

Metabolomics is an 'omics' approach that aims to comprehensively analyse all metabolites in a biological sample, and has great potential for directly elucidating plant metabolic processes. Increasing evidence supports the view that plants produce a broad range of low-molecular-weight secondary metabolites responsible for variation from species to species, thus enabling the use of secondary metabolite profiling in the chemotaxonomy. To gain deeper insights into the metabolites to increasing plant diversity, we performed systematic untargeted metabolite profiling to exploit the different parts and species of Aconitum as a case study. Application of ultraperformance liquid chromatography-quadrupole time-of-flight-high-definition mass spectrometry (UPLC-QTOF-HDMS) equipped with electrospray ionisation and coupled with pattern recognition analyses to study constituents in the root of two kinds of Aconitum species. Twenty-two metabolites between the mother root of Aconitum carmichaelii Debx (CHW) and lateral root of Aconitum carmichaelii Debx (SFZ) and 13 metabolites between the CHW and root of Aconitum kusnezoffii Reichb (CW) have been identified. Of note, songorine, carmichaeline and isotalatizidine did not exist in CW, whereas they are present in the SFZ and CHW. Metabolomics based UPLC-QTOF-HDMS with multivariate statistical models was effective for analysis of constituents in the root of two kinds of Aconitum species. Copyright © 2012 John Wiley & Sons, Ltd.

Metabolic dependence of green tea on plucking positions revisited: a metabolomic study.

PubMed

Lee, Jang-Eun; Lee, Bum-Jin; Hwang, Jeong-Ah; Ko, Kwang-Sup; Chung, Jin-Oh; Kim, Eun-Hee; Lee, Sang-Jun; Hong, Young-Shick

2011-10-12

The dependence of global green tea metabolome on plucking positions was investigated through (1)H nuclear magnetic resonance (NMR) analysis coupled with multivariate statistical data set. Pattern recognition methods, such as principal component analysis (PCA) and orthogonal projection on latent structure-discriminant analysis (OPLS-DA), were employed for a finding metabolic discrimination among fresh green tea leaves plucked at different positions from young to old leaves. In addition to clear metabolic discrimination among green tea leaves, elevations in theanine, caffeine, and gallic acid levels but reductions in catechins, such as epicatechin (EC), epigallocatechin (EGC), epicatechin-3-gallate (ECG), and epigallocatechin-3-gallate (EGCG), glucose, and sucrose levels were observed, as the green tea plant grows up. On the other hand, the younger the green tea leaf is, the more theanine, caffeine, and gallic acid but the lesser catechins accumlated in the green tea leaf, revealing a reverse assocation between theanine and catechins levels due to incorporaton of theanine into catechins with growing up green tea plant. Moreover, as compared to the tea leaf, the observation of marked high levels of theanine and low levels of catechins in green tea stems exhibited a distinct tea plant metabolism between the tea leaf and the stem. This metabolomic approach highlights taking insight to global metabolic dependence of green tea leaf on plucking position, thereby providing distinct information on green tea production with specific tea quality.

Training in metabolomics research. I. Designing the experiment, collecting and extracting samples and generating metabolomics data

PubMed Central

Barnes, Stephen; Benton, H. Paul; Casazza, Krista; Cooper, Sara J.; Cui, Xiangqin; Du, Xiuxia; Engler, Jeffrey; Kabarowski, Janusz H.; Li, Shuzhao; Pathmasiri, Wimal; Prasain, Jeevan K.; Renfrow, Matthew B.; Tiwari, Hemant K.

2016-01-01

The study of metabolism has had a long history. Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. The National Institutes of Health Common Fund Metabolomics Program was established in 2012 to stimulate interest in the approaches and technologies of metabolomics. To deliver one of the program’s goals, the University of Alabama at Birmingham has hosted an annual 4-day short course in metabolomics for faculty, postdoctoral fellows and graduate students from national and international institutions. This paper is the first part of a summary of the training materials presented in the course to be used as a resource for all those embarking on metabolomics research. PMID:27434804

A global approach to analysis and interpretation of metabolic data for plant natural product discovery.

PubMed

Hur, Manhoi; Campbell, Alexis Ann; Almeida-de-Macedo, Marcia; Li, Ling; Ransom, Nick; Jose, Adarsh; Crispin, Matt; Nikolau, Basil J; Wurtele, Eve Syrkin

2013-04-01

Discovering molecular components and their functionality is key to the development of hypotheses concerning the organization and regulation of metabolic networks. The iterative experimental testing of such hypotheses is the trajectory that can ultimately enable accurate computational modelling and prediction of metabolic outcomes. This information can be particularly important for understanding the biology of natural products, whose metabolism itself is often only poorly defined. Here, we describe factors that must be in place to optimize the use of metabolomics in predictive biology. A key to achieving this vision is a collection of accurate time-resolved and spatially defined metabolite abundance data and associated metadata. One formidable challenge associated with metabolite profiling is the complexity and analytical limits associated with comprehensively determining the metabolome of an organism. Further, for metabolomics data to be efficiently used by the research community, it must be curated in publicly available metabolomics databases. Such databases require clear, consistent formats, easy access to data and metadata, data download, and accessible computational tools to integrate genome system-scale datasets. Although transcriptomics and proteomics integrate the linear predictive power of the genome, the metabolome represents the nonlinear, final biochemical products of the genome, which results from the intricate system(s) that regulate genome expression. For example, the relationship of metabolomics data to the metabolic network is confounded by redundant connections between metabolites and gene-products. However, connections among metabolites are predictable through the rules of chemistry. Therefore, enhancing the ability to integrate the metabolome with anchor-points in the transcriptome and proteome will enhance the predictive power of genomics data. We detail a public database repository for metabolomics, tools and approaches for statistical analysis of metabolomics data, and methods for integrating these datasets with transcriptomic data to create hypotheses concerning specialized metabolisms that generate the diversity in natural product chemistry. We discuss the importance of close collaborations among biologists, chemists, computer scientists and statisticians throughout the development of such integrated metabolism-centric databases and software.

A global approach to analysis and interpretation of metabolic data for plant natural product discovery†

PubMed Central

Hur, Manhoi; Campbell, Alexis Ann; Almeida-de-Macedo, Marcia; Li, Ling; Ransom, Nick; Jose, Adarsh; Crispin, Matt; Nikolau, Basil J.

2013-01-01

Discovering molecular components and their functionality is key to the development of hypotheses concerning the organization and regulation of metabolic networks. The iterative experimental testing of such hypotheses is the trajectory that can ultimately enable accurate computational modelling and prediction of metabolic outcomes. This information can be particularly important for understanding the biology of natural products, whose metabolism itself is often only poorly defined. Here, we describe factors that must be in place to optimize the use of metabolomics in predictive biology. A key to achieving this vision is a collection of accurate time-resolved and spatially defined metabolite abundance data and associated metadata. One formidable challenge associated with metabolite profiling is the complexity and analytical limits associated with comprehensively determining the metabolome of an organism. Further, for metabolomics data to be efficiently used by the research community, it must be curated in publically available metabolomics databases. Such databases require clear, consistent formats, easy access to data and metadata, data download, and accessible computational tools to integrate genome system-scale datasets. Although transcriptomics and proteomics integrate the linear predictive power of the genome, the metabolome represents the nonlinear, final biochemical products of the genome, which results from the intricate system(s) that regulate genome expression. For example, the relationship of metabolomics data to the metabolic network is confounded by redundant connections between metabolites and gene-products. However, connections among metabolites are predictable through the rules of chemistry. Therefore, enhancing the ability to integrate the metabolome with anchor-points in the transcriptome and proteome will enhance the predictive power of genomics data. We detail a public database repository for metabolomics, tools and approaches for statistical analysis of metabolomics data, and methods for integrating these dataset with transcriptomic data to create hypotheses concerning specialized metabolism that generates the diversity in natural product chemistry. We discuss the importance of close collaborations among biologists, chemists, computer scientists and statisticians throughout the development of such integrated metabolism-centric databases and software. PMID:23447050

A systems biology approach toward understanding seed composition in soybean.

PubMed

Li, Ling; Hur, Manhoi; Lee, Joon-Yong; Zhou, Wenxu; Song, Zhihong; Ransom, Nick; Demirkale, Cumhur Yusuf; Nettleton, Dan; Westgate, Mark; Arendsee, Zebulun; Iyer, Vidya; Shanks, Jackie; Nikolau, Basil; Wurtele, Eve Syrkin

2015-01-01

The molecular, biochemical, and genetic mechanisms that regulate the complex metabolic network of soybean seed development determine the ultimate balance of protein, lipid, and carbohydrate stored in the mature seed. Many of the genes and metabolites that participate in seed metabolism are unknown or poorly defined; even more remains to be understood about the regulation of their metabolic networks. A global omics analysis can provide insights into the regulation of seed metabolism, even without a priori assumptions about the structure of these networks. With the future goal of predictive biology in mind, we have combined metabolomics, transcriptomics, and metabolic flux technologies to reveal the global developmental and metabolic networks that determine the structure and composition of the mature soybean seed. We have coupled this global approach with interactive bioinformatics and statistical analyses to gain insights into the biochemical programs that determine soybean seed composition. For this purpose, we used Plant/Eukaryotic and Microbial Metabolomics Systems Resource (PMR, http://www.metnetdb.org/pmr, a platform that incorporates metabolomics data to develop hypotheses concerning the organization and regulation of metabolic networks, and MetNet systems biology tools http://www.metnetdb.org for plant omics data, a framework to enable interactive visualization of metabolic and regulatory networks. This combination of high-throughput experimental data and bioinformatics analyses has revealed sets of specific genes, genetic perturbations and mechanisms, and metabolic changes that are associated with the developmental variation in soybean seed composition. Researchers can explore these metabolomics and transcriptomics data interactively at PMR.

Metabolic Fingerprinting to Assess the Impact of Salinity on Carotenoid Content in Developing Tomato Fruits

PubMed Central

Van Meulebroek, Lieven; Hanssens, Jochen; Steppe, Kathy; Vanhaecke, Lynn

2016-01-01

As the presence of health-promoting substances has become a significant aspect of tomato fruit appreciation, this study investigated nutrient solution salinity as a tool to enhance carotenoid accumulation in cherry tomato fruit (Solanum lycopersicum L. cv. Juanita). Hereby, a key objective was to uncover the underlying mechanisms of carotenoid metabolism, moving away from typical black box research strategies. To this end, a greenhouse experiment with five salinity treatments (ranging from 2.0 to 5.0 decisiemens (dS) m−1) was carried out and a metabolomic fingerprinting approach was applied to obtain valuable insights on the complicated interactions between salinity treatments, environmental conditions, and the plant’s genetic background. Hereby, several hundreds of metabolites were attributed a role in the plant’s salinity response (at the fruit level), whereby the overall impact turned out to be highly depending on the developmental stage. In addition, 46 of these metabolites embraced a dual significance as they were ascribed a prominent role in carotenoid metabolism as well. Based on the specific mediating actions of the retained metabolites, it could be determined that altered salinity had only marginal potential to enhance carotenoid accumulation in the concerned tomato fruit cultivar. This study invigorates the usefulness of metabolomics in modern agriculture, for instance in modeling tomato fruit quality. Moreover, the metabolome changes that were caused by the different salinity levels may enclose valuable information towards other salinity-related plant processes as well. PMID:27240343

Fusarium oxysporum mediates systems metabolic reprogramming of chickpea roots as revealed by a combination of proteomics and metabolomics.

PubMed

Kumar, Yashwant; Zhang, Limin; Panigrahi, Priyabrata; Dholakia, Bhushan B; Dewangan, Veena; Chavan, Sachin G; Kunjir, Shrikant M; Wu, Xiangyu; Li, Ning; Rajmohanan, Pattuparambil R; Kadoo, Narendra Y; Giri, Ashok P; Tang, Huiru; Gupta, Vidya S

2016-07-01

Molecular changes elicited by plants in response to fungal attack and how this affects plant-pathogen interaction, including susceptibility or resistance, remain elusive. We studied the dynamics in root metabolism during compatible and incompatible interactions between chickpea and Fusarium oxysporum f. sp. ciceri (Foc), using quantitative label-free proteomics and NMR-based metabolomics. Results demonstrated differential expression of proteins and metabolites upon Foc inoculations in the resistant plants compared with the susceptible ones. Additionally, expression analysis of candidate genes supported the proteomic and metabolic variations in the chickpea roots upon Foc inoculation. In particular, we found that the resistant plants revealed significant increase in the carbon and nitrogen metabolism; generation of reactive oxygen species (ROS), lignification and phytoalexins. The levels of some of the pathogenesis-related proteins were significantly higher upon Foc inoculation in the resistant plant. Interestingly, results also exhibited the crucial role of altered Yang cycle, which contributed in different methylation reactions and unfolded protein response in the chickpea roots against Foc. Overall, the observed modulations in the metabolic flux as outcome of several orchestrated molecular events are determinant of plant's role in chickpea-Foc interactions. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Gene Discovery of Characteristic Metabolic Pathways in the Tea Plant (Camellia sinensis) Using ‘Omics’-Based Network Approaches: A Future Perspective

PubMed Central

Zhang, Shihua; Zhang, Liang; Tai, Yuling; Wang, Xuewen; Ho, Chi-Tang; Wan, Xiaochun

2018-01-01

Characteristic secondary metabolites, including flavonoids, theanine and caffeine, in the tea plant (Camellia sinensis) are the primary sources of the rich flavors, fresh taste, and health benefits of tea. The decoding of genes involved in these characteristic components is still significantly lagging, which lays an obstacle for applied genetic improvement and metabolic engineering. With the popularity of high-throughout transcriptomics and metabolomics, ‘omics’-based network approaches, such as gene co-expression network and gene-to-metabolite network, have emerged as powerful tools for gene discovery of plant-specialized (secondary) metabolism. Thus, it is pivotal to summarize and introduce such system-based strategies in facilitating gene identification of characteristic metabolic pathways in the tea plant (or other plants). In this review, we describe recent advances in transcriptomics and metabolomics for transcript and metabolite profiling, and highlight ‘omics’-based network strategies using successful examples in model and non-model plants. Further, we summarize recent progress in ‘omics’ analysis for gene identification of characteristic metabolites in the tea plant. Limitations of the current strategies are discussed by comparison with ‘omics’-based network approaches. Finally, we demonstrate the potential of introducing such network strategies in the tea plant, with a prospects ending for a promising network discovery of characteristic metabolite genes in the tea plant. PMID:29915604

A Central Role of Abscisic Acid in Stress-Regulated Carbohydrate Metabolism

PubMed Central

Kempa, Stefan; Krasensky, Julia; Dal Santo, Silvia; Kopka, Joachim; Jonak, Claudia

2008-01-01

Background Abiotic stresses adversely affect plant growth and development. The hormone abscisic acid (ABA) plays a central role in the response and adaptation to environmental constraints. However, apart from the well established role of ABA in regulating gene expression programmes, little is known about its function in plant stress metabolism. Principal Findings Using an integrative multiparallel approach of metabolome and transcriptome analyses, we studied the dynamic response of the model glyophyte Arabidopsis thaliana to ABA and high salt conditions. Our work shows that salt stress induces complex re-adjustment of carbohydrate metabolism and that ABA triggers the initial steps of carbon mobilisation. Significance These findings open new perspectives on how high salinity and ABA impact on central carbohydrate metabolism and highlight the power of iterative combinatorial approaches of non-targeted and hypothesis-driven experiments in stress biology. PMID:19081841

The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datasets.

PubMed

Carroll, Adam J; Badger, Murray R; Harvey Millar, A

2010-07-14

Standardization of analytical approaches and reporting methods via community-wide collaboration can work synergistically with web-tool development to result in rapid community-driven expansion of online data repositories suitable for data mining and meta-analysis. In metabolomics, the inter-laboratory reproducibility of gas-chromatography/mass-spectrometry (GC/MS) makes it an obvious target for such development. While a number of web-tools offer access to datasets and/or tools for raw data processing and statistical analysis, none of these systems are currently set up to act as a public repository by easily accepting, processing and presenting publicly submitted GC/MS metabolomics datasets for public re-analysis. Here, we present MetabolomeExpress, a new File Transfer Protocol (FTP) server and web-tool for the online storage, processing, visualisation and statistical re-analysis of publicly submitted GC/MS metabolomics datasets. Users may search a quality-controlled database of metabolite response statistics from publicly submitted datasets by a number of parameters (eg. metabolite, species, organ/biofluid etc.). Users may also perform meta-analysis comparisons of multiple independent experiments or re-analyse public primary datasets via user-friendly tools for t-test, principal components analysis, hierarchical cluster analysis and correlation analysis. They may interact with chromatograms, mass spectra and peak detection results via an integrated raw data viewer. Researchers who register for a free account may upload (via FTP) their own data to the server for online processing via a novel raw data processing pipeline. MetabolomeExpress https://www.metabolome-express.org provides a new opportunity for the general metabolomics community to transparently present online the raw and processed GC/MS data underlying their metabolomics publications. Transparent sharing of these data will allow researchers to assess data quality and draw their own insights from published metabolomics datasets.

Characterising and correcting batch variation in an automated direct infusion mass spectrometry (DIMS) metabolomics workflow.

PubMed

Kirwan, J A; Broadhurst, D I; Davidson, R L; Viant, M R

2013-06-01

Direct infusion mass spectrometry (DIMS)-based untargeted metabolomics measures many hundreds of metabolites in a single experiment. While every effort is made to reduce within-experiment analytical variation in untargeted metabolomics, unavoidable sources of measurement error are introduced. This is particularly true for large-scale multi-batch experiments, necessitating the development of robust workflows that minimise batch-to-batch variation. Here, we conducted a purpose-designed, eight-batch DIMS metabolomics study using nanoelectrospray (nESI) Fourier transform ion cyclotron resonance mass spectrometric analyses of mammalian heart extracts. First, we characterised the intrinsic analytical variation of this approach to determine whether our existing workflows are fit for purpose when applied to a multi-batch investigation. Batch-to-batch variation was readily observed across the 7-day experiment, both in terms of its absolute measurement using quality control (QC) and biological replicate samples, as well as its adverse impact on our ability to discover significant metabolic information within the data. Subsequently, we developed and implemented a computational workflow that includes total-ion-current filtering, QC-robust spline batch correction and spectral cleaning, and provide conclusive evidence that this workflow reduces analytical variation and increases the proportion of significant peaks. We report an overall analytical precision of 15.9%, measured as the median relative standard deviation (RSD) for the technical replicates of the biological samples, across eight batches and 7 days of measurements. When compared against the FDA guidelines for biomarker studies, which specify an RSD of <20% as an acceptable level of precision, we conclude that our new workflows are fit for purpose for large-scale, high-throughput nESI DIMS metabolomics studies.

Comparative mass spectrometry & nuclear magnetic resonance metabolomic approaches for nutraceuticals quality control analysis: a brief review.

PubMed

Farag, Mohamed A

2014-01-01

The number of botanical dietary supplements in the market has recently increased primarily due to increased health awareness. Standardization and quality control of the constituents of these plant extracts is an important topic, particularly when such ingredients are used long term as dietary supplements, or in cases where higher doses are marketed as drugs. The development of fast, comprehensive, and effective untargeted analytical methods for plant extracts is of high interest. Nuclear magnetic resonance spectroscopy and mass spectrometry are the most informative tools, each of which enables high-throughput and global analysis of hundreds of metabolites in a single step. Although only one of the two techniques is utilized in the majority of plant metabolomics applications, there is a growing interest in combining the data from both platforms to effectively unravel the complexity of plant samples. The application of combined MS and NMR in the quality control of nutraceuticals forms the major part of this review. Finally I will look at the future developments and perspectives of these two technologies for the quality control of herbal materials.

Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis.

PubMed

Xia, Jianguo; Wishart, David S

2016-09-07

MetaboAnalyst (http://www.metaboanalyst.ca) is a comprehensive Web application for metabolomic data analysis and interpretation. MetaboAnalyst handles most of the common metabolomic data types from most kinds of metabolomics platforms (MS and NMR) for most kinds of metabolomics experiments (targeted, untargeted, quantitative). In addition to providing a variety of data processing and normalization procedures, MetaboAnalyst also supports a number of data analysis and data visualization tasks using a range of univariate, multivariate methods such as PCA (principal component analysis), PLS-DA (partial least squares discriminant analysis), heatmap clustering and machine learning methods. MetaboAnalyst also offers a variety of tools for metabolomic data interpretation including MSEA (metabolite set enrichment analysis), MetPA (metabolite pathway analysis), and biomarker selection via ROC (receiver operating characteristic) curve analysis, as well as time series and power analysis. This unit provides an overview of the main functional modules and the general workflow of the latest version of MetaboAnalyst (MetaboAnalyst 3.0), followed by eight detailed protocols. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

An Overview on the Importance of Combining Complementary Analytical Platforms in Metabolomic Research.

PubMed

Gonzalez-Dominguez, Alvaro; Duran-Guerrero, Enrique; Fernandez-Recamales, Angeles; Lechuga-Sancho, Alfonso Maria; Sayago, Ana; Schwarz, Monica; Segundo, Carmen; Gonzalez-Dominguez, Raul

2017-01-01

The analytical bias introduced by most of the commonly used techniques in metabolomics considerably hinders the simultaneous detection of all metabolites present in complex biological samples. In order to solve this limitation, the combination of complementary approaches is emerging in recent years as the most suitable strategy in order to maximize metabolite coverage. This review article presents a general overview of the most important analytical techniques usually employed in metabolomics: nuclear magnetic resonance, mass spectrometry and hybrid approaches. Furthermore, we emphasize the potential of integrating various tools in the form of metabolomic multi-platforms in order to get a deeper metabolome characterization, for which a revision of the existing literature in this field is provided. This review is not intended to be exhaustive but, rather, to give a practical and concise guide to readers not familiar with analytical chemistry on the considerations to account for the proper selection of the technique to be used in a metabolomic experiment in biomedical research. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Can NMR solve some significant challenges in metabolomics?

PubMed Central

Gowda, G.A. Nagana; Raftery, Daniel

2015-01-01

The field of metabolomics continues to witness rapid growth driven by fundamental studies, methods development, and applications in a number of disciplines that include biomedical science, plant and nutrition sciences, drug development, energy and environmental sciences, toxicology, etc. NMR spectroscopy is one of the two most widely used analytical platforms in the metabolomics field, along with mass spectrometry (MS). NMR's excellent reproducibility and quantitative accuracy, its ability to identify structures of unknown metabolites, its capacity to generate metabolite profiles using intact biospecimens with no need for separation, and its capabilities for tracing metabolic pathways using isotope labeled substrates offer unique strengths for metabolomics applications. However, NMR's limited sensitivity and resolution continue to pose a major challenge and have restricted both the number and the quantitative accuracy of metabolites analyzed by NMR. Further, the analysis of highly complex biological samples has increased the demand for new methods with improved detection, better unknown identification, and more accurate quantitation of larger numbers of metabolites. Recent efforts have contributed significant improvements in these areas, and have thereby enhanced the pool of routinely quantifiable metabolites. Additionally, efforts focused on combining NMR and MS promise opportunities to exploit the combined strength of the two analytical platforms for direct comparison of the metabolite data, unknown identification and reliable biomarker discovery that continue to challenge the metabolomics field. This article presents our perspectives on the emerging trends in NMR-based metabolomics and NMR's continuing role in the field with an emphasis on recent and ongoing research from our laboratory. PMID:26476597

Can NMR solve some significant challenges in metabolomics?

NASA Astrophysics Data System (ADS)

Nagana Gowda, G. A.; Raftery, Daniel

2015-11-01

The field of metabolomics continues to witness rapid growth driven by fundamental studies, methods development, and applications in a number of disciplines that include biomedical science, plant and nutrition sciences, drug development, energy and environmental sciences, toxicology, etc. NMR spectroscopy is one of the two most widely used analytical platforms in the metabolomics field, along with mass spectrometry (MS). NMR's excellent reproducibility and quantitative accuracy, its ability to identify structures of unknown metabolites, its capacity to generate metabolite profiles using intact bio-specimens with no need for separation, and its capabilities for tracing metabolic pathways using isotope labeled substrates offer unique strengths for metabolomics applications. However, NMR's limited sensitivity and resolution continue to pose a major challenge and have restricted both the number and the quantitative accuracy of metabolites analyzed by NMR. Further, the analysis of highly complex biological samples has increased the demand for new methods with improved detection, better unknown identification, and more accurate quantitation of larger numbers of metabolites. Recent efforts have contributed significant improvements in these areas, and have thereby enhanced the pool of routinely quantifiable metabolites. Additionally, efforts focused on combining NMR and MS promise opportunities to exploit the combined strength of the two analytical platforms for direct comparison of the metabolite data, unknown identification and reliable biomarker discovery that continue to challenge the metabolomics field. This article presents our perspectives on the emerging trends in NMR-based metabolomics and NMR's continuing role in the field with an emphasis on recent and ongoing research from our laboratory.

Integrated transcriptomics and metabolomics decipher differences in the resistance of pedunculate oak to the herbivore Tortrix viridana L.

PubMed Central

2013-01-01

Background The interaction between insect pests and their host plants is a never-ending race of evolutionary adaption. Plants have developed an armament against insect herbivore attacks, and attackers continuously learn how to address it. Using a combined transcriptomic and metabolomic approach, we investigated the molecular and biochemical differences between Quercus robur L. trees that resisted (defined as resistant oak type) or were susceptible (defined as susceptible oak type) to infestation by the major oak pest, Tortrix viridana L. Results Next generation RNA sequencing revealed hundreds of genes that exhibited constitutive and/or inducible differential expression in the resistant oak compared to the susceptible oak. Distinct differences were found in the transcript levels and the metabolic content with regard to tannins, flavonoids, and terpenoids, which are compounds involved in the defence against insect pests. The results of our transcriptomic and metabolomic analyses are in agreement with those of a previous study in which we showed that female moths prefer susceptible oaks due to their specific profile of herbivore-induced volatiles. These data therefore define two oak genotypes that clearly differ on the transcriptomic and metabolomic levels, as reflected by their specific defensive compound profiles. Conclusions We conclude that the resistant oak type seem to prefer a strategy of constitutive defence responses in contrast to more induced defence responses of the susceptible oaks triggered by feeding. These results pave the way for the development of biomarkers for an early determination of potentially green oak leaf roller-resistant genotypes in natural pedunculate oak populations in Europe. PMID:24160444

Plant stress biomarkers from biosimulations: the Transcriptome-To-Metabolome (TTM) technology - effects of drought stress on rice.

PubMed

Phelix, C F; Feltus, F A

2015-01-01

Measuring biomarkers from plant tissue samples is challenging and expensive when the desire is to integrate transcriptomics, fluxomics, metabolomics, lipidomics, proteomics, physiomics and phenomics. We present a computational biology method where only the transcriptome needs to be measured and is used to derive a set of parameters for deterministic kinetic models of metabolic pathways. The technology is called Transcriptome-To-Metabolome (TTM) biosimulations, currently under commercial development, but available for non-commercial use by researchers. The simulated results on metabolites of 30 primary and secondary metabolic pathways in rice (Oryza sativa) were used as the biomarkers to predict whether the transcriptome was from a plant that had been under drought conditions. The rice transcriptomes were accessed from public archives and each individual plant was simulated. This unique quality of the TTM technology allows standard analyses on biomarker assessments, i.e. sensitivity, specificity, positive and negative predictive values, accuracy, receiver operator characteristics (ROC) curve and area under the ROC curve (AUC). Two validation methods were also used, the holdout and 10-fold cross validations. Initially 17 metabolites were identified as candidate biomarkers based on either statistical significance on binary phenotype when compared with control samples or recognition from the literature. The top three biomarkers based on AUC were gibberellic acid 12 (0.89), trehalose (0.80) and sn1-palmitate-sn2-oleic-phosphatidylglycerol (0.70). Neither heat map analyses of transcriptomes nor all 300 metabolites clustered the stressed and control groups effectively. The TTM technology allows the emergent properties of the integrated system to generate unique and useful 'Omics' information. © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands.

Metabolome analysis of Arabidopsis thaliana roots identifies a key metabolic pathway for iron acquisition.

PubMed

Schmidt, Holger; Günther, Carmen; Weber, Michael; Spörlein, Cornelia; Loscher, Sebastian; Böttcher, Christoph; Schobert, Rainer; Clemens, Stephan

2014-01-01

Fe deficiency compromises both human health and plant productivity. Thus, it is important to understand plant Fe acquisition strategies for the development of crop plants which are more Fe-efficient under Fe-limited conditions, such as alkaline soils, and have higher Fe density in their edible tissues. Root secretion of phenolic compounds has long been hypothesized to be a component of the reduction strategy of Fe acquisition in non-graminaceous plants. We therefore subjected roots of Arabidopsis thaliana plants grown under Fe-replete and Fe-deplete conditions to comprehensive metabolome analysis by gas chromatography-mass spectrometry and ultra-pressure liquid chromatography electrospray ionization quadrupole time-of-flight mass spectrometry. Scopoletin and other coumarins were found among the metabolites showing the strongest response to two different Fe-limited conditions, the cultivation in Fe-free medium and in medium with an alkaline pH. A coumarin biosynthesis mutant defective in ortho-hydroxylation of cinnamic acids was unable to grow on alkaline soil in the absence of Fe fertilization. Co-cultivation with wild-type plants partially rescued the Fe deficiency phenotype indicating a contribution of extracellular coumarins to Fe solubilization. Indeed, coumarins were detected in root exudates of wild-type plants. Direct infusion mass spectrometry as well as UV/vis spectroscopy indicated that coumarins are acting both as reductants of Fe(III) and as ligands of Fe(II).

Training in metabolomics research. I. Designing the experiment, collecting and extracting samples and generating metabolomics data.

PubMed

Barnes, Stephen; Benton, H Paul; Casazza, Krista; Cooper, Sara J; Cui, Xiangqin; Du, Xiuxia; Engler, Jeffrey; Kabarowski, Janusz H; Li, Shuzhao; Pathmasiri, Wimal; Prasain, Jeevan K; Renfrow, Matthew B; Tiwari, Hemant K

2016-07-01

The study of metabolism has had a long history. Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. The National Institutes of Health Common Fund Metabolomics Program was established in 2012 to stimulate interest in the approaches and technologies of metabolomics. To deliver one of the program's goals, the University of Alabama at Birmingham has hosted an annual 4-day short course in metabolomics for faculty, postdoctoral fellows and graduate students from national and international institutions. This paper is the first part of a summary of the training materials presented in the course to be used as a resource for all those embarking on metabolomics research. The complete set of training materials including slide sets and videos can be viewed at http://www.uab.edu/proteomics/metabolomics/workshop/workshop_june_2015.php. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

The essential role of coumarin secretion for Fe acquisition from alkaline soil

PubMed Central

Clemens, Stephan; Weber, Michael

2016-01-01

ABSTRACT Plant productivity is limited by the scarcity of the essential micronutrient iron particularly in alkaline soils. The root secretion of phenolics has long been recognized as a component of the acidification-reduction strategy to acquire iron (strategy I). However, very little molecular insight into this process was available until recently several research groups independently discovered the important role of coumarins for the growth of Arabidopsis thaliana under Fe-limited conditions. Genome-wide analyses of iron deficiency responses, mutant screening and metabolomics experiments all converged on the finding that the synthesis and root exudation of scopoletin, esculetin and other coumarins is essential for iron uptake from substrates with low iron availability. Here we describe the evidence supporting this conclusion and discuss important questions that now have to be addressed in order to better understand the mechanistic basis of coumarin-dependent iron uptake and its significance within the plant kingdom. PMID:26618918

Use of Rhizosphere Metabolomics to Investigate Exudation of Phenolics by Arabidopsis Roots

NASA Astrophysics Data System (ADS)

Lee, Yong Jian; Rai, Amit; Reuben, Sheela; Nesati, Victor; Almeida, Reinaldo; Swarup, Sanjay

2013-04-01

The rhizosphere is a specialised micro-niche for bacteria that have an active exchange of signals and nutrients with the host plant. Nearly 20% of photosynthates are released as root exudates, which consist of primary metabolites and products of secondary metabolism which are largely phenolic in nature. Previously, using rhizosphere metabolomics, we showed that nearly 50% of organic carbon in the exudates is in the form of phenolic compounds, of which the largest fraction is from the phenylpropanoid synthesis pathway. Using Arabidopsis as a model, we have demonstrated that a biased rhizosphere can be created using plants with varying levels of phenylpropanoids due to mutations in the biosynthetic or regulatory genes. These phenylpropanoids levels are reflected in the exudates, and exudates from lines with regulatory gene mutations, tt8 and ttg, have higher levels of phenylpropanoids, whereas biosynthetic mutant line, tt4, has very low and undetectable levels of phenylpropanoids. The biased rhizosphere of tt8 and ttg lines provides a nutritional advantage to rhizobacteria that can utilize these phenylpropanoids such as quercetin. With such a strategy to increase the competitiveness of plant growth-promoting rhizobacteria (PGPR) such as Pseudomonas putida, this system can be applied to improve plant performance. In order to better understand the metabolic basis of the nutritional advantage behind the competitiveness of the favoured P. putida, we elucidated its quercetin utilization pathway. We have recently cloned the gene for quercetin oxidoreductase (QuoA) and expressed it in transgenic Arabidopsis lines to alter the plant phenylpropanoid metabolism, using a gain of function approach. Since phenylpropanoid biosynthesis in plants involve formation of quercetin from naringenin, we envisaged that QuoA expression in plants will provide us with a genetic tool to "reverse" this biosynthetic step. This perturbation led to a decrease in flavonoids and an increase in lignin and anthocyanin metabolites. We describe here the metabolites present in the root exudates using high resolution accurate mass (HRAM) metabolomics approach. Using this approach, biased rhizosphere for another class of PGPR strains can now be created. In this case, lignin- and anthocyanin- utilizing strains will be selectively preferred. We have set up a platform to perform metabolomics of exudates at the root surface. This has allowed us to use the liquid extraction surface analysis (LESA) system using a Thermo Velos Pro Orbitrap-MS to identify differences in exudate profiles along the root system of Arabidopsis. This platform enables direct sampling and measurement from plant roots grown aeroponically. As the metabolites are extracted from root surface and directly injected into the mass spectrometer, there is minimal loss of sample in this process. This method will now allow us to further dissect rhizosphere properties from places such as young root apex, as well as from the more mature base of roots. Taken together, these resources of altered rhizosphere, nutrient utilization pathways in microbes and surface analysis technology will help in extending our understanding of the processes in the plant rhizosphere.

Metabolomics to Decipher the Chemical Defense of Cereals against Fusarium graminearum and Deoxynivalenol Accumulation

PubMed Central

Gauthier, Léa; Atanasova-Penichon, Vessela; Chéreau, Sylvain; Richard-Forget, Florence

2015-01-01

Fusarium graminearum is the causal agent of Fusarium head blight (FHB) and Gibberella ear rot (GER), two devastating diseases of wheat, barley, and maize. Furthermore, F. graminearum species can produce type B trichothecene mycotoxins that accumulate in grains. Use of FHB and GER resistant cultivars is one of the most promising strategies to reduce damage induced by F. graminearum. Combined with genetic approaches, metabolomic ones can provide powerful opportunities for plant breeding through the identification of resistant biomarker metabolites which have the advantage of integrating the genetic background and the influence of the environment. In the past decade, several metabolomics attempts have been made to decipher the chemical defense that cereals employ to counteract F. graminearum. By covering the major classes of metabolites that have been highlighted and addressing their potential role, this review demonstrates the complex and integrated network of events that cereals can orchestrate to resist to F. graminearum. PMID:26492237

Systematization of the protein sequence diversity in enzymes related to secondary metabolic pathways in plants, in the context of big data biology inspired by the KNApSAcK motorcycle database.

PubMed

Ikeda, Shun; Abe, Takashi; Nakamura, Yukiko; Kibinge, Nelson; Hirai Morita, Aki; Nakatani, Atsushi; Ono, Naoaki; Ikemura, Toshimichi; Nakamura, Kensuke; Altaf-Ul-Amin, Md; Kanaya, Shigehiko

2013-05-01

Biology is increasingly becoming a data-intensive science with the recent progress of the omics fields, e.g. genomics, transcriptomics, proteomics and metabolomics. The species-metabolite relationship database, KNApSAcK Core, has been widely utilized and cited in metabolomics research, and chronological analysis of that research work has helped to reveal recent trends in metabolomics research. To meet the needs of these trends, the KNApSAcK database has been extended by incorporating a secondary metabolic pathway database called Motorcycle DB. We examined the enzyme sequence diversity related to secondary metabolism by means of batch-learning self-organizing maps (BL-SOMs). Initially, we constructed a map by using a big data matrix consisting of the frequencies of all possible dipeptides in the protein sequence segments of plants and bacteria. The enzyme sequence diversity of the secondary metabolic pathways was examined by identifying clusters of segments associated with certain enzyme groups in the resulting map. The extent of diversity of 15 secondary metabolic enzyme groups is discussed. Data-intensive approaches such as BL-SOM applied to big data matrices are needed for systematizing protein sequences. Handling big data has become an inevitable part of biology.

Monitoring Metabolite Profiles of Cannabis sativa L. Trichomes during Flowering Period Using 1H NMR-Based Metabolomics and Real-Time PCR.

PubMed

Happyana, Nizar; Kayser, Oliver

2016-08-01

Cannabis sativa trichomes are glandular structures predominantly responsible for the biosynthesis of cannabinoids, the biologically active compounds unique to this plant. To the best of our knowledge, most metabolomic works on C. sativa that have been reported previously focused their investigations on the flowers and leaves of this plant. In this study, (1)H NMR-based metabolomics and real-time PCR analysis were applied for monitoring the metabolite profiles of C. sativa trichomes, variety Bediol, during the last 4 weeks of the flowering period. Partial least squares discriminant analysis models successfully classified metabolites of the trichomes based on the harvest time. Δ (9)-Tetrahydrocannabinolic acid (1) and cannabidiolic acid (2) constituted the vital differential components of the organic preparations, while asparagine, glutamine, fructose, and glucose proved to be their water-extracted counterparts. According to RT-PCR analysis, gene expression levels of olivetol synthase and olivetolic acid cyclase influenced the accumulation of cannabinoids in the Cannabis trichomes during the monitoring time. Moreover, quantitative (1)H NMR and RT-PCR analysis of the Cannabis trichomes suggested that the gene regulation of cannabinoid biosynthesis in the C. sativa variety Bediol is unique when compared with other C. sativa varieties. Georg Thieme Verlag KG Stuttgart · New York.

Effect of Antibiotics and Diet on Enterolactone Concentration and Metabolome Studied by Targeted and Nontargeted LC-MS Metabolomics.

PubMed

Bolvig, Anne K; Nørskov, Natalja P; Hedemann, Mette S; Foldager, Leslie; McCarthy-Sinclair, Brendan; Marco, Maria L; Lærke, Helle N; Bach Knudsen, Knud E

2017-06-02

High plant lignan intake is associated with a number of health benefits, possibly induced by the lignan metabolite enterolactone (ENL). The gut microbiota plays a crucial role in converting dietary lignans into ENL, and epidemiological studies have shown that use of antibiotics is associated with lower levels of ENL. Here we investigate the link between antibiotic use and lignan metabolism in pigs using LC-MS/MS. The effect of lignan intake and antibiotic use on the gut microbial community and the pig metabolome is studied by 16S rRNA sequencing and nontargeted LC-MS. Treatment with antibiotics resulted in substantially lower concentrations of ENL compared with concentrations detected in untreated animals, whereas the plasma concentrations of plant lignans were unchanged. Both diet and antibiotic treatment affected the clustering of urinary metabolites and significantly altered the proportions of taxa in the gut microbiota. Diet, but not antibiotic treatment, affected the plasma lipid profile, and a lower concentration of LDL cholesterol was observed in the pigs fed a high lignan diet. This study provides solid support for the associations between ENL concentrations and use of antibiotics found in humans and indicates that the lower ENL concentration may be a consequence of the ecological changes in the microbiota.

Metabolomics for the Authentication of Natural Extracts Used in Flavors and Fragrances: the Case Study of Violet Leaf Absolutes from Viola odorata.

PubMed

Saint-Lary, Laure; Roy, Céline; Paris, Jean-Philippe; Martin, Jean-François; Thomas, Olivier P; Fernandez, Xavier

2016-06-01

Natural extracts used in fine fragrances (alcoholic perfumes) are rare and precious. As such, they represent an interesting target for fraudulent practices called adulterations. Absolutes, important materials used in the creation of perfumes, are obtained by organic solvent extraction of raw plant materials. Because the nonvolatile part of these natural extracts is not normalized and scarcely reported, highlighting potential adulterations present in this fraction appears highly challenging. For the first time, we investigated the use of nontargeted UHPLC-ToFMS metabolomics for this purpose, considering Viola odorata l., a plant largely used in the perfume industry, as a model. Significant differences in the metabolic fingerprints of the violet leaf absolutes were evidenced according to geographical locations, and/or adulterations. Additionally, markers of the geographical origin were detected through their molecular weight/most probable molecular formula and retention time, while adulterations were statistically validated. In this study, we thus clearly demonstrated the efficiency of UHPLC-ToFMS-based metabolomics in accelerating both the identification of the origin of raw materials as well as the search for potential adulterations in absolutes, natural products of high added value. © 2016 Verlag Helvetica Chimica Acta AG, Zürich.

Clinical application of metabolomics in neonatology.

PubMed

Fanos, Vassilios; Antonucci, Roberto; Barberini, Luigi; Noto, Antonio; Atzori, Luigi

2012-04-01

The youngest and more rapidly increasing "omic" discipline, called metabolomics, is the process of describing the phenotype of a cell, tissue or organism through the full complement of metabolites present. Metabolomics measure global sets of low molecular weight metabolites (including amino acids, organic acids, sugars, fatty acids, lipids, steroids, small peptides, vitamins, etc.), thus providing a "snapshot" of the metabolic status of a cell, tissue or organism in relation to genetic variations or external stimuli. The use of metabolomics appears to be a promising tool in neonatology. The management of sick newborns might improve if more information on perinatal/neonatal maturational processes and their metabolic background were available. Urine ("a window on the organism") is a biofluid particularly suitable for metabolomic analysis in neonatology because it may be collected by using simple, noninvasive techniques and because it may provide valuable diagnostic information. In this review, the authors report the few literature data on neonatal metabolomics, including their personal experience, in the following fields: intrauterine growth restriction, perinatal transition, asphyxia, brain injury and hypothermia, maternal milk evaluation, postnatal maturation, bronchiolitis, sepsis, patent ductus arteriosus, respiratory distress syndrome, nephrouropathies, metabolic diseases, antibiotic treatment, perinatal programming and long-term outcome in extremely low birth-weight infants.

Can NMR solve some significant challenges in metabolomics?

PubMed

Nagana Gowda, G A; Raftery, Daniel

2015-11-01

The field of metabolomics continues to witness rapid growth driven by fundamental studies, methods development, and applications in a number of disciplines that include biomedical science, plant and nutrition sciences, drug development, energy and environmental sciences, toxicology, etc. NMR spectroscopy is one of the two most widely used analytical platforms in the metabolomics field, along with mass spectrometry (MS). NMR's excellent reproducibility and quantitative accuracy, its ability to identify structures of unknown metabolites, its capacity to generate metabolite profiles using intact bio-specimens with no need for separation, and its capabilities for tracing metabolic pathways using isotope labeled substrates offer unique strengths for metabolomics applications. However, NMR's limited sensitivity and resolution continue to pose a major challenge and have restricted both the number and the quantitative accuracy of metabolites analyzed by NMR. Further, the analysis of highly complex biological samples has increased the demand for new methods with improved detection, better unknown identification, and more accurate quantitation of larger numbers of metabolites. Recent efforts have contributed significant improvements in these areas, and have thereby enhanced the pool of routinely quantifiable metabolites. Additionally, efforts focused on combining NMR and MS promise opportunities to exploit the combined strength of the two analytical platforms for direct comparison of the metabolite data, unknown identification and reliable biomarker discovery that continue to challenge the metabolomics field. This article presents our perspectives on the emerging trends in NMR-based metabolomics and NMR's continuing role in the field with an emphasis on recent and ongoing research from our laboratory. Copyright © 2015 Elsevier Inc. All rights reserved.

Metabolomic profiling of the nectars of Aquilegia pubescens and A. Canadensis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Noutsos, Christos; Perera, Ann M.; Nikolau, Basil J.

To date, variation in nectar chemistry of flowering plants has not been studied in detail. Such variation exerts considerable influence on pollinator–plant interactions, as well as on flower traits that play important roles in the selection of a plant for visitation by specific pollinators. Over the past 60 years the Aquilegia genus has been used as a key model for speciation studies. In this study, we defined the metabolomic profiles of flower samples of two Aquilegia species, A. Canadensis and A. pubescens. We identified a total of 75 metabolites that were classified into six main categories: organic acids, fattymore » acids, amino acids, esters, sugars, and unknowns. The mean abundances of 25 of these metabolites were significantly different between the two species, providing insights into interspecies variation in floral chemistry. Using the PlantSEED biochemistry database, we found that the majority of these metabolites are involved in biosynthetic pathways. Finally, we explored the annotated genome of A. coerulea, using the PlantSEED pipeline and reconstructed the metabolic network of Aquilegia. As a result, this network, which contains the metabolic pathways involved in generating the observed chemical variation, is now publicly available from the DOE Systems Biology Knowledge Base (KBase; http://kbase.us).« less

Metabolomic profiling of the nectars of Aquilegia pubescens and A. Canadensis

DOE PAGES

Noutsos, Christos; Perera, Ann M.; Nikolau, Basil J.; ...

2015-05-01

To date, variation in nectar chemistry of flowering plants has not been studied in detail. Such variation exerts considerable influence on pollinator–plant interactions, as well as on flower traits that play important roles in the selection of a plant for visitation by specific pollinators. Over the past 60 years the Aquilegia genus has been used as a key model for speciation studies. In this study, we defined the metabolomic profiles of flower samples of two Aquilegia species, A. Canadensis and A. pubescens. We identified a total of 75 metabolites that were classified into six main categories: organic acids, fattymore » acids, amino acids, esters, sugars, and unknowns. The mean abundances of 25 of these metabolites were significantly different between the two species, providing insights into interspecies variation in floral chemistry. Using the PlantSEED biochemistry database, we found that the majority of these metabolites are involved in biosynthetic pathways. Finally, we explored the annotated genome of A. coerulea, using the PlantSEED pipeline and reconstructed the metabolic network of Aquilegia. As a result, this network, which contains the metabolic pathways involved in generating the observed chemical variation, is now publicly available from the DOE Systems Biology Knowledge Base (KBase; http://kbase.us).« less

Effect of the environment on the secondary metabolic profile of Tithonia diversifolia: a model for environmental metabolomics of plants.

PubMed

Sampaio, Bruno Leite; Edrada-Ebel, RuAngelie; Da Costa, Fernando Batista

2016-07-07

Tithonia diversifolia is an invasive weed commonly found in tropical ecosystems. In this work, we investigate the influence of different abiotic environmental factors on the plant's metabolite profile by multivariate statistical analyses of spectral data deduced by UHPLC-DAD-ESI-HRMS and NMR methods. Different plant part samples of T. diversifolia which included leaves, stems, roots, and inflorescences were collected from two Brazilian states throughout a 24-month period, along with the corresponding monthly environmental data. A metabolomic approach employing concatenated LC-MS and NMR data was utilised for the first time to study the relationships between environment and plant metabolism. A seasonal pattern was observed for the occurrence of metabolites that included sugars, sesquiterpenes lactones and phenolics in the leaf and stem parts, which can be correlated to the amount of rainfall and changes in temperature. The distribution of the metabolites in the inflorescence and root parts were mainly affected by variation of some soil nutrients such as Ca, Mg, P, K and Cu. We highlight the environment-metabolism relationship for T. diversifolia and the combined analytical approach to obtain reliable data that contributed to a holistic understanding of the influence of abiotic environmental factors on the production of metabolites in various plant parts.

Exploring natural variation of Pinus pinaster Aiton using metabolomics: Is it possible to identify the region of origin of a pine from its metabolites?

PubMed

Meijón, Mónica; Feito, Isabel; Oravec, Michal; Delatorre, Carolina; Weckwerth, Wolfram; Majada, Juan; Valledor, Luis

2016-02-01

Natural variation of the metabolome of Pinus pinaster was studied to improve understanding of its role in the adaptation process and phenotypic diversity. The metabolomes of needles and the apical and basal section of buds were analysed in ten provenances of P. pinaster, selected from France, Spain and Morocco, grown in a common garden for 5 years. The employment of complementary mass spectrometry techniques (GC-MS and LC-Orbitrap-MS) together with bioinformatics tools allowed the reliable quantification of 2403 molecular masses. The analysis of the metabolome showed that differences were maintained across provenances and that the metabolites characteristic of each organ are mainly related to amino acid metabolism, while provenances were distinguishable essentially through secondary metabolism when organs were analysed independently. Integrative analyses of metabolome, environmental and growth data provided a comprehensive picture of adaptation plasticity in conifers. These analyses defined two major groups of plants, distinguished by secondary metabolism: that is, either Atlantic or Mediterranean provenance. Needles were the most sensitive organ, where strong correlations were found between flavonoids and the water regime of the geographic origin of the provenance. The data obtained point to genome specialization aimed at maximizing the drought stress resistance of trees depending on their origin. © 2016 John Wiley & Sons Ltd.

Applying metabolomics to cardiometabolic intervention studies and trials: past experiences and a roadmap for the future.

PubMed

Rankin, Naomi J; Preiss, David; Welsh, Paul; Sattar, Naveed

2016-10-01

Metabolomics and lipidomics are emerging methods for detailed phenotyping of small molecules in samples. It is hoped that such data will: (i) enhance baseline prediction of patient response to pharmacotherapies (beneficial or adverse); (ii) reveal changes in metabolites shortly after initiation of therapy that may predict patient response, including adverse effects, before routine biomarkers are altered; and( iii) give new insights into mechanisms of drug action, particularly where the results of a trial of a new agent were unexpected, and thus help future drug development. In these ways, metabolomics could enhance research findings from intervention studies. This narrative review provides an overview of metabolomics and lipidomics in early clinical intervention studies for investigation of mechanisms of drug action and prediction of drug response (both desired and undesired). We highlight early examples from drug intervention studies associated with cardiometabolic disease. Despite the strengths of such studies, particularly the use of state-of-the-art technologies and advanced statistical methods, currently published studies in the metabolomics arena are largely underpowered and should be considered as hypothesis-generating. In order for metabolomics to meaningfully improve stratified medicine approaches to patient treatment, there is a need for higher quality studies, with better exploitation of biobanks from randomized clinical trials i.e. with large sample size, adjudicated outcomes, standardized procedures, validation cohorts, comparison witth routine biochemistry and both active and control/placebo arms. On the basis of this review, and based on our research experience using clinically established biomarkers, we propose steps to more speedily advance this area of research towards potential clinical impact. © The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

Metabolomics of tomato xylem sap during bacterial wilt reveals Ralstonia solanacearum produces abundant putrescine, a metabolite that accelerates wilt disease.

PubMed

Lowe-Power, Tiffany M; Hendrich, Connor G; von Roepenack-Lahaye, Edda; Li, Bin; Wu, Dousheng; Mitra, Raka; Dalsing, Beth L; Ricca, Patrizia; Naidoo, Jacinth; Cook, David; Jancewicz, Amy; Masson, Patrick; Thomma, Bart; Lahaye, Thomas; Michael, Anthony J; Allen, Caitilyn

2018-04-01

Ralstonia solanacearum thrives in plant xylem vessels and causes bacterial wilt disease despite the low nutrient content of xylem sap. We found that R. solanacearum manipulates its host to increase nutrients in tomato xylem sap, enabling it to grow better in sap from infected plants than in sap from healthy plants. Untargeted GC/MS metabolomics identified 22 metabolites enriched in R. solanacearum-infected sap. Eight of these could serve as sole carbon or nitrogen sources for R. solanacearum. Putrescine, a polyamine that is not a sole carbon or nitrogen source for R. solanacearum, was enriched 76-fold to 37 µM in R. solanacearum-infected sap. R. solanacearum synthesized putrescine via a SpeC ornithine decarboxylase. A ΔspeC mutant required ≥ 15 µM exogenous putrescine to grow and could not grow alone in xylem even when plants were treated with putrescine. However, co-inoculation with wildtype rescued ΔspeC growth, indicating R. solanacearum produced and exported putrescine to xylem sap. Intriguingly, treating plants with putrescine before inoculation accelerated wilt symptom development and R. solanacearum growth and systemic spread. Xylem putrescine concentration was unchanged in putrescine-treated plants, so the exogenous putrescine likely accelerated disease indirectly by affecting host physiology. These results indicate that putrescine is a pathogen-produced virulence metabolite. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

Metabolomics and neuroanatomical evaluation of post-mortem changes in the hippocampus.

PubMed

Gonzalez-Riano, Carolina; Tapia-González, Silvia; García, Antonia; Muñoz, Alberto; DeFelipe, Javier; Barbas, Coral

2017-08-01

Understanding the human brain is the ultimate goal in neuroscience, but this is extremely challenging in part due to the fact that brain tissue obtained from autopsy is practically the only source of normal brain tissue and also since changes at different levels of biological organization (genetic, molecular, biochemical, anatomical) occur after death due to multiple mechanisms. Here we used metabolomic and anatomical techniques to study the possible relationship between post-mortem time (PT)-induced changes that may occur at both the metabolomics and anatomical levels in the same brains. Our experiments have mainly focused on the hippocampus of the mouse. We found significant metabolomic changes at 2 h PT, whereas the integrity of neurons and glia, at the anatomical/ neurochemical level, was not significantly altered during the first 5 h PT for the majority of histological markers.

Application of Stable Isotope-Assisted Metabolomics for Cell Metabolism Studies

PubMed Central

You, Le; Zhang, Baichen; Tang, Yinjie J.

2014-01-01

The applications of stable isotopes in metabolomics have facilitated the study of cell metabolisms. Stable isotope-assisted metabolomics requires: (1) properly designed tracer experiments; (2) stringent sampling and quenching protocols to minimize isotopic alternations; (3) efficient metabolite separations; (4) high resolution mass spectrometry to resolve overlapping peaks and background noises; and (5) data analysis methods and databases to decipher isotopic clusters over a broad m/z range (mass-to-charge ratio). This paper overviews mass spectrometry based techniques for precise determination of metabolites and their isotopologues. It also discusses applications of isotopic approaches to track substrate utilization, identify unknown metabolites and their chemical formulas, measure metabolite concentrations, determine putative metabolic pathways, and investigate microbial community populations and their carbon assimilation patterns. In addition, 13C-metabolite fingerprinting and metabolic models can be integrated to quantify carbon fluxes (enzyme reaction rates). The fluxome, in combination with other “omics” analyses, may give systems-level insights into regulatory mechanisms underlying gene functions. More importantly, 13C-tracer experiments significantly improve the potential of low-resolution gas chromatography-mass spectrometry (GC-MS) for broad-scope metabolism studies. We foresee the isotope-assisted metabolomics to be an indispensable tool in industrial biotechnology, environmental microbiology, and medical research. PMID:24957020

HR-MAS NMR metabolomics of 'Swingle' citrumelo rootstock genetically modified to overproduce proline.

PubMed

de Oliveira, Caroline S; Carlos, Eduardo F; Vieira, Luiz G E; Lião, Luciano M; Alcantara, Glaucia B

2014-08-01

The accumulation of proline is a typical physiological response to abiotic stresses in higher plants. 'Swingle' citrumelo, an important rootstock for citrus production, has been modified with a mutated Δ(1)-pyrroline-5-carboxylate synthetase gene (VaP5CSF129A) linked to the cauliflower mosaic virus 35S promoter to induce the overproduction of free proline. This paper presents a comparative metabolomic study of nontransgenic versus transgenic 'Swingle' citrumelo plants with high endogenous proline. (1)H high-resolution magic angle spinning nuclear magnetic resonance spectroscopy and multivariate analysis showed significant differences in some metabolites between the nontransgenic and transgenic leaves and roots. The overproduction of proline has reduced the sucrose content in transgenic leaves, revealing a metabolic cost for these plants. In roots, the high level of free proline acts for the adjustment of cation-anion balance, causing the reduction of acetic acid content. The same sucrose level in roots indicates that they can be considered as sucrose sink. Similar behavior may be waited for fruits produced on transgenic rootstock. Copyright © 2014 John Wiley & Sons, Ltd.

System-Wide Hypersensitive Response-Associated Transcriptome and Metabolome Reprogramming in Tomato1[W][OA

PubMed Central

Etalo, Desalegn W.; Stulemeijer, Iris J.E.; Peter van Esse, H.; de Vos, Ric C.H.; Bouwmeester, Harro J.; Joosten, Matthieu H.A.J.

2013-01-01

The hypersensitive response (HR) is considered to be the hallmark of the resistance response of plants to pathogens. To study HR-associated transcriptome and metabolome reprogramming in tomato (Solanum lycopersicum), we used plants that express both a resistance gene to Cladosporium fulvum and the matching avirulence gene of this pathogen. In these plants, massive reprogramming occurred, and we found that the HR and associated processes are highly energy demanding. Ubiquitin-dependent protein degradation, hydrolysis of sugars, and lipid catabolism are used as alternative sources of amino acids, energy, and carbon skeletons, respectively. We observed strong accumulation of secondary metabolites, such as hydroxycinnamic acid amides. Coregulated expression of WRKY transcription factors and genes known to be involved in the HR, in addition to a strong enrichment of the W-box WRKY-binding motif in the promoter sequences of the coregulated genes, point to WRKYs as the most prominent orchestrators of the HR. Our study has revealed several novel HR-related genes, and reverse genetics tools will allow us to understand the role of each individual component in the HR. PMID:23719893

Transcriptome and metabolome analysis of plant sulfate starvation and resupply provides novel information on transcriptional regulation of metabolism associated with sulfur, nitrogen and phosphorus nutritional responses in Arabidopsis

PubMed Central

Bielecka, Monika; Watanabe, Mutsumi; Morcuende, Rosa; Scheible, Wolf-Rüdiger; Hawkesford, Malcolm J.; Hesse, Holger; Hoefgen, Rainer

2015-01-01

Sulfur is an essential macronutrient for plant growth and development. Reaching a thorough understanding of the molecular basis for changes in plant metabolism depending on the sulfur-nutritional status at the systems level will advance our basic knowledge and help target future crop improvement. Although the transcriptional responses induced by sulfate starvation have been studied in the past, knowledge of the regulation of sulfur metabolism is still fragmentary. This work focuses on the discovery of candidates for regulatory genes such as transcription factors (TFs) using ‘omics technologies. For this purpose a short term sulfate-starvation/re-supply approach was used. ATH1 microarray studies and metabolite determinations yielded 21 TFs which responded more than 2-fold at the transcriptional level to sulfate starvation. Categorization by response behaviors under sulfate-starvation/re-supply and other nutrient starvations such as nitrate and phosphate allowed determination of whether the TF genes are specific for or common between distinct mineral nutrient depletions. Extending this co-behavior analysis to the whole transcriptome data set enabled prediction of putative downstream genes. Additionally, combinations of transcriptome and metabolome data allowed identification of relationships between TFs and downstream responses, namely, expression changes in biosynthetic genes and subsequent metabolic responses. Effect chains on glucosinolate and polyamine biosynthesis are discussed in detail. The knowledge gained from this study provides a blueprint for an integrated analysis of transcriptomics and metabolomics and application for the identification of uncharacterized genes. PMID:25674096

Integrated analysis of transcriptomic and metabolomic data reveals critical metabolic pathways involved in rotenoid biosynthesis in the medicinal plant Mirabilis himalaica.

