Investigation of the relationship between the metabolic profile of tobacco leaves in different planting regions and climate factors using a pseudotargeted method based on gas chromatography/mass spectrometry

Exploring Metabolic Characteristics in Different Geographical Locations and Yields of Nicotiana tabacum L. Using Gas Chromatography-Mass Spectrometry Pseudotargeted Metabolomics Combined with Chemometrics

The quality of crops is closely associated with their geographical location and yield, which is reflected in the composition of their metabolites. Hence, we employed GC-MS pseudotargeted metabolomics to investigate the metabolic characteristics of high-, medium-, and low-yield Nicotiana tabacum (tobacco) leaves from the Bozhou (sweet honey flavour) and Shuicheng (light flavour) regions of Guizhou Province. A total of 124 metabolites were identified and classified into 22 chemical categories. Principal component analysis revealed that the geographical location exerted a greater influence on the metabolic profiling than the yield. Light-flavoured tobacco exhibited increased levels of sugar metabolism- and glycolysis-related intermediate products (trehalose, glucose-6-phosphate, and fructose-6-phosphate) and a few amino acids (proline and leucine), while sweet honey-flavoured tobacco exhibited increases in the tricarboxylic acid cycle (TCA cycle) and the phenylpropane metabolic pathway (p-hydroxybenzoic acid, caffeic acid, and maleic acid). Additionally, metabolite pathway enrichment analysis conducted at different yields and showed that both Shuicheng and Bozhou exhibited changes in six pathways and four of them were the same, mainly C/N metabolism. Metabolic pathway analysis revealed higher levels of intermediates related to glycolysis and sugar, amino acid, and alkaloid metabolism in the high-yield samples, while higher levels of phenylpropane in the low-yield samples. This study demonstrated that GC-MS pseudotargeted metabolomics-based metabolic profiling can be used to effectively discriminate tobacco leaves from different geographical locations and yields, thus facilitating a better understanding of the relationship between metabolites, yield, and geographical location. Consequently, metabolic profiles can serve as valuable indicators for characterizing tobacco yield and geographical location.

Phytoprostanes and phytofurans: Bioactive compounds in aerial parts of Acacia cyanophylla Lindl

The relevance of oxylipins as biomarkers of oxidative stress has been established in recent years. Phytoprostanes and phytofurans are plant metabolites derived from peroxidation of α-linolenic acid (ALA) induced by ROS. Previous findings have suggested new valuable biological properties for these new active compounds in the frame of diverse pathophysiological situations and health constraints. Lipidomic profiling of different aerial parts of the same Acacia cyanophylla Lindl. specimen, was evaluated for the first time here, using LC-MS/MS technology. Analysis revealed the existence of six PhytoPs and three PhytoFs. Stems have the highest amount of these metabolites with 179.35 ng/g and 320.79 ng/g respectively. This first complete profile paves the way to explore Acacia cyanophylla Lindl. as a source of plant oxylipins for therapeutic or pharmaceutical uses.

Metabolome of flue-cured tobacco is significantly affected by the presence of leaf stem

BACKGROUND

Leaves of tobacco (Nicotiana tabacum L.) are flue-cured to use as a key industrial supply in various parts of the world. The quality of tobacco leaves is dependent on chemical components and their proportions. Generally, the stem attached to tobacco leaf is detached before curing. However, the leaf stem remains green for an extended period of time (as compared to leaf) during flue-curing. Hence, it is expected to affect the quality of tobacco's final product.

RESULTS

To understand the impact of the green stem of leaf on the metabolome of flue-cured tobacco, we employed a broad targeted metabolomics approach. We selected two tobacco cultivars (Yun87 and K326) and cultivated them in five geographic locations in China. For flue-curing, leaves were harvested without a stem (L) or with an attached stem (SPL). After metabolome analysis, a total of 1027 metabolites were annotated in these samples. A variable number of metabolites were differentially accumulated between both types of leaves (depending on geographic location or cultivar) representing an influence of environment or genotype. Interestingly, only 68 metabolites were differentially accumulated between L and SPL samples irrespective of the cultivar or geographic location. These differentially accumulated metabolites belonged to major groups of primary and secondary metabolites. We have discussed the importance of identified metabolites in terms of carbon, nitrogen, and polyphenolic metabolism.

