A systematic approach to determine the impact of elevated CO2 levels on the chemical composition of wheat (Triticum aestivum)

Two wheat genetic lines (responsive and non-responsive to elevated CO₂) grown under ambient and free-air CO₂ enrichment (FACE) conditions were compared using fuzzy chromatography mass spectrometry (FCMS) metabolite fingerprinting. A more comprehensive survey of the changes in their chemical composition was made on selected samples using ultra-high-performance liquid chromatography (UHPLC) metabolomic profiling with high resolution accurate mass/tandem mass spectrometry (HRAM/MSⁿ). Principal component analysis (PCA) of the metabolite fingerprints showed four clusters for the two genetic lines (responsive and non-responsive) and the two CO₂ levels (ambient and elevated) in score plots. Metabolite profiling of representative samples for each of the four clusters identified 25 and 16 compounds from negative and positive data, respectively, including amino acids, saccharides, phenolic acids, flavonoids, and lipids. Loading plots demonstrated that some saccharides and lipids were responsible for discriminating between not only two genetic lines but also two CO₂ levels. Analysis of free amino acids (not bound) showed a clear pattern of reduced concentration for both lines with elevated CO₂. After acid hydrolysis, the responsive line 6 (41% increase in yield) showed the same pattern observed for free amino acids, but the non-responsive line 5 (6% increase in yield) showed different trends in concentrations of amino acids with elevated CO₂.     

Effects of PM2.5 on metabolic pathways based on metabolomics

As one of the common air pollutants, fine particulate matter/particulate matter 2.5 (PM_2.5) is an important risk factor affecting human health. Many epidemiological studies have shown that PM_2.5 increases the risk of various diseases. However, its underlying biological mechanisms have not been well understood. Metabolomics is an emerging field that has been used to identify the metabolic pathways involved in pathogenesis by analyzing changes in metabolite levels for disease diagnosis and treatment development. Many metabolomics-based studies have shown that the pathophysiological changes caused by PM_2.5 exposure may involve disturbances in various metabolites and metabolic pathways. In this paper, a brief review of the research progress of the effects of PM_2.5 on the metabolic pathways using metabolomics is presented.     

Preliminary study of patients with chronic mountain sickness by GC-TOF-MS based serum metabolomics analysis

AIM: To evaluate specific metabolomics profiles in the serum of patients with chronic mountain sickness (CMS) and to explore the potential metabolic biomarkers in the native Tibetans living on the Qinghai-Tibet Pla-teau.METHODS: A gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) approach as a metabolomics technique was used to evaluate metabolic differences. The native Tibetan CMS patients (n=10) and healthy Tibetan controls (n=10) were enrolled from YuShu in Qinghai province in this study. The serum samples were collected and analyzed by GC-TOF-MS coupled with a series of multivariate statistical analyses such as principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA).RESULTS: The intergroup differences between CMS patients and control subjects have been observed. A list of differential metabolites and several top altered metabolic pathways have been identified. The levels of fumaric acid, an intermediate in the tricarboxylic acid (TCA) cycle, and inosine were highly upregulated in the CMS patients, suggesting a greater effort to hypoxic adaptation in high elevation area. Other differential metabolites, such as methyl phosphate, 2-ketoadipate, lyxose and phytanic acid were also identified. Importantly, the differential metabolites possessed higher area under the ROC curve (AUC) values, indicating an excellent clinical ability for the prediction of CMS. Increased levels of amino acids (isoleucine, glycine, serine, L-cysteine, citrulline and trimethyllysine) were detected in CMS group, yet significantly decreased levels of sulfuric acid, oxamic acid, lyxose and glutamine were also detected in CMS group than those in control group. At the same time, the levels of ribose and glucose-1-phosphate were markedly elevated in CMS group (P<0.05).CONCLUSION: The metabolic activities are significantly altered in the serum of CMS patients. High altitude hypoxia may act on the disturbed glucose metabolism and amino acid metabolism in part of the Tibetan triggered by CMS.     

Where systems biology meets postharvest

According to the dictionary, a system is something like “a group or combination of interrelated, interdependent, or interacting elements forming a collective entity”. In postharvest, fresh harvested food crops can be considered isolated small scale systems. Postharvest research aims to understand the quality of these ‘systems’ as influenced by postharvest conditions. The phenotypic quality of horticultural produce is based on genetic traits that are expressed through a cascade of reactions subject to complex regulatory mechanisms and diverse environmental conditions. Ultimately, to fully understand postharvest phenomena, a systemic approach that links genetic and environmental responses and identifies the underlying biological networks is required. Thanks to the development of high throughput omics techniques such system-wide approaches have become a viable option to support traditional postharvest research. This review provides an overview of systems biology and how it can lead postharvest research into a new era.     

From classical taxonomy to genome and metabolome: towards comprehensive quality standards for medicinal herb raw materials and extracts

Fundamental to herbal medicine quality is the use of 'authentic' medicinal herb species. Species, however, 'represent more or less arbitrary and subjective man-made units'. Against this background, we discuss, with illustrative examples, the importance of defining species boundaries by accommodating both the fixed (shared) diagnostic and varying (within-species) traits in medicinal herb populations. We emphasize the role of taxonomy, floristic information and genomic profiling in authenticating medicinal herb species, in addition to the need to include within species phytochemical profile variations while developing herbal extract identification protocols. We outline the application of species-specific genomic and phytochemical markers, chemoprofiling and chemometrics as additional tools to develop qualifying herbal extract references. We list the diagnostic traits available subsequent to each step during the medicinal herb extract manufacturing process and delineate limits to qualification of extract references.     

