Plant phenotype demarcation using nontargeted LC-MS and GC-MS metabolite profiling

A Metabolomics Assay to Diagnose Citrus Huanglongbing Disease and to Aid in Assessment of Treatments to Prevent or Cure Infection

Citrus greening disease, or Huanglongbing (HLB), has devastated citrus crops globally in recent years. The causal bacterium, 'Candidatus Liberibacter asiaticus', presents a sampling issue for qPCR diagnostics and results in a high false negative rate. In this work, we compared six metabolomics assays to identify HLB-infected citrus trees from leaf tissue extracted from 30 control and 30 HLB-infected trees. A liquid chromatography-mass spectrometry-based assay was most accurate. A final partial least squares-discriminant analysis (PLS-DA) model was trained and validated on 690 leaf samples with corresponding qPCR measures from three citrus varieties (Rio Red grapefruit, Hamlin sweet orange, and Valencia sweet orange) from orchards in Florida and Texas. Trees were naturally infected with HLB transmitted by the insect vector Diaphorina citri. In a randomized validation set, the assay was 99.9% accurate to classify diseased from nondiseased samples. This model was applied to samples from trees receiving plant defense-inducer compounds or biological treatments to prevent or cure HLB infection. From two trials, HLB-related metabolite abundances and PLS-DA scores were tracked longitudinally and compared with those of control trees. We demonstrate how our assay can assess tree health and the efficacy of HLB treatments and conclude that no trialed treatment was efficacious.

Nutrient Solution Flowing Environment Affects Metabolite Synthesis Inducing Root Thigmomorphogenesis of Lettuce (Lactuca sativa L.) in Hydroponics

The principal difference between hydroponics and other substrate cultivation methods is the flowing liquid hydroponic cultivation substrate. Our previous studies have revealed that a suitable flowing environment of nutrient solution promoted root development and plant growth, while an excess flow environment was unfavorable for plants. To explain the thigmomorphogenetic response of excess flow-induced metabolic changes, six groups of lettuce (Lactuca sativa L.), including two flow conditions and three time periods, were grown. Compared with the plants without flow, the plants with flow showed decreased root fresh weight, total root length, root surface area, and root volume but increased average root diameter and root density. The roots with flow had more upregulated metabolites than those without flow, suggesting that the flow may trigger metabolic synthesis and activity. Seventy-nine common differential metabolites among six groups were screened, and enrichment analysis showed the most significant enrichment in the arginine biosynthesis pathway. Arginine was present in all the groups and exhibited greater concentrations in roots with flow than without flow. It can be speculated from the results that a high-flowing environment of nutrient solution promotes arginine synthesis, resulting in changes in root morphology. The findings provide insights on root thigmomorphogenesis affected by its growing conditions and help understand how plants respond to environmental mechanical forces.

Lipidomes of Icelandic bryophytes and screening of high contents of polyunsaturated fatty acids by using lipidomics approach

Bryophytes (mosses, liverworts, and hornworts) have interested researchers because of their high chemical diversity and their potential uses in pharmaceutical, food, and cosmetic industries. Specifically, long-chain polyunsaturated fatty acids (l-PUFA) such as arachidonic acid (AA) and eicosapentaenoic acid (EPA) are commonly found in bryophytes, but not in vascular plants. Bryophytes accumulate PUFAs in cold or even freezing temperature to keep the cell fluidity. Iceland has a long history of bryophyte vegetation. These bryophytes are highly adapted to the harsh environment in Iceland and therefore are expected to produce high amounts of PUFAs. However, despite the fact that hundreds of mosses and liverworts have been found in Iceland, their lipid profiles largely remain unknown. In this study, we performed untargeted lipidomics by using UPLC-ESI-QTOF-MS as a rapid screening strategy to examine the lipid compositions of 39 local bryophyte species in Iceland and aimed to find high AA and EPA producers. A total of 280 lipid molecular species from 15 lipid classes were quantified with isotope-labeled internal standards. AA and EPA were abundantly distributed in the phospholipids (mainly PC and PE) and glycerolipids (MGDG and DGDG) in six moss species, namely Racomotrium lanuginosum, R. ericoides, Bryum psedotriquetrium, Plagiomnium ellipticum, Hylocomium splendens, and Rhytidiadelphus triquetrus. Two of the six species (B. psedotriquetrium and H. splendens) also accumulated high concentrations of PUFA-containing-triacylglycerols.

Metabolomic Profiling of Different Antrodia cinnamomea Phenotypes

Antrodia cinnamomea (AC) is a precious medicinal fungus with numerous therapeutic benefits. Based on the color appearance of its fruiting bodies, AC can be divided into red AC (RAC), yellow AC (YAC), and white AC (WAC); however, the differences in their metabolomic profiles remain unknown. This study aimed to analyze the metabolomic profiles of three different AC phenotypes and examine their relationship to the color appearance of fruiting bodies. The results showed that although RAC, YAC, and WAC appear to have a relatively similar profile of index triterpenoids, their total triterpenoid contents were significantly different. Among the annotated triterpenoids, many of them were highly present in RAC but not in YAC and WAC, and the relative contents of the four ergostanes (antcamphin F, antcamphin L, antcin B, and antcin K) and one lanostane (versisponic acid D) were found to be significantly different among AC phenotypes. The metabolomic profiles of the AC fruiting bodies demonstrated a total of 140 metabolites, and 41 of them were very different among AC phenotypes. This study indicates that red, yellow, and white AC can biosynthesize the diverse structures of triterpenoids, and RAC possesses a relatively higher contents of triterpenoids and diverse unannotated metabolites than YAC and WAC.

MASPC_Transform: A Plant Point Cloud Segmentation Network Based on Multi-Head Attention Separation and Position Code

Plant point cloud segmentation is an important step in 3D plant phenotype research. Because the stems, leaves, flowers, and other organs of plants are often intertwined and small in size, this makes plant point cloud segmentation more challenging than other segmentation tasks. In this paper, we propose MASPC_Transform, a novel plant point cloud segmentation network base on multi-head attention separation and position code. The proposed MASPC_Transform establishes connections for similar point clouds scattered in different areas of the point cloud space through multiple attention heads. In order to avoid the aggregation of multiple attention heads, we propose a multi-head attention separation loss based on spatial similarity, so that the attention positions of different attention heads can be dispersed as much as possible. In order to reduce the impact of point cloud disorder and irregularity on feature extraction, we propose a new point cloud position coding method, and use the position coding network based on this method in the local and global feature extraction modules of MASPC_Transform. We evaluate our MASPC_Transform on the ROSE_X dataset. Compared with the state-of-the-art approaches, the proposed MASPC_Transform achieved better segmentation results.