CONCLUSION

The present research is the first comprehensive description of several metabolites in tobacco leaves related to the contribution of leaf stem. The current study opens novel prospects for investigating the potential of such metabolites in improving the quality of flue-cured tobacco.

Identification of the key metabolites and related genes network modules highly associated with the nutrients and taste components among different Pepino (Solanum muricatum) cultivars

There is considerable knowledge about plant compounds that produce flavor, scent, and aroma. Aside from the similarities, however, groups of plant-produced nutrients and taste components have little in common with each other. Network analysis holds promise for metabolic gene discovery, which is especially important in plant systems where metabolic networks are not yet fully resolved. To bridge this gap, we propose a joint model of gene regulation and metabolic reactions in two different pepino varieties. Differential metabolomics analysis is carried out for detection of eventual interaction of compound. We adopted a multi-omics approach to profile the transcriptome and metabolome analyze differences in phenolic acids, flavonoids, organic acids, lipids, alkaloids, and sugars between LOF and SRF. The two most predominant classes of metabolites are phenolic acids and lipids in pepino. Overall results show enrichment in most DEGs was carbohydrate and biosynthesis of secondary metabolites pathway. Results of DEMs predominantly comprised N-p-coumaroyl agmatine and tryptamine, and significant differences were observed in their expression between LOF and SRF. Integrated DEMs and DEGs specific networks were constructed by combining two types of networks: transcriptional regulatory networks composed of interactions between DEMs and the regulated genes, and pepino metabolite-metabolite interaction networks. Newly discovered features, such as DEGs (USPA, UBE2 and DELLA) involved in the production of secondary metabolites are found in coregulated gene clusters. Moreover, lipid metabolites were most involved in DEMs correlations by OPLS-DA while identifying a significant number of DEGs co-regulated by SENP1, HMGCS et al. These results further that the metabolite discrepancies result from characterized the nutrients and taste components between two pepino genotype. Among the possible causes of the differences between species in pepino metabolite concentrations is co-regulated by these DEGs, continue to suggest that novel features of metabolite biosynthetic pathway remain to be uncovered. Finally, the integrated metabolome and transcriptome analyses have revealed that many important metabolic pathways are regulated at the transcriptional level. The metabolites content differences observed among varieties of the same species mainly originates from different regulated genes and enzymes expression. Overall, this study provides new insights into the underlying causes of differences in the plant metabolites and suggests that genetic data can be used to improve its nutrients and taste components.

Nitrogen application and differences in leaf number retained after topping affect the tobacco (Nicotiana tabacum) transcriptome and metabolome

BACKGROUND

Agronomic treatments such as the application of nitrogen fertilizer and topping (removal of the inflorescence and top leaves) cause substantial changes in plant metabolism. To explore these changes, we conducted comparative transcriptomic and metabolomic analyses of leaves collected from four positions along the stem on plants exposed to two nitrogen doses and with different numbers of leaves retained after topping in tobacco (Nicotiana tabacum).

RESULTS

We identified 13,330 unique differentially expressed genes and 32 differentially abundant metabolites. Through RNA-seq and WGCNA analyze, we constructed 2 co-expression networks (green and blue) highly correlation to N application and leaf number retained, predicted a hub gene NtGER3 may play an important role in N metabolism related to amino acid (cysteine) through CK pathway in tobacco leaves, NtARFs may participated in modulating the auxin signal and N in bottom leaves and NtRAP2.12 as key gene involved in N regulation by ethylene pathway. What's more, our data prove C/N transformation and balance affect the "source - flow - sink" redistribution and remobilization in tobacco during growth and development process.

CONCLUSIONS

Overall, this comparative transcriptomics study provides novel insight into the complex molecular mechanisms underlying plant responses to different levels of nitrogen application and the number of leaves remaining after topping in plants.

