Multi-Omics Approaches Against Abiotic and Biotic Stress-A Review

Plants face an array of environmental stresses, including both abiotic and biotic stresses. These stresses significantly impact plant lifespan and reduce agricultural crop productivity. Abiotic stresses, such as ultraviolet (UV) radiation, high and low temperatures, salinity, drought, floods, heavy metal toxicity, etc., contribute to widespread crop losses globally. On the other hand, biotic stresses, such as those caused by insects, fungi, and weeds, further exacerbate these challenges. These stressors can hinder plant systems at various levels, including molecular, cellular, and development processes. To overcome these challenges, multi-omics computational approaches offer a significant tool for characterizing the plant's biomolecular pool, which is crucial for maintaining homeostasis and signaling response to environmental changes. Integrating multiple layers of omics data, such as proteomics, metabolomics, ionomics, interactomics, and phenomics, simplifies the study of plant resistance mechanisms. This comprehensive approach enables the development of regulatory networks and pathway maps, identifying potential targets for improving resistance through genetic engineering or breeding strategies. This review highlights the valuable insights from integrating multi-omics approaches to unravel plant stress responses to both biotic and abiotic factors. By decoding gene regulation and transcriptional networks, these techniques reveal critical mechanisms underlying stress tolerance. Furthermore, the role of secondary metabolites in bio-based products in enhancing plant stress mitigation is discussed. Genome editing tools offer promising strategies for improving plant resilience, as evidenced by successful case studies combating various stressors. On the whole, this review extensively discusses an advanced multi-omics approach that aids in understanding the molecular basis of resistance and developing novel strategies to improve crops' or organisms' resilience to abiotic and biotic stresses.

Metabolite-driven mechanisms reveal chemical ecology of Lehmann Lovegrass (Eragrostis lehmanniana) invasion in North American semi-arid ecosystems

Invasive plants threaten global ecosystems, yet traditional analyses of functional traits cannot fully explain their dominance over co-occurring natives. Metabolomics offers insights into plant invasions, but single-technique studies often miss critical biochemical mechanisms. We employ a multimodal metabolomics approach (¹H NMR, LC MS/MS, FT-ICR-MS, and MALDI-MSI) to investigate the biochemical basis of Lehmann lovegrass (Eragrostis lehmanniana) invasion in semi-arid North America, comparing it with a co-occurring native grass, Arizona cottontop (Digitaria californica). Our analysis reveals three metabolomic traits of Lehmann lovegrass compared to Arizona cottontop: Enhanced nitrogen allocation in shoots, reduced defensive metabolites in root layers; and increased root exudate modulation under stress conditions. These traits suggest Lehmann lovegrass succeeds through adaptation to increasing aridity rather than direct competition, demonstrating adaptation to nutrient-poor environments and high phenotypic plasticity in response to increasing aridity. This integrated metabolomic approach provides new mechanistic insights into invasion ecology and plant adaptation under environmental change.

Headspace aroma and secondary metabolites profiling in 3 Pelargonium taxa using a multiplex approach of SPME-GC/MS and high resolution-UPLC/MS/MS coupled to chemometrics

BACKGROUND

The present study focuses on the aroma and secondary metabolites profiling of three Pelargonium graveolens cultivars, baladi (GRB), sondos (GRS) and shish (GRSH), grown in Egypt. Utilizing a multiplex approach combining high resolution-ultraperformance liquid chromatography (HR-UPLC)/tandem mass spectrometry (MS/MS) and gas chromatography (GC)-MS coupled with chemometrics, the study aims to identify and profile various secondary metabolites and aroma compounds in these cultivars.

RESULTS

HR-UPLC/MS/MS analysis led to the annotation of 111 secondary metabolites, including phenolics, flavonoids, terpenes and fatty acids, with several compounds being reported for the first time in geranium. Multivariate data analysis identified vinylanisole, dimethoxy-flavonol, and eicosadienoic acid as discriminatory metabolites among the cultivars, particularly distinguishing the GRS cultivar in its phenolics profile. In total, 34 aroma compounds were detected using headspace solid-phase microextraction coupled with GC-MS, including alcohols, esters, ketones, ethers and monoterpene hydrocarbons. The major metabolites contributing to aroma discrimination among the cultivars were β-citronellol in GRB, α-farnesene in GRS and isomenthone in GRSH.

CONCLUSION

The study provides a comprehensive profiling of the secondary metabolites and aroma compounds in the three Pelargonium graveolens cultivars. The GRS cultivar was identified as particularly distinct in both its phenolics and aroma profiles, suggesting its potential as a premium variety for cultivation and use. Future studies should focus on isolating and investigating the newly detected metabolites and exploring the biological effects of these compounds in food applications and other uses. © 2024 Society of Chemical Industry.

Comparative Investigation of the Differences in Chemical Compounds between Raw and Processed Mume Fructus Using Plant Metabolomics Combined with Chemometrics Methods