Non-targeted metabolomic analysis for the comparative evaluation of volatile organic compounds in 20 globally representative cucumber lines

Volatile organic compounds (VOCs) are one of the main fruit-quality determinants in cucumber. Here, we investigated the differences in the VOC and primary metabolite composition among 20 representative cucumber lines. Results of non-targeted metabolomics revealed that the cucumber breeding line of the Korean group showed a unique VOC composition in the fruit peel compared to the other groups. Fruit-flesh VOCs significantly differed among Korean, European, and Thai fruits. The main cucumber flavor components, 2-hexenal, hexanal, 6-nonenal, 2,4-nonadienal, and 2,6-nonadienal, were lower in the Korean cucumber lines than in the others. Conversely, linoleic acid derivatives and α-linolenic acid, which are precursors of these VOCs, were abundant in Korean cucumber line. This suggests that the metabolism related to the characteristic flavor of cucumber are downregulated in Korean cucumber line. This study provides novel insights into the fruit flavor-associated metabolome in various cucumber lines.

A comparative phytochemical study of nine Lauraceae species by using chemometric data analysis

The diversity of secondary metabolites of individual plants results from multiple enzymatic processes in planta and various environmental factors, such as temperature, moisture, and soil conditions. Chemical composition analysis of plants can lead to a new method to understand relationship among comparable plants along with biological classification such as genetic and anatomical method. In this study, the chemical diversity of nine different Lauraceae species was investigated, and the plant samples were chemically analyzed and classified. Multivariate analysis methods, such as PLS-DA, were used to select important metabolites distinguishing the nine Lauraceae species. The selected metabolites were identified through preparative LC-MS or MS/MS fragment pattern analysis. In addition, the chemical dendrogram for the nine Lauraceae species was interpreted through molecular network analysis and compared with the genetic dendrogram. This approach enabled us to compare the complete chemical compositions of multiple plant samples to identify relationships among plants.

Hexose transporter SWEET5 confers galactose sensitivity to Arabidopsis pollen germination via a galactokinase

Galactose is an abundant and essential sugar used for the biosynthesis of many macromolecules in different organisms, including plants. Galactose metabolism is tightly and finely controlled, since excess galactose and its derivatives are inhibitory to plant growth. In Arabidopsis (Arabidopsis thaliana), root growth and pollen germination are strongly inhibited by excess galactose. However, the mechanism of galactose-induced inhibition during pollen germination remains obscure. In this study, we characterized a plasma membrane-localized transporter, Arabidopsis Sugars Will Eventually be Exported Transporter 5, that transports glucose and galactose. SWEET5 protein levels started to accumulate at the tricellular stage of pollen development and peaked in mature pollen, before rapidly declining after pollen germinated. SWEET5 levels are responsible for the dosage-dependent sensitivity to galactose, and galactokinase is essential for these inhibitory effects during pollen germination. However, sugar measurement results indicate that galactose flux dynamics and sugar metabolism, rather than the steady-state galactose level, may explain phenotypic differences between sweet5 and Col-0 in galactose inhibition of pollen germination.

Lanthanide Metal-Organic Framework-Based Fluorescent Sensor Arrays to Discriminate and Quantify Ingredients of Natural Medicine

The discrimination and quantification of the ingredients from natural medicines are a challenging issue due to their complicated and various structures. Metal-organic frameworks (MOFs) have shown great promise in sensing applications. Here, we report a fluorescent sensor array for rapid identification of some natural compounds using a sensor array composed of four kinds of lanthanide (Eu³⁺ and Tb³⁺) fluorescent MOFs (Ln-MOFs), which have diversified fluorescent responses to 26 active/toxic compounds including 12 saponins, 7 flavonoids, 3 stilbenes, and 4 anthraquinones. The fluorescence of the Ln-MOFs after reaction with the compounds was summarized as datasets and processed by principle component analysis (PCA) and hierarchical cluster analysis (HCA) methods. The corresponding responses of the 4 types of compounds are well separated on 2D/3D PCA score plots and HCA dendrograms. We have also tested typical blind samples by concentration-dependent PCA, and an accuracy of 100% was obtained. In addition, the response mechanisms of the Ln-MOFs to the compounds were also studied. Compared with traditional methods using liquid chromatography-mass spectrometry, the developed fluorescent sensor array provides a more efficient and economic strategy to discriminate various active/toxic ingredients in natural medicine.

Enhancing Salt Tolerance of Plants: From Metabolic Reprogramming to Exogenous Chemical Treatments and Molecular Approaches

Plants grow on soils that not only provide support for root anchorage but also act as a reservoir of water and nutrients important for plant growth and development. However, environmental factors, such as high salinity, hinder the uptake of nutrients and water from the soil and reduce the quality and productivity of plants. Under high salinity, plants attempt to maintain cellular homeostasis through the production of numerous stress-associated endogenous metabolites that can help mitigate the stress. Both primary and secondary metabolites can significantly contribute to survival and the maintenance of growth and development of plants on saline soils. Existing studies have suggested that seed/plant-priming with exogenous metabolites is a promising approach to increase crop tolerance to salt stress without manipulation of the genome. Recent advancements have also been made in genetic engineering of various metabolic genes involved in regulation of plant responses and protection of the cells during salinity, which have therefore resulted in many more basic and applied studies in both model and crop plants. In this review, we discuss the recent findings of metabolic reprogramming, exogenous treatments with metabolites and genetic engineering of metabolic genes for the improvement of plant salt tolerance.