Geographic and position-based variations in phyllospheric bacterial communities present on flue-cured tobacco

Although tobacco leaves (TLs) contain abundant bacteria, how the geography and leaf position of TLs affect these bacteria is unclear. Here, TLs at different positions from Henan (HN, strong flavor style) and Yunnan (YN, fresh flavor style) provinces were collected, and the bacteria were characterized by Illumina sequencing at harvest and 1 year of storage. Bacterial communities were very different between TLs originating from different geographical areas and positions, and beta diversity analysis showed that leaf position was the most important factor for phyllospheric bacterial communities, followed by geographical area and storage time. At the genus level, Subdoligranulum, Thermus, and Acinetobacter were obviously more abundant in HN than in YN, while Blautia and Ruminococcus were significantly more abundant in YN. These differences in bacterial communities decreased after 1 year of storage, indicating that the microbiota tends to become similar during tobacco processing. Storage time also affected the phyllospheric bacteria of TLs, as the bacterial communities shifted significantly on both HN and YN TLs after 1 year of storage. Significant differences in the predicted genes were also observed between the different geographic locations and leaf positions. Potential human pathogens, including Acinetobacter, Methylobacterium, and Escherichia-Shigella, were greatly different between TLs originating from different areas and positions. These data suggested that geographic variations and positions were associated with phyllospheric bacterial communities on TLs, which may be related to not only the flavor style and quality of TLs but also the potential health risks to humans. KEY POINTS: • Tobacco leaf position and tobacco growth location affected bacterial communities. • Microbial communities of TLs shifted significantly after one year of storage. • Potential human pathogens differed at different leaf positions and growth locations.

Chromatographic Profiling with Machine Learning Discriminates the Maturity Grades of Nicotiana tabacum L. Leaves

Nicotiana tabacum L. (NTL) is an important agricultural and economical crop. Its maturity is one of the key factors affecting its quality. Traditionally, maturity is discriminated visually by humans, which is subjective and empirical. In this study, we concentrated on detecting as many compounds as possible in NTL leaves from different maturity grades using ultra-performance liquid chromatography ion trap time-of-flight mass spectrometry (UPLC-IT-TOF/MS). Then, the low-dimensional embedding of LC-MS dataset by t-distributed stochastic neighbor embedding (t-SNE) clearly showed the separation of the leaves from different maturity grades. The discriminant models between different maturity grades were established using orthogonal partial least squares discriminant analysis (OPLS-DA). The quality metrics of the models are R2Y = 0.939 and Q2 = 0.742 (unripe and ripe), R2Y = 0.900 and Q2 = 0.847 (overripe and ripe), and R2Y = 0.972 and Q2 = 0.930 (overripe and unripe). The differential metabolites were screened by their variable importance in projection (VIP) and p-Values. The existing tandem mass spectrometry library of plant metabolites, the user-defined library of structures, and MS-FINDER were combined to identify these metabolites. A total of 49 compounds were identified, including 12 amines, 14 lipids, 10 phenols, and 13 others. The results can be used to discriminate the maturity grades of the leaves and ensure their quality.

Characterization and functional analysis of phytoene synthase gene family in tobacco

BACKGROUND

Carotenoids play important roles in photosynthesis, hormone signaling, and secondary metabolism. Phytoene synthase (PSY) catalyzes the first step of the carotenoid biosynthetic pathway. In this study, we aimed to characterize the PSY genes in tobacco and analyze their function.

RESULTS

In this study, we identified three groups of PSY genes, namely PSY1, PSY2, and PSY3, in four Nicotiana species; phylogenetic analysis indicated that these genes shared a high similarity with those in tomato but not with those in monocots such as rice and maize. The expression levels of PSY1 and PSY2 were observed to be highest in leaves compared to other tissues, and they could be elevated by treatment with certain phytohormones and exposure to strong light. No PSY3 expression was detected under these conditions. We constructed virus-induced PSY1 and PSY2 silencing in tobacco and found that the newly emerged leaves in these plants were characterized by severe bleaching and markedly decreased carotenoid and chlorophyll content. Thylakoid membrane protein complex levels in the gene-silenced plants were also less than those in the control plants. The chlorophyll fluorescence parameters such as Fv/Fm, ΦPSII, qP, and NPQ, which reflect photosynthetic system activities, of the gene-silenced plants were also significantly decreased. We further performed RNA-Seq and metabonomics analysis between gene-silenced tobacco and control plants. RNA-Seq results showed that abiotic stress, isoprenoid compounds, and amino acid catabolic processes were upregulated, whereas the biosynthesis of cell wall components was downregulated. Metabolic analysis results were consistent with the RNA-Seq. We also found the downstream genes in carotenoid biosynthesis pathways were upregulated, and putative transcription factors that regulate carotenoid biosynthesis were identified.