PubMed

Gu, Li; Zhang, Zhong-Yi; Quan, Hong; Li, Ming-Jie; Zhao, Fang-Yu; Xu, Yuan-Jiang; Liu, Jiang; Sai, Man; Zheng, Wei-Lie; Lan, Xiao-Zhong

2018-06-01

Mirabilis himalaica (Edgew.) Heimerl is among the most important genuine medicinal plants in Tibet. However, the biosynthesis mechanisms of the active compounds in this species are unclear, severely limiting its application. To clarify the molecular biosynthesis mechanism of the key representative active compounds, specifically rotenoid, which is of special medicinal value for M. himalaica, RNA sequencing and TOF-MS technologies were used to construct transcriptomic and metabolomic libraries from the roots, stems, and leaves of M. himalaica plants collected from their natural habitat. As a result, each of the transcriptomic libraries from the different tissues was sequenced, generating more than 10 Gb of clean data ultimately assembled into 147,142 unigenes. In the three tissues, metabolomic analysis identified 522 candidate compounds, of which 170 metabolites involved in 114 metabolic pathways were mapped to the KEGG. Of these genes, 61 encoding enzymes were identified to function at key steps of the pathways related to rotenoid biosynthesis, where 14 intermediate metabolites were also located. An integrated analysis of metabolic and transcriptomic data revealed that most of the intermediate metabolites and enzymes related to rotenoid biosynthesis were synthesized in the roots, stems and leaves of M. himalaica, which suggested that the use of non-medicinal tissues to extract compounds was feasible. In addition, the CHS and CHI genes were found to play important roles in rotenoid biosynthesis, especially, since CHS might be an important rate-limiting enzyme. This study provides a hypothetical basis for the screening of new active metabolites and the metabolic engineering of rotenoid in M. himalaica.

Effects of Combined Low Glutathione with Mild Oxidative and Low Phosphorus Stress on the Metabolism of Arabidopsis thaliana

PubMed Central

Fukushima, Atsushi; Iwasa, Mami; Nakabayashi, Ryo; Kobayashi, Makoto; Nishizawa, Tomoko; Okazaki, Yozo; Saito, Kazuki; Kusano, Miyako

2017-01-01

Plants possess highly sensitive mechanisms that monitor environmental stress levels for a dose-dependent fine-tuning of their growth and development. Differences in plant responses to severe and mild abiotic stresses have been recognized. Although many studies have revealed that glutathione can contribute to plant tolerance to various environmental stresses, little is known about the relationship between glutathione and mild abiotic stress, especially the effect of stress-induced altered glutathione levels on the metabolism. Here, we applied a systems biology approach to identify key pathways involved in the gene-to-metabolite networks perturbed by low glutathione content under mild abiotic stress in Arabidopsis thaliana. We used glutathione synthesis mutants (cad2-1 and pad2-1) and plants overexpressing the gene encoding γ-glutamylcysteine synthetase, the first enzyme of the glutathione biosynthetic pathway. The plants were exposed to two mild stress conditions—oxidative stress elicited by methyl viologen and stress induced by the limited availability of phosphate. We observed that the mutants and transgenic plants showed similar shoot growth as that of the wild-type plants under mild abiotic stress. We then selected the synthesis mutants and performed multi-platform metabolomics and microarray experiments to evaluate the possible effects on the overall metabolome and the transcriptome. As a common oxidative stress response, several flavonoids that we assessed showed overaccumulation, whereas the mild phosphate stress resulted in increased levels of specific kaempferol- and quercetin-glycosides. Remarkably, in addition to a significant increased level of sugar, osmolytes, and lipids as mild oxidative stress-responsive metabolites, short-chain aliphatic glucosinolates over-accumulated in the mutants, whereas the level of long-chain aliphatic glucosinolates and specific lipids decreased. Coordinated gene expressions related to glucosinolate and flavonoid biosynthesis also supported the metabolite responses in the pad2-1 mutant. Our results suggest that glutathione synthesis mutants accelerate transcriptional regulatory networks to control the biosynthetic pathways involved in glutathione-independent scavenging metabolites, and that they might reconfigure the metabolic networks in primary and secondary metabolism, including lipids, glucosinolates, and flavonoids. This work provides a basis for the elucidation of the molecular mechanisms involved in the metabolic and transcriptional regulatory networks in response to combined low glutathione content with mild oxidative and nutrient stress in A. thaliana. PMID:28894456

Screening ecological impacts of environmental surface waters using cell-based metabolomics

EPA Science Inventory

Anthropogenic chemicals are routinely detected in aquatic ecosystems downstream from wastewater treatment plants (WWTPs), industrial and agricultural operations, and numerous other sources. Various studies have shown that exposure to such complex chemical mixtures can produce adv...

Cell-based Metabolomics for Assessing Chemical Exposure and Toxicity of Environmental Surface Waters

EPA Science Inventory

Waste water treatment plants (WWTPs), concentrated animal feeding operations (CAFOs), mining activities, and agricultural operations release contaminants that negatively affect surface water quality. Traditional methods using live animals/fish to monitor/assess contaminant exposu...

Growth of Malignant Non-CNS Tumors Alters Brain Metabolome

PubMed Central

Kovalchuk, Anna; Nersisyan, Lilit; Mandal, Rupasri; Wishart, David; Mancini, Maria; Sidransky, David; Kolb, Bryan; Kovalchuk, Olga

2018-01-01

Cancer survivors experience numerous treatment side effects that negatively affect their quality of life. Cognitive side effects are especially insidious, as they affect memory, cognition, and learning. Neurocognitive deficits occur prior to cancer treatment, arising even before cancer diagnosis, and we refer to them as “tumor brain.” Metabolomics is a new area of research that focuses on metabolome profiles and provides important mechanistic insights into various human diseases, including cancer, neurodegenerative diseases, and aging. Many neurological diseases and conditions affect metabolic processes in the brain. However, the tumor brain metabolome has never been analyzed. In our study we used direct flow injection/mass spectrometry (DI-MS) analysis to establish the effects of the growth of lung cancer, pancreatic cancer, and sarcoma on the brain metabolome of TumorGraft™ mice. We found that the growth of malignant non-CNS tumors impacted metabolic processes in the brain, affecting protein biosynthesis, and amino acid and sphingolipid metabolism. The observed metabolic changes were similar to those reported for neurodegenerative diseases and brain aging, and may have potential mechanistic value for future analysis of the tumor brain phenomenon. PMID:29515623

Metabolomic profiling and genomic analysis of wheat aneuploid lines to identify genes controlling biochemical pathways in mature grain.

PubMed

Francki, Michael G; Hayton, Sarah; Gummer, Joel P A; Rawlinson, Catherine; Trengove, Robert D

2016-02-01

Metabolomics is becoming an increasingly important tool in plant genomics to decipher the function of genes controlling biochemical pathways responsible for trait variation. Although theoretical models can integrate genes and metabolites for trait variation, biological networks require validation using appropriate experimental genetic systems. In this study, we applied an untargeted metabolite analysis to mature grain of wheat homoeologous group 3 ditelosomic lines, selected compounds that showed significant variation between wheat lines Chinese Spring and at least one ditelosomic line, tracked the genes encoding enzymes of their biochemical pathway using the wheat genome survey sequence and determined the genetic components underlying metabolite variation. A total of 412 analytes were resolved in the wheat grain metabolome, and principal component analysis indicated significant differences in metabolite profiles between Chinese Spring and each ditelosomic lines. The grain metabolome identified 55 compounds positively matched against a mass spectral library where the majority showed significant differences between Chinese Spring and at least one ditelosomic line. Trehalose and branched-chain amino acids were selected for detailed investigation, and it was expected that if genes encoding enzymes directly related to their biochemical pathways were located on homoeologous group 3 chromosomes, then corresponding ditelosomic lines would have a significant reduction in metabolites compared with Chinese Spring. Although a proportion showed a reduction, some lines showed significant increases in metabolites, indicating that genes directly and indirectly involved in biosynthetic pathways likely regulate the metabolome. Therefore, this study demonstrated that wheat aneuploid lines are suitable experimental genetic system to validate metabolomics-genomics networks. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Implication of Fusarium graminearum primary metabolism in its resistance to benzimidazole fungicides as revealed by 1H NMR metabolomics.

PubMed

Sevastos, A; Kalampokis, I F; Panagiotopoulou, A; Pelecanou, M; Aliferis, K A

2018-06-01

Fungal metabolomics is a field of high potential but yet largely unexploited. Focusing on plant-pathogenic fungi, no metabolomics studies exist on their resistance to fungicides, which represents a major issue that the agrochemical and agricultural sectors are facing. Fungal infections cause quantitative, but also qualitative yield losses, especially in the case of mycotoxin-producing species. The aim of the study was to correlate metabolic changes in Fusarium graminearum strains' metabolomes with their carbendazim-resistant level and discover corresponding metabolites-biomarkers, with primary focus on its primary metabolism. For this purpose, comparative 1 H NMR metabolomics was applied to a wild-type and four carbendazim-resistant Fusarium graminearum strains following or not exposure to the fungicide. Results showed an excellent discrimination between the strains based on their carbendazim-resistance following exposure to low concentration of the fungicide (2 mg L -1 ). Both genotype and fungicide treatments had a major impact on fungal metabolism. Among the signatory metabolites, a positive correlation was discovered between the content of F. graminearum strains in amino acids of the aromatic and pyruvate families, l-glutamate, l-proline, l-serine, pyroglutamate, and succinate and their carbendazim-resistance level. In contrary, their content in l-glutamine and l-threonine, had a negative correlation. Many of these metabolites play important roles in fungal physiology and responses to stresses. This work represents a proof-of-concept of the applicability of 1 H NMR metabolomics for high-throughput screening of fungal mutations leading to fungicide resistance, and the study of its biochemical basis, focusing on the involvement of primary metabolism. Results could be further exploited in programs of resistance monitoring, genetic engineering, and crop protection for combating fungal resistance to fungicides. Copyright © 2018 Elsevier Inc. All rights reserved.

Supporting metabolomics with adaptable software: design architectures for the end-user.

PubMed

Sarpe, Vladimir; Schriemer, David C

2017-02-01

Large and disparate sets of LC-MS data are generated by modern metabolomics profiling initiatives, and while useful software tools are available to annotate and quantify compounds, the field requires continued software development in order to sustain methodological innovation. Advances in software development practices allow for a new paradigm in tool development for metabolomics, where increasingly the end-user can develop or redeploy utilities ranging from simple algorithms to complex workflows. Resources that provide an organized framework for development are described and illustrated with LC-MS processing packages that have leveraged their design tools. Full access to these resources depends in part on coding experience, but the emergence of workflow builders and pluggable frameworks strongly reduces the skill level required. Developers in the metabolomics community are encouraged to use these resources and design content for uptake and reuse. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cell-based metabolomics for assessing chemical exposure and toxicity of environmental surface waters (presentation)

EPA Science Inventory

Introduction: Waste water treatment plants (WWTPs), concentrated animal feeding operations (CAFOs), mining activities, and agricultural operations release contaminants that negatively affect surface water quality. Traditional methods using live animals (e.g. fish) to monitor/as...

MaizeCyc: Metabolic networks in maize

USDA-ARS?s Scientific Manuscript database

MaizeCyc is a catalog of known and predicted metabolic and transport pathways that enables plant researchers to graphically represent the metabolome of maize (Zea mays), thereby supporting integrated systems-biology analysis. Supported analyses include molecular and genetic/phenotypic profiling (e.g...

Drought delays development of the sorghum root microbiome and enriches for monoderm bacteria

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Ling; Naylor, Dan; Dong, Zhaobin

Here, drought stress is a major obstacle to crop productivity, and the severity and frequency of drought are expected to increase in the coming century. Certain root-associated bacteria have been shown to mitigate the negative effects of drought stress on plant growth, and manipulation of the crop microbiome is an emerging strategy for overcoming drought stress in agricultural systems, yet the effect of drought on the development of the root microbiome is poorly understood. Through 16S rRNA amplicon and metatranscriptome sequencing, as well as root metabolomics, we demonstrate that drought delays the development of the early sorghum root microbiome andmore » causes increased abundance and activity of monoderm bacteria, which lack an outer cell membrane and contain thick cell walls. Our data suggest that altered plant metabolism and increased activity of bacterial ATP-binding cassette (ABC) transporter genes are correlated with these shifts in community composition. Finally, inoculation experiments with monoderm isolates indicate that increased colonization of the root during drought can positively impact plant growth. Collectively, these results demonstrate the role that drought plays in restructuring the root microbiome and highlight the importance of temporal sampling when studying plant-associated microbiomes.« less

Drought delays development of the sorghum root microbiome and enriches for monoderm bacteria

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Ling; Naylor, Dan; Dong, Zhaobin

Drought stress is a major obstacle to crop productivity and the severity and frequency of drought are expected to increase in the coming century. Certain root-associated bacteria have been shown to mitigate the negative effects of drought stress on plant growth, and manipulation of the crop microbiome is an emerging strategy for overcoming drought stress in agricultural systems, yet the effect of drought on the development of the root microbiome is poorly understood. Through16S amplicon and metatranscriptome sequencing, as well as root metabolomics, we demonstrate that drought delays the development of the early sorghum root microbiome and causes increased abundancemore » and activity of monoderm bacteria, which lack an outer cell membrane and contain thick cell walls. Our data suggest that altered plant metabolism and increased activity of bacterial ABC (ATP-binding cassette)-transporter genes may mediate these shifts in community composition. Finally, experiments with fluorescently tagged monoderms indicate that increased colonization of the root during drought can positively impact plant growth. Collectively, these results demonstrate the role drought plays in restructuring the root microbiome and highlight the importance of temporal sampling when studying plant-associated microbiomes.« less

Drought delays development of the sorghum root microbiome and enriches for monoderm bacteria.

PubMed

Xu, Ling; Naylor, Dan; Dong, Zhaobin; Simmons, Tuesday; Pierroz, Grady; Hixson, Kim K; Kim, Young-Mo; Zink, Erika M; Engbrecht, Kristin M; Wang, Yi; Gao, Cheng; DeGraaf, Stephanie; Madera, Mary A; Sievert, Julie A; Hollingsworth, Joy; Birdseye, Devon; Scheller, Henrik V; Hutmacher, Robert; Dahlberg, Jeffery; Jansson, Christer; Taylor, John W; Lemaux, Peggy G; Coleman-Derr, Devin

2018-05-01

Drought stress is a major obstacle to crop productivity, and the severity and frequency of drought are expected to increase in the coming century. Certain root-associated bacteria have been shown to mitigate the negative effects of drought stress on plant growth, and manipulation of the crop microbiome is an emerging strategy for overcoming drought stress in agricultural systems, yet the effect of drought on the development of the root microbiome is poorly understood. Through 16S rRNA amplicon and metatranscriptome sequencing, as well as root metabolomics, we demonstrate that drought delays the development of the early sorghum root microbiome and causes increased abundance and activity of monoderm bacteria, which lack an outer cell membrane and contain thick cell walls. Our data suggest that altered plant metabolism and increased activity of bacterial ATP-binding cassette (ABC) transporter genes are correlated with these shifts in community composition. Finally, inoculation experiments with monoderm isolates indicate that increased colonization of the root during drought can positively impact plant growth. Collectively, these results demonstrate the role that drought plays in restructuring the root microbiome and highlight the importance of temporal sampling when studying plant-associated microbiomes. Copyright © 2018 the Author(s). Published by PNAS.

Drought delays development of the sorghum root microbiome and enriches for monoderm bacteria

DOE PAGES

Xu, Ling; Naylor, Dan; Dong, Zhaobin; ...

2018-04-16

Here, drought stress is a major obstacle to crop productivity, and the severity and frequency of drought are expected to increase in the coming century. Certain root-associated bacteria have been shown to mitigate the negative effects of drought stress on plant growth, and manipulation of the crop microbiome is an emerging strategy for overcoming drought stress in agricultural systems, yet the effect of drought on the development of the root microbiome is poorly understood. Through 16S rRNA amplicon and metatranscriptome sequencing, as well as root metabolomics, we demonstrate that drought delays the development of the early sorghum root microbiome andmore » causes increased abundance and activity of monoderm bacteria, which lack an outer cell membrane and contain thick cell walls. Our data suggest that altered plant metabolism and increased activity of bacterial ATP-binding cassette (ABC) transporter genes are correlated with these shifts in community composition. Finally, inoculation experiments with monoderm isolates indicate that increased colonization of the root during drought can positively impact plant growth. Collectively, these results demonstrate the role that drought plays in restructuring the root microbiome and highlight the importance of temporal sampling when studying plant-associated microbiomes.« less

Stereoselective effects of ibuprofen in adult zebrafish (Danio rerio) using UPLC-TOF/MS-based metabolomics.

PubMed

Song, Yue; Chai, Tingting; Yin, Zhiqiang; Zhang, Xining; Zhang, Wei; Qian, Yongzhong; Qiu, Jing

2018-06-09

Ibuprofen (IBU), as a commonly used non-steroidal anti-inflammatory drug (NSAID) and pharmaceutical and personal care product (PPCP), is frequently prescribed by doctors to relieve pain. It is widely released into environmental water and soil in the form of chiral enantiomers by the urination and defecation of humans or animals and by sewage discharge from wastewater treatment plants. This study focused on the alteration of metabolism in the adult zebrafish (Danio rerio) brain after exposure to R-(-)-/S-(+)-/rac-IBU at 5 μg L -1 for 28 days. A total of 45 potential biomarkers and related pathways, including amino acids and their derivatives, purine and its derivatives, nucleotides and other metabolites, were observed with untargeted metabolomics. To validate the metabolic disorders induced by IBU, 22 amino acids and 3 antioxidant enzymes were selected to be quantitated and determined using targeted metabolomics and enzyme assay. Stereoselective changes were observed in the 45 identified biomarkers from the untargeted metabolomics analysis. The 22 amino acids quantitated in targeted metabolomics and 3 antioxidant enzymes determined in enzyme assay also showed stereoselective changes after R-(-)-/S-(+)-/rac-IBU exposure. Results showed that even at a low concentration of R-(-)-/S-(+)-/rac-IBU, disorders in metabolism and antioxidant defense systems were still induced with stereoselectivity. Our study may enable a better understanding of the risks of chiral PPCPs in aquatic organisms in the environment. Copyright © 2018 Elsevier Ltd. All rights reserved.

Partial least squares model and design of experiments toward the analysis of the metabolome of Jatropha gossypifolia leaves: Extraction and chromatographic fingerprint optimization.

PubMed

Pilon, Alan Cesar; Carnevale Neto, Fausto; Freire, Rafael Teixeira; Cardoso, Patrícia; Carneiro, Renato Lajarim; Da Silva Bolzani, Vanderlan; Castro-Gamboa, Ian

2016-03-01

A major challenge in metabolomic studies is how to extract and analyze an entire metabolome. So far, no single method was able to clearly complete this task in an efficient and reproducible way. In this work we proposed a sequential strategy for the extraction and chromatographic separation of metabolites from leaves Jatropha gossypifolia using a design of experiments and partial least square model. The effect of 14 different solvents on extraction process was evaluated and an optimized separation condition on liquid chromatography was estimated considering mobile phase composition and analysis time. The initial conditions of extraction using methanol and separation in 30 min between 5 and 100% water/methanol (1:1 v/v) with 0.1% of acetic acid, 20 μL sample volume, 3.0 mL min(-1) flow rate and 25°C column temperature led to 107 chromatographic peaks. After the optimization strategy using i-propanol/chloroform (1:1 v/v) for extraction, linear gradient elution of 60 min between 5 and 100% water/(acetonitrile/methanol 68:32 v/v with 0.1% of acetic acid), 30 μL sample volume, 2.0 mL min(-1) flow rate, and 30°C column temperature, we detected 140 chromatographic peaks, 30.84% more peaks compared to initial method. This is a reliable strategy using a limited number of experiments for metabolomics protocols. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Metabolic profiles of flooding-tolerant mechanism in early-stage soybean responding to initial stress.

PubMed

Wang, Xin; Zhu, Wei; Hashiguchi, Akiko; Nishimura, Minoru; Tian, Jingkui; Komatsu, Setsuko

2017-08-01

Metabolomic analysis of flooding-tolerant mutant and abscisic acid-treated soybeans suggests that accumulated fructose might play a role in initial flooding tolerance through regulation of hexokinase and phosphofructokinase. Soybean is sensitive to flooding stress, which markedly reduces plant growth. To explore the mechanism underlying initial-flooding tolerance in soybean, mass spectrometry-based metabolomic analysis was performed using flooding-tolerant mutant and abscisic-acid treated soybeans. Among the commonly-identified metabolites in both flooding-tolerant materials, metabolites involved in carbohydrate and organic acid displayed same profile at initial-flooding stress. Sugar metabolism was highlighted in both flooding-tolerant materials with the decreased and increased accumulation of sucrose and fructose, respectively, compared to flooded soybeans. Gene expression of hexokinase 1 was upregulated in flooded soybean; however, it was downregulated in both flooding-tolerant materials. Metabolites involved in carbohydrate/organic acid and proteins related to glycolysis/tricarboxylic acid cycle were integrated. Increased protein abundance of phosphofructokinase was identified in both flooding-tolerant materials, which was in agreement with its enzyme activity. Furthermore, sugar metabolism was pointed out as the tolerant-responsive process at initial-flooding stress with the integration of metabolomics, proteomics, and transcriptomics. Moreover, application of fructose declined the increased fresh weight of plant induced by flooding stress. These results suggest that fructose might be the critical metabolite through regulation of hexokinase and phosphofructokinase to confer initial-flooding stress in soybean.

Metabolome analysis of biosynthetic mutants reveals a diversity of metabolic changes and allows identification of a large number of new compounds in Arabidopsis.

PubMed

Böttcher, Christoph; von Roepenack-Lahaye, Edda; Schmidt, Jürgen; Schmotz, Constanze; Neumann, Steffen; Scheel, Dierk; Clemens, Stephan

2008-08-01

Metabolomics is facing a major challenge: the lack of knowledge about metabolites present in a given biological system. Thus, large-scale discovery of metabolites is considered an essential step toward a better understanding of plant metabolism. We show here that the application of a metabolomics approach generating structural information for the analysis of Arabidopsis (Arabidopsis thaliana) mutants allows the efficient cataloging of metabolites. Fifty-six percent of the features that showed significant differences in abundance between seeds of wild-type, transparent testa4, and transparent testa5 plants could be annotated. Seventy-five compounds were structurally characterized, 21 of which could be identified. About 40 compounds had not been known from Arabidopsis before. Also, the high-resolution analysis revealed an unanticipated expansion of metabolic conversions upstream of biosynthetic blocks. Deficiency in chalcone synthase results in the increased seed-specific biosynthesis of a range of phenolic choline esters. Similarly, a lack of chalcone isomerase activity leads to the accumulation of various naringenin chalcone derivatives. Furthermore, our data provide insight into the connection between p-coumaroyl-coenzyme A-dependent pathways. Lack of flavonoid biosynthesis results in elevated synthesis not only of p-coumarate-derived choline esters but also of sinapate-derived metabolites. However, sinapoylcholine is not the only accumulating end product. Instead, we observed specific and sophisticated changes in the complex pattern of sinapate derivatives.

Metabolomic Tools to Assess the Chemistry and Bioactivity of Endophytic Aspergillus Strain.

PubMed

Tawfike, Ahmed F; Tate, Rothwelle; Abbott, Gráinne; Young, Louise; Viegelmann, Christina; Schumacher, Marc; Diederich, Marc; Edrada-Ebel, RuAngelie

2017-10-01

Endophytic fungi associated with medicinal plants are a potential source of novel chemistry and biology that may find applications as pharmaceutical and agrochemical drugs. In this study, a combination of metabolomics and bioactivity-guided approaches were employed to isolate secondary metabolites with cytotoxicity against cancer cells from an endophytic Aspergillus aculeatus. The endophyte was isolated from the Egyptian medicinal plant Terminalia laxiflora and identified using molecular biological methods. Metabolomics and dereplication studies were accomplished by utilizing the MZmine software coupled with the universal Dictionary of Natural Products database. Metabolic profiling, with aid of multivariate data analysis, was performed at different stages of the growth curve to choose the optimized method suitable for up-scaling. The optimized culture method yielded a crude extract abundant with biologically-active secondary metabolites. Crude extracts were fractionated using different high-throughput chromatographic techniques. Purified compounds were identified by HR-ESI-MS, 1D- and 2D-NMR. This study introduced a new method of dereplication utilizing both high-resolution mass spectrometry and NMR spectroscopy. The metabolites were putatively identified by applying a chemotaxonomic filter. We also present a short review on the diverse chemistry of terrestrial endophytic strains of Aspergillus, which has become a part of our dereplication work and this will be of wide interest to those working in this field. © 2017 Wiley-VHCA AG, Zurich, Switzerland.

Laser assisted microdissection, an efficient technique to understand tissue specific gene expression patterns and functional genomics in plants.

PubMed

Gautam, Vibhav; Sarkar, Ananda K

2015-04-01

Laser assisted microdissection (LAM) is an advanced technology used to perform tissue or cell-specific expression profiling of genes and proteins, owing to its ability to isolate the desired tissue or cell type from a heterogeneous population. Due to the specificity and high efficiency acquired during its pioneering use in medical science, the LAM technique has quickly been adopted for use in many biological researches. Today, it has become a potent tool to address a wide range of questions in diverse field of plant biology. Beginning with comparative transcriptome analysis of different tissues such as reproductive parts, meristems, lateral organs, roots etc., LAM has also been extensively used in plant-pathogen interaction studies, proteomics, and metabolomics. In combination with next generation sequencing and proteomics analysis, LAM has opened up promising opportunities in the area of large scale functional studies in plants. Ever since the advent of this technique, significant improvements have been achieved in term of its instrumentation and method, which has made LAM a more efficient tool applicable in wider research areas. Here, we discuss the advancement of LAM technique with special emphasis on its methodology and highlight its scope in modern research areas of plant biology. Although we put emphasis on use of LAM in transcriptome studies, which is mostly used, we also discuss its recent application and scope in proteome and metabolome studies.

Galanthamine, an anti-cholinesterase drug, effects plant growth and development in Artemisia tridentata Nutt. via modulation of auxin and neurotransmitter signaling.

PubMed

Turi, Christina E; Axwik, Katarina E; Smith, Anderson; Jones, A Maxwell P; Saxena, Praveen K; Murch, Susan J

2014-01-01

Galanthamine is a naturally occurring acetylcholinesterase (AchE) inhibitor that has been well established as a drug for treatment of mild to moderate Alzheimer disease, but the role of the compound in plant metabolism is not known. The current study was designed to investigate whether galanthamine could redirect morphogenesis of Artemisia tridentata Nutt. cultures by altering concentration of endogenous neurosignaling molecules acetylcholine (Ach), auxin (IAA), melatonin (Mel), and serotonin (5HT). Exposure of axenic A. tridentata cultures to 10 µM galanthamine decreased the concentration of endogenous Ach, IAA, MEL, and AchE, and altered plant growth in a manner reminiscent of 2-4D toxicity. Galanthamine itself demonstrated IAA activity in an oat coleoptile elongation bioassay, 20 µM galanthamine showed no significant difference compared with 5 μM IAA or 5 μM 1-Naphthaleneacetic acid (NAA). Metabolomic analysis detected between 20,921 to 27,891 compounds in A. tridentata plantlets and showed greater commonality between control and 5 µM treatments. Furthermore, metabolomic analysis putatively identified coumarins scopoletin/isoscopoletin, and scopolin in A. tridentata leaf extracts and these metabolites linearly increased in response to galanthamine treatments. Overall, these data indicate that galanthamine is an allelopathic phytochemical and support the hypothesis that neurologically active compounds in plants help ensure plant survival and adaptation to environmental challenges.

Galanthamine, an anticholinesterase drug, effects plant growth and development in Artemisia tridentate Nutt. via modulation of auxin and neutrotransmitter signaling.

PubMed

Turi, Christina E; Axwik, Katarina E; Smith, Anderson; Jones, A Maxwell P; Saxena, Praveen K; Murch, Susan J

2014-01-01

Galanthamine is a naturally occurring acetylcholinesterase (AchE) inhibitor that has been well established as a drug for treatment of mild to moderate Alzheimer disease, but the role of the compound in plant metabolism is not known. The current study was designed to investigate whether galanthamine could redirect morphogenesis of Artemisia tridentata Nutt. cultures by altering concentration of endogenous neurosignaling molecules acetylcholine (Ach), auxin (IAA), melatonin (Mel), and serotonin (5HT). Exposure of axenic A. tridentata cultures to 10 µM galanthamine decreased the concentration of endogenous Ach, IAA, MEL, and AchE, and altered plant growth in a manner reminiscent of 2-4D toxicity. Galanthamine itself demonstrated IAA activity in an oat coleotile elongation bioassay, 20 µM galanthamine showed no significant difference compared with 5 μM IAA or 5 μM 1-Naphthaleneacetic acid (NAA). Metabolomic analysis detected between 20,921 to 27,891 compounds in A. tridentata plantlets and showed greater commonality between control and 5 µM treatments. Furthermore, metabolomic analysis putatively identified coumarins scopoletin/isoscopoletin, and scopolin in A. tridentata leaf extracts and these metabolites linearly increased in response to galanthamine treatments. Overall, these data indicate that galanthamine is an allelopathic phytochemical and support the hypothesis that neurologically active compounds in plants help ensure plant survival and adaptation to environmental challenges.

Highlighting the effects of coumarin on adult plants of Arabidopsis thaliana (L.) Heynh. by an integrated -omic approach.

PubMed

Araniti, Fabrizio; Scognamiglio, Monica; Chambery, Angela; Russo, Rosita; Esposito, Assunta; D'Abrosca, Brigida; Fiorentino, Antonio; Lupini, Antonio; Sunseri, Francesco; Abenavoli, Maria Rosa

2017-06-01

In this study, the effects of the allelochemical coumarin through a metabolomic, proteomic and morpho-physiological approach in Arabidopsis adult plants (25days old) were investigated. Metabolomic analysis evidenced an increment of amino acids and a high accumulation of soluble sugars, after 6days of coumarin treatment. This effect was accompanied by a strong decrease on plant fresh and dry weights, as well as on total protein content. On the contrary, coumarin did not affect leaf number but caused a reduction in leaf area. An alteration of water status was confirmed by a reduction of relative water content and an increase in leaf osmotic potential. Moreover, coumarin impaired plant bio-membranes through an increase of lipid peroxidation and H 2 O 2 content suggesting that coumarin treatment might induce oxidative stress. Coumarin reduced the effective quantum yield of the photosystem II, the energy dissipation in the form of heat, the maximum PSII efficiency, the coefficient of the photochemical quenching and the estimated electron transport rate, while it significantly stimulated the fluorescence emission and the coefficient of the non photochemical quenching. Finally, the proteomic characterization of coumarin-treated plants revealed a down-regulation of the ROS detoxifying proteins, responsible of oxidative damage and consequently of physiological cascade effects. Copyright © 2017 Elsevier GmbH. All rights reserved.

Effect of the environment on the secondary metabolic profile of Tithonia diversifolia: a model for environmental metabolomics of plants

NASA Astrophysics Data System (ADS)

Sampaio, Bruno Leite; Edrada-Ebel, Ruangelie; da Costa, Fernando Batista

2016-07-01

Tithonia diversifolia is an invasive weed commonly found in tropical ecosystems. In this work, we investigate the influence of different abiotic environmental factors on the plant’s metabolite profile by multivariate statistical analyses of spectral data deduced by UHPLC-DAD-ESI-HRMS and NMR methods. Different plant part samples of T. diversifolia which included leaves, stems, roots, and inflorescences were collected from two Brazilian states throughout a 24-month period, along with the corresponding monthly environmental data. A metabolomic approach employing concatenated LC-MS and NMR data was utilised for the first time to study the relationships between environment and plant metabolism. A seasonal pattern was observed for the occurrence of metabolites that included sugars, sesquiterpenes lactones and phenolics in the leaf and stem parts, which can be correlated to the amount of rainfall and changes in temperature. The distribution of the metabolites in the inflorescence and root parts were mainly affected by variation of some soil nutrients such as Ca, Mg, P, K and Cu. We highlight the environment-metabolism relationship for T. diversifolia and the combined analytical approach to obtain reliable data that contributed to a holistic understanding of the influence of abiotic environmental factors on the production of metabolites in various plant parts.

Effect of the environment on the secondary metabolic profile of Tithonia diversifolia: a model for environmental metabolomics of plants

PubMed Central

Sampaio, Bruno Leite; Edrada-Ebel, RuAngelie; Da Costa, Fernando Batista

2016-01-01

Tithonia diversifolia is an invasive weed commonly found in tropical ecosystems. In this work, we investigate the influence of different abiotic environmental factors on the plant’s metabolite profile by multivariate statistical analyses of spectral data deduced by UHPLC-DAD-ESI-HRMS and NMR methods. Different plant part samples of T. diversifolia which included leaves, stems, roots, and inflorescences were collected from two Brazilian states throughout a 24-month period, along with the corresponding monthly environmental data. A metabolomic approach employing concatenated LC-MS and NMR data was utilised for the first time to study the relationships between environment and plant metabolism. A seasonal pattern was observed for the occurrence of metabolites that included sugars, sesquiterpenes lactones and phenolics in the leaf and stem parts, which can be correlated to the amount of rainfall and changes in temperature. The distribution of the metabolites in the inflorescence and root parts were mainly affected by variation of some soil nutrients such as Ca, Mg, P, K and Cu. We highlight the environment-metabolism relationship for T. diversifolia and the combined analytical approach to obtain reliable data that contributed to a holistic understanding of the influence of abiotic environmental factors on the production of metabolites in various plant parts. PMID:27383265

Novel Approach to Identify Potential Bioactive Plant Metabolites: Pharmacological and Metabolomics Analyses of Ethanol and Hot Water Extracts of Several Canadian Medicinal Plants of the Cree of Eeyou Istchee.

PubMed

Shang, Nan; Saleem, Ammar; Musallam, Lina; Walshe-Roussel, Brendan; Badawi, Alaa; Cuerrier, Alain; Arnason, John T; Haddad, Pierre S

2015-01-01

We evaluated and compared the antidiabetic potential and molecular mechanisms of 17 Cree plants' ethanol extracts (EE) and hot water extracts (HWE) on glucose homeostasis in vitro and used metabolomics to seek links with the content of specific phytochemicals. Several EE of medical plants stimulated muscle glucose uptake and inhibited hepatic G6Pase activity. Some HWE partially or completely lost these antidiabetic activities in comparison to EE. Only R. groenlandicum retained similar potential between EE and HWE in both assays. In C2C12 muscle cells, EE of R. groenlandicum, A. incana and S. purpurea stimulated glucose uptake by activating AMP-activated protein kinase (AMPK) pathway and increasing glucose transporter type 4 (GLUT4) expression. In comparison to EE, HWE of R. groenlandicum exhibited similar activities; HWE of A. incana completely lost its effect on all parameters; interestingly, HWE of S. purpurea activated insulin pathway instead of AMPK pathway to increase glucose uptake. In the liver, for a subset of 5 plants, HWE and EE activated AMPK pathway whereas the EE and HWE of S. purpurea and K. angustifolia also activated insulin pathways. Quercetin-3-O-galactoside and quercetin 3-O-α-L-arabinopyranoside, were successfully identified by discriminant analysis as biomarkers of HWE plant extracts that stimulate glucose uptake in vitro. More importantly, the latter compound was not identified by previous bioassay-guided fractionation.

Metabolomics Characterization of Two Apocynaceae Plants, Catharanthus roseus and Vinca minor, Using GC-MS and LC-MS Methods in Combination.

PubMed

Chen, Qi; Lu, Xueyan; Guo, Xiaorui; Guo, Qingxi; Li, Dewen

2017-06-17

Catharanthus roseus ( C. roseus ) and Vinca minor ( V. minor ) are two common important medical plants belonging to the family Apocynaceae. In this study, we used non-targeted GC-MS and targeted LC-MS metabolomics to dissect the metabolic profile of two plants with comparable phenotypic and metabolic differences. A total of 58 significantly different metabolites were present in different quantities according to PCA and PLS-DA score plots of the GC-MS analysis. The 58 identified compounds comprised 16 sugars, eight amino acids, nine alcohols and 18 organic acids. We subjected these metabolites into KEGG pathway enrichment analysis and highlighted 27 metabolic pathways, concentrated on the TCA cycle, glycometabolism, oligosaccharides, and polyol and lipid transporter (RFOS). Among the primary metabolites, trehalose, raffinose, digalacturonic acid and gallic acid were revealed to be the most significant marker compounds between the two plants, presumably contributing to species-specific phenotypic and metabolic discrepancy. The profiling of nine typical alkaloids in both plants using LC-MS method highlighted higher levels of crucial terpenoid indole alkaloid (TIA) intermediates of loganin, serpentine, and tabersonine in V. minor than in C. roseus . The possible underlying process of the metabolic flux from primary metabolism pathways to TIA synthesis was discussed and proposed. Generally speaking, this work provides a full-scale comparison of primary and secondary metabolites between two medical plants and a metabolic explanation of their TIA accumulation and phenotype differences.

High-resolution metabolic mapping of cell types in plant roots

PubMed Central

Moussaieff, Arieh; Rogachev, Ilana; Brodsky, Leonid; Malitsky, Sergey; Toal, Ted W.; Belcher, Heather; Yativ, Merav; Brady, Siobhan M.; Benfey, Philip N.; Aharoni, Asaph

2013-01-01

Metabolite composition offers a powerful tool for understanding gene function and regulatory processes. However, metabolomics studies on multicellular organisms have thus far been performed primarily on whole organisms, organs, or cell lines, losing information about individual cell types within a tissue. With the goal of profiling metabolite content in different cell populations within an organ, we used FACS to dissect GFP-marked cells from Arabidopsis roots for metabolomics analysis. Here, we present the metabolic profiles obtained from five GFP-tagged lines representing core cell types in the root. Fifty metabolites were putatively identified, with the most prominent groups being glucosinolates, phenylpropanoids, and dipeptides, the latter of which is not yet explored in roots. The mRNA expression of enzymes or regulators in the corresponding biosynthetic pathways was compared with the relative metabolite abundance. Positive correlations suggest that the rate-limiting steps in biosynthesis of glucosinolates in the root are oxidative modifications of side chains. The current study presents a work flow for metabolomics analyses of cell-type populations. PMID:23476065

Untargeted metabolomic analysis of tomato pollen development and heat stress response.

PubMed

Paupière, Marine J; Müller, Florian; Li, Hanjing; Rieu, Ivo; Tikunov, Yury M; Visser, Richard G F; Bovy, Arnaud G

2017-06-01

Pollen development metabolomics. Developing pollen is among the plant structures most sensitive to high temperatures, and a decrease in pollen viability is often associated with an alteration of metabolite content. Most of the metabolic studies of pollen have focused on a specific group of compounds, which limits the identification of physiologically important metabolites. To get a better insight into pollen development and the pollen heat stress response, we used a liquid chromatography-mass spectrometry platform to detect secondary metabolites in pollen of tomato (Solanum lycopersicum L.) at three developmental stages under control conditions and after a short heat stress at 38 °C. Under control conditions, the young microspores accumulated a large amount of alkaloids and polyamines, whereas the mature pollen strongly accumulated flavonoids. The heat stress treatment led to accumulation of flavonoids in the microspore. The biological role of the detected metabolites is discussed. This study provides the first untargeted metabolomic analysis of developing pollen under a changing environment that can serve as reference for further studies.

Metabolomic-Guided Isolation of Bioactive Natural Products from Curvularia sp., an Endophytic Fungus of Terminalia laxiflora.

PubMed

Tawfike, Ahmed F; Abbott, Grainne; Young, Louise; Edrada-Ebel, RuAngelie

2018-02-01

Endophytic fungi associated with medicinal plants are a potential source of novel chemistry and biology. Metabolomic tools were successfully employed to compare the metabolite fingerprints of solid and liquid culture extracts of endophyte Curvularia sp. isolated from the leaves of Terminalia laxiflora . Natural product databases were used to dereplicate metabolites in order to determine known compounds and the presence of new natural products. Multivariate analysis highlighted the putative metabolites responsible for the bioactivity of the fungal extract and its fractions on NF- κ B and the myelogenous leukemia cell line K562. Metabolomic tools and dereplication studies using high-resolution electrospray ionization mass spectrometry directed the fractionation and isolation of the bioactive components from the fungal extracts. This resulted in the isolation of N -acetylphenylalanine (1: ) and two linear peptide congeners of 1: : dipeptide N -acetylphenylalanyl-L-phenylalanine (2: ) and tripeptide N -acetylphenylalanyl-L-phenylalanyl-L-leucine (3: ). Georg Thieme Verlag KG Stuttgart · New York.

Time-resolved metabolomics reveals metabolic modulation in rice foliage

PubMed Central

Sato, Shigeru; Arita, Masanori; Soga, Tomoyoshi; Nishioka, Takaaki; Tomita, Masaru

2008-01-01

Background To elucidate the interaction of dynamics among modules that constitute biological systems, comprehensive datasets obtained from "omics" technologies have been used. In recent plant metabolomics approaches, the reconstruction of metabolic correlation networks has been attempted using statistical techniques. However, the results were unsatisfactory and effective data-mining techniques that apply appropriate comprehensive datasets are needed. Results Using capillary electrophoresis mass spectrometry (CE-MS) and capillary electrophoresis diode-array detection (CE-DAD), we analyzed the dynamic changes in the level of 56 basic metabolites in plant foliage (Oryza sativa L. ssp. japonica) at hourly intervals over a 24-hr period. Unsupervised clustering of comprehensive metabolic profiles using Kohonen's self-organizing map (SOM) allowed classification of the biochemical pathways activated by the light and dark cycle. The carbon and nitrogen (C/N) metabolism in both periods was also visualized as a phenotypic linkage map that connects network modules on the basis of traditional metabolic pathways rather than pairwise correlations among metabolites. The regulatory networks of C/N assimilation/dissimilation at each time point were consistent with previous works on plant metabolism. In response to environmental stress, glutathione and spermidine fluctuated synchronously with their regulatory targets. Adenine nucleosides and nicotinamide coenzymes were regulated by phosphorylation and dephosphorylation. We also demonstrated that SOM analysis was applicable to the estimation of unidentifiable metabolites in metabolome analysis. Hierarchical clustering of a correlation coefficient matrix could help identify the bottleneck enzymes that regulate metabolic networks. Conclusion Our results showed that our SOM analysis with appropriate metabolic time-courses effectively revealed the synchronous dynamics among metabolic modules and elucidated the underlying biochemical functions. The application of discrimination of unidentified metabolites and the identification of bottleneck enzymatic steps even to non-targeted comprehensive analysis promise to facilitate an understanding of large-scale interactions among components in biological systems. PMID:18564421

Comparative physiological and metabolomics analysis of wheat (Triticum aestivum L.) following post-anthesis heat stress

PubMed Central

Beecher, Chris; MacDonald, Greg

2018-01-01

Genetic improvement for stress tolerance requires a solid understanding of biochemical processes involved with different physiological mechanisms and their relationships with different traits. The objective of this study was to demonstrate genetic variability in altered metabolic levels in a panel of six wheat genotypes in contrasting temperature regimes, and to quantify the correlation between those metabolites with different traits. In a controlled environment experiment, heat stress (35:28 ± 0.08°C) was initiated 10 days after anthesis. Flag leaves were collected 10 days after heat treatment to employ an untargeted metabolomics profiling using LC-HRMS based technique called IROA. High temperature stress produced significant genetic variations for cell and thylakoid membrane damage, and yield related traits. 64 known metabolites accumulated 1.5 fold of higher or lower due to high temperature stress. In general, metabolites that increased the most under heat stress (L-tryptophan, pipecolate) showed negative correlation with different traits. Contrary, the metabolites that decreased the most under heat stress (drummondol, anthranilate) showed positive correlation with the traits. Aminoacyl-tRNA biosysnthesis and plant secondary metabolite biosynthesis pathways were most impacted by high temperature stress. The robustness of metabolic change and their relationship with phenotypes renders those metabolites as potential bio-markers for genetic improvement. PMID:29897945

Comparative Metabolomics Approach Detects Stress-Specific Responses during Coral Bleaching in Soft Corals.

PubMed

Farag, Mohamed A; Meyer, Achim; Ali, Sara E; Salem, Mohamed A; Giavalisco, Patrick; Westphal, Hildegard; Wessjohann, Ludger A

2018-06-01

Chronic exposure to ocean acidification and elevated sea-surface temperatures pose significant stress to marine ecosystems. This in turn necessitates costly acclimation responses in corals in both the symbiont and host, with a reorganization of cell metabolism and structure. A large-scale untargeted metabolomics approach comprising gas chromatography mass spectrometry (GC-MS) and ultraperformance liquid chromatography coupled to high resolution mass spectrometry (UPLC-MS) was applied to profile the metabolite composition of the soft coral Sarcophyton ehrenbergi and its dinoflagellate symbiont. Metabolite profiling compared ambient conditions with response to simulated climate change stressors and with the sister species, S. glaucum. Among ∼300 monitored metabolites, 13 metabolites were modulated. Incubation experiments providing four selected upregulated metabolites (alanine, GABA, nicotinic acid, and proline) in the culturing water failed to subside the bleaching response at temperature-induced stress, despite their known ability to mitigate heat stress in plants or animals. Thus, the results hint to metabolite accumulation (marker) during heat stress. This study provides the first detailed map of metabolic pathways transition in corals in response to different environmental stresses, accounting for the superior thermal tolerance of S. ehrenbergi versus S. glaucum, which can ultimately help maintain a viable symbiosis and mitigate against coral bleaching.

An Integrative Genetic Study of Rice Metabolism, Growth and Stochastic Variation Reveals Potential C/N Partitioning Loci

NASA Astrophysics Data System (ADS)

Li, Baohua; Zhang, Yuanyuan; Mohammadi, Seyed Abolghasem; Huai, Dongxin; Zhou, Yongming; Kliebenstein, Daniel J.

2016-07-01

Studying the genetic basis of variation in plant metabolism has been greatly facilitated by genomic and metabolic profiling advances. In this study, we use metabolomics and growth measurements to map QTL in rice, a major staple crop. Previous rice metabolism studies have largely focused on identifying genes controlling major effect loci. To complement these studies, we conducted a replicated metabolomics analysis on a japonica (Lemont) by indica (Teqing) rice recombinant inbred line population and focused on the genetic variation for primary metabolism. Using independent replicated studies, we show that in contrast to other rice studies, the heritability of primary metabolism is similar to Arabidopsis. The vast majority of metabolic QTLs had small to moderate effects with significant polygenic epistasis. Two metabolomics QTL hotspots had opposing effects on carbon and nitrogen rich metabolites suggesting that they may influence carbon and nitrogen partitioning, with one locus co-localizing with SUSIBA2 (WRKY78). Comparing QTLs for metabolomic and a variety of growth related traits identified few overlaps. Interestingly, the rice population displayed fewer loci controlling stochastic variation for metabolism than was found in Arabidopsis. Thus, it is possible that domestication has differentially impacted stochastic metabolite variation more than average metabolite variation.

A Sister Group Contrast Using Untargeted Global Metabolomic Analysis Delineates the Biochemical Regulation Underlying Desiccation Tolerance in Sporobolus stapfianus[C][W][OA

PubMed Central

Oliver, Melvin J.; Guo, Lining; Alexander, Danny C.; Ryals, John A.; Wone, Bernard W.M.; Cushman, John C.

2011-01-01

Understanding how plants tolerate dehydration is a prerequisite for developing novel strategies for improving drought tolerance. The desiccation-tolerant (DT) Sporobolus stapfianus and the desiccation-sensitive (DS) Sporobolus pyramidalis formed a sister group contrast to reveal adaptive metabolic responses to dehydration using untargeted global metabolomic analysis. Young leaves from both grasses at full hydration or at 60% relative water content (RWC) and from S. stapfianus at lower RWCs were analyzed using liquid and gas chromatography linked to mass spectrometry or tandem mass spectrometry. Comparison of the two species in the fully hydrated state revealed intrinsic differences between the two metabolomes. S. stapfianus had higher concentrations of osmolytes, lower concentrations of metabolites associated with energy metabolism, and higher concentrations of nitrogen metabolites, suggesting that it is primed metabolically for dehydration stress. Further reduction of the leaf RWC to 60% instigated a metabolic shift in S. stapfianus toward the production of protective compounds, whereas S. pyramidalis responded differently. The metabolomes of S. stapfianus leaves below 40% RWC were strongly directed toward antioxidant production, nitrogen remobilization, ammonia detoxification, and soluble sugar production. Collectively, the metabolic profiles obtained uncovered a cascade of biochemical regulation strategies critical to the survival of S. stapfianus under desiccation. PMID:21467579

A Generic Multiple Reaction Monitoring Based Approach for Plant Flavonoids Profiling Using a Triple Quadrupole Linear Ion Trap Mass Spectrometry

NASA Astrophysics Data System (ADS)

Yan, Zhixiang; Lin, Ge; Ye, Yang; Wang, Yitao; Yan, Ru

2014-06-01

Flavonoids are one of the largest classes of plant secondary metabolites serving a variety of functions in plants and associating with a number of health benefits for humans. Typically, they are co-identified with many other secondary metabolites using untargeted metabolomics. The limited data quality of untargeted workflow calls for a shift from the breadth-first to the depth-first screening strategy when a specific biosynthetic pathway is focused on. Here we introduce a generic multiple reaction monitoring (MRM)-based approach for flavonoids profiling in plants using a hybrid triple quadrupole linear ion trap (QTrap) mass spectrometer. The approach includes four steps: (1) preliminary profiling of major aglycones by multiple ion monitoring triggered enhanced product ion scan (MIM-EPI); (2) glycones profiling by precursor ion triggered EPI scan (PI-EPI) of major aglycones; (3) comprehensive aglycones profiling by combining MIM-EPI and neutral loss triggered EPI scan (NL-EPI) of major glycone; (4) in-depth flavonoids profiling by MRM-EPI with elaborated MRM transitions. Particularly, incorporation of the NH3 loss and sugar elimination proved to be very informative and confirmative for flavonoids screening. This approach was applied for profiling flavonoids in Astragali radix ( Huangqi), a famous herb widely used for medicinal and nutritional purposes in China. In total, 421 flavonoids were tentatively characterized, among which less than 40 have been previously reported in this medicinal plant. This MRM-based approach provides versatility and sensitivity that required for flavonoids profiling in plants and serves as a useful tool for plant metabolomics.

Assessing chemical exposure and ecological impacts of environmental surface waters using cell culture-based metabolomic

EPA Science Inventory

Waste water treatment plants (WWTPs), as well as industrial and agricultural operations release complex mixtures of anthropogenic chemicals that negatively affect surface water quality. Previous studies have shown that exposure to such complex chemical mixtures can produce adver...

KEGG Bioinformatics Resource for Plant Genomics and Metabolomics.

PubMed

Kanehisa, Minoru

2016-01-01

In the era of high-throughput biology it is necessary to develop not only elaborate computational methods but also well-curated databases that can be used as reference for data interpretation. KEGG ( http://www.kegg.jp/ ) is such a reference knowledge base with two specific aims. One is to compile knowledge on high-level functions of the cell and the organism in terms of the molecular interaction and reaction networks, which is implemented in KEGG pathway maps, BRITE functional hierarchies, and KEGG modules. The other is to expand knowledge on genes and proteins involved in the molecular networks from experimentally observed organisms to other organisms using the concept of orthologs, which is implemented in the KEGG Orthology (KO) system. Thus, KEGG is a generic resource applicable to all organisms and enables interpretation of high-level functions from genomic and molecular data. Here we first present a brief overview of the entire KEGG resource, and then give an introduction of how to use KEGG in plant genomics and metabolomics research.

Differentiating signals to make biological sense - A guide through databases for MS-based non-targeted metabolomics.

PubMed

Gil de la Fuente, Alberto; Grace Armitage, Emily; Otero, Abraham; Barbas, Coral; Godzien, Joanna

2017-09-01

Metabolite identification is one of the most challenging steps in metabolomics studies and reflects one of the greatest bottlenecks in the entire workflow. The success of this step determines the success of the entire research, therefore the quality at which annotations are given requires special attention. A variety of tools and resources are available to aid metabolite identification or annotation, offering different and often complementary functionalities. In preparation for this article, almost 50 databases were reviewed, from which 17 were selected for discussion, chosen for their online ESI-MS functionality. The general characteristics and functions of each database is discussed in turn, considering the advantages and limitations of each along with recommendations for optimal use of each tool, as derived from experiences encountered at the Centre for Metabolomics and Bioanalysis (CEMBIO) in Madrid. These databases were evaluated considering their utility in non-targeted metabolomics, including aspects such as identifier assignment, structural assignment and interpretation of results. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling

DOE PAGES

Benton, H. Paul; Ivanisevic, Julijana; Mahieu, Nathaniel G.; ...

2014-12-12

An autonomous metabolomic workflow combining mass spectrometry analysis with tandem mass spectrometry data acquisition was designed to allow for simultaneous data processing and metabolite characterization. Although previously tandem mass spectrometry data have been generated on the fly, the experiments described herein combine this technology with the bioinformatic resources of XCMS and METLIN. We can analyze large profiling datasets and simultaneously obtain structural identifications, as a result of this unique integration. Furthermore, validation of the workflow on bacterial samples allowed the profiling on the order of a thousand metabolite features with simultaneous tandem mass spectra data acquisition. The tandem mass spectrometrymore » data acquisition enabled automatic search and matching against the METLIN tandem mass spectrometry database, shortening the current workflow from days to hours. Overall, the autonomous approach to untargeted metabolomics provides an efficient means of metabolomic profiling, and will ultimately allow the more rapid integration of comparative analyses, metabolite identification, and data analysis at a systems biology level.« less

Real-time metabolome profiling of the metabolic switch between starvation and growth.

PubMed

Link, Hannes; Fuhrer, Tobias; Gerosa, Luca; Zamboni, Nicola; Sauer, Uwe

2015-11-01

Metabolic systems are often the first networks to respond to environmental changes, and the ability to monitor metabolite dynamics is key for understanding these cellular responses. Because monitoring metabolome changes is experimentally tedious and demanding, dynamic data on time scales from seconds to hours are scarce. Here we describe real-time metabolome profiling by direct injection of living bacteria, yeast or mammalian cells into a high-resolution mass spectrometer, which enables automated monitoring of about 300 compounds in 15-30-s cycles over several hours. We observed accumulation of energetically costly biomass metabolites in Escherichia coli in carbon starvation-induced stationary phase, as well as the rapid use of these metabolites upon growth resumption. By combining real-time metabolome profiling with modeling and inhibitor experiments, we obtained evidence for switch-like feedback inhibition in amino acid biosynthesis and for control of substrate availability through the preferential use of the metabolically cheaper one-step salvaging pathway over costly ten-step de novo purine biosynthesis during growth resumption.

Modelling short time series in metabolomics: a functional data analysis approach.

PubMed

Montana, Giovanni; Berk, Maurice; Ebbels, Tim

2011-01-01

Metabolomics is the study of the complement of small molecule metabolites in cells, biofluids and tissues. Many metabolomic experiments are designed to compare changes observed over time under two or more experimental conditions (e.g. a control and drug-treated group), thus producing time course data. Models from traditional time series analysis are often unsuitable because, by design, only very few time points are available and there are a high number of missing values. We propose a functional data analysis approach for modelling short time series arising in metabolomic studies which overcomes these obstacles. Our model assumes that each observed time series is a smooth random curve, and we propose a statistical approach for inferring this curve from repeated measurements taken on the experimental units. A test statistic for detecting differences between temporal profiles associated with two experimental conditions is then presented. The methodology has been applied to NMR spectroscopy data collected in a pre-clinical toxicology study.

MetMatch: A Semi-Automated Software Tool for the Comparison and Alignment of LC-HRMS Data from Different Metabolomics Experiments

PubMed Central

Koch, Stefan; Bueschl, Christoph; Doppler, Maria; Simader, Alexandra; Meng-Reiterer, Jacqueline; Lemmens, Marc; Schuhmacher, Rainer

2016-01-01

Due to its unsurpassed sensitivity and selectivity, LC-HRMS is one of the major analytical techniques in metabolomics research. However, limited stability of experimental and instrument parameters may cause shifts and drifts of retention time and mass accuracy or the formation of different ion species, thus complicating conclusive interpretation of the raw data, especially when generated in different analytical batches. Here, a novel software tool for the semi-automated alignment of different measurement sequences is presented. The tool is implemented in the Java programming language, it features an intuitive user interface and its main goal is to facilitate the comparison of data obtained from different metabolomics experiments. Based on a feature list (i.e., processed LC-HRMS chromatograms with mass-to-charge ratio (m/z) values and retention times) that serves as a reference, the tool recognizes both m/z and retention time shifts of single or multiple analytical datafiles/batches of interest. MetMatch is also designed to account for differently formed ion species of detected metabolites. Corresponding ions and metabolites are matched and chromatographic peak areas, m/z values and retention times are combined into a single data matrix. The convenient user interface allows for easy manipulation of processing results and graphical illustration of the raw data as well as the automatically matched ions and metabolites. The software tool is exemplified with LC-HRMS data from untargeted metabolomics experiments investigating phenylalanine-derived metabolites in wheat and T-2 toxin/HT-2 toxin detoxification products in barley. PMID:27827849

MetMatch: A Semi-Automated Software Tool for the Comparison and Alignment of LC-HRMS Data from Different Metabolomics Experiments.