Variation of Microbiological and Biochemical Profiles of Laowo Dry-Cured Ham, an Indigenous Fermented Food, during Ripening by GC-TOF-MS and UPLC-QTOF-MS

Fermented foods have unique microbiota and metabolomic profiles that can support dietary diversity, digestion, and gut health of consumers. Laowo ham (LWH) is an example of an indigenous fermented food from Southwestern China that has cultural, ecological, economic, and health significance to local communities. We carried out ethnobiological surveys coupled with metagenomic and metabolomic analyses using GC-TOF-MS and UPLC-QTOF-MS to elucidate the microbiota and metabolic profiles of LWH samples at different ripening stages. The results from high-throughput sequencing showed a total of 502 bacterial genera in LWH samples with 12 genera of bacteria and 6 genera of fungi identified as dominant groups. This is the first study to our knowledge to report the bacteria of Lentibacillus and Mesorhizobium along with fungi Eremascus and Xerochrysium on a fermented meat product. Findings further revealed that the metabolite profiles among LWH samples were significantly different. In total, 27 and 30 metabolites from GC-TOF-MS and UPLC-QTOF-MS analysis, respectively, were annotated as highly discriminative metabolites. Among the differential compounds, the relative contents of most amino acids showed the highest in the LWH sample ripened for two years, while some metabolites with potential therapeutic effects such as levetiracetam were the most abundant in the LWH sample ripened for three years. The correlation analysis indicated that the dominant microbes were closely related to differential metabolites, highlighting the importance of their functional characterization. Findings indicate that the consumption of LWH contributes to microbiological and chemical diversity of human diets as well as suggests efficacy of combining GC-MS and LC-MS to study the metabolites in dry-cured meat products.

An integration of UPLC-DAD/ESI-Q-TOF MS, GC-MS, and PCA analysis for quality evaluation and identification of cultivars of Chrysanthemi Flos (Juhua)

BACKGROUND

Chrysanthemi Flos (CF), as a popular traditional Chinese medicine (TCM), has five main cultivars in China, namely "Chuju", "Boju", "Gongju", "Huaiju" and "Hangju". Due to their habitats and processing methods, great quality variations occur yet no systematical study has ever been carried out to evaluate such variations.

PURPOSE

In this study, we aim to establish a new approach that can serve both as a quality control method and as an identification method for cultivars of CF.

METHOD

The components in CF samples were identified by a combination of UPLC-ESI-Q-TOF/MS and GC/MS. Furthermore, a multimodal quantitative method was established by UPLC-UV coupled with principal component analysis (PCA) and the similarity evaluation system (SES), which was used to control and identify four cultivars of CF.

RESULTS

18 compounds of flavonoids and caffeoylquinic acids were identified and ten of them were quantified using UPLC-ESI-Q-TOF/MS. Different cultivars of CF could be clearly distinguished with the fingerprints evaluation and principal component analysis (PCA). A total of 74 volatile compounds were detected by GC/MS. The distinctness of volatile components was observed. By the combination of UPLC-ESI-Q-TOF/MS and GC/MS, an identification and quality control method for CF was successfully established.

CONCLUSION

The combination of UPLC-ESI-Q-TOF/MS and GC/MS could act as a comprehensive multimodal method for both identification and quality control of herbal medicines. This study provided new insights into the overall evaluation method for herbal medicines possessing different cultivars.

Developmental Stage- and Genotype-Dependent Regulation of Specialized Metabolite Accumulation in Fruit Tissues of Different Citrus Varieties

Flavor traits in citrus are the result of a blend of low molecular weight metabolites including sugars, acids, flavonoids and limonoids, these latter being mainly responsible for the characteristic bitter flavor in citrus. In this work, the genotype- and developmental stage-dependent accumulation of flavonoids and limonoids is addressed. To fulfill this goal, three models for citrus bitterness: bitter Duncan grapefruit, bittersweet Thomson orange and sweet Wase mandarin were selected from a total of eight different varieties. Compounds were annotated from LC/ESI-QqTOF-MS non-targeted metabolite profiles from albedo and pulp tissues. Results indicated that the specific blend of compounds providing the characteristic flavor trait is genotype-specific and hence under genetic control, but it is also regulated at the developmental level. Metabolite profiles in albedo mirrored those found in pulp, the edible part of the fruit, despite differences in the concentration and accumulation/depletion rates being found. This is particularly relevant for polymethoxylated flavones and glycosylated limonoids that showed a clear partitioning towards albedo and pulp tissues, respectively. Fruit ripening was characterized by a reduction in flavonoids and the accumulation of limonoid glycosides. However, bitter grapefruit showed higher levels of limonin A-ring lactone and naringin in contrast to sweeter orange and mandarin. Data indicated that the accumulation profile was compound class-specific and conserved among the studied varieties despite differing in the respective accumulation and/or depletion rate, leading to different specialized metabolite concentration at the full ripe stage, consistent with the flavor trait output.

Untargeted Metabolomics Analysis of Eggplant (Solanum melongena L.) Fruit and Its Correlation to Fruit Morphologies

Eggplant is one of the most widely cultivated vegetables in the world and has high biodiversity in terms of fruit shape, size, and color. Therefore, fruit morphology and nutrient content become important considerations for both consumers and breeders who develop new eggplant-based products. To gain insight on the diversity of eggplant metabolites, twenty-one eggplant accessions were analyzed by untargeted metabolomics using GC-MS and LC-MS. The dataset of eggplant fruit morphologies, and metabolites specific to different eggplant fruit accessions were used for correlation analysis. Untargeted metabolomics analysis using LC-MS and GC-MS was able to detect 136 and 207 peaks, respectively. Fifty-one (51) metabolites from the LC-MS analysis and 207 metabolites from the GC-MS analysis were putatively identified, which included alkaloids, terpenes, terpenoids, fatty acids, and flavonoids. Spearman correlation analysis revealed that 14 fruit morphologies were correlated with several metabolites. This information will be very useful for the development of strategies for eggplant breeding.