CONCLUSIONS

Our results suggest that PSY can regulate carotenoid contents not only by controlling the first biosynthesis step but also by exerting effects on the expression of downstream genes, which would thereby affect photosynthetic activity. Meanwhile, PSY may affect other processes such as amino acid catabolism and cell wall organization. The information we report here may aid further research on PSY genes and carotenoid biosynthesis.

Comparative transcriptome and metabolomic profiling reveal the complex mechanisms underlying the developmental dynamics of tobacco leaves

Although the leaf is the most important photosynthetic organ in most plants, many of the molecular mechanisms underlying leaf developmental dynamics remain to be explored. To better understand the transcriptional regulatory mechanisms involved in leaf development, we conducted comparative transcriptomic and metabolomic analysis of leaves from seven positions on tobacco (Nicotiana tabacum) plants. A total of 35,622 unique differentially expressed genes and 79 metabolites were identified. A time-series expression analysis detected two interesting transcriptional profiles, one comprising 10,197 genes that displayed continual up-regulation during leaf development and another comprising 4696 genes that displayed continual down-regulation. Combining these data with co-expression network results identified four important regulatory networks involved in photorespiration and the tricarboxylic acid cycle; these networks may regulate carbon/nitrogen balance during leaf development. We also found that the transcription factor NtGATA5 acts as a hub associated with C and N metabolism and chloroplast development during leaf development through regulation of phytohormones. Furthermore, we investigated the transcriptional dynamics of genes involved in the auxin, cytokinin, and jasmonic acid biosynthesis and signaling pathways during tobacco leaf development. Overall, our study greatly expands the understanding of the regulatory network controlling developmental dynamics in plant leaves.

Development of a plasma pseudotargeted metabolomics method based on ultra-high-performance liquid chromatography-mass spectrometry

Untargeted methods are typically used in the detection and discovery of small organic compounds in metabolomics research, and ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) is one of the most commonly used platforms for untargeted metabolomics. Although they are non-biased and have high coverage, untargeted approaches suffer from unsatisfying repeatability and a requirement for complex data processing. Targeted metabolomics based on triple-quadrupole mass spectrometry (TQMS) could be a complementary tool because of its high sensitivity, high specificity and excellent quantification ability. However, it is usually applicable to known compounds: compounds whose identities are known and/or are expected to be present in the analyzed samples. Pseudotargeted metabolomics merges the advantages of untargeted and targeted metabolomics and can act as an alternative to the untargeted method. Here, we describe a detailed protocol of pseudotargeted metabolomics using UHPLC-TQMS. An in-depth, untargeted metabolomics experiment involving multiple UHPLC-HRMS runs with MS at different collision energies (both positive and negative) is performed using a mixture obtained using small amounts of the analyzed samples. XCMS, CAMERA and Multiple Reaction Monitoring (MRM)-Ion Pair Finder are used to find and annotate peaks and choose transitions that will be used to analyze the real samples. A set of internal standards is used to correct for variations in retention time. High coverage and high-performance quantitative analysis can be realized. The entire protocol takes ~5 d to complete and enables the simultaneously semiquantitative analysis of 800-1,300 metabolites.

Integrating transcriptome and metabolome reveals molecular networks involved in genetic and environmental variation in tobacco

Tobacco (Nicotiana tabacum) is one of the most widely cultivated commercial non-food crops with significant social and economic impacts. Here we profiled transcriptome and metabolome from 54 tobacco samples (2-3 replicates; n = 151 in total) collected from three varieties (i.e. genetic factor), three locations (i.e. environmental factor), and six developmental stages (i.e. developmental process). We identified 3,405 differentially expressed (DE) genes (DEGs) and 371 DE metabolites, respectively. We used quantitative real-time PCR to validate 20 DEGs, and confirmed 18/20 (90%) DEGs between three locations and 16/20 (80%) with the same trend across developmental stages. We then constructed nine co-expression gene modules and four co-expression metabolite modules , and defined seven de novo regulatory networks, including nicotine- and carotenoid-related regulatory networks. A novel two-way Pearson correlation approach was further proposed to integrate co-expression gene and metabolite modules to identify joint gene-metabolite relations. Finally, we further integrated DE and network results to prioritize genes by its functional importance and identified a top-ranked novel gene, LOC107773232, as a potential regulator involved in the carotenoid metabolism pathway. Thus, the results and systems-biology approaches provide a new avenue to understand the molecular mechanisms underlying complex genetic and environmental perturbations in tobacco.