PubMed

Koch, Stefan; Bueschl, Christoph; Doppler, Maria; Simader, Alexandra; Meng-Reiterer, Jacqueline; Lemmens, Marc; Schuhmacher, Rainer

2016-11-02

Due to its unsurpassed sensitivity and selectivity, LC-HRMS is one of the major analytical techniques in metabolomics research. However, limited stability of experimental and instrument parameters may cause shifts and drifts of retention time and mass accuracy or the formation of different ion species, thus complicating conclusive interpretation of the raw data, especially when generated in different analytical batches. Here, a novel software tool for the semi-automated alignment of different measurement sequences is presented. The tool is implemented in the Java programming language, it features an intuitive user interface and its main goal is to facilitate the comparison of data obtained from different metabolomics experiments. Based on a feature list (i.e., processed LC-HRMS chromatograms with mass-to-charge ratio ( m / z ) values and retention times) that serves as a reference, the tool recognizes both m / z and retention time shifts of single or multiple analytical datafiles/batches of interest. MetMatch is also designed to account for differently formed ion species of detected metabolites. Corresponding ions and metabolites are matched and chromatographic peak areas, m / z values and retention times are combined into a single data matrix. The convenient user interface allows for easy manipulation of processing results and graphical illustration of the raw data as well as the automatically matched ions and metabolites. The software tool is exemplified with LC-HRMS data from untargeted metabolomics experiments investigating phenylalanine-derived metabolites in wheat and T-2 toxin/HT-2 toxin detoxification products in barley.

ACP and Citrus: Plant Responses to Psyllid Feeding

USDA-ARS?s Scientific Manuscript database

Progress is reported on the Citrus Research Board funded project: 5300-150 Biomarkers for the detection of Liberibacter infection in citrus through H-NMR-based metabolomics. Proton nuclear magnetic resonance (H-NMR) was used to determine the effects of Asian citrus psyllid (ACP) feeding on leaf meta...

Understanding water deficit stress-induced changes in the basic metabolism of higher plants - biotechnologically and sustainably improving agriculture and the ecoenvironment in arid regions of the globe.

PubMed

Shao, Hong-Bo; Chu, Li-Ye; Jaleel, C Abdul; Manivannan, P; Panneerselvam, R; Shao, Ming-An

2009-01-01

Water is vital for plant growth, development and productivity. Permanent or temporary water deficit stress limits the growth and distribution of natural and artificial vegetation and the performance of cultivated plants (crops) more than any other environmental factor. Productive and sustainable agriculture necessitates growing plants (crops) in arid and semiarid regions with less input of precious resources such as fresh water. For a better understanding and rapid improvement of soil-water stress tolerance in these regions, especially in the water-wind eroded crossing region, it is very important to link physiological and biochemical studies to molecular work in genetically tractable model plants and important native plants, and further extending them to practical ecological restoration and efficient crop production. Although basic studies and practices aimed at improving soil water stress resistance and plant water use efficiency have been carried out for many years, the mechanisms involved at different scales are still not clear. Further understanding and manipulating soil-plant water relationships and soil-water stress tolerance at the scales of ecology, physiology and molecular biology can significantly improve plant productivity and environmental quality. Currently, post-genomics and metabolomics are very important in exploring anti-drought gene resources in various life forms, but modern agriculturally sustainable development must be combined with plant physiological measures in the field, on the basis of which post-genomics and metabolomics have further practical prospects. In this review, we discuss physiological and molecular insights and effects in basic plant metabolism, drought tolerance strategies under drought conditions in higher plants for sustainable agriculture and ecoenvironments in arid and semiarid areas of the world. We conclude that biological measures are the bases for the solutions to the issues relating to the different types of sustainable development.

Metabolic footprint of epiphytic bacteria on Arabidopsis thaliana leaves

PubMed Central

Ryffel, Florian; Helfrich, Eric JN; Kiefer, Patrick; Peyriga, Lindsay; Portais, Jean-Charles; Piel, Jörn; Vorholt, Julia A

2016-01-01

The phyllosphere, which is defined as the parts of terrestrial plants above the ground, is a large habitat for different microorganisms that show a high extent of adaption to their environment. A number of hypotheses were generated by culture-independent functional genomics studies to explain the competitiveness of specialized bacteria in the phyllosphere. In contrast, in situ data at the metabolome level as a function of bacterial colonization are lacking. Here, we aimed to obtain new insights into the metabolic interplay between host and epiphytes upon colonization of Arabidopsis thaliana leaves in a controlled laboratory setting using environmental metabolomics approaches. Quantitative nuclear magnetic resonance (NMR) and imaging high-resolution mass spectrometry (IMS) methods were used to identify Arabidopsis leaf surface compounds and their possible involvement in the epiphytic lifestyle by relative changes in compound pools. The dominant carbohydrates on the leaf surfaces were sucrose, fructose and glucose. These sugars were significantly and specifically altered after epiphytic leaf colonization by the organoheterotroph Sphingomonas melonis or the phytopathogen Pseudomonas syringae pv. tomato, but only to a minor extent by the methylotroph Methylobacterium extorquens. In addition to carbohydrates, IMS revealed surprising alterations in arginine metabolism and phytoalexin biosynthesis that were dependent on the presence of bacteria, which might reflect the consequences of bacterial activity and the recognition of not only pathogens but also commensals by the plant. These results highlight the power of environmental metabolomics to aid in elucidating the molecular basis underlying plant–epiphyte interactions in situ. PMID:26305156

The mzTab data exchange format: communicating mass-spectrometry-based proteomics and metabolomics experimental results to a wider audience.

PubMed

Griss, Johannes; Jones, Andrew R; Sachsenberg, Timo; Walzer, Mathias; Gatto, Laurent; Hartler, Jürgen; Thallinger, Gerhard G; Salek, Reza M; Steinbeck, Christoph; Neuhauser, Nadin; Cox, Jürgen; Neumann, Steffen; Fan, Jun; Reisinger, Florian; Xu, Qing-Wei; Del Toro, Noemi; Pérez-Riverol, Yasset; Ghali, Fawaz; Bandeira, Nuno; Xenarios, Ioannis; Kohlbacher, Oliver; Vizcaíno, Juan Antonio; Hermjakob, Henning

2014-10-01

The HUPO Proteomics Standards Initiative has developed several standardized data formats to facilitate data sharing in mass spectrometry (MS)-based proteomics. These allow researchers to report their complete results in a unified way. However, at present, there is no format to describe the final qualitative and quantitative results for proteomics and metabolomics experiments in a simple tabular format. Many downstream analysis use cases are only concerned with the final results of an experiment and require an easily accessible format, compatible with tools such as Microsoft Excel or R. We developed the mzTab file format for MS-based proteomics and metabolomics results to meet this need. mzTab is intended as a lightweight supplement to the existing standard XML-based file formats (mzML, mzIdentML, mzQuantML), providing a comprehensive summary, similar in concept to the supplemental material of a scientific publication. mzTab files can contain protein, peptide, and small molecule identifications together with experimental metadata and basic quantitative information. The format is not intended to store the complete experimental evidence but provides mechanisms to report results at different levels of detail. These range from a simple summary of the final results to a representation of the results including the experimental design. This format is ideally suited to make MS-based proteomics and metabolomics results available to a wider biological community outside the field of MS. Several software tools for proteomics and metabolomics have already adapted the format as an output format. The comprehensive mzTab specification document and extensive additional documentation can be found online. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

The mzTab Data Exchange Format: Communicating Mass-spectrometry-based Proteomics and Metabolomics Experimental Results to a Wider Audience*

PubMed Central

Griss, Johannes; Jones, Andrew R.; Sachsenberg, Timo; Walzer, Mathias; Gatto, Laurent; Hartler, Jürgen; Thallinger, Gerhard G.; Salek, Reza M.; Steinbeck, Christoph; Neuhauser, Nadin; Cox, Jürgen; Neumann, Steffen; Fan, Jun; Reisinger, Florian; Xu, Qing-Wei; del Toro, Noemi; Pérez-Riverol, Yasset; Ghali, Fawaz; Bandeira, Nuno; Xenarios, Ioannis; Kohlbacher, Oliver; Vizcaíno, Juan Antonio; Hermjakob, Henning

2014-01-01

The HUPO Proteomics Standards Initiative has developed several standardized data formats to facilitate data sharing in mass spectrometry (MS)-based proteomics. These allow researchers to report their complete results in a unified way. However, at present, there is no format to describe the final qualitative and quantitative results for proteomics and metabolomics experiments in a simple tabular format. Many downstream analysis use cases are only concerned with the final results of an experiment and require an easily accessible format, compatible with tools such as Microsoft Excel or R. We developed the mzTab file format for MS-based proteomics and metabolomics results to meet this need. mzTab is intended as a lightweight supplement to the existing standard XML-based file formats (mzML, mzIdentML, mzQuantML), providing a comprehensive summary, similar in concept to the supplemental material of a scientific publication. mzTab files can contain protein, peptide, and small molecule identifications together with experimental metadata and basic quantitative information. The format is not intended to store the complete experimental evidence but provides mechanisms to report results at different levels of detail. These range from a simple summary of the final results to a representation of the results including the experimental design. This format is ideally suited to make MS-based proteomics and metabolomics results available to a wider biological community outside the field of MS. Several software tools for proteomics and metabolomics have already adapted the format as an output format. The comprehensive mzTab specification document and extensive additional documentation can be found online. PMID:24980485

Atmo-metabolomics: a new measurement approach for investigating aerosol composition and ecosystem functioning.

NASA Astrophysics Data System (ADS)

Rivas-Ubach, A.; Liu, Y.; Sardans, J.; Tfaily, M. M.; Kim, Y. M.; Bourrianne, E.; Paša-Tolić, L.; Penuelas, J.; Guenther, A. B.

2016-12-01

Aerosols play crucial roles in the processes controlling the composition of the atmosphere and the functioning of ecosystems. Gaining a deeper understanding of the chemical composition of aerosols is one of the major challenges for atmospheric and climate scientists and is beginning to be recognized as important for ecological research. Better comprehension of aerosol chemistry can potentially provide valuable information on atmospheric processes such as oxidation of organics and the production of cloud condensation nuclei as well as provide an approximation of the general status of an ecosystem through the measurement of certain stress biomarkers. In this study, we describe an efficient aerosol sampling method, the metabolite extraction and the analytical procedures for the chemical characterization of aerosols, namely, the atmo-metabolome. We used mass spectrometry (MS) coupled to liquid chromatography (LC-MS), gas chromatography (GC-MS) and Fourier transform ion cyclotron resonance (FT-ICR-MS) to characterize the atmo-metabolome of two marked seasons; spring and summer. Our sampling and extraction methods demonstrated to be suitable for aerosol chemical characterization with any of the analytical platforms used in this study. The atmo-metabolome between spring and summer showed overall statistically differences. We identified several metabolites that can be attributed to pollen and other plant-related aerosols. Spring aerosols exhibit higher concentrations of metabolites linked to higher plant activity while summer samples had higher concentrations of metabolites that may reflect certain oxidative stresses in primary producers. Moreover, the elemental composition of aerosols showed clear different between seasons. Summer aerosols were generally higher in molecular weight and with higher O/C ratios, indicating higher oxidation levels and condensation of compounds relative to spring. Our method represents an advanced approach for characterizing the composition of aerosols that will benefit scientists attempting to understand complex atmospheric processes and the ecosystem status across a whole ecoregion.

A statistical analysis of the effects of urease pre-treatment on the measurement of the urinary metabolome by gas chromatography–mass spectrometry

DOE PAGES

Webb-Robertson, Bobbie-Jo; Kim, Young -Mo; Zink, Erika M.; ...

2014-02-27

Urease pre-treatment of urine has been utilized since the early 1960s to remove high levels of urea from samples prior to further processing and analysis by gas chromatography-mass spectrometry (GC-MS). Aside from the obvious depletion or elimination of urea, the effect, if any, of urease pre-treatment on the urinary metabolome has not been studied in detail. Here, we report the results of three separate but related experiments that were designed to assess possible indirect effects of urease pre-treatment on the urinary metabolome as measured by GC-MS. In total, 235 GC-MS analyses were performed and over 106 identified and 200 unidentifiedmore » metabolites were quantified across the three experiments. The results showed that data from urease pre-treated samples 1) had the same or lower coefficients of variance among reproducibly detected metabolites, 2) more accurately reflected quantitative differences and the expected ratios among different urine volumes, and 3) increased the number of metabolite identifications. Altogether, we observed no negative consequences of urease pre-treatment. In contrast, urease pretreatment enhanced the ability to distinguish between volume-based and biological sample types compared to no treatment. Taken together, these results show that urease pretreatment of urine offers multiple beneficial effects that outweigh any artifacts that may be introduced to the data in urinary metabolomics analyses.« less

A Statistical Analysis of the Effects of Urease Pre-treatment on the Measurement of the Urinary Metabolome by Gas Chromatography-Mass Spectrometry

PubMed Central

Webb-Robertson, Bobbie-Jo; Kim, Young-Mo; Zink, Erika M.; Hallaian, Katherine A.; Zhang, Qibin; Madupu, Ramana; Waters, Katrina M.; Metz, Thomas O.

2014-01-01

Urease pre-treatment of urine has been utilized since the early 1960s to remove high levels of urea from samples prior to further processing and analysis by gas chromatography-mass spectrometry (GC-MS). Aside from the obvious depletion or elimination of urea, the effect, if any, of urease pre-treatment on the urinary metabolome has not been studied in detail. Here, we report the results of three separate but related experiments that were designed to assess possible indirect effects of urease pre-treatment on the urinary metabolome as measured by GC-MS. In total, 235 GC-MS analyses were performed and over 106 identified and 200 unidentified metabolites were quantified across the three experiments. The results showed that data from urease pre-treated samples 1) had the same or lower coefficients of variance among reproducibly detected metabolites, 2) more accurately reflected quantitative differences and the expected ratios among different urine volumes, and 3) increased the number of metabolite identifications. Overall, we observed no negative consequences of urease pre-treatment. In contrast, urease pretreatment enhanced the ability to distinguish between volume-based and biological sample types compared to no treatment. Taken together, these results show that urease pretreatment of urine offers multiple beneficial effects that outweigh any artifacts that may be introduced to the data in urinary metabolomics analyses. PMID:25254001

Apple replant disease and the –omics: interaction of apple rootstock metabolome and the soil microbiome

USDA-ARS?s Scientific Manuscript database

Apple replant disease (ARD) negatively impacts tree health and reduces crop yield in new orchard plantings. Use of tolerant rootstock cultivars can diminish the growth limiting effects of ARD; however specific rootstock attributes enabling ARD tolerance are not understood. Systems biology tools were...

High Sensitivity NMR and Mixture Analysis for Nematode Behavioral Metabolomics

USDA-ARS?s Scientific Manuscript database

Nematodes are the most abundant animal on earth, and they parasitize virtually all plants and animals. Caenorhabditis elegans is a free-living nematode that lives in soil and composting material. We have shown that C. elegans releases at least 40 small molecules into its environment including many...

Metabolic Reprogramming in Leaf Lettuce Grown Under Different Light Quality and Intensity Conditions Using Narrow-Band LEDs.

PubMed

Kitazaki, Kazuyoshi; Fukushima, Atsushi; Nakabayashi, Ryo; Okazaki, Yozo; Kobayashi, Makoto; Mori, Tetsuya; Nishizawa, Tomoko; Reyes-Chin-Wo, Sebastian; Michelmore, Richard W; Saito, Kazuki; Shoji, Kazuhiro; Kusano, Miyako

2018-05-21

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. Four types of monochromatic LEDs (one blue, two green and one red) and white fluorescent light (control) were used at low and high intensities (100 and 300 μmol·m -2 ·s -1 , respectively). Multi-platform mass spectrometry-based metabolomics and RNA-Seq were used to determine changes in the metabolome and transcriptome of lettuce plants in response to different light qualities and intensities. Metabolic pathway analysis revealed distinct regulatory mechanisms involved in flavonoid and phenylpropanoid biosynthetic pathways under blue and green wavelengths. Taken together, these data suggest that the energy transmitted by green light is effective in creating a balance between biomass production and the production of secondary metabolites involved in plant defence.

Metabolomic Profiling of Bradyrhizobium diazoefficiens-Induced Root Nodules Reveals Both Host Plant-Specific and Developmental Signatures

PubMed Central

Lardi, Martina; Murset, Valérie; Fischer, Hans-Martin; Mesa, Socorro; Ahrens, Christian H.; Zamboni, Nicola; Pessi, Gabriella

2016-01-01

Bradyrhizobium diazoefficiens is a nitrogen-fixing endosymbiont, which can grow inside root-nodule cells of the agriculturally important soybean and other host plants. Our previous studies described B. diazoefficiens host-specific global expression changes occurring during legume infection at the transcript and protein level. In order to further characterize nodule metabolism, we here determine by flow injection–time-of-flight mass spectrometry analysis the metabolome of (i) nodules and roots from four different B. diazoefficiens host plants; (ii) soybean nodules harvested at different time points during nodule development; and (iii) soybean nodules infected by two strains mutated in key genes for nitrogen fixation, respectively. Ribose (soybean), tartaric acid (mungbean), hydroxybutanoyloxybutanoate (siratro) and catechol (cowpea) were among the metabolites found to be specifically elevated in one of the respective host plants. While the level of C4-dicarboxylic acids decreased during soybean nodule development, we observed an accumulation of trehalose-phosphate at 21 days post infection (dpi). Moreover, nodules from non-nitrogen-fixing bacteroids (nifA and nifH mutants) showed specific metabolic alterations; these were also supported by independent transcriptomics data. The alterations included signs of nitrogen limitation in both mutants, and an increased level of a phytoalexin in nodules induced by the nifA mutant, suggesting that the tissue of these nodules exhibits defense and stress reactions. PMID:27240350

Metabolomics analysis reveals the metabolic and functional roles of flavonoids in light-sensitive tea leaves.

PubMed

Zhang, Qunfeng; Liu, Meiya; Ruan, Jianyun

2017-03-20

As the predominant secondary metabolic pathway in tea plants, flavonoid biosynthesis increases with increasing temperature and illumination. However, the concentration of most flavonoids decreases greatly in light-sensitive tea leaves when they are exposed to light, which further improves tea quality. To reveal the metabolism and potential functions of flavonoids in tea leaves, a natural light-sensitive tea mutant (Huangjinya) cultivated under different light conditions was subjected to metabolomics analysis. The results showed that chlorotic tea leaves accumulated large amounts of flavonoids with ortho-dihydroxylated B-rings (e.g., catechin gallate, quercetin and its glycosides etc.), whereas total flavonoids (e.g., myricetrin glycoside, epigallocatechin gallate etc.) were considerably reduced, suggesting that the flavonoid components generated from different metabolic branches played different roles in tea leaves. Furthermore, the intracellular localization of flavonoids and the expression pattern of genes involved in secondary metabolic pathways indicate a potential photoprotective function of dihydroxylated flavonoids in light-sensitive tea leaves. Our results suggest that reactive oxygen species (ROS) scavenging and the antioxidation effects of flavonoids help chlorotic tea plants survive under high light stress, providing new evidence to clarify the functional roles of flavonoids, which accumulate to high levels in tea plants. Moreover, flavonoids with ortho-dihydroxylated B-rings played a greater role in photo-protection to improve the acclimatization of tea plants.

Integrated network analysis and effective tools in plant systems biology

PubMed Central

Fukushima, Atsushi; Kanaya, Shigehiko; Nishida, Kozo

2014-01-01

One of the ultimate goals in plant systems biology is to elucidate the genotype-phenotype relationship in plant cellular systems. Integrated network analysis that combines omics data with mathematical models has received particular attention. Here we focus on the latest cutting-edge computational advances that facilitate their combination. We highlight (1) network visualization tools, (2) pathway analyses, (3) genome-scale metabolic reconstruction, and (4) the integration of high-throughput experimental data and mathematical models. Multi-omics data that contain the genome, transcriptome, proteome, and metabolome and mathematical models are expected to integrate and expand our knowledge of complex plant metabolisms. PMID:25408696

A Vegetal Biopolymer-Based Biostimulant Promoted Root Growth in Melon While Triggering Brassinosteroids and Stress-Related Compounds

PubMed Central

Lucini, Luigi; Rouphael, Youssef; Cardarelli, Mariateresa; Bonini, Paolo; Baffi, Claudio; Colla, Giuseppe

2018-01-01

Plant biostimulants are receiving great interest for boosting root growth during the first phenological stages of vegetable crops. The present study aimed at elucidating the morphological, physiological, and metabolomic changes occurring in greenhouse melon treated with the biopolymer-based biostimulant Quik-link, containing lateral root promoting peptides, and lignosulphonates. The vegetal-based biopolymer was applied at five rates (0, 0.06, 0.12, 0.24, or 0.48 mL plant-1) as substrate drench. The application of biopolymer-based biostimulant at 0.12 and 0.24 mL plant-1 enhanced dry weight of melon leaves and total biomass by 30.5 and 27.7%, respectively, compared to biopolymer applications at 0.06 mL plant-1 and untreated plants. The root dry biomass, total root length, and surface in biostimulant-treated plants were significantly higher at 0.24 mL plant-1 and to a lesser extent at 0.12 and 0.48 mL plant-1, in comparison to 0.06 mL plant-1 and untreated melon plants. A convoluted biochemical response to the biostimulant treatment was highlighted through UHPLC/QTOF-MS metabolomics, in which brassinosteroids and their interaction with other hormones appeared to play a pivotal role. Root metabolic profile was more markedly altered than leaves, following application of the biopolymer-based biostimulant. Brassinosteroids triggered in roots could have been involved in changes of root development observed after biostimulant application. These hormones, once transported to shoots, could have caused an hormonal imbalance. Indeed, the involvement of abscisic acid, cytokinins, and gibberellin related compounds was observed in leaves following root application of the biopolymer-based biostimulant. Nonetheless, the treatment triggered an accumulation of several metabolites involved in defense mechanisms against biotic and abiotic stresses, such as flavonoids, carotenoids, and glucosinolates, thus potentially improving resistance toward plant stresses. PMID:29692795

Data Mining Methods for Omics and Knowledge of Crude Medicinal Plants toward Big Data Biology

PubMed Central

Afendi, Farit M.; Ono, Naoaki; Nakamura, Yukiko; Nakamura, Kensuke; Darusman, Latifah K.; Kibinge, Nelson; Morita, Aki Hirai; Tanaka, Ken; Horai, Hisayuki; Altaf-Ul-Amin, Md.; Kanaya, Shigehiko

2013-01-01

Molecular biological data has rapidly increased with the recent progress of the Omics fields, e.g., genomics, transcriptomics, proteomics and metabolomics that necessitates the development of databases and methods for efficient storage, retrieval, integration and analysis of massive data. The present study reviews the usage of KNApSAcK Family DB in metabolomics and related area, discusses several statistical methods for handling multivariate data and shows their application on Indonesian blended herbal medicines (Jamu) as a case study. Exploration using Biplot reveals many plants are rarely utilized while some plants are highly utilized toward specific efficacy. Furthermore, the ingredients of Jamu formulas are modeled using Partial Least Squares Discriminant Analysis (PLS-DA) in order to predict their efficacy. The plants used in each Jamu medicine served as the predictors, whereas the efficacy of each Jamu provided the responses. This model produces 71.6% correct classification in predicting efficacy. Permutation test then is used to determine plants that serve as main ingredients in Jamu formula by evaluating the significance of the PLS-DA coefficients. Next, in order to explain the role of plants that serve as main ingredients in Jamu medicines, information of pharmacological activity of the plants is added to the predictor block. Then N-PLS-DA model, multiway version of PLS-DA, is utilized to handle the three-dimensional array of the predictor block. The resulting N-PLS-DA model reveals that the effects of some pharmacological activities are specific for certain efficacy and the other activities are diverse toward many efficacies. Mathematical modeling introduced in the present study can be utilized in global analysis of big data targeting to reveal the underlying biology. PMID:24688691

Robust volcano plot: identification of differential metabolites in the presence of outliers.

PubMed

Kumar, Nishith; Hoque, Md Aminul; Sugimoto, Masahiro

2018-04-11

The identification of differential metabolites in metabolomics is still a big challenge and plays a prominent role in metabolomics data analyses. Metabolomics datasets often contain outliers because of analytical, experimental, and biological ambiguity, but the currently available differential metabolite identification techniques are sensitive to outliers. We propose a kernel weight based outlier-robust volcano plot for identifying differential metabolites from noisy metabolomics datasets. Two numerical experiments are used to evaluate the performance of the proposed technique against nine existing techniques, including the t-test and the Kruskal-Wallis test. Artificially generated data with outliers reveal that the proposed method results in a lower misclassification error rate and a greater area under the receiver operating characteristic curve compared with existing methods. An experimentally measured breast cancer dataset to which outliers were artificially added reveals that our proposed method produces only two non-overlapping differential metabolites whereas the other nine methods produced between seven and 57 non-overlapping differential metabolites. Our data analyses show that the performance of the proposed differential metabolite identification technique is better than that of existing methods. Thus, the proposed method can contribute to analysis of metabolomics data with outliers. The R package and user manual of the proposed method are available at https://github.com/nishithkumarpaul/Rvolcano .

Metabolic fingerprinting of Angelica sinensis during growth using UPLC-TOFMS and chemometrics data analysis

PubMed Central

2013-01-01

Background The radix of Angelica sinensis is widely used as a medicinal herbal and metabolomics research of this plant during growth is necessary. Results Principal component analysis of the UPLC-QTOFMS data showed that these 27 samples could be separated into 4 different groups. The chemical markers accounting for these separations were identified from the PCA loadings plot. These markers were further verified by accurate mass tandem mass and retention times of available reference standards. The study has shown that accumulation of secondary metabolites of Angelica sinensis is closely related to the growth periods. Conclusions The UPLC-QTOFMS based metabolomics approach has great potential for analysis of the alterations of secondary metabolites of Angelica sinensis during growth. PMID:23453085

Plant-microbe interactions driven by exometabolite preferences of rhizosphere bacteria

NASA Astrophysics Data System (ADS)

Zhalnina, K.; Louie, K. B.; Mansoori, N.; Hao, Z.; Gao, J.; Cho, H. J.; Karaoz, U.; Loqué, D.; Bowen, B.; Firestone, M.; Brodie, E.; Northen, T.

2016-12-01

It is known that rhizosphere bacteria can impact important processes during plant development. In `return' plants release substantial quantities of soluble C into the soil surrounding its roots, attracting bacteria and other soil organisms. Given the potential beneficial and detrimental consequences of stimulating high densities of organisms adjacent to newly formed root, regulating the chemical composition of exudates would represent a potential means of plant selection for beneficial microorganisms. If exudate resource composition functions to select specific microorganisms, then one would expect that substrate specialization exists within the rhizosphere microbiome. Here we provide evidence that in the rhizosphere of wild oats (Avena barbata), specific metabolites are exuded that are preferentially used by selected bacteria in rhizosphere and this substrate specialization, together with the changing composition of root exudates, drives the observed successional patterns. To investigate the relationship between exudates and rhizosphere bacteria we first analyzed exudate composition of hydroponically grown plants using LC-MS/MS based metabolomics. We then designed a medium to simulate plant exudates and using this medium we examined the substrate preferences of a diversity of rhizosphere bacterial isolates. We then assessed the ability of soil isolates to consume exudate components by LC-MS/MS based metabolomics. These substrate preferences were then related to genomic features and successional patterns of bacteria in the Avena rhizosphere. The major fraction of plant exudates was found to be composed of amino- and carboxylic acids, sugars, nucleosides, quaternary amines and plant hormones. Amino acids, sugars and nucleosides were consumed by all analyzed isolates. However, isolates that were preferentially stimulated by plant growth, revealed substrate utilization preferences towards aromatic organic acids, while those not responding to growing roots did not utilize these compounds under these conditions. This substrate partitioning among rhizosphere bacteria can be suggested as a potential mechanism for how plants influence the structure of their rhizosphere microbiome and provides a key insight into the mechanisms underlying patterns of ecological succession in soil.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sussman, Michael R.

The 2012 Gordon Conference on Plant Molecular Biology will present cutting-edge research on molecular aspects of plant growth and development, with particular emphasis on recent discoveries in molecular mechanisms involved with plant signaling systems. The Conference will feature a wide range of topics in plant molecular biology including hormone receptors and early events in hormone signaling, plant perception of and response to plant pathogen and symbionts, as well as technological and biological aspects of epigenomics particularly as it relates to signaling systems that regulate plant growth and development. Genomic approaches to plant signaling will be emphasized, including genomic profiling technologiesmore » for quantifying various biological subsystems, such as the epigenome, transcriptome, phosphorylome, and metabolome. The meeting will include an important session devoted to answering the question, "What are the biological and technological limits of plant breeding/genetics, and how can they be solved"?« less

Review: Genetically modified plants for the promotion of human health.

PubMed

Yonekura-Sakakibara, Keiko; Saito, Kazuki

2006-12-01

Plants are attractive biological resources because of their ability to produce a huge variety of chemical compounds, and the familiarity of production in even the most rural settings. Genetic engineering gives plants additional characteristics and value for cultivation and post-harvest. Genetically modified (GM) plants of the "first generation" were conferred with traits beneficial to producers, whereas GM plants in subsequent "generations" are intended to provide beneficial traits for consumers. Golden Rice is a promising example of a GM plant in the second generation, and has overcome a number of obstacles for practical use. Furthermore, consumer-acceptable plants with health-promoting properties that are genetically modified using native genes are being developed. The emerging technology of metabolomics will also support the commercial realization of GM plants by providing comprehensive analyzes of plant biochemical components.

Biotechnological approaches to study plant responses to stress.

PubMed

Pérez-Clemente, Rosa M; Vives, Vicente; Zandalinas, Sara I; López-Climent, María F; Muñoz, Valeria; Gómez-Cadenas, Aurelio

2013-01-01

Multiple biotic and abiotic environmental stress factors affect negatively various aspects of plant growth, development, and crop productivity. Plants, as sessile organisms, have developed, in the course of their evolution, efficient strategies of response to avoid, tolerate, or adapt to different types of stress situations. The diverse stress factors that plants have to face often activate similar cell signaling pathways and cellular responses, such as the production of stress proteins, upregulation of the antioxidant machinery, and accumulation of compatible solutes. Over the last few decades advances in plant physiology, genetics, and molecular biology have greatly improved our understanding of plant responses to abiotic stress conditions. In this paper, recent progresses on systematic analyses of plant responses to stress including genomics, proteomics, metabolomics, and transgenic-based approaches are summarized.

Biotechnological Approaches to Study Plant Responses to Stress

PubMed Central

Pérez-Clemente, Rosa M.; Vives, Vicente; Zandalinas, Sara I.; López-Climent, María F.; Muñoz, Valeria; Gómez-Cadenas, Aurelio

2013-01-01

Multiple biotic and abiotic environmental stress factors affect negatively various aspects of plant growth, development, and crop productivity. Plants, as sessile organisms, have developed, in the course of their evolution, efficient strategies of response to avoid, tolerate, or adapt to different types of stress situations. The diverse stress factors that plants have to face often activate similar cell signaling pathways and cellular responses, such as the production of stress proteins, upregulation of the antioxidant machinery, and accumulation of compatible solutes. Over the last few decades advances in plant physiology, genetics, and molecular biology have greatly improved our understanding of plant responses to abiotic stress conditions. In this paper, recent progresses on systematic analyses of plant responses to stress including genomics, proteomics, metabolomics, and transgenic-based approaches are summarized. PMID:23509757

MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments.

PubMed

Franceschi, Pietro; Mylonas, Roman; Shahaf, Nir; Scholz, Matthias; Arapitsas, Panagiotis; Masuero, Domenico; Weingart, Georg; Carlin, Silvia; Vrhovsek, Urska; Mattivi, Fulvio; Wehrens, Ron

2014-01-01

Due to their sensitivity and speed, mass-spectrometry based analytical technologies are widely used to in metabolomics to characterize biological phenomena. To address issues like metadata organization, quality assessment, data processing, data storage, and, finally, submission to public repositories, bioinformatic pipelines of a non-interactive nature are often employed, complementing the interactive software used for initial inspection and visualization of the data. These pipelines often are created as open-source software allowing the complete and exhaustive documentation of each step, ensuring the reproducibility of the analysis of extensive and often expensive experiments. In this paper, we will review the major steps which constitute such a data processing pipeline, discussing them in the context of an open-source software for untargeted MS-based metabolomics experiments recently developed at our institute. The software has been developed by integrating our metaMS R package with a user-friendly web-based application written in Grails. MetaMS takes care of data pre-processing and annotation, while the interface deals with the creation of the sample lists, the organization of the data storage, and the generation of survey plots for quality assessment. Experimental and biological metadata are stored in the ISA-Tab format making the proposed pipeline fully integrated with the Metabolights framework.

Selenium Biofortification in Fragaria × ananassa: Implications on Strawberry Fruits Quality, Content of Bioactive Health Beneficial Compounds and Metabolomic Profile

PubMed Central

Mimmo, Tanja; Tiziani, Raphael; Valentinuzzi, Fabio; Lucini, Luigi; Nicoletto, Carlo; Sambo, Paolo; Scampicchio, Matteo; Pii, Youry; Cesco, Stefano

2017-01-01

Selenium (Se) is an essential nutrient for humans, due to its antioxidant properties, whereas, to date, its essentiality to plants still remains to be demonstrated. Nevertheless, if added to the cultivation substrate, plants growth resulted enhanced. However, the concentration of Se in agricultural soils is very variable, ranging from 0.01 mg kg-1 up to 10 mg kg-1 in seleniferous areas. Therefore several studies have been performed aimed at bio-fortifying crops with Se and the approaches exploited were mainly based on the application of Se fertilizers. The aim of the present research was to assess the biofortification potential of Se in hydroponically grown strawberry fruits and its effects on qualitative parameters and nutraceutical compounds. The supplementation with Se did not negatively affect the growth and the yield of strawberries, and induced an accumulation of Se in fruits. Furthermore, the metabolomic analyses highlighted an increase in flavonoid and polyphenol compounds, which contributes to the organoleptic features and antioxidant capacity of fruits; in addition, an increase in the fruits sweetness also was detected in biofortified strawberries. In conclusion, based on our observations, strawberry plants seem a good target for Se biofortification, thus allowing the increase in the human intake of this essential micronutrient. PMID:29163609

Comparative analysis of volatile oils in the stems and roots of Ephedra sinica via GC-MS-based plant metabolomics.

PubMed

Lv, Meng-Ying; Sun, Jian-Bo; Wang, Min; Fan, Hong-Yan; Zhang, Zun-Jian; Xu, Feng-Guo

2016-02-01

With a great difference in therapeutic effects of Mahuang (MH, the stems of Ephedra sinica) and Mahuanggen (MHG, the roots of Ephedra sinica), chemical differences between MH and MHG should be investigated. In the present study, gas chromatography-mass spectrometry (GC-MS)-based plant metabolomics was employed to compare volatile oil profiles of MH and MHG. The antioxidant activities of volatile oils from MH and MHG were also compared. 32 differential chemical markers were identified according to the variable importance in the projection (VIP) value of orthogonal partial least squares discriminant analysis (OPLS-DA) and P value of Mann-Whitney test. Among them, chemical markers of tetramethylpyrazine (TMP) and α-terpineol were quantified. Their contents were much higher in most MH samples compared with MHG. The antioxidant assay demonstrated that MH had significantly higher free radical-scavenging activity than MHG. Although MH and MHG derived from the same medicinal plant, there was much difference in their volatile oil profiles. MH samples had significantly higher content of two reported pharmacologically important chemical markers of TMP and α-terpineol, which may account for their different antioxidant activities. Copyright © 2016 China Pharmaceutical University. Published by Elsevier B.V. All rights reserved.

Phosphate stresses affect ionome and metabolome in tea plants.

PubMed

Ding, Zhaotang; Jia, Sisi; Wang, Yu; Xiao, Jun; Zhang, Yinfei

2017-11-01

In order to study the response of tea plants to P stress, we conducted the ionomic and metabolomic analysis by ICP-OES, GC-MS and LC-MS. The results demonstrated that P was antagonistic with S, and was cooperative with Cu, Zn, Mn and Fe under P-deficiency. However, P was antagonistic with Mn, Fe and S, and was cooperative with Cu and Zn under P-excess. Moreover, P-deficiency or excess reduced the syntheses of flavonoids and phosphorylated metabolites. P-deficiency decreased the amount of glutamate and increased the content of glutamine, while P-excess decreased the content of glutamine. Besides, P-deficiency increased three organic acids and decreased three organic acids. P-excess increased the contents of malic acid, oxalic acid, ribonic acid and etc. involved in primary metabolism, but decreased the contents of p-coumaric acid, indoleacrylic acid, related to secondary metabolism. Furthermore, the contents of Mn and Zn were found to be positively related to the amounts of myricetin and quercetin, and the content of Mn to be positively related to the amount of arabinose. The results implied that the P stresses severely disturbed the metabolism of minerals and metabolites in tea plants, which influenced the yield and quality of tea. Copyright © 2017. Published by Elsevier Masson SAS.

Transcription Factor Arabidopsis Activating Factor1 Integrates Carbon Starvation Responses with Trehalose Metabolism1[OPEN

PubMed Central

Garapati, Prashanth; Feil, Regina; Lunn, John Edward; Van Dijck, Patrick; Balazadeh, Salma; Mueller-Roeber, Bernd

2015-01-01

Plants respond to low carbon supply by massive reprogramming of the transcriptome and metabolome. We show here that the carbon starvation-induced NAC (for NO APICAL MERISTEM/ARABIDOPSIS TRANSCRIPTION ACTIVATION FACTOR/CUP-SHAPED COTYLEDON) transcription factor Arabidopsis (Arabidopsis thaliana) Transcription Activation Factor1 (ATAF1) plays an important role in this physiological process. We identified TREHALASE1, the only trehalase-encoding gene in Arabidopsis, as a direct downstream target of ATAF1. Overexpression of ATAF1 activates TREHALASE1 expression and leads to reduced trehalose-6-phosphate levels and a sugar starvation metabolome. In accordance with changes in expression of starch biosynthesis- and breakdown-related genes, starch levels are generally reduced in ATAF1 overexpressors but elevated in ataf1 knockout plants. At the global transcriptome level, genes affected by ATAF1 are broadly associated with energy and carbon starvation responses. Furthermore, transcriptional responses triggered by ATAF1 largely overlap with expression patterns observed in plants starved for carbon or energy supply. Collectively, our data highlight the existence of a positively acting feedforward loop between ATAF1 expression, which is induced by carbon starvation, and the depletion of cellular carbon/energy pools that is triggered by the transcriptional regulation of downstream gene regulatory networks by ATAF1. PMID:26149570

Selenium Biofortification in Fragaria × ananassa: Implications on Strawberry Fruits Quality, Content of Bioactive Health Beneficial Compounds and Metabolomic Profile.

PubMed

Mimmo, Tanja; Tiziani, Raphael; Valentinuzzi, Fabio; Lucini, Luigi; Nicoletto, Carlo; Sambo, Paolo; Scampicchio, Matteo; Pii, Youry; Cesco, Stefano

2017-01-01

Selenium (Se) is an essential nutrient for humans, due to its antioxidant properties, whereas, to date, its essentiality to plants still remains to be demonstrated. Nevertheless, if added to the cultivation substrate, plants growth resulted enhanced. However, the concentration of Se in agricultural soils is very variable, ranging from 0.01 mg kg -1 up to 10 mg kg -1 in seleniferous areas. Therefore several studies have been performed aimed at bio-fortifying crops with Se and the approaches exploited were mainly based on the application of Se fertilizers. The aim of the present research was to assess the biofortification potential of Se in hydroponically grown strawberry fruits and its effects on qualitative parameters and nutraceutical compounds. The supplementation with Se did not negatively affect the growth and the yield of strawberries, and induced an accumulation of Se in fruits. Furthermore, the metabolomic analyses highlighted an increase in flavonoid and polyphenol compounds, which contributes to the organoleptic features and antioxidant capacity of fruits; in addition, an increase in the fruits sweetness also was detected in biofortified strawberries. In conclusion, based on our observations, strawberry plants seem a good target for Se biofortification, thus allowing the increase in the human intake of this essential micronutrient.

Comparative metabolomic analysis highlights the involvement of sugars and glycerol in melatonin-mediated innate immunity against bacterial pathogen in Arabidopsis

PubMed Central

Qian, Yongqiang; Tan, Dun-Xian; Reiter, Russel J.; Shi, Haitao

2015-01-01

Melatonin is an important secondary messenger in plant innate immunity against the bacterial pathogen Pseudomonas syringe pv. tomato (Pst) DC3000 in the salicylic acid (SA)- and nitric oxide (NO)-dependent pathway. However, the metabolic homeostasis in melatonin-mediated innate immunity is unknown. In this study, comparative metabolomic analysis found that the endogenous levels of both soluble sugars (fructose, glucose, melibose, sucrose, maltose, galatose, tagatofuranose and turanose) and glycerol were commonly increased after both melatonin treatment and Pst DC3000 infection in Arabidopsis. Further studies showed that exogenous pre-treatment with fructose, glucose, sucrose, or glycerol increased innate immunity against Pst DC3000 infection in wild type (Col-0) Arabidopsis plants, but largely alleviated their effects on the innate immunity in SA-deficient NahG plants and NO-deficient mutants. This indicated that SA and NO are also essential for sugars and glycerol-mediated disease resistance. Moreover, exogenous fructose, glucose, sucrose and glycerol pre-treatments remarkably increased endogenous NO level, but had no significant effect on the endogenous melatonin level. Taken together, this study highlights the involvement of sugars and glycerol in melatonin-mediated innate immunity against bacterial pathogen in SA and NO-dependent pathway in Arabidopsis. PMID:26508076

The application of rumen simulation technique (RUSITEC) for studying dynamics of the bacterial community and metabolome in rumen fluid and the effects of a challenge with Clostridium perfringens.

PubMed

Wetzels, Stefanie U; Eger, Melanie; Burmester, Marion; Kreienbrock, Lothar; Abdulmawjood, Amir; Pinior, Beate; Wagner, Martin; Breves, Gerhard; Mann, Evelyne

2018-01-01

The rumen simulation technique (RUSITEC) is a well-established semicontinuous in vitro model for investigating ruminal fermentation; however, information on the stability of the ruminal bacterial microbiota and metabolome in the RUSITEC system is rarely available. The availability of high resolution methods, such as high-throughput sequencing and metabolomics improve our knowledge about the rumen microbial ecosystem and its fermentation processes. Thus, we used Illumina MiSeq 16S rRNA amplicon sequencing and a combination of direct injection mass spectrometry with a reverse-phase LC-MS/MS to evaluate the dynamics of the bacterial community and the concentration of several metabolites in a RUSITEC experiment as a function of time and in response to a challenge with a pathogenic Clostridium perfringens (C. perfringens) strain. After four days of equilibration, samples were collected on days 5, 6, 7, 10, 12 and 15 of the steady-state and experimental period. From a total of six fermenters, three non-infected fermenters were used for investigating time-dependent alterations; three fermenters were incubated with C. perfringens and compared with the non-infected vessels at days 10, 12 and 15. Along the time-line, there was no statistically significant change of the overall bacterial community, however, some phylotypes were enriched at certain time points. A decrease in Fibrobacter and Elusimicrobia over time was followed by an increase in Firmicutes and Actinobacteria. In contrast, classical fermentation measurements such as pH, redox potential, NH3-N, short chain fatty acids and the concentrations of metabolites determined by metabolomics (biogenic amines, hexoses and amino acids) remained stable throughout the experiment. In response to C. perfringens addition the concentrations of several amino acids increased. Although the overall bacterial community was not altered here either, some minor changes such as an enrichment of Synergistetes and Bacteroidetes were detectable over time. In conclusion, both, the bacterial community composition and the metabolome in the RUSITEC system were relatively stable during the experiment.

NMR analysis reveals a wealth of metabolites in root-knot nematode resistant roots of Citrullus amarus watermelon plants

USDA-ARS?s Scientific Manuscript database

Citrullus amarus (CA) (previously known as Citrullus lanatus var. citroides) accessions collected in southern Africa are known to have resistance to root-knot nematodes (RKN) and are suitable rootstocks for grafted watermelon. A comparative metabolomics study was performed to identify unique metabol...

Sporobolus stapfianus: Insights into desiccation tolerance in the resurrection grasses from linking transcriptomics to metabolomics

USDA-ARS?s Scientific Manuscript database

Understanding the response of resurrection angiosperms to dehydration and rehydration is critical in order to decipher the mechanistic aspects of how plants cope with the rigors of water loss from their vegetative tissues. We have focused our studies on the C4 resurrection grass, Sprobolus stapfianu...

Impact of overexpression of cytosolic isoform of O-acetylserine sulfhydrylase on soybean nodulation and nodule metabolome

USDA-ARS?s Scientific Manuscript database

Nitrogen-fixing nodules, which are also major sites of sulfur assimilation, contribute significantly to the sulfur needs of the whole soybean plants. Nodules are the predominant sites for cysteine accumulation and the activity of O-acetylserine sulfhydrylase (OASS; also known as O-acetylserine(thio...

Metabolomic analysis to evaluate the effects of drought stress on selected African eggplant accessions

USDA-ARS?s Scientific Manuscript database

Drought stress is one of the main abiotic stresses that affect crops. It leads to biochemical changes that can have adverse effects on plant growth, development and productivity. African eggplants are important vegetable and fruit crops reported to adapt and thrive well under drought stress. The div...

Nuclear magnetic resonance (NMR)-based metabolomics for cancer research.

PubMed

Ranjan, Renuka; Sinha, Neeraj

2018-05-07

Nuclear magnetic resonance (NMR) has emerged as an effective tool in various spheres of biomedical research, amongst which metabolomics is an important method for the study of various types of disease. Metabolomics has proved its stronghold in cancer research by the development of different NMR methods over time for the study of metabolites, thus identifying key players in the aetiology of cancer. A plethora of one-dimensional and two-dimensional NMR experiments (in solids, semi-solids and solution phases) are utilized to obtain metabolic profiles of biofluids, cell extracts and tissue biopsy samples, which can further be subjected to statistical analysis. Any alteration in the assigned metabolite peaks gives an indication of changes in metabolic pathways. These defined changes demonstrate the utility of NMR in the early diagnosis of cancer and provide further measures to combat malignancy and its progression. This review provides a snapshot of the trending NMR techniques and the statistical analysis involved in the metabolomics of diseases, with emphasis on advances in NMR methodology developed for cancer research. Copyright © 2018 John Wiley & Sons, Ltd.

Recommendations for Improving Identification and Quantification in Non-Targeted, GC-MS-Based Metabolomic Profiling of Human Plasma

PubMed Central

Wang, Hanghang; Muehlbauer, Michael J.; O’Neal, Sara K.; Newgard, Christopher B.; Hauser, Elizabeth R.; Shah, Svati H.

2017-01-01

The field of metabolomics as applied to human disease and health is rapidly expanding. In recent efforts of metabolomics research, greater emphasis has been placed on quality control and method validation. In this study, we report an experience with quality control and a practical application of method validation. Specifically, we sought to identify and modify steps in gas chromatography-mass spectrometry (GC-MS)-based, non-targeted metabolomic profiling of human plasma that could influence metabolite identification and quantification. Our experimental design included two studies: (1) a limiting-dilution study, which investigated the effects of dilution on analyte identification and quantification; and (2) a concentration-specific study, which compared the optimal plasma extract volume established in the first study with the volume used in the current institutional protocol. We confirmed that contaminants, concentration, repeatability and intermediate precision are major factors influencing metabolite identification and quantification. In addition, we established methods for improved metabolite identification and quantification, which were summarized to provide recommendations for experimental design of GC-MS-based non-targeted profiling of human plasma. PMID:28841195

Shotgun metabolomic approach based on mass spectrometry for hepatic mitochondria of mice under arsenic exposure.

PubMed

García-Sevillano, M A; García-Barrera, T; Navarro, F; Montero-Lobato, Z; Gómez-Ariza, J L

2015-04-01

Mass spectrometry (MS)-based toxicometabolomics requires analytical approaches for obtaining unbiased metabolic profiles. The present work explores the general application of direct infusion MS using a high mass resolution analyzer (a hybrid systems triple quadrupole-time-of-flight) and a complementary gas chromatography-MS analysis to mitochondria extracts from mouse hepatic cells, emphasizing on mitochondria isolation from hepatic cells with a commercial kit, sample treatment after cell lysis, comprehensive metabolomic analysis and pattern recognition from metabolic profiles. Finally, the metabolomic platform was successfully checked on a case-study based on the exposure experiment of mice Mus musculus to inorganic arsenic during 12 days. Endogenous metabolites alterations were recognized by partial least squares-discriminant analysis. Subsequently, metabolites were identified by combining MS/MS analysis and metabolomics databases. This work reports for the first time the effects of As-exposure on hepatic mitochondria metabolic pathways based on MS, and reveals disturbances in Krebs cycle, β-oxidation pathway, amino acids degradation and perturbations in creatine levels. This non-target analysis provides extensive metabolic information from mitochondrial organelle, which could be applied to toxicology, pharmacology and clinical studies.

Proteomic and metabolomic analyses of soybean root tips under flooding stress.

PubMed

Komatsu, Setsuko; Nakamura, Takuji; Sugimoto, Yurie; Sakamoto, Kazunori

2014-01-01

Flooding is one of the serious problems for soybean plants because it inhibits growth. Proteomic and metabolomic techniques were used to determine whether proteins and metabolites are altered in the root tips of soybeans under flooding stress. Two-day-old soybean plants were flooded for 2 days, and proteins and metabolites were extracted from root tips. Flooding-responsive proteins were identified using two-dimensional- or SDS-polyacrylamide gel electrophoresis- based proteomics techniques. Using both techniques, 172 proteins increased and 105 proteins decreased in abundance in the root tips of flood-stressed soybean. The abundance of methionine synthase, heat shock cognate protein, urease, and phosphoenol pyruvate carboxylase was significantly increased by flooding stress. Furthermore, 73 flooding-responsive metabolites were identified using capillary electrophoresis-mass spectrometry. The levels of gamma-aminobutyric acid, glycine, NADH2, and phosphoenol pyruvate were increased by flooding stress. Taken together, these results suggest that synthesis of phosphoenol pyruvate by way of oxaloacetate produced in the tricarboxylic acid cycle is activated in soybean root tips in response to flooding stress, and that flooding stress also leads to modulation of the urea cycle in the root tips.

Integrated Proteomics and Metabolomics Suggests Symbiotic Metabolism and Multimodal Regulation in a Fungal-Endobacterial System: Symbiotic Metabolism and Multimodal Regulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Zhou; Yao, Qiuming; Dearth, Stephen P.

Many plant-associated fungi host endosymbiotic endobacteria with reduced genomes. While endobacteria play important roles in these tri-partite plant-fungal-endobacterial systems, the active physiology of fungal endobacteria has not been characterized extensively by systems biology approaches. Here in this paper, we use integrated proteomics and metabolomics to characterize the relationship between the endobacterium Mycoavidus sp. and the root-associated fungus Mortierella elongata. In nitrogen-poor media, M. elongata had decreased growth but hosted a large and growing endobacterial population. The active endobacterium likely extracted malate from the fungal host as the primary carbon substrate for energy production and biosynthesis of phospho-sugars, nucleobases, peptidoglycan, andmore » some amino acids. The endobacterium obtained nitrogen by importing a variety of nitrogen-containing compounds. Further, nitrogen limitation significantly perturbed the carbon and nitrogen flows in the fungal metabolic network. M. elongata regulated many pathways by concordant changes on enzyme abundances, post-translational modifications, reactant concentrations, and allosteric effectors. Lastly, such multimodal regulations may be a general mechanism for metabolic modulation.« less

Detecting early signs of heat and drought stress in Phoenix dactylifera (date palm)

PubMed Central

Safronov, Omid; Kreuzwieser, Jürgen; Haberer, Georg; Alyousif, Mohamed S.; Schulze, Waltraud; Al-Harbi, Naif; Arab, Leila; Ache, Peter; Stempfl, Thomas; Kruse, Joerg; Mayer, Klaus X.; Hedrich, Rainer; Rennenberg, Heinz

2017-01-01

Plants adapt to the environment by either long-term genome evolution or by acclimatization processes where the cellular processes and metabolism of the plant are adjusted within the existing potential in the genome. Here we studied the adaptation strategies in date palm, Phoenix dactylifera, under mild heat, drought and combined heat and drought by transcriptomic and metabolomic profiling. In transcriptomics data, combined heat and drought resembled heat response, whereas in metabolomics data it was more similar to drought. In both conditions, soluble carbohydrates, such as fucose, and glucose derivatives, were increased, suggesting a switch to carbohydrate metabolism and cell wall biogenesis. This result is consistent with the evidence from transcriptomics and cis-motif analysis. In addition, transcriptomics data showed transcriptional activation of genes related to reactive oxygen species in all three conditions (drought, heat, and combined heat and drought), suggesting increased activity of enzymatic antioxidant systems in cytosol, chloroplast and peroxisome. Finally, the genes that were differentially expressed in heat and combined heat and drought stresses were significantly enriched for circadian and diurnal rhythm motifs, suggesting new stress avoidance strategies. PMID:28570677

Integrated Proteomics and Metabolomics Suggests Symbiotic Metabolism and Multimodal Regulation in a Fungal-Endobacterial System: Symbiotic Metabolism and Multimodal Regulation

DOE PAGES

Li, Zhou; Yao, Qiuming; Dearth, Stephen P.; ...

2016-11-21

Many plant-associated fungi host endosymbiotic endobacteria with reduced genomes. While endobacteria play important roles in these tri-partite plant-fungal-endobacterial systems, the active physiology of fungal endobacteria has not been characterized extensively by systems biology approaches. Here in this paper, we use integrated proteomics and metabolomics to characterize the relationship between the endobacterium Mycoavidus sp. and the root-associated fungus Mortierella elongata. In nitrogen-poor media, M. elongata had decreased growth but hosted a large and growing endobacterial population. The active endobacterium likely extracted malate from the fungal host as the primary carbon substrate for energy production and biosynthesis of phospho-sugars, nucleobases, peptidoglycan, andmore » some amino acids. The endobacterium obtained nitrogen by importing a variety of nitrogen-containing compounds. Further, nitrogen limitation significantly perturbed the carbon and nitrogen flows in the fungal metabolic network. M. elongata regulated many pathways by concordant changes on enzyme abundances, post-translational modifications, reactant concentrations, and allosteric effectors. Lastly, such multimodal regulations may be a general mechanism for metabolic modulation.« less

Integrated proteomics and metabolomics suggests symbiotic metabolism and multimodal regulation in a fungal-endobacterial system.

PubMed

Li, Zhou; Yao, Qiuming; Dearth, Stephen P; Entler, Matthew R; Castro Gonzalez, Hector F; Uehling, Jessie K; Vilgalys, Rytas J; Hurst, Gregory B; Campagna, Shawn R; Labbé, Jessy L; Pan, Chongle

2017-03-01

Many plant-associated fungi host endosymbiotic endobacteria with reduced genomes. While endobacteria play important roles in these tri-partite plant-fungal-endobacterial systems, the active physiology of fungal endobacteria has not been characterized extensively by systems biology approaches. Here, we use integrated proteomics and metabolomics to characterize the relationship between the endobacterium Mycoavidus sp. and the root-associated fungus Mortierella elongata. In nitrogen-poor media, M. elongata had decreased growth but hosted a large and growing endobacterial population. The active endobacterium likely extracted malate from the fungal host as the primary carbon substrate for energy production and biosynthesis of phospho-sugars, nucleobases, peptidoglycan and some amino acids. The endobacterium obtained nitrogen by importing a variety of nitrogen-containing compounds. Further, nitrogen limitation significantly perturbed the carbon and nitrogen flows in the fungal metabolic network. M. elongata regulated many pathways by concordant changes on enzyme abundances, post-translational modifications, reactant concentrations and allosteric effectors. Such multimodal regulations may be a general mechanism for metabolic modulation. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

Comparative metabolomics in vegans and omnivores reveal constraints on diet-dependent gut microbiota metabolite production

PubMed Central

Wu, Gary D; Compher, Charlene; Chen, Eric Z; Smith, Sarah A; Shah, Rachana D; Bittinger, Kyle; Chehoud, Christel; Albenberg, Lindsey G; Nessel, Lisa; Gilroy, Erin; Star, Julie; Weljie, Aalim M; Flint, Harry J; Metz, David C; Bennett, Michael J; Li, Hongzhe; Bushman, Frederic D; Lewis, James D

2015-01-01

Objective The consumption of an agrarian diet is associated with a reduced risk for many diseases associated with a ‘Westernised’ lifestyle. Studies suggest that diet affects the gut microbiota, which subsequently influences the metabolome, thereby connecting diet, microbiota and health. However, the degree to which diet influences the composition of the gut microbiota is controversial. Murine models and studies comparing the gut microbiota in humans residing in agrarian versus Western societies suggest that the influence is large. To separate global environmental influences from dietary influences, we characterised the gut microbiota and the host metabolome of individuals consuming an agrarian diet in Western society. Design and results Using 16S rRNA-tagged sequencing as well as plasma and urinary metabolomic platforms, we compared measures of dietary intake, gut microbiota composition and the plasma metabolome between healthy human vegans and omnivores, sampled in an urban USA environment. Plasma metabolome of vegans differed markedly from omnivores but the gut microbiota was surprisingly similar. Unlike prior studies of individuals living in agrarian societies, higher consumption of fermentable substrate in vegans was not associated with higher levels of faecal short chain fatty acids, a finding confirmed in a 10-day controlled feeding experiment. Similarly, the proportion of vegans capable of producing equol, a soy-based gut microbiota metabolite, was less than that was reported in Asian societies despite the high consumption of soy-based products. Conclusions Evidently, residence in globally distinct societies helps determine the composition of the gut microbiota that, in turn, influences the production of diet-dependent gut microbial metabolites. PMID:25431456

Untargeted metabolomics studies employing NMR and LC-MS reveal metabolic coupling between Nanoarcheum equitans and its archaeal host Ignicoccus hospitalis.

PubMed

Hamerly, Timothy; Tripet, Brian P; Tigges, Michelle; Giannone, Richard J; Wurch, Louie; Hettich, Robert L; Podar, Mircea; Copié, Valerie; Bothner, Brian

2015-08-01

Interspecies interactions are the basis of microbial community formation and infectious diseases. Systems biology enables the construction of complex models describing such interactions, leading to a better understanding of disease states and communities. However, before interactions between complex organisms can be understood, metabolic and energetic implications of simpler real-world host-microbe systems must be worked out. To this effect, untargeted metabolomics experiments were conducted and integrated with proteomics data to characterize key molecular-level interactions between two hyperthermophilic microbial species, both of which have reduced genomes. Metabolic changes and transfer of metabolites between the archaea Ignicoccus hospitalis and Nanoarcheum equitans were investigated using integrated LC-MS and NMR metabolomics. The study of such a system is challenging, as no genetic tools are available, growth in the laboratory is challenging, and mechanisms by which they interact are unknown. Together with information about relative enzyme levels obtained from shotgun proteomics, the metabolomics data provided useful insights into metabolic pathways and cellular networks of I. hospitalis that are impacted by the presence of N. equitans , including arginine, isoleucine, and CTP biosynthesis. On the organismal level, the data indicate that N. equitans exploits metabolites generated by I. hospitalis to satisfy its own metabolic needs. This finding is based on N. equitans 's consumption of a significant fraction of the metabolite pool in I. hospitalis that cannot solely be attributed to increased biomass production for N. equitans . Combining LC-MS and NMR metabolomics datasets improved coverage of the metabolome and enhanced the identification and quantitation of cellular metabolites.