Metabolomic Evaluation of the Quality of Leaf Lettuce Grown in Practical Plant Factory to Capture Metabolite Signature

Vegetables produce metabolites that affect their taste and nutritional value and compounds that contribute to human health. The quality of vegetables grown in plant factories under hydroponic cultivation, e.g., their sweetness and softness, can be improved by controlling growth factors including the temperature, humidity, light source, and fertilizer. However, soil is cheaper than hydroponic cultivation and the visual phenotype of vegetables grown under the two conditions is different. As it is not clear whether their metabolite composition is also different, we studied leaf lettuce raised under the hydroponic condition in practical plant factory and strictly controlled soil condition. We chose two representative cultivars, "black rose" (BR) and "red fire" (RF) because they are of high economic value. Metabolite profiling by comprehensive gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) resulted in the annotation of 101 metabolites from 223 peaks detected by GC-MS; LC-MS yielded 95 peaks. The principal component analysis (PCA) scatter plot showed that the most distinct separation patterns on the first principal component (PC1) coincided with differences in the cultivation methods. There were no clear separations related to cultivar differences in the plot. PC1 loading revealed the discriminant metabolites for each cultivation method. The level of amino acids such as lysine, phenylalanine, tryptophan, and valine was significantly increased in hydroponically grown leaf lettuce, while soil-cultivation derived leaf lettuce samples contained significantly higher levels of fatty-acid derived alcohols (tetracosanol and hexacosanol) and lettuce-specific sesquiterpene lactones (lactucopicrin-15-oxalate and 15-deoxylactucin-8-sulfate). These findings suggest that the metabolite composition of leaf lettuce is primarily affected by its cultivation condition. As the discriminant metabolites reveal important factors that contribute to the nutritional value and taste characteristics of leaf lettuce, we performed comprehensive metabolite profiling to identify metabolite compositions, i.e., metabolite signature, that directly improve its quality and value.

Metabolite fingerprinting, pathway analyses, and bioactivity correlations for plant species belonging to the Cornaceae, Fabaceae, and Rosaceae families

A multi-parallel approach gauging the mass spectrometry-based metabolite fingerprinting coupled with bioactivity and pathway evaluations could serve as an efficacious tool for inferring plant taxonomic orders. Thirty-four species from three plant families, namely Cornaceae (7), Fabaceae (9), and Rosaceae (18) were subjected to metabolite profiling using gas chromatography-time-of-flight-mass spectrometry (GC-TOF-MS) and ultrahigh performance liquid chromatography-linear trap quadrupole-ion trap-mass spectrometry (UHPLC-LTQ-IT-MS/MS), followed by multivariate analyses to determine the metabolites characteristic of these families. The partial least squares discriminant analysis (PLS-DA) revealed the distinct clustering pattern of metabolites for each family. The pathway analysis further highlighted the relatively higher proportions of flavonols and ellagitannins in the Cornaceae family than in the other two families. Higher levels of phenolic acids and flavan-3-ols were observed among species from the Rosaceae family, while amino acids, flavones, and isoflavones were more abundant among the Fabaceae family members. The antioxidant activities of plant extracts were measured using ABTS, DPPH, and FRAP assays, and indicated that extracts from the Rosaceae family had the highest activity, followed by those from Cornaceae and Fabaceae. The correlation map analysis positively links the proportional concentration of metabolites with their relative antioxidant activities, particularly in Cornaceae and Rosaceae. This work highlights the pre-eminence of the multi-parallel approach involving metabolite profiling and bioactivity evaluations coupled with metabolic pathways as an efficient methodology for the evaluation of plant phylogenies.

Detection of QTL for metabolic and agronomic traits in wheat with adjustments for variation at genetic loci that affect plant phenology

Mapping of quantitative trait loci associated with levels of individual metabolites (mQTL) was combined with the mapping of agronomic traits to investigate the genetic basis of variation and co-variation in metabolites, agronomic traits, and plant phenology in a field-grown bread wheat population. Metabolome analysis was performed using liquid chromatography-mass spectrometry resulting in identification of mainly polar compounds, including secondary metabolites. A total of 558 metabolic features were obtained from the flag leaves of 179 doubled haploid lines, of which 197 features were putatively identified, mostly as alkaloids, flavonoids and phenylpropanoids. Coordinated genetic control was observed for several groups of metabolites, such as organic acids influenced by two loci on chromosome 7A. Five major phenology-related loci, which were introduced as cofactors in the analyses, differed in their impact upon metabolic and agronomic traits with QZad-aww-7A having more impact on the expression of both metabolite and agronomic QTL than Ppd-B1, Vrn-A1, Eps, and QZad-aww-7D. This QTL study validates the utility of combining agronomic and metabolomic traits as an approach to identify potential trait enhancement targets for breeding selection and reinforces previous results that demonstrate the importance of including plant phenology in the assessment of useful traits in this wheat mapping population.

Comparison of GC-MS and GC×GC-MS in the analysis of human serum samples for biomarker discovery

We compared the performance of gas chromatography time-of-flight mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS) for metabolite biomarker discovery. Metabolite extracts from 109 human serum samples were analyzed on both platforms with a pooled serum sample analyzed after every 9 biological samples for the purpose of quality control (QC). The experimental data derived from the pooled QC samples showed that the GC×GC-MS platform detected about three times as many peaks as the GC-MS platform at a signal-to-noise ratio SNR ≥ 50, and three times the number of metabolites were identified by mass spectrum matching with a spectral similarity score Rsim ≥ 600. Twenty-three metabolites had statistically significant abundance changes between the patient samples and the control samples in the GC-MS data set while 34 metabolites in the GC×GC-MS data set showed statistically significant differences. Among these two groups of metabolite biomarkers, nine metabolites were detected in both the GC-MS and GC×GC-MS data sets with the same direction and similar magnitude of abundance changes between the control and patient sample groups. Manual verification indicated that the difference in the number of the biomarkers discovered using these two platforms was mainly due to the limited resolution of chromatographic peaks by the GC-MS platform, which can result in severe peak overlap making subsequent spectrum deconvolution for metabolite identification and quantification difficult.

Non-targeted metabolite profiling of citrus juices as a tool for variety discrimination and metabolite flow analysis

BACKGROUND

Genetic diversity of citrus includes intrageneric hybrids, cultivars arising from cross-pollination and/or somatic mutations with particular biochemical compounds such as sugar, acids and secondary metabolite composition.