The roles of metabolic pathways in maintaining primary dormancy of Pinus koraiensis seeds

BACKGROUND

Korean pine seeds have primary dormancy following dispersal, leading to poor seed germination and seedling establishment. Metabolic homeostasis determines whether the seeds are dormant or non-dormant. However, the specific metabolic pathways that maintain the primary dormancy of pine seeds are poorly understood.

RESULTS

Metabolic analysis was employed on the embryos of PDRS (seeds released from primary dormancy) and PDS (primary dormant seeds) on days 0, 5 and 11 after incubation under a germination-inductive temperature. A larger metabolic switch occurred in PDRS embryos from days 0 to 11. The contents of ninety metabolites were significantly changed from days 0 to 5, 83% of which (including most sugars, organic acids and amino acids) increased, reflecting that biosynthetic metabolism processes are initiated. The contents of ninety-two metabolites showed distinct variations from days 5 to 11, 71% of which (including most organic acids and almost all amino acids) reduced substantially. Fructose 6-phosphate, inositol-3-phosphate, 3-phosphoglyceric and D-glucose-6-phosphate contents showed the most decrease with decreasing 409-, 75-, 58- and 41-fold, indicating that the glycolysis and tricarboxylic acid (TCA) cycle strongly slowed down. The contents of the most metabolites in PDS embryos also displayed a relatively larger alteration only from days 0 to 5. Although 64% of metabolites increased from days 0 to 5, their levels were still lower compared with PDRS embryos. Furthermore, most metabolites were not further accumulated from days 5 to 11. Unlike PDRS embryos, almost all amino acids in PDS embryos did not exhibit a substantial decrease from days 5 to 11. Also, there was not a major decrease in the levels of metabolites involved mainly in glycolysis and TCA cycle, while some intermediates even increased.

CONCLUSIONS

The attenuated biosynthetic metabolism processes, the lower utilization rate of amino acids and the higher operation rate of glycolysis and TCA in embryos maintain primary dormancy.

Metabolic responses ofSaccharomyces cerevisiaeto ethanol stress using gas chromatography-mass spectrometry

Metabolic responses ofSaccharomyces cerevisiaeunder ethanol stress by a metabolomics method based on GC-MS.

Metabolic profiles of Cuibi-1 and Zhongyan-100 flue-cured tobacco leaves in different growing regions by gas chromatography/mass spectrometry

The metabolic profiles of tobacco leaves of two differential Chinese cultivars from different growing regions were analysed using gas chromatography-mass spectrometry (GC-MS). The results of principal component analysis, partial least-squares discriminant analysis and hierarchical cluster analysis showed significant differences in metabolome among three groups, identified 24 differential metabolites, and analysed the metabolic pathway in which the metabolites were involved. Among them, 13 metabolites were associated with geographical regions, including seven organic and fatty acids, four carbohydrates and two secondary metabolites. Four amino acids and two monosaccharides were associated with cultivars and the remaining five metabolites were associated with both. The relationships among the differential metabolites and the distinct characteristics of environment and cultivar were further discussed. In addition, correlation analysis indicated that most of the differential carbohydrates were negatively correlated with the differential amino acids and organic acids. Taken together, this study demonstrates the metabolite differences between two cultivars in different regions, and highlights the effect of environment and cultivar on tobacco leaf metabolism.

