Co-reporter:Yanni Zhao;Chunxia Zhao;Huina Zhou;Yanli Li;Yuwei Chang;Jia Zhou;Junjie Zhang;Lifeng Jin;Fucheng Lin;Guowang Xu
Journal of Proteome Research November 1, 2013 Volume 12(Issue 11) pp:5072-5083
Publication Date(Web):2017-2-22
DOI:10.1021/pr400799a
An improved pseudotargeted method using gas chromatography/mass spectrometry (GC/MS) was developed to investigate the metabolic profile of tobacco leaves from three planting regions (Yunnan, Guizhou, and Henan provinces). The analytical characteristics of the method with regard to reproducibility, precision, linearity, and stability were satisfactory for metabolic profiling study. Partial least-squares-discriminant analysis and hierarchical cluster analysis demonstrated that the metabolic profiles of tobacco from the Yunnan and Guizhou regions were different from that from the Henan province. The amino acid (e.g., phenylalanine, leucine, and tyrosine) and carbohydrate (e.g., fructose, trehalose, and sucrose) contents were the highest in Henan tobacco. The highest contents of organic acids (e.g., isocitrate, citrate, and fumarate) of the TCA cycle and antioxidants (e.g., quinate, chlorogenic acid, and ascorbate) were found in Guizhou tobacco. The correlation coefficients between metabolite content and climate factors (rainfall, sunshine, and temperature) demonstrated that drought facilitated the accumulation of sugars and amino acids. The content of TCA cycle intermediates could be influenced by multiple climate factors. This study demonstrates that the pseudotargeted method with GC/MS is suitable for the investigation of the metabolic profiling of tobacco leaves and the assessment of differential metabolite levels related to the growing regions.Keywords: climate; GC/MS; metabolic profiling; metabolomics; pseudotargeted; tobacco leaf;
Co-reporter:Lili Li, Weijie Ren, Hongwei Kong, Chunxia Zhao, Xinjie Zhao, Xiaohui Lin, Xin Lu, Guowang Xu
Analytica Chimica Acta 2017 Volume 990(Volume 990) pp:
Publication Date(Web):16 October 2017
DOI:10.1016/j.aca.2017.07.058
•A MS/MS-based peak alignment method for LC-MS metabolomics data was developed.•A rigorous strategy for screening endogenous reference variables was proposed.•MS/MS data were used to screen rigorous endogenous reference variables and in further peak alignment.•The developed method had good performance, especially for metabolomics data with larger retention time drift.Liquid chromatography-mass spectrometry (LC-MS) is an important analytical platform for metabolomics study. Peak alignment of metabolomics dataset is one of the keys for a successful metabolomics study. In this work, a MS/MS-based peak alignment method for LC-MS metabolomics data was developed. A rigorous strategy for screening endogenous reference variables was proposed. Firstly, candidate endogenous reference variables were selected based on MS, MS/MS and retention time in all samples. Multiple robust endogenous reference variables were obtained through further evaluation and confirmation. Then retention time of each metabolite feature was corrected by local linear regression using the four nearest neighbor robust reference variables. Finally, peak alignment was carried out based on corrected retention time, MS and MS/MS. Comparing with the other two peak alignment methods, the developed method showed a good performance and was suitable for metabolomics data with larger retention time drift. Our approach provides a simple and robust alignment method which is reliable to align LC-MS metabolomics dataset.Download high-res image (275KB)Download full-size image
Co-reporter:Yanni Zhao, Zhiqiang Hao, Chunxia Zhao, Jieyu Zhao, Junjie Zhang, Yanli Li, Lili Li, Xin Huang, Xiaohui Lin, Zhongda Zeng, Xin Lu, and Guowang Xu
Analytical Chemistry 2016 Volume 88(Issue 4) pp:2234
Publication Date(Web):January 12, 2016
DOI:10.1021/acs.analchem.5b03912
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.
Co-reporter:Jieyu Zhao; Yanni Zhao; Chunxiu Hu; Chunxia Zhao; Junjie Zhang; Lili Li; Jun Zeng; Xiaojun Peng; Xin Lu;Guowang Xu
Journal of Proteome Research 2016 Volume 15(Issue 2) pp:468-476
Publication Date(Web):January 19, 2016
DOI:10.1021/acs.jproteome.5b00807
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.
Co-reporter:Yanni Zhao;Chunxia Zhao;Yanli Li;Yuwei Chang;Junjie Zhang;Zhongda Zeng;Guowang Xu
Journal of Separation Science 2014 Volume 37( Issue 16) pp:2177-2184
Publication Date(Web):
DOI:10.1002/jssc.201400097
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.
Co-reporter:Yong Li;Tao Pang;Yanli Li;Guozhu Ye;Guowang Xu
Journal of Separation Science 2013 Volume 36( Issue 9-10) pp:1545-1552
Publication Date(Web):
DOI:10.1002/jssc.201201037
A “ppseudo” targeted method using GC-MS-selected ions monitoring was applied to investigate the chemical characteristics of commercial cigarettes made in China and foreign countries. To identify the components and define the quantative ions for SIM acquisition, a quality control sample was analyzed using GC-MS full scan. Acquired data were treated with a homemade software. A peak table with 312 components and their related quantitation ions was achieved for SIM acquisition. Structure elucidation was performed using library searching, retention index, standard compounds, and fitted retention time. The fitted retention time was calculated by a linear correction curve obtained using measured and library retention time to verify compounds. A total of 90 compounds were elucidated. Chemical characteristics of different cigarette brands were investigated. The data acquisition was carried out in SIM mode. The principal component and the hierarchical clustering analyses showed that the Chinese domestic flue-cured cigarettes were significantly different from the domestic blended, the foreign flue-cured, and blended cigarettes. Sixty-seven differential compounds were defined using the nonparametric Mann–Whitney test and the group blending samples comparison. Chinese domestic flue-cured cigarettes have higher concentration of saccharides and lower concentration of organic acids and amino acids.
Co-reporter:Junjie Zhang;Chunxia Zhao;Yuwei Chang;Yanni Zhao;Qinghua Li;Guowang Xu
Journal of Separation Science 2013 Volume 36( Issue 17) pp:2868-2877
Publication Date(Web):
DOI:10.1002/jssc.201300450
Amino acids are one of the most important metabolites of organisms. They play an important role in plant growth, development, and product quality. A method based on RP ultra-performance LC with single quadrupole MS and 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate precolumn derivatization was developed for the analysis of free amino acids in flue-cured tobacco leaves. Unlike the corresponding UV detection method, this method avoids matrix interference of complicated tobacco components, and the quantitative accuracy and resolution were improved. Twenty free amino acids were detected in flue-cured tobacco leaves. The method showed a good linearity with correlation coefficients of 0.9966–0.9998. The LODs for derivatized amino acids were 0.2–9.7 fmol/μL. Good repeatability with an RSD of 2.5–8.6% and satisfactory intra- and interday precisions were obtained. The developed method was used to investigate free amino acids in flue-cured tobacco leaves in China. The effects of aroma type, variety, and growing regions on free amino acids were investigated. The results showed that free amino acids in tobacco were affected by growing regions and varieties.