Untargeted metabolomics studies employing NMR and LC-MS reveal metabolic coupling between Nanoarcheum equitans and its archaeal host Ignicoccus hospitalis

PubMed Central

Hamerly, Timothy; Tripet, Brian P.; Tigges, Michelle; Giannone, Richard J.; Wurch, Louie; Hettich, Robert L.; Podar, Mircea; Copié, Valerie; Bothner, Brian

2014-01-01

Interspecies interactions are the basis of microbial community formation and infectious diseases. Systems biology enables the construction of complex models describing such interactions, leading to a better understanding of disease states and communities. However, before interactions between complex organisms can be understood, metabolic and energetic implications of simpler real-world host-microbe systems must be worked out. To this effect, untargeted metabolomics experiments were conducted and integrated with proteomics data to characterize key molecular-level interactions between two hyperthermophilic microbial species, both of which have reduced genomes. Metabolic changes and transfer of metabolites between the archaea Ignicoccus hospitalis and Nanoarcheum equitans were investigated using integrated LC-MS and NMR metabolomics. The study of such a system is challenging, as no genetic tools are available, growth in the laboratory is challenging, and mechanisms by which they interact are unknown. Together with information about relative enzyme levels obtained from shotgun proteomics, the metabolomics data provided useful insights into metabolic pathways and cellular networks of I. hospitalis that are impacted by the presence of N. equitans, including arginine, isoleucine, and CTP biosynthesis. On the organismal level, the data indicate that N. equitans exploits metabolites generated by I. hospitalis to satisfy its own metabolic needs. This finding is based on N. equitans’s consumption of a significant fraction of the metabolite pool in I. hospitalis that cannot solely be attributed to increased biomass production for N. equitans. Combining LC-MS and NMR metabolomics datasets improved coverage of the metabolome and enhanced the identification and quantitation of cellular metabolites. PMID:26273237

A systems-wide comparison of red rice (Oryza longistaminata) tissues identifies rhizome specific genes and proteins that are targets for cultivated rice improvement

PubMed Central

2014-01-01

Background The rhizome, the original stem of land plants, enables species to invade new territory and is a critical component of perenniality, especially in grasses. Red rice (Oryza longistaminata) is a perennial wild rice species with many valuable traits that could be used to improve cultivated rice cultivars, including rhizomatousness, disease resistance and drought tolerance. Despite these features, little is known about the molecular mechanisms that contribute to rhizome growth, development and function in this plant. Results We used an integrated approach to compare the transcriptome, proteome and metabolome of the rhizome to other tissues of red rice. 116 Gb of transcriptome sequence was obtained from various tissues and used to identify rhizome-specific and preferentially expressed genes, including transcription factors and hormone metabolism and stress response-related genes. Proteomics and metabolomics approaches identified 41 proteins and more than 100 primary metabolites and plant hormones with rhizome preferential accumulation. Of particular interest was the identification of a large number of gene transcripts from Magnaportha oryzae, the fungus that causes rice blast disease in cultivated rice, even though the red rice plants showed no sign of disease. Conclusions A significant set of genes, proteins and metabolites appear to be specifically or preferentially expressed in the rhizome of O. longistaminata. The presence of M. oryzae gene transcripts at a high level in apparently healthy plants suggests that red rice is resistant to this pathogen, and may be able to provide genes to cultivated rice that will enable resistance to rice blast disease. PMID:24521476

Illuminating a plant’s tissue-specific metabolic diversity using computational metabolomics and information theory

PubMed Central

Li, Dapeng; Heiling, Sven; Baldwin, Ian T.

2016-01-01

Secondary metabolite diversity is considered an important fitness determinant for plants’ biotic and abiotic interactions in nature. This diversity can be examined in two dimensions. The first one considers metabolite diversity across plant species. A second way of looking at this diversity is by considering the tissue-specific localization of pathways underlying secondary metabolism within a plant. Although these cross-tissue metabolite variations are increasingly regarded as important readouts of tissue-level gene function and regulatory processes, they have rarely been comprehensively explored by nontargeted metabolomics. As such, important questions have remained superficially addressed. For instance, which tissues exhibit prevalent signatures of metabolic specialization? Reciprocally, which metabolites contribute most to this tissue specialization in contrast to those metabolites exhibiting housekeeping characteristics? Here, we explore tissue-level metabolic specialization in Nicotiana attenuata, an ecological model with rich secondary metabolism, by combining tissue-wide nontargeted mass spectral data acquisition, information theory analysis, and tandem MS (MS/MS) molecular networks. This analysis was conducted for two different methanolic extracts of 14 tissues and deconvoluted 895 nonredundant MS/MS spectra. Using information theory analysis, anthers were found to harbor the most specialized metabolome, and most unique metabolites of anthers and other tissues were annotated through MS/MS molecular networks. Tissue–metabolite association maps were used to predict tissue-specific gene functions. Predictions for the function of two UDP-glycosyltransferases in flavonoid metabolism were confirmed by virus-induced gene silencing. The present workflow allows biologists to amortize the vast amount of data produced by modern MS instrumentation in their quest to understand gene function. PMID:27821729

Stable Isotope-Assisted Evaluation of Different Extraction Solvents for Untargeted Metabolomics of Plants

PubMed Central

Doppler, Maria; Kluger, Bernhard; Bueschl, Christoph; Schneider, Christina; Krska, Rudolf; Delcambre, Sylvie; Hiller, Karsten; Lemmens, Marc; Schuhmacher, Rainer

2016-01-01

The evaluation of extraction protocols for untargeted metabolomics approaches is still difficult. We have applied a novel stable isotope-assisted workflow for untargeted LC-HRMS-based plant metabolomics , which allows for the first time every detected feature to be considered for method evaluation. The efficiency and complementarity of commonly used extraction solvents, namely 1 + 3 (v/v) mixtures of water and selected organic solvents (methanol, acetonitrile or methanol/acetonitrile 1 + 1 (v/v)), with and without the addition of 0.1% (v/v) formic acid were compared. Four different wheat organs were sampled, extracted and analysed by LC-HRMS. Data evaluation was performed with the in-house-developed MetExtract II software and R. With all tested solvents a total of 871 metabolites were extracted in ear, 785 in stem, 733 in leaf and 517 in root samples, respectively. Between 48% (stem) and 57% (ear) of the metabolites detected in a particular organ were found with all extraction mixtures, and 127 of 996 metabolites were consistently shared between all extraction agent/organ combinations. In aqueous methanol, acidification with formic acid led to pronounced pH dependency regarding the precision of metabolite abundance and the number of detectable metabolites, whereas extracts of acetonitrile-containing mixtures were less affected. Moreover, methanol and acetonitrile have been found to be complementary with respect to extraction efficiency. Interestingly, the beneficial properties of both solvents can be combined by the use of a water-methanol-acetonitrile mixture for global metabolite extraction instead of aqueous methanol or aqueous acetonitrile alone. PMID:27367667

From common to rare Zingiberaceae plants - A metabolomics study using GC-MS.

PubMed

Barbosa, Gina B; Jayasinghe, Nirupama S; Natera, Siria H A; Inutan, Ellen D; Peteros, Nonita P; Roessner, Ute

2017-08-01

Zingiberaceae plants, commonly known as gingers, have been popular for their medicinal and culinary uses since time immemorial. In spite of their numerous health-promoting applications, many Zingiberaceae plants still receive no scientific attention. Moreover, existing reports mostly focused only on the Zingiberaceae rhizomes. Here, untargeted metabolite profiling using Gas Chromatography - Mass Spectrometry (GC-MS) was used to compare the metabolic composition of leaves and rhizomes of the more common gingers, Zingiber officinale Rosc. (ZO), Curcuma longa L. (CL), and Etlingera elatior (Jack) R.M. Smith (EE), and the rare gingers, Amomum muricarpum Elmer (AM), Etlingera philippinensis (Ridl.) R.M. Smith (EP), and Hornstedtia conoidea Ridl. (HC). Principal component analysis (PCA) demonstrated that different species show substantial chemical differentiation and revealed potential markers among the different Zingiberaceae plants. Interestingly, the leaves of AM, CL, EE, EP, and HC had significantly higher levels of chlorogenic acid than ZO. Moreover, rhizomes of EP and HC were found to contain significantly higher levels of amino acids than ZO. Sugars and organic acids were generally less abundant in ZO leaves and rhizomes than in the other gingers. The leaves of EP and rhizomes of AM were found most similar to the leaves and rhizomes of common gingers, respectively. Results of this study provide significant baseline information on assessing the possible usage of the leaves of common gingers and further propagation and exploration of EP and AM. This study, being the first metabolomics report on rare plants such as AM, EP and HC, affirms the usefulness of untargeted metabolite profiling in exploring under-investigated plants. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cultivar Diversity of Grape Skin Polyphenol Composition and Changes in Response to Drought Investigated by LC-MS Based Metabolomics

PubMed Central

Pinasseau, Lucie; Vallverdú-Queralt, Anna; Verbaere, Arnaud; Roques, Maryline; Meudec, Emmanuelle; Le Cunff, Loïc; Péros, Jean-Pierre; Ageorges, Agnès; Sommerer, Nicolas; Boulet, Jean-Claude; Terrier, Nancy; Cheynier, Véronique

2017-01-01

Phenolic compounds represent a large family of plant secondary metabolites, essential for the quality of grape and wine and playing a major role in plant defense against biotic and abiotic stresses. Phenolic composition is genetically driven and greatly affected by environmental factors, including water stress. A major challenge for breeding of grapevine cultivars adapted to climate change and with high potential for wine-making is to dissect the complex plant metabolic response involved in adaptation mechanisms. A targeted metabolomics approach based on ultra high-performance liquid chromatography coupled to triple quadrupole mass spectrometry (UHPLC-QqQ-MS) analysis in the Multiple Reaction Monitoring (MRM) mode has been developed for high throughput profiling of the phenolic composition of grape skins. This method enables rapid, selective, and sensitive quantification of 96 phenolic compounds (anthocyanins, phenolic acids, stilbenoids, flavonols, dihydroflavonols, flavan-3-ol monomers, and oligomers…), and of the constitutive units of proanthocyanidins (i.e., condensed tannins), giving access to detailed polyphenol composition. It was applied on the skins of mature grape berries from a core-collection of 279 Vitis vinifera cultivars grown with or without watering to assess the genetic variation for polyphenol composition and its modulation by irrigation, in two successive vintages (2014–2015). Distribution of berry weights and δ13C values showed that non irrigated vines were subjected to a marked water stress in 2014 and to a very limited one in 2015. Metabolomics analysis of the polyphenol composition and chemometrics analysis of this data demonstrated an influence of water stress on the biosynthesis of different polyphenol classes and cultivar differences in metabolic response to water deficit. Correlation networks gave insight on the relationships between the different polyphenol metabolites and related biosynthetic pathways. They also established patterns of polyphenol response to drought, with different molecular families affected either positively or negatively in the different cultivars, with potential impact on grape and wine quality. PMID:29163566

Effect on transcriptome and metabolome of stacked transgenic maize containing insecticidal cry and glyphosate tolerance epsps genes.

PubMed

Wang, Xu-Jing; Zhang, Xin; Yang, Jiang-Tao; Wang, Zhi-Xing

2018-03-01

Gene stacking is a developing trend in agricultural biotechnology. Unintended effects in stacked transgenic plants are safety issues considered by the public and researchers. Omics techniques provide useful tools to assess unintended effects. In this paper, stacked transgenic maize 12-5×IE034 that contained insecticidal cry and glyphosate tolerance G10-epsps genes was obtained by crossing of transgenic maize varieties 12-5 and IE034. Transcriptome and metabolome analyses were performed for different maize varieties, including 12-5×IE034, 12-5, IE034, and conventional varieties collected from different provinces in China. The transcriptome results were as follows. The nine maize varieties had obvious differences in gene expression. There were 3561-5538 differentially expressed genes between 12-5×IE034 and its parents and transgenic receptor, which were far fewer than the number of differentially expressed genes in different traditional maize varieties. Cluster analysis indicated that there were close relationships between 12-5×IE034 and its parents. The metabolome results were as follows. For the nine detected maize varieties, the number of different metabolites ranged from 0 to 240. Compared with its parents, 12-5 and IE034, the hybrid variety 12-5×IE034 had 15 and 112 different metabolites, respectively. Hierarchical cluster analysis with Pearson's correlation analysis showed that the differences between 12-5×IE034 and its parents were fewer than those between other maize varieties. Shikimate pathway-related genes and metabolites analysis results showed that the effects of hybrid stacking are less than those from transformation and differing genotypes. Thus, the differences due to breeding stack were fewer than those due to natural variation among maize varieties. This paper provides scientific data for assessing unintended effects in stacked transgenic plants. © 2018 The Authors The Plant Journal © 2018 John Wiley & Sons Ltd.

Advances in Genetical Genomics of Plants

PubMed Central

Joosen, R.V.L.; Ligterink, W.; Hilhorst, H.W.M.; Keurentjes, J.J.B.

2009-01-01

Natural variation provides a valuable resource to study the genetic regulation of quantitative traits. In quantitative trait locus (QTL) analyses this variation, captured in segregating mapping populations, is used to identify the genomic regions affecting these traits. The identification of the causal genes underlying QTLs is a major challenge for which the detection of gene expression differences is of major importance. By combining genetics with large scale expression profiling (i.e. genetical genomics), resulting in expression QTLs (eQTLs), great progress can be made in connecting phenotypic variation to genotypic diversity. In this review we discuss examples from human, mouse, Drosophila, yeast and plant research to illustrate the advances in genetical genomics, with a focus on understanding the regulatory mechanisms underlying natural variation. With their tolerance to inbreeding, short generation time and ease to generate large families, plants are ideal subjects to test new concepts in genetics. The comprehensive resources which are available for Arabidopsis make it a favorite model plant but genetical genomics also found its way to important crop species like rice, barley and wheat. We discuss eQTL profiling with respect to cis and trans regulation and show how combined studies with other ‘omics’ technologies, such as metabolomics and proteomics may further augment current information on transcriptional, translational and metabolomic signaling pathways and enable reconstruction of detailed regulatory networks. The fast developments in the ‘omics’ area will offer great potential for genetical genomics to elucidate the genotype-phenotype relationships for both fundamental and applied research. PMID:20514216

Untargeted metabolomics analysis reveals dynamic changes in azelaic acid- and salicylic acid derivatives in LPS-treated Nicotiana tabacum cells.

PubMed

Mhlongo, M I; Tugizimana, F; Piater, L A; Steenkamp, P A; Madala, N E; Dubery, I A

2017-01-22

To counteract biotic stress factors, plants employ multilayered defense mechanisms responsive to pathogen-derived elicitor molecules, and regulated by different phytohormones and signaling molecules. Here, lipopolysaccharide (LPS), a microbe-associated molecular pattern (MAMP) molecule, was used to induce defense responses in Nicotiana tabacum cell suspensions. Intracellular metabolites were extracted with methanol and analyzed using a liquid chromatography-mass spectrometry (UHPLC-qTOF-MS/MS) platform. The generated data were processed and examined with multivariate and univariate statistical tools. The results show time-dependent dynamic changes and accumulation of glycosylated signaling molecules, specifically those of azelaic acid, salicylic acid and methyl-salicylate as contributors to the altered metabolomic state in LPS-treated cells. Copyright © 2016 Elsevier Inc. All rights reserved.

Mass spectrometric based approaches in urine metabolomics and biomarker discovery.

PubMed

Khamis, Mona M; Adamko, Darryl J; El-Aneed, Anas

2017-03-01

Urine metabolomics has recently emerged as a prominent field for the discovery of non-invasive biomarkers that can detect subtle metabolic discrepancies in response to a specific disease or therapeutic intervention. Urine, compared to other biofluids, is characterized by its ease of collection, richness in metabolites and its ability to reflect imbalances of all biochemical pathways within the body. Following urine collection for metabolomic analysis, samples must be immediately frozen to quench any biogenic and/or non-biogenic chemical reactions. According to the aim of the experiment; sample preparation can vary from simple procedures such as filtration to more specific extraction protocols such as liquid-liquid extraction. Due to the lack of comprehensive studies on urine metabolome stability, higher storage temperatures (i.e. 4°C) and repetitive freeze-thaw cycles should be avoided. To date, among all analytical techniques, mass spectrometry (MS) provides the best sensitivity, selectivity and identification capabilities to analyze the majority of the metabolite composition in the urine. Combined with the qualitative and quantitative capabilities of MS, and due to the continuous improvements in its related technologies (i.e. ultra high-performance liquid chromatography [UPLC] and hydrophilic interaction liquid chromatography [HILIC]), liquid chromatography (LC)-MS is unequivocally the most utilized and the most informative analytical tool employed in urine metabolomics. Furthermore, differential isotope tagging techniques has provided a solution to ion suppression from urine matrix thus allowing for quantitative analysis. In addition to LC-MS, other MS-based technologies have been utilized in urine metabolomics. These include direct injection (infusion)-MS, capillary electrophoresis-MS and gas chromatography-MS. In this article, the current progresses of different MS-based techniques in exploring the urine metabolome as well as the recent findings in providing potentially diagnostic urinary biomarkers are discussed. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:115-134, 2017. © 2015 Wiley Periodicals, Inc.

MASTR-MS: a web-based collaborative laboratory information management system (LIMS) for metabolomics.

PubMed

Hunter, Adam; Dayalan, Saravanan; De Souza, David; Power, Brad; Lorrimar, Rodney; Szabo, Tamas; Nguyen, Thu; O'Callaghan, Sean; Hack, Jeremy; Pyke, James; Nahid, Amsha; Barrero, Roberto; Roessner, Ute; Likic, Vladimir; Tull, Dedreia; Bacic, Antony; McConville, Malcolm; Bellgard, Matthew

2017-01-01

An increasing number of research laboratories and core analytical facilities around the world are developing high throughput metabolomic analytical and data processing pipelines that are capable of handling hundreds to thousands of individual samples per year, often over multiple projects, collaborations and sample types. At present, there are no Laboratory Information Management Systems (LIMS) that are specifically tailored for metabolomics laboratories that are capable of tracking samples and associated metadata from the beginning to the end of an experiment, including data processing and archiving, and which are also suitable for use in large institutional core facilities or multi-laboratory consortia as well as single laboratory environments. Here we present MASTR-MS, a downloadable and installable LIMS solution that can be deployed either within a single laboratory or used to link workflows across a multisite network. It comprises a Node Management System that can be used to link and manage projects across one or multiple collaborating laboratories; a User Management System which defines different user groups and privileges of users; a Quote Management System where client quotes are managed; a Project Management System in which metadata is stored and all aspects of project management, including experimental setup, sample tracking and instrument analysis, are defined, and a Data Management System that allows the automatic capture and storage of raw and processed data from the analytical instruments to the LIMS. MASTR-MS is a comprehensive LIMS solution specifically designed for metabolomics. It captures the entire lifecycle of a sample starting from project and experiment design to sample analysis, data capture and storage. It acts as an electronic notebook, facilitating project management within a single laboratory or a multi-node collaborative environment. This software is being developed in close consultation with members of the metabolomics research community. It is freely available under the GNU GPL v3 licence and can be accessed from, https://muccg.github.io/mastr-ms/.

Green systems biology - From single genomes, proteomes and metabolomes to ecosystems research and biotechnology.

PubMed

Weckwerth, Wolfram

2011-12-10

Plants have shaped our human life form from the outset. With the emerging recognition of world population feeding, global climate change and limited energy resources with fossil fuels, the relevance of plant biology and biotechnology is becoming dramatically important. One key issue is to improve plant productivity and abiotic/biotic stress resistance in agriculture due to restricted land area and increasing environmental pressures. Another aspect is the development of CO(2)-neutral plant resources for fiber/biomass and biofuels: a transition from first generation plants like sugar cane, maize and other important nutritional crops to second and third generation energy crops such as Miscanthus and trees for lignocellulose and algae for biomass and feed, hydrogen and lipid production. At the same time we have to conserve and protect natural diversity and species richness as a foundation of our life on earth. Here, biodiversity banks are discussed as a foundation of current and future plant breeding research. Consequently, it can be anticipated that plant biology and ecology will have more indispensable future roles in all socio-economic aspects of our life than ever before. We therefore need an in-depth understanding of the physiology of single plant species for practical applications as well as the translation of this knowledge into complex natural as well as anthropogenic ecosystems. Latest developments in biological and bioanalytical research will lead into a paradigm shift towards trying to understand organisms at a systems level and in their ecosystemic context: (i) shotgun and next-generation genome sequencing, gene reconstruction and annotation, (ii) genome-scale molecular analysis using OMICS technologies and (iii) computer-assisted analysis, modeling and interpretation of biological data. Systems biology combines these molecular data, genetic evolution, environmental cues and species interaction with the understanding, modeling and prediction of active biochemical networks up to whole species populations. This process relies on the development of new technologies for the analysis of molecular data, especially genomics, metabolomics and proteomics data. The ambitious aim of these non-targeted 'omic' technologies is to extend our understanding beyond the analysis of separated parts of the system, in contrast to traditional reductionistic hypothesis-driven approaches. The consequent integration of genotyping, pheno/morphotyping and the analysis of the molecular phenotype using metabolomics, proteomics and transcriptomics will reveal a novel understanding of plant metabolism and its interaction with the environment. The analysis of single model systems - plants, fungi, animals and bacteria - will finally emerge in the analysis of populations of plants and other organisms and their adaptation to the ecological niche. In parallel, this novel understanding of ecophysiology will translate into knowledge-based approaches in crop plant biotechnology and marker- or genome-assisted breeding approaches. In this review the foundations of green systems biology are described and applications in ecosystems research are presented. Knowledge exchange of ecosystems research and green biotechnology merging into green systems biology is anticipated based on the principles of natural variation, biodiversity and the genotype-phenotype environment relationship as the fundamental drivers of ecology and evolution. Copyright © 2011 Elsevier B.V. All rights reserved.

COordination of Standards in MetabOlomicS (COSMOS): facilitating integrated metabolomics data access.

PubMed

Salek, Reza M; Neumann, Steffen; Schober, Daniel; Hummel, Jan; Billiau, Kenny; Kopka, Joachim; Correa, Elon; Reijmers, Theo; Rosato, Antonio; Tenori, Leonardo; Turano, Paola; Marin, Silvia; Deborde, Catherine; Jacob, Daniel; Rolin, Dominique; Dartigues, Benjamin; Conesa, Pablo; Haug, Kenneth; Rocca-Serra, Philippe; O'Hagan, Steve; Hao, Jie; van Vliet, Michael; Sysi-Aho, Marko; Ludwig, Christian; Bouwman, Jildau; Cascante, Marta; Ebbels, Timothy; Griffin, Julian L; Moing, Annick; Nikolski, Macha; Oresic, Matej; Sansone, Susanna-Assunta; Viant, Mark R; Goodacre, Royston; Günther, Ulrich L; Hankemeier, Thomas; Luchinat, Claudio; Walther, Dirk; Steinbeck, Christoph

Metabolomics has become a crucial phenotyping technique in a range of research fields including medicine, the life sciences, biotechnology and the environmental sciences. This necessitates the transfer of experimental information between research groups, as well as potentially to publishers and funders. After the initial efforts of the metabolomics standards initiative, minimum reporting standards were proposed which included the concepts for metabolomics databases. Built by the community, standards and infrastructure for metabolomics are still needed to allow storage, exchange, comparison and re-utilization of metabolomics data. The Framework Programme 7 EU Initiative 'coordination of standards in metabolomics' (COSMOS) is developing a robust data infrastructure and exchange standards for metabolomics data and metadata. This is to support workflows for a broad range of metabolomics applications within the European metabolomics community and the wider metabolomics and biomedical communities' participation. Here we announce our concepts and efforts asking for re-engagement of the metabolomics community, academics and industry, journal publishers, software and hardware vendors, as well as those interested in standardisation worldwide (addressing missing metabolomics ontologies, complex-metadata capturing and XML based open source data exchange format), to join and work towards updating and implementing metabolomics standards.

Expression analysis in response to drought stress in soybean: Shedding light on the regulation of metabolic pathway genes.

PubMed

Guimarães-Dias, Fábia; Neves-Borges, Anna Cristina; Viana, Antonio Americo Barbosa; Mesquita, Rosilene Oliveira; Romano, Eduardo; de Fátima Grossi-de-Sá, Maria; Nepomuceno, Alexandre Lima; Loureiro, Marcelo Ehlers; Alves-Ferreira, Márcio

2012-06-01

Metabolomics analysis of wild type Arabidopsis thaliana plants, under control and drought stress conditions revealed several metabolic pathways that are induced under water deficit. The metabolic response to drought stress is also associated with ABA dependent and independent pathways, allowing a better understanding of the molecular mechanisms in this model plant. Through combining an in silico approach and gene expression analysis by quantitative real-time PCR, the present work aims at identifying genes of soybean metabolic pathways potentially associated with water deficit. Digital expression patterns of Arabidopsis genes, which were selected based on the basis of literature reports, were evaluated under drought stress condition by Genevestigator. Genes that showed strong induction under drought stress were selected and used as bait to identify orthologs in the soybean genome. This allowed us to select 354 genes of putative soybean orthologs of 79 Arabidopsis genes belonging to 38 distinct metabolic pathways. The expression pattern of the selected genes was verified in the subtractive libraries available in the GENOSOJA project. Subsequently, 13 genes from different metabolic pathways were selected for validation by qPCR experiments. The expression of six genes was validated in plants undergoing drought stress in both pot-based and hydroponic cultivation systems. The results suggest that the metabolic response to drought stress is conserved in Arabidopsis and soybean plants.

Metabolic discrimination of sea buckthorn from different Hippophaë species by 1H NMR based metabolomics.

PubMed

Liu, Yue; Fan, Gang; Zhang, Jing; Zhang, Yi; Li, Jingjian; Xiong, Chao; Zhang, Qi; Li, Xiaodong; Lai, Xianrong

2017-05-08

Sea buckthorn (Hippophaë; Elaeagnaceae) berries are widely consumed in traditional folk medicines, nutraceuticals, and as a source of food. The growing demand of sea buckthorn berries and morphological similarity of Hippophaë species leads to confusions, which might cause misidentification of plants used in natural products. Detailed information and comparison of the complete set of metabolites of different Hippophaë species are critical for their objective identification and quality control. Herein, the variation among seven species and seven subspecies of Hippophaë was studied using proton nuclear magnetic resonance ( 1 H NMR) metabolomics combined with multivariate data analysis, and the important metabolites were quantified by quantitative 1 H NMR (qNMR) method. The results showed that different Hippophaë species can be clearly discriminated and the important interspecific discriminators, including organic acids, L-quebrachitol, and carbohydrates were identified. Statistical differences were found among most of the Hippophaë species and subspecies at the content levels of the aforementioned interspecific discriminators via qNMR and one-way analysis of variance (ANOVA) test. These findings demonstrated that 1 H NMR-based metabolomics is an applicable and effective approach for simultaneous metabolic profiling, species differentiation and quality assessment.

Comparative metabolomics of drought acclimation in model and forage legumes.

PubMed

Sanchez, Diego H; Schwabe, Franziska; Erban, Alexander; Udvardi, Michael K; Kopka, Joachim

2012-01-01

Water limitation has become a major concern for agriculture. Such constraints reinforce the urgent need to understand mechanisms by which plants cope with water deprivation. We used a non-targeted metabolomic approach to explore plastic systems responses to non-lethal drought in model and forage legume species of the Lotus genus. In the model legume Lotus. japonicus, increased water stress caused gradual increases of most of the soluble small molecules profiled, reflecting a global and progressive reprogramming of metabolic pathways. The comparative metabolomic approach between Lotus species revealed conserved and unique metabolic responses to drought stress. Importantly, only few drought-responsive metabolites were conserved among all species. Thus we highlight a potential impediment to translational approaches that aim to engineer traits linked to the accumulation of compatible solutes. Finally, a broad comparison of the metabolic changes elicited by drought and salt acclimation revealed partial conservation of these metabolic stress responses within each of the Lotus species, but only few salt- and drought-responsive metabolites were shared between all. The implications of these results are discussed with regard to the current insights into legume water stress physiology. © 2011 Blackwell Publishing Ltd.

Metabolomics study on the hepatoprotective effect of scoparone using ultra-performance liquid chromatography/electrospray ionization quadruple time-of-flight mass spectrometry.

PubMed

Zhang, Aihua; Sun, Hui; Dou, Shengshan; Sun, Wenjun; Wu, Xiuhong; Wang, Ping; Wang, Xijun

2013-01-07

Scoparone is an important constituent of Yinchenhao (Artemisia annua L.), a famous medicinal plant, and displayed bright prospects in the prevention and therapy of liver injury. However, the precise molecular mechanism of hepatoprotective effects has not been comprehensively explored. Here, metabolomics techniques are the comprehensive assessment of endogenous metabolites in a biological system and may provide additional insight into the mechanisms. The present investigation was designed to assess the effects and possible mechanisms of scoparone against carbon tetrachloride-induced liver injury. Ultra-performance liquid chromatography/electrospray ionization quadruple time-of-flight mass spectrometry (UPLC/ESI-Q-TOF/MS) combined with pattern recognition approaches including principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were integrated to discover differentiating metabolites. Results indicate five ions in the positive mode as differentiating metabolites. Functional pathway analysis revealed that the alterations in these metabolites were associated with primary bile acid biosynthesis, pyrimidine metabolism. Of note, scoparone has a potential pharmacological effect through regulating multiple perturbed pathways to the normal state. Our findings also showed that the robust metabolomics techniques are promising for getting biomarkers and clarifying mechanisms of disease, highlighting insights into drug discovery.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aurich, Maike K.; Fleming, Ronan M. T.; Thiele, Ines

Metabolomic data sets provide a direct read-out of cellular phenotypes and are increasingly generated to study biological questions. Previous work, by us and others, revealed the potential of analyzing extracellular metabolomic data in the context of the metabolic model using constraint-based modeling. With the MetaboTools, we make our methods available to the broader scientific community. The MetaboTools consist of a protocol, a toolbox, and tutorials of two use cases. The protocol describes, in a step-wise manner, the workflow of data integration, and computational analysis. The MetaboTools comprise the Matlab code required to complete the workflow described in the protocol. Tutorialsmore » explain the computational steps for integration of two different data sets and demonstrate a comprehensive set of methods for the computational analysis of metabolic models and stratification thereof into different phenotypes. The presented workflow supports integrative analysis of multiple omics data sets. Importantly, all analysis tools can be applied to metabolic models without performing the entire workflow. Taken together, the MetaboTools constitute a comprehensive guide to the intra-model analysis of extracellular metabolomic data from microbial, plant, or human cells. In conclusion, this computational modeling resource offers a broad set of computational analysis tools for a wide biomedical and non-biomedical research community.« less

Comparative metabolomics in vegans and omnivores reveal constraints on diet-dependent gut microbiota metabolite production.

PubMed

Wu, Gary D; Compher, Charlene; Chen, Eric Z; Smith, Sarah A; Shah, Rachana D; Bittinger, Kyle; Chehoud, Christel; Albenberg, Lindsey G; Nessel, Lisa; Gilroy, Erin; Star, Julie; Weljie, Aalim M; Flint, Harry J; Metz, David C; Bennett, Michael J; Li, Hongzhe; Bushman, Frederic D; Lewis, James D

2016-01-01

The consumption of an agrarian diet is associated with a reduced risk for many diseases associated with a 'Westernised' lifestyle. Studies suggest that diet affects the gut microbiota, which subsequently influences the metabolome, thereby connecting diet, microbiota and health. However, the degree to which diet influences the composition of the gut microbiota is controversial. Murine models and studies comparing the gut microbiota in humans residing in agrarian versus Western societies suggest that the influence is large. To separate global environmental influences from dietary influences, we characterised the gut microbiota and the host metabolome of individuals consuming an agrarian diet in Western society. Using 16S rRNA-tagged sequencing as well as plasma and urinary metabolomic platforms, we compared measures of dietary intake, gut microbiota composition and the plasma metabolome between healthy human vegans and omnivores, sampled in an urban USA environment. Plasma metabolome of vegans differed markedly from omnivores but the gut microbiota was surprisingly similar. Unlike prior studies of individuals living in agrarian societies, higher consumption of fermentable substrate in vegans was not associated with higher levels of faecal short chain fatty acids, a finding confirmed in a 10-day controlled feeding experiment. Similarly, the proportion of vegans capable of producing equol, a soy-based gut microbiota metabolite, was less than that was reported in Asian societies despite the high consumption of soy-based products. Evidently, residence in globally distinct societies helps determine the composition of the gut microbiota that, in turn, influences the production of diet-dependent gut microbial metabolites. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Untargeted metabolomics studies employing NMR and LC–MS reveal metabolic coupling between Nanoarcheum equitans and its archaeal host Ignicoccus hospitalis

DOE PAGES

Hamerly, Timothy; Tripet, Brian P.; Tigges, Michelle; ...

2014-11-05

Interactions between species are the basis of microbial community formation and infectious diseases. Systems biology enables the construction of complex models describing such interactions, leading to a better understanding of disease states and communities. However, before interactions between complex organisms can be understood, metabolic and energetic implications of simpler real-world host-microbe systems must be worked out. To this effect, untargeted metabolomics experiments were conducted and integrated with proteomics data to characterize key molecular-level interactions between two hyperthermophilic microbial species, both of which have reduced genomes. Metabolic changes and transfer of metabolites between the archaea Ignicoccus hospitalis and Nanoarcheum equitans weremore » investigated using integrated LC–MS and NMR metabolomics. The study of such a system is challenging, as no genetic tools are available, growth in the laboratory is challenging, and mechanisms by which they interact are unknown. Together with information about relative enzyme levels obtained from shotgun proteomics, the metabolomics data provided useful insights into metabolic pathways and cellular networks of I. hospitalis that are impacted by the presence of N. equitans, including arginine, isoleucine, and CTP biosynthesis. On the organismal level, the data indicate that N. equitans exploits metabolites generated by I. hospitalis to satisfy its own metabolic needs. Lastly, this finding is based on N. equitans’s consumption of a significant fraction of the metabolite pool in I. hospitalis that cannot solely be attributed to increased biomass production for N. equitans. Combining LC–MS and NMR metabolomics datasets improved coverage of the metabolome and enhanced the identification and quantitation of cellular metabolites.« less

Spatially resolved in vivo plant metabolomics by laser ablation-based mass spectrometry imaging (MSI) techniques: LDI-MSI and LAESI

PubMed Central

Bartels, Benjamin; Svatoš, Aleš

2015-01-01

This short review aims to summarize the current developments and applications of mass spectrometry-based methods for in situ profiling and imaging of plants with minimal or no sample pre-treatment or manipulation. Infrared-laser ablation electrospray ionization and UV-laser desorption/ionization methods are reviewed. The underlying mechanisms of the ionization techniques–namely, laser ablation of biological samples and electrospray ionization–as well as variations of the LAESI ion source for specific targets of interest are described. PMID:26217345

An UPLC-ESI-MS/MS Assay Using 6-Aminoquinolyl-N-Hydroxysuccinimidyl Carbamate Derivatization for Targeted Amino Acid Analysis: Application to Screening of Arabidopsis thaliana Mutants.

PubMed

Salazar, Carolina; Armenta, Jenny M; Shulaev, Vladimir

2012-07-06

In spite of the large arsenal of methodologies developed for amino acid assessment in complex matrices, their implementation in metabolomics studies involving wide-ranging mutant screening is hampered by their lack of high-throughput, sensitivity, reproducibility, and/or wide dynamic range. In response to the challenge of developing amino acid analysis methods that satisfy the criteria required for metabolomic studies, improved reverse-phase high-performance liquid chromatography-mass spectrometry (RPHPLC-MS) methods have been recently reported for large-scale screening of metabolic phenotypes. However, these methods focus on the direct analysis of underivatized amino acids and, therefore, problems associated with insufficient retention and resolution are observed due to the hydrophilic nature of amino acids. It is well known that derivatization methods render amino acids more amenable for reverse phase chromatographic analysis by introducing highly-hydrophobic tags in their carboxylic acid or amino functional group. Therefore, an analytical platform that combines the 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) pre-column derivatization method with ultra performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS/MS) is presented in this article. For numerous reasons typical amino acid derivatization methods would be inadequate for large scale metabolic projects. However, AQC derivatization is a simple, rapid and reproducible way of obtaining stable amino acid adducts amenable for UPLC-ESI-MS/MS and the applicability of the method for high-throughput metabolomic analysis in Arabidopsis thaliana is demonstrated in this study. Overall, the major advantages offered by this amino acid analysis method include high-throughput, enhanced sensitivity and selectivity; characteristics that showcase its utility for the rapid screening of the preselected plant metabolites without compromising the quality of the metabolic data. The presented method enabled thirty-eight metabolites (proteinogenic amino acids and related compounds) to be analyzed within 10 min with detection limits down to 1.02 × 10-11 M (i.e., atomole level on column), which represents an improved sensitivity of 1 to 5 orders of magnitude compared to existing methods. Our UPLC-ESI-MS/MS method is one of the seven analytical platforms used by the Arabidopsis Metabolomics Consortium. The amino acid dataset obtained by analysis of Arabidopsis T-DNA mutant stocks with our platform is captured and open to the public in the web portal PlantMetabolomics.org. The analytical platform herein described could find important applications in other studies where the rapid, high-throughput and sensitive assessment of low abundance amino acids in complex biosamples is necessary.

An UPLC-ESI-MS/MS Assay Using 6-Aminoquinolyl-N-Hydroxysuccinimidyl Carbamate Derivatization for Targeted Amino Acid Analysis: Application to Screening of Arabidopsis thaliana Mutants

PubMed Central

Salazar, Carolina; Armenta, Jenny M.; Shulaev, Vladimir

2012-01-01

In spite of the large arsenal of methodologies developed for amino acid assessment in complex matrices, their implementation in metabolomics studies involving wide-ranging mutant screening is hampered by their lack of high-throughput, sensitivity, reproducibility, and/or wide dynamic range. In response to the challenge of developing amino acid analysis methods that satisfy the criteria required for metabolomic studies, improved reverse-phase high-performance liquid chromatography-mass spectrometry (RPHPLC-MS) methods have been recently reported for large-scale screening of metabolic phenotypes. However, these methods focus on the direct analysis of underivatized amino acids and, therefore, problems associated with insufficient retention and resolution are observed due to the hydrophilic nature of amino acids. It is well known that derivatization methods render amino acids more amenable for reverse phase chromatographic analysis by introducing highly-hydrophobic tags in their carboxylic acid or amino functional group. Therefore, an analytical platform that combines the 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) pre-column derivatization method with ultra performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS/MS) is presented in this article. For numerous reasons typical amino acid derivatization methods would be inadequate for large scale metabolic projects. However, AQC derivatization is a simple, rapid and reproducible way of obtaining stable amino acid adducts amenable for UPLC-ESI-MS/MS and the applicability of the method for high-throughput metabolomic analysis in Arabidopsis thaliana is demonstrated in this study. Overall, the major advantages offered by this amino acid analysis method include high-throughput, enhanced sensitivity and selectivity; characteristics that showcase its utility for the rapid screening of the preselected plant metabolites without compromising the quality of the metabolic data. The presented method enabled thirty-eight metabolites (proteinogenic amino acids and related compounds) to be analyzed within 10 min with detection limits down to 1.02 × 10−11 M (i.e., atomole level on column), which represents an improved sensitivity of 1 to 5 orders of magnitude compared to existing methods. Our UPLC-ESI-MS/MS method is one of the seven analytical platforms used by the Arabidopsis Metabolomics Consortium. The amino acid dataset obtained by analysis of Arabidopsis T-DNA mutant stocks with our platform is captured and open to the public in the web portal PlantMetabolomics.org. The analytical platform herein described could find important applications in other studies where the rapid, high-throughput and sensitive assessment of low abundance amino acids in complex biosamples is necessary. PMID:24957640

A Guideline to Univariate Statistical Analysis for LC/MS-Based Untargeted Metabolomics-Derived Data

PubMed Central

Vinaixa, Maria; Samino, Sara; Saez, Isabel; Duran, Jordi; Guinovart, Joan J.; Yanes, Oscar

2012-01-01

Several metabolomic software programs provide methods for peak picking, retention time alignment and quantification of metabolite features in LC/MS-based metabolomics. Statistical analysis, however, is needed in order to discover those features significantly altered between samples. By comparing the retention time and MS/MS data of a model compound to that from the altered feature of interest in the research sample, metabolites can be then unequivocally identified. This paper reports on a comprehensive overview of a workflow for statistical analysis to rank relevant metabolite features that will be selected for further MS/MS experiments. We focus on univariate data analysis applied in parallel on all detected features. Characteristics and challenges of this analysis are discussed and illustrated using four different real LC/MS untargeted metabolomic datasets. We demonstrate the influence of considering or violating mathematical assumptions on which univariate statistical test rely, using high-dimensional LC/MS datasets. Issues in data analysis such as determination of sample size, analytical variation, assumption of normality and homocedasticity, or correction for multiple testing are discussed and illustrated in the context of our four untargeted LC/MS working examples. PMID:24957762

A Guideline to Univariate Statistical Analysis for LC/MS-Based Untargeted Metabolomics-Derived Data.

PubMed

Vinaixa, Maria; Samino, Sara; Saez, Isabel; Duran, Jordi; Guinovart, Joan J; Yanes, Oscar

2012-10-18

Several metabolomic software programs provide methods for peak picking, retention time alignment and quantification of metabolite features in LC/MS-based metabolomics. Statistical analysis, however, is needed in order to discover those features significantly altered between samples. By comparing the retention time and MS/MS data of a model compound to that from the altered feature of interest in the research sample, metabolites can be then unequivocally identified. This paper reports on a comprehensive overview of a workflow for statistical analysis to rank relevant metabolite features that will be selected for further MS/MS experiments. We focus on univariate data analysis applied in parallel on all detected features. Characteristics and challenges of this analysis are discussed and illustrated using four different real LC/MS untargeted metabolomic datasets. We demonstrate the influence of considering or violating mathematical assumptions on which univariate statistical test rely, using high-dimensional LC/MS datasets. Issues in data analysis such as determination of sample size, analytical variation, assumption of normality and homocedasticity, or correction for multiple testing are discussed and illustrated in the context of our four untargeted LC/MS working examples.

In Vitro Assessment of Plants Growing in Cuba Belonging to Solanaceae Family Against Leishmania amazonensis.

PubMed

Monzote, Lianet; Jiménez, Jenny; Cuesta-Rubio, Osmany; Márquez, Ingrid; Gutiérrez, Yamile; da Rocha, Cláudia Quintino; Marchi, Mary; Setzer, William N; Vilegas, Wagner

2016-11-01

In this study, an in vitro antileishmanial assessment of plant extracts from 12 genera and 46 species growing in Cuba belonging to Solanaceae family was performed. A total of 226 extracts were screened against promastigotes of Leishmania amazonensis, and cytotoxicity of active extracts [median inhibitory concentration (IC 50 ) promastigotes <100 µg/mL] was determined on peritoneal macrophage from BALB/c mice. Extracts that showed selective index >5 were then assayed against intracellular amastigote. Metabolomics analysis of promissory extracts was performed using chemical profile obtained by ultra performance liquid chromatography. Only 11 extracts (4.9%) from nine plants were selected as potentially actives: Brunfelsia cestroides A. Rich, Capsicum annuum L., Capsicum chinense Jacq., Cestrum nocturnum L., Nicotiana plumbaginifolia Viv., Solanum havanense Jacq., Solanum myriacanthum Dunal, Solanum nudum Dunal and Solanum seaforthianum And., with IC 50  < 50 µg/mL and selectivity index >5. Metabolomics analysis demonstrated significant differences in the chemical profiles with an average of 42.8 (range 31-88) compounds from m/z 104 to 1477, which demonstrated the complex mixture of compounds. In addition, no common markers among active extracts were identified. The results demonstrate the importance of the Solanaceae family to search new antileishmanial agents, particularly in unexplored species of this family. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Identification of a Collagenase-Inhibiting Flavonoid from Alchemilla vulgaris Using NMR-Based Metabolomics.

PubMed

Mandrone, Manuela; Coqueiro, Aline; Poli, Ferruccio; Antognoni, Fabiana; Choi, Young Hae

2018-05-24

This paper describes the use of 1 H NMR profiling and chemometrics in order to facilitate the selection of medicinal plants as potential sources of collagenase inhibitors. A total of 49 plants with reported ethnobotanical uses, such as the healing of wounds and burns, treatment of skin-related diseases, rheumatism, arthritis, and bone diseases, were initially chosen as potential candidates. The in vitro collagenase inhibitory activity of hydroalcoholic extracts of these plants was tested. Moreover, their phytochemical profiles were analyzed by 1 H NMR and combined with the inhibitory activity data by an orthogonal partial least squares model. The results showed a correlation between the bioactivity and the concentration of phenolics, including flavonoids, phenylpropanoids, and tannins, in the extracts. Considering the eventual false-positive effect on the bioactivity given by tannins, a tannin removal procedure was performed on the most active extracts. After this procedure, Alchemilla vulgaris was the most persistently active, proving to owe its activity to compounds other than tannins. Thus, this plant was selected as the most promising and further investigated through bioassay-guided fractionation, which resulted in the isolation of a flavonoid, quercetin-3- O - β -glucuronide, as confirmed by NMR and HRMS spectra. This compound showed not only a higher activity than other flavonoids with the same aglycone moiety, but was also higher than doxycycline (positive control), the only Federal Drug Administration-approved collagenase inhibitor. The approach employed in this study, namely the integration of metabolomics and bioactivity-guided fractionation, showed great potential as a tool for plant selection and identification of bioactive compounds in natural product research. Georg Thieme Verlag KG Stuttgart · New York.

A Metabolomic Approach Applied to a Liquid Chromatography Coupled to High-Resolution Tandem Mass Spectrometry Method (HPLC-ESI-HRMS/MS): Towards the Comprehensive Evaluation of the Chemical Composition of Cannabis Medicinal Extracts.

PubMed

Citti, Cinzia; Battisti, Umberto Maria; Braghiroli, Daniela; Ciccarella, Giuseppe; Schmid, Martin; Vandelli, Maria Angela; Cannazza, Giuseppe

2018-03-01

Cannabis sativa L. is a powerful medicinal plant and its use has recently increased for the treatment of several pathologies. Nonetheless, side effects, like dizziness and hallucinations, and long-term effects concerning memory and cognition, can occur. Most alarming is the lack of a standardised procedure to extract medicinal cannabis. Indeed, each galenical preparation has an unknown chemical composition in terms of cannabinoids and other active principles that depends on the extraction procedure. This study aims to highlight the main differences in the chemical composition of Bediol® extracts when the extraction is carried out with either ethyl alcohol or olive oil for various times (0, 60, 120 and 180 min for ethyl alcohol, and 0, 60, 90 and 120 min for olive oil). Cannabis medicinal extracts (CMEs) were analysed by liquid chromatography coupled to high-resolution tandem mass spectrometry (LC-MS/MS) using an untargeted metabolomics approach. The data sets were processed by unsupervised multivariate analysis. Our results suggested that the main difference lies in the ratio of acid to decarboxylated cannabinoids, which dramatically influences the pharmacological activity of CMEs. Minor cannabinoids, alkaloids, and amino acids contributing to this difference are also discussed. The main cannabinoids were quantified in each extract applying a recently validated LC-MS and LC-UV method. Notwithstanding the use of a standardised starting plant material, great changes are caused by different extraction procedures. The metabolomics approach is a useful tool for the evaluation of the chemical composition of cannabis extracts. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

American Gut: an Open Platform for Citizen Science Microbiome Research

PubMed Central

2018-01-01

ABSTRACT Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the United States, United Kingdom, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes compared to environmental samples; demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations; uncover new molecules and kinds of molecular communities in the human stool metabolome; and examine emergent associations among the microbiome, metabolome, and the diversity of plants that are consumed (rather than relying on reductive categorical variables such as veganism, which have little or no explanatory power). We also demonstrate the utility of the living data resource and cross-cohort comparison to confirm existing associations between the microbiome and psychiatric illness and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education. IMPORTANCE We show that a citizen science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones. Of particular interest is integrating n = 1 study data with the population data, showing that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes, and the effect of diverse plants in the diet, which we confirm with untargeted metabolomics on hundreds of samples. PMID:29795809

American Gut: an Open Platform for Citizen Science Microbiome Research.

PubMed

McDonald, Daniel; Hyde, Embriette; Debelius, Justine W; Morton, James T; Gonzalez, Antonio; Ackermann, Gail; Aksenov, Alexander A; Behsaz, Bahar; Brennan, Caitriona; Chen, Yingfeng; DeRight Goldasich, Lindsay; Dorrestein, Pieter C; Dunn, Robert R; Fahimipour, Ashkaan K; Gaffney, James; Gilbert, Jack A; Gogul, Grant; Green, Jessica L; Hugenholtz, Philip; Humphrey, Greg; Huttenhower, Curtis; Jackson, Matthew A; Janssen, Stefan; Jeste, Dilip V; Jiang, Lingjing; Kelley, Scott T; Knights, Dan; Kosciolek, Tomasz; Ladau, Joshua; Leach, Jeff; Marotz, Clarisse; Meleshko, Dmitry; Melnik, Alexey V; Metcalf, Jessica L; Mohimani, Hosein; Montassier, Emmanuel; Navas-Molina, Jose; Nguyen, Tanya T; Peddada, Shyamal; Pevzner, Pavel; Pollard, Katherine S; Rahnavard, Gholamali; Robbins-Pianka, Adam; Sangwan, Naseer; Shorenstein, Joshua; Smarr, Larry; Song, Se Jin; Spector, Timothy; Swafford, Austin D; Thackray, Varykina G; Thompson, Luke R; Tripathi, Anupriya; Vázquez-Baeza, Yoshiki; Vrbanac, Alison; Wischmeyer, Paul; Wolfe, Elaine; Zhu, Qiyun; Knight, Rob

2018-01-01

Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the United States, United Kingdom, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes compared to environmental samples; demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations; uncover new molecules and kinds of molecular communities in the human stool metabolome; and examine emergent associations among the microbiome, metabolome, and the diversity of plants that are consumed (rather than relying on reductive categorical variables such as veganism, which have little or no explanatory power). We also demonstrate the utility of the living data resource and cross-cohort comparison to confirm existing associations between the microbiome and psychiatric illness and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education. IMPORTANCE We show that a citizen science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones. Of particular interest is integrating n = 1 study data with the population data, showing that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes, and the effect of diverse plants in the diet, which we confirm with untargeted metabolomics on hundreds of samples.

Natural isotope correction of MS/MS measurements for metabolomics and (13)C fluxomics.

PubMed

Niedenführ, Sebastian; ten Pierick, Angela; van Dam, Patricia T N; Suarez-Mendez, Camilo A; Nöh, Katharina; Wahl, S Aljoscha

2016-05-01

Fluxomics and metabolomics are crucial tools for metabolic engineering and biomedical analysis to determine the in vivo cellular state. Especially, the application of (13)C isotopes allows comprehensive insights into the functional operation of cellular metabolism. Compared to single MS, tandem mass spectrometry (MS/MS) provides more detailed and accurate measurements of the metabolite enrichment patterns (tandem mass isotopomers), increasing the accuracy of metabolite concentration measurements and metabolic flux estimation. MS-type data from isotope labeling experiments is biased by naturally occurring stable isotopes (C, H, N, O, etc.). In particular, GC-MS(/MS) requires derivatization for the usually non-volatile intracellular metabolites introducing additional natural isotopes leading to measurements that do not directly represent the carbon labeling distribution. To make full use of LC- and GC-MS/MS mass isotopomer measurements, the influence of natural isotopes has to be eliminated (corrected). Our correction approach is analyzed for the two most common applications; (13)C fluxomics and isotope dilution mass spectrometry (IDMS) based metabolomics. Natural isotopes can have an impact on the calculated flux distribution which strongly depends on the substrate labeling and the actual flux distribution. Second, we show that in IDMS based metabolomics natural isotopes lead to underestimated concentrations that can and should be corrected with a nonlinear calibration. Our simulations indicate that the correction for natural abundance in isotope based fluxomics and quantitative metabolomics is essential for correct data interpretation. © 2015 Wiley Periodicals, Inc.

Rapid two-dimensional ALSOFAST-HSQC experiment for metabolomics and fluxomics studies: application to a 13C-enriched cancer cell model treated with gold nanoparticles.

PubMed

Schätzlein, Martina Palomino; Becker, Johanna; Schulze-Sünninghausen, David; Pineda-Lucena, Antonio; Herance, José Raul; Luy, Burkhard

2018-04-01

Isotope labeling enables the use of 13 C-based metabolomics techniques with strongly improved resolution for a better identification of relevant metabolites and tracing of metabolic fluxes in cell and animal models, as required in fluxomics studies. However, even at high NMR-active isotope abundance, the acquisition of one-dimensional 13 C and classical two-dimensional 1 H, 13 C-HSQC experiments remains time consuming. With the aim to provide a shorter, more efficient alternative, herein we explored the ALSOFAST-HSQC experiment with its rapid acquisition scheme for the analysis of 13 C-labeled metabolites in complex biological mixtures. As an initial step, the parameters of the pulse sequence were optimized to take into account the specific characteristics of the complex samples. We then applied the fast two-dimensional experiment to study the effect of different kinds of antioxidant gold nanoparticles on a HeLa cancer cell model grown on 13 C glucose-enriched medium. As a result, 1 H, 13 C-2D correlations could be obtained in a couple of seconds to few minutes, allowing a simple and reliable identification of various 13 C-enriched metabolites and the determination of specific variations between the different sample groups. Thus, it was possible to monitor glucose metabolism in the cell model and study the antioxidant effect of the coated gold nanoparticles in detail. Finally, with an experiment time of only half an hour, highly resolved 1 H, 13 C-HSQC spectra using the ALSOFAST-HSQC pulse sequence were acquired, revealing the isotope-position-patterns of the corresponding 13 C-nuclei from carbon multiplets. Graphical abstract Fast NMR applied to metabolomics and fluxomics studies with gold nanoparticles.

Metabolic profiling and enzyme analyses indicate a potential role of antioxidant systems in complementing glyphosate resistance in an Amaranthus palmeri biotype

USDA-ARS?s Scientific Manuscript database

Targeted metabolomic profiling and biochemical assays were employed to identify metabolite-level perturbations induced by glyphosate in susceptible (S) and resistant (R) biotypes of Amaranthus palmeri. Plants were treated with 0.4 kg ae ha-1 glyphosate and tissues were harvested at 8 and 72 hours af...

SWAPDT: A method for Short-time Withering Assessment of Probability for Drought Tolerance in Camellia sinensis validated by targeted metabolomics.

PubMed

Nyarukowa, Christopher; Koech, Robert; Loots, Theodor; Apostolides, Zeno

2016-07-01

Climate change is causing droughts affecting crop production on a global scale. Classical breeding and selection strategies for drought-tolerant cultivars will help prevent crop losses. Plant breeders, for all crops, need a simple and reliable method to identify drought-tolerant cultivars, but such a method is missing. Plant metabolism is often disrupted by abiotic stress conditions. To survive drought, plants reconfigure their metabolic pathways. Studies have documented the importance of metabolic regulation, i.e. osmolyte accumulation such as polyols and sugars (mannitol, sorbitol); amino acids (proline) during drought. This study identified and quantified metabolites in drought tolerant and drought susceptible Camellia sinensis cultivars under wet and drought stress conditions. For analyses, GC-MS and LC-MS were employed for metabolomics analysis.%RWC results show how the two drought tolerant and two drought susceptible cultivars differed significantly (p≤0.05) from one another; the drought susceptible exhibited rapid water loss compared to the drought tolerant. There was a significant variation (p<0.05) in metabolite content (amino acid, sugars) between drought tolerant and drought susceptible tea cultivars after short-time withering conditions. These metabolite changes were similar to those seen in other plant species under drought conditions, thus validating this method. The Short-time Withering Assessment of Probability for Drought Tolerance (SWAPDT) method presented here provides an easy method to identify drought tolerant tea cultivars that will mitigate the effects of drought due to climate change on crop losses. Copyright © 2016. Published by Elsevier GmbH.

Iron-dependent modifications of the flower transcriptome, proteome, metabolome, and hormonal content in an Arabidopsis ferritin mutant

PubMed Central

Sudre, Damien; Gutierrez-Carbonell, Elain; Lattanzio, Giuseppe; Rellán-Álvarez, Rubén; Gaymard, Frédéric; Wohlgemuth, Gert; Fiehn, Oliver; Álvarez-Fernández, Ana; Zamarreño, Angel M.; Bacaicoa, Eva; Duy, Daniela; García-Mina, Jose-María; Abadía, Javier; Philippar, Katrin; López-Millán, Ana-Flor; Briat, Jean-François

2013-01-01

Iron homeostasis is an important process for flower development and plant fertility. The role of plastids in these processes has been shown to be essential. To document the relationships between plastid iron homeostasis and flower biology further, a global study (transcriptome, proteome, metabolome, and hormone analysis) was performed of Arabidopsis flowers from wild-type and triple atfer1-3-4 ferritin mutant plants grown under iron-sufficient or excess conditions. Some major modifications in specific functional categories were consistently observed at these three omic levels, although no significant overlaps of specific transcripts and proteins were detected. These modifications concerned redox reactions and oxidative stress, as well as amino acid and protein catabolism, this latter point being exemplified by an almost 10-fold increase in urea concentration of atfer1-3-4 flowers from plants grown under iron excess conditions. The mutant background caused alterations in Fe–haem redox proteins located in membranes and in hormone-responsive proteins. Specific effects of excess Fe in the mutant included further changes in these categories, supporting the idea that the mutant is facing a more intense Fe/redox stress than the wild type. The mutation and/or excess Fe had a strong impact at the membrane level, as denoted by the changes in the transporter and lipid metabolism categories. In spite of the large number of genes and proteins responsive to hormones found to be regulated in this study, changes in the hormonal balance were restricted to cytokinins, especially in the mutant plants grown under Fe excess conditions. PMID:23682113

Metabolomics Reveals How Cucumber (Cucumis sativus) Reprograms Metabolites to Cope with Silver Ions and Silver Nanoparticle-Induced Oxidative Stress.