Metabolic changes in primary, secondary, and lipid metabolism in tobacco leaf in response to topping

As an important cultivation practice used for flue-cured tobacco, topping affects diverse biological processes in the later stages of development and growth. Some studies have focused on using tobacco genes to reflect the physiological changes caused by topping. However, the complex metabolic shifts in the leaf resulting from topping have not yet been investigated in detail. In this study, a comprehensive metabolic profile of primary, secondary, and lipid metabolism in flue-cured tobacco leaf was generated with use of a multiple platform consisting of gas chromatography-mass spectrometry, capillary electrophoresis-mass spectrometry, and liquid chromatography-mass spectrometry/ultraviolet spectroscopy. A total of 367 metabolites were identified and determined. Both principal component analysis and the number of significantly different metabolites indicated that topping had the greatest influence on the upper leaves. During the early stage of topping, great lipid level variations in the upper leaves were observed, and antioxidant defense metabolites were accumulated. This indicated that the topping activated lipid turnover and the antioxidant defense system. At the mature stage, lower levels of senescence-related metabolites and higher levels of secondary metabolites were found in the topped mature leaves. This implied that topping delayed leaf senescence and promoted secondary metabolite accumulation. This study provides a global view of the metabolic perturbation in response to topping. Graphical abstract Metabolic alterations in tobacco leaf in response to topping using a multiplatform metabolomics.

Discovery and validation of potential urinary biomarkers for bladder cancer diagnosis using a pseudotargeted GC-MS metabolomics method

Bladder cancer (BC) is the second most prevalent malignancy in the urinary system and is associated with significant mortality; thus, there is an urgent need for novel noninvasive diagnostic biomarkers. A urinary pseudotargeted method based on gas chromatography-mass spectrometry was developed and validated for a BC metabolomics study. The method exhibited good repeatability, intraday and interday precision, linearity and metabolome coverage. A total of 76 differential metabolites were defined in the discovery sample set, 58 of which were verified using an independent validation urine set. The verified differential metabolites revealed that energy metabolism, anabolic metabolism and cell redox states were disordered in BC. Based on a binary logistic regression analysis, a four-biomarker panel was defined for the diagnosis of BC. The area under the receiving operator characteristic curve was 0.885 with 88.0% sensitivity and 85.7% specificity in the discovery set and 0.804 with 78.0% sensitivity and 70.3% specificity in the validation set. The combinatorial biomarker panel was also useful for the early diagnosis of BC. This approach can be used to discriminate non-muscle invasive and low-grade BCs from healthy controls with satisfactory sensitivity and specificity. The results show that the developed urinary metabolomics method can be employed to effectively screen noninvasive biomarkers.

Influences of Normalization Method on Biomarker Discovery in Gas Chromatography-Mass Spectrometry-Based Untargeted Metabolomics: What Should Be Considered?

Data reduction techniques in gas chromatography-mass spectrometry-based untargeted metabolomics has made the following workflow of data analysis more lucid. However, the normalization process still perplexes researchers, and its effects are always ignored. In order to reveal the influences of normalization method, five representative normalization methods (mass spectrometry total useful signal, median, probabilistic quotient normalization, remove unwanted variation-random, and systematic ratio normalization) were compared in three real data sets with different types. First, data reduction techniques were used to refine the original data. Then, quality control samples and relative log abundance plots were utilized to evaluate the unwanted variations and the efficiencies of normalization process. Furthermore, the potential biomarkers which were screened out by the Mann-Whitney U test, receiver operating characteristic curve analysis, random forest, and feature selection algorithm Boruta in different normalized data sets were compared. The results indicated the determination of the normalization method was difficult because the commonly accepted rules were easy to fulfill but different normalization methods had unforeseen influences on both the kind and number of potential biomarkers. Lastly, an integrated strategy for normalization method selection was recommended.

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

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

The development of plasma pseudotargeted GC-MS metabolic profiling and its application in bladder cancer

Bladder cancer (BC) is a fatal malignancy with considerable mortality. BC urinary metabolomics has been extensively investigated for biomarker discovery, but few BC blood metabolomic studies have been performed. Hence, a plasma pseudotargeted metabolomic method based on gas chromatography-mass spectrometry with selected ion monitoring (GC-MS-SIM) was developed to study metabolic alterations in BC. The analytical performance of the developed method was compared with that of a nontargeted method. The relative standard deviation (RSD) values of 89 and 70.7 % of the peaks obtained using the pseudotargeted and nontargeted methods, respectively, were less than 20 %. The Pearson correlations of 90.7 and 78.3 % of the peaks obtained using the pseudotargeted and nontargeted methods, respectively, exceeded 0.90 in the linearity evaluation. Compared with the nontargeted method, the signal-to-noise ratios (S/N) of 97.9 and 69.3 % of the peaks increased two- and fivefold, respectively. The developed method was fully validated, with good precision, recovery, and stability of the trimethylsilyl (TMS) derivatives. The method was applied to investigate BC. Significant increases in the contents of metabolites involved in, for example, the pentose phosphate pathway (PPP) and nucleotide and fatty acid synthesis were found in the high-grade (HG) BC group compared to the healthy control (HC) group. These differences imply that the activated PPP may regulate BC cell proliferation by promoting lipid and nucleotide biosynthesis and the detoxification of reactive oxygen species (ROS). These results illustrate that the plasma pseudotargeted method is a powerful tool for metabolic profiling. Graphical abstract The plasma pseudotargeted metabolic profiling suggested the metabolic alterations in bladder cancer (BC) and the significantly differential metabolites for BC discrimination.

