Jieyu Zhao

Discovery and Validation of Plasma Biomarkers for Major Depressive Disorder Classification Based on Liquid Chromatography–Mass Spectrometry

Major depressive disorder (MDD) is a debilitating mental disease with a pronounced impact on the quality of life of many people; however, it is still difficult to diagnose MDD accurately. In this study, a nontargeted metabolomics approach based on ultra-high-performance liquid chromatography equipped with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) was used to find the differential metabolites in plasma samples from patients with MDD and healthy controls. Furthermore, a validation analysis focusing on the differential metabolites was performed in another batch of samples using a targeted approach based on the dynamic multiple reactions monitoring method. Levels of acyl carnitines, ether lipids, and tryptophan pronouncedly decreased, whereas LPCs, LPEs, and PEs markedly increased in MDD subjects as compared with the healthy controls. Disturbed pathways, mainly located in acyl carnitine metabolism, lipid metabolism, and tryptophan metabolism, were clearly brought to light in MDD subjects. The binary logistic regression result showed that carnitine C10:1, PE-O 36:5, LPE 18:1 sn-2, and tryptophan can be used as a combinational biomarker to distinguish not only moderate but also severe MDD from healthy control with good sensitivity and specificity. Our findings, on one hand, provide critical insight into the pathological mechanism of MDD and, on the other hand, supply a combinational biomarker to aid the diagnosis of MDD in clinical usage.

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.

Study of polar metabolites in tobacco from different geographical origins by using capillary electrophoresis-mass spectrometry

Many metabolites in plant are highly polar and ionic. Their analysis using gas chromatography–mass spectrometry and liquid chromatography–mass spectrometry can be problematic. Therefore a capillary electrophoresis–mass spectrometry (CE–MS) method with charge-driven separation characteristic was developed to investigate polar metabolites in tobacco. To obtain as many features as possible, extraction of polar metabolites was optimized by the design of experiments and evaluated by univariate statistics. Method validation was carried out to evaluate the analytical characteristics including calibration curve, precision, sample stability and extraction reproducibility. The developed method was successfully applied in studying 30 tobacco leaves obtained from Yunnan and Guizhou provinces in China. A total of 154 polar metabolites were identified based on available database. Multivariate pattern recognition clearly revealed the metabolic differences between the two geographic areas and 43 significantly different metabolites were defined by the non-parametric hypothesis test (Mann–Whitney U test) and false discovery rate. Some key metabolites involved in photosynthesis such as ribulose 1,5-disphosphate, fructose 1,6-diphosphate, glycine, betaine, GABA and serine were found to be susceptible to environmental conditions. This study shows that the metabolic profiling based on CE–MS can clearly discriminate tobacco leaves of different geographical origins and understand the relationship between plant metabolites and their geographical origins.

Comprehensive investigation of tobacco leaves during natural early senescence via multi-platform metabolomics analyses

Senescence is the final stage of leaf growth and development. Many different physiological activities occur during this process. A comprehensive metabolomics analysis of tobacco middle leaves at 5 different developmental stages was implemented through multi-platform methods based on liquid chromatography, capillary electrophoresis and gas chromatography coupled with mass spectrometry. In total, 412 metabolites were identified, including pigments, sterols, lipids, amino acids, polyamines, sugars and secondary metabolites. Dramatic metabolic changes were observed. Firstly, membrane degradation and chlorophyll down-regulation occurred after the 50% flower bud stage. Levels of major membrane lipids decreased, including those of the glycolipids in chloroplast thylakoids and phospholipids in membrane envelopes. Clear decreases in free sterols and acylated sterol glucosides were detected along with the accumulation of sterol esters. The accumulation of alkaloids was found. The amino acid levels were significantly decreased, particularly those of N-rich amino acids (glutamine and asparagine), thus reflecting N translocation. Subsequently, the antioxidant system was activated. Sugar alcohols and polyphenols accumulated when the lower leaves turned yellow. These results comprehensively revealed the metabolic changes that occur during tobacco leaf development and senescence under natural conditions.

Metabolomics study of cured tobacco using liquid chromatography with mass spectrometry: method development and its application in investigating the chemical differences of tobacco from three growing regions.

Cured tobacco is an important plant material. Component studies are a big challenge for its significantly diverse chemical properties and vastly different concentrations. In this work, liquid chromatography with quadrupole time-of-flight mass spectrometry was used to perform a metabolomics study of cured tobacco owing to its efficient separation and detection of semipolar metabolites. A solvent of methanol/water (8:2, v/v) and 30 min of ultrasound time were found to be optimal to perform extraction. 95, 92, and 93% of metabolite features had within 20% of coefficient of variation for repeatability, intraday and interday precision analysis, respectively, indicating a good stability of the method developed. 113 metabolites were identified in cured tobacco based on accurate mass, retention time, and MS/MS fragments. The developed method was applied to a metabolomics study of cured tobacco from three growing regions. Forty three metabolites were found to be contributed to the classification. It is shown that the developed method can be applied to metabolomics analysis of plant materials.

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.

Sample-directed pseudotargeted method for the metabolic profiling analysis of rice seeds based on liquid chromatography with mass spectrometry.

Rice is one of the most important food crops in the world. Metabolite composition in rice seeds varies significantly depending on genetic variety, climatic alternation and agricultural practice. Metabolomics is a powerful tool to reveal the metabolic response of rice to various conditions. In this work, a rice seed sample-directed pseudotargeted metabolomics method was first established and validated based on ultra high performance liquid chromatography with triple quadrupole mass spectrometry in the multiple reaction monitoring mode. A total of 749 and 617 ion pairs in positive and negative modes were achieved, respectively. Among them, about 200 metabolites were identified or tentatively identified. The developed method showed better linearity and repeatability than those of non-targeted metabolomics method. Good intra-day and inter-day precisions, recoveries and wide linear range were also obtained. Furthermore, the method was applied for the investigation of metabolic variation of rice seeds with two wild cultivars and their transgenic lines that were grown in two locations. Principal component analysis indicated that the effects of cultivar and location on metabolic variations were far more than those of gene modification. The nonparametric Mann-Whitney U test revealed that most metabolites were influenced by cultivar, location and gene modifications together.

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

AbstractAs 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 abstractMetabolic alterations in tobacco leaf in response to topping using a multiplatform metabolomics

Metabolic responses of rice leaves and seeds under transgenic backcross breeding and pesticide stress by pseudotargeted metabolomics

Pesticide and anti-insect gene are two effective strategies to prevent insects from seriously influencing the growth and production of crops in agroecosystem. Few investigators have yet concerned the metabolic responses of different plant tissues to pesticide treatment and transgene with backcross breeding. In this study, the metabolic variations in samples of rice leaf and seed induced by transgenic backcross breeding and pesticide stress were investigated by a pseudotargeted metabolomics method based on gas chromatography–mass spectrometry. The results showed transgenic backcross breeding caused diverse metabolic changes for rice leaf and seed. Higher abundances of a wide range of carbohydrates, antioxidants and phenols were observed in transgenic backcross breeding leaves, while some amino acids and carbohydrates in rice seeds were down-regulated after transgenic backcross breeding. Moreover, the defense responses of rice leaves to pesticide stress were tightly associated with transgenic backcross breeding. Defense system accompanied with the accumulations of phenols and antioxidants was rapidly activated in non-transgenic parent compared to transgenic backcross breeding leaves under pesticide stress.