PubMed

Zhang, Huiling; Du, Wenchao; Peralta-Videa, Jose R; Gardea-Torresdey, Jorge L; White, Jason C; Keller, Arturo A; Guo, Hongyan; Ji, Rong; Zhao, Lijuan

2018-06-14

Due to their well-known antifungal activity, the intentional use of Ag nanoparticle (NPs) as sustainable nano-fungicides is expected to increase in agriculture. However, the impacts of AgNPs on plants must be critically evaluated to guarantee their safe use in food production. In this study, 4-week-old cucumber (Cucumis sativus) plants received a foliar application of AgNPs (4 or 40 mg per plant) or Ag+ (0.04 or 0.4 mg per plant) for seven days. Gas chromatography-mass spectrometry (GC-MS) based non-target metabolomics enabled the identification and quantification of 268 metabolites in cucumber leaves. Multivariate analysis revealed that all the treatments significantly altered the metabolite profile. Exposure to AgNPs resulted in metabolic reprogramming, including activation of antioxidant defense systems (up-regulation of phenolic compounds) and down-regulation of photosynthesis (up-regulation of phytol). Additionally, AgNPs enhanced respiration (up-regulation of TCA cycle intermediates), inhibited photorespiration (down-regulation of glycine/serine ratio), altered membrane properties (up-regulation of pentadecanoic and arachidonic acid, down-regulation of linoleic and linolenic acid), and reduced of inorganic nitrogen fixation (down-regulation of glutamine and asparagine). Although Ag ions induced some of the same metabolic changes, alterations in the levels of carbazole, indoleactate, raffinose, adenosine, lactamide, erythrose, and p-benzoquinone were AgNPs-specific. The results of this study offer new insight into the molecular mechanisms by which cucumber responds to AgNPs exposure and provide important information to support the sustainable use of AgNPs in agriculture.

The need for agriculture phenotyping: "moving from genotype to phenotype".

PubMed

Boggess, Mark V; Lippolis, John D; Hurkman, William J; Fagerquist, Clifton K; Briggs, Steve P; Gomes, Aldrin V; Righetti, Pier Giorgio; Bala, Kumar

2013-11-20

Increase in the world population has called for the increased demand for agricultural productivity. Traditional methods to augment crop and animal production are facing exacerbating pressures in keeping up with population growth. This challenge has in turn led to the transformational change in the use of biotechnology tools to meet increased productivity for both plant and animal systems. Although many challenges exist, the use of proteomic techniques to understand agricultural problems is steadily increasing. This review discusses the impact of genomics, proteomics, metabolomics and phenotypes on plant, animal and bacterial systems to achieve global food security and safety and we highlight examples of intra and extra mural research work that is currently being done to increase agricultural productivity. This review focuses on the global demand for increased agricultural productivity arising from population growth and how we can address this challenge using biotechnology. With a population well above seven billion humans, in a very unbalanced nutritional state (20% overweight, 20% risking starvation) drastic measures have to be taken at the political, infrastructure and scientific levels. While we cannot influence politics, it is our duty as scientists to see what can be done to feed humanity. Hence we highlight the transformational change in the use of biotechnology tools over traditional methods to increase agricultural productivity (plant and animal). Specifically, this review deals at length on how a three-pronged attack, namely combined genomics, proteomics and metabolomics, can help to ensure global food security and safety. This article is part of a Special Issue entitled: Translational Plant Proteomics. Copyright © 2013 Elsevier B.V. All rights reserved.

Using next generation transcriptome sequencing to predict an ectomycorrhizal metablome.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larsen, P. E.; Sreedasyam, A.; Trivedi, G

Mycorrhizae, symbiotic interactions between soil fungi and tree roots, are ubiquitous in terrestrial ecosystems. The fungi contribute phosphorous, nitrogen and mobilized nutrients from organic matter in the soil and in return the fungus receives photosynthetically-derived carbohydrates. This union of plant and fungal metabolisms is the mycorrhizal metabolome. Understanding this symbiotic relationship at a molecular level provides important contributions to the understanding of forest ecosystems and global carbon cycling. We generated next generation short-read transcriptomic sequencing data from fully-formed ectomycorrhizae between Laccaria bicolor and aspen (Populus tremuloides) roots. The transcriptomic data was used to identify statistically significantly expressed gene models usingmore » a bootstrap-style approach, and these expressed genes were mapped to specific metabolic pathways. Integration of expressed genes that code for metabolic enzymes and the set of expressed membrane transporters generates a predictive model of the ectomycorrhizal metabolome. The generated model of mycorrhizal metabolome predicts that the specific compounds glycine, glutamate, and allantoin are synthesized by L. bicolor and that these compounds or their metabolites may be used for the benefit of aspen in exchange for the photosynthetically-derived sugars fructose and glucose. The analysis illustrates an approach to generate testable biological hypotheses to investigate the complex molecular interactions that drive ectomycorrhizal symbiosis. These models are consistent with experimental environmental data and provide insight into the molecular exchange processes for organisms in this complex ecosystem. The method used here for predicting metabolomic models of mycorrhizal systems from deep RNA sequencing data can be generalized and is broadly applicable to transcriptomic data derived from complex systems.« less

Plant Molecular Biology 2008 Gordon Research Conference - July 13-18, 2008

DOE Office of Scientific and Technical Information (OSTI.GOV)

Richard M. Amasino

The Plant Molecular Biology Conference has traditionally covered a breadth of exciting topics and the 2008 conference will continue in that tradition. There will be sessions on metabolism; new methods to study genomes, proteomes and metabolomes; plant-microbe interactions; plant hormones; epigenetics. A new topic for the conference this year will be bioenergy. Thus this conference will bring together a range of disciplines to foster the exchange ideas and to permit the participants to learn of the latest developments and ideas in diverse areas of plant biology. The conference provides an excellent opportunity for individuals to discuss their research because additionalmore » speakers in each session will be selected from submitted abstracts. There will also be a poster session each day for a two-hour period prior to dinner.« less

Ozone affects growth and development of Pieris brassicae on the wild host plant Brassica nigra.

PubMed

Khaling, Eliezer; Papazian, Stefano; Poelman, Erik H; Holopainen, Jarmo K; Albrectsen, Benedicte R; Blande, James D

2015-04-01

When plants are exposed to ozone they exhibit changes in both primary and secondary metabolism, which may affect their interactions with herbivorous insects. Here we investigated the performance and preferences of the specialist herbivore Pieris brassicae on the wild plant Brassica nigra under elevated ozone conditions. The direct and indirect effects of ozone on the plant-herbivore system were studied. In both cases ozone exposure had a negative effect on P. brassicae development. However, in dual-choice tests larvae preferentially consumed plant material previously fumigated with the highest concentration tested, showing a lack of correlation between larval preference and performance on ozone exposed plants. Metabolomic analysis of leaf material subjected to combinations of ozone and herbivore-feeding, and focussing on known defence metabolites, indicated that P. brassicae behaviour and performance were associated with ozone-induced alterations to glucosinolate and phenolic pools. Copyright © 2015 Elsevier Ltd. All rights reserved.

Single-cell-type Proteomics: Toward a Holistic Understanding of Plant Function*

PubMed Central

Dai, Shaojun; Chen, Sixue

2012-01-01

Multicellular organisms such as plants contain different types of cells with specialized functions. Analyzing the protein characteristics of each type of cell will not only reveal specific cell functions, but also enhance understanding of how an organism works. Most plant proteomics studies have focused on using tissues and organs containing a mixture of different cells. Recent single-cell-type proteomics efforts on pollen grains, guard cells, mesophyll cells, root hairs, and trichomes have shown utility. We expect that high resolution proteomic analyses will reveal novel functions in single cells. This review provides an overview of recent developments in plant single-cell-type proteomics. We discuss application of the approach for understanding important cell functions, and we consider the technical challenges of extending the approach to all plant cell types. Finally, we consider the integration of single-cell-type proteomics with transcriptomics and metabolomics with the goal of providing a holistic understanding of plant function. PMID:22982375

DOE Office of Scientific and Technical Information (OSTI.GOV)

Webb-Robertson, Bobbie-Jo; Kim, Young -Mo; Zink, Erika M.

Urease pre-treatment of urine has been utilized since the early 1960s to remove high levels of urea from samples prior to further processing and analysis by gas chromatography-mass spectrometry (GC-MS). Aside from the obvious depletion or elimination of urea, the effect, if any, of urease pre-treatment on the urinary metabolome has not been studied in detail. Here, we report the results of three separate but related experiments that were designed to assess possible indirect effects of urease pre-treatment on the urinary metabolome as measured by GC-MS. In total, 235 GC-MS analyses were performed and over 106 identified and 200 unidentifiedmore » metabolites were quantified across the three experiments. The results showed that data from urease pre-treated samples 1) had the same or lower coefficients of variance among reproducibly detected metabolites, 2) more accurately reflected quantitative differences and the expected ratios among different urine volumes, and 3) increased the number of metabolite identifications. Altogether, we observed no negative consequences of urease pre-treatment. In contrast, urease pretreatment enhanced the ability to distinguish between volume-based and biological sample types compared to no treatment. Taken together, these results show that urease pretreatment of urine offers multiple beneficial effects that outweigh any artifacts that may be introduced to the data in urinary metabolomics analyses.« less

Evaluation of non-volatile metabolites in beer stored at high temperature and utility as an accelerated method to predict flavour stability.

PubMed

Heuberger, Adam L; Broeckling, Corey D; Sedin, Dana; Holbrook, Christian; Barr, Lindsay; Kirkpatrick, Kaylyn; Prenni, Jessica E

2016-06-01

Flavour stability is vital to the brewing industry as beer is often stored for an extended time under variable conditions. Developing an accelerated model to evaluate brewing techniques that affect flavour stability is an important area of research. Here, we performed metabolomics on non-volatile compounds in beer stored at 37 °C between 1 and 14 days for two beer types: an amber ale and an India pale ale. The experiment determined high temperature to influence non-volatile metabolites, including the purine 5-methylthioadenosine (5-MTA). In a second experiment, three brewing techniques were evaluated for improved flavour stability: use of antioxidant crowns, chelation of pro-oxidants, and varying plant content in hops. Sensory analysis determined the hop method was associated with improved flavour stability, and this was consistent with reduced 5-MTA at both regular and high temperature storage. Future studies are warranted to understand the influence of 5-MTA on flavour and aging within different beer types. Copyright © 2016 Elsevier Ltd. All rights reserved.

nmrML: A Community Supported Open Data Standard for the Description, Storage, and Exchange of NMR Data.

PubMed

Schober, Daniel; Jacob, Daniel; Wilson, Michael; Cruz, Joseph A; Marcu, Ana; Grant, Jason R; Moing, Annick; Deborde, Catherine; de Figueiredo, Luis F; Haug, Kenneth; Rocca-Serra, Philippe; Easton, John; Ebbels, Timothy M D; Hao, Jie; Ludwig, Christian; Günther, Ulrich L; Rosato, Antonio; Klein, Matthias S; Lewis, Ian A; Luchinat, Claudio; Jones, Andrew R; Grauslys, Arturas; Larralde, Martin; Yokochi, Masashi; Kobayashi, Naohiro; Porzel, Andrea; Griffin, Julian L; Viant, Mark R; Wishart, David S; Steinbeck, Christoph; Salek, Reza M; Neumann, Steffen

2018-01-02

NMR is a widely used analytical technique with a growing number of repositories available. As a result, demands for a vendor-agnostic, open data format for long-term archiving of NMR data have emerged with the aim to ease and encourage sharing, comparison, and reuse of NMR data. Here we present nmrML, an open XML-based exchange and storage format for NMR spectral data. The nmrML format is intended to be fully compatible with existing NMR data for chemical, biochemical, and metabolomics experiments. nmrML can capture raw NMR data, spectral data acquisition parameters, and where available spectral metadata, such as chemical structures associated with spectral assignments. The nmrML format is compatible with pure-compound NMR data for reference spectral libraries as well as NMR data from complex biomixtures, i.e., metabolomics experiments. To facilitate format conversions, we provide nmrML converters for Bruker, JEOL and Agilent/Varian vendor formats. In addition, easy-to-use Web-based spectral viewing, processing, and spectral assignment tools that read and write nmrML have been developed. Software libraries and Web services for data validation are available for tool developers and end-users. The nmrML format has already been adopted for capturing and disseminating NMR data for small molecules by several open source data processing tools and metabolomics reference spectral libraries, e.g., serving as storage format for the MetaboLights data repository. The nmrML open access data standard has been endorsed by the Metabolomics Standards Initiative (MSI), and we here encourage user participation and feedback to increase usability and make it a successful standard.

Morphological, proteomic and metabolomic insight into the effect of cerium dioxide nanoparticles to Phaseolus vulgaris L. under soil or foliar application.

PubMed

Salehi, Hajar; Chehregani, Abdolkarim; Lucini, Luigi; Majd, Ahmad; Gholami, Mansour

2018-03-01

Chemically synthesized nanoparticles (NPs) are widely used in industry and concern over their impact on the environment is rising. In this study, greenhouse grown bean (Phaseolus vulgaris L.) plants were treated with CeO 2 NPs suspensions at 0, 250, 500, 1000, and 2000mgL -1 either aerially by spraying or via soil application. At 15days after treatment, plants were analyzed for Ce uptake, morphological and biochemical assays, as well as high-resolution mass spectrometry based metabolomics and proteomics. The results from ICP-MS assays showed a dose dependent absorption, uptake and translocation of Ce through both roots and leaves; Ce content increased from 0.68 up to 1894mgkg -1 following spray application, while concentrations were three orders lower following soil application (0.59 to 2.19mgkg -1 ). Electrolyte leakage increased with NPs rate, from 25.2% to 70.3% and from 24.8% to 32.9% following spray and soil application, respectively. Spraying lowered stomatal density (from 337 to 113 per mm 2 ) and increased stomatal length (from 12.8 to 19.4μm), and altered photosynthesis and electron transport chain biochemical machinery. The increase in Ce content induced accumulation of osmolites (proline increased from 0.54 to 0.65mg/g under spray application), phytosiderophores (muconate and mugineate compounds showed increase fold-changes >16) and proteins involved in folding or turnover. NPs application induced membrane damage, as evidenced by the increase in membrane lipids degradates and by the increase in electrolyte leakage, and caused oxidative stress. Most of the responses were not linear but dose-dependent, whereas metabolic disruption is expected at the highest NPs dosage. Both proteomics and metabolomics highlighted a stronger effect of CeO 2 NPs spraying, as compared to soil application. High concentrations of NPs in the environment have been confirmed to pose toxicity concern towards plants, although important differences could be highlighted between aerial deposition and soil contamination. Copyright © 2017 Elsevier B.V. All rights reserved.

Systems-Level Annotation of a Metabolomics Data Set Reduces 25 000 Features to Fewer than 1000 Unique Metabolites.

PubMed

Mahieu, Nathaniel G; Patti, Gary J

2017-10-03

When using liquid chromatography/mass spectrometry (LC/MS) to perform untargeted metabolomics, it is now routine to detect tens of thousands of features from biological samples. Poor understanding of the data, however, has complicated interpretation and masked the number of unique metabolites actually being measured in an experiment. Here we place an upper bound on the number of unique metabolites detected in Escherichia coli samples analyzed with one untargeted metabolomics method. We first group multiple features arising from the same analyte, which we call "degenerate features", using a context-driven annotation approach. Surprisingly, this analysis revealed thousands of previously unreported degeneracies that reduced the number of unique analytes to ∼2961. We then applied an orthogonal approach to remove nonbiological features from the data using the 13 C-based credentialing technology. This further reduced the number of unique analytes to less than 1000. Our 90% reduction in data is 5-fold greater than previously published studies. On the basis of the results, we propose an alternative approach to untargeted metabolomics that relies on thoroughly annotated reference data sets. To this end, we introduce the creDBle database ( http://creDBle.wustl.edu ), which contains accurate mass, retention time, and MS/MS fragmentation data as well as annotations of all credentialed features.

MetaboTools: A comprehensive toolbox for analysis of genome-scale metabolic models

DOE PAGES

Aurich, Maike K.; Fleming, Ronan M. T.; Thiele, Ines

2016-08-03

Metabolomic data sets provide a direct read-out of cellular phenotypes and are increasingly generated to study biological questions. Previous work, by us and others, revealed the potential of analyzing extracellular metabolomic data in the context of the metabolic model using constraint-based modeling. With the MetaboTools, we make our methods available to the broader scientific community. The MetaboTools consist of a protocol, a toolbox, and tutorials of two use cases. The protocol describes, in a step-wise manner, the workflow of data integration, and computational analysis. The MetaboTools comprise the Matlab code required to complete the workflow described in the protocol. Tutorialsmore » explain the computational steps for integration of two different data sets and demonstrate a comprehensive set of methods for the computational analysis of metabolic models and stratification thereof into different phenotypes. The presented workflow supports integrative analysis of multiple omics data sets. Importantly, all analysis tools can be applied to metabolic models without performing the entire workflow. Taken together, the MetaboTools constitute a comprehensive guide to the intra-model analysis of extracellular metabolomic data from microbial, plant, or human cells. In conclusion, this computational modeling resource offers a broad set of computational analysis tools for a wide biomedical and non-biomedical research community.« less

A Metabolomic Approach to Target Compounds from the Asteraceae Family for Dual COX and LOX Inhibition

PubMed Central

Chagas-Paula, Daniela A.; Zhang, Tong; Da Costa, Fernando B.; Edrada-Ebel, RuAngelie

2015-01-01

The application of metabolomics in phytochemical analysis is an innovative strategy for targeting active compounds from a complex plant extract. Species of the Asteraceae family are well-known to exhibit potent anti-inflammatory (AI) activity. Dual inhibition of the enzymes COX-1 and 5-LOX is essential for the treatment of several inflammatory diseases, but there is not much investigation reported in the literature for natural products. In this study, 57 leaf extracts (EtOH-H2O 7:3, v/v) from different genera and species of the Asteraceae family were tested against COX-1 and 5-LOX while HPLC-ESI-HRMS analysis of the extracts indicated high diversity in their chemical compositions. Using O2PLS-DA (R2 > 0.92; VIP > 1 and positive Y-correlation values), dual inhibition potential of low-abundance metabolites was determined. The O2PLS-DA results exhibited good validation values (cross-validation = Q2 > 0.7 and external validation = P2 > 0.6) with 0% of false positive predictions. The metabolomic approach determined biomarkers for the required biological activity and detected active compounds in the extracts displaying unique mechanisms of action. In addition, the PCA data also gave insights on the chemotaxonomy of the family Asteraceae across its diverse range of genera and tribes. PMID:26184333

Characterization of a novel, ubiquitous fungal endophyte from the rhizosphere and root endosphere of Populus trees

DOE PAGES

Vélez, Jessica M.; Tschaplinski, Timothy J.; Vilgalys, Rytas; ...

2017-04-07

Here, we examined variation in growth rate, patterns of nitrogen utilization, and competitive interactions of Atractiellarhizophila isolates from the roots of Populus hosts. Atractiella grew significantly faster on media substituted with inorganic nitrogen sources and slower in the presence of another fungal genus. In order to determine plausible causal mechanisms we used metabolomics to explore competitive interactions between Atractiella strains and Fusarium oxysporum or Leptosphaerulina chartarum. Metabolomic screening of potential microbial inhibitors showed increased levels of glycosides produced in vitro by Atractiella when grown with a different fungal genus, relative to when grown alone. Overall, our results suggest Atractiella ismore » a poor competitor with other fungi via direct routes e.g. faster growth rates, but may utilize chemical interactions and possibly nitrogen sources to defend itself, and niche partition its way to abundance in the plant host root and rhizosphere.« less

Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

DOE PAGES

Boiteau, Rene M.; Hoyt, David W.; Nicora, Carrie D.; ...

2018-01-17

Here, we introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS 2), and NMR in a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS 2 approach is well suited for discovery ofmore » new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.« less

Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boiteau, Rene M.; Hoyt, David W.; Nicora, Carrie D.

Here, we introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS 2), and NMR in a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS 2 approach is well suited for discovery ofmore » new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.« less

Characterization of a novel, ubiquitous fungal endophyte from the rhizosphere and root endosphere of Populus trees

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vélez, Jessica M.; Tschaplinski, Timothy J.; Vilgalys, Rytas

Here, we examined variation in growth rate, patterns of nitrogen utilization, and competitive interactions of Atractiellarhizophila isolates from the roots of Populus hosts. Atractiella grew significantly faster on media substituted with inorganic nitrogen sources and slower in the presence of another fungal genus. In order to determine plausible causal mechanisms we used metabolomics to explore competitive interactions between Atractiella strains and Fusarium oxysporum or Leptosphaerulina chartarum. Metabolomic screening of potential microbial inhibitors showed increased levels of glycosides produced in vitro by Atractiella when grown with a different fungal genus, relative to when grown alone. Overall, our results suggest Atractiella ismore » a poor competitor with other fungi via direct routes e.g. faster growth rates, but may utilize chemical interactions and possibly nitrogen sources to defend itself, and niche partition its way to abundance in the plant host root and rhizosphere.« less

Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

PubMed Central

Hoyt, David W.; Nicora, Carrie D.; Kinmonth-Schultz, Hannah A.; Ward, Joy K.

2018-01-01

We introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS2), and NMR into a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter out the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture, and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS2 approach is well suited to the discovery of new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases. PMID:29342073

Evolution of the metabolome in response to selection for increased immunity in populations of Drosophila melanogaster

PubMed Central

Gogna, Navdeep; Gupta, Vanika

2017-01-01

We used NMR-based metabolomics to test two hypotheses–(i) there will be evolved differences in the metabolome of selected and control populations even under un-infected conditions and (ii) post infection, the metabolomes of the selected and control populations will respond differently. We selected replicate populations of Drosophila melanogaster for increased survivorship (I) against a gram-negative pathogen. We subjected the selected (I) and their control populations (S) to three different treatments: (1) infected with heat-killed bacteria (i), (2) sham infected (s), and (3) untreated (u). We performed 1D and 2D NMR experiments to identify the metabolic differences. Multivariate analysis of the metabolic profiles of the untreated (Iu and Su) flies yielded higher concentrations of lipids, organic acids, sugars, amino acids, NAD and AMP in the Iu treatment as compared to the Su treatment, showing that even in the absence of infection, the metabolome of the I and S regimes was different. In the S and I regimes, post infection/injury, concentration of metabolites directly or indirectly associated with energy related pathways (lipids, organic acids, sugars) declined while the concentration of metabolites that are probably associated with immune response (amino acids) increased. However, in most cases, the I regime flies had a higher concentration of such metabolites even under un-infected conditions. The change in the metabolite concentration upon infection/injury was not always comparable between I and S regimes (in case of lactate, alanine, leucine, lysine, threonine) indicating that the I and S regimes had evolved to respond differentially to infection and to injury. PMID:29149207

Automated LC-HRMS(/MS) Approach for the Annotation of Fragment Ions Derived from Stable Isotope Labeling-Assisted Untargeted Metabolomics

PubMed Central

2014-01-01

Structure elucidation of biological compounds is still a major bottleneck of untargeted LC-HRMS approaches in metabolomics research. The aim of the present study was to combine stable isotope labeling and tandem mass spectrometry for the automated interpretation of the elemental composition of fragment ions and thereby facilitate the structural characterization of metabolites. The software tool FragExtract was developed and evaluated with LC-HRMS/MS spectra of both native 12C- and uniformly 13C (U-13C)-labeled analytical standards of 10 fungal substances in pure solvent and spiked into fungal culture filtrate of Fusarium graminearum respectively. Furthermore, the developed approach is exemplified with nine unknown biochemical compounds contained in F. graminearum samples derived from an untargeted metabolomics experiment. The mass difference between the corresponding fragment ions present in the MS/MS spectra of the native and U-13C-labeled compound enabled the assignment of the number of carbon atoms to each fragment signal and allowed the generation of meaningful putative molecular formulas for each fragment ion, which in turn also helped determine the elemental composition of the precursor ion. Compared to laborious manual analysis of the MS/MS spectra, the presented algorithm marks an important step toward efficient fragment signal elucidation and structure annotation of metabolites in future untargeted metabolomics studies. Moreover, as demonstrated for a fungal culture sample, FragExtract also assists the characterization of unknown metabolites, which are not contained in databases, and thus exhibits a significant contribution to untargeted metabolomics research. PMID:24965664

Evolution of the metabolome in response to selection for increased immunity in populations of Drosophila melanogaster.

PubMed

Gogna, Navdeep; Sharma, Rakesh; Gupta, Vanika; Dorai, Kavita; Prasad, N G

2017-01-01

We used NMR-based metabolomics to test two hypotheses-(i) there will be evolved differences in the metabolome of selected and control populations even under un-infected conditions and (ii) post infection, the metabolomes of the selected and control populations will respond differently. We selected replicate populations of Drosophila melanogaster for increased survivorship (I) against a gram-negative pathogen. We subjected the selected (I) and their control populations (S) to three different treatments: (1) infected with heat-killed bacteria (i), (2) sham infected (s), and (3) untreated (u). We performed 1D and 2D NMR experiments to identify the metabolic differences. Multivariate analysis of the metabolic profiles of the untreated (Iu and Su) flies yielded higher concentrations of lipids, organic acids, sugars, amino acids, NAD and AMP in the Iu treatment as compared to the Su treatment, showing that even in the absence of infection, the metabolome of the I and S regimes was different. In the S and I regimes, post infection/injury, concentration of metabolites directly or indirectly associated with energy related pathways (lipids, organic acids, sugars) declined while the concentration of metabolites that are probably associated with immune response (amino acids) increased. However, in most cases, the I regime flies had a higher concentration of such metabolites even under un-infected conditions. The change in the metabolite concentration upon infection/injury was not always comparable between I and S regimes (in case of lactate, alanine, leucine, lysine, threonine) indicating that the I and S regimes had evolved to respond differentially to infection and to injury.

1H NMR Metabolomics: A New Molecular Level Tool for Assessment of Organic Contaminant Bioavailability to Earthworms in Soil

NASA Astrophysics Data System (ADS)

McKelvie, J. R.; Wolfe, D. M.; Celejewski, M. A.; Simpson, A. J.; Simpson, M. J.

2009-05-01

At contaminated field sites, the complete removal of polycyclic aromatic hydrocarbons (PAHs) is rarely achieved since a portion of these compounds remain tightly bound to the soil matrix. The concentration of PAHs in soil typically decreases until a plateau is reached, at which point the remaining contaminant is considered non- bioavailable. Numerous soil extraction techniques, including cyclodextrin extraction, have been developed to estimate contaminant bioavailability. However, these are indirect methods that do not directly measure the response of organisms to chemical exposure in soil. Earthworm metabolomics offers a promising new way to directly evaluate the bioavailability and toxicity of contaminants in soil. Metabolomics involves the measurement of changes in small-molecule metabolites, including sugars and amino acids, in living organisms due to an external stress, such as contaminant exposure. The objective of this study was to compare cyclodextrin extraction of soil (a bioavailability proxy) and 1H NMR metabolomic analysis of aqueous earthworm tissue extracts as indicators of contaminant bioavailability. A 30 day laboratory experiment was conducted using phenanthrene-spiked sphagnum peat soil and the OECD recommended earthworm species for toxicity testing, Eisenia fetida. The initial phenanthrene concentration in the soil was 320 mg/kg. Rapid biodegradation of phenanthrene occurred and concentrations decreased to 16 mg/kg within 15 days. After 15 days, phenanthrene biodegradation slowed and cyclodextrin extraction of the soil suggested that phenanthrene was no longer bioavailable. Multivariate statistical analysis of the 1H NMR spectra for E. fetida tissue extracts indicated that the metabolic profile of phenanthrene exposed earthworms differed from control earthworms throughout the 30 day experiment. This suggests that the residual phenanthrene remaining in the soil after 15 days continued to elicit a metabolic response, even though it was not extractable using cyclodextrin. Hence, while cyclodextrin extraction may serve as a good proxy for microbial bioavailability, our results suggest that it may not serve as a good proxy for earthworm bioavailability. 1H NMR metabolomics therefore offers considerable promise as a novel, molecular-level method to directly monitor earthworm bioavailability of potentially toxic and persistent compounds in the environment.

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

PubMed Central

Liu, Xiaojing; Ser, Zheng; Cluntun, Ahmad A.; Mentch, Samantha J.; Locasale, Jason W.

2014-01-01

Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. However, current platforms have different limiting factors, such as labor intensive sample preparations, low detection limits, slow scan speeds, intensive method optimization for each metabolite, and the inability to measure both positively and negatively charged ions in single experiments. Therefore, a novel metabolomics protocol could advance metabolomics studies. Amide-based hydrophilic chromatography enables polar metabolite analysis without any chemical derivatization. High resolution MS using the Q-Exactive (QE-MS) has improved ion optics, increased scan speeds (256 msec at resolution 70,000), and has the capability of carrying out positive/negative switching. Using a cold methanol extraction strategy, and coupling an amide column with QE-MS enables robust detection of 168 targeted polar metabolites and thousands of additional features simultaneously.  Data processing is carried out with commercially available software in a highly efficient way, and unknown features extracted from the mass spectra can be queried in databases. PMID:24894601

A Metabolomic Approach to the Study of Wine Micro-Oxygenation

PubMed Central

Arapitsas, Panagiotis; Scholz, Matthias; Vrhovsek, Urska; Di Blasi, Stefano; Biondi Bartolini, Alessandra; Masuero, Domenico; Perenzoni, Daniele; Rigo, Adelio; Mattivi, Fulvio

2012-01-01

Wine micro-oxygenation is a globally used treatment and its effects were studied here by analysing by untargeted LC-MS the wine metabolomic fingerprint. Eight different procedural variations, marked by the addition of oxygen (four levels) and iron (two levels) were applied to Sangiovese wine, before and after malolactic fermentation. Data analysis using supervised and unsupervised multivariate methods highlighted some known candidate biomarkers, together with a number of metabolites which had never previously been considered as possible biomarkers for wine micro-oxygenation. Various pigments and tannins were identified among the known candidate biomarkers. Additional new information was obtained suggesting a correlation between oxygen doses and metal contents and changes in the concentration of primary metabolites such as arginine, proline, tryptophan and raffinose, and secondary metabolites such as succinic acid and xanthine. Based on these findings, new hypotheses regarding the formation and reactivity of wine pigment during micro-oxygenation have been proposed. This experiment highlights the feasibility of using unbiased, untargeted metabolomic fingerprinting to improve our understanding of wine chemistry. PMID:22662221

A Multiplatform Metabolomic Approach to the Basis of Antimonial Action and Resistance in Leishmania infantum

PubMed Central

Castilho-Martins, Emerson A.; Tavares, Marina F. M.; Barbas, Coral; López-Gonzálvez, Ángeles; Rivas, Luis

2015-01-01

There is a rising resistance against antimony drugs, the gold-standard for treatment until some years ago. That is a serious problem due to the paucity of drugs in current clinical use. In a research to reveal how these drugs affect the parasite during treatment and to unravel the underlying basis for their resistance, we have employed metabolomics to study treatment in Leishmania infantum promastigotes. This was accomplished first through the untargeted analysis of metabolic snapshots of treated and untreated parasites both resistant and responders, utilizing a multiplatform approach to give the widest as possible coverage of the metabolome, and additionally through novel monitoring of the origin of the detected alterations through a 13C traceability experiment. Our data stress a multi-target metabolic alteration with treatment, affecting in particular the cell redox system that is essential to cope with detoxification and biosynthetic processes. Additionally, relevant changes were noted in amino acid metabolism. Our results are in agreement with other authors studying other Leishmania species. PMID:26161866

Informatics for Metabolomics.

PubMed

Kusonmano, Kanthida; Vongsangnak, Wanwipa; Chumnanpuen, Pramote

2016-01-01

Metabolome profiling of biological systems has the powerful ability to provide the biological understanding of their metabolic functional states responding to the environmental factors or other perturbations. Tons of accumulative metabolomics data have thus been established since pre-metabolomics era. This is directly influenced by the high-throughput analytical techniques, especially mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based techniques. Continuously, the significant numbers of informatics techniques for data processing, statistical analysis, and data mining have been developed. The following tools and databases are advanced for the metabolomics society which provide the useful metabolomics information, e.g., the chemical structures, mass spectrum patterns for peak identification, metabolite profiles, biological functions, dynamic metabolite changes, and biochemical transformations of thousands of small molecules. In this chapter, we aim to introduce overall metabolomics studies from pre- to post-metabolomics era and their impact on society. Directing on post-metabolomics era, we provide a conceptual framework of informatics techniques for metabolomics and show useful examples of techniques, tools, and databases for metabolomics data analysis starting from preprocessing toward functional interpretation. Throughout the framework of informatics techniques for metabolomics provided, it can be further used as a scaffold for translational biomedical research which can thus lead to reveal new metabolite biomarkers, potential metabolic targets, or key metabolic pathways for future disease therapy.

Enhancement of gama-aminobutyric acid (GABA) and other health-related metabolites in germinated red rice (Oryza sativa L.) by ultrasonication.

PubMed

Ding, Junzhou; Ulanov, Alexander V; Dong, Mengyi; Yang, Tewu; Nemzer, Boris V; Xiong, Shanbai; Zhao, Siming; Feng, Hao

2018-01-01

Red rice (Oryza sativa L.) that has a red (reddish brown) bran layer in de-hulled rice is known to contain rich biofunctional components. Germination is an effective technique to improve the nutritional quality, digestibility, and flavor of de-hulled rice. Ultrasonication, a form of physical stimulation, has been documented as a novel approach to improve the nutritional quality of plant-based food. This study was undertaken to test the use of ultrasound to enhance the nutritional value of red rice. Ultrasonication (5min, 16W/L) was applied to rice during soaking or after 66h germination. Changes of metabolites (amino acids, sugars, and organic acids) in red rice treated by ultrasonication were determined using a GC/MS plant primary metabolomics analysis platform. Differential expressed metabolites were identified through multivariate statistical analysis. Results showed that γ-aminobutyric acid (GABA) and riboflavin (vitamin B 2 ) in red rice significantly increased after germination for 72h, and then experienced a further increase after treatment by ultrasound at different stages during germination. The metabolomics analysis showed that some plant metabolites, i.e. GABA, O-phosphoethanolamine, and glucose-6-phosphate were significantly increased after the ultrasonic treatment (VIP>1.5) in comparison with the untreated germinated rice. The findings of this study showed that controlled germination with ultrasonic stress is an effective method to enhance GABA and other health-promoted components in de-hulled rice. Copyright © 2017 Elsevier B.V. All rights reserved.

Metabolic responses of willow (Salix purpurea L.) leaves to mycorrhization as revealed by mass spectrometry and 1H NMR spectroscopy metabolite profiling

PubMed Central

Aliferis, Konstantinos A.; Chamoun, Rony; Jabaji, Suha

2015-01-01

The root system of most terrestrial plants form symbiotic interfaces with arbuscular mycorrhizal fungi (AMF), which are important for nutrient cycling and ecosystem sustainability. The elucidation of the undergoing changes in plants' metabolism during symbiosis is essential for understanding nutrient acquisition and for alleviation of soil stresses caused by environmental cues. Within this context, we have undertaken the task of recording the fluctuation of willow (Salix purpurea L.) leaf metabolome in response to AMF inoculation. The development of an advanced metabolomics/bioinformatics protocol employing mass spectrometry (MS) and 1H NMR analyzers combined with the in-house-built metabolite library for willow (http://willowmetabolib.research.mcgill.ca/index.html) are key components of the research. Analyses revealed that AMF inoculation of willow causes up-regulation of various biosynthetic pathways, among others, those of flavonoid, isoflavonoid, phenylpropanoid, and the chlorophyll and porphyrin pathways, which have well-established roles in plant physiology and are related to resistance against environmental stresses. The recorded fluctuation in the willow leaf metabolism is very likely to provide AMF-inoculated willows with a significant advantage compared to non-inoculated ones when they are exposed to stresses such as, high levels of soil pollutants. The discovered biomarkers of willow response to AMF inoculation and corresponding pathways could be exploited in biomarker-assisted selection of willow cultivars with superior phytoremediation capacity or genetic engineering programs. PMID:26042135

RAPTOR controls developmental growth transitions by altering the hormonal and metabolic balance.

PubMed

Salem, Mohamed A; Li, Yan; Bajdzienko, Krzysztof; Fisahn, Joachim; Watanabe, Mutsumi; Hoefgen, Rainer; Schöttler, Mark Aurel; Giavalisco, Patrick

2018-04-23

Vegetative growth requires the systemic coordination of numerous cellular processes, which are controlled by regulatory proteins that monitor extra- and intra-cellular cues and translate them into growth decisions. In eukaryotes, one of the central factors regulating growth is the Ser/Thr protein kinase Target of Rapamycin (TOR), which forms complexes with regulatory proteins. To understand the function of one such regulatory protein, Regulatory-Associated Protein of TOR 1B (RAPTOR1B) in plants, we analyzed the effect of raptor1b mutations on growth and physiology in Arabidopsis thaliana by detailed phenotyping, metabolomic, lipidomic, and proteomic analysis. Mutation of RAPTR1B resulted in a strong reduction of TOR kinase activity, leading to massive changes in central carbon and nitrogen metabolism, accumulation of excess starch, and induction of autophagy. These shifts led to a significant, reduction of plant growth that occurred non-linearly during developmental stage transtions.. This phenotype was accompanied by changes in cell morphology and tissue anatomy. In contrast to previous studies in rice, we found that the Arabidopsis raptor1b mutation did not affect chloroplast development or photosynthetic electron transport efficiency; however, it resulted in decreased CO2 assimilation rate and increased stomatal conductance. The raptor1b mutants also had reduced abscisic acid levels. Surprisingly, ABA feeding experiments resulted in partial complementation of the growth phenotypes, indicating the tight interaction between TOR function and hormone synthesis and signaling in plants. {copyright, serif} 2018 American Society of Plant Biologists. All rights reserved.

NASA Space Biology Plant Research for 2010-2020

NASA Technical Reports Server (NTRS)

Levine, H. G.; Tomko, D. L.; Porterfield, D. M.

2012-01-01

The U.S. National Research Council (NRC) recently published "Recapturing a Future for Space Exploration: Life and Physical Sciences Research for a New Era" (http://www.nap.edu/catalog.php?record id=13048), and NASA completed a Space Biology Science Plan to develop a strategy for implementing its recommendations ( http://www.nasa.gov/exploration/library/esmd documents.html). The most important recommendations of the NRC report on plant biology in space were that NASA should: (1) investigate the roles of microbial-plant systems in long-term bioregenerative life support systems, and (2) establish a robust spaceflight program of research analyzing plant growth and physiological responses to the multiple stimuli encountered in spaceflight environments. These efforts should take advantage of recently emerged analytical technologies (genomics, transcriptomics, proteomics, metabolomics) and apply modern cellular and molecular approaches in the development of a vigorous flight-based and ground-based research program. This talk will describe NASA's strategy and plans for implementing these NRC Plant Space Biology recommendations. New research capabilities for Plant Biology, optimized by providing state-of-the-art automated technology and analytical techniques to maximize scientific return, will be described. Flight experiments will use the most appropriate platform to achieve science results (e.g., ISS, free flyers, sub-orbital flights) and NASA will work closely with its international partners and other U.S. agencies to achieve its objectives. One of NASA's highest priorities in Space Biology is the development research capabilities for use on the International Space Station and other flight platforms for studying multiple generations of large plants. NASA will issue recurring NASA Research Announcements (NRAs) that include a rapid turn-around model to more fully engage the biology community in designing experiments to respond to the NRC recommendations. In doing so, NASA's Space Biology research will optimize ISS research utilization, develop and demonstrate technology and hardware that will enable new science, and contribute to the base of fundamental knowledge that will facilitate development of new tools for human space exploration and Earth applications. By taking these steps, NASA will energize the Space Biology user community and advance our knowledge of the effect of the space flight environment on living systems.

Chemometric and biological validation of a capillary electrophoresis metabolomic experiment of Schistosoma mansoni infection in mice.

PubMed

Garcia-Perez, Isabel; Angulo, Santiago; Utzinger, Jürg; Holmes, Elaine; Legido-Quigley, Cristina; Barbas, Coral

2010-07-01

Metabonomic and metabolomic studies are increasingly utilized for biomarker identification in different fields, including biology of infection. The confluence of improved analytical platforms and the availability of powerful multivariate analysis software have rendered the multiparameter profiles generated by these omics platforms a user-friendly alternative to the established analysis methods where the quality and practice of a procedure is well defined. However, unlike traditional assays, validation methods for these new multivariate profiling tools have yet to be established. We propose a validation for models obtained by CE fingerprinting of urine from mice infected with the blood fluke Schistosoma mansoni. We have analysed urine samples from two sets of mice infected in an inter-laboratory experiment where different infection methods and animal husbandry procedures were employed in order to establish the core biological response to a S. mansoni infection. CE data were analysed using principal component analysis. Validation of the scores consisted of permutation scrambling (100 repetitions) and a manual validation method, using a third of the samples (not included in the model) as a test or prediction set. The validation yielded 100% specificity and 100% sensitivity, demonstrating the robustness of these models with respect to deciphering metabolic perturbations in the mouse due to a S. mansoni infection. A total of 20 metabolites across the two experiments were identified that significantly discriminated between S. mansoni-infected and noninfected control samples. Only one of these metabolites, allantoin, was identified as manifesting different behaviour in the two experiments. This study shows the reproducibility of CE-based metabolic profiling methods for disease characterization and screening and highlights the importance of much needed validation strategies in the emerging field of metabolomics.

Functional Analysis of Metabolomics Data.

PubMed

Chagoyen, Mónica; López-Ibáñez, Javier; Pazos, Florencio

2016-01-01

Metabolomics aims at characterizing the repertory of small chemical compounds in a biological sample. As it becomes more massive and larger sets of compounds are detected, a functional analysis is required to convert these raw lists of compounds into biological knowledge. The most common way of performing such analysis is "annotation enrichment analysis," also used in transcriptomics and proteomics. This approach extracts the annotations overrepresented in the set of chemical compounds arisen in a given experiment. Here, we describe the protocols for performing such analysis as well as for visualizing a set of compounds in different representations of the metabolic networks, in both cases using free accessible web tools.

The Human Urine Metabolome

PubMed Central

Bouatra, Souhaila; Aziat, Farid; Mandal, Rupasri; Guo, An Chi; Wilson, Michael R.; Knox, Craig; Bjorndahl, Trent C.; Krishnamurthy, Ramanarayan; Saleem, Fozia; Liu, Philip; Dame, Zerihun T.; Poelzer, Jenna; Huynh, Jessica; Yallou, Faizath S.; Psychogios, Nick; Dong, Edison; Bogumil, Ralf; Roehring, Cornelia; Wishart, David S.

2013-01-01

Urine has long been a “favored” biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS), direct flow injection mass spectrometry (DFI/LC-MS/MS), inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify) a total of: 209 (209) by NMR, 179 (85) by GC-MS, 127 (127) by DFI/LC-MS/MS, 40 (40) by ICP-MS and 10 (10) by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database containing the complete set of 2651 confirmed human urine metabolite species, their structures (3079 in total), concentrations, related literature references and links to their known disease associations are freely available at http://www.urinemetabolome.ca. PMID:24023812

Dissemination of metabolomics results: role of MetaboLights and COSMOS.

PubMed

Salek, Reza M; Haug, Kenneth; Steinbeck, Christoph

2013-05-17

With ever-increasing amounts of metabolomics data produced each year, there is an even greater need to disseminate data and knowledge produced in a standard and reproducible way. To assist with this a general purpose, open source metabolomics repository, MetaboLights, was launched in 2012. To promote a community standard, initially culminated as metabolomics standards initiative (MSI), COordination of Standards in MetabOlomicS (COSMOS) was introduced. COSMOS aims to link life science e-infrastructures within the worldwide metabolomics community as well as develop and maintain open source exchange formats for raw and processed data, ensuring better flow of metabolomics information.

UPLC-MS for metabolomics: a giant step forward in support of pharmaceutical research.

PubMed

Nassar, Ala F; Wu, Terence; Nassar, Samuel F; Wisnewski, Adam V

2017-02-01

Metabolomics is a relatively new and rapidly growing area of post-genomic biological research. As use of metabolomics technology grows throughout the spectrum of drug discovery and development, and its applications broaden, its impact is expanding dramatically. This review seeks to provide the reader with a brief history of the development of metabolomics, its significance and strategies for conducting metabolomics studies. The most widely used analytical tools for metabolomics: NMR, LC-MS and GC-MS, are discussed along with considerations for their use. Herein, we will show how metabolomics can assist in pharmaceutical research studies, such as pharmacology and toxicology, and discuss some examples of the importance of metabolomics analysis in research and development. Copyright © 2016 Elsevier Ltd. All rights reserved.

UPLC/Q-TOF MS-Based Metabolomics and qRT-PCR in Enzyme Gene Screening with Key Role in Triterpenoid Saponin Biosynthesis of Polygala tenuifolia

PubMed Central

Li, Zhenyu; Xu, Xiaoshuang; Peng, Bing; Qin, Xuemei; Du, Guanhua

2014-01-01

Background The dried root of Polygala tenuifolia, named Radix Polygalae, is a well-known traditional Chinese medicine. Triterpenoid saponins are some of the most important components of Radix Polygalae extracts and are widely studied because of their valuable pharmacological properties. However, the relationship between gene expression and triterpenoid saponin biosynthesis in P. tenuifolia is unclear. Methodology/Findings In this study, ultra-performance liquid chromatography (UPLC) coupled with quadrupole time-of-flight mass spectrometry (Q-TOF MS)-based metabolomic analysis was performed to identify and quantify the different chemical constituents of the roots, stems, leaves, and seeds of P. tenuifolia. A total of 22 marker compounds (VIP>1) were explored, and significant differences in all 7 triterpenoid saponins among the different tissues were found. We also observed an efficient reference gene GAPDH for different tissues in this plant and determined the expression level of some genes in the triterpenoid saponin biosynthetic pathway. Results showed that MVA pathway has more important functions in the triterpenoid saponin biosynthesis of P. tenuifolia. The expression levels of squalene synthase (SQS), squalene monooxygenase (SQE), and beta-amyrin synthase (β-AS) were highly correlated with the peak area intensity of triterpenoid saponins compared with data from UPLC/Q-TOF MS-based metabolomic analysis. Conclusions/Significance This finding suggested that a combination of UPLC/Q-TOF MS-based metabolomics and gene expression analysis can effectively elucidate the mechanism of triterpenoid saponin biosynthesis and can provide useful information on gene discovery. These findings can serve as a reference for using the overexpression of genes encoding for SQS, SQE, and/or β-AS to increase the triterpenoid saponin production of P. tenuifolia. PMID:25148032

High-level adherence to a Mediterranean diet beneficially impacts the gut microbiota and associated metabolome.

PubMed

De Filippis, Francesca; Pellegrini, Nicoletta; Vannini, Lucia; Jeffery, Ian B; La Storia, Antonietta; Laghi, Luca; Serrazanetti, Diana I; Di Cagno, Raffaella; Ferrocino, Ilario; Lazzi, Camilla; Turroni, Silvia; Cocolin, Luca; Brigidi, Patrizia; Neviani, Erasmo; Gobbetti, Marco; O'Toole, Paul W; Ercolini, Danilo

2016-11-01

Habitual diet plays a major role in shaping the composition of the gut microbiota, and also determines the repertoire of microbial metabolites that can influence the host. The typical Western diet corresponds to that of an omnivore; however, the Mediterranean diet (MD), common in the Western Mediterranean culture, is to date a nutritionally recommended dietary pattern that includes high-level consumption of cereals, fruit, vegetables and legumes. To investigate the potential benefits of the MD in this cross-sectional survey, we assessed the gut microbiota and metabolome in a cohort of Italian individuals in relation to their habitual diets. We retrieved daily dietary information and assessed gut microbiota and metabolome in 153 individuals habitually following omnivore, vegetarian or vegan diets. The majority of vegan and vegetarian subjects and 30% of omnivore subjects had a high adherence to the MD. We were able to stratify individuals according to both diet type and adherence to the MD on the basis of their dietary patterns and associated microbiota. We detected significant associations between consumption of vegetable-based diets and increased levels of faecal short-chain fatty acids, Prevotella and some fibre-degrading Firmicutes, whose role in human gut warrants further research. Conversely, we detected higher urinary trimethylamine oxide levels in individuals with lower adherence to the MD. High-level consumption of plant foodstuffs consistent with an MD is associated with beneficial microbiome-related metabolomic profiles in subjects ostensibly consuming a Western diet. This study was registered at clinical trials.gov as NCT02118857. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

UPLC/Q-TOF MS-based metabolomics and qRT-PCR in enzyme gene screening with key role in triterpenoid saponin biosynthesis of Polygala tenuifolia.

PubMed

Zhang, Fusheng; Li, Xiaowei; Li, Zhenyu; Xu, Xiaoshuang; Peng, Bing; Qin, Xuemei; Du, Guanhua

2014-01-01

The dried root of Polygala tenuifolia, named Radix Polygalae, is a well-known traditional Chinese medicine. Triterpenoid saponins are some of the most important components of Radix Polygalae extracts and are widely studied because of their valuable pharmacological properties. However, the relationship between gene expression and triterpenoid saponin biosynthesis in P. tenuifolia is unclear. In this study, ultra-performance liquid chromatography (UPLC) coupled with quadrupole time-of-flight mass spectrometry (Q-TOF MS)-based metabolomic analysis was performed to identify and quantify the different chemical constituents of the roots, stems, leaves, and seeds of P. tenuifolia. A total of 22 marker compounds (VIP>1) were explored, and significant differences in all 7 triterpenoid saponins among the different tissues were found. We also observed an efficient reference gene GAPDH for different tissues in this plant and determined the expression level of some genes in the triterpenoid saponin biosynthetic pathway. Results showed that MVA pathway has more important functions in the triterpenoid saponin biosynthesis of P. tenuifolia. The expression levels of squalene synthase (SQS), squalene monooxygenase (SQE), and beta-amyrin synthase (β-AS) were highly correlated with the peak area intensity of triterpenoid saponins compared with data from UPLC/Q-TOF MS-based metabolomic analysis. This finding suggested that a combination of UPLC/Q-TOF MS-based metabolomics and gene expression analysis can effectively elucidate the mechanism of triterpenoid saponin biosynthesis and can provide useful information on gene discovery. These findings can serve as a reference for using the overexpression of genes encoding for SQS, SQE, and/or β-AS to increase the triterpenoid saponin production of P. tenuifolia.

UPLC-QTOF analysis reveals metabolomic changes in the flag leaf of wheat (Triticum aestivum L.) under low-nitrogen stress.

PubMed

Zhang, Yang; Ma, Xin-Ming; Wang, Xiao-Chun; Liu, Ji-Hong; Huang, Bing-Yan; Guo, Xiao-Yang; Xiong, Shu-Ping; La, Gui-Xiao

2017-02-01

Wheat is one of the most important grain crop plants worldwide. Nitrogen (N) is an essential macronutrient for the growth and development of wheat and exerts a marked influence on its metabolites. To investigate the influence of low nitrogen stress on various metabolites of the flag leaf of wheat (Triticum aestivum L.), a metabolomic analysis of two wheat cultivars under different induced nitrogen levels was conducted during two important growth periods based on large-scale untargeted metabolomic analysis using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF). Multivariate analyses-such as principle components analysis (PCA) and orthogonal partial least square discriminant analysis (OPLS-DA)-were used for data analysis. PCA yielded distinctive clustering information among the samples, classifying the wheat flag samples into two categories: those under normal N treatment and low N treatment. By processing OPLS-DA, eleven secondary metabolites were shown to be responsible for classifying the two groups. The secondary metabolites may be considered potential biomarkers of low nitrogen stress. Chemical analyses showed that most of the identified secondary metabolites were flavonoids and their related derivatives, such as iso-vitexin, iso-orientin and methylisoorientin-2″-O-rhamnoside, etc. This study confirmed the effect of low nitrogen stress on the metabolism of wheat, and revealed that the accumulation of secondary metabolites is a response to abiotic stresses. Meanwhile, we aimed to identify markers which could be used to monitor the nitrogen status of wheat crops, presumably to guide appropriate fertilization regimens. Furthermore, the UPLC-QTOF metabolic platform technology can be used to study metabolomic variations of wheat under abiotic stresses. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Quantitative and qualitative shifts in defensive metabolites define chemical defense investment during leaf development in Inga, a genus of tropical trees.

PubMed

Wiggins, Natasha L; Forrister, Dale L; Endara, María-José; Coley, Phyllis D; Kursar, Thomas A

2016-01-01

Selective pressures imposed by herbivores are often positively correlated with investments that plants make in defense. Research based on the framework of an evolutionary arms race has improved our understanding of why the amount and types of defenses differ between plant species. However, plant species are exposed to different selective pressures during the life of a leaf, such that expanding leaves suffer more damage from herbivores and pathogens than mature leaves. We hypothesize that this differential selective pressure may result in contrasting quantitative and qualitative defense investment in plants exposed to natural selective pressures in the field. To characterize shifts in chemical defenses, we chose six species of Inga, a speciose Neotropical tree genus. Focal species represent diverse chemical, morphological, and developmental defense traits and were collected from a single site in the Amazonian rainforest. Chemical defenses were measured gravimetrically and by characterizing the metabolome of expanding and mature leaves. Quantitative investment in phenolics plus saponins, the major classes of chemical defenses identified in Inga, was greater for expanding than mature leaves (46% and 24% of dry weight, respectively). This supports the theory that, because expanding leaves are under greater selective pressure from herbivores, they rely more upon chemical defense as an antiherbivore strategy than do mature leaves. Qualitatively, mature and expanding leaves were distinct and mature leaves contained more total and unique metabolites. Intraspecific variation was greater for mature leaves than expanding leaves, suggesting that leaf development is canalized. This study provides a snapshot of chemical defense investment in a speciose genus of tropical trees during the short, few-week period of leaf development. Exploring the metabolome through quantitative and qualitative profiling enables a more comprehensive examination of foliar chemical defense investment.

Metabolomics and Epidemiology Working Group

Cancer.gov

The Metabolomics and Epidemiology (MetEpi) Working Group promotes metabolomics analyses in population-based studies, as well as advancement in the field of metabolomics for broader biomedical and public health research.

Dissemination of metabolomics results: role of MetaboLights and COSMOS

PubMed Central

2013-01-01

With ever-increasing amounts of metabolomics data produced each year, there is an even greater need to disseminate data and knowledge produced in a standard and reproducible way. To assist with this a general purpose, open source metabolomics repository, MetaboLights, was launched in 2012. To promote a community standard, initially culminated as metabolomics standards initiative (MSI), COordination of Standards in MetabOlomicS (COSMOS) was introduced. COSMOS aims to link life science e-infrastructures within the worldwide metabolomics community as well as develop and maintain open source exchange formats for raw and processed data, ensuring better flow of metabolomics information. PMID:23683662

Phenylpropanoid Defences in Nicotiana tabacum Cells: Overlapping Metabolomes Indicate Common Aspects to Priming Responses Induced by Lipopolysaccharides, Chitosan and Flagellin-22

PubMed Central

Mhlongo, Msizi I.; Piater, Lizelle A.; Madala, Ntakadzeni E.; Steenkamp, Paul A.; Dubery, Ian A.

2016-01-01

Plants have evolved both constitutive and inducible defence strategies to cope with different biotic stimuli and stresses. Exposure of a plant to a challenging stress can lead to a primed state that allows it to launch a more rapid and stronger defence. Here we applied a metabolomic approach to study and compare the responses induced in Nicotiana tabacum cells by microbe-associated molecular pattern (MAMP) molecules, namely lipopolysaccharides (LPS), chitosan (CHT) and flagellin-22 (FLG22). Early response metabolites, extracted with methanol, were analysed by UHPLC-MS/MS. Using multivariate statistical tools the metabolic profiles induced by these elicitors were analysed. In the metabolic fingerprint of these agents a total of 19 cinnamic acid derivatives conjugated to quinic acids (chlorogenic acids), shikimic acid, tyramine, polyamines or glucose were found as discriminant biomarkers. In addition, treatment with the phytohormones salicylic acid (SA), methyljasmonic acid (MJ) and abscisic acid (ABA) resulted in differentially-induced phenylpropanoid pathway metabolites. The results indicate that the phenylpropanoid pathway is activated by these elicitors while hydroxycinnamic acid derivatives are commonly associated with the metabolic response to the MAMPs, and that the activated responses are modulated by both SA and MJ, with ABA not playing a role. PMID:26978774

1H-NMR metabolomic profiling reveals a distinct metabolic recovery response in shoots and roots of temporarily drought-stressed sugar beets

PubMed Central

Maucourt, Mickaël; Deborde, Catherine; Moing, Annick; Gibon, Yves; Goldbach, Heiner E.; Wimmer, Monika A.

2018-01-01

Yield formation in regions with intermittent drought periods depends on the plant’s ability to recover after cessation of the stress. The present work assessed differences in metabolic recovery of leaves and roots of drought-stressed sugar beets with high temporal resolution. Plants were subjected to drought for 13 days, and rewatered for 12 days. At one to two-day intervals, plant material was harvested for untargeted 1H-NMR metabolomic profiling, targeted analyses of hexose-phosphates, starch, amino acids, nitrate and proteins, and physiological measurements including relative water content, osmotic potential, electrolyte leakage and malondialdehyde concentrations. Drought triggered changes in primary metabolism, especially increases in amino acids in both organs, but leaves and roots responded with different dynamics to rewatering. After a transient normalization of most metabolites within 8 days, a second accumulation of amino acids in leaves might indicate a stress imprint beneficial in upcoming drought events. Repair mechanisms seemed important during initial recovery and occurred at the expense of growth for at least 12 days. These results indicate that organ specific metabolic recovery responses might be related to distinct functions and concomitant disparate stress levels in above- and belowground organs. With respect to metabolism, recovery was not simply a reversal of the stress responses. PMID:29738573

Matrix assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) for direct visualization of plant metabolites in situ

DOE PAGES

Sturtevant, Drew; Lee, Young -Jin; Chapman, Kent D.

2015-11-22

Direct visualization of plant tissues by matrix assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) has revealed key insights into the localization of metabolites in situ. Recent efforts have determined the spatial distribution of primary and secondary metabolites in plant tissues and cells. Strategies have been applied in many areas of metabolism including isotope flux analyses, plant interactions, and transcriptional regulation of metabolite accumulation. Technological advances have pushed achievable spatial resolution to subcellular levels and increased instrument sensitivity by several orders of magnitude. Furthermore, it is anticipated that MALDI-MSI and other MSI approaches will bring a new level of understanding tomore » metabolomics as scientists will be encouraged to consider spatial heterogeneity of metabolites in descriptions of metabolic pathway regulation.« less

Matrix assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) for direct visualization of plant metabolites in situ

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sturtevant, Drew; Lee, Young -Jin; Chapman, Kent D.

