scholarly journals Metabolite Profiling of Sorghum Seeds of Different Colors from Different Sweet Sorghum Cultivars Using a Widely Targeted Metabolomics Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yaxing Zhou ◽  
Zhenguo Wang ◽  
Yan Li ◽  
Zhigang Li ◽  
Hui Liu ◽  
...  
Keyword(s):  
Sweet Sorghum ◽  
Principal Component ◽  
Seed Color ◽  
Targeted Metabolomics ◽  
Phenotypic Differences ◽  
Benzoic Acid Derivatives ◽  
Orthogonal Signal Correction ◽  
Significant Difference ◽  
Comprehensive Comparison ◽  
Widely Targeted Metabolomics

Sweet sorghum (Sorghum bicolor) is one of the most important cereal crops in the world with colorful seeds. To study the diversity and cultivar-specificity of phytochemicals in sweet sorghum seeds, widely targeted metabolomics was used to analyze the metabolic profiles of the white, red, and purple seeds from three sweet sorghum cultivars Z6, Z27, and HC4. We identified 651 metabolites that were divided into 24 categories, including fatty acids, glycerolipids, flavonoids, benzoic acid derivatives, anthocyanins, and nucleotides and its derivatives. Among them, 217 metabolites were selected as significantly differential metabolites which could be related to the seed color by clustering analysis, principal component analysis (PCA), and orthogonal signal correction and partial least squares-discriminant analysis (OPLS-DA). A significant difference was shown between the red seed and purple seed samples, Z27 and HC4, in which 106 were downregulated and 111 were upregulated. The result indicated that 240 metabolites were significantly different, which could be related to the purple color with 58 metabolites downregulated and 182 metabolites upregulated. And 199 metabolites might be involved in the red phenotype with 54 downregulated and 135 upregulated. There were 45 metabolites that were common to all three cultivars, while cyanidin O-malonyl-malonyl hexoside, cyanidin O-acetylhexoside, and cyanidin 3-O-glucosyl-malonylglucoside were significantly upregulated red seeds, which could be the basis for the variety of seed colors. Generally, our findings provide a comprehensive comparison of the metabolites between the three phenotypes of S. bicolor and an interpretation of phenotypic differences from the point of metabolomics.

scholarly journals Metabolite Profiling of Different Sweet sorghum cultivars Seeds

2019 ◽  
Author(s):  
Yaxing Zhou ◽  
Zhenguo Wang ◽  
Yan Li ◽  
Zhigang Li ◽  
Hui Liu ◽  
...  
Keyword(s):  
Sweet Sorghum ◽  
Principal Component ◽  
Venn Diagram ◽  
Seed Color ◽  
Benzoic Acid Derivatives ◽  
Orthogonal Signal Correction ◽  
Signal Correction ◽  
Comparison Groups ◽  
Different Color ◽  
Diagram Analysis

Abstract Background Sorghum bicolor is one of the most important cereal crops in the world and is widely grown in arid or semi-arid areas. Results This study focused on the metabolic Diversity of three Sweet sorghum cultivars with white, red, and purple seeds to elucidate the factors responsible for the differences in Seed color. We found 651 metabolites were divided into 24 categories including Lipids_Fatty acids, Lipids_Glycerolipids, Flavonoid, Benzoic acid derivatives, Anthocyanins, Nucleotide and its derivates, etc. Through clustering analysis, principal component analysis (PCA), and orthogonal signal correction and partial least squares-discriminant analysis (OPLS-DA), different samples were clearly separated. It shows that contained metabolites of three groups are quite different. There are 217 significantly different metabolites between Z27 and HC4 (106 down-regulated, 111up-regulated), 240 between Z6 and HC4 (58 down-regulated, 182 up-regulated), 199 between Z6 and Z27 (54 down-regulated, 135 up-regulated). Venn diagram analysis indicated that 45 the differential metabolites were common to all three comparison groups. Conclusions This study provides new insights into the differences of metabolites between different color seeds and provides theoretical basis for the sufficient utilization of Sweet sorghum cultivars.