RESULTS

Secondary metabolite profiles of juices from 12 commercial varieties grouped into blonde and navel types, mandarins, lemons and grapefruits were analyzed by LC/ESI-QTOF-MS. HCA on metabolite profiling data revealed the existence of natural groups demarcating fruit types and varieties associated to specific composition patterns. The unbiased classification provided by HCA was used for PLS-DA to find the potential variables (mass chromatographic features) responsible for the classification. Abscisic acid and derivatives, several flavonoids and limonoids were identified by analysis of mass spectra. To facilitate interpretation, metabolites were represented as flow charts depicting biosynthetic pathways. Mandarins 'Fortune' and 'Hernandina' along with oranges showed higher ABA contents and ABA degradation products were present as glycosylated forms in oranges and certain mandarins. All orange and grapefruit varieties showed high limonin contents and its glycosylated form, that was only absent in lemons. The rest of identified limonoids were highly abundant in oranges. Particularly, Sucrenya cultivar showed a specific accumulation of obacunone and limonoate A-ring lactone. Polymethoxylated flavanones (tangeritin and isomers) were absolutely absent from lemons and grapefruits whereas kaempferol deoxyhexose hexose isomer #2, naringin and neohesperidin were only present in these cultivars.

CONCLUSIONS

Analysis of relative metabolite build-up in closely-related genotypes allowed the efficient demarcation of cultivars and suggested the existence of genotype-specific regulatory mechanisms underlying the differential metabolite accumulation.

Metabolic profiling of Commiphora wightii (guggul) reveals a potential source for pharmaceuticals and nutraceuticals

Guggul gum resin from Commiphora wightii (syn. Commiphoramukul) has been used for centuries in Ayurveda to treat a variety of ailments. The NMR and GC-MS based non-targeted metabolite profiling identified 118 chemically diverse metabolites including amino acids, fatty acids, organic acids, phenolic acids, pregnane-derivatives, steroids, sterols, sugars, sugar alcohol, terpenoids, and tocopherol from aqueous and non-aqueous extracts of leaves, stem, roots, latex and fruits of C. wightii. Out of 118, 51 structurally diverse aqueous metabolites were characterized by NMR spectroscopy. For the first time quinic acid and myo-inositol were identified as the major metabolites in C. wightii. Very high concentration of quinic acid was found in fruits (553.5 ± 39.38 mg g(-1) dry wt.) and leaves (212.9 ± 10.37 mg g(-1) dry wt.). Similarly, high concentration of myo-inositol (168.8 ± 13.84 mg g(-1) dry wt.) was observed from fruits. The other metabolites of cosmeceutical, medicinal, nutraceutical and industrial significance such as α-tocopherol, n-methylpyrrolidone (NMP), trans-farnesol, prostaglandin F2, protocatechuic, gallic and cinnamic acids were identified from non-aqueous extracts using GC-MS. These important metabolites have thus far not been reported from this plant. Isolation of a fungal endophyte, (Nigrospora sps.) from this plant is the first report. The fungal endophyte produced a substantial quantity of bostrycin and deoxybostrycin known for their antitumor properties. Very high concentrations of quinic acid and myo-inositol in leaves and fruits; a substantial quantity of α-tocopherol and NMP in leaves, trans-farnesol in fruits, bostrycin and deoxybostrycin from its endophyte makes the taxa distinct, since these metabolites with medicinal properties find immense applications as dietary supplements and nutraceuticals.

Gas chromatography-mass spectrometry of biofluids and extracts

Gas chromatography-mass spectrometry (GC-MS) has been widely used in metabonomics analyses of biofluid samples. Biofluids provide a wealth of information about the metabolism of the whole body and from multiple regions of the body that can be used to study general health status and organ function. Blood serum and blood plasma, for example, can provide a comprehensive picture of the whole body, while urine can be used to monitor the function of the kidneys, and cerebrospinal fluid (CSF) will provide information about the status of the brain and central nervous system (CNS). Different methods have been developed for the extraction of metabolites from biofluids, these ranging from solvent extracts, acids, heat denaturation, and filtration. These methods vary widely in terms of efficiency of protein removal and in the number of metabolites extracted. Consequently, for all biofluid-based metabonomics studies, it is vital to optimize and standardize all steps of sample preparation, including initial extraction of metabolites. In this chapter, recommendations are made of the optimum experimental conditions for biofluid samples for GC-MS, with a particular focus on blood serum and plasma samples.

Primary and secondary metabolite profiling of doenjang, a fermented soybean paste during industrial processing

In this study, a comprehensive metabolite profile analysis of doenjang, a fermented soybean paste, at various steps of its industrial 5-step production process was conducted, by combining gas and liquid chromatography-mass spectrometry techniques with multivariate analysis. From the partial least squares discriminant analysis of primary and secondary metabolites, the patterns were clearly distinguishable between the various processing steps (step 1: steaming, step 2: drying, step 3: meju fermentation, step 4: brining, step 5: doenjang aging). Of the primary metabolites, most of the monosaccharides, amino acids, and fatty acids increased in steps 3-5. Isoflavone and soyasaponin derivatives were major secondary metabolites identified during the processing of doenjang. Isoflavone glycosides gradually decreased after step 1, while isoflavone aglycones distinctly increased in steps 4-5. Soyasaponins generally decreased during processing after step 2. Increased isoflavone aglycones, such as daidzein, glycitein, and genistein, were observed in steps 4-5 showed the strongest positive correlation with doenjang's antioxidant potential and total phenolic content.

Secondary metabolite profiling of Curcuma species grown at different locations using GC/TOF and UPLC/Q-TOF MS

Curcuma, a genus of rhizomatous herbaceous species, has been used as a spice, traditional medicine, and natural dye. In this study, the metabolite profile of Curcuma extracts was determined using gas chromatography-time of flight mass spectrometry (GC/TOF MS) and ultrahigh-performance liquid chromatography–quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF MS) to characterize differences between Curcuma aromatica and Curcuma longa grown on the Jeju-do or Jin-do islands, South Korea. Previous studies have performed primary metabolite profiling of Curcuma species grown in different regions using NMR-based metabolomics. This study focused on profiling of secondary metabolites from the hexane extract of Curcuma species. Principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) plots showed significant differences between the C. aromatica and C. longa metabolite profiles, whereas geographical location had little effect. A t-test was performed to identify statistically significant metabolites, such as terpenoids. Additionally, targeted profiling using UPLC/Q-TOF MS showed that the concentration of curcuminoids differed depending on the plant origin. Based on these results, a combination of GC- and LC-MS allowed us to analyze curcuminoids and terpenoids, the typical bioactive compounds of Curcuma, which can be used to discriminate Curcuma samples according to species or geographical origin.