Direct visualization of plant tissues by matrix assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) has revealed key insights into the localization of metabolites in situ. Recent efforts have determined the spatial distribution of primary and secondary metabolites in plant tissues and cells. Strategies have been applied in many areas of metabolism including isotope flux analyses, plant interactions, and transcriptional regulation of metabolite accumulation. Technological advances have pushed achievable spatial resolution to subcellular levels and increased instrument sensitivity by several orders of magnitude. Furthermore, it is anticipated that MALDI-MSI and other MSI approaches will bring a new level of understanding tomore » metabolomics as scientists will be encouraged to consider spatial heterogeneity of metabolites in descriptions of metabolic pathway regulation.« less

The future of metabolomics in ELIXIR

PubMed Central

van Rijswijk, Merlijn; Beirnaert, Charlie; Caron, Christophe; Cascante, Marta; Dominguez, Victoria; Dunn, Warwick B.; Ebbels, Timothy M. D.; Giacomoni, Franck; Gonzalez-Beltran, Alejandra; Hankemeier, Thomas; Haug, Kenneth; Izquierdo-Garcia, Jose L.; Jimenez, Rafael C.; Jourdan, Fabien; Kale, Namrata; Klapa, Maria I.; Kohlbacher, Oliver; Koort, Kairi; Kultima, Kim; Le Corguillé, Gildas; Moreno, Pablo; Moschonas, Nicholas K.; Neumann, Steffen; O’Donovan, Claire; Reczko, Martin; Rocca-Serra, Philippe; Rosato, Antonio; Salek, Reza M.; Sansone, Susanna-Assunta; Satagopam, Venkata; Schober, Daniel; Shimmo, Ruth; Spicer, Rachel A.; Spjuth, Ola; Thévenot, Etienne A.; Viant, Mark R.; Weber, Ralf J. M.; Willighagen, Egon L.; Zanetti, Gianluigi; Steinbeck, Christoph

2017-01-01

Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the “Future of metabolomics in ELIXIR” was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases. PMID:29043062

The future of metabolomics in ELIXIR.

PubMed

van Rijswijk, Merlijn; Beirnaert, Charlie; Caron, Christophe; Cascante, Marta; Dominguez, Victoria; Dunn, Warwick B; Ebbels, Timothy M D; Giacomoni, Franck; Gonzalez-Beltran, Alejandra; Hankemeier, Thomas; Haug, Kenneth; Izquierdo-Garcia, Jose L; Jimenez, Rafael C; Jourdan, Fabien; Kale, Namrata; Klapa, Maria I; Kohlbacher, Oliver; Koort, Kairi; Kultima, Kim; Le Corguillé, Gildas; Moreno, Pablo; Moschonas, Nicholas K; Neumann, Steffen; O'Donovan, Claire; Reczko, Martin; Rocca-Serra, Philippe; Rosato, Antonio; Salek, Reza M; Sansone, Susanna-Assunta; Satagopam, Venkata; Schober, Daniel; Shimmo, Ruth; Spicer, Rachel A; Spjuth, Ola; Thévenot, Etienne A; Viant, Mark R; Weber, Ralf J M; Willighagen, Egon L; Zanetti, Gianluigi; Steinbeck, Christoph

2017-01-01

Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the "Future of metabolomics in ELIXIR" was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases.

Understanding Aquatic Rhizosphere Processes Through Metabolomics and Metagenomics Approach

NASA Astrophysics Data System (ADS)

Lee, Yong Jian; Mynampati, Kalyan; Drautz, Daniela; Arumugam, Krithika; Williams, Rohan; Schuster, Stephan; Kjelleberg, Staffan; Swarup, Sanjay

2013-04-01

The aquatic rhizosphere is a region around the roots of aquatic plants. Many studies focusing on terrestrial rhizosphere have led to a good understanding of the interactions between the roots, its exudates and its associated rhizobacteria. The rhizosphere of free-floating roots, however, is a different habitat that poses several additional challenges, including rapid diffusion rates of signals and nutrient molecules, which are further influenced by the hydrodynamic forces. These can lead to rapid diffusion and complicates the studying of diffusible factors from both plant and/or rhizobacterial origins. These plant systems are being increasingly used for self purification of water bodies to provide sustainable solution. A better understanding of these processes will help in improving their performance for ecological engineering of freshwater systems. The same principles can also be used to improve the yield of hydroponic cultures. Novel toolsets and approaches are needed to investigate the processes occurring in the aquatic rhizosphere. We are interested in understanding the interaction between root exudates and the complex microbial communities that are associated with the roots, using a systems biology approach involving metabolomics and metagenomics. With this aim, we have developed a RhizoFlowCell (RFC) system that provides a controlled study of aquatic plants, observed the root biofilms, collect root exudates and subject the rhizosphere system to changes in various chemical or physical perturbations. As proof of concept, we have used RFC to test the response of root exudation patterns of Pandanus amaryllifolius after exposure to the pollutant naphthalene. Complexity of root exudates in the aquatic rhizosphere was captured using this device and analysed using LC-qTOF-MS. The highly complex metabolomic profile allowed us to study the dynamics of the response of roots to varying levels of naphthalene. The metabolic profile changed within 5mins after spiking with 20mg/L of naphthalene and reached a new steady state within 72 hours. An active microbial biofilm was formed during this process, which was imaged by light microscopy and confocal laser scanning microscopy and showed active changes in the biofilm. We have begun to unravel the complexity of rhizobacterial communities associated with aquatic plants. Using fluorescence in-situ hybridization (FISH) and Illumina Miseq Next Generation Sequencing of metagenomic DNA, we investigated the root-associated microbial community of P. amaryllifolius grown in two different water sources. The community structure of rhizobacteria from plants grown in freshwater lake or rainwater stored in tanks are highly similar. The top three phyla in both setups belonged to Proteobacteria, Bacteriocedes and Actinobacteria, as validated by FISH analyses. This suggests that the rhizosphere have an innate ability to attract and recruit rhizobacterial communities, possibly through the metabolic compounds secreted through root exudation. The selection pressure through plant host is higher compared to environmental pressures that are different between the two water sources. In comparison with the terrestrial rhizosphere, the aquatic rhizosphere microbiome seems more specialised and has a high influence by the host. We are using these findings to further understand the role of microbes in the performance of freshwater aquatic plants.

Enabling Efficient and Confident Annotation of LC−MS Metabolomics Data through MS1 Spectrum and Time Prediction

DOE PAGES

Broeckling, Corey D.; Ganna, Andrea; Layer, Mark; ...

2016-09-08

Liquid chromatography coupled to electrospray ionization-mass spectrometry (LC–ESI-MS) is a versatile and robust platform for metabolomic analysis. However, while ESI is a soft ionization technique, in-source phenomena including multimerization, nonproton cation adduction, and in-source fragmentation complicate interpretation of MS data. Here, we report chromatographic and mass spectrometric behavior of 904 authentic standards collected under conditions identical to a typical nontargeted profiling experiment. The data illustrate that the often high level of complexity in MS spectra is likely to result in misinterpretation during the annotation phase of the experiment and a large overestimation of the number of compounds detected. However, ourmore » analysis of this MS spectral library data indicates that in-source phenomena are not random but depend at least in part on chemical structure. These nonrandom patterns enabled predictions to be made as to which in-source signals are likely to be observed for a given compound. Using the authentic standard spectra as a training set, we modeled the in-source phenomena for all compounds in the Human Metabolome Database to generate a theoretical in-source spectrum and retention time library. A novel spectral similarity matching platform was developed to facilitate efficient spectral searching for nontargeted profiling applications. Taken together, this collection of experimental spectral data, predictive modeling, and informatic tools enables more efficient, reliable, and transparent metabolite annotation.« less

Enabling Efficient and Confident Annotation of LC-MS Metabolomics Data through MS1 Spectrum and Time Prediction

DOE PAGES

Broeckling, Corey D.; Ganna, Andrea; Layer, Mark; ...

2016-08-25

Liquid chromatography coupled to electrospray ionization-mass spectrometry (LC–ESI-MS) is a versatile and robust platform for metabolomic analysis. However, while ESI is a soft ionization technique, in-source phenomena including multimerization, nonproton cation adduction, and in-source fragmentation complicate interpretation of MS data. Here, we report chromatographic and mass spectrometric behavior of 904 authentic standards collected under conditions identical to a typical nontargeted profiling experiment. The data illustrate that the often high level of complexity in MS spectra is likely to result in misinterpretation during the annotation phase of the experiment and a large overestimation of the number of compounds detected. However, ourmore » analysis of this MS spectral library data indicates that in-source phenomena are not random but depend at least in part on chemical structure. These nonrandom patterns enabled predictions to be made as to which in-source signals are likely to be observed for a given compound. Using the authentic standard spectra as a training set, we modeled the in-source phenomena for all compounds in the Human Metabolome Database to generate a theoretical in-source spectrum and retention time library. A novel spectral similarity matching platform was developed to facilitate efficient spectral searching for nontargeted profiling applications. Taken together, this collection of experimental spectral data, predictive modeling, and informatic tools enables more efficient, reliable, and transparent metabolite annotation.« less

Effects of N source concentration and NH4(+)/NO3(-) ratio on phenylethanoid glycoside pattern in tissue cultures of Plantago lanceolata L.: a metabolomics driven full-factorial experiment with LC-ESI-MS(3.).

PubMed

Gonda, Sándor; Kiss-Szikszai, Attila; Szűcs, Zsolt; Máthé, Csaba; Vasas, Gábor

2014-10-01

Tissue cultures of a medicinal plant, Plantago lanceolata L. were screened for phenylethanoid glycosides (PGs) and other natural products (NPs) with LC-ESI-MS(3). The effects of N source concentration and NH4(+)/NO3(-) ratio were evaluated in a full-factorial (FF) experiment. N concentrations of 10, 20, 40 and 60mM, and NH4(+)/NO3(-) ratios of 0, 0.11, 0.20 and 0.33 (ratio of NH4(+) in total N source) were tested. Several peaks could be identified as PGs, of which, 16 could be putatively identified from the MS/MS/MS spectra. N source concentration and NH4(+)/NO3(-) ratio had significant effects on the metabolome, their effects on individual PGs were different despite these metabolites were of the same biosynthethic class. Chief PGs were plantamajoside and acteoside (verbascoside), their highest concentrations were 3.54±0.83% and 1.30±0.40% of dry weight, on media 10(0.33) and 40(0.33), respectively. NH4(+)/NO3(-) ratio and N source concentration effects were examined on a set of 89 NPs. For most NPs, high increases in abundance were observed compared to Murashige-Skoog medium. Abundances of 42 and 10 NPs were significantly influenced by the N source concentration and the NH4(+)/NO3(-) ratio, respectively. Optimal media for production of different NP clusters were 10(0), 10(0.11) and 40(0.33). Interaction was observed between NH4(+)/NO3(-) ratio and N source concentration for many NPs. It was shown in simulated experiments, that one-factor at a time (OFAT) experimental designs lead to sub-optimal media compositions for production of many NPs, and alternative experimental designs (e.g. FF) should be preferred when optimizing medium N source for optimal yield of NPs. If using OFAT, the N source concentration is to be optimized first, followed by NH4(+)/NO3(-) ratio, as this reduces the likeliness of suboptimal yield results. Copyright © 2014 Elsevier Ltd. All rights reserved.

Metabolomic characterization of laborers exposed to welding fumes.

PubMed

Wang, Kuo-Ching; Kuo, Ching-Hua; Tian, Tze-Feng; Tsai, Mong-Hsun; Chiung, Yin-Mei; Hsiech, Chun-Ming; Tsai, Sung-Jeng; Wang, San-Yuan; Tsai, Dong-Ming; Huang, Chiang-Ching; Tseng, Y Jane

2012-03-19

The complex composition of welding fumes, multiplicity of molecular targets, diverse cellular effects, and lifestyles associated with laborers vastly complicate the assessment of welding fume exposure. The urinary metabolomic profiles of 35 male welders and 16 male office workers at a Taiwanese shipyard were characterized via (1)H NMR spectroscopy and pattern recognition methods. Blood samples for the same 51 individuals were also collected, and the expression levels of the cytokines and other inflammatory markers were examined. This study dichotomized the welding exposure variable into high (welders) versus low (office workers) exposures to examine the differences of continuous outcome markers-metabolites and inflammatory markers-between the two groups. Fume particle assessments showed that welders were exposed to different concentrations of chromium, nickel, and manganese particles. Multivariate statistical analysis of urinary metabolomic patterns showed higher levels of glycine, taurine, betaine/TMAO, serine, S-sulfocysteine, hippurate, gluconate, creatinine, and acetone and lower levels of creatine among welders, while only TNF-α was significantly associated with welding fume exposure among all cytokines and other inflammatory markers measured. Of the identified metabolites, the higher levels of glycine, taurine, and betaine among welders were suspected to play some roles in modulating inflammatory and oxidative tissue injury processes. In this metabolomics experiment, we also discovered that the association of the identified metabolites with welding exposure was confounded by smoking, but not with drinking, which is a finding consistent with known modified response of inflammatory markers among smokers. Our results correspond with prior studies that utilized nonmetabolomic analytical techniques and suggest that the metabolomic profiling is an efficient method to characterize the overall effect of welding fume exposure and other confounders. © 2012 American Chemical Society

New findings on the in vivo antioxidant activity of Curcuma longa extract by an integrated (1)H NMR and HPLC-MS metabolomic approach.

PubMed

Dall'Acqua, Stefano; Stocchero, Matteo; Boschiero, Irene; Schiavon, Mariano; Golob, Samuel; Uddin, Jalal; Voinovich, Dario; Mammi, Stefano; Schievano, Elisabetta

2016-03-01

Curcuminoids possess powerful antioxidant activity as demonstrated in many chemical in vitro tests and in several in vivo trials. Nevertheless, the mechanism of this activity is not completely elucidated and studies on the in vivo antioxidant effects are still needed. Metabolomics may be used as an attractive approach for such studies and in this paper, we describe the effects of oral administration of a Curcuma longa L. extract (150 mg/kg of total curcuminoids) to 12 healthy rats with particular attention to urinary markers of oxidative stress. The experiment was carried out over 33 days and changes in the 24-h urine samples metabolome were evaluated by (1)H NMR and HPLC-MS. Both techniques produced similar representations for the collected samples confirming our previous study. Modifications of the urinary metabolome lead to the observation of different variables proving the complementarity of (1)H NMR and HPLC-MS for metabolomic purposes. The urinary levels of allantoin, m-tyrosine, 8-hydroxy-2'-deoxyguanosine, and nitrotyrosine were decreased in the treated group thus supporting an in vivo antioxidant effect of the oral administration of Curcuma extract to healthy rats. On the other hand, urinary TMAO levels were higher in the treated compared to the control group suggesting a role of curcumin supplementation on microbiota or on TMAO urinary excretion. Furthermore, the urinary levels of the sulphur containing compounds taurine and cystine were also changed suggesting a role for such constituents in the biochemical pathways involved in Curcuma extract bioactivity and indicating the need for further investigation on the complex role of antioxidant curcumin effects. Copyright © 2015 Elsevier B.V. All rights reserved.

Discovery and Characterization of the 3-Hydroxyacyl-ACP Dehydratase Component of the Plant Mitochondrial Fatty Acid Synthase System1[OPEN

PubMed Central

Okazaki, Yozo; Lithio, Andrew; Jin, Huanan

2017-01-01

We report the characterization of the Arabidopsis (Arabidopsis thaliana) 3-hydroxyacyl-acyl carrier protein dehydratase (mtHD) component of the mitochondrial fatty acid synthase (mtFAS) system, encoded by AT5G60335. The mitochondrial localization and catalytic capability of mtHD were demonstrated with a green fluorescent protein transgenesis experiment and by in vivo complementation and in vitro enzymatic assays. RNA interference (RNAi) knockdown lines with reduced mtHD expression exhibit traits typically associated with mtFAS mutants, namely a miniaturized morphological appearance, reduced lipoylation of lipoylated proteins, and altered metabolomes consistent with the reduced catalytic activity of lipoylated enzymes. These alterations are reversed when mthd-rnai mutant plants are grown in a 1% CO2 atmosphere, indicating the link between mtFAS and photorespiratory deficiency due to the reduced lipoylation of glycine decarboxylase. In vivo biochemical feeding experiments illustrate that sucrose and glycolate are the metabolic modulators that mediate the alterations in morphology and lipid accumulation. In addition, both mthd-rnai and mtkas mutants exhibit reduced accumulation of 3-hydroxytetradecanoic acid (i.e. a hallmark of lipid A-like molecules) and abnormal chloroplastic starch granules; these changes are not reversible by the 1% CO2 atmosphere, demonstrating two novel mtFAS functions that are independent of photorespiration. Finally, RNA sequencing analysis revealed that mthd-rnai and mtkas mutants are nearly equivalent to each other in altering the transcriptome, and these analyses further identified genes whose expression is affected by a functional mtFAS system but independent of photorespiratory deficiency. These data demonstrate the nonredundant nature of the mtFAS system, which contributes unique lipid components needed to support plant cell structure and metabolism. PMID:28202596

Grade-Dependent Metabolic Reprogramming in Kidney Cancer Revealed by Combined Proteomics and Metabolomics Analysis [Combined Proteomics and Metabolomics Analysis Reveals Grade-Dependent Metabolism Pathways in Kidney Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wettersten, Hiromi I.; Hakimi, A. Ari; Morin, Dexter

Kidney cancer [or renal cell carcinoma (RCC)] is known as “the internist's tumor” because it has protean systemic manifestations, suggesting that it utilizes complex, nonphysiologic metabolic pathways. Given the increasing incidence of this cancer and its lack of effective therapeutic targets, we undertook an extensive analysis of human RCC tissue employing combined grade-dependent proteomics and metabolomics analysis to determine how metabolic reprogramming occurring in this disease allows it to escape available therapeutic approaches. After validation experiments in RCC cell lines that were wild-type or mutant for the Von Hippel–Lindau tumor suppressor, in characterizing higher-grade tumors, we found that the Warburgmore » effect is relatively more prominent at the expense of the tricarboxylic acid cycle and oxidative metabolism in general. Further, we found that the glutamine metabolism pathway acts to inhibit reactive oxygen species, as evidenced by an upregulated glutathione pathway, whereas the β-oxidation pathway is inhibited, leading to increased fatty acylcarnitines. In support of findings from previous urine metabolomics analyses, we also documented tryptophan catabolism associated with immune suppression, which was highly represented in RCC compared with other metabolic pathways. Altogether, our results offer a rationale to evaluate novel antimetabolic treatment strategies being developed in other disease settings as therapeutic strategies in RCC« less

Differential Off-line LC-NMR (DOLC-NMR) Metabolomics To Monitor Tyrosine-Induced Metabolome Alterations in Saccharomyces cerevisiae.

PubMed

Hammerl, Richard; Frank, Oliver; Hofmann, Thomas

2017-04-19

A novel differential off-line LC-NMR approach (DOLC-NMR) was developed to capture and quantify nutrient-induced metabolome alterations in Saccharomyces cerevisiae. Off-line coupling of HPLC separation and 1 H NMR spectroscopy supported by automated comparative bucket analyses, followed by quantitative 1 H NMR using ERETIC 2 (electronic reference to access in vivo concentrations), has been successfully used to quantitatively record changes in the metabolome of S. cerevisiae upon intervention with the aromatic amino acid l-tyrosine. Among the 33 metabolites identified, glyceryl succinate, tyrosol acetate, tyrosol lactate, tyrosol succinate, and N-acyl-tyrosine derivatives such as N-(1-oxooctyl)-tyrosine are reported for the first time as yeast metabolites. Depending on the chain length, N-(1-oxooctyl)-, N-(1-oxodecanyl)-, N-(1-oxododecanyl)-, N-(1-oxomyristinyl)-, N-(1-oxopalmityl)-, and N-(1-oxooleoyl)-l-tyrosine imparted a kokumi taste enhancement above their recognition thresholds ranging between 145 and 1432 μmol/L (model broth). Finally, carbon module labeling (CAMOLA) and carbon bond labeling (CABOLA) experiments with 13 C 6 -glucose as the carbon source confirmed the biosynthetic pathway leading to the key metabolites; for example, the aliphatic side chain of N-(1-oxooctyl)-tyrosine could be shown to be generated via de novo fatty acid biosynthesis from four C 2 -carbon modules (acetyl-CoA) originating from glucose.

Grade-Dependent Metabolic Reprogramming in Kidney Cancer Revealed by Combined Proteomics and Metabolomics Analysis [Combined Proteomics and Metabolomics Analysis Reveals Grade-Dependent Metabolism Pathways in Kidney Cancer

DOE PAGES

Wettersten, Hiromi I.; Hakimi, A. Ari; Morin, Dexter; ...

2015-05-07

Kidney cancer [or renal cell carcinoma (RCC)] is known as “the internist's tumor” because it has protean systemic manifestations, suggesting that it utilizes complex, nonphysiologic metabolic pathways. Given the increasing incidence of this cancer and its lack of effective therapeutic targets, we undertook an extensive analysis of human RCC tissue employing combined grade-dependent proteomics and metabolomics analysis to determine how metabolic reprogramming occurring in this disease allows it to escape available therapeutic approaches. After validation experiments in RCC cell lines that were wild-type or mutant for the Von Hippel–Lindau tumor suppressor, in characterizing higher-grade tumors, we found that the Warburgmore » effect is relatively more prominent at the expense of the tricarboxylic acid cycle and oxidative metabolism in general. Further, we found that the glutamine metabolism pathway acts to inhibit reactive oxygen species, as evidenced by an upregulated glutathione pathway, whereas the β-oxidation pathway is inhibited, leading to increased fatty acylcarnitines. In support of findings from previous urine metabolomics analyses, we also documented tryptophan catabolism associated with immune suppression, which was highly represented in RCC compared with other metabolic pathways. Altogether, our results offer a rationale to evaluate novel antimetabolic treatment strategies being developed in other disease settings as therapeutic strategies in RCC« less

Untargeted metabolomics unravels functionalities of phosphorylation sites in Saccharomyces cerevisiae.

PubMed

Raguz Nakic, Zrinka; Seisenbacher, Gerhard; Posas, Francesc; Sauer, Uwe

2016-11-15

Coordinated through a complex network of kinases and phosphatases, protein phosphorylation regulates essentially all cellular processes in eukaryotes. Recent advances in proteomics enable detection of thousands of phosphorylation sites (phosphosites) in single experiments. However, functionality of the vast majority of these sites remains unclear and we lack suitable approaches to evaluate functional relevance at a pace that matches their detection. Here, we assess functionality of 26 phosphosites by introducing phosphodeletion and phosphomimic mutations in 25 metabolic enzymes and regulators from the TOR and HOG signaling pathway in Saccharomyces cerevisiae by phenotypic analysis and untargeted metabolomics. We show that metabolomics largely outperforms growth analysis and recovers 10 out of the 13 previously characterized phosphosites and suggests functionality for several novel sites, including S79 on the TOR regulatory protein Tip41. We analyze metabolic profiles to identify consequences underlying regulatory phosphorylation events and detecting glycerol metabolism to have a so far unknown influence on arginine metabolism via phosphoregulation of the glycerol dehydrogenases. Further, we also find S508 in the MAPKK Pbs2 as a potential link for cross-talking between HOG signaling and the cell wall integrity pathway. We demonstrate that metabolic profiles can be exploited for gaining insight into regulatory consequences and biological roles of phosphosites. Altogether, untargeted metabolomics is a fast, sensitive and informative approach appropriate for future large-scale functional analyses of phosphosites.

Interactive Effects of UV-B Light with Abiotic Factors on Plant Growth and Chemistry, and Their Consequences for Defense against Arthropod Herbivores

PubMed Central

Escobar-Bravo, Rocio; Klinkhamer, Peter G. L.; Leiss, Kirsten A.

2017-01-01

Ultraviolet-B (UV-B) light plays a crucial role in plant–herbivorous arthropods interactions by inducing changes in constitutive and inducible plant defenses. In particular, constitutive defenses can be modulated by UV-B-induced photomorphogenic responses and changes in the plant metabolome. In accordance, the prospective use of UV-B light as a tool to increase plant protection in agricultural practice has gained increasing interest. Changes in the environmental conditions might, however, modulate the UV-B -induced plant responses. While in some cases plant responses to UV-B can increase adaptation to changes in certain abiotic factors, UV-B-induced responses might be also antagonized by the changing environment. The outcome of these interactions might have a great influence on how plants interact with their enemies, e.g., herbivorous arthropods. Here, we provide a review on the interactive effects of UV-B and light quantity and quality, increased temperature and drought stress on plant biochemistry, and we discuss the implications of the outcome of these interactions for plant resistance to arthropod pests. PMID:28303147

Metabolomics for laboratory diagnostics.

PubMed

Bujak, Renata; Struck-Lewicka, Wiktoria; Markuszewski, Michał J; Kaliszan, Roman

2015-09-10

Metabolomics is an emerging approach in a systems biology field. Due to continuous development in advanced analytical techniques and in bioinformatics, metabolomics has been extensively applied as a novel, holistic diagnostic tool in clinical and biomedical studies. Metabolome's measurement, as a chemical reflection of a current phenotype of a particular biological system, is nowadays frequently implemented to understand pathophysiological processes involved in disease progression as well as to search for new diagnostic or prognostic biomarkers of various organism's disorders. In this review, we discussed the research strategies and analytical platforms commonly applied in the metabolomics studies. The applications of the metabolomics in laboratory diagnostics in the last 5 years were also reviewed according to the type of biological sample used in the metabolome's analysis. We also discussed some limitations and further improvements which should be considered taking in mind potential applications of metabolomic research and practice. Copyright © 2014 Elsevier B.V. All rights reserved.

Leaf metabolite profile of the Brazilian resurrection plant Barbacenia purpurea Hook. (Velloziaceae) shows two time-dependent responses during desiccation and recovering

PubMed Central

Suguiyama, Vanessa F.; Silva, Emerson A.; Meirelles, Sergio T.; Centeno, Danilo C.; Braga, Marcia R.

2014-01-01

Barbacenia purpurea is a resurrection species endemic to rock outcrops, in Rio de Janeiro, Brazil. It tolerates great temperature variations, which are associated to periods of up to 30 days without precipitation. Using a metabolomic approach, we analyzed, under winter and summer conditions, changes in the leaf metabolite profile (MP) of potted plants of B. purpurea submitted to daily watered and water deficit for at least 20 days and subsequent slow rehydration for 5 days. Leaves were collected at different time points and had their MP analyzed by GC/MS, HPAEC, and UHPLC techniques, allowing the identification of more than 60 different compounds, including organic and amino acids, sugars, and polyols, among others. In the winter experiment, results suggest the presence of two time-dependent responses in B. purpurea under water stress. The first one starts with the increase in the content of caffeoyl-quinic acids, substances with strong antioxidant activity, until the 16th day of water suppression. When RWC reached less than 80 and 70%, in winter and summer respectively, it was observed an increase in polyols and monosaccharides, followed by an increment in the content of RFO, suggesting osmotic adjustment. Amino acids, such as GABA and asparagine, also increased due to 16 days of water suppression. During rehydration, the levels of the mentioned compounds became similar to those found at the beginning of the experiment and when compared to daily watered plants. We conclude that the tolerance of B. purpurea to dehydration involves the perception of water deficit intensity, which seems to result in different strategies to overcome the gradient of water availability imposed along a certain period of stress mainly during winter. Data from summer experiment indicate that the metabolism of B. pupurea was already primed for drought stress. The accumulation of phenolics in summer seemed to be more temperature and irradiance-dependent than on the RWC. PMID:24672534

Similar, but different: structurally related azelaic acid and hexanoic acid trigger differential metabolomic and transcriptomic responses in tobacco cells.

PubMed

Djami-Tchatchou, Arnaud T; Ncube, Efficient N; Steenkamp, Paul A; Dubery, Ian A

2017-11-29

Plants respond to various stress stimuli by activating an enhanced broad-spectrum defensive ability. The development of novel resistance inducers represents an attractive, alternative crop protection strategy. In this regard, hexanoic acid (Hxa, a chemical elicitor) and azelaic acid (Aza, a natural signaling compound) have been proposed as inducers of plant defense, by means of a priming mechanism. Here, we investigated both the mode of action and the complementarity of Aza and Hxa as priming agents in Nicotiana tabacum cells in support of enhanced defense. Metabolomic analyses identified signatory biomarkers involved in the establishment of a pre-conditioned state following Aza and Hxa treatment. Both inducers affected the metabolomes in a similar manner and generated common biomarkers: caffeoylputrescine glycoside, cis-5-caffeoylquinic acid, feruloylglycoside, feruloyl-3-methoxytyramine glycoside and feruloyl-3-methoxytyramine conjugate. Subsequently, quantitative real time-PCR was used to investigate the expression of inducible defense response genes: phenylalanine ammonia lyase, hydroxycinnamoyl CoA quinate transferase and hydroxycinnamoyl transferase to monitor activation of the early phenylpropanoid pathway and chlorogenic acids metabolism, while ethylene response element-binding protein, small sar1 GTPase, heat shock protein 90, RAR1, SGT1, non-expressor of PR genes 1 and thioredoxin were analyzed to report on signal transduction events. Pathogenesis-related protein 1a and defensin were quantified to investigate the activation of defenses regulated by salicylic acid and jasmonic acid respectively. The qPCR results revealed differential expression kinetics and, in general (except for NPR1, Thionin and PR1a), the relative gene expression ratios observed in the Hxa-treated cells were significantly greater than the expression observed in the cells treated with Aza. The results indicate that Aza and Hxa have a similar priming effect through activation of genes involved in the establishment of systemic acquired resistance, associated with enhanced synthesis of hydroxycinnamic acids and related conjugates.

Integrated Transcriptome and Metabolic Analyses Reveals Novel Insights into Free Amino Acid Metabolism in Huangjinya Tea Cultivar

PubMed Central

Zhang, Qunfeng; Liu, Meiya; Ruan, Jianyun

2017-01-01

The chlorotic tea variety Huangjinya, a natural mutant, contains enhanced levels of free amino acids in its leaves, which improves the drinking quality of its brewed tea. Consequently, this chlorotic mutant has a higher economic value than the non-chlorotic varieties. However, the molecular mechanisms behind the increased levels of free amino acids in this mutant are mostly unknown, as are the possible effects of this mutation on the overall metabolome and biosynthetic pathways in tea leaves. To gain further insight into the effects of chlorosis on the global metabolome and biosynthetic pathways in this mutant, Huangjinya plants were grown under normal and reduced sunlight, resulting in chlorotic and non-chlorotic leaves, respectively; their leaves were analyzed using transcriptomics as well as targeted and untargeted metabolomics. Approximately 5,000 genes (8.5% of the total analyzed) and ca. 300 metabolites (14.5% of the total detected) were significantly differentially regulated, thus indicating the occurrence of marked effects of light on the biosynthetic pathways in this mutant plant. Considering primary metabolism, including that of sugars, amino acids, and organic acids, significant changes were observed in the expression of genes involved in both nitrogen (N) and carbon metabolism. The suite of changes not only generated an increase in amino acids, including glutamic acid, glutamine, and theanine, but it also elevated the levels of free ammonium, citrate, and α-ketoglutarate, and lowered the levels of mono- and di-saccharides and of caffeine as compared with the non-chlorotic leaves. Taken together, our results suggest that the increased levels of amino acids in the chlorotic vs. non-chlorotic leaves are likely due to increased protein catabolism and/or decreased glycolysis and diminished biosynthesis of nitrogen-containing compounds other than amino acids, including chlorophyll, purines, nucleotides, and alkaloids. PMID:28321230

Chemical Assignment of Structural Isomers of Sulfur-Containing Metabolites in Garlic by Liquid Chromatography-Fourier Transform Ion Cyclotron Resonance-Mass Spectrometry.

PubMed

Nakabayashi, Ryo; Sawada, Yuji; Aoyagi, Morihiro; Yamada, Yutaka; Hirai, Masami Yokota; Sakurai, Tetsuya; Kamoi, Takahiro; Rowan, Daryl D; Saito, Kazuki

2016-02-01

The chemical assignment of metabolites is crucial to understanding the relation between food composition and biological activity. This study was designed to detect and chemically assign sulfur-containing metabolites by using LC-Fourier transform ion cyclotron resonance-mass spectrometry (FTICR-MS) in Allium plants. Ultrahigh resolution (>250,000 full width at half-maximum) and mass accuracy (<1 mDa) by FTICR-MS allowed us to distinguish ions containing sulfur isotopes ((32)S and (34)S). Putative 69 S-containing monoisotopic ions (S-ions) were extracted from the metabolome data of onion (Allium cepa), green onion (Allium fistulosum), and garlic (Allium sativum) on the basis of theoretical mass differences between (32)S-ions and their (34)S-substituted counterparts and on the natural abundance of (34)S. Eight S-ions were chemically assigned by using the reference data according to the guidelines of the Metabolomics Standards Initiative. Three ions detected in garlic were assigned as derived from the isomers γ-glutamyl-S-1-propenylcysteine and γ-glutamyl-S-2-propenylcysteine and as S-2-propenylmercaptoglutathione on the basis of differences in key product ions identified in reference tandem MS spectra. The ability to discriminate between such geometric isomers will be extremely useful for the chemical assignment of unknown metabolites in MS-based metabolomics. © 2016 American Society for Nutrition.

A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets

PubMed Central

Carreer, William J.; Flight, Robert M.; Moseley, Hunter N. B.

2013-01-01

New metabolomics applications of ultra-high resolution and accuracy mass spectrometry can provide thousands of detectable isotopologues, with the number of potentially detectable isotopologues increasing exponentially with the number of stable isotopes used in newer isotope tracing methods like stable isotope-resolved metabolomics (SIRM) experiments. This huge increase in usable data requires software capable of correcting the large number of isotopologue peaks resulting from SIRM experiments in a timely manner. We describe the design of a new algorithm and software system capable of handling these high volumes of data, while including quality control methods for maintaining data quality. We validate this new algorithm against a previous single isotope correction algorithm in a two-step cross-validation. Next, we demonstrate the algorithm and correct for the effects of natural abundance for both 13C and 15N isotopes on a set of raw isotopologue intensities of UDP-N-acetyl-D-glucosamine derived from a 13C/15N-tracing experiment. Finally, we demonstrate the algorithm on a full omics-level dataset. PMID:24404440

Role of metabolomics in TBI research

PubMed Central

Wolahan, Stephanie M.; Hirt, Daniel; Braas, Daniel; Glenn, Thomas C.

2016-01-01

Synopsis Metabolomics is an important member of the omics community in that it defines which small molecules may be responsible for disease states. This article reviews the essential principles of metabolomics from specimen preparation, chemical analysis, and advanced statistical methods. Metabolomics in TBI has so far been underutilized. Future metabolomics based studies focused on the diagnoses, prognoses, and treatment effects, need to be conducted across all types of TBI. PMID:27637396

Application of metabolomics to toxicology of drugs of abuse: A mini review of metabolomics approach to acute and chronic toxicity studies.

PubMed

Zaitsu, Kei; Hayashi, Yumi; Kusano, Maiko; Tsuchihashi, Hitoshi; Ishii, Akira

2016-02-01

Metabolomics has been widely applied to toxicological fields, especially to elucidate the mechanism of action of toxicity. In this review, metabolomics application with focus on the studies of chronic and acute toxicities of drugs of abuse like stimulants, opioids and the recently-distributed designer drugs will be presented in addition to an outline of basic analytical techniques used in metabolomics. Limitation of metabolomics studies and future perspectives will be also provided. Copyright © 2015 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.

Siderophore biosynthesis coordinately modulated the virulence-associated interactive metabolome of uropathogenic Escherichia coli and human urine.

PubMed

Su, Qiao; Guan, Tianbing; Lv, Haitao

2016-04-14

Uropathogenic Escherichia coli (UPEC) growth in women's bladders during urinary tract infection (UTI) incurs substantial chemical exchange, termed the "interactive metabolome", which primarily accounts for the metabolic costs (utilized metabolome) and metabolic donations (excreted metabolome) between UPEC and human urine. Here, we attempted to identify the individualized interactive metabolome between UPEC and human urine. We were able to distinguish UPEC from non-UPEC by employing a combination of metabolomics and genetics. Our results revealed that the interactive metabolome between UPEC and human urine was markedly different from that between non-UPEC and human urine, and that UPEC triggered much stronger perturbations in the interactive metabolome in human urine. Furthermore, siderophore biosynthesis coordinately modulated the individualized interactive metabolome, which we found to be a critical component of UPEC virulence. The individualized virulence-associated interactive metabolome contained 31 different metabolites and 17 central metabolic pathways that were annotated to host these different metabolites, including energetic metabolism, amino acid metabolism, and gut microbe metabolism. Changes in the activities of these pathways mechanistically pinpointed the virulent capability of siderophore biosynthesis. Together, our findings provide novel insights into UPEC virulence, and we propose that siderophores are potential targets for further discovery of drugs to treat UPEC-induced UTI.

Verticillium longisporum Infection Affects the Leaf Apoplastic Proteome, Metabolome, and Cell Wall Properties in Arabidopsis thaliana

PubMed Central

Floerl, Saskia; Majcherczyk, Andrzej; Possienke, Mareike; Feussner, Kirstin; Tappe, Hella; Gatz, Christiane; Feussner, Ivo; Kües, Ursula; Polle, Andrea

2012-01-01

Verticillium longisporum (VL) is one of the most devastating diseases in important oil crops from the family of Brassicaceae. The fungus resides for much time of its life cycle in the extracellular fluid of the vascular system, where it cannot be controlled by conventional fungicides. To obtain insights into the biology of VL-plant interaction in the apoplast, the secretome consisting of the extracellular proteome and metabolome as well as cell wall properties were studied in the model Brassicaceae, Arabidopsis thaliana. VL infection resulted in increased production of cell wall material with an altered composition of carbohydrate polymers and increased lignification. The abundance of several hundred soluble metabolites changed in the apoplast of VL-infected plants including signalling and defence compounds such as glycosides of salicylic acid, lignans and dihydroxybenzoic acid as well as oxylipins. The extracellular proteome of healthy leaves was enriched in antifungal proteins. VL caused specific increases in six apoplast proteins (three peroxidases PRX52, PRX34, P37, serine carboxypeptidase SCPL20, α-galactosidase AGAL2 and a germin-like protein GLP3), which have functions in defence and cell wall modification. The abundance of a lectin-like, chitin-inducible protein (CILLP) was reduced. Since the transcript levels of most of the induced proteins were not elevated until late infection time points (>20 dpi), whereas those of CILLP and GLP3 were reduced at earlier time points, our results may suggest that VL enhances its virulence by rapid down-regulation and delay of induction of plant defence genes. PMID:22363647

Enhancement of plant metabolite fingerprinting by machine learning.

PubMed

Scott, Ian M; Vermeer, Cornelia P; Liakata, Maria; Corol, Delia I; Ward, Jane L; Lin, Wanchang; Johnson, Helen E; Whitehead, Lynne; Kular, Baldeep; Baker, John M; Walsh, Sean; Dave, Anuja; Larson, Tony R; Graham, Ian A; Wang, Trevor L; King, Ross D; Draper, John; Beale, Michael H

2010-08-01

Metabolite fingerprinting of Arabidopsis (Arabidopsis thaliana) mutants with known or predicted metabolic lesions was performed by (1)H-nuclear magnetic resonance, Fourier transform infrared, and flow injection electrospray-mass spectrometry. Fingerprinting enabled processing of five times more plants than conventional chromatographic profiling and was competitive for discriminating mutants, other than those affected in only low-abundance metabolites. Despite their rapidity and complexity, fingerprints yielded metabolomic insights (e.g. that effects of single lesions were usually not confined to individual pathways). Among fingerprint techniques, (1)H-nuclear magnetic resonance discriminated the most mutant phenotypes from the wild type and Fourier transform infrared discriminated the fewest. To maximize information from fingerprints, data analysis was crucial. One-third of distinctive phenotypes might have been overlooked had data models been confined to principal component analysis score plots. Among several methods tested, machine learning (ML) algorithms, namely support vector machine or random forest (RF) classifiers, were unsurpassed for phenotype discrimination. Support vector machines were often the best performing classifiers, but RFs yielded some particularly informative measures. First, RFs estimated margins between mutant phenotypes, whose relations could then be visualized by Sammon mapping or hierarchical clustering. Second, RFs provided importance scores for the features within fingerprints that discriminated mutants. These scores correlated with analysis of variance F values (as did Kruskal-Wallis tests, true- and false-positive measures, mutual information, and the Relief feature selection algorithm). ML classifiers, as models trained on one data set to predict another, were ideal for focused metabolomic queries, such as the distinctiveness and consistency of mutant phenotypes. Accessible software for use of ML in plant physiology is highlighted.

The 'prime-ome': towards a holistic approach to priming.

PubMed

Balmer, Andrea; Pastor, Victoria; Gamir, Jordi; Flors, Victor; Mauch-Mani, Brigitte

2015-07-01

Plants can be primed to respond faster and more strongly to stress and multiple pathways, specific for the encountered challenge, are involved in priming. This adaptability of priming makes it difficult to pinpoint an exact mechanism: the same phenotypic observation might be the consequence of unrelated underlying events. Recently, details of the molecular aspects of establishing a primed state and its transfer to offspring have come to light. Advances in techniques for detection and quantification of elements spanning the fields of transcriptomics, proteomics, and metabolomics, together with adequate bioinformatics tools, will soon allow us to take a holistic approach to plant defence. This review highlights the state of the art of new strategies to study defence priming in plants and provides perspectives towards 'prime-omics'. Copyright © 2015 Elsevier Ltd. All rights reserved.

Language of plants: Where is the word?

PubMed

Šimpraga, Maja; Takabayashi, Junji; Holopainen, Jarmo K

2016-04-01

Plants emit biogenic volatile organic compounds (BVOCs) causing transcriptomic, metabolomic and behavioral responses in receiver organisms. Volatiles involved in such responses are often called "plant language". Arthropods having sensitive chemoreceptors can recognize language released by plants. Insect herbivores, pollinators and natural enemies respond to composition of volatiles from plants with specialized receptors responding to different types of compounds. In contrast, the mechanism of how plants "hear" volatiles has remained obscured. In a plant-plant communication, several individually emitted compounds are known to prime defense response in receiver plants with a specific manner according to the chemical structure of each volatile compound. Further, composition and ratio of volatile compounds in the plant-released plume is important in plant-insect and plant-plant interactions mediated by plant volatiles. Studies on volatile-mediated plant-plant signaling indicate that the signaling distances are rather short, usually not longer than one meter. Volatile communication from plants to insects such as pollinators could be across distances of hundreds of meters. As many of the herbivore induced VOCs have rather short atmospheric life times, we suggest that in long-distant communications with plant volatiles, reaction products in the original emitted compounds may have additional information value of the distance to emission source together with the original plant-emitted compounds. © 2015 Institute of Botany, Chinese Academy of Sciences.

Genetic engineering of cytokinin metabolism: prospective way to improve agricultural traits of crop plants.

PubMed

Zalabák, David; Pospíšilová, Hana; Šmehilová, Mária; Mrízová, Katarína; Frébort, Ivo; Galuszka, Petr

2013-01-01

Cytokinins (CKs) are ubiquitous phytohormones that participate in development, morphogenesis and many physiological processes throughout plant kingdom. In higher plants, mutants and transgenic cells and tissues with altered activity of CK metabolic enzymes or perception machinery, have highlighted their crucial involvement in different agriculturally important traits, such as productivity, increased tolerance to various stresses and overall plant morphology. Furthermore, recent precise metabolomic analyses have elucidated the specific occurrence and distinct functions of different CK types in various plant species. Thus, smooth manipulation of active CK levels in a spatial and temporal way could be a very potent tool for plant biotechnology in the future. This review summarises recent advances in cytokinin research ranging from transgenic alteration of CK biosynthetic, degradation and glucosylation activities and CK perception to detailed elucidation of molecular processes, in which CKs work as a trigger in model plants. The first attempts to improve the quality of crop plants, focused on cereals are discussed, together with proposed mechanism of action of the responses involved. Copyright © 2011 Elsevier Inc. All rights reserved.

Novel Approach to Classify Plants Based on Metabolite-Content Similarity.

PubMed

Liu, Kang; Abdullah, Azian Azamimi; Huang, Ming; Nishioka, Takaaki; Altaf-Ul-Amin, Md; Kanaya, Shigehiko

2017-01-01

Secondary metabolites are bioactive substances with diverse chemical structures. Depending on the ecological environment within which they are living, higher plants use different combinations of secondary metabolites for adaptation (e.g., defense against attacks by herbivores or pathogenic microbes). This suggests that the similarity in metabolite content is applicable to assess phylogenic similarity of higher plants. However, such a chemical taxonomic approach has limitations of incomplete metabolomics data. We propose an approach for successfully classifying 216 plants based on their known incomplete metabolite content. Structurally similar metabolites have been clustered using the network clustering algorithm DPClus. Plants have been represented as binary vectors, implying relations with structurally similar metabolite groups, and classified using Ward's method of hierarchical clustering. Despite incomplete data, the resulting plant clusters are consistent with the known evolutional relations of plants. This finding reveals the significance of metabolite content as a taxonomic marker. We also discuss the predictive power of metabolite content in exploring nutritional and medicinal properties in plants. As a byproduct of our analysis, we could predict some currently unknown species-metabolite relations.

Novel Approach to Classify Plants Based on Metabolite-Content Similarity

PubMed Central

Abdullah, Azian Azamimi; Huang, Ming; Nishioka, Takaaki

2017-01-01

Secondary metabolites are bioactive substances with diverse chemical structures. Depending on the ecological environment within which they are living, higher plants use different combinations of secondary metabolites for adaptation (e.g., defense against attacks by herbivores or pathogenic microbes). This suggests that the similarity in metabolite content is applicable to assess phylogenic similarity of higher plants. However, such a chemical taxonomic approach has limitations of incomplete metabolomics data. We propose an approach for successfully classifying 216 plants based on their known incomplete metabolite content. Structurally similar metabolites have been clustered using the network clustering algorithm DPClus. Plants have been represented as binary vectors, implying relations with structurally similar metabolite groups, and classified using Ward's method of hierarchical clustering. Despite incomplete data, the resulting plant clusters are consistent with the known evolutional relations of plants. This finding reveals the significance of metabolite content as a taxonomic marker. We also discuss the predictive power of metabolite content in exploring nutritional and medicinal properties in plants. As a byproduct of our analysis, we could predict some currently unknown species-metabolite relations. PMID:28164123

Analysis of metabolomics datasets with high-performance computing and metabolite atlases

DOE PAGES

Yao, Yushu; Sun, Terence; Wang, Tony; ...

2015-07-20

Even with the widespread use of liquid chromatography mass spectrometry (LC/MS) based metabolomics, there are still a number of challenges facing this promising technique. Many, diverse experimental workflows exist; yet there is a lack of infrastructure and systems for tracking and sharing of information. Here, we describe the Metabolite Atlas framework and interface that provides highly-efficient, web-based access to raw mass spectrometry data in concert with assertions about chemicals detected to help address some of these challenges. This integration, by design, enables experimentalists to explore their raw data, specify and refine features annotations such that they can be leveraged formore » future experiments. Fast queries of the data through the web using SciDB, a parallelized database for high performance computing, make this process operate quickly. Furthermore, by using scripting containers, such as IPython or Jupyter, to analyze the data, scientists can utilize a wide variety of freely available graphing, statistics, and information management resources. In addition, the interfaces facilitate integration with systems biology tools to ultimately link metabolomics data with biological models.« less

Applications of Metabolomics in Cancer Studies.

PubMed

Armitage, Emily Grace; Ciborowski, Michal

2017-01-01

Since the start of metabolomics as a field of research, the number of studies related to cancer has grown to such an extent that cancer metabolomics now represents its own discipline. In this chapter, the applications of metabolomics in cancer studies are explored. Different approaches and analytical platforms can be employed for the analysis of samples depending on the goal of the study and the aspects of the cancer metabolome being investigated. Analyses have concerned a range of cancers including lung, colorectal, bladder, breast, gastric, oesophageal and thyroid, amongst others. Developments in these strategies and methodologies that have been applied are discussed, in addition to exemplifying the use of cancer metabolomics in the discovery of biomarkers and in the assessment of therapy (both pharmaceutical and nutraceutical). Finally, the application of cancer metabolomics in personalised medicine is presented.

Allelopatic Potential of Dittrichia viscosa (L.) W. Greuter Mediated by VOCs: A Physiological and Metabolomic Approach.

PubMed

Araniti, Fabrizio; Lupini, Antonio; Sunseri, Francesco; Abenavoli, Maria Rosa

2017-01-01

Dittrichia viscosa (L.) W. Greuter is a pioneer species belonging to the Compositae family. It is widespread in the Mediterranean basin, where it is considered invasive. It is a source of secondary metabolites, playing an important ecological role. D. viscosa plant extracts showed a phytotoxic activity on several physiological processes of different species. In the current study, the allelopathic potential of D. viscosa VOCs, released by its foliage, was evaluated on seed germination and root growth of lettuce. The VOCs effect was also studied on lettuce adult plants in microcosm systems, which better mimicked the open field conditions. D. viscosa VOCs inhibited both seed germination and root growth of lettuce. The VOCs composition revealed a large presence of terpenoids, responsible of the effects observed. Moreover, D. viscosa VOCs caused an alteration on plant water status accompanied by oxidative damages and photoinhibition on lettuce adult plants.

Allelopatic Potential of Dittrichia viscosa (L.) W. Greuter Mediated by VOCs: A Physiological and Metabolomic Approach

PubMed Central

Lupini, Antonio; Sunseri, Francesco; Abenavoli, Maria Rosa

2017-01-01

Dittrichia viscosa (L.) W. Greuter is a pioneer species belonging to the Compositae family. It is widespread in the Mediterranean basin, where it is considered invasive. It is a source of secondary metabolites, playing an important ecological role. D. viscosa plant extracts showed a phytotoxic activity on several physiological processes of different species. In the current study, the allelopathic potential of D. viscosa VOCs, released by its foliage, was evaluated on seed germination and root growth of lettuce. The VOCs effect was also studied on lettuce adult plants in microcosm systems, which better mimicked the open field conditions. D. viscosa VOCs inhibited both seed germination and root growth of lettuce. The VOCs composition revealed a large presence of terpenoids, responsible of the effects observed. Moreover, D. viscosa VOCs caused an alteration on plant water status accompanied by oxidative damages and photoinhibition on lettuce adult plants. PMID:28085959

Cultivar Determination of Ricinus communis via the Metabolome: a Proof of Concept Investigation

DTIC Science & Technology

2009-08-01

metabolome found in an organism is the result of the interaction between the organisms’ genome and the environment. Metabolomics has been applied to...Cultivar Determination of Ricinus communis via the Metabolome : a Proof of Concept Investigation Simon P. B. Ovenden, Benjamin R. Gordon¹, Christina...appropriateness of studying the metabolome of Ricinus communis for cultivar and provenance determination. Seeds from fourteen R. communis specimens (a total of 56

The Effects of Endocrine Disruptors on Steroidogenesis Gene Expression Dynamics in Fathead Minnow

EPA Science Inventory

Steroid hormones play key roles in regulating reproduction and development and fish and other vertebrates. This presentation reports results from two in vitro experiments aimed characterizing the dynamics of transcriptional and metabolomic responses to endocrine disrupting chemi...

QCScreen: a software tool for data quality control in LC-HRMS based metabolomics.

PubMed

Simader, Alexandra Maria; Kluger, Bernhard; Neumann, Nora Katharina Nicole; Bueschl, Christoph; Lemmens, Marc; Lirk, Gerald; Krska, Rudolf; Schuhmacher, Rainer

2015-10-24

Metabolomics experiments often comprise large numbers of biological samples resulting in huge amounts of data. This data needs to be inspected for plausibility before data evaluation to detect putative sources of error e.g. retention time or mass accuracy shifts. Especially in liquid chromatography-high resolution mass spectrometry (LC-HRMS) based metabolomics research, proper quality control checks (e.g. for precision, signal drifts or offsets) are crucial prerequisites to achieve reliable and comparable results within and across experimental measurement sequences. Software tools can support this process. The software tool QCScreen was developed to offer a quick and easy data quality check of LC-HRMS derived data. It allows a flexible investigation and comparison of basic quality-related parameters within user-defined target features and the possibility to automatically evaluate multiple sample types within or across different measurement sequences in a short time. It offers a user-friendly interface that allows an easy selection of processing steps and parameter settings. The generated results include a coloured overview plot of data quality across all analysed samples and targets and, in addition, detailed illustrations of the stability and precision of the chromatographic separation, the mass accuracy and the detector sensitivity. The use of QCScreen is demonstrated with experimental data from metabolomics experiments using selected standard compounds in pure solvent. The application of the software identified problematic features, samples and analytical parameters and suggested which data files or compounds required closer manual inspection. QCScreen is an open source software tool which provides a useful basis for assessing the suitability of LC-HRMS data prior to time consuming, detailed data processing and subsequent statistical analysis. It accepts the generic mzXML format and thus can be used with many different LC-HRMS platforms to process both multiple quality control sample types as well as experimental samples in one or more measurement sequences.

Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics

PubMed Central

Giacomoni, Franck; Le Corguillé, Gildas; Monsoor, Misharl; Landi, Marion; Pericard, Pierre; Pétéra, Mélanie; Duperier, Christophe; Tremblay-Franco, Marie; Martin, Jean-François; Jacob, Daniel; Goulitquer, Sophie; Thévenot, Etienne A.; Caron, Christophe

2015-01-01

Summary: The complex, rapidly evolving field of computational metabolomics calls for collaborative infrastructures where the large volume of new algorithms for data pre-processing, statistical analysis and annotation can be readily integrated whatever the language, evaluated on reference datasets and chained to build ad hoc workflows for users. We have developed Workflow4Metabolomics (W4M), the first fully open-source and collaborative online platform for computational metabolomics. W4M is a virtual research environment built upon the Galaxy web-based platform technology. It enables ergonomic integration, exchange and running of individual modules and workflows. Alternatively, the whole W4M framework and computational tools can be downloaded as a virtual machine for local installation. Availability and implementation: http://workflow4metabolomics.org homepage enables users to open a private account and access the infrastructure. W4M is developed and maintained by the French Bioinformatics Institute (IFB) and the French Metabolomics and Fluxomics Infrastructure (MetaboHUB). Contact: contact@workflow4metabolomics.org PMID:25527831

Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics.

PubMed

Giacomoni, Franck; Le Corguillé, Gildas; Monsoor, Misharl; Landi, Marion; Pericard, Pierre; Pétéra, Mélanie; Duperier, Christophe; Tremblay-Franco, Marie; Martin, Jean-François; Jacob, Daniel; Goulitquer, Sophie; Thévenot, Etienne A; Caron, Christophe

2015-05-01

The complex, rapidly evolving field of computational metabolomics calls for collaborative infrastructures where the large volume of new algorithms for data pre-processing, statistical analysis and annotation can be readily integrated whatever the language, evaluated on reference datasets and chained to build ad hoc workflows for users. We have developed Workflow4Metabolomics (W4M), the first fully open-source and collaborative online platform for computational metabolomics. W4M is a virtual research environment built upon the Galaxy web-based platform technology. It enables ergonomic integration, exchange and running of individual modules and workflows. Alternatively, the whole W4M framework and computational tools can be downloaded as a virtual machine for local installation. http://workflow4metabolomics.org homepage enables users to open a private account and access the infrastructure. W4M is developed and maintained by the French Bioinformatics Institute (IFB) and the French Metabolomics and Fluxomics Infrastructure (MetaboHUB). contact@workflow4metabolomics.org. © The Author 2014. Published by Oxford University Press.

Dereplication of Natural Products Using GC-TOF Mass Spectrometry: Improved Metabolite Identification by Spectral Deconvolution Ratio Analysis.

PubMed

Carnevale Neto, Fausto; Pilon, Alan C; Selegato, Denise M; Freire, Rafael T; Gu, Haiwei; Raftery, Daniel; Lopes, Norberto P; Castro-Gamboa, Ian

2016-01-01

Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, thereby avoiding re-isolation of known natural products. However, due to the complex nature of biological samples and their large concentration range, dereplication requires the use of chemometric tools to comprehensively extract information from the acquired data. In this work we developed a reliable GC-MS-based method for the identification of non-targeted plant metabolites by combining the Ratio Analysis of Mass Spectrometry deconvolution tool (RAMSY) with Automated Mass Spectral Deconvolution and Identification System software (AMDIS). Plants species from Solanaceae, Chrysobalanaceae and Euphorbiaceae were selected as model systems due to their molecular diversity, ethnopharmacological potential, and economical value. The samples were analyzed by GC-MS after methoximation and silylation reactions. Dereplication was initiated with the use of a factorial design of experiments to determine the best AMDIS configuration for each sample, considering linear retention indices and mass spectral data. A heuristic factor (CDF, compound detection factor) was developed and applied to the AMDIS results in order to decrease the false-positive rates. Despite the enhancement in deconvolution and peak identification, the empirical AMDIS method was not able to fully deconvolute all GC-peaks, leading to low MF values and/or missing metabolites. RAMSY was applied as a complementary deconvolution method to AMDIS to peaks exhibiting substantial overlap, resulting in recovery of low-intensity co-eluted ions. The results from this combination of optimized AMDIS with RAMSY attested to the ability of this approach as an improved dereplication method for complex biological samples such as plant extracts.

Dereplication of Natural Products Using GC-TOF Mass Spectrometry: Improved Metabolite Identification by Spectral Deconvolution Ratio Analysis

PubMed Central

Carnevale Neto, Fausto; Pilon, Alan C.; Selegato, Denise M.; Freire, Rafael T.; Gu, Haiwei; Raftery, Daniel; Lopes, Norberto P.; Castro-Gamboa, Ian

2016-01-01

Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, thereby avoiding re-isolation of known natural products. However, due to the complex nature of biological samples and their large concentration range, dereplication requires the use of chemometric tools to comprehensively extract information from the acquired data. In this work we developed a reliable GC-MS-based method for the identification of non-targeted plant metabolites by combining the Ratio Analysis of Mass Spectrometry deconvolution tool (RAMSY) with Automated Mass Spectral Deconvolution and Identification System software (AMDIS). Plants species from Solanaceae, Chrysobalanaceae and Euphorbiaceae were selected as model systems due to their molecular diversity, ethnopharmacological potential, and economical value. The samples were analyzed by GC-MS after methoximation and silylation reactions. Dereplication was initiated with the use of a factorial design of experiments to determine the best AMDIS configuration for each sample, considering linear retention indices and mass spectral data. A heuristic factor (CDF, compound detection factor) was developed and applied to the AMDIS results in order to decrease the false-positive rates. Despite the enhancement in deconvolution and peak identification, the empirical AMDIS method was not able to fully deconvolute all GC-peaks, leading to low MF values and/or missing metabolites. RAMSY was applied as a complementary deconvolution method to AMDIS to peaks exhibiting substantial overlap, resulting in recovery of low-intensity co-eluted ions. The results from this combination of optimized AMDIS with RAMSY attested to the ability of this approach as an improved dereplication method for complex biological samples such as plant extracts. PMID:27747213

Pre-analytic evaluation of volumetric absorptive microsampling and integration in a mass spectrometry-based metabolomics workflow.