Mume Fructus is a well-known herbal medicine and food with a long history of processing and application. Different processing methods impact the intrinsic quality of Mume Fructus. Thus, it is of great significance to investigate the changes in chemical components during processing (i.e., raw compared to the pulp and charcoal forms). In this study, plant metabolomics methods based on mass spectrometry detection were established to analyze the chemical ingredients of Mume Fructus comprehensively. Chemometric strategies were combined to analyze the profile differences of Mume Fructus after different processing methods. The established strategy identified 98 volatile and 89 non-volatile compounds of Mume Fructus by gas chromatography-mass spectrometry (GC-MS) and ultra-high performance liquid chromatography coupled with quadrupole time of flight mass spectrometry (UHPLC-Q-TOF-MS/MS), respectively. Moreover, the orthogonal partial least squares discriminant analysis (OPLS-DA) indicated that raw Mume Fructus and the Mume Fructus pulp and charcoal were distributed in three regions. Subsequently, 19 volatile and 16 non-volatile components were selected as potential chemical component markers with variable importance in the projection using (VIP) >1 as the criterion, and the accuracy was verified by a Back Propagation Neural Network (BP-NN). To further understand the difference in the content of Mume Fructus before and after processing, 16 non-volatile chemical component markers were quantitatively determined by ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS/MS). The results revealed that, compared with raw Mume Fructus, the total content of 16 components in the pulp of Mume Fructus increased while it decreased in the charcoal. Therefore, this study used GC-MS, UHPLC-Q-TOF-MS/MS and UHPLC-MS/MS modern technology to analyze the differences in chemical components before and after the processing of Mume Fructus and provided a material basis for further research on the quality evaluation and efficacy of Mume Fructus.

Plant metabolomics: a new strategy and tool for quality evaluation of Chinese medicinal materials

The present quality control method of Chinese medicinal materials (CMM) has obvious deficiency, which cannot be compatible with the multi-target and multi-component characteristics and production process of CMM. Plant metabolomics with a huge impetus to comprehensively characterize the metabolites and clarify the complexity and integrity of CMM, has been widely used in the research of CMM. This article comprehensively reviewed the application of plant metabolomics in the quality control of CMM. It introduced the concept, technique, and application examples, discussed the prospects, limitations, improvements of plant metabolomics. MS and NMR, as important techniques for plant metabolomics, are mainly highlighted in the case references. The purpose of this article is to clarify the advantage of plants metabolomics for promoting the optimization of the CMM quality control system and proposing a system approach to realize the overall quality control of CMM based on plant metabolomics combined with multidisciplinary method.

A review of the traditional use of southern African medicinal plants for the treatment of inflammation and inflammatory pain

ETHNOPHARMACOLOGICAL RELEVANCE

Inflammation is a serious global concern due to its debilitating symptoms, resulting in considerable suffering and lost productivity. Chronic and auto-immune inflammatory diseases are of particular concern. Several pharmaceutical therapies are already available. However, the use of non-steroidal anti-inflammatory drugs (NSAID's) is accompanied by harmful and toxic side effects. Hence, the search for safer alternative therapeutics with limited side effects is imperative. The use of medicinal plants is common practice amongst the southern African population and may provide targets for drug development.

AIM OF THE STUDY

This study aims to review and document the medicinal uses and pharmacological properties of southern African medicinal plants used for inflammation and pain-related ailments.

MATERIAL AND METHODS

An extensive literature review was undertaken to identify southern African plants used traditionally to treat inflammation. A variety of ethnobotanical books and grey literature, as well as ScienceDirect, Google Scholar and Scopus search engines were used as sources of information.

RESULTS

This review identified 555 medicinal plants from 118 families which were traditionally used in southern Africa to treat inflammation and pain. Fabaceae was the most prominent family with 63 species, followed by Asteraceae (54 species) and Apocynaceae (33 species). The top category of ailments indicated include non-specific inflammation with 150 species, followed by inflammatory pain (148 species), headache (114 species) and toothache (114 species).

CONCLUSION

Despite a large number of southern African medicinal plants used to treat inflammation and pain, relatively few have been screened for their anti-inflammatory properties. Furthermore, biologically active plant extracts have been tested against relatively few inflammatory markers and considerable further work is required.

A simple strategy to monitor the temporal and spatial distribution of alkaloids in sacred lotus leaves

Owing to the high degree of diversity of metabolite pools and complexity of spatial and temporal distributions within biological tissues, currently available methods for metabolite characterization face large challenges. In this study, the temporal and spatial distributions of the alkaloid components of the medicinal plant lotus (Nelumbo nucifera) were investigated over various growth phases. The results showed that alkaloid biosynthesis in lotus leaf is regulated by development and that there is maximum accumulation of alkaloids when the lotus leaf was completely expanded. Furthermore, alkaloid content tended to be stable in mature lotus leaves. However, there was significant variation in the alkaloid content of lotus leaves with different genotypes, suggesting that genetic background is an important factor that affects the temporal and spatial distributions of alkaloids in sacred lotus leaves. The dynamic contents of alkaloids during the growth and development of lotus leaves provide insight into basic biological differences when sampling.

In Planta Nanosensors: Understanding Biocorona Formation for Functional Design

Climate change and population growth are straining agricultural output. To counter these changes and meet the growing demand for food and energy, the monitoring and engineering of crops are becoming increasingly necessary. Nanoparticle-based sensors have emerged in recent years as new tools to advance agricultural practices. As these nanoparticle-based sensors enter and travel through the complex biofluids within plants, biomolecules including proteins, metabolites, lipids, and carbohydrates adsorb onto the nanoparticle surfaces, forming a coating known as the "bio-corona". Understanding these nanoparticle-biomolecule interactions that govern nanosensor function in plants will be essential to successfully develop and translate nanoparticle-based sensors into broader agricultural practice.