Metabolic Profiling with Gas Chromatography-Mass Spectrometry and Capillary Electrophoresis-Mass Spectrometry Reveals the Carbon-Nitrogen Status of Tobacco Leaves Across Different Planting Areas

The interaction between carbon (C) and nitrogen (N) metabolism can reflect plant growth status and environmental factors. Little is known regarding the connections between C-N metabolism and growing regions under field conditions. To comprehensively investigate the relationship in mature tobacco leaves, we established metabolomics approaches based on gas chromatography-mass spectrometry (GC-MS) and capillary electrophoresis-time-of-flight-mass spectrometry (CE-TOF-MS). Approximately 240 polar metabolites were determined. Multivariate statistical analysis revealed that the growing region greatly influenced the metabolic profiles of tobacco leaves. A metabolic correlation network and related pathway maps were used to reveal the global overview of the alteration of C-N metabolism across three typical regions. In Yunnan, sugars and tricarboxylic acid (TCA) cycle intermediates were closely correlated with amino acid pools. Henan tobacco leaves showed positive correlation between the pentose phosphate pathway (PPP) intermediates and C-rich secondary metabolism. In Guizhou, the proline and asparagine had significant links with TCA cycle intermediates and urea cycle, and antioxidant accumulation was observed in response to drought. These results demonstrate that combined analytical approaches have great potential to detect polar metabolites and provide information on C-N metabolism related to planting regional characteristics.

A Novel Strategy for Large-Scale Metabolomics Study by Calibrating Gross and Systematic Errors in Gas Chromatography-Mass Spectrometry

Metabolomics is increasingly applied to discover and validate metabolite biomarkers and illuminate biological variations. Combination of multiple analytical batches in large-scale and long-term metabolomics is commonly utilized to generate robust metabolomics data, but gross and systematic errors are often observed. The appropriate calibration methods are required before statistical analyses. Here, we develop a novel correction strategy for large-scale and long-term metabolomics study, which could integrate metabolomics data from multiple batches and different instruments by calibrating gross and systematic errors. The gross error calibration method applied various statistical and fitting models of the feature ratios between two adjacent quality control (QC) samples to screen and calibrate outlier variables. Virtual QC of each sample was produced by a linear fitting model of the feature intensities between two neighboring QCs to obtain a correction factor and remove the systematic bias. The suggested method was applied to handle metabolic profiling data of 1197 plant samples in nine batches analyzed by two gas chromatography-mass spectrometry instruments. The method was evaluated by the relative standard deviations of all the detected peaks, the average Pearson correlation coefficients, and Euclidean distance of QCs and non-QC replicates. The results showed the established approach outperforms the commonly used internal standard correction and total intensity signal correction methods, it could be used to integrate the metabolomics data from multiple analytical batches and instruments, and it allows the frequency of QC to one injection of every 20 real samples. The suggested method makes a large amount of metabolomics analysis practicable.

A metabolomics study delineating geographical location-associated primary metabolic changes in the leaves of growing tobacco plants by GC-MS and CE-MS

Ecological conditions and developmental senescence significantly affect the physiological metabolism of plants, yet relatively little is known about the influence of geographical location on dynamic changes in plant leaves during growth. Pseudotargeted gas chromatography-selected ion monitoring-mass spectrometry and capillary electrophoresis-mass spectrometry were used to investigate a time course of the metabolic responses of tobacco leaves to geographical location. Principal component analysis revealed obvious metabolic discrimination between growing districts relative to cultivars. A complex carbon and nitrogen metabolic network was modulated by environmental factors during growth. When the Xuchang and Dali Districts in China were compared, the results indicated that higher rates of photosynthesis, photorespiration and respiration were utilized in Xuchang District to generate the energy and carbon skeletons needed for the biosynthesis of nitrogen-containing metabolites. The increased abundance of defense-associated metabolites generated from the shikimate-phenylpropanoid pathway in Xuchang relative to Dali was implicated in protection against stress.