Leaf metabolites profiling between red and green phenotypes of Suaeda salsa by widely targeted metabolomics

2019 ◽  
Vol 46 (9) ◽  
pp. 845 ◽  
Author(s):  
Xin Wang ◽  
Junhong Bai ◽  
Wei Wang ◽  
Guangliang Zhang
Keyword(s):  
Yellow River ◽  
Yellow River Delta ◽  
Leaf Traits ◽  
Zeatin Riboside ◽  
Suaeda Salsa ◽  
Targeted Metabolomics ◽  
Phenotypic Differences ◽  
Comprehensive Comparison ◽  
Widely Targeted Metabolomics ◽  
Leaf Succulence

The Chenopodiaceae Suaeda salsa (L.) Pall. is a traditional Chinese medicine and food with green and red phenotypes in the Yellow River Delta. We identified 521 metabolites using widely targeted metabolomics, of which 165 were selected as significantly differential metabolites which could be related to the leaf traits of different phenotypes of S. salsa. Two anthocyanins (i.e. cyanidin O-acetylhexoside and delphinidin-3-O-(6ʹ-O-α-rhamnopyranosy l-β-glucopyranoside)) were responsible for red colour in red leaves of S. salsa. Gallic acid, which existed only in red one, was the main reason for leaf succulence. D-arabitol and ribitol were two significantly upregulated carbohydrates in red phenotype. Four alkaloids (i.e. harmaline, aminophylline, pipecolate and trigonelline) were upregulated in red leaves. Hormonal changed involved a decrease in indoleacetic acid-valine (IAA-Val), N6-isopentenyladenosine-5ʹ-monophosphate (iPRMP), isopentenyladenineriboside (iPR), trans-abscisic acid (S-ABA), salicylic acid O-hexoside, methyl jasmonate, N6-isopentenyladenine (iP), trans-zeatin riboside-O-glucoside iso2, trans-zeatin riboside-O-glucoside, and a tendency for dihydrozeatin 9-O-glucoside (DZ9G) down accumulation. In addition, the regulation of amino acids and lipids also contributed to the adaptation of red phenotype to harsh environment. Generally, our findings provide a comprehensive comparison of the metabolites between two phenotypes of S. salsa and an interpretation of phenotypic differences from the point of metabolomics.

scholarly journals Characterization of two closely related citrus cultivars using UPLC-ESI-MS/MS-based widely targeted metabolomics

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254759
Author(s):  
Fu Wang ◽  
Lin Chen ◽  
Shiwei Chen ◽  
Hongping Chen ◽  
Youping Liu
Keyword(s):  
Effective Means ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Morphological Identification ◽  
Targeted Metabolomics ◽  
Esi Ms ◽  
Orthogonal Signal Correction ◽  
Widely Targeted Metabolomics ◽  
Quality Difference

Citrus cultivars are widely spread worldwide, and some of them only differ by specific mutations along the genome. It is difficult to distinguish them by traditional morphological identification. To accurately identify such similar cultivars, the subtle differences between them must be detected. In this study, UPLC-ESI-MS/MS-based widely targeted metabolomics analysis was conducted to study the chemical differences between two closely related citrus cultivars, Citrus reticulata ‘DHP’ and C. reticulata ‘BZH’. Totally 352 metabolites including 11 terpenoids, 35 alkaloids, 80 phenolic acids, 25 coumarins, 7 lignans, 184 flavonoids and 10 other compounds were detected and identified; Among them, 15 metabolites are unique to DHP and 16 metabolites are unique to BZH. Hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal signal correction and partial least squares-discriminant analysis (OPLS-DA) can be used to clearly discriminate between DHP and BZH. 93 metabolites including 36 down-regulated and 57 up-regulated are significantly different in DHP and BZH. They are mainly involved in the biosynthesis of flavonoids, flavones, flavonols, and isoflavonoids. In addition, the relative content levels of flavonoids, alkaloids, and terpenoids are much higher in the peel of DHP than that of BZH, the presence of which may correlate with the quality difference of the peels. The results reported herein indicate that metabolite analysis based on UPLC-ESI-MS/MS is an effective means of identifying cultivars with different genotypes, especially those that cannot be distinguished based on traditional identification methods.