A comprehensive review on carotenoids in foods and feeds: status quo, applications, patents, and research needs

Carotenoids are isoprenoids widely distributed in foods that have been always part of the diet of humans. Unlike the other so-called food bioactives, some carotenoids can be converted into retinoids exhibiting vitamin A activity, which is essential for humans. Furthermore, they are much more versatile as they are relevant in foods not only as sources of vitamin A, but also as natural pigments, antioxidants, and health-promoting compounds. Lately, they are also attracting interest in the context of nutricosmetics, as they have been shown to provide cosmetic benefits when ingested in appropriate amounts. In this work, resulting from the collaborative work of participants of the COST Action European network to advance carotenoid research and applications in agro-food and health (EUROCAROTEN, www.eurocaroten.eu, https://www.cost.eu/actions/CA15136/#tabs|Name:overview) research on carotenoids in foods and feeds is thoroughly reviewed covering aspects such as analysis, carotenoid food sources, carotenoid databases, effect of processing and storage conditions, new trends in carotenoid extraction, daily intakes, use as human, and feed additives are addressed. Furthermore, classical and recent patents regarding the obtaining and formulation of carotenoids for several purposes are pinpointed and briefly discussed. Lastly, emerging research lines as well as research needs are highlighted.

Analysis of the effect of cadmium stress on root exudates of Sedum plumbizincicola based on metabolomics

Root exudates are the most direct manifestation of the response of plants changes in the external environment. Therefore, based on non-targeted gas chromatography-time-of-flight mass spectrometry and metabolomics, the response of Sedum plumbizincicola root exudates to Cd stress was used to reveal the possible mechanism of resistance to or accumulation of Cd. The results showed that Cd significantly changed the composition and contents of S. plumbizincicola root exudates. A total of 155 metabolites were identified in S. plumbizincicola root exudates, among which 33 showed significant differences under Cd stress, including organic acids, amino acids, lipids, and polyols. Cd stress suppressed organic acid metabolism and lipid metabolism in S. plumbizincicola and significantly affected amino acid metabolism. There were 16 metabolic pathways related to Cd stress, among which arginine and proline metabolism, valine, leucine, and isoleucine biosynthesis, glycine, serine, and threonine metabolism, glutathione metabolism, and purine metabolism were the key pathways with the highest correlation, and were closely related to the stress resistance of S. plumbizincicola.

Flavonoids and caffeoylquinic acids in Chrysanthemum morifolium Ramat flowers: A potentially rich source of bioactive compounds

Varieties of chrysanthemums are among the world's most valuable edible ornamental crops. However, the availability and relationship between the bio-chemicals of chrysanthemums and their morphological variations remain unclear. We developed liquid chromatography mass spectrometry to construct a spectral tag library to identify and quantify chemicals of 7 caffeoylquinic acids, 21 flavones and flavonols, 4 carotenoids, and 13 other compounds in 27 cultivars and representative tea of Chrysanthemum morifolium. A correlation analysis found that more acacetin 7-O-galactoside (23) resulted in lighter colored flowers and less acacetin (43) and kaempferol (44) was associated with yellow flowers. Hot-H₂O extraction of C. morifolium tea showed that most flavonoids and caffeoylquinic acids dissolved out at 30 min, with 20.977 and 8.958 mg/g GW indicated that C. morifolium, which is used in food and tea, is rich in flavonoids and carotenoids. The results improve our understanding of flavonoid biosynthesis and the mechanisms responsible for flower color.

Metabolomics Reveals Distinct Metabolites between Lonicera japonica and Lonicera macranthoides Based on GC-MS

Lonicera japonica Thunb. (LJ) and Lonicera macranthoides Hand. -Mazz. (LM) have been widely used in Chinese medicine for thousands of years. Although the morphological characteristics of LJ and LM are quite similar, there are significant distinctions of medicinal ingredients (mainly the secondary metabolites) and clinical indications between them. However, the in-depth differences of primary metabolites have not thoroughly been studied yet. Therefore, gas chromatography-mass spectrometry- (GC-MS-) based metabolomics method combined with chemometric methods were performed to analyze the distinction in this study. The results showed that LJ and LM were obviously classified into two groups. 10 metabolites were obtained as biomarkers on account of their p values, pcorr values, and differing variable importance in projection (VIP) values. Metabolic pathway analysis showed that the galactose metabolism and starch and sucrose metabolism gathered as potential pathways caused these extraordinary differences of primary metabolites between LJ and LM. Further, we found that the differences of main medicinal ingredients between LJ and LM could be interpreted from these metabolites according to the analysis of mainly related pathways. The metabolites involved in the starch and sucrose metabolism presented upregulated in LJ, while almost all metabolites in the galactose metabolism, the TCA cycle, and the phenolic acid part of phenylpropanoid metabolism were downregulated in LJ. Therefore, the energy stored in the starch and sucrose metabolism may be saved to produce flavonoid, which could be the reason that the level of flavonoid of phenylpropanoid metabolism is higher in LJ compared to LM. Consequently, this study presented an effective tool for quality evaluation of LJ and LM and laid a foundation for further studies of the metabolic mechanisms and high-quality manufacturing of them.

Metabolomic Determination of Specialized Metabolites Using Liquid Chromatography-Tandem Mass Spectrometry in the Traditional Chinese Medicines Astragali Radix and Hedysari Radix

The Traditional Chinese Medicines (TCMs) Astragali Radix (AR) derived from Astragalus membranaceus (Fisch.) Bge. var. mongholicus (Bge.) Hsiao and A. membranaceus (Fisch.) Bge., and Hedysari Radix (HR) derived from Hedysarum polybotrys Hand.-Mazz. (family Leguminosae) are well-known for increasing the tonic effects on “Qi.” A better insight into the specialized (secondary) metabolites is essential to understand the effects of TCM; however, such metabolites remain largely unknown. Here, we performed a metabolomics-based analysis using liquid chromatography-tandem mass spectrometry in 3 plant tissues—periderm, phloem, and xylem—to identify potential bioactive metabolites. Multivariate statistical analysis revealed 29 metabolites showing a significant difference between groups and 10 biomarker candidates of AR and HR. An anti-inflammatory assay showed that the xylem of both AR and HR and the phloem of HR showed higher anti-inflammatory activity than the positive control quercetin in terms of nitric oxide inhibition.