A correlation network approach to metabolic data analysis for tomato fruits

Network analysis of correlations between abundances of metabolites across tomato genotypes can help in unraveling the biological basis of organoleptic variation in tomato. We illustrate how to construct and interpret simple correlations networks using metabolic data collected on a diverse set of tomato genotypes. Various types of correlations are calculated and displayed in the form of networks. Interpretations on the basis of network analyses are compared to interpretations following principal components analysis.     

粒径对平菇栽培用玉米芯发酵料代谢物的影响

为了解玉米芯粒径对平菇栽培用发酵料中代谢物的影响,采用代谢组学技术分析添加不同粒径玉米芯的发酵料中微生物代谢物及其代谢通路.结果表明,添加小粒径玉米芯(D50=0.5 cm)和大粒径玉米芯(D50=1.5 cm)的发酵料中微生物代谢物差异显著.在正离子(POS)和负离子(NEG)模式下分别筛选得到464种和201种差异...     

Competitive sorption of microbial metabolites on an iron oxide mineral

A large fraction of soil organic matter (SOM) is composed of small molecules of microbial origin. However, the biotic and abiotic cycling of these nutrients is poorly understood and is a critical component of the global carbon cycle. Although there are many factors controlling the accessibility of SOM to microbes, sorption to mineral surfaces is among the most significant. Here, we investigated the competitive sorption of a complex pool of microbial metabolites on ferrihydrite, an iron oxide mineral, using a lysate prepared from a soil bacterium, Pseudomonas stutzeri RCH2. After a 24-h incubation with a range of mineral concentrations, more than half of the metabolites showed significant decreases in solution concentration. Phosphate-containing metabolites showed the greatest degree of sorption followed by dicarboxylates and metabolites containing both nitrogen and an aromatic moiety. Similar trends were observed when comparing sorption of metabolites with an equimolar metabolite mixture rather than a bacterial lysate. Interestingly, ectoine, lysine, two disaccharides and uracil were found not to sorb and may be more bioavailable in iron oxide-rich soils. Additionally, the highest-sorbing metabolites were examined for their ability to mobilize mineral-sorbed phosphate. All phosphate-containing metabolites tested and glutathione released phosphate from the mineral surface within 30 min of metabolite addition. These findings of preferential sorption behavior within a complex pool of microbial metabolites may provide insight into the cycling of SOM and specific nutrient availability. Finally, the release of highly-sorptive metabolites may be an underexplored mechanism utilized by microbial communities to gain access to limited environmental nutrients.     

Determining metabolic features of maintenance hemodialysis patients with diabetic nephropathy treated with glucose-added dialysate based on HPLC-MS/MS Q-TOF

AIM：To investigate the metabolic features of maintenance hemodialysis patients with diabetic nephropathy treated with glucose-added dialysate (containing glucose at concentration of 5.5 mmol/L for one time) by high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (HPLC-MS/MS Q-TOF). METHODS：Self-control study was conducted in 10 maintenance hemodialysis patients with diabetic nephropathy, who were dialyzed with glucose-free dialysate for one time (as glucose-free dialysate group, G- group) and then changed to glucose-added dialysate for another time (as glucose-added dialysate group, G+ group). The serum samples from the patients in G- group and G+ group before and after hemodialysis were analyzed and tested by the method of HPLC-MS/MS Q-TOF. In order to identify the differential metabolites, the metabonomic data was processed by principal component analysis (PCA) and orthogonal signal correction-partial least square discriminate analysis (OSC-PLS-DA). RESULTS：Regardless of before or after hemodialysis, the PCA model could not distinguish the serum samples from G+ group and G- group, but the samples could be effectively distinguish by OSC-PLS-DA model. The substances lined with variable importance in projection (VIP) value > 3 in the OSC-PLS-DA model and P<0.05 in the paired sample t-test as differential metabolites of the 2 groups and included metabolites such as hydrocortisone, lithocholic acid, aspartic acid, N-methyl niacinamide and dihydroxyprostaglandin F. The concentrations of hydrocortisone and lithochlic acid, which was able to raise the levels of blood glucose and gluconeogenesis, were lower in G+ group than those in G- group. The concentration of aspartic acid, which was involved in gluconeogenesis and also a kind of excitatory neurotransmitter, was lower in G+ group than that in G- group. The concentrations of N-methyl niacinamide and dihydroxyprostaglandin F, which reflected the level of oxidative stress, were higher in G+ gfroup than those in G- group. CONCLUSION：Using glucose-added dialysis for one time compared with glucose-free dialysis, metabolomics method confirms that the metabolic state in the maintenance hemodialysis patients with diabetic nephropathy is stable, and might reduce the level of gluconeogenesis and be superior in protecting central nervous system and improving nutritional status. However, according to the results of our present study, it might have the risk of increasing the level of oxidative stress.