Correlation between species-specific metabolite profiles and bioactivities of blueberries (Vaccinium spp.)

Metabolite profiling of three blueberry species (Vaccinium bracteatum Thunb., V. oldhamii Miquel., and V. corymbosum L.) was performed using gas chromatography-time-of-flight-mass spectrometry (GC-TOF-MS) and ultraperformance liquid chromatography-quadrupole-time-of-flight-mass spectrometry (UPLC-Q-TOF-MS) combined multivariate analysis. Partial least-squares discriminant analysis clearly showed metabolic differences among species. GC-TOF-MS analysis revealed significant differences in amino acids, organic acids, fatty acids, sugars, and phenolic acids among the three blueberry species. UPLC-Q-TOF-MS analysis indicated that anthocyanins were the major metabolites distinguishing V. bracteatum from V. oldhamii. The contents of anthocyanins such as glycosides of cyanidin were high in V. bracteatum, while glycosides of delphinidin, petunidin, and malvidin were high in V. oldhamii. Antioxidant activities assessed using ABTS and DPPH assays showed the greatest activity in V. oldhamii and revealed the highest correlation with total phenolic, total flavonoid, and total anthocyanin contents and their metabolites.

Metabolomics in plant environmental physiology

Changes in plant metabolism are at the heart of plant developmental processes, underpinning many of the ways in which plants respond to the environment. As such, the comprehensive study of plant metabolism, or metabolomics, is highly valuable in identifying phenotypic effects of abiotic and biotic stresses on plants. When study is in reference to analysing samples that are relevant to environmental or ecologically based hypotheses, it is termed 'environmental metabolomics'. The emergence of environmental metabolomics as one of the latest of the omics technologies has been one of the most critically important recent developments in plant physiology. Its applications broach the entire landscape of plant ecology, from the understanding of plant plasticity and adaptation through to community composition and even genetic modification in crops. The multitude of novel studies published utilizing metabolomics methods employ a variety of techniques, from the initial stages of tissue sampling, through to sample preservation, transportation, and analysis. This review introduces the concept and applications of plant environmental metabolomics as an ecologically important investigative tool. It examines the main techniques used in situ within field sites, with particular reference to sampling and processing, and those more appropriate for use in laboratory-based settings with emphasis on secondary metabolite analysis.

Comparative metabolomics in Glycine max and Glycine soja under salt stress to reveal the phenotypes of their offspring

Metabolomics is developing as an important functional genomics tool for understanding plant systems' response to genetic and environmental changes. Here, we characterized the metabolic changes of cultivated soybean C08 (Glycine max L. Merr) and wild soybean W05 (Glycine soja Sieb.et Zucc.) under salt stress using MS-based metabolomics, in order to reveal the phenotypes of their eight hybrid offspring (9H0086, 9H0124, 9H0391, 9H0736, 9H0380, 9H0400, 9H0434, and 9H0590). Total small molecule extracts of soybean seedling leaves were profiled by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-Fourier transform mass spectrometry (LC-FT/MS). We found that wild soybean contained higher amounts of disaccharides, sugar alcohols, and acetylated amino acids than cultivated soybean, but with lower amounts of monosaccharides, carboxylic acids, and unsaturated fatty acids. Further investigations demonstrated that the ability of soybean to tolerate salt was mainly based on synthesis of compatible solutes, induction of reactive oxygen species (ROS) scavengers, cell membrane modifications, and induction of plant hormones. On the basis of metabolic phenotype, the salt-tolerance abilities of 9H0086, 9H0124, 9H0391, 9H0736, 9H0380, 9H0400, 9H0434, and 9H0590 were discriminated. Our results demonstrated that MS-based metabolomics provides a fast and powerful approach to discriminate the salt-tolerance characteristics of soybeans.

Metabolomic characterization of rhubarb species by capillary electrophoresis and ultra-high-pressure liquid chromatography

This study developed CE and ultra-high-pressure LC (UHPLC) methods coupled with UV detectors to characterize the metabolomic profiles of different rhubarb species. The optimal CE conditions used a BGE with 15 mM sodium tetraborate, 15 mM sodium dihydrogen phosphate monohydrate, 30 mM sodium deoxycholate, and 30% ACN v/v at pH 8.3. The optimal UHPLC conditions used a mobile phase composed of 0.05% phosphate buffer and ACN with gradient elution. The gradient profile increased linearly from 10 to 21% ACN within the first 25 min, then increased to 33% ACN for the next 10 min. It took another 5 min to reach the 65% ACN, then for the next 5 min, it stayed unchanged. Sixteen samples of Rheum officinale and Rheum tanguticum collected from various locations were analyzed by CE and UHPLC methods. The metabolite profiles of CE were aligned and baseline corrected before chemometric analysis. Metabolomic signatures of rhubarb species from CE and UHPLC were clustered using principle component analysis and distance-based redundancy analysis; the clusters were not only able to discriminate different species but also different cultivation regions. Similarity measurements were performed by calculating the correlation coefficient of each sample with the authentic samples. Hybrid rhizome was clearly identified through similarity measurement of UHPLC metabolite profile and later confirmed by gene sequencing. The present study demonstrated that CE and UHPLC are efficient and effective tools to identify and authenticate herbs even coupled with simple detectors.