Metabolomics analysis of Camellia sinensis with respect to harvesting time

The metabolites of green tea influence its quality and physiological characteristics. Therefore, to further increase the utilization of green tea leaves, it is imperative to understand the distribution and variation of their secondary metabolites with respect to different harvesting times. This study compared the metabolomes of young leaves of 'Anji Baicha' between early spring tea and late spring tea in positive and negative ESI modes using UPLC-ESI-Q-TOF/MS. Potential biomarkers were selected by principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) of chemometrics methods. Results showed that the metabolic profiles of young leaves in early and late spring tea were significantly different. The metabolite-related pathways associated with these differences included those involved in biosynthesis of flavonoids, phenylpropanoids, flavone and flavonol, phenylalanine, tyrosine, and tryptophan. In early spring tea leaves, concentrations of amino acids (l-glutamine and l-tryptophan), (S)-(-)-limonene, most of the catechins, and flavonol/flavone glycosides were found to be significantly increased, while proanthocyanidins (proanthocyanidin A1, prodelphinidin A1, and prodelphinidin A₂ 3'-gallate) concentrations were significantly decreased. As a result of the metabolomics analysis of young leaves of green tea plants with respect to different harvesting time, information regarding physiological characteristics and optimal harvesting time was obtained.

Botanical metabolite ions extraction from full electrospray ionization mass spectrometry using high-dimensional penalized regression

INTRODUCTION

Mass spectrometric data analysis of complex biological mixtures can be a challenge due to its vast datasets. There is lack of data treatment pipelines to analyze chemical signals versus noise. These tasks, so far, have been up to the discretion of the analysts.

OBJECTIVES

The aim of this work is to demonstrate an analytical workflow that would enhance the confidence in metabolomics before answering biological questions by serial dilution of botanical complex mixture and high-dimensional data analysis. Furthermore, we would like to provide an alternative approach to a univariate p-value cutoff from t-test for blank subtraction procedure between negative control and biological samples.

METHODS

A serial dilution of complex mixture analysis under electrospray ionization was proposed to study firsthand chemical complexity of metabolomics. Advanced statistical models using high-dimensional penalized regression were employed to study both the concentration and ion intensity relationship and the ion-ion relationship per second of retention time sub dataset. The multivariate analysis was carried out with a tool built in-house, so called metabolite ions extraction and visualization, which was implemented in R environment.

RESULTS

A test case of the medicinal plant goldenseal (Hydrastis canandensis L.), showed an increase in metabolome coverage of features deemed as "important" by a multivariate analysis compared to features deemed as "significant" by a univariate t-test. For an illustration, the data analysis workflow suggested an unexpected putative compound, 20-hydroxyecdysone. This suggestion was confirmed with MS/MS acquisition and literature search.

CONCLUSION

The multivariate analytical workflow selects "true" metabolite ions signals and provides an alternative approach to a univariate p-value cutoff from t-test, thus enhancing the data analysis process of metabolomics.

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

BACKGROUND

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'.

OBJECTIVE

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.

MATERIALS AND METHODS

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).

RESULTS

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.

CONCLUSION

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.

Genetic analysis of stilbenoid profiles in grapevine stems reveals a major mQTL hotspot on chromosome 18 associated with disease-resistance motifs

Grapevine (Vitis spp.) contains a wealth of phytochemicals that have received considerable attention due to health-promoting properties and biological activities as phytoalexins. To date, the genetic basis of the quantitative variations for these potentially beneficial compounds has been limited. Here, metabolic quantitative trait locus (mQTL) mapping was conducted using grapevine stems of a segregating F₂ population. Metabolic profiling of grapevine stems was performed using liquid chromatography-high-resolution mass spectrometry (LC-HRMS), resulting in the detection of 1317 ions/features. In total, 19 of these features matched with literature-reported stilbenoid masses and were genetically mapped using a 1449-SNP linkage map and R/qtl software, resulting in the identification of four mQTLs. Two large-effect mQTLs that corresponded to a stilbenoid dimer and a trimer were mapped on chromosome 18, accounting for phenotypic variances of 29.0% and 38.4%. Functional annotations of these large-effect mQTLs on the VitisNet network database revealed a major hotspot of disease-resistance motifs on chromosome 18. This 2.8-Mbp region contains 48 genes with R-gene motifs, including variants of TIR, NBS, and LRR, that might potentially confer resistance to powdery mildew, downy mildew, or other pathogens. The locus also encompasses genes associated with flavonoid and biosynthetic pathways that are likely involved in the production of secondary metabolites, including phytoalexins. In addition, haplotype dosage effects of the five mQTLs further characterized the genomic regions for differential production of stilbenoids that can be applied in resistance breeding through manipulation of stilbenoid production in planta.

Stacked Injections of Biphasic Extractions for Improved Metabolomic Coverage and Sample Throughput

Omics technologies attempt to provide comprehensive coverage of their target analytes. Comprehensive coverage of metabolites, the aim of nontargeted metabolomics applications, is hindered by the extreme diversity in physiochemical properties of the metabolome. One approach to deal with this challenge is the use of biphasic extractions. These methods generate two largely complementary extracts from a single sample, with an organic lipid-rich fraction and an aqueous fraction containing largely primary and secondary metabolites. To improve metabolite coverage, these two fractions are then independently analyzed resulting in a doubling of the experimental time. In this manuscript, we describe a novel injection approach, stacked injections of a biphasic extraction (SIBE), which enables simultaneous analysis of the two fractions. We demonstrate that SIBE offers nearly 3-fold more total peak area than a monophasic extract without dramatically increasing instrumentation time required for the analysis. The analytical variance is very slightly increased; however, significant improvements in retention time stability are obtained with SIBE vs monophasic injections. Collectively, these data indicate that SIBE is a viable injection approach whenever comprehensive metabolomic coverage is desired.