PubMed

Volani, Chiara; Caprioli, Giulia; Calderisi, Giovanni; Sigurdsson, Baldur B; Rainer, Johannes; Gentilini, Ivo; Hicks, Andrew A; Pramstaller, Peter P; Weiss, Guenter; Smarason, Sigurdur V; Paglia, Giuseppe

2017-10-01

Volumetric absorptive microsampling (VAMS) is a novel approach that allows single-drop (10 μL) blood collection. Integration of VAMS with mass spectrometry (MS)-based untargeted metabolomics is an attractive solution for both human and animal studies. However, to boost the use of VAMS in metabolomics, key pre-analytical questions need to be addressed. Therefore, in this work, we integrated VAMS in a MS-based untargeted metabolomics workflow and investigated pre-analytical strategies such as sample extraction procedures and metabolome stability at different storage conditions. We first evaluated the best extraction procedure for the polar metabolome and found that the highest number and amount of metabolites were recovered upon extraction with acetonitrile/water (70:30). In contrast, basic conditions (pH 9) resulted in divergent metabolite profiles mainly resulting from the extraction of intracellular metabolites originating from red blood cells. In addition, the prolonged storage of blood samples at room temperature caused significant changes in metabolome composition, but once the VAMS devices were stored at - 80 °C, the metabolome remained stable for up to 6 months. The time used for drying the sample did also affect the metabolome. In fact, some metabolites were rapidly degraded or accumulated in the sample during the first 48 h at room temperature, indicating that a longer drying step will significantly change the concentration in the sample. Graphical abstract Volumetric absorptive microsampling (VAMS) is a novel technology that allows single-drop blood collection and, in combination with mass spectrometry (MS)-based untargeted metabolomics, represents an attractive solution for both human and animal studies. In this work, we integrated VAMS in a MS-based untargeted metabolomics workflow and investigated pre-analytical strategies such as sample extraction procedures and metabolome stability at different storage conditions. The latter revealed that prolonged storage of blood samples at room temperature caused significant changes in metabolome composition, but if VAMS devices were stored at - 80 °C, the metabolome remained stable for up to 6 months.

Potential Impact and Study Considerations of Metabolomics in Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association.

PubMed

Cheng, Susan; Shah, Svati H; Corwin, Elizabeth J; Fiehn, Oliver; Fitzgerald, Robert L; Gerszten, Robert E; Illig, Thomas; Rhee, Eugene P; Srinivas, Pothur R; Wang, Thomas J; Jain, Mohit

2017-04-01

Through the measure of thousands of small-molecule metabolites in diverse biological systems, metabolomics now offers the potential for new insights into the factors that contribute to complex human diseases such as cardiovascular disease. Targeted metabolomics methods have already identified new molecular markers and metabolomic signatures of cardiovascular disease risk (including branched-chain amino acids, select unsaturated lipid species, and trimethylamine- N -oxide), thus in effect linking diverse exposures such as those from dietary intake and the microbiota with cardiometabolic traits. As technologies for metabolomics continue to evolve, the depth and breadth of small-molecule metabolite profiling in complex systems continue to advance rapidly, along with prospects for ongoing discovery. Current challenges facing the field of metabolomics include scaling throughput and technical capacity for metabolomics approaches, bioinformatic and chemoinformatic tools for handling large-scale metabolomics data, methods for elucidating the biochemical structure and function of novel metabolites, and strategies for determining the true clinical relevance of metabolites observed in association with cardiovascular disease outcomes. Progress made in addressing these challenges will allow metabolomics the potential to substantially affect diagnostics and therapeutics in cardiovascular medicine. © 2017 American Heart Association, Inc.

Relationships between drought, heat and air humidity responses revealed by transcriptome-metabolome co-analysis.

PubMed

Georgii, Elisabeth; Jin, Ming; Zhao, Jin; Kanawati, Basem; Schmitt-Kopplin, Philippe; Albert, Andreas; Winkler, J Barbro; Schäffner, Anton R

2017-07-10

Elevated temperature and reduced water availability are frequently linked abiotic stresses that may provoke distinct as well as interacting molecular responses. Based on non-targeted metabolomic and transcriptomic measurements from Arabidopsis rosettes, this study aims at a systematic elucidation of relevant components in different drought and heat scenarios as well as relationships between molecular players of stress response. In combined drought-heat stress, the majority of single stress responses are maintained. However, interaction effects between drought and heat can be discovered as well; these relate to protein folding, flavonoid biosynthesis and growth inhibition, which are enhanced, reduced or specifically induced in combined stress, respectively. Heat stress experiments with and without supplementation of air humidity for maintenance of vapor pressure deficit suggest that decreased relative air humidity due to elevated temperature is an important component of heat stress, specifically being responsible for hormone-related responses to water deprivation. Remarkably, this "dry air effect" is the primary trigger of the metabolomic response to heat. In contrast, the transcriptomic response has a substantial temperature component exceeding the dry air component and including up-regulation of many transcription factors and protein folding-related genes. Data level integration independent of prior knowledge on pathways and condition labels reveals shared drought and heat responses between transcriptome and metabolome, biomarker candidates and co-regulation between genes and metabolic compounds, suggesting novel players in abiotic stress response pathways. Drought and heat stress interact both at transcript and at metabolite response level. A comprehensive, non-targeted view of this interaction as well as non-interacting processes is important to be taken into account when improving tolerance to abiotic stresses in breeding programs. Transcriptome and metabolome may respond with different extent to individual stress components. Their contrasting behavior in response to temperature stress highlights that the protein folding machinery effectively shields the metabolism from stress. Disentangling the complex relationships between transcriptome and metabolome in response to stress is an enormous challenge. As demonstrated by case studies with supporting evidence from additional data, the large dataset provided in this study may assist in determining linked genetic and metabolic features as candidates for future mechanistic analyses.

Alterations in Grapevine Leaf Metabolism Occur Prior to Esca Apoplexy Appearance.

PubMed

Magnin-Robert, Maryline; Adrian, Marielle; Trouvelot, Sophie; Spagnolo, Alessandro; Jacquens, Lucile; Letousey, Patricia; Rabenoelina, Fanja; Harir, Mourad; Roullier-Gall, Chloé; Clément, Christophe; Schmitt-Kopplin, Philippe; Vallat, Armelle; Abou-Mansour, Eliane; Fontaine, Florence

2017-12-01

Esca disease is one of the major grapevine trunk diseases in Europe and the etiology is complex, since several inhabiting fungi are identified to be associated with this disease. Among the foliar symptom expressions, the apoplectic form may be distinguished and characterized by sudden dieback of shoots, leaf drop, and shriveling of grape clusters in a few days that can ultimately induce the plant death. To further understand this drastic event, we conducted transcriptomic and metabolomic analyses to characterize responses of leaves during the period preceding symptom appearance (20 and 7 days before foliar symptom expression) and at the day of apoplexy expression. Transcriptomic and metabolomic analyses provide signatures for the apoplectic leaves and most changes concerning the metabolism of carbohydrates, amino acids, and phenylpropanoids. In deciphering glutathione-S-transferase (GST), its preferential location in phloem, correlated with the upregulation of GST genes and a decrease of the glutathione level, offers further support to the putative role of glutathione during apoplexy expression.

Nontargeted metabolite profiles and sensory properties of strawberry cultivars grown both organically and conventionally.

PubMed

Kårlund, Anna; Hanhineva, Kati; Lehtonen, Marko; Karjalainen, Reijo O; Sandell, Mari

2015-01-28

Strawberry (Fragaria × ananassa Duch.) contains many secondary metabolites potentially beneficial for human health, and several of these compounds contribute to strawberry sensory properties, as well. In this study, three strawberry cultivars grown both conventionally and organically were subjected to nontargeted metabolite profiling analysis with LC-qTOF-ESI-MS and to descriptive sensory evaluation by a trained panel. Combined metabolome and sensory data (PLS model) revealed that 79% variation in the metabolome explained 88% variation in the sensory profiles. Flavonoids and condensed and hydrolyzable tannins determined the orosensory properties, and fatty acids contributed to the odor attributes of strawberry. Overall, the results indicated that the chemical composition and sensory quality of strawberries grown in different cultivation systems vary mostly according to cultivar. Organic farming practices may enhance the accumulation of some plant metabolites in specific strawberry genotypes. Careful cultivar selection is a key factor for the improvement of nutritional quality and marketing value of organic strawberries.

Two-Phase Extraction for Comprehensive Analysis of the Plant Metabolome by NMR.

PubMed

Schripsema, Jan; Dagnino, Denise

2018-01-01

Metabolomics is the area of research, which strives to obtain complete metabolic fingerprints, to detect differences between them, and to provide hypothesis to explain those differences [1]. But obtaining complete metabolic fingerprints is not an easy task. Metabolite extraction is a key step during this process, and much research has been devoted to finding the best solvent mixture to extract as much metabolites as possible.Here a procedure is described for analysis of both polar and apolar metabolites using a two-phase extraction system. D 2 O and CDCl 3 are the solvents of choice, and their major advantage is that, for the identification of the compounds, standard databases can be used because D 2 O and CDCl 3 are the solvents most commonly used for pure compound NMR spectra. The procedure enables the absolute quantification of components via the addition of suitable internal standards. The extracts are also suitable for further analysis with other systems like LC-MS or GC-MS.

Quality and safety of herbal medical products: regulation and the need for quality assurance along the value chains.

PubMed

Heinrich, Michael

2015-07-01

Herbal medicines and products derived from them are a diverse group of products for which different (and often limited) levels of evidence are available. As importantly, such products generally vary in their composition and are at the end of an often poorly understood value chain, which often links producers in biodiversity rich countries with the large markets in the North. This paper discusses the current regulatory framework of such herbal medical products (with a focus on the UK) and using examples from our own metabolomic research on Curcumal longa L. (turmeric, Zingiberaceae) how value chains impact on the composition and quality (and thus the safety) of such products. Overall, our recent research demonstrates the need for studying the links between producers and consumers of commodities produced in provider countries and that plant metabolomics offer a novel way of assessing the chemical variability along a value chain. © 2015 The British Pharmacological Society.

Metabolic profiling of root exudates from two ecotypes of Sedum alfredii treated with Pb based on GC-MS

NASA Astrophysics Data System (ADS)

Luo, Qing; Wang, Shiyu; Sun, Li-Na; Wang, Hui

2017-01-01

Phytoremediation is an effective method to remediate Pb-contaminated soils and root exudates play an important role in this process. Based on gas chromatography-mass spectrometry (GC-MS) and metabolomics method, this study focuses on the comparative metabolic profiling analysis of root exudates from the Pb-accumulating and non-accumulating ecotypes of Sedum alfredii treated with 0 and 50 μmol/L Pb. The results obtained show that plant type and Pb stress can significantly change the concentrations and species of root exudates, and fifteen compounds were identified and assumed to be potential biomarkers. Leaching experiments showed that l-alanine, l-proline and oxalic acid have a good effect to activate Pb in soil, glyceric acid and 2-hydroxyacetic acid have a general effect to activate Pb in soil. 4-Methylphenol and 2-methoxyphenol might be able to activate Pb in soil, glycerol and diethyleneglycol might be able to stabilize Pb in soil, but these activation effect and stabilization effect were all not obvious.

Metabolic profiling of two maize (Zea mays L.) inbred lines inoculated with the nitrogen fixing plant-interacting bacteria Herbaspirillum seropedicae and Azospirillum brasilense

PubMed Central

Brusamarello-Santos, Liziane Cristina; Gilard, Françoise; Brulé, Lenaïg; Quilleré, Isabelle; Gourion, Benjamin; Ratet, Pascal; Maltempi de Souza, Emanuel; Lea, Peter J.; Hirel, Bertrand

2017-01-01

Maize roots can be colonized by free-living atmospheric nitrogen (N2)-fixing bacteria (diazotrophs). However, the agronomic potential of non-symbiotic N2-fixation in such an economically important species as maize, has still not been fully exploited. A preliminary approach to improve our understanding of the mechanisms controlling the establishment of such N2-fixing associations has been developed, using two maize inbred lines exhibiting different physiological characteristics. The bacterial-plant interaction has been characterized by means of a metabolomic approach. Two established model strains of Nif+ diazotrophic bacteria, Herbaspirillum seropedicae and Azospirillum brasilense and their Nif- couterparts defficient in nitrogenase activity, were used to evaluate the impact of the bacterial inoculation and of N2 fixation on the root and leaf metabolic profiles. The two N2-fixing bacteria have been used to inoculate two genetically distant maize lines (FV252 and FV2), already characterized for their contrasting physiological properties. Using a well-controlled gnotobiotic experimental system that allows inoculation of maize plants with the two diazotrophs in a N-free medium, we demonstrated that both maize lines were efficiently colonized by the two bacterial species. We also showed that in the early stages of plant development, both bacterial strains were able to reduce acetylene, suggesting that they contain functional nitrogenase activity and are able to efficiently fix atmospheric N2 (Fix+). The metabolomic approach allowed the identification of metabolites in the two maize lines that were representative of the N2 fixing plant-bacterial interaction, these included mannitol and to a lesser extend trehalose and isocitrate. Whilst other metabolites such as asparagine, although only exhibiting a small increase in maize roots following bacterial infection, were specific for the two Fix+ bacterial strains, in comparison to their Fix- counterparts. Moreover, a number of metabolites exhibited a maize-genotype specific pattern of accumulation, suggesting that the highly diverse maize genetic resources could be further exploited in terms of beneficial plant-bacterial interactions for optimizing maize growth, with reduced N fertilization inputs. PMID:28362815

Metabolic profiling of two maize (Zea mays L.) inbred lines inoculated with the nitrogen fixing plant-interacting bacteria Herbaspirillum seropedicae and Azospirillum brasilense.

PubMed

Brusamarello-Santos, Liziane Cristina; Gilard, Françoise; Brulé, Lenaïg; Quilleré, Isabelle; Gourion, Benjamin; Ratet, Pascal; Maltempi de Souza, Emanuel; Lea, Peter J; Hirel, Bertrand

2017-01-01

Maize roots can be colonized by free-living atmospheric nitrogen (N2)-fixing bacteria (diazotrophs). However, the agronomic potential of non-symbiotic N2-fixation in such an economically important species as maize, has still not been fully exploited. A preliminary approach to improve our understanding of the mechanisms controlling the establishment of such N2-fixing associations has been developed, using two maize inbred lines exhibiting different physiological characteristics. The bacterial-plant interaction has been characterized by means of a metabolomic approach. Two established model strains of Nif+ diazotrophic bacteria, Herbaspirillum seropedicae and Azospirillum brasilense and their Nif- couterparts defficient in nitrogenase activity, were used to evaluate the impact of the bacterial inoculation and of N2 fixation on the root and leaf metabolic profiles. The two N2-fixing bacteria have been used to inoculate two genetically distant maize lines (FV252 and FV2), already characterized for their contrasting physiological properties. Using a well-controlled gnotobiotic experimental system that allows inoculation of maize plants with the two diazotrophs in a N-free medium, we demonstrated that both maize lines were efficiently colonized by the two bacterial species. We also showed that in the early stages of plant development, both bacterial strains were able to reduce acetylene, suggesting that they contain functional nitrogenase activity and are able to efficiently fix atmospheric N2 (Fix+). The metabolomic approach allowed the identification of metabolites in the two maize lines that were representative of the N2 fixing plant-bacterial interaction, these included mannitol and to a lesser extend trehalose and isocitrate. Whilst other metabolites such as asparagine, although only exhibiting a small increase in maize roots following bacterial infection, were specific for the two Fix+ bacterial strains, in comparison to their Fix- counterparts. Moreover, a number of metabolites exhibited a maize-genotype specific pattern of accumulation, suggesting that the highly diverse maize genetic resources could be further exploited in terms of beneficial plant-bacterial interactions for optimizing maize growth, with reduced N fertilization inputs.

Arsenic Hyperaccumulation Strategies: An Overview

PubMed Central

Souri, Zahra; Karimi, Naser; Sandalio, Luisa M.

2017-01-01

Arsenic (As) pollution, which is on the increase around the world, poses a growing threat to the environment. Phytoremediation, an important green technology, uses different strategies, including As uptake, transport, translocation, and detoxification, to remediate this metalloid. Arsenic hyperaccumulator plants have developed various strategies to accumulate and tolerate high concentrations of As. In these plants, the formation of AsIII complexes with GSH and phytochelatins and their transport into root and shoot vacuoles constitute important mechanisms for coping with As stress. The oxidative stress induced by reactive oxygen species (ROS) production is one of the principal toxic effects of As; moreover, the strong antioxidative defenses in hyperaccumulator plants could constitute an important As detoxification strategy. On the other hand, nitric oxide activates antioxidant enzyme and phytochelatins biosynthesis which enhances As stress tolerance in plants. Although several studies have focused on transcription, metabolomics, and proteomic changes in plants induced by As, the mechanisms involved in As transport, translocation, and detoxification in hyperaccumulator plants need to be studied in greater depth. This review updates recent progress made in the study of As uptake, translocation, chelation, and detoxification in As hyperaccumulator plants. PMID:28770198

Systems Biology of Metabolic Regulation by Estrogen Receptor Signaling in Breast Cancer.

PubMed

Zhao, Yiru Chen; Madak Erdogan, Zeynep

2016-03-17

With the advent of the -omics approaches our understanding of the chronic diseases like cancer and metabolic syndrome has improved. However, effective mining of the information in the large-scale datasets that are obtained from gene expression microarrays, deep sequencing experiments or metabolic profiling is essential to uncover and then effectively target the critical regulators of diseased cell phenotypes. Estrogen Receptor α (ERα) is one of the master transcription factors regulating the gene programs that are important for estrogen responsive breast cancers. In order to understand to role of ERα signaling in breast cancer metabolism we utilized transcriptomic, cistromic and metabolomic data from MCF-7 cells treated with estradiol. In this report we described generation of samples for RNA-Seq, ChIP-Seq and metabolomics experiments and the integrative computational analysis of the obtained data. This approach is useful in delineating novel molecular mechanisms and gene regulatory circuits that are regulated by a particular transcription factor which impacts metabolism of normal or diseased cells.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schwender, Jorg; Konig, Christina; Klapperstuck, Matthias

An attempt has been made to define the extent to which metabolic flux in central plant metabolism is reflected by changes in the transcriptome and metabolome, based on an analysis of in vitro cultured immature embryos of two oilseed rape (Brassica napus) accessions which contrast for seed lipid accumulation. Metabolic flux analysis (MFA) was used to constrain a flux balance metabolic model which included 671 biochemical and transport reactions within the central metabolism. This highly confident flux information was eventually used for comparative analysis of flux vs. transcript (metabolite). Metabolite profiling succeeded in identifying 79 intermediates within the central metabolism,more » some of which differed quantitatively between the two accessions and displayed a significant shift corresponding to flux. An RNA-Seq based transcriptome analysis revealed a large number of genes which were differentially transcribed in the two accessions, including some enzymes/proteins active in major metabolic pathways. With a few exceptions, differential activity in the major pathways (glycolysis, TCA cycle, amino acid, and fatty acid synthesis) was not reflected in contrasting abundances of the relevant transcripts. The conclusion was that transcript abundance on its own cannot be used to infer metabolic activity/fluxes in central plant metabolism. Lastly, this limitation needs to be borne in mind in evaluating transcriptome data and designing metabolic engineering experiments.« less

Co-Culture of Plant Beneficial Microbes as Source of Bioactive Metabolites.

PubMed

Vinale, F; Nicoletti, R; Borrelli, F; Mangoni, A; Parisi, O A; Marra, R; Lombardi, N; Lacatena, F; Grauso, L; Finizio, S; Lorito, M; Woo, S L

2017-10-30

In microbial cultures the production of secondary metabolites is affected by experimental conditions, and the discovery of novel compounds is often prevented by the re-isolation of known metabolites. To limit this, it is possible to cultivate microorganisms by simulating naturally occurring interactions, where microbes co-exist in complex communities. In this work, co-culturing experiments of the biocontrol agent Trichoderma harzianum M10 and the endophyte Talaromyces pinophilus F36CF have been performed to elicit the expression of genes which are not transcribed in standard laboratory assays. Metabolomic analysis revealed that the co-culture induced the accumulation of siderophores for both fungi, while production of M10 harzianic and iso-harzianic acids was not affected by F36CF. Conversely, metabolites of the latter strain, 3-O-methylfunicone and herquline B, were less abundant when M10 was present. A novel compound, hereby named harziaphilic acid, was isolated from fungal co-cultures, and fully characterized. Moreover, harzianic and harziaphilic acids did not affect viability of colorectal cancer and healthy colonic epithelial cells, but selectively reduced cancer cell proliferation. Our results demonstrated that the co-cultivation of plant beneficial fungi may represent an effective strategy to modulate the production of bioactive metabolites and possibly identify novel compounds.

Common bean varieties demonstrate differential physiological and metabolic responses to the pathogenic fungus Sclerotinia sclerotiorum.

PubMed

Robison, Faith M; Turner, Marie F; Jahn, Courtney E; Schwartz, Howard F; Prenni, Jessica E; Brick, Mark A; Heuberger, Adam L

2018-02-24

Plant physiology and metabolism are important components of a plant response to microbial pathogens. Physiological resistance of common bean (Phaseolus vulgaris L.) to the fungal pathogen Sclerotinia sclerotiorum has been established, but the mechanisms of resistance are largely unknown. Here, the physiological and metabolic responses of bean varieties that differ in physiological resistance to S. sclerotiorum are investigated. Upon infection, the resistant bean variety A195 had a unique physiological response that included reduced photosynthesis and maintaining a higher leaf surface pH during infection. Leaf metabolomics was performed on healthy tissue adjacent to the necrotic lesion at 16, 24, and 48 hr post inoculation, and 144 metabolites were detected that varied between A195 and Sacramento following infection. The metabolites that varied in leaves included amines/amino acids, organic acids, phytoalexins, and ureides. The metabolic pathways associated with resistance included amine metabolism, uriede-based nitrogen remobilization, antioxidant production, and bean-specific phytoalexin production. A second experiment was conducted in stems of 13 bean genotypes with varying resistance. Stem resistance was associated with phytoalexin production, but unlike leaf metabolism, lipid changes were associated with susceptibility. Taken together, the data supports a multifaceted, physiometabolic response of common bean to S. sclerotiorum that mediates resistance. © 2018 John Wiley & Sons Ltd.

Metabolomic profiling of the phytomedicinal constituents of Carica papaya L. leaves and seeds by 1H NMR spectroscopy and multivariate statistical analysis.

PubMed

Gogna, Navdeep; Hamid, Neda; Dorai, Kavita

2015-11-10

Extracts from the Carica papaya L. plant are widely reported to contain metabolites with antibacterial, antioxidant and anticancer activity. This study aims to analyze the metabolic profiles of papaya leaves and seeds in order to gain insights into their phytomedicinal constituents. We performed metabolite fingerprinting using 1D and 2D 1H NMR experiments and used multivariate statistical analysis to identify those plant parts that contain the most concentrations of metabolites of phytomedicinal value. Secondary metabolites such as phenyl propanoids, including flavonoids, were found in greater concentrations in the leaves as compared to the seeds. UPLC-ESI-MS verified the presence of significant metabolites in the papaya extracts suggested by the NMR analysis. Interestingly, the concentration of eleven secondary metabolites namely caffeic, cinnamic, chlorogenic, quinic, coumaric, vanillic, and protocatechuic acids, naringenin, hesperidin, rutin, and kaempferol, were higher in young as compared to old papaya leaves. The results of the NMR analysis were corroborated by estimating the total phenolic and flavonoid content of the extracts. Estimation of antioxidant activity in leaves and seed extracts by DPPH and ABTS in-vitro assays and antioxidant capacity in C2C12 cell line also showed that papaya extracts exhibit high antioxidant activity. Copyright © 2015 Elsevier B.V. All rights reserved.

Time-saving design of experiment protocol for optimization of LC-MS data processing in metabolomic approaches.

PubMed

Zheng, Hong; Clausen, Morten Rahr; Dalsgaard, Trine Kastrup; Mortensen, Grith; Bertram, Hanne Christine

2013-08-06

We describe a time-saving protocol for the processing of LC-MS-based metabolomics data by optimizing parameter settings in XCMS and threshold settings for removing noisy and low-intensity peaks using design of experiment (DoE) approaches including Plackett-Burman design (PBD) for screening and central composite design (CCD) for optimization. A reliability index, which is based on evaluation of the linear response to a dilution series, was used as a parameter for the assessment of data quality. After identifying the significant parameters in the XCMS software by PBD, CCD was applied to determine their values by maximizing the reliability and group indexes. Optimal settings by DoE resulted in improvements of 19.4% and 54.7% in the reliability index for a standard mixture and human urine, respectively, as compared with the default setting, and a total of 38 h was required to complete the optimization. Moreover, threshold settings were optimized by using CCD for further improvement. The approach combining optimal parameter setting and the threshold method improved the reliability index about 9.5 times for a standards mixture and 14.5 times for human urine data, which required a total of 41 h. Validation results also showed improvements in the reliability index of about 5-7 times even for urine samples from different subjects. It is concluded that the proposed methodology can be used as a time-saving approach for improving the processing of LC-MS-based metabolomics data.

Metabolomics of cereals under biotic stress: current knowledge and techniques

PubMed Central

Balmer, Dirk; Flors, Victor; Glauser, Gaetan; Mauch-Mani, Brigitte

2013-01-01

Prone to attacks by pathogens and pests, plants employ intricate chemical defense mechanisms consisting of metabolic adaptations. However, many plant attackers are manipulating the host metabolism to counteract defense responses and to induce favorable nutritional conditions. Advances in analytical chemistry have allowed the generation of extensive metabolic profiles during plant-pathogen and pest interactions. Thereby, metabolic processes were found to be highly specific for given tissues, species, and plant-pathogen/pest interactions. The clusters of identified compounds not only serve as base in the quest of novel defense compounds, but also as markers for the characterization of the plants' defensive state. The latter is especially useful in agronomic applications where meaningful markers are essential for crop protection. Cereals such as maize make use of their metabolic arsenal during both local and systemic defense responses, and the chemical response is highly adapted to specific attackers. Here, we summarize highlights and recent findings of metabolic patterns of cereals under pathogen and pest attack. PMID:23630531

Contact chemosensation of phytochemicals by insect herbivores

PubMed Central

Burse, Antje

2017-01-01

Contact chemosensation, or tasting, is a complex process governed by nonvolatile phytochemicals that tell host-seeking insects whether they should accept or reject a plant. During this process, insect gustatory receptors (GRs) contribute to deciphering a host plant's metabolic code. GRs recognise many different classes of nonvolatile compounds; some GRs are likely to be narrowly tuned and others, broadly tuned. Although primary and/or secondary plant metabolites influence the insect's feeding choice, their decoding by GRs is challenging, because metabolites in planta occur in complex mixtures that have additive or inhibitory effects; in diverse forms composed of structurally unrelated molecules; and at different concentrations depending on the plant species, its tissue and developmental stage. Future studies of the mechanism of insect herbivore GRs will benefit from functional characterisation taking into account the spatio-temporal dynamics and diversity of the plant's metabolome. Metabolic information, in turn, will help to elucidate the impact of single ligands and complex natural mixtures on the insect's feeding choice. PMID:28485430

2010 Plant Molecular Biology Gordon Research Conference

DOE Office of Scientific and Technical Information (OSTI.GOV)

Michael Sussman

The Plant Molecular Biology Conference has traditionally covered a breadth of exciting topics and the 2010 conference will continue in that tradition. Emerging concerns about food security have inspired a program with three main themes: (1) genomics, natural variation and breeding to understand adaptation and crop improvement, (2) hormonal cross talk, and (3) plant/microbe interactions. There are also sessions on epigenetics and proteomics/metabolomics. Thus this conference will bring together a range of disciplines, will foster the exchange of ideas and enable participants to learn of the latest developments and ideas in diverse areas of plant biology. The conference provides anmore » excellent opportunity for individuals to discuss their research because additional speakers in each session will be selected from submitted abstracts. There will also be a poster session each day for a two-hour period prior to dinner. In particular, this conference plays a key role in enabling students and postdocs (the next generation of research leaders) to mingle with pioneers in multiple areas of plant science.« less

Plant iTRAQ-based proteomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Handakumbura, Pubudu; Hixson, Kim K.; Purvine, Samuel O.

We present a simple one-­pot extraction protocol, which rapidly isolates hydrophyllic metabolites, lipids, and proteins from the same pulverized plant sample. Also detailed is a global plant proteomics sample preparation method utilizing iTRAQ multiplexing reagents that enables deep proteome coverage due to the use of HPLC fractionation of the peptides prior to mass spectrometric analysis. We have successfully used this protocol on several different plant tissues (e.g., roots, stems, leaves) from different plants (e.g., sorghum, poplar, Arabidopsis, soybean), and have been able to successfully detect and quantify thousands of proteins. Multiplexing strategies such as iTRAQ and the bioinformatics strategy outlinedmore » here, ultimately provide insight into which proteins are significantly changed in abundance between two or more groups (e.g., control, perturbation). Our bioinformatics strategy yields z-­score values, which normalize the expression data into a format that can easily be cross-­compared with other expression data (i.e., metabolomics, transcriptomics) obtained from different analytical methods and instrumentation.« less

Functional molecular markers for crop improvement.

PubMed

Kage, Udaykumar; Kumar, Arun; Dhokane, Dhananjay; Karre, Shailesh; Kushalappa, Ajjamada C

2016-10-01

A tremendous decline in cultivable land and resources and a huge increase in food demand calls for immediate attention to crop improvement. Though molecular plant breeding serves as a viable solution and is considered as "foundation for twenty-first century crop improvement", a major stumbling block for crop improvement is the availability of a limited functional gene pool for cereal crops. Advancement in the next generation sequencing (NGS) technologies integrated with tools like metabolomics, proteomics and association mapping studies have facilitated the identification of candidate genes, their allelic variants and opened new avenues to accelerate crop improvement through development and use of functional molecular markers (FMMs). The FMMs are developed from the sequence polymorphisms present within functional gene(s) which are associated with phenotypic trait variations. Since FMMs obviate the problems associated with random DNA markers, these are considered as "the holy grail" of plant breeders who employ targeted marker assisted selections (MAS) for crop improvement. This review article attempts to consider the current resources and novel methods such as metabolomics, proteomics and association studies for the identification of candidate genes and their validation through virus-induced gene silencing (VIGS) for the development of FMMs. A number of examples where the FMMs have been developed and used for the improvement of cereal crops for agronomic, food quality, disease resistance and abiotic stress tolerance traits have been considered.

Comparison of partial least squares and random forests for evaluating relationship between phenolics and bioactivities of Neptunia oleracea.

PubMed

Lee, Soo Yee; Mediani, Ahmed; Maulidiani, Maulidiani; Khatib, Alfi; Ismail, Intan Safinar; Zawawi, Norhasnida; Abas, Faridah

2018-01-01

Neptunia oleracea is a plant consumed as a vegetable and which has been used as a folk remedy for several diseases. Herein, two regression models (partial least squares, PLS; and random forest, RF) in a metabolomics approach were compared and applied to the evaluation of the relationship between phenolics and bioactivities of N. oleracea. In addition, the effects of different extraction conditions on the phenolic constituents were assessed by pattern recognition analysis. Comparison of the PLS and RF showed that RF exhibited poorer generalization and hence poorer predictive performance. Both the regression coefficient of PLS and the variable importance of RF revealed that quercetin and kaempferol derivatives, caffeic acid and vitexin-2-O-rhamnoside were significant towards the tested bioactivities. Furthermore, principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) results showed that sonication and absolute ethanol are the preferable extraction method and ethanol ratio, respectively, to produce N. oleracea extracts with high phenolic levels and therefore high DPPH scavenging and α-glucosidase inhibitory activities. Both PLS and RF are useful regression models in metabolomics studies. This work provides insight into the performance of different multivariate data analysis tools and the effects of different extraction conditions on the extraction of desired phenolics from plants. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

A guide to the identification of metabolites in NMR-based metabonomics/metabolomics experiments.

PubMed

Dona, Anthony C; Kyriakides, Michael; Scott, Flora; Shephard, Elizabeth A; Varshavi, Dorsa; Veselkov, Kirill; Everett, Jeremy R

2016-01-01

Metabonomics/metabolomics is an important science for the understanding of biological systems and the prediction of their behaviour, through the profiling of metabolites. Two technologies are routinely used in order to analyse metabolite profiles in biological fluids: nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), the latter typically with hyphenation to a chromatography system such as liquid chromatography (LC), in a configuration known as LC-MS. With both NMR and MS-based detection technologies, the identification of the metabolites in the biological sample remains a significant obstacle and bottleneck. This article provides guidance on methods for metabolite identification in biological fluids using NMR spectroscopy, and is illustrated with examples from recent studies on mice.

Training in metabolomics research. II. Processing and statistical analysis of metabolomics data, metabolite identification, pathway analysis, applications of metabolomics and its future

PubMed Central

Barnes, Stephen; Benton, H. Paul; Casazza, Krista; Cooper, Sara; Cui, Xiangqin; Du, Xiuxia; Engler, Jeffrey; Kabarowski, Janusz H.; Li, Shuzhao; Pathmasiri, Wimal; Prasain, Jeevan K.; Renfrow, Matthew B.; Tiwari, Hemant K.

2017-01-01

Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites, and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. This second part of a comprehensive description of the methods of metabolomics focuses on data analysis, emerging methods in metabolomics and the future of this discipline. PMID:28239968

THE ATHENS LAB'S ROLE IN EPA'S COMPUTATIONAL TOXICOLOGY PROGRAM WITH AN EMPHASIS ON METABOLOMICS AS A DIAGNOSTIC TOOL FOR TOXICOLOGY

EPA Science Inventory

This presentation gives a brief introduction to EPA's computational toxicology program and the Athens Lab's role in it. The talk also covered a brief introduction to metabolomics; advantages/disadvanage of metabolomics for toxicity assessment; goals of the EPA Athens metabolomics...

Can Untargeted Metabolomics Be Utilized in Drug Discovery/Development?

PubMed

Caldwell, Gary W; Leo, Gregory C

2017-01-01

Untargeted metabolomics is a promising approach for reducing the significant attrition rate for discovering and developing drugs in the pharmaceutical industry. This review aims to highlight the practical decision-making value of untargeted metabolomics for the advancement of drug candidates in drug discovery/development including potentially identifying and validating novel therapeutic targets, creating alternative screening paradigms, facilitating the selection of specific and translational metabolite biomarkers, identifying metabolite signatures for the drug efficacy mechanism of action, and understanding potential drug-induced toxicity. The review provides an overview of the pharmaceutical process workflow to discover and develop new small molecule drugs followed by the metabolomics process workflow that is involved in conducting metabolomics studies. The pros and cons of the major components of the pharmaceutical and metabolomics workflows are reviewed and discussed. Finally, selected untargeted metabolomics literature examples, from primarily 2010 to 2016, are used to illustrate why, how, and where untargeted metabolomics can be integrated into the drug discovery/preclinical drug development process. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Metabolomics in amyotrophic lateral sclerosis: how far can it take us?

PubMed

Blasco, H; Patin, F; Madji Hounoum, B; Gordon, P H; Vourc'h, P; Andres, C R; Corcia, P

2016-03-01

Amyotrophic lateral sclerosis (ALS) is the most common adult-onset motor neuron disease. Alongside identification of aetiologies, development of biomarkers is a foremost research priority. Metabolomics is one promising approach that is being utilized in the search for diagnosis and prognosis markers. Our aim is to provide an overview of the principal research in metabolomics applied to ALS. References were identified using PubMed with the terms 'metabolomics' or 'metabolomic' and 'ALS' or 'amyotrophic lateral sclerosis' or 'MND' or 'motor neuron disorders'. To date, nine articles have reported metabolomics research in patients and a few additional studies examined disease physiology and drug effects in patients or models. Metabolomics contribute to a better understanding of ALS pathophysiology but, to date, no biomarker has been validated for diagnosis, principally due to the heterogeneity of the disease and the absence of applied standardized methodology for biomarker discovery. A consensus on best metabolomics methodology as well as systematic independent validation will be an important accomplishment on the path to identifying the long-awaited biomarkers for ALS and to improve clinical trial designs. © 2016 EAN.

The Human Serum Metabolome

PubMed Central

Psychogios, Nikolaos; Hau, David D.; Peng, Jun; Guo, An Chi; Mandal, Rupasri; Bouatra, Souhaila; Sinelnikov, Igor; Krishnamurthy, Ramanarayan; Eisner, Roman; Gautam, Bijaya; Young, Nelson; Xia, Jianguo; Knox, Craig; Dong, Edison; Huang, Paul; Hollander, Zsuzsanna; Pedersen, Theresa L.; Smith, Steven R.; Bamforth, Fiona; Greiner, Russ; McManus, Bruce; Newman, John W.; Goodfriend, Theodore; Wishart, David S.

2011-01-01

Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically important biofluids, such as cerebrospinal fluid, urine and blood. As part of an ongoing effort to systematically characterize the human metabolome through the Human Metabolome Project, we have undertaken the task of characterizing the human serum metabolome. In doing so, we have combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with today's technology) in the human serum metabolome. Our use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these platforms or technologies. Tables containing the complete set of 4229 confirmed and highly probable human serum compounds, their concentrations, related literature references and links to their known disease associations are freely available at http://www.serummetabolome.ca. PMID:21359215

Metabolomics in chemical ecology.

PubMed

Kuhlisch, Constanze; Pohnert, Georg

2015-07-01

Chemical ecology elucidates the nature and role of natural products as mediators of organismal interactions. The emerging techniques that can be summarized under the concept of metabolomics provide new opportunities to study such environmentally relevant signaling molecules. Especially comparative tools in metabolomics enable the identification of compounds that are regulated during interaction situations and that might play a role as e.g. pheromones, allelochemicals or in induced and activated defenses. This approach helps overcoming limitations of traditional bioassay-guided structure elucidation approaches. But the power of metabolomics is not limited to the comparison of metabolic profiles of interacting partners. Especially the link to other -omics techniques helps to unravel not only the compounds in question but the entire biosynthetic and genetic re-wiring, required for an ecological response. This review comprehensively highlights successful applications of metabolomics in chemical ecology and discusses existing limitations of these novel techniques. It focuses on recent developments in comparative metabolomics and discusses the use of metabolomics in the systems biology of organismal interactions. It also outlines the potential of large metabolomics initiatives for model organisms in the field of chemical ecology.

Siderophore biosynthesis coordinately modulated the virulence-associated interactive metabolome of uropathogenic Escherichia coli and human urine

PubMed Central

Su, Qiao; Guan, Tianbing; Lv, Haitao

2016-01-01

Uropathogenic Escherichia coli (UPEC) growth in women’s bladders during urinary tract infection (UTI) incurs substantial chemical exchange, termed the “interactive metabolome”, which primarily accounts for the metabolic costs (utilized metabolome) and metabolic donations (excreted metabolome) between UPEC and human urine. Here, we attempted to identify the individualized interactive metabolome between UPEC and human urine. We were able to distinguish UPEC from non-UPEC by employing a combination of metabolomics and genetics. Our results revealed that the interactive metabolome between UPEC and human urine was markedly different from that between non-UPEC and human urine, and that UPEC triggered much stronger perturbations in the interactive metabolome in human urine. Furthermore, siderophore biosynthesis coordinately modulated the individualized interactive metabolome, which we found to be a critical component of UPEC virulence. The individualized virulence-associated interactive metabolome contained 31 different metabolites and 17 central metabolic pathways that were annotated to host these different metabolites, including energetic metabolism, amino acid metabolism, and gut microbe metabolism. Changes in the activities of these pathways mechanistically pinpointed the virulent capability of siderophore biosynthesis. Together, our findings provide novel insights into UPEC virulence, and we propose that siderophores are potential targets for further discovery of drugs to treat UPEC-induced UTI. PMID:27076285

Metabolomics in Toxicology and Preclinical Research

PubMed Central

Ramirez, Tzutzuy; Daneshian, Mardas; Kamp, Hennicke; Bois, Frederic Y.; Clench, Malcolm R.; Coen, Muireann; Donley, Beth; Fischer, Steven M.; Ekman, Drew R.; Fabian, Eric; Guillou, Claude; Heuer, Joachim; Hogberg, Helena T.; Jungnickel, Harald; Keun, Hector C.; Krennrich, Gerhard; Krupp, Eckart; Luch, Andreas; Noor, Fozia; Peter, Erik; Riefke, Bjoern; Seymour, Mark; Skinner, Nigel; Smirnova, Lena; Verheij, Elwin; Wagner, Silvia; Hartung, Thomas; van Ravenzwaay, Bennard; Leist, Marcel

2013-01-01

Summary Metabolomics, the comprehensive analysis of metabolites in a biological system, provides detailed information about the biochemical/physiological status of a biological system, and about the changes caused by chemicals. Metabolomics analysis is used in many fields, ranging from the analysis of the physiological status of genetically modified organisms in safety science to the evaluation of human health conditions. In toxicology, metabolomics is the -omics discipline that is most closely related to classical knowledge of disturbed biochemical pathways. It allows rapid identification of the potential targets of a hazardous compound. It can give information on target organs and often can help to improve our understanding regarding the mode-of-action of a given compound. Such insights aid the discovery of biomarkers that either indicate pathophysiological conditions or help the monitoring of the efficacy of drug therapies. The first toxicological applications of metabolomics were for mechanistic research, but different ways to use the technology in a regulatory context are being explored. Ideally, further progress in that direction will position the metabolomics approach to address the challenges of toxicology of the 21st century. To address these issues, scientists from academia, industry, and regulatory bodies came together in a workshop to discuss the current status of applied metabolomics and its potential in the safety assessment of compounds. We report here on the conclusions of three working groups addressing questions regarding 1) metabolomics for in vitro studies 2) the appropriate use of metabolomics in systems toxicology, and 3) use of metabolomics in a regulatory context. PMID:23665807

Atmospheric vs. anaerobic processing of metabolome samples for the metabolite profiling of a strict anaerobic bacterium, Clostridium acetobutylicum.

PubMed

Lee, Sang-Hyun; Kim, Sooah; Kwon, Min-A; Jung, Young Hoon; Shin, Yong-An; Kim, Kyoung Heon

2014-12-01

Well-established metabolome sample preparation is a prerequisite for reliable metabolomic data. For metabolome sampling of a Gram-positive strict anaerobe, Clostridium acetobutylicum, fast filtration and metabolite extraction with acetonitrile/methanol/water (2:2:1, v/v) at -20°C under anaerobic conditions has been commonly used. This anaerobic metabolite processing method is laborious and time-consuming since it is conducted in an anaerobic chamber. Also, there have not been any systematic method evaluation and development of metabolome sample preparation for strict anaerobes and Gram-positive bacteria. In this study, metabolome sampling and extraction methods were rigorously evaluated and optimized for C. acetobutylicum by using gas chromatography/time-of-flight mass spectrometry-based metabolomics, in which a total of 116 metabolites were identified. When comparing the atmospheric (i.e., in air) and anaerobic (i.e., in an anaerobic chamber) processing of metabolome sample preparation, there was no significant difference in the quality and quantity of the metabolomic data. For metabolite extraction, pure methanol at -20°C was a better solvent than acetonitrile/methanol/water (2:2:1, v/v/v) at -20°C that is frequently used for C. acetobutylicum, and metabolite profiles were significantly different depending on extraction solvents. This is the first evaluation of metabolite sample preparation under aerobic processing conditions for an anaerobe. This method could be applied conveniently, efficiently, and reliably to metabolome analysis for strict anaerobes in air. © 2014 Wiley Periodicals, Inc.

Create, run, share, publish, and reference your LC-MS, FIA-MS, GC-MS, and NMR data analysis workflows with the Workflow4Metabolomics 3.0 Galaxy online infrastructure for metabolomics.

PubMed

Guitton, Yann; Tremblay-Franco, Marie; Le Corguillé, Gildas; Martin, Jean-François; Pétéra, Mélanie; Roger-Mele, Pierrick; Delabrière, Alexis; Goulitquer, Sophie; Monsoor, Misharl; Duperier, Christophe; Canlet, Cécile; Servien, Rémi; Tardivel, Patrick; Caron, Christophe; Giacomoni, Franck; Thévenot, Etienne A

2017-12-01

Metabolomics is a key approach in modern functional genomics and systems biology. Due to the complexity of metabolomics data, the variety of experimental designs, and the multiplicity of bioinformatics tools, providing experimenters with a simple and efficient resource to conduct comprehensive and rigorous analysis of their data is of utmost importance. In 2014, we launched the Workflow4Metabolomics (W4M; http://workflow4metabolomics.org) online infrastructure for metabolomics built on the Galaxy environment, which offers user-friendly features to build and run data analysis workflows including preprocessing, statistical analysis, and annotation steps. Here we present the new W4M 3.0 release, which contains twice as many tools as the first version, and provides two features which are, to our knowledge, unique among online resources. First, data from the four major metabolomics technologies (i.e., LC-MS, FIA-MS, GC-MS, and NMR) can be analyzed on a single platform. By using three studies in human physiology, alga evolution, and animal toxicology, we demonstrate how the 40 available tools can be easily combined to address biological issues. Second, the full analysis (including the workflow, the parameter values, the input data and output results) can be referenced with a permanent digital object identifier (DOI). Publication of data analyses is of major importance for robust and reproducible science. Furthermore, the publicly shared workflows are of high-value for e-learning and training. The Workflow4Metabolomics 3.0 e-infrastructure thus not only offers a unique online environment for analysis of data from the main metabolomics technologies, but it is also the first reference repository for metabolomics workflows. Copyright © 2017 Elsevier Ltd. All rights reserved.

Microbiome and metabolome modifying effects of several cardiovascular disease interventions in apo-E-/- mice.

PubMed

Ryan, Paul M; London, Lis E E; Bjorndahl, Trent C; Mandal, Rupasri; Murphy, Kiera; Fitzgerald, Gerald F; Shanahan, Fergus; Ross, R Paul; Wishart, David S; Caplice, Noel M; Stanton, Catherine

2017-03-13

There is strong evidence indicating that gut microbiota have the potential to modify, or be modified by the drugs and nutritional interventions that we rely upon. This study aims to characterize the compositional and functional effects of several nutritional, neutraceutical, and pharmaceutical cardiovascular disease interventions on the gut microbiome, through metagenomic and metabolomic approaches. Apolipoprotein-E-deficient mice were fed for 24 weeks either high-fat/cholesterol diet alone (control, HFC) or high-fat/cholesterol in conjunction with one of three dietary interventions, as follows: plant sterol ester (PSE), oat β-glucan (OBG) and bile salt hydrolase-active Lactobacillus reuteri APC 2587 (BSH), or the drug atorvastatin (STAT). The gut microbiome composition was then investigated, in addition to the host fecal and serum metabolome. We observed major shifts in the composition of the gut microbiome of PSE mice, while OBG and BSH mice displayed more modest fluctuations, and STAT showed relatively few alterations. Interestingly, these compositional effects imparted by PSE were coupled with an increase in acetate and reduction in isovalerate (p < 0.05), while OBG promoted n-butyrate synthesis (p < 0.01). In addition, PSE significantly dampened the microbial production of the proatherogenic precursor compound, trimethylamine (p < 0.05), attenuated cholesterol accumulation, and nearly abolished atherogenesis in the model (p < 0.05). However, PSE supplementation produced the heaviest mice with the greatest degree of adiposity (p < 0.05). Finally, PSE, OBG, and STAT all appeared to have considerable impact on the host serum metabolome, including alterations in several acylcarnitines previously associated with a state of metabolic dysfunction (p < 0.05). We observed functional alterations in microbial and host-derived metabolites, which may have important implications for systemic metabolic health, suggesting that cardiovascular disease interventions may have a significant impact on the microbiome composition and functionality. This study indicates that the gut microbiome-modifying effects of novel therapeutics should be considered, in addition to the direct host effects.

Haystack, a web-based tool for metabolomics research

PubMed Central

2014-01-01

Background Liquid chromatography coupled to mass spectrometry (LCMS) has become a widely used technique in metabolomics research for differential profiling, the broad screening of biomolecular constituents across multiple samples to diagnose phenotypic differences and elucidate relevant features. However, a significant limitation in LCMS-based metabolomics is the high-throughput data processing required for robust statistical analysis and data modeling for large numbers of samples with hundreds of unique chemical species. Results To address this problem, we developed Haystack, a web-based tool designed to visualize, parse, filter, and extract significant features from LCMS datasets rapidly and efficiently. Haystack runs in a browser environment with an intuitive graphical user interface that provides both display and data processing options. Total ion chromatograms (TICs) and base peak chromatograms (BPCs) are automatically displayed, along with time-resolved mass spectra and extracted ion chromatograms (EICs) over any mass range. Output files in the common .csv format can be saved for further statistical analysis or customized graphing. Haystack's core function is a flexible binning procedure that converts the mass dimension of the chromatogram into a set of interval variables that can uniquely identify a sample. Binned mass data can be analyzed by exploratory methods such as principal component analysis (PCA) to model class assignment and identify discriminatory features. The validity of this approach is demonstrated by comparison of a dataset from plants grown at two light conditions with manual and automated peak detection methods. Haystack successfully predicted class assignment based on PCA and cluster analysis, and identified discriminatory features based on analysis of EICs of significant bins. Conclusion Haystack, a new online tool for rapid processing and analysis of LCMS-based metabolomics data is described. It offers users a range of data visualization options and supports non-biased differential profiling studies through a unique and flexible binning function that provides an alternative to conventional peak deconvolution analysis methods. PMID:25350247

Haystack, a web-based tool for metabolomics research.

PubMed

Grace, Stephen C; Embry, Stephen; Luo, Heng

2014-01-01

Liquid chromatography coupled to mass spectrometry (LCMS) has become a widely used technique in metabolomics research for differential profiling, the broad screening of biomolecular constituents across multiple samples to diagnose phenotypic differences and elucidate relevant features. However, a significant limitation in LCMS-based metabolomics is the high-throughput data processing required for robust statistical analysis and data modeling for large numbers of samples with hundreds of unique chemical species. To address this problem, we developed Haystack, a web-based tool designed to visualize, parse, filter, and extract significant features from LCMS datasets rapidly and efficiently. Haystack runs in a browser environment with an intuitive graphical user interface that provides both display and data processing options. Total ion chromatograms (TICs) and base peak chromatograms (BPCs) are automatically displayed, along with time-resolved mass spectra and extracted ion chromatograms (EICs) over any mass range. Output files in the common .csv format can be saved for further statistical analysis or customized graphing. Haystack's core function is a flexible binning procedure that converts the mass dimension of the chromatogram into a set of interval variables that can uniquely identify a sample. Binned mass data can be analyzed by exploratory methods such as principal component analysis (PCA) to model class assignment and identify discriminatory features. The validity of this approach is demonstrated by comparison of a dataset from plants grown at two light conditions with manual and automated peak detection methods. Haystack successfully predicted class assignment based on PCA and cluster analysis, and identified discriminatory features based on analysis of EICs of significant bins. Haystack, a new online tool for rapid processing and analysis of LCMS-based metabolomics data is described. It offers users a range of data visualization options and supports non-biased differential profiling studies through a unique and flexible binning function that provides an alternative to conventional peak deconvolution analysis methods.

Applying quantitative metabolomics based on chemical isotope labeling LC-MS for detecting potential milk adulterant in human milk.

PubMed

Mung, Dorothea; Li, Liang

2018-02-25

There is an increasing demand for donor human milk to feed infants for various reasons including that a mother may be unable to provide sufficient amounts of milk for their child or the milk is considered unsafe for the baby. Selling and buying human milk via the Internet has gained popularity. However, there is a risk of human milk sold containing other adulterants such as animal or plant milk. Analytical tools for rapid detection of adulterants in human milk are needed. We report a quantitative metabolomics method for detecting potential milk adulterants (soy, almond, cow, goat and infant formula milk) in human milk. It is based on the use of a high-performance chemical isotope labeling (CIL) LC-MS platform to profile the metabolome of an unknown milk sample, followed by multivariate or univariate comparison of the resultant metabolomic profile with that of human milk to determine the differences. Using dansylation LC-MS to profile the amine/phenol submetabolome, we could detect an average of 4129 ± 297 (n = 9) soy metabolites, 3080 ± 470 (n = 9) almond metabolites, 4256 ± 136 (n = 18) cow metabolites, 4318 ± 198 (n = 9) goat metabolites, 4444 ± 563 (n = 9) infant formula metabolites, and 4020 ± 375 (n = 30) human metabolites. This high level of coverage allowed us to readily differentiate the six different types of samples. From the analysis of binary mixtures of human milk containing 5, 10, 25, 50 and 75% other type of milk, we demonstrated that this method could be used to detect the presence of as low as 5% adulterant in human milk. We envisage that this method could be applied to detect contaminant or adulterant in other types of food or drinks. Copyright © 2017 Elsevier B.V. All rights reserved.

Diversity and association of phenotypic and metabolomic traits in the close model grasses Brachypodium distachyon, B. stacei and B. hybridum

PubMed Central

López-Álvarez, Diana; Zubair, Hassan; Beckmann, Manfred; Draper, John

2017-01-01

Abstract Background and Aims Morphological traits in combination with metabolite fingerprinting were used to investigate inter- and intraspecies diversity within the model annual grasses Brachypodium distachyon, Brachypodium stacei and Brachypodium hybridum. Methods Phenotypic variation of 15 morphological characters and 2219 nominal mass (m/z) signals generated using flow infusion electrospray ionization–mass spectrometry (FIE–MS) were evaluated in individuals from a total of 174 wild populations and six inbred lines, and 12 lines, of the three species, respectively. Basic statistics and multivariate principal component analysis and discriminant analysis were used to differentiate inter- and intraspecific variability of the two types of variable, and their association was assayed with the rcorr function. Key Results Basic statistics and analysis of variance detected eight phenotypic characters [(stomata) leaf guard cell length, pollen grain length, (plant) height, second leaf width, inflorescence length, number of spikelets per inflorescence, lemma length, awn length] and 434 tentatively annotated metabolite signals that significantly discriminated the three species. Three phenotypic traits (pollen grain length, spikelet length, number of flowers per inflorescence) might be genetically fixed. The three species showed different metabolomic profiles. Discriminant analysis significantly discriminated the three taxa with both morphometric and metabolome traits and the intraspecific phenotypic diversity within B. distachyon and B. stacei. The populations of B. hybridum were considerably less differentiated. Conclusions Highly explanatory metabolite signals together with morphological characters revealed concordant patterns of differentiation of the three taxa. Intraspecific phenotypic diversity was observed between northern and southern Iberian populations of B. distachyon and between eastern Mediterranean/south-western Asian and western Mediterranean populations of B. stacei. Significant association was found for pollen grain length and lemma length and ten and six metabolomic signals, respectively. These results would guide the selection of new germplasm lines of the three model grasses in ongoing genome-wide association studies. PMID:28040672

Metabolomic fingerprinting employing DART-TOFMS for authentication of tomatoes and peppers from organic and conventional farming.

PubMed

Novotná, H; Kmiecik, O; Gałązka, M; Krtková, V; Hurajová, A; Schulzová, V; Hallmann, E; Rembiałkowska, E; Hajšlová, J

2012-01-01

The rapidly growing demand for organic food requires the availability of analytical tools enabling their authentication. Recently, metabolomic fingerprinting/profiling has been demonstrated as a challenging option for a comprehensive characterisation of small molecules occurring in plants, since their pattern may reflect the impact of various external factors. In a two-year pilot study, concerned with the classification of organic versus conventional crops, ambient mass spectrometry consisting of a direct analysis in real time (DART) ion source and a time-of-flight mass spectrometer (TOFMS) was employed. This novel methodology was tested on 40 tomato and 24 pepper samples grown under specified conditions. To calculate statistical models, the obtained data (mass spectra) were processed by the principal component analysis (PCA) followed by linear discriminant analysis (LDA). The results from the positive ionisation mode enabled better differentiation between organic and conventional samples than the results from the negative mode. In this case, the recognition ability obtained by LDA was 97.5% for tomato and 100% for pepper samples and the prediction abilities were above 80% for both sample sets. The results suggest that the year of production had stronger influence on the metabolomic fingerprints compared with the type of farming (organic versus conventional). In any case, DART-TOFMS is a promising tool for rapid screening of samples. Establishing comprehensive (multi-sample) long-term databases may further help to improve the quality of statistical classification models.

Multiomics in grape berry skin revealed specific induction of the stilbene synthetic pathway by ultraviolet-C irradiation.

PubMed

Suzuki, Mami; Nakabayashi, Ryo; Ogata, Yoshiyuki; Sakurai, Nozomu; Tokimatsu, Toshiaki; Goto, Susumu; Suzuki, Makoto; Jasinski, Michal; Martinoia, Enrico; Otagaki, Shungo; Matsumoto, Shogo; Saito, Kazuki; Shiratake, Katsuhiro

2015-05-01

Grape (Vitis vinifera) accumulates various polyphenolic compounds, which protect against environmental stresses, including ultraviolet-C (UV-C) light and pathogens. In this study, we looked at the transcriptome and metabolome in grape berry skin after UV-C irradiation, which demonstrated the effectiveness of omics approaches to clarify important traits of grape. We performed transcriptome analysis using a genome-wide microarray, which revealed 238 genes up-regulated more than 5-fold by UV-C light. Enrichment analysis of Gene Ontology terms showed that genes encoding stilbene synthase, a key enzyme for resveratrol synthesis, were enriched in the up-regulated genes. We performed metabolome analysis using liquid chromatography-quadrupole time-of-flight mass spectrometry, and 2,012 metabolite peaks, including unidentified peaks, were detected. Principal component analysis using the peaks showed that only one metabolite peak, identified as resveratrol, was highly induced by UV-C light. We updated the metabolic pathway map of grape in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and in the KaPPA-View 4 KEGG system, then projected the transcriptome and metabolome data on a metabolic pathway map. The map showed specific induction of the resveratrol synthetic pathway by UV-C light. Our results showed that multiomics is a powerful tool to elucidate the accumulation mechanisms of secondary metabolites, and updated systems, such as KEGG and KaPPA-View 4 KEGG for grape, can support such studies. © 2015 American Society of Plant Biologists. All Rights Reserved.

Metabolomic prediction of yield in hybrid rice.