Metabolomics as a tool to investigate abiotic stress tolerance in plants

Metabolites reflect the integration of gene expression, protein interaction and other different regulatory processes and are therefore closer to the phenotype than mRNA transcripts or proteins alone. Amongst all –omics technologies, metabolomics is the most transversal and can be applied to different organisms with little or no modifications. It has been successfully applied to the study of molecular phenotypes of plants in response to abiotic stress in order to find particular patterns associated to stress tolerance. These studies have highlighted the essential involvement of primary metabolites: sugars, amino acids and Krebs cycle intermediates as direct markers of photosynthetic dysfunction as well as effectors of osmotic readjustment. On the contrary, secondary metabolites are more specific of genera and species and respond to particular stress conditions as antioxidants, Reactive Oxygen Species (ROS) scavengers, coenzymes, UV and excess radiation screen and also as regulatory molecules. In addition, the induction of secondary metabolites by several abiotic stress conditions could also be an effective mechanism of cross-protection against biotic threats, providing a link between abiotic and biotic stress responses. Moreover, the presence/absence and relative accumulation of certain metabolites along with gene expression data provides accurate markers (mQTL or MWAS) for tolerant crop selection in breeding programs.

Nontargeted metabolite profiling in compatible pathogen-inoculated tobacco (Nicotiana tabacum L. cv. Wisconsin 38) using UPLC-Q-TOF/MS

A biphasic reactive oxygen species (ROS) production has previously been observed in tobacco at 1 and 48 h after inoculation with the hemibiotrophic compatible pathogen, Phytophthora parasitica var. nicotianae (Ppn). To characterize the response of tobacco to biphasically produced ROS concerning the propagation of Ppn, ultraperformance liquid chromatography-quadrupole-time of flight/ mass spectrometry (UPLC-Q-TOF/MS) based metabolic profiling combined with multivariate statistical analysis was performed. Among the nonredundant 355 mass ions in ESI+ mode and 345 mass ions in ESI- mode that were selected as significantly changed by Ppn inoculation (|p(corr)| > 0.6 on S-plot of orthogonal partial least-squares discriminant analysis (OPLS-DA), fold-change > 2, and p < 0.05 in the independent two-sample t test), 76 mass ions were identified on the basis of their accurate mass ions and MS/MS spectra. Phenolic amino acids, phenylpropanoids, hydroxycinnamic acid amides, linoleic acid, linolenic acid, lysophospholipids, glycoglycerolipids, and trioxidized phospholipids were identified as having changed after Ppn inoculation. On the basis of their quantitative changes, the metabolic responses occurring at each phase of ROS production after Ppn inoculation were investigated in this study.

A fast and precise method to identify indolic glucosinolates and camalexin in plants by combining mass spectrometric and biological information

In this manuscript, a fast and accurate identification and quantitation by mass spectrometry of indolic glucosinolates and camalexin involved in defense in Arabidopsis thaliana are described. Two elicitation systems, inoculation with Botrytis cinerea and treatment with AgNO(3), were used in Col-0 wild-type and mutant genotypes impaired in the biosynthesis of the selected metabolites. Identification of analytes was carried out by nontargeted LC/ESI-QTOF-MS profiling. Confirmation of indolic glucosinolates and camalexin was achieved by their absence in the cyp79B2/B3 and pad3 mutants as well as their respective fragmentation upon collision-induced dissociation. Camalexin accumulation was induced only after AgNO(3) treatment, whereas all indolic glucosinolates were constitutively present. Inoculation with Botrytis did not influence camalexin concentration but caused most aliphatic and indolic glucosinolates contents to decrease. Only the pen 3.1 mutant showed increased indolic glucosinolate levels after Botrytis or AgNO(3) treatments. In addition, profiles of secondary metabolite in nontreated Col-0 and mutant plants were analyzed by means of partial least squares coupled to discriminant analysis (PLS-DA), and differences in the basal levels of indolic glucosinolates and tryptophan between cyp79B2/B3 plants and the rest of genotypes, including Col-0, were found. This probably has to be taken into consideration when comparing stress responses of Col-0 and cyp79B2/B3. The use of mutants carrying alterations in biosynthetic pathways is proposed as a useful strategy to identify secondary metabolites.

PyMS: a Python toolkit for processing of gas chromatography-mass spectrometry (GC-MS) data. Application and comparative study of selected tools

Background

Gas chromatography–mass spectrometry (GC-MS) is a technique frequently used in targeted and non-targeted measurements of metabolites. Most existing software tools for processing of raw instrument GC-MS data tightly integrate data processing methods with graphical user interface facilitating interactive data processing. While interactive processing remains critically important in GC-MS applications, high-throughput studies increasingly dictate the need for command line tools, suitable for scripting of high-throughput, customized processing pipelines.

Results

PyMS comprises a library of functions for processing of instrument GC-MS data developed in Python. PyMS currently provides a complete set of GC-MS processing functions, including reading of standard data formats (ANDI- MS/NetCDF and JCAMP-DX), noise smoothing, baseline correction, peak detection, peak deconvolution, peak integration, and peak alignment by dynamic programming. A novel common ion single quantitation algorithm allows automated, accurate quantitation of GC-MS electron impact (EI) fragmentation spectra when a large number of experiments are being analyzed. PyMS implements parallel processing for by-row and by-column data processing tasks based on Message Passing Interface (MPI), allowing processing to scale on multiple CPUs in distributed computing environments. A set of specifically designed experiments was performed in-house and used to comparatively evaluate the performance of PyMS and three widely used software packages for GC-MS data processing (AMDIS, AnalyzerPro, and XCMS).

Conclusions

PyMS is a novel software package for the processing of raw GC-MS data, particularly suitable for scripting of customized processing pipelines and for data processing in batch mode. PyMS provides limited graphical capabilities and can be used both for routine data processing and interactive/exploratory data analysis. In real-life GC-MS data processing scenarios PyMS performs as well or better than leading software packages. We demonstrate data processing scenarios simple to implement in PyMS, yet difficult to achieve with many conventional GC-MS data processing software. Automated sample processing and quantitation with PyMS can provide substantial time savings compared to more traditional interactive software systems that tightly integrate data processing with the graphical user interface.

LC-MS-based metabolomics

Metabolomics aims at identification and quantitation of small molecules involved in metabolic reactions. LC-MS has enjoyed a growing popularity as the platform for metabolomic studies due to its high throughput, soft ionization, and good coverage of metabolites. The success of a LC-MS-based metabolomic study often depends on multiple experimental, analytical, and computational steps. This review presents a workflow of a typical LC-MS-based metabolomic analysis for identification and quantitation of metabolites indicative of biological/environmental perturbations. Challenges and current solutions in each step of the workflow are reviewed. The review intends to help investigators understand the challenges in metabolomic studies and to determine appropriate experimental, analytical, and computational methods to address these challenges.