Standard Key Steps in Mass Spectrometry-Based Plant Metabolomics Experiments: Instrument Performance and Analytical Method Validation

Studies of the plant metabolome include the analysis of a wide range of chemical species with very diverse physicochemical properties requiring powerful analytical tools for the separation, characterization, and quantification of this vast compound diversity present in plant matrices. In quantitative metabolomics studies, major efforts are put into optimizing sample extraction and separation as well as instrument conditions to measure specific plant metabolites. Here, challenges in the use of mass spectrometry (MS) as a quantitative tool in plant metabolomics experiments are discussed, and an overview of the most critical steps in the development and validation of MS-based analytical methods is presented.

Uptake and transformations of engineered nanomaterials: Critical responses observed in terrestrial plants and the model plant Arabidopsis thaliana

With the applications of engineered nanomaterials (ENMs) continually expanding and production quickly growing, residues of ENMs will end up in the environment at levels that may be harmful to non-target organisms. Many of the tunable properties that have made them desirable, such as type, size, charge, or coating, also contribute to the current difficulties in understanding the fate of ENMs in the environment. This review article focuses on studies that investigate plant-ENM interactions, including techniques used to study these interactions and documented plant responses due to the phytotoxic effects of ENMs. The many variables which can be altered for an experiment, such as type, size, and concentration of ENMs, make it difficult to formulate generalizations about the uptake mechanism involved, or to make an inference on the subcellular localization and distribution of the internalized ENMs in plant tissue. In order to avoid these challenges, studies can utilize a model organism such as Arabidopsis thaliana, and a combination of analytical techniques that can reveal complementary information in order to assess how the different experimental conditions influence the uptake and phytotoxicity of ENMs. This review presents recent studies regarding plant-ENM interactions employing Arabidopsis to demonstrate how the use of this model plant can advance our understanding of plant-ENM interactions and guide additional studies using other plant species. Overarching results suggest that more sensitive tests and consistency in experimental designs are needed to fully assess and understand the phytotoxic effects of ENMs in the environment.

Methanol Generates Numerous Artifacts during Sample Extraction and Storage of Extracts in Metabolomics Research

Many metabolomics studies use mixtures of (acidified) methanol and water for sample extraction. In the present study, we investigated if the extraction with methanol can result in artifacts. To this end, wheat leaves were extracted with mixtures of native and deuterium-labeled methanol and water, with or without 0.1% formic acid. Subsequently, the extracts were analyzed immediately or after storage at 10 °C, −20 °C or −80 °C with an HPLC-HESI-QExactive HF-Orbitrap instrument. Our results showed that 88 (8%) of the >1100 detected compounds were derived from the reaction with methanol and either formed during sample extraction or short-term storage. Artifacts were found for various substance classes such as flavonoids, carotenoids, tetrapyrrols, fatty acids and other carboxylic acids that are typically investigated in metabolomics studies. 58 of 88 artifacts were common between the two tested extraction variants. Remarkably, 34 of 73 (acidified extraction solvent) and 33 of 73 (non-acidified extraction solvent) artifacts were formed de novo as none of these meth(ox)ylated metabolites were found after extraction of native leaf samples with CD₃OH/H₂O. Moreover, sample extracts stored at 10 °C for several days, as can typically be the case during longer measurement sequences, led to an increase in both the number and abundance of methylated artifacts. In contrast, frozen sample extracts were relatively stable during a storage period of one week. Our study shows that caution has to be exercised if methanol is used as the extraction solvent as the detected metabolites might be artifacts rather than natural constituents of the biological system. In addition, we recommend storing sample extracts in deep freezers immediately after extraction until measurement.

MetExtract II: A Software Suite for Stable Isotope-Assisted Untargeted Metabolomics

Stable isotope labeling (SIL) techniques have the potential to enhance different aspects of liquid chromatography–high-resolution mass spectrometry (LC-HRMS)-based untargeted metabolomics methods including metabolite detection, annotation of unknown metabolites, and comparative quantification. In this work, we present MetExtract II, a software toolbox for detection of biologically derived compounds. It exploits SIL-specific isotope patterns and elution profiles in LC-HRMS(/MS) data. The toolbox consists of three complementary modules: M1 (AllExtract) uses mixtures of uniformly highly isotope-enriched and native biological samples for selective detection of the entire accessible metabolome. M2 (TracExtract) is particularly suited to probe the metabolism of endogenous or exogenous secondary metabolites and facilitates the untargeted screening of tracer derivatives from concurrently metabolized native and uniformly labeled tracer substances. With M3 (FragExtract), tandem mass spectrometry (MS/MS) fragments of corresponding native and uniformly labeled ions are evaluated and automatically assigned with putative sum formulas. Generated results can be graphically illustrated and exported as a comprehensive data matrix that contains all detected pairs of native and labeled metabolite ions that can be used for database queries, metabolome-wide internal standardization, and statistical analysis. The software, associated documentation, and sample data sets are freely available for noncommercial use at http://metabolomics-ifa.boku.ac.at/metextractII.