PubMed

Xu, Shizhong; Xu, Yang; Gong, Liang; Zhang, Qifa

2016-10-01

Rice (Oryza sativa) provides a staple food source for more than 50% of the world's population. An increase in yield can significantly contribute to global food security. Hybrid breeding can potentially help to meet this goal because hybrid rice often shows a considerable increase in yield when compared with pure-bred cultivars. We recently developed a marker-guided prediction method for hybrid yield and showed a substantial increase in yield through genomic hybrid breeding. We now have transcriptomic and metabolomic data as potential resources for prediction. Using six prediction methods, including least absolute shrinkage and selection operator (LASSO), best linear unbiased prediction (BLUP), stochastic search variable selection, partial least squares, and support vector machines using the radial basis function and polynomial kernel function, we found that the predictability of hybrid yield can be further increased using these omic data. LASSO and BLUP are the most efficient methods for yield prediction. For high heritability traits, genomic data remain the most efficient predictors. When metabolomic data are used, the predictability of hybrid yield is almost doubled compared with genomic prediction. Of the 21 945 potential hybrids derived from 210 recombinant inbred lines, selection of the top 10 hybrids predicted from metabolites would lead to a ~30% increase in yield. We hypothesize that each metabolite represents a biologically built-in genetic network for yield; thus, using metabolites for prediction is equivalent to using information integrated from these hidden genetic networks for yield prediction. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.

The Interplay between Carbon Availability and Growth in Different Zones of the Growing Maize Leaf.

PubMed

Czedik-Eysenberg, Angelika; Arrivault, Stéphanie; Lohse, Marc A; Feil, Regina; Krohn, Nicole; Encke, Beatrice; Nunes-Nesi, Adriano; Fernie, Alisdair R; Lunn, John E; Sulpice, Ronan; Stitt, Mark

2016-10-01

Plants assimilate carbon in their photosynthetic tissues in the light. However, carbon is required during the night and in nonphotosynthetic organs. It is therefore essential that plants manage their carbon resources spatially and temporally and coordinate growth with carbon availability. In growing maize (Zea mays) leaf blades, a defined developmental gradient facilitates analyses in the cell division, elongation, and mature zones. We investigated the responses of the metabolome and transcriptome and polysome loading, as a qualitative proxy for protein synthesis, at dusk, dawn, and 6, 14, and 24 h into an extended night, and tracked whole-leaf elongation over this time course. Starch and sugars are depleted by dawn in the mature zone, but only after an extension of the night in the elongation and division zones. Sucrose (Suc) recovers partially between 14 and 24 h into the extended night in the growth zones, but not the mature zone. The global metabolome and transcriptome track these zone-specific changes in Suc. Leaf elongation and polysome loading in the growth zones also remain high at dawn, decrease between 6 and 14 h into the extended night, and then partially recover, indicating that growth processes are determined by local carbon status. The level of Suc-signaling metabolite trehalose-6-phosphate, and the trehalose-6-phosphate:Suc ratio are much higher in growth than mature zones at dusk and dawn but fall in the extended night. Candidate genes were identified by searching for transcripts that show characteristic temporal response patterns or contrasting responses to carbon starvation in growth and mature zones. © 2016 American Society of Plant Biologists. All Rights Reserved.

Enhancement of Plant Metabolite Fingerprinting by Machine Learning1[W

PubMed Central

Scott, Ian M.; Vermeer, Cornelia P.; Liakata, Maria; Corol, Delia I.; Ward, Jane L.; Lin, Wanchang; Johnson, Helen E.; Whitehead, Lynne; Kular, Baldeep; Baker, John M.; Walsh, Sean; Dave, Anuja; Larson, Tony R.; Graham, Ian A.; Wang, Trevor L.; King, Ross D.; Draper, John; Beale, Michael H.

2010-01-01

Metabolite fingerprinting of Arabidopsis (Arabidopsis thaliana) mutants with known or predicted metabolic lesions was performed by 1H-nuclear magnetic resonance, Fourier transform infrared, and flow injection electrospray-mass spectrometry. Fingerprinting enabled processing of five times more plants than conventional chromatographic profiling and was competitive for discriminating mutants, other than those affected in only low-abundance metabolites. Despite their rapidity and complexity, fingerprints yielded metabolomic insights (e.g. that effects of single lesions were usually not confined to individual pathways). Among fingerprint techniques, 1H-nuclear magnetic resonance discriminated the most mutant phenotypes from the wild type and Fourier transform infrared discriminated the fewest. To maximize information from fingerprints, data analysis was crucial. One-third of distinctive phenotypes might have been overlooked had data models been confined to principal component analysis score plots. Among several methods tested, machine learning (ML) algorithms, namely support vector machine or random forest (RF) classifiers, were unsurpassed for phenotype discrimination. Support vector machines were often the best performing classifiers, but RFs yielded some particularly informative measures. First, RFs estimated margins between mutant phenotypes, whose relations could then be visualized by Sammon mapping or hierarchical clustering. Second, RFs provided importance scores for the features within fingerprints that discriminated mutants. These scores correlated with analysis of variance F values (as did Kruskal-Wallis tests, true- and false-positive measures, mutual information, and the Relief feature selection algorithm). ML classifiers, as models trained on one data set to predict another, were ideal for focused metabolomic queries, such as the distinctiveness and consistency of mutant phenotypes. Accessible software for use of ML in plant physiology is highlighted. PMID:20566707

Environmental metabolomics: a SWOT analysis (strengths, weaknesses, opportunities, and threats).

PubMed

Miller, Marion G

2007-02-01

Metabolomic approaches have the potential to make an exceptional contribution to understanding how chemicals and other environmental stressors can affect both human and environmental health. However, the application of metabolomics to environmental exposures, although getting underway, has not yet been extensively explored. This review will use a SWOT analysis model to discuss some of the strengths, weaknesses, opportunities, and threats that are apparent to an investigator venturing into this relatively new field. SWOT has been used extensively in business settings to uncover new outlooks and identify problems that would impede progress. The field of environmental metabolomics provides great opportunities for discovery, and this is recognized by a high level of interest in potential applications. However, understanding the biological consequence of environmental exposures can be confounded by inter- and intra-individual differences. Metabolomic profiles can yield a plethora of data, the interpretation of which is complex and still being evaluated and researched. The development of the field will depend on the availability of technologies for data handling and that permit ready access metabolomic databases. Understanding the relevance of metabolomic endpoints to organism health vs adaptation vs variation is an important step in understanding what constitutes a substantive environmental threat. Metabolomic applications in reproductive research are discussed. Overall, the development of a comprehensive mechanistic-based interpretation of metabolomic changes offers the possibility of providing information that will significantly contribute to the protection of human health and the environment.

[Exploring the mechanism of rhizoma coptidis in treating type II diabetes mellitus based on metabolomics by gas chromatography-mass spectrometry].

PubMed

Wang, Jing; Yuan, Zimin; Kong, Hongwei; Li, Yong; Lu, Xin; Xu, Guowang

2012-01-01

Metabolomics was used to explore the mechanism of Rhizoma coptidis in treating type II diabetes mellitus. The rat model of type II diabetes mellitus was constructed by an injection of streptozocin (40 mg/kg), along with diets of fat emulsion. The rats were divided into four groups, the control group, the model group, the Rhizoma coptidis group (10 g/kg) and the metformin group (0.08 g/kg). After the treatment for 30 d, blood samples were collected to test biomedical indexes, and 24 h urine samples were collected for the metabolomics experiment. In the Rhizoma coptidis group, fasting blood glucose (FBG), total cholesterol (TC) and total plasma triglycerides (TG) were significantly decreased by 59.26%, 58.66% and 42.18%, respectively, compared with those in the model group. Based on gas chromatography-mass spectrometry, a urinary metabolomics method was used to study the mechanism of Rhizoma coptidis in treating diabetes mellitus. Based on the principal component analysis, it was found that the model group and control group were separated into two different clusters. The Rhizoma coptidis group was located between the model group and the control group, closer to the control group. Twelve significantly changed metabolites of diabetes mellitus were detected and identified, including 4-methyl phenol, benzoic acid, aminomalonic acid, and so on. After diabetic rats were administered with Rhizoma coptidis, 7 metabolites were significantly changed, and L-ascorbic acid and aminomalonic acid which related with the oxidative stress were significantly regulated to normal. The pharmacological results showed that Rhizoma coptidis could display anti-hyperglycemic and anti-hyperlipidemic effects. The Rhizoma coptidis had antioxidation function in preventing the occurrence of complications with diabetes mellitus to some extent. The work illustrates that the metabolomics method is a useful tool to study the treatment mechanism of traditional Chinese medicine.

Liquid chromatography-mass spectrometry in metabolomics research: mass analyzers in ultra high pressure liquid chromatography coupling.

PubMed

Forcisi, Sara; Moritz, Franco; Kanawati, Basem; Tziotis, Dimitrios; Lehmann, Rainer; Schmitt-Kopplin, Philippe

2013-05-31

The present review gives an introduction into the concept of metabolomics and provides an overview of the analytical tools applied in non-targeted metabolomics with a focus on liquid chromatography (LC). LC is a powerful analytical tool in the study of complex sample matrices. A further development and configuration employing Ultra-High Pressure Liquid Chromatography (UHPLC) is optimized to provide the largest known liquid chromatographic resolution and peak capacity. Reasonably UHPLC plays an important role in separation and consequent metabolite identification of complex molecular mixtures such as bio-fluids. The most sensitive detectors for these purposes are mass spectrometers. Almost any mass analyzer can be optimized to identify and quantify small pre-defined sets of targets; however, the number of analytes in metabolomics is far greater. Optimized protocols for quantification of large sets of targets may be rendered inapplicable. Results on small target set analyses on different sample matrices are easily comparable with each other. In non-targeted metabolomics there is almost no analytical method which is applicable to all different matrices due to limitations pertaining to mass analyzers and chromatographic tools. The specifications of the most important interfaces and mass analyzers are discussed. We additionally provide an exemplary application in order to demonstrate the level of complexity which remains intractable up to date. The potential of coupling a high field Fourier Transform Ion Cyclotron Resonance Mass Spectrometer (ICR-FT/MS), the mass analyzer with the largest known mass resolving power, to UHPLC is given with an example of one human pre-treated plasma sample. This experimental example illustrates one way of overcoming the necessity of faster scanning rates in the coupling with UHPLC. The experiment enabled the extraction of thousands of features (analytical signals). A small subset of this compositional space could be mapped into a mass difference network whose topology shows specificity toward putative metabolite classes and retention time. Copyright © 2013 Elsevier B.V. All rights reserved.

Comprehensive Metabolite Identification Strategy Using Multiple Two-Dimensional NMR Spectra of a Complex Mixture Implemented in the COLMARm Web Server

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bingol, Kerem; Li, Da-Wei; Zhang, Bo

Identification of metabolites in complex mixtures represents a key step in metabolomics. A new strategy is introduced, which is implemented in a new public web server, COLMARm, that permits the co-analysis of up to three 2D NMR spectra, namely 13C-1H HSQC, 1H-1H TOCSY, and 13C-1H HSQC-TOCSY for the comprehensive, accurate, and efficient performance of this task. The highly versatile and interactive nature of COLMARm permits its application to a wide range of metabolomics samples independent of the magnetic field. Database query is performed using the HSQC spectrum and the top metabolite hits are then validated against the TOCSY-type experiment(s) bymore » superimposing the expected cross-peaks on the mixture spectrum. In this way the user can directly accept or reject candidate metabolites by taking advantage of the complementary spectral information offered by these experiments and their different sensitivities. The power of COLMARm is demonstrated for a human serum sample uncovering the existence of 14 metabolites that hitherto were not identified by NMR.« less

Metabolomic Studies of Oral Biofilm, Oral Cancer, and Beyond

PubMed Central

Washio, Jumpei; Takahashi, Nobuhiro

2016-01-01

Oral diseases are known to be closely associated with oral biofilm metabolism, while cancer tissue is reported to possess specific metabolism such as the ‘Warburg effect’. Metabolomics might be a useful method for clarifying the whole metabolic systems that operate in oral biofilm and oral cancer, however, technical limitations have hampered such research. Fortunately, metabolomics techniques have developed rapidly in the past decade, which has helped to solve these difficulties. In vivo metabolomic analyses of the oral biofilm have produced various findings. Some of these findings agreed with the in vitro results obtained in conventional metabolic studies using representative oral bacteria, while others differed markedly from them. Metabolomic analyses of oral cancer tissue not only revealed differences between metabolomic profiles of cancer and normal tissue, but have also suggested a specific metabolic system operates in oral cancer tissue. Saliva contains a variety of metabolites, some of which might be associated with oral or systemic disease; therefore, metabolomics analysis of saliva could be useful for identifying disease-specific biomarkers. Metabolomic analyses of the oral biofilm, oral cancer, and saliva could contribute to the development of accurate diagnostic, techniques, safe and effective treatments, and preventive strategies for oral and systemic diseases. PMID:27271597

Metabolomic Studies of Oral Biofilm, Oral Cancer, and Beyond.

PubMed

Washio, Jumpei; Takahashi, Nobuhiro

2016-06-02

Oral diseases are known to be closely associated with oral biofilm metabolism, while cancer tissue is reported to possess specific metabolism such as the 'Warburg effect'. Metabolomics might be a useful method for clarifying the whole metabolic systems that operate in oral biofilm and oral cancer, however, technical limitations have hampered such research. Fortunately, metabolomics techniques have developed rapidly in the past decade, which has helped to solve these difficulties. In vivo metabolomic analyses of the oral biofilm have produced various findings. Some of these findings agreed with the in vitro results obtained in conventional metabolic studies using representative oral bacteria, while others differed markedly from them. Metabolomic analyses of oral cancer tissue not only revealed differences between metabolomic profiles of cancer and normal tissue, but have also suggested a specific metabolic system operates in oral cancer tissue. Saliva contains a variety of metabolites, some of which might be associated with oral or systemic disease; therefore, metabolomics analysis of saliva could be useful for identifying disease-specific biomarkers. Metabolomic analyses of the oral biofilm, oral cancer, and saliva could contribute to the development of accurate diagnostic, techniques, safe and effective treatments, and preventive strategies for oral and systemic diseases.

Training in metabolomics research. II. Processing and statistical analysis of metabolomics data, metabolite identification, pathway analysis, applications of metabolomics and its future.

PubMed

Barnes, Stephen; Benton, H Paul; Casazza, Krista; Cooper, Sara J; Cui, Xiangqin; Du, Xiuxia; Engler, Jeffrey; Kabarowski, Janusz H; Li, Shuzhao; Pathmasiri, Wimal; Prasain, Jeevan K; Renfrow, Matthew B; Tiwari, Hemant K

2016-08-01

Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. This second part of a comprehensive description of the methods of metabolomics focuses on data analysis, emerging methods in metabolomics and the future of this discipline. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Metabolomics: a state-of-the-art technology for better understanding of male infertility.

PubMed

Minai-Tehrani, A; Jafarzadeh, N; Gilany, K

2016-08-01

Male factor infertility affects approximately half of the infertile couples, in spite of many years of research on male infertility treatment and diagnosis; several outstanding questions remain to be addressed. In this regard, metabolomics as a novel field of omics has been suggested to be applied for male infertility problems. A variety of terms associated with metabolite quantity and quality have been established to demonstrate mixtures of metabolites. Despite metabolomics and metabolite analyses have been around more than decades, a limited number of studies concerning male infertility have been carried out. In this review, we summarised the latest finding in metabolomics techniques and metabolomics biomarkers correlated with male infertility. The rapid progress of a variety of metabolomics platforms, such as nonoptical and optical spectroscopy, could ease separation, recognition, classification and quantification of several metabolites and their metabolic pathways. Here, we recommend that the novel biomarkers determined in the course of metabolomics analysis may stand for potential application of treatment and future clinical practice. © 2015 Blackwell Verlag GmbH.

Present and foreseeable future of metabolomics in forensic analysis.

PubMed

Castillo-Peinado, L S; Luque de Castro, M D

2016-06-21

The revulsive publications during the last years on the precariousness of forensic sciences worldwide have promoted the move of major steps towards improvement of this science. One of the steps (viz. a higher involvement of metabolomics in the new era of forensic analysis) deserves to be discussed under different angles. Thus, the characteristics of metabolomics that make it a useful tool in forensic analysis, the aspects in which this omics is so far implicit, but not mentioned in forensic analyses, and how typical forensic parameters such as the post-mortem interval or fingerprints take benefits from metabolomics are critically discussed in this review. The way in which the metabolomics-forensic binomial succeeds when either conventional or less frequent samples are used is highlighted here. Finally, the pillars that should support future developments involving metabolomics and forensic analysis, and the research required for a fruitful in-depth involvement of metabolomics in forensic analysis are critically discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

Untargeted metabolomics reveals specific withanolides and fatty acyl glycoside as tentative metabolites to differentiate organic and conventional Physalis peruviana fruits.

PubMed

Llano, Sandra M; Muñoz-Jiménez, Ana M; Jiménez-Cartagena, Claudio; Londoño-Londoño, Julián; Medina, Sonia

2018-04-01

The agronomic production systems may affect the levels of food metabolites. Metabolomics approaches have been applied as useful tool for the characterization of fruit metabolome. In this study, metabolomics techniques were used to assess the differences in phytochemical composition between goldenberry samples produced by organic and conventional systems. To verify that the organic samples were free of pesticides, individual pesticides were analyzed. Principal component analysis showed a clear separation of goldenberry samples from two different farming systems. Via targeted metabolomics assays, whereby carotenoids and ascorbic acid were analyzed, not statistical differences between both crops were found. Conversely, untargeted metabolomics allowed us to identify two withanolides and one fatty acyl glycoside as tentative metabolites to differentiate goldenberry fruits, recording organic fruits higher amounts of these compounds than conventional samples. Hence, untargeted metabolomics technology could be suitable to research differences on phytochemicals under different agricultural management practices and to authenticate organic products. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ultrasound: a subexploited tool for sample preparation in metabolomics.

PubMed

Luque de Castro, M D; Delgado-Povedano, M M

2014-01-02

Metabolomics, one of the most recently emerged "omics", has taken advantage of ultrasound (US) to improve sample preparation (SP) steps. The metabolomics-US assisted SP step binomial has experienced a dissimilar development that has depended on the area (vegetal or animal) and the SP step. Thus, vegetal metabolomics and US assisted leaching has received the greater attention (encompassing subdisciplines such as metallomics, xenometabolomics and, mainly, lipidomics), but also liquid-liquid extraction and (bio)chemical reactions in metabolomics have taken advantage of US energy. Also clinical and animal samples have benefited from US assisted SP in metabolomics studies but in a lesser extension. The main effects of US have been shortening of the time required for the given step, and/or increase of its efficiency or availability for automation; nevertheless, attention paid to potential degradation caused by US has been scant or nil. Achievements and weak points of the metabolomics-US assisted SP step binomial are discussed and possible solutions to the present shortcomings are exposed. Copyright © 2013 Elsevier B.V. All rights reserved.

Metabolomics through the lens of precision cardiovascular medicine.

PubMed

Lam, Sin Man; Wang, Yuan; Li, Bowen; Du, Jie; Shui, Guanghou

2017-03-20

Metabolomics, which targets at the extensive characterization and quantitation of global metabolites from both endogenous and exogenous sources, has emerged as a novel technological avenue to advance the field of precision medicine principally driven by genomics-oriented approaches. In particular, metabolomics has revealed the cardinal roles that the environment exerts in driving the progression of major diseases threatening public health. Herein, the existent and potential applications of metabolomics in two key areas of precision cardiovascular medicine will be critically discussed: 1) the use of metabolomics in unveiling novel disease biomarkers and pathological pathways; 2) the contribution of metabolomics in cardiovascular drug development. Major issues concerning the statistical handling of big data generated by metabolomics, as well as its interpretation, will be briefly addressed. Finally, the need for integration of various omics branches and adopting a multi-omics approach to precision medicine will be discussed. Copyright © 2017 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.

A Metabolomic Perspective on Coeliac Disease

PubMed Central

Calabrò, Antonio

2014-01-01

Metabolomics is an “omic” science that is now emerging with the purpose of elaborating a comprehensive analysis of the metabolome, which is the complete set of metabolites (i.e., small molecules intermediates) in an organism, tissue, cell, or biofluid. In the past decade, metabolomics has already proved to be useful for the characterization of several pathological conditions and offers promises as a clinical tool. A metabolomics investigation of coeliac disease (CD) revealed that a metabolic fingerprint for CD can be defined, which accounts for three different but complementary components: malabsorption, energy metabolism, and alterations in gut microflora and/or intestinal permeability. In this review, we will discuss the major advancements in metabolomics of CD, in particular with respect to the role of gut microbiome and energy metabolism. PMID:24665364

Potato stem cuttings to study Verticillium dahliae infection for resistance breeding and ‘omics’ studies

USDA-ARS?s Scientific Manuscript database

The use of consistent and effective methods for early discrimination of resistance to pathogens and selection of appropriate times for tissue sampling are important for experiments focused on global gene expression and metabolomics. Assays for resistance to the vascular pathogen Verticillium dahliae...

Large Scale Proteomic Data and Network-Based Systems Biology Approaches to Explore the Plant World.

PubMed

Di Silvestre, Dario; Bergamaschi, Andrea; Bellini, Edoardo; Mauri, PierLuigi

2018-06-03

The investigation of plant organisms by means of data-derived systems biology approaches based on network modeling is mainly characterized by genomic data, while the potential of proteomics is largely unexplored. This delay is mainly caused by the paucity of plant genomic/proteomic sequences and annotations which are fundamental to perform mass-spectrometry (MS) data interpretation. However, Next Generation Sequencing (NGS) techniques are contributing to filling this gap and an increasing number of studies are focusing on plant proteome profiling and protein-protein interactions (PPIs) identification. Interesting results were obtained by evaluating the topology of PPI networks in the context of organ-associated biological processes as well as plant-pathogen relationships. These examples foreshadow well the benefits that these approaches may provide to plant research. Thus, in addition to providing an overview of the main-omic technologies recently used on plant organisms, we will focus on studies that rely on concepts of module, hub and shortest path, and how they can contribute to the plant discovery processes. In this scenario, we will also consider gene co-expression networks, and some examples of integration with metabolomic data and genome-wide association studies (GWAS) to select candidate genes will be mentioned.

The Recent Developments in Sample Preparation for Mass Spectrometry-Based Metabolomics.

PubMed

Gong, Zhi-Gang; Hu, Jing; Wu, Xi; Xu, Yong-Jiang

2017-07-04

Metabolomics is a critical member in systems biology. Although great progress has been achieved in metabolomics, there are still some problems in sample preparation, data processing and data interpretation. In this review, we intend to explore the roles, challenges and trends in sample preparation for mass spectrometry- (MS-) based metabolomics. The newly emerged sample preparation methods were also critically examined, including laser microdissection, in vivo sampling, dried blood spot, microwave, ultrasound and enzyme-assisted extraction, as well as microextraction techniques. Finally, we provide some conclusions and perspectives for sample preparation in MS-based metabolomics.

Metabolomics as a tool to identify biomarkers to predict and improve outcomes in reproductive medicine: a systematic review.

PubMed

Bracewell-Milnes, Timothy; Saso, Srdjan; Abdalla, Hossam; Nikolau, Dimitrios; Norman-Taylor, Julian; Johnson, Mark; Holmes, Elaine; Thum, Meen-Yau

2017-11-01

Infertility is a complex disorder with significant medical, psychological and financial consequences for patients. With live-birth rates per cycle below 30% and a drive from the Human Fertilisation and Embryology Authority (HFEA) to encourage single embryo transfer, there is significant research in different areas aiming to improve success rates of fertility treatments. One such area is investigating the causes of infertility at a molecular level, and metabolomics techniques provide a platform for studying relevant biofluids in the reproductive tract. The aim of this systematic review is to examine the recent findings for the potential application of metabolomics to female reproduction, specifically to the metabolomics of follicular fluid (FF), embryo culture medium (ECM) and endometrial fluid. To our knowledge no other systematic review has investigated this topic. English peer-reviewed journals on PubMed, Science Direct, SciFinder, were systematically searched for studies investigating metabolomics and the female reproductive tract with no time restriction set for publications. Studies were assessed for quality using the risk of bias assessment and ROBIN-I. There were 21 studies that met the inclusion criteria and were included in the systematic review. Metabolomic studies have been employed for the compositional analysis of various biofluids in the female reproductive tract, including FF, ECM, blastocoele fluid and endometrial fluid. There is some weak evidence that metabolomics technologies studying ECM might be able to predict the viability of individual embryos and implantation rate better than standard embryo morphology, However these data were not supported by randomized the controlled trials (RCTs) which showed no evidence that using metabolomics is able to improve the most important reproductive outcomes, such as clinical pregnancy and live-birth rates. This systematic review provides guidance for future metabolomic studies on biofluids of the female reproductive tract, with a summary of the current findings, promise and pitfalls in metabolomic techniques. The approaches discussed can be adapted by other metabolomic studies. A range of sophisticated modern metabolomic techniques are now more widely available and have been applied to the analysis of the female reproductive tract. However, this review has revealed the paucity of metabolomic studies in the field of fertility and the inconsistencies of findings between different studies, as well as a lack of research examining the metabolic effects of various gynecological diseases. By incorporating metabolomic technology into an increased number of well designed studies, a much greater understanding of infertility at a molecular level could be achieved. However, there is currently no evidence for the use of metabolomics in clinical practice to improve fertility outcomes. © The Author 2017. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com

COnsortium of METabolomics Studies (COMETS)

Cancer.gov

The COnsortium of METabolomics Studies (COMETS) is an extramural-intramural partnership that promotes collaboration among prospective cohort studies that follow participants for a range of outcomes and perform metabolomic profiling of individuals.

Psychosocial Stress and Ovarian Cancer Risk: Metabolomics and Perceived Stress

DTIC Science & Technology

2015-10-01

AWARD NUMBER: W81XWH-13-1-0493 TITLE: Psychosocial Stress and Ovarian Cancer Risk: Metabolomics and Perceived Stress PRINCIPAL INVESTIGATOR...SUBTITLE 5a. CONTRACT NUMBER Psychosocial Stress and Ovarian Cancer Risk: Metabolomics and Perceived Stress 5b. GRANT NUMBER W81XWH-13-1-0493 5c...TERMS ovarian cancer, psychosocial stress, depression, anxiety, social support, metabolomics 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF

Molecular Networking As a Drug Discovery, Drug Metabolism, and Precision Medicine Strategy.

PubMed

Quinn, Robert A; Nothias, Louis-Felix; Vining, Oliver; Meehan, Michael; Esquenazi, Eduardo; Dorrestein, Pieter C

2017-02-01

Molecular networking is a tandem mass spectrometry (MS/MS) data organizational approach that has been recently introduced in the drug discovery, metabolomics, and medical fields. The chemistry of molecules dictates how they will be fragmented by MS/MS in the gas phase and, therefore, two related molecules are likely to display similar fragment ion spectra. Molecular networking organizes the MS/MS data as a relational spectral network thereby mapping the chemistry that was detected in an MS/MS-based metabolomics experiment. Although the wider utility of molecular networking is just beginning to be recognized, in this review we highlight the principles behind molecular networking and its use for the discovery of therapeutic leads, monitoring drug metabolism, clinical diagnostics, and emerging applications in precision medicine. Copyright © 2016. Published by Elsevier Ltd.

Profiling the metabolome changes caused by cranberry procyanidins in plasma of female rats using (1) H NMR and UHPLC-Q-Orbitrap-HRMS global metabolomics approaches.

PubMed

Liu, Haiyan; Garrett, Timothy J; Tayyari, Fariba; Gu, Liwei

2015-11-01

The objective was to investigate the metabolome changes in female rats gavaged with partially purified cranberry procyanidins (PPCP) using (1) H NMR and UHPLC-Q-Orbitrap-HRMS metabolomics approaches, and to identify the contributing metabolites. Twenty-four female Sprague-Dawley rats were randomly separated into two groups and administered PPCP or partially purified apple procyanidins (PPAP) for three times using a 250 mg extracts/kg body weight dose. Plasma was collected 6 h after the last gavage and analyzed using (1) H NMR and UHPLC-Q-Orbitrap-HRMS. No metabolome difference was observed using (1) H NMR metabolomics approach. However, LC-HRMS metabolomics data show that metabolome in the plasma of female rats administered PPCP differed from those gavaged with PPAP. Eleven metabolites were tentatively identified from a total of 36 discriminant metabolic features based on accurate masses and/or product ion spectra. PPCP caused a greater increase of exogenous metabolites including p-hydroxybenzoic acid, phenol, phenol-sulphate, catechol sulphate, 3, 4-dihydroxyphenylvaleric acid, and 4'-O-methyl-(-)-epicatechin-3'-O-beta-glucuronide in rat plasma. Furthermore, the plasma level of O-methyl-(-)-epicatechin-O-glucuronide, 4-hydroxy-5-(hydroxyphenyl)-valeric acid-O-sulphate, 5-(hydroxyphenyl)-ϒ-valerolactone-O-sulphate, 4-hydroxydiphenylamine, and peonidin-3-O-hexose were higher in female rats administered with PPAP. The metabolome changes caused by cranberry procyanidins were revealed using an UHPLC-Q-Orbitrap-HRMS global metabolomics approach. Exogenous and microbial metabolites were the major identified discriminate biomarkers. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Chemotherapy-induced gastrointestinal toxicity is associated with changes in serum and urine metabolome and fecal microbiota in male Sprague-Dawley rats.

PubMed

Forsgård, Richard A; Marrachelli, Vannina G; Korpela, Katri; Frias, Rafael; Collado, Maria Carmen; Korpela, Riitta; Monleon, Daniel; Spillmann, Thomas; Österlund, Pia

2017-08-01

Chemotherapy-induced gastrointestinal toxicity (CIGT) is a complex process that involves multiple pathophysiological mechanisms. We have previously shown that commonly used chemotherapeutics 5-fluorouracil, oxaliplatin, and irinotecan damage the intestinal mucosa and increase intestinal permeability to iohexol. We hypothesized that CIGT is associated with alterations in fecal microbiota and metabolome. Our aim was to characterize these changes and examine how they relate to the severity of CIGT. A total of 48 male Sprague-Dawley rats were injected intraperitoneally either with 5-fluorouracil (150 mg/kg), oxaliplatin (15 mg/kg), or irinotecan (200 mg/kg). Body weight change was measured daily after drug administration and the animals were euthanized after 72 h. Blood, urine, and fecal samples were collected at baseline and at the end of the experiment. The changes in the composition of fecal microbiota were analyzed with 16S rRNA gene sequencing. Metabolic changes in serum and urine metabolome were measured with 1 mm proton nuclear magnetic resonance ( 1 H-NMR). Irinotecan increased the relative abundance of Fusobacteria and Proteobacteria, while 5-FU and oxaliplatin caused only minor changes in the composition of fecal microbiota. All chemotherapeutics increased the levels of serum fatty acids and N(CH 3 ) 3 moieties and decreased the levels of Krebs cycle metabolites and free amino acids. Chemotherapeutic drugs, 5-fluorouracil, oxaliplatin, and irinotecan, induce several microbial and metabolic changes which may play a role in the pathophysiology of CIGT. The observed changes in intestinal permeability, fecal microbiota, and metabolome suggest the activation of inflammatory processes.

Computational analyses of spectral trees from electrospray multi-stage mass spectrometry to aid metabolite identification.

PubMed

Cao, Mingshu; Fraser, Karl; Rasmussen, Susanne

2013-10-31

Mass spectrometry coupled with chromatography has become the major technical platform in metabolomics. Aided by peak detection algorithms, the detected signals are characterized by mass-over-charge ratio (m/z) and retention time. Chemical identities often remain elusive for the majority of the signals. Multi-stage mass spectrometry based on electrospray ionization (ESI) allows collision-induced dissociation (CID) fragmentation of selected precursor ions. These fragment ions can assist in structural inference for metabolites of low molecular weight. Computational investigations of fragmentation spectra have increasingly received attention in metabolomics and various public databases house such data. We have developed an R package "iontree" that can capture, store and analyze MS2 and MS3 mass spectral data from high throughput metabolomics experiments. The package includes functions for ion tree construction, an algorithm (distMS2) for MS2 spectral comparison, and tools for building platform-independent ion tree (MS2/MS3) libraries. We have demonstrated the utilization of the package for the systematic analysis and annotation of fragmentation spectra collected in various metabolomics platforms, including direct infusion mass spectrometry, and liquid chromatography coupled with either low resolution or high resolution mass spectrometry. Assisted by the developed computational tools, we have demonstrated that spectral trees can provide informative evidence complementary to retention time and accurate mass to aid with annotating unknown peaks. These experimental spectral trees once subjected to a quality control process, can be used for querying public MS2 databases or de novo interpretation. The putatively annotated spectral trees can be readily incorporated into reference libraries for routine identification of metabolites.

Retinal metabolic events in preconditioning light stress as revealed by wide-spectrum targeted metabolomics.

PubMed

de la Barca, Juan Manuel Chao; Huang, Nuan-Ting; Jiao, Haihan; Tessier, Lydie; Gadras, Cédric; Simard, Gilles; Natoli, Riccardo; Tcherkez, Guillaume; Reynier, Pascal; Valter, Krisztina

2017-01-01

Light is the primary stimulus for vision, but may also cause damage to the retina. Pre-exposing the retina to sub-lethal amount of light (or preconditioning) improves chances for retinal cells to survive acute damaging light stress. This study aims at exploring the changes in retinal metabolome after mild light stress and identifying mechanisms that may be involved in preconditioning. Retinas from 12 rats exposed to mild light stress (1000 lux × for 12 h) and 12 controls were collected one and seven days after light stress (LS). One retina was used for targeted metabolomics analysis using the Biocrates p180 kit while the fellow retina was used for histological and immunohistochemistry analysis. Immunohistochemistry confirmed that in this experiment, a mild LS with retinal immune response and minimal photoreceptor loss occurred. Compared to controls, LS induced an increased concentration in phosphatidylcholines. The concentration in some amino acids and biogenic amines, particularly those related to the nitric oxide pathway (like asymmetric dimethylarginine (ADMA), arginine and citrulline) also increased 1 day after LS. 7 days after LS, the concentration in two sphingomyelins and phenylethylamine was found to be higher. We further found that in controls, retina metabolome was different between males and females: male retinas had an increased concentration in tyrosine, acetyl-ornithine, phosphatidylcholines and (acyl)-carnitines. Besides retinal sexual metabolic dimorphism, this study shows that preconditioning is mostly associated with re-organisation of lipid metabolism and changes in amino acid composition, likely reflecting the involvement of arginine-dependent NO signalling.

Non-Photochemical Quenching Capacity in Arabidopsis thaliana Affects Herbivore Behaviour

PubMed Central

Johansson Jänkänpää, Hanna; Frenkel, Martin; Zulfugarov, Ismayil; Reichelt, Michael; Krieger-Liszkay, Anja; Mishra, Yogesh; Gershenzon, Jonathan; Moen, Jon; Lee, Choon-Hwan; Jansson, Stefan

2013-01-01

Under natural conditions, plants have to cope with numerous stresses, including light-stress and herbivory. This raises intriguing questions regarding possible trade-offs between stress defences and growth. As part of a program designed to address these questions we have compared herbivory defences and damage in wild type Arabidopsis thaliana and two “photoprotection genotypes”, npq4 and oePsbS, which respectively lack and overexpress PsbS (a protein that plays a key role in qE-type non-photochemical quenching). In dual-choice feeding experiments both a specialist (Plutella xylostella) and a generalist (Spodoptera littoralis) insect herbivore preferred plants that expressed PsbS most strongly. In contrast, although both herbivores survived equally well on each of the genotypes, for oviposition female P. xylostella adults preferred plants that expressed PsbS least strongly. However, there were no significant differences between the genotypes in levels of the 10 most prominent glucosinolates; key substances in the Arabidopsis anti-herbivore chemical defence arsenal. After transfer from a growth chamber to the field we detected significant differences in the genotypes’ metabolomic profiles at all tested time points, using GC-MS, but no consistent “metabolic signature” for the lack of PsbS. These findings suggest that the observed differences in herbivore preferences were due to differences in the primary metabolism of the plants rather than their contents of typical “defence compounds”. A potentially significant factor is that superoxide accumulated most rapidly and to the highest levels under high light conditions in npq4 mutants. This could trigger changes in planta that are sensed by herbivores either directly or indirectly, following its dismutation to H2O2. PMID:23301046

Metabolite profiling of somatic embryos of Cyclamen persicum in comparison to zygotic embryos, endosperm, and testa

PubMed Central

Winkelmann, Traud; Ratjens, Svenja; Bartsch, Melanie; Rode, Christina; Niehaus, Karsten; Bednarz, Hanna

2015-01-01

Somatic embryogenesis has been shown to be an efficient in vitro plant regeneration system for many crops such as the important ornamental plant Cyclamen persicum, for which this regeneration pathway of somatic embryogenesis is of interest for the vegetative propagation of parental lines as well as elite plants. However, somatic embryogenesis is not commercially used in many crops due to several unsolved problems, such as malformations, asynchronous development, deficiencies in maturation and germination of somatic embryos. In contrast, zygotic embryos in seeds develop and germinate without abnormalities in most cases. Instead of time-consuming and labor-intensive experiments involving tests of different in vitro culture conditions and plant growth regulator supplements, we follow a more directed approach. Zygotic embryos served as a reference and were compared to somatic embryos in metabolomic analyses allowing the future optimization of the in vitro system. The aims of this study were to detect differences in the metabolite profiles of torpedo stage somatic and zygotic embryos of C. persicum. Moreover, major metabolites in endosperm and testa were identified and quantified. Two sets of extracts of two to four biological replicates each were analyzed. In total 52 metabolites were identified and quantified in the different tissues. One of the most significant differences between somatic and zygotic embryos was that the proline concentration in the zygotic embryos was about 40 times higher than that found in somatic embryos. Epicatechin, a scavenger for reactive oxygen species, was found in highest abundance in the testa. Sucrose, the most abundant metabolite was detected in significantly higher concentrations in zygotic embryos. Also, a yet unknown trisaccharide, was significantly enriched in zygotic embryos. PMID:26300898

Applications of Fourier Transform Ion Cyclotron Resonance (FT-ICR) and Orbitrap Based High Resolution Mass Spectrometry in Metabolomics and Lipidomics.

PubMed

Ghaste, Manoj; Mistrik, Robert; Shulaev, Vladimir

2016-05-25

Metabolomics, along with other "omics" approaches, is rapidly becoming one of the major approaches aimed at understanding the organization and dynamics of metabolic networks. Mass spectrometry is often a technique of choice for metabolomics studies due to its high sensitivity, reproducibility and wide dynamic range. High resolution mass spectrometry (HRMS) is a widely practiced technique in analytical and bioanalytical sciences. It offers exceptionally high resolution and the highest degree of structural confirmation. Many metabolomics studies have been conducted using HRMS over the past decade. In this review, we will explore the latest developments in Fourier transform mass spectrometry (FTMS) and Orbitrap based metabolomics technology, its advantages and drawbacks for using in metabolomics and lipidomics studies, and development of novel approaches for processing HRMS data.

Applications of Fourier Transform Ion Cyclotron Resonance (FT-ICR) and Orbitrap Based High Resolution Mass Spectrometry in Metabolomics and Lipidomics

PubMed Central

Ghaste, Manoj; Mistrik, Robert; Shulaev, Vladimir

2016-01-01

Metabolomics, along with other “omics” approaches, is rapidly becoming one of the major approaches aimed at understanding the organization and dynamics of metabolic networks. Mass spectrometry is often a technique of choice for metabolomics studies due to its high sensitivity, reproducibility and wide dynamic range. High resolution mass spectrometry (HRMS) is a widely practiced technique in analytical and bioanalytical sciences. It offers exceptionally high resolution and the highest degree of structural confirmation. Many metabolomics studies have been conducted using HRMS over the past decade. In this review, we will explore the latest developments in Fourier transform mass spectrometry (FTMS) and Orbitrap based metabolomics technology, its advantages and drawbacks for using in metabolomics and lipidomics studies, and development of novel approaches for processing HRMS data. PMID:27231903

Metabolomics: available results, current research projects in breast cancer, and future applications.

PubMed

Claudino, Wederson Marcos; Quattrone, Alessandro; Biganzoli, Laura; Pestrin, Marta; Bertini, Ivano; Di Leo, Angelo

2007-07-01

Metabolomics is the newest "omics" science. It is a dynamic portrait of the metabolic status of living systems. Metabolomics has brought new insights on metabolic fluxes and a more comprehensive and holistic understanding of a cell's environment. This burgeoning field promises to be a potential tool to fill the gap between genotype and phenotype. As its preceding "omics" sciences (ie, genomics and proteomics), metabolomics' aim is to dredge information hidden in a sea of data. This technology permits simultaneous monitoring of many hundreds, or thousands, of macro- and small molecules, as well as functional monitoring of multiple pivotal cellular pathways. In addition, elucidation of cellular responses to molecular damage, including evolutionarily conserved inducible molecular defense systems, could be achieved with metabolomics and could lead to the discovery of new biomarkers of molecular responses to functional perturbations. If metabolomic information could be translated into diagnostic tests, it might have the potential to impact on clinical practice, and it might lead to the supplementation of traditional biomarkers of cellular integrity, cell and tissue homeostasis, and morphological alterations that result from cell damage or death. In this review the concept and characteristics of metabolomics are introduced. Main current applications of metabolomics in cancer research are reviewed, including its potential in the drug discovery field, and, last but not least, its potential impact in the field of monitoring response and toxicity to anticancer agents. In the last section, research projects ongoing at our institution and future challenges for metabolomics will be presented and briefly discussed.

Application of the amniotic fluid metabolome to the study of fetal malformations, using Down syndrome as a specific model.

PubMed

Huang, Jun; Mo, Jinhua; Zhao, Guili; Lin, Qiyin; Wei, Guanhui; Deng, Weinan; Chen, Dunjin; Yu, Bolan

2017-11-01

Although monitoring and diagnosis of fetal diseases in utero remains a challenge, metabolomics may provide an additional tool to study the etiology and pathophysiology of fetal diseases at a functional level. In order to explore specific markers of fetal disease, metabolites were analyzed in two separate sets of experiments using amniotic fluid from fetuses with Down syndrome (DS) as a model. Both sets included 10‑15 pairs of controls and cases, and amniotic fluid samples were processed separately; metabolomic fingerprinting was then conducted using UPLC‑MS. Significantly altered metabolites involved in respective metabolic pathways were compared in the two experimental sets. In addition, significantly altered metabolic pathways were further compared with the genomic characters of the DS fetuses. The data suggested that metabolic profiles varied across different experiments, however alterations in the 4 metabolic pathways of the porphyrin metabolism, bile acid metabolism, hormone metabolism and amino acid metabolism, were validated for the two experimental sets. Significant changes in metabolites of coproporphyrin III, glycocholic acid, taurochenodeoxycholate, taurocholate, hydrocortisone, pregnenolone sulfate, L‑histidine, L‑arginine, L‑glutamate and L‑glutamine were further confirmed. Analysis of these metabolic alterations was linked to aberrant gene expression at chromosome 21 of the DS fetus. The decrease in coproporphyrin III in the DS fetus may portend abnormal erythropoiesis, and unbalanced glutamine‑glutamate concentration was observed to be closely associated with abnormal brain development in the DS fetus. Therefore, alterations in amniotic fluid metabolites may provide important clues to understanding the etiology of fetal disease and help to develop diagnostic testing for clinical applications.

Metabolomics and Type 2 Diabetes: Translating Basic Research into Clinical Application.

PubMed

Klein, Matthias S; Shearer, Jane

2016-01-01

Type 2 diabetes (T2D) and its comorbidities have reached epidemic proportions, with more than half a billion cases expected by 2030. Metabolomics is a fairly new approach for studying metabolic changes connected to disease development and progression and for finding predictive biomarkers to enable early interventions, which are most effective against T2D and its comorbidities. In metabolomics, the abundance of a comprehensive set of small biomolecules (metabolites) is measured, thus giving insight into disease-related metabolic alterations. This review shall give an overview of basic metabolomics methods and will highlight current metabolomics research successes in the prediction and diagnosis of T2D. We summarized key metabolites changing in response to T2D. Despite large variations in predictive biomarkers, many studies have replicated elevated plasma levels of branched-chain amino acids and their derivatives, aromatic amino acids and α-hydroxybutyrate ahead of T2D manifestation. In contrast, glycine levels and lysophosphatidylcholine C18:2 are depressed in both predictive studies and with overt disease. The use of metabolomics for predicting T2D comorbidities is gaining momentum, as are our approaches for translating basic metabolomics research into clinical applications. As a result, metabolomics has the potential to enable informed decision-making in the realm of personalized medicine.

Metabolomics and Type 2 Diabetes: Translating Basic Research into Clinical Application

PubMed Central

Klein, Matthias S.; Shearer, Jane

2016-01-01

Type 2 diabetes (T2D) and its comorbidities have reached epidemic proportions, with more than half a billion cases expected by 2030. Metabolomics is a fairly new approach for studying metabolic changes connected to disease development and progression and for finding predictive biomarkers to enable early interventions, which are most effective against T2D and its comorbidities. In metabolomics, the abundance of a comprehensive set of small biomolecules (metabolites) is measured, thus giving insight into disease-related metabolic alterations. This review shall give an overview of basic metabolomics methods and will highlight current metabolomics research successes in the prediction and diagnosis of T2D. We summarized key metabolites changing in response to T2D. Despite large variations in predictive biomarkers, many studies have replicated elevated plasma levels of branched-chain amino acids and their derivatives, aromatic amino acids and α-hydroxybutyrate ahead of T2D manifestation. In contrast, glycine levels and lysophosphatidylcholine C18:2 are depressed in both predictive studies and with overt disease. The use of metabolomics for predicting T2D comorbidities is gaining momentum, as are our approaches for translating basic metabolomics research into clinical applications. As a result, metabolomics has the potential to enable informed decision-making in the realm of personalized medicine. PMID:26636104

New Strategies and Challenges in Lung Proteomics and Metabolomics. An Official American Thoracic Society Workshop Report.

PubMed

Bowler, Russell P; Wendt, Chris H; Fessler, Michael B; Foster, Matthew W; Kelly, Rachel S; Lasky-Su, Jessica; Rogers, Angela J; Stringer, Kathleen A; Winston, Brent W

2017-12-01

This document presents the proceedings from the workshop entitled, "New Strategies and Challenges in Lung Proteomics and Metabolomics" held February 4th-5th, 2016, in Denver, Colorado. It was sponsored by the National Heart Lung Blood Institute, the American Thoracic Society, the Colorado Biological Mass Spectrometry Society, and National Jewish Health. The goal of this workshop was to convene, for the first time, relevant experts in lung proteomics and metabolomics to discuss and overcome specific challenges in these fields that are unique to the lung. The main objectives of this workshop were to identify, review, and/or understand: (1) emerging technologies in metabolomics and proteomics as applied to the study of the lung; (2) the unique composition and challenges of lung-specific biological specimens for metabolomic and proteomic analysis; (3) the diverse informatics approaches and databases unique to metabolomics and proteomics, with special emphasis on the lung; (4) integrative platforms across genetic and genomic databases that can be applied to lung-related metabolomic and proteomic studies; and (5) the clinical applications of proteomics and metabolomics. The major findings and conclusions of this workshop are summarized at the end of the report, and outline the progress and challenges that face these rapidly advancing fields.

Diagnosis of gastroenterological diseases by metabolome analysis using gas chromatography-mass spectrometry.

PubMed

Yoshida, Masaru; Hatano, Naoya; Nishiumi, Shin; Irino, Yasuhiro; Izumi, Yoshihiro; Takenawa, Tadaomi; Azuma, Takeshi

2012-01-01

Recently, metabolome analysis has been increasingly applied to biomarker detection and disease diagnosis in medical studies. Metabolome analysis is a strategy for studying the characteristics and interactions of low molecular weight metabolites under a specific set of conditions and is performed using mass spectrometry and nuclear magnetic resonance spectroscopy. There is a strong possibility that changes in metabolite levels reflect the functional status of a cell because alterations in their levels occur downstream of DNA, RNA, and protein. Therefore, the metabolite profile of a cell is more likely to represent the current status of a cell than DNA, RNA, or protein. Thus, owing to the rapid development of mass spectrometry analytical techniques metabolome analysis is becoming an important experimental method in life sciences including the medical field. Here, we describe metabolome analysis using liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry (GC-MS), capillary electrophoresis-mass spectrometry, and matrix assisted laser desorption ionization-mass spectrometry. Then, the findings of studies about GC-MS-based metabolome analysis of gastroenterological diseases are summarized, and our research results are also introduced. Finally, we discuss the realization of disease diagnosis by metabolome analysis. The development of metabolome analysis using mass spectrometry will aid the discovery of novel biomarkers, hopefully leading to the early detection of various diseases.

Capillary electrophoresis - Mass spectrometry metabolomics analysis revealed enrichment of hypotaurine in rat glioma tissues.

PubMed

Gao, Peng; Ji, Min; Fang, Xueyan; Liu, Yingyang; Yu, Zhigang; Cao, Yunfeng; Sun, Aijun; Zhao, Liang; Zhang, Yong

2017-11-15

Glioma is one of the most lethal brain malignancies with unknown etiologies. Many metabolomics analysis aiming at diverse kinds of samples had been performed. Due to the varied adopted analytical platforms, the reported disease-related metabolites were not consistent across different studies. Comparable metabolomics results are more likely to be acquired by analyzing the same sample types with identical analytical platform. For tumor researches, tissue samples metabolomics analysis own the unique advantage that it can gain more direct insight into disease-specific pathological molecules. In this light, a previous reported capillary electrophoresis - mass spectrometry human tissues metabolomics analysis method was employed to profile the metabolome of rat C6 cell implantation gliomas and the corresponding precancerous tissues. It was found that 9 metabolites increased in the glioma tissues. Of them, hypotaurine was the only metabolite that enriched in the malignant tissues as what had been reported in the relevant human tissues metabolomics analysis. Furthermore, hypotaurine was also proved to inhibit α-ketoglutarate-dependent dioxygenases (2-KDDs) through immunocytochemistry staining and in vitro enzymatic activity assays by using C6 cell cultures. This study reinforced the previous conclusion that hypotaurine acted as a competitive inhibitor of 2-KDDs and proved the value of metabolomics in oncology studies. Copyright © 2017. Published by Elsevier Inc.

Improved classification accuracy in 1- and 2-dimensional NMR metabolomics data using the variance stabilising generalised logarithm transformation

PubMed Central

Parsons, Helen M; Ludwig, Christian; Günther, Ulrich L; Viant, Mark R

2007-01-01

Background Classifying nuclear magnetic resonance (NMR) spectra is a crucial step in many metabolomics experiments. Since several multivariate classification techniques depend upon the variance of the data, it is important to first minimise any contribution from unwanted technical variance arising from sample preparation and analytical measurements, and thereby maximise any contribution from wanted biological variance between different classes. The generalised logarithm (glog) transform was developed to stabilise the variance in DNA microarray datasets, but has rarely been applied to metabolomics data. In particular, it has not been rigorously evaluated against other scaling techniques used in metabolomics, nor tested on all forms of NMR spectra including 1-dimensional (1D) 1H, projections of 2D 1H, 1H J-resolved (pJRES), and intact 2D J-resolved (JRES). Results Here, the effects of the glog transform are compared against two commonly used variance stabilising techniques, autoscaling and Pareto scaling, as well as unscaled data. The four methods are evaluated in terms of the effects on the variance of NMR metabolomics data and on the classification accuracy following multivariate analysis, the latter achieved using principal component analysis followed by linear discriminant analysis. For two of three datasets analysed, classification accuracies were highest following glog transformation: 100% accuracy for discriminating 1D NMR spectra of hypoxic and normoxic invertebrate muscle, and 100% accuracy for discriminating 2D JRES spectra of fish livers sampled from two rivers. For the third dataset, pJRES spectra of urine from two breeds of dog, the glog transform and autoscaling achieved equal highest accuracies. Additionally we extended the glog algorithm to effectively suppress noise, which proved critical for the analysis of 2D JRES spectra. Conclusion We have demonstrated that the glog and extended glog transforms stabilise the technical variance in NMR metabolomics datasets. This significantly improves the discrimination between sample classes and has resulted in higher classification accuracies compared to unscaled, autoscaled or Pareto scaled data. Additionally we have confirmed the broad applicability of the glog approach using three disparate datasets from different biological samples using 1D NMR spectra, 1D projections of 2D JRES spectra, and intact 2D JRES spectra. PMID:17605789

Plenty Is No Plague: Streptomyces Symbiosis with Crops.

PubMed

Rey, Thomas; Dumas, Bernard

2017-01-01

Streptomyces spp. constitute a major clade of the phylum Actinobacteria. These Gram-positive, filamentous prokaryotes are ubiquitous in soils and marine sediments, and are commonly found in the rhizosphere or inside plant roots. Plant-interacting Streptomyces have received limited attention, in contrast to Streptomyces spp. extensively investigated for decades in medicine given their rich potential for secondary metabolite biosynthesis. Recent genomic, metabolomic, and biotechnological advances have produced key insights into Streptomyces spp., paving the way to the use of their metabolites in agriculture. In this Opinion article we propose how Streptomyces spp. could dominate future aspects of crop nutrition and protection. Risks and benefits of the use of these microorganisms in agriculture are also discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Metabolomic Studies in Drosophila.

PubMed

Cox, James E; Thummel, Carl S; Tennessen, Jason M

2017-07-01

Metabolomic analysis provides a powerful new tool for studies of Drosophila physiology. This approach allows investigators to detect thousands of chemical compounds in a single sample, representing the combined contributions of gene expression, enzyme activity, and environmental context. Metabolomics has been used for a wide range of studies in Drosophila , often providing new insights into gene function and metabolic state that could not be obtained using any other approach. In this review, we survey the uses of metabolomic analysis since its entry into the field. We also cover the major methods used for metabolomic studies in Drosophila and highlight new directions for future research. Copyright © 2017 by the Genetics Society of America.

Endocrinology Meets Metabolomics: Achievements, Pitfalls, and Challenges.

PubMed

Tokarz, Janina; Haid, Mark; Cecil, Alexander; Prehn, Cornelia; Artati, Anna; Möller, Gabriele; Adamski, Jerzy

2017-10-01

The metabolome, although very dynamic, is sufficiently stable to provide specific quantitative traits related to health and disease. Metabolomics requires balanced use of state-of-the-art study design, chemical analytics, biostatistics, and bioinformatics to deliver meaningful answers to contemporary questions in human disease research. The technology is now frequently employed for biomarker discovery and for elucidating the mechanisms underlying endocrine-related diseases. Metabolomics has also enriched genome-wide association studies (GWAS) in this area by providing functional data. The contributions of rare genetic variants to metabolome variance and to the human phenotype have been underestimated until now. Copyright © 2017 Elsevier Ltd. All rights reserved.

Plant volatiles induced by herbivore egg deposition affect insects of different trophic levels.

PubMed

Fatouros, Nina E; Lucas-Barbosa, Dani; Weldegergis, Berhane T; Pashalidou, Foteini G; van Loon, Joop J A; Dicke, Marcel; Harvey, Jeffrey A; Gols, Rieta; Huigens, Martinus E

2012-01-01

Plants release volatiles induced by herbivore feeding that may affect the diversity and composition of plant-associated arthropod communities. However, the specificity and role of plant volatiles induced during the early phase of attack, i.e. egg deposition by herbivorous insects, and their consequences on insects of different trophic levels remain poorly explored. In olfactometer and wind tunnel set-ups, we investigated behavioural responses of a specialist cabbage butterfly (Pieris brassicae) and two of its parasitic wasps (Trichogramma brassicae and Cotesia glomerata) to volatiles of a wild crucifer (Brassica nigra) induced by oviposition of the specialist butterfly and an additional generalist moth (Mamestra brassicae). Gravid butterflies were repelled by volatiles from plants induced by cabbage white butterfly eggs, probably as a means of avoiding competition, whereas both parasitic wasp species were attracted. In contrast, volatiles from plants induced by eggs of the generalist moth did neither repel nor attract any of the tested community members. Analysis of the plant's volatile metabolomic profile by gas chromatography-mass spectrometry and the structure of the plant-egg interface by scanning electron microscopy confirmed that the plant responds differently to egg deposition by the two lepidopteran species. Our findings imply that prior to actual feeding damage, egg deposition can induce specific plant responses that significantly influence various members of higher trophic levels.

METABOLOMICS IN SMALL FISH TOXICOLOGY AND OTHER ENVIRONMENTAL APPLICATIONS

EPA Science Inventory

Although lagging behind applications targeted to human endpoints, metabolomics offers great potential in environmental applications, including ecotoxicology. Indeed, the advantages of metabolomics (relative to other 'omic techniques) may be more tangible in ecotoxicology because...

'Omics' techniques for identifying flooding-response mechanisms in soybean.

PubMed

Komatsu, Setsuko; Shirasaka, Naoki; Sakata, Katsumi

2013-11-20

Plant growth and productivity are adversely influenced by various environmental stresses, which often lead to reduced seedling growth and decreased crop yields. Plants respond to stressful conditions through changes in 'omics' profiles, including transcriptomics, proteomics, and metabolomics. Linking plant phenotype to gene expression patterns, protein abundance, and metabolite accumulation is one of the main challenges for improving agricultural production. 'Omics' approaches may shed insight into the mechanisms that function in soybean in response to environmental stresses, particularly flooding by frequent rain, which occurs worldwide due to changes in global climate. Flooding causes significant reductions in the growth and yield of several crops, especially soybean. The application of 'omics' techniques may facilitate the development of flood-tolerant cultivars of soybean. In this review, the use of 'omics' techniques towards understanding the flooding-responsive mechanisms of soybeans is discussed, as the findings from these studies are expected to have applications in both breeding and agronomy. This article is part of a Special Issue entitled: Translational Plant Proteomics. Copyright © 2012 Elsevier B.V. All rights reserved.

Biotic Interactions in the Rhizosphere: A Diverse Cooperative Enterprise for Plant Productivity1[C

PubMed Central

De-la-Peña, Clelia; Loyola-Vargas, Víctor M.

2014-01-01

Microbes and plants have evolved biochemical mechanisms to communicate with each other. The molecules responsible for such communication are secreted during beneficial or harmful interactions. Hundreds of these molecules secreted into the rhizosphere have been identified, and their functions are being studied in order to understand the mechanisms of interaction and communication among the different members of the rhizosphere community. The importance of root and microbe secretion to the underground habitat in improving crop productivity is increasingly recognized, with the discovery and characterization of new secreting compounds found in the rhizosphere. Different omic approaches, such as genomics, transcriptomics, proteomics, and metabolomics, have expanded our understanding of the first signals between microbes and plants. In this review, we highlight the more recent discoveries related to molecules secreted into the rhizosphere and how they affect plant productivity, either negatively or positively. In addition, we include a survey of novel approaches to studying the rhizosphere and emerging opportunities to direct future studies. PMID:25118253