A rapid, simple method for the genetic discrimination of intact Arabidopsis thaliana mutant seeds using metabolic profiling by direct analysis in real-time mass spectrometry

BACKGROUND

Efficient high throughput screening systems of useful mutants are prerequisite for study of plant functional genomics and lots of application fields. Advance in such screening tools, thanks to the development of analytic instruments. Direct analysis in real-time (DART)-mass spectrometry (MS) by ionization of complex materials at atmospheric pressure is a rapid, simple, high-resolution analytical technique. Here we describe a rapid, simple method for the genetic discrimination of intact Arabidopsis thaliana mutant seeds using metabolic profiling by DART-MS.

RESULTS

To determine whether this DART-MS combined by multivariate analysis can perform genetic discrimination based on global metabolic profiling, intact Arabidopsis thaliana mutant seeds were subjected to DART-MS without any sample preparation. Partial least squares-discriminant analysis (PLS-DA) of DART-MS spectral data from intact seeds classified 14 different lines of seeds into two distinct groups: Columbia (Col-0) and Landsberg erecta (Ler) ecotype backgrounds. A hierarchical dendrogram based on partial least squares-discriminant analysis (PLS-DA) subdivided the Col-0 ecotype into two groups: mutant lines harboring defects in the phenylpropanoid biosynthetic pathway and mutants without these defects. These results indicated that metabolic profiling with DART-MS could discriminate intact Arabidopsis seeds at least ecotype level and metabolic pathway level within same ecotype.

CONCLUSION

The described DART-MS combined by multivariate analysis allows for rapid screening and metabolic characterization of lots of Arabidopsis mutant seeds without complex metabolic preparation steps. Moreover, potential novel metabolic markers can be detected and used to clarify the genetic relationship between Arabidopsis cultivars. Furthermore this technique can be applied to predict the novel gene function of metabolic mutants regardless of morphological phenotypes.

Towards a systemic metabolic signature of the arbuscular mycorrhizal interaction

Our experiments addressed systemic metabolic effects in above-ground plant tissue as part of the plant's response to the arbuscular mycorrhizal (AM) interaction. Due to the physiology of this interaction, we expected effects in the areas of plant mineral nutrition, carbon allocation and stress-related metabolism, but also a notable dependence of respective metabolic changes on environmental conditions and on plant developmental programs. To assess these issues, we analyzed metabolite profiles from mycorrhizal and non-mycorrhizal Lotus japonicus grown under greenhouse conditions at three different time points in the growing season in three different above-ground organs (flowers, sink leaves and source leaves). Statistical analysis of our data revealed a number of significant changes in individual experiments with little overlap between these experiments, indicating the expected impact of external conditions on the plant's response to AM colonization. Partial least square-discriminant analysis (PLS-DA) nevertheless revealed considerable similarities between the datasets, and loading analysis of the component separating mycorrhizal and non-mycorrhizal plants allowed the defining of a core set of metabolites responsible for this separation. This core set was observed in experiments with and without mycorrhiza-induced growth effects. It corroborated trends already indicated by the significant changes from individual experiments and suggested a negative systemic impact of AM colonization on central catabolic metabolism as well as on amino acid metabolism. In addition, metabolic signals for an increase in stress experienced by plant tissue were recorded in flowers and source leaves.

Common and divergent physiological, hormonal and metabolic responses of Arabidopsis thaliana and Thellungiella halophila to water and salt stress

To explain the higher tolerance of Thellungiella to abiotic stress in comparison to Arabidopsis, several studies have focused on differences in ion absorption and gene expression. However, little is known about hormone regulation and metabolic responses. In this work, plants of both species were subjected to desiccation and salt stress to compare common and divergent responses. In control conditions, the number of significantly upregulated mass features as well as proline levels was higher in Tellungiella than in Arabidopsis. When subjected to desiccation, both species exhibited similar rates of water loss but proline over accumulation only occurred in Thellungiella; both species accumulated ABA and JA with a similar trend although Arabidopsis showed higher concentrations of both hormones which indicated a stronger impact of desiccation on Arabidopsis. However, Arabidopsis showed a higher number of significantly altered mass features than Thellungiella. Under salt stress, Thellungiella plants accumulated lower amounts of Cl(-) ions than Arabidopsis but exhibited a similar proline response. Under these conditions, ABA and JA levels increased in Arabidopsis whereas minimal changes in both hormone concentrations were recorded in Thellungiella. Contrastingly, the impact of salt stress on metabolite profiles was higher in Thellungiella than in Arabidopsis. Overall, data indicated that physiological responses in Arabidopsis are induced after stress imposition through hormonal regulation whereas Thellungiella has a basal metabolic configuration, better prepared to endure environmental cues.

Urinary metabonomics study in a rat model in response to protein-energy malnutrition by using gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry

Systematic studies were performed on the biological perturbations in metabolic phenotype responding to protein-energy malnutrition through global metabolic profiling analysis, in combination with pattern recognition. The malnutrition rat model was established through five weeks of strict diet restriction, and the metabonome data obtained from gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) were integrated to approximate the comprehensive metabolic signature. Principal component analysis and orthogonal projection to latent structure analysis were used for the classification of metabolic phenotypes and discovery of differentiating metabolites. The perturbations in the urine profiles of malnourished rats were marked by higher levels of creatine, threitol, pyroglutamic acid, gluconic acid and kynurenic acid, as well as decreased levels of succinic acid, cis-aconitic acid, citric acid, isocitric acid, threonic acid, trimethylglycine, N-methylnicotinic acid and uric acid. The alterations in these metabolites were associated with perturbations in energy metabolism, carbohydrate, amino acid, and fatty acid metabolism, purine metabolism, cofactor and vitamin metabolism, in response to protein and energy malnutrition. Our findings show the integration of GC-MS and LC-MS techniques for untargeted metabolic profiling analysis was promising for nutriology.