High-resolution MALDI mass spectrometry imaging of gallotannins and monoterpene glucosides in the root of Paeonia lactiflora

High-resolution atmospheric-pressure scanning microprobe matrix-assisted laser desorption/ionization mass spectrometry imaging (AP-SMALDI MSI) at 10 μm pixel size was performed to unravel the spatio-chemical distribution of major secondary metabolites in the root of Paeonia lactiflora. The spatial distributions of two major classes of bioactive components, gallotannins and monoterpene glucosides, were investigated and visualized at the cellular level in tissue sections of P. lactiflora roots. Accordingly, other primary and secondary metabolites were imaged, including amino acids, carbohydrates, lipids and monoterpenes, indicating the capability of untargeted localization of metabolites by using high-resolution MSI platform. The employed AP-SMALDI MSI system provides significant technological advancement in the visualization of individual molecular species at the cellular level. In contrast to previous histochemical studies of tannins using unspecific staining reagents, individual gallotannin species were accurately localized and unequivocally discriminated from other phenolic components in the root tissues. High-quality ion images were obtained, providing significant clues for understanding the biosynthetic pathway of gallotannins and monoterpene glucosides and possibly helping to decipher the role of tannins in xylem cells differentiation and in the defence mechanisms of plants, as well as to investigate the interrelationship between tannins and lignins.

Recent advances in stable isotope-enabled mass spectrometry-based plant metabolomics

Methods employing isotope labeled compounds have been an important part of the bioanalytical canon for many decades. The past fifteen years have seen the development of many new approaches using stable (non-radioactive) isotopes as labels for high-throughput bioanalytical, 'omics-scale' measurements of metabolites (metabolomics) and proteins (proteomics). This review examines stable isotopic labeling approaches that have been developed for labeling whole intact plants, plant tissues, or crude extracts of plant materials with stable isotopes (mainly using ²H, ¹³C, ¹⁵N, ¹⁸O or ³⁴S). The application of metabolome-scale labeling for improving metabolite annotation, metabolic pathway elucidation, and relative quantification in mass spectrometry-based metabolomics of plants is also reviewed.

Omic Relief for the Biotically Stressed: Metabolomics of Plant Biotic Interactions

Many aspects of the way plants protect themselves against pathogen attack, or react upon such an attack, are realized by metabolites. The ambitious aim of metabolomics, namely the identification and annotation of the entire cellular metabolome, still poses a considerable challenge due to the high diversity of the metabolites in the cell. Recent advances in analytical methods and data analysis have resulted in improved sensitivity, accuracy, and capacity, allowing the analysis of several hundreds or even thousands of compounds within one sample. Investigators have only recently begun to acknowledge and harness the power of metabolomics to elucidate key questions in the study of plant biotic interactions; we review trends and developments in the field.

Measuring relative utilization of aerobic glycolysis in breast cancer cells by positional isotopic discrimination

The ability of cancer cells to produce lactate through aerobic glycolysis is a hallmark of cancer. In this study, we established a positional isotopic labeling and LC-MS-based method that can specifically measure the conversion of glucose to lactate in glycolysis. We show that the rate of aerobic glycolysis is closely correlated with glucose uptake and lactate production in breast cancer cells. We also found that the production of [3-(13) C]lactate is significantly elevated in metastatic breast cancer cells and in early stage metastatic mammary tumors in mice. Our findings may enable the development of a biomarker for the diagnosis of aggressive breast cancer.

Plant Metabolomics: An Indispensable System Biology Tool for Plant Science

As genomes of many plant species have been sequenced, demand for functional genomics has dramatically accelerated the improvement of other omics including metabolomics. Despite a large amount of metabolites still remaining to be identified, metabolomics has contributed significantly not only to the understanding of plant physiology and biology from the view of small chemical molecules that reflect the end point of biological activities, but also in past decades to the attempts to improve plant behavior under both normal and stressed conditions. Hereby, we summarize the current knowledge on the genetic and biochemical mechanisms underlying plant growth, development, and stress responses, focusing further on the contributions of metabolomics to practical applications in crop quality improvement and food safety assessment, as well as plant metabolic engineering. We also highlight the current challenges and future perspectives in this inspiring area, with the aim to stimulate further studies leading to better crop improvement of yield and quality.

Metabolomic application in toxicity evaluation and toxicological biomarker identification of natural product

Natural product plays a vital role in disease prevention and treatment since the appearance of civilization, but the toxicity severely hinders its wide use. In order to avoid toxic effect as far as possible and use natural product safely, more comprehensive understandings of toxicity are urgently required. Since the metabolome represents the physiological or pathological status of organisms, metabolomics-based toxicology is of significance to observe potential injury before toxins have caused physiological or pathological damages. Metabolomics-based toxicology can evaluate toxicity and identify toxicological biomarker of natural product, which is helpful to guide clinical medication and reduce adverse drug reactions. In the past decades, dozens of metabolomic researches have been implemented on toxicity evaluation, toxicological biomarker identification and potential mechanism exploration of nephrotoxicity, hepatotoxicity, cardiotoxicity and central nervous system toxicity induced by pure compounds, extracts and compound prescriptions. In this paper, metabolomic technology, sample preparation, data process and analysis, and metabolomics-based toxicological research of natural product are reviewed, and finally, the potential problems and further perspectives in toxicological metabolomic investigations of natural product are discussed.

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

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.

Mass spectrometry imaging for plant biology: a review

Mass spectrometry imaging (MSI) is a developing technique to measure the spatio-temporal distribution of many biomolecules in tissues. Over the preceding decade, MSI has been adopted by plant biologists and applied in a broad range of areas, including primary metabolism, natural products, plant defense, plant responses to abiotic and biotic stress, plant lipids and the developing field of spatial metabolomics. This review covers recent advances in plant-based MSI, general aspects of instrumentation, analytical approaches, sample preparation and the current trends in respective plant research.