Plant metabolite profiles and the buffering capacities of ecosystems

In spite of some inherent challenges, metabolite profiling is becoming increasingly popular under field conditions. It has been used successfully to address topics like species interactions, connections between growth and chemical stoichiometry or the plant's stress response. Stress exerts a particularly clear impact on plant metabolomes and has become a central topic in many metabolite profiling experiments in the fields. In contrast to phytochambers, however, external stress is often at least partially absorbed by the environment when measuring under field conditions. Such stress-buffering capacities of (agro)-ecosystems are of crucial interest given the ever-increasing anthropogenic impact on ecosystems and this review promotes the idea of using plant metabolite profiles for respective measurements. More specifically I propose to use parameters of the response of key plant species to a given stress treatment as proxies for measuring and comparing stress-buffering capacities of ecosystems. Stress response parameters accessible by metabolite profiling comprise for example the intensity or duration of the impact of stress or the ability of the plant organism to recover from this impact after a given time. Analyses of ecosystem stress-buffering capacities may improve our understanding of how ecosystems cope with stress and may improve our abilities to predict ecosystem changes.

Development of urinary pseudotargeted LC-MS-based metabolomics method and its application in hepatocellular carcinoma biomarker discovery

Hepatocellular carcinoma (HCC) is one of the pestilent malignancies leading to cancer-related death. Discovering effective biomarkers for HCC diagnosis is an urgent demand. To identify potential metabolite biomarkers, we developed a urinary pseudotargeted method based on liquid chromatography-hybrid triple quadrupole linear ion trap mass spectrometry (LC-QTRAP MS). Compared with nontargeted method, the pseudotargeted method can achieve better data quality, which benefits differential metabolites discovery. The established method was applied to cirrhosis (CIR) and HCC investigation. It was found that urinary nucleosides, bile acids, citric acid, and several amino acids were significantly changed in liver disease groups compared with the controls, featuring the dysregulation of purine metabolism, energy metabolism, and amino metabolism in liver diseases. Furthermore, some metabolites such as cyclic adenosine monophosphate, glutamine, and short- and medium-chain acylcarnitines were the differential metabolites of HCC and CIR. On the basis of binary logistic regression, butyrylcarnitine (carnitine C4:0) and hydantoin-5-propionic acid were defined as combinational markers to distinguish HCC from CIR. The area under curve was 0.786 and 0.773 for discovery stage and validation stage samples, respectively. These data show that the established pseudotargeted method is a complementary one of targeted and nontargeted methods for metabolomics study.

Study of metabolite differences of flue-cured tobacco from different regions using a pseudotargeted gas chromatography with mass spectrometry selected-ion monitoring method

A pseudotargeted method based on gas chromatography and mass spectrometry with selected-ion monitoring was established to investigate the metabolite differences of flue-cured tobacco from three different growing regions. The mixed solvent of acetonitrile/isopropanol/water (3:3:2, v/v/v) was chosen as the optimal extraction system based on the good repeatability and extraction efficiency. A self-developed software coupled with commercial software was used to establish the pseudotargeted method including 289 peaks and 47 groups. Multivariable statistical analysis indicated that tobacco samples can be obviously separated based on the geographical origins. On the basis of a Mann-Whitney U test, organic acids, phenols, and alkaloids had higher levels in Hunan province. In contrast, a large proportion of amino acids (including L-tyrosine, L-proline, and serine), sucrose, and linoleic acid were the highest in Yunnan province. Meanwhile, multiple metabolic pathways (including carbohydrate metabolism, tricarboxylic acid cycle, and nitrogen metabolism) were influenced by growing regions. Twenty-eight differential metabolites, which had great contributions to the classification of tobacco samples of three growing regions, were further defined. The results demonstrated that the developed pseudotargeted method was a powerful tool to investigate the metabolic profiling of tobacco leaves and discriminate tobacco leaves of different growing regions.