scholarly journals Transcriptome Analyses of Myometrium from Fibroid Patients Reveals Phenotypic Differences Compared to Non-Diseased Myometrium

2021 ◽  
Vol 22 (7) ◽  
pp. 3618
Author(s):  
Emmanuel N. Paul ◽  
Gregory W. Burns ◽  
Tyler J. Carpenter ◽  
Joshua A. Grey ◽  
Asgerally T. Fazleabas ◽  
...  
Keyword(s):  
Uterine Fibroid ◽  
Three Dimensional ◽  
Uterine Fibroids ◽  
Principal Component ◽  
Leading Edge ◽  
Gene Set Enrichment ◽  
Phenotypic Differences ◽  
False Discovery ◽  
Gene Sets ◽  
High Concordance

Uterine fibroid tissues are often compared to their matched myometrium in an effort to understand their pathophysiology, but it is not clear whether the myometria of uterine fibroid patients represent truly non-disease control tissues. We analyzed the transcriptomes of myometrial samples from non-fibroid patients (M) and compared them with fibroid (F) and matched myometrial (MF) samples to determine whether there is a phenotypic difference between fibroid and non-fibroid myometria. Multidimensional scaling plots revealed that M samples clustered separately from both MF and F samples. A total of 1169 differentially expressed genes (DEGs) (false discovery rate < 0.05) were observed in the MF comparison with M. Overrepresented Gene Ontology terms showed a high concordance of upregulated gene sets in MF compared to M, particularly extracellular matrix and structure organization. Gene set enrichment analyses showed that the leading-edge genes from the TGFβ signaling and inflammatory response gene sets were significantly enriched in MF. Overall comparison of the three tissues by three-dimensional principal component analyses showed that M, MF, and F samples clustered separately from each other and that a total of 732 DEGs from F vs. M were not found in the F vs. MF, which are likely understudied in the pathogenesis of uterine fibroids and could be key genes for future investigation. These results suggest that the transcriptome of fibroid-associated myometrium is different from that of non-diseased myometrium and that fibroid studies should consider using both matched myometrium and non-diseased myometrium as controls.

scholarly journals Inhibition of Kynurenine Metabolism and Its Effect in Mitochondrial Function in Hepatocellular Carcinoma

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 124-125
Author(s):  
Raul Castro-Portuguez ◽  
Samuel Freitas ◽  
George Sutphin
Keyword(s):  
Hepatocellular Carcinoma ◽  
Mitochondrial Function ◽  
De Novo ◽  
Principal Component ◽  
Kynurenine Pathway ◽  
The Cancer Genome Atlas ◽  
Wilcoxon Test ◽  
Nad Synthesis ◽  
Significant Difference ◽  
Kynurenine Metabolism

Abstract Hepatocellular carcinoma (HCC) is the most prevalent cancer in the liver. The majority of ingested tryptophan is processed in the liver through the kynurenine pathway, the endpoint of which is de novo NAD+ biosynthesis. Dysregulation of tryptophan-kynurenine metabolism and NAD+ synthesis may promote mitochondrial malfunction, tumor reprogramming, and carcinogenesis. Using a publicly available gene expression dataset from liver hepatocellular carcinoma (LIHC) samples available through The Cancer Genome Atlas (TCGA; n = 371), we employed Principal Component Analysis (PCA), hierarchical clustering, gene-pattern expression profiling, and survival analysis to cluster patients and determine overall survival. Our analysis of genes encoding kynurenine pathway enzymes determined that patients with high QPRT expression had a poor prognosis with decreased median survival, with no effect on the maximum survival. There is a significant difference in the survival between patients with high QPRT expression relative to patients with high HAAO/AFMID expression (HR = 1.2, [95% CI 0.5-1.8] P = 0.0181, Gehan-Breslow-Wilcoxon Test). Patients with high QPRT expression have higher survival rates compared with low QPRT expression (HR = 1.4, [95% CI 0.9-2.2] P = 0.0344, Gehan-Breslow-Wilcoxon Test). To test the consequences of kynurenine-pathway inhibition in mitochondrial function and morphology we use 4-Cl-3HAA, an irreversible HAAO inhibitor, and observed a small increase in mitochondrial fragmentation in HepG2 cells after 24 hours of treatment. We conclude that kynurenine metabolism may be useful as a biomarker to predict patient prognosis among HCC patients. In ongoing work, we are testing QPRT inhibitors in cell culture as a potential adjuvant for chemotherapies.