Metabolomics in chemical ecology

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.

Patterns of metabolite changes identified from large-scale gene perturbations in Arabidopsis using a genome-scale metabolic network

Metabolomics enables quantitative evaluation of metabolic changes caused by genetic or environmental perturbations. However, little is known about how perturbing a single gene changes the metabolic system as a whole and which network and functional properties are involved in this response. To answer this question, we investigated the metabolite profiles from 136 mutants with single gene perturbations of functionally diverse Arabidopsis (Arabidopsis thaliana) genes. Fewer than 10 metabolites were changed significantly relative to the wild type in most of the mutants, indicating that the metabolic network was robust to perturbations of single metabolic genes. These changed metabolites were closer to each other in a genome-scale metabolic network than expected by chance, supporting the notion that the genetic perturbations changed the network more locally than globally. Surprisingly, the changed metabolites were close to the perturbed reactions in only 30% of the mutants of the well-characterized genes. To determine the factors that contributed to the distance between the observed metabolic changes and the perturbation site in the network, we examined nine network and functional properties of the perturbed genes. Only the isozyme number affected the distance between the perturbed reactions and changed metabolites. This study revealed patterns of metabolic changes from large-scale gene perturbations and relationships between characteristics of the perturbed genes and metabolic changes.

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

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.

K-targeted metabolomic analysis extends chemical subtraction to DESIGNER extracts: selective depletion of extracts of hops (Humulus lupulus)

This study introduces a flexible and compound targeted approach to Deplete and Enrich Select Ingredients to Generate Normalized Extract Resources, generating DESIGNER extracts, by means of chemical subtraction or augmentation of metabolites. Targeting metabolites based on their liquid-liquid partition coefficients (K values), K targeting uses countercurrent separation methodology to remove single or multiple compounds from a chemically complex mixture, according to the following equation: DESIGNER extract = total extract ± target compound(s). Expanding the scope of the recently reported depletion of extracts by immunoaffinity or solid phase liquid chromatography, the present approach allows a more flexible, single- or multi-targeted removal of constituents from complex extracts such as botanicals. Chemical subtraction enables both chemical and biological characterization, including detection of synergism/antagonism by both the subtracted targets and the remaining metabolite mixture, as well as definition of the residual complexity of all fractions. The feasibility of the DESIGNER concept is shown by K-targeted subtraction of four bioactive prenylated phenols, isoxanthohumol (1), 8-prenylnaringenin (2), 6-prenylnaringenin (3), and xanthohumol (4), from a standardized hops (Humulus lupulus L.) extract using specific solvent systems. Conversely, adding K-targeted isolates allows enrichment of the original extract and hence provides an augmented DESIGNER material. Multiple countercurrent separation steps were used to purify each of the four compounds, and four DESIGNER extracts with varying depletions were prepared. The DESIGNER approach innovates the characterization of chemically complex extracts through integration of enabling technologies such as countercurrent separation, K-by-bioactivity, the residual complexity concepts, as well as quantitative analysis by (1)H NMR, LC-MS, and HiFSA-based NMR fingerprinting.

Measuring the chemical and cytotoxic variability of commercially available kava (Piper methysticum G. Forster)

Formerly used world-wide as a popular botanical medicine to reduce anxiety, reports of hepatotoxicity linked to consuming kava extracts in the late 1990s have resulted in global restrictions on kava use and have hindered kava-related research. Despite its presence on the United States Food and Drug Administration consumer advisory list for the past decade, export data from kava producing countries implies that US kava imports, which are not publicly reported, are both increasing and of a fairly high volume. We have measured the variability in extract chemical composition and cytotoxicity towards human lung adenocarcinoma A549 cancer cells of 25 commercially available kava products. Results reveal a high level of variation in chemical content and cytotoxicity of currently available kava products. As public interest and use of kava products continues to increase in the United States, efforts to characterize products and expedite research of this potentially useful botanical medicine are necessary.

High resolution mass spectrometry based techniques at the crossroads of metabolic pathways

The metabolome is the set of small molecular mass compounds found in biological media, and metabolomics, which refers to as the analysis of metabolome in a given biological condition, deals with the large scale detection and quantification of metabolites in biological media. It is a data driven and multidisciplinary approach combining analytical chemistry for data acquisition, and biostatistics, informatics and biochemistry for mining and interpretation of these data. Since the middle of the 2000s, high resolution mass spectrometry is widely used in metabolomics, mainly because the detection and identification of metabolites are improved compared to low resolution instruments. As the field of HRMS is quickly and permanently evolving, the aim of this work is to review its use in different aspects of metabolomics, including data acquisition, metabolite annotation, identification and quantification. At last, we would like to show that, thanks to their versatility, HRMS instruments are the most appropriate to achieve optimal metabolome coverage, at the border of other omics fields such as lipidomics and glycomics.

Metabolomics of genetically modified crops

Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs) making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not) the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade.

A novel stable isotope labelling assisted workflow for improved untargeted LC-HRMS based metabolomics research

Many untargeted LC-ESI-HRMS based metabolomics studies are still hampered by the large proportion of non-biological sample derived signals included in the generated raw data. Here, a novel, powerful stable isotope labelling (SIL)-based metabolomics workflow is presented, which facilitates global metabolome extraction, improved metabolite annotation and metabolome wide internal standardisation (IS). The general concept is exemplified with two different cultivation variants, (1) co-cultivation of the plant pathogenic fungi Fusarium graminearum on non-labelled and highly ¹³C enriched culture medium and (2) experimental cultivation under native conditions and use of globally U-¹³C labelled biological reference samples as exemplified with maize and wheat. Subsequent to LC-HRMS analysis of mixtures of labelled and non-labelled samples, two-dimensional data filtering of SIL specific isotopic patterns is performed to better extract truly biological derived signals together with the corresponding number of carbon atoms of each metabolite ion. Finally, feature pairs are convoluted to feature groups each representing a single metabolite. Moreover, the correction of unequal matrix effects in different sample types and the improvement of relative metabolite quantification with metabolome wide IS are demonstrated for the F. graminearum experiment. Data processing employing the presented workflow revealed about 300 SIL derived feature pairs corresponding to 87-135 metabolites in F. graminearum samples and around 800 feature pairs corresponding to roughly 350 metabolites in wheat samples. SIL assisted IS, by the use of globally U-¹³C labelled biological samples, reduced the median CV value from 7.1 to 3.6 % for technical replicates and from 15.1 to 10.8 % for biological replicates in the respective F. graminearum samples.

Evaluating solvent extraction systems using metabolomics approaches

Metabolomics generated features were used as unbiased metrics to identify solvents that produce botanical extracts with the greatest chemical diversity.

Spectral deconvolution for gas chromatography mass spectrometry-based metabolomics: current status and future perspectives

Mass spectrometry coupled to gas chromatography (GC-MS) has been widely applied in the field of metabolomics. Success of this application has benefited greatly from computational workflows that process the complex raw mass spectrometry data and extract the qualitative and quantitative information of metabolites. Among the computational algorithms within a workflow, deconvolution is critical since it reconstructs a pure mass spectrum for each component that the mass spectrometer observes. Based on the pure spectrum, the corresponding component can be eventually identified and quantified. Deconvolution is challenging due to the existence of co-elution. In this review, we focus on progress that has been made in the development of deconvolution algorithms and provide thoughts on future developments that will expand the application of GC-MS in metabolomics.

Toxicity of engineered nanoparticles in the environment

While nanoparticles occur naturally in the environment and have been intentionally used for centuries, the production and use of engineered nanoparticles has seen a recent spike, which makes environmental release almost certain. Therefore, recent efforts to characterize the toxicity of engineered nanoparticles have focused on the environmental implications, including exploration of toxicity to organisms from wide-ranging parts of the ecosystem food webs. Herein, we summarize the current understanding of toxicity of engineered nanoparticles to representatives of various trophic levels, including bacteria, plants, and multicellular aquatic/terrestrial organisms, to highlight important challenges within the field of econanotoxicity, challenges that analytical chemists are expertly poised to address.

Untargeted metabolomics: an emerging approach to determine the composition of herbal products

Natural remedies, such as those based on traditional Chinese medicines, have become more popular also in western countries over the last 10 years. The composition of these herbal products is largely unknown and difficult to determine. Moreover, since plants respond to their environment changing the metabolome, the composition of plant material can vary depending on the plant growth conditions.

However, there is a growing need of a deeper knowledge on such natural remedies also in view of the growing number of reports of toxicity following the consumption of herbal supplements. Untargeted metabolomics is a useful approach for the simultaneous analysis of many compounds in herbal products. In particular, liquid chromatography/mass spectrometry (LC-MS) can determine presence, amount and sometime structures of plant metabolites in complex herbal mixtures, with significant advantages over techniques such as nuclear magnetic resonance (NMR) spectroscopy and gas chromatography/mass spectrometry (GC-MS).

Unravelling the genetic bases of non-target-site-based resistance (NTSR) to herbicides: a major challenge for weed science in the forthcoming decade

Non-target-site-based resistance (NTSR) can confer unpredictable cross-resistance to herbicides. However, the genetic determinants of NTSR remain poorly known. The current, urgent challenge for weed scientists is thus to elucidate the bases of NTSR so that detection tools are developed, the evolution of NTSR is understood, the efficacy of the shrinking herbicide portfolio is maintained and integrated weed management strategies, including fully effective herbicide applications, are designed and implemented. In this paper, the importance of NTSR in resistance to herbicides is underlined. The most likely way in which NTSR evolves-by accumulation of different mechanisms within individual plants-is described. The NTSR mechanisms, which can interfere with herbicide penetration, translocation and accumulation at the target site, and/or protect the plant against the consequences of herbicide action, are then reviewed. NTSR is a part of the plant stress response. As such, NTSR is a dynamic process unrolling over time that involves 'protectors' directly interfering with herbicide action, and also regulators controlling 'protector' expression. NTSR is thus a quantitative trait. On this basis, a three-step procedure is proposed, based on the use of the 'omics' (genomics, transcriptomics, proteomics or metabolomics), to unravel the genetic bases of NTSR.

Plant metabolomics: from experimental design to knowledge extraction

Metabolomics is one of the most recent additions to the functional genomics approaches. It involves the use of analytical chemistry techniques to provide high-density data of metabolic profiles. Data is then analyzed using advanced statistics and databases to extract biological information, thus providing the metabolic phenotype of an organism. Large variety of metabolites produced by plants through the complex metabolic networks and their dynamic changes in response to various perturbations can be studied using metabolomics. Here, we describe the basic features of plant metabolic diversity and analytical methods to describe this diversity, which includes experimental workflows starting from experimental design, sample preparation, hardware and software choices, combined with knowledge extraction methods. Finally, we describe a scenario for using these workflows to identify differential metabolites and their pathways from complex biological samples.

Biotechnological approaches to study plant responses to stress

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.