Calibration Transfer between Miniature Photodiode Array-Based Spectrometers in the near Infrared Assessment of Mandarin Soluble Solids Content

2002 ◽  
Vol 10 (1) ◽  
pp. 27-35 ◽  
Author(s):  
C.V. Greensill ◽  
K.B. Walsh
Keyword(s):  
Near Infrared ◽  
Model Updating ◽  
Soluble Solids ◽  
Soluble Solid Content ◽  
Calibration Model ◽  
Calibration Transfer ◽  
Orthogonal Signal Correction ◽  
Significant Difference ◽  
Photodiode Array ◽  
Direct Standardisation

The transfer of predictive models among photodiode array based, short wave near infrared spectrometers using the same illumination/detection optical geometry has been attempted using various chemometric techniques, including slope and bias correction (SBC), direct standardisation (DS), piecewise direct standardisation (PDS), double window PDS (DWPDS), orthogonal signal correction (OSC), finite impulse transform (FIR) and wavelet transform (WT). Additionally, an interpolation and photometric response correction method, a wavelength selection method and a model updating method were assessed. Calibration transfer was attempted across two populations of mandarin fruit. Model performance was compared in terms of root mean squared error of prediction ( RMSEP), using Fearn's significance testing, for calibration transfer (standardisation) between pairs of spectrometers from a group of four spectrometers. For example, when a calibration model (Root Mean Square Error of Cross-Validation [ RMSECV = 0.26% soluble solid content (SSC)], developed on one spectrometer, was used with spectral data collected on another spectrometer, a poor prediction resulted ( RMSEP = 2.5% SSC). A modified WT method performed significantly better (e.g. RMSEP = 0.25% SSC) than all other standardisation methods (10 of 12 cases), and almost on a par with model updating (MU) (nine cases with no significant difference, one case and two cases significantly better for WT and MU, respectively).

scholarly journals Extensive Metabolite Profiling in the Unexploited Organs of Black Tiger for Their Potential Valorization in the Pharmaceutical Industry

Life ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 544
Author(s):  
Jianfei Gao ◽  
Kangning Xiong ◽  
Wei Zhou ◽  
Weijie Li
Keyword(s):  
Acid Metabolism ◽  
Metabolite Profile ◽  
Industrial Applications ◽  
Targeted Metabolomics ◽  
Arginine Biosynthesis ◽  
Nutritional Values ◽  
Phenylpropanoid Biosynthesis ◽  
Tyrosine Metabolism ◽  
Organ Specific ◽  
Widely Targeted Metabolomics

Black tiger (Kadsura coccinea (Lem.)) has been reported to hold enormous pharmaceutical potential. The fruit and rhizome of black tiger are highly exploited in the pharmaceutical and other industries. However, the most important organs from the plant such as the leaf and stem are considered biowastes mainly because a comprehensive metabolite profile has not been reported in these organs. Knowledge of the metabolic landscape of the unexploited black tiger organs could help identify and isolate important compounds with pharmaceutical and nutritional values for a better valorization of the species. In this study, we used a widely targeted metabolomics approach to profile the metabolomes of the K. coccinea leaf (KL) and stem (KS) and compared them with the root (KR). We identified 642, 650 and 619 diverse metabolites in KL, KS and KR, respectively. A total of 555 metabolites were mutually detected among the three organs, indicating that the leaf and stem organs may also hold potential for medicinal, nutritional and industrial applications. Most of the differentially accumulated metabolites between organs were enriched in flavone and flavonol biosynthesis, phenylpropanoid biosynthesis, arginine and proline metabolism, arginine biosynthesis, tyrosine metabolism and 2-oxocarboxylic acid metabolism pathways. In addition, several important organ-specific metabolites were detected in K. coccinea. In conclusion, we provide extensive metabolic information to stimulate black tiger leaf and stem valorization in human healthcare and food.

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