Citrus tristeza virus infection in sweet orange trees and a mandarin × tangor cross alters low molecular weight metabolites assessed using gas chromatography mass spectrometry (GC/MS)

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• 作者：Alberto Pasamontes ; William H. K. Cheung ; Jason Simmons…
• 关键词：Citrus tristeza virus (CTV) ; Feature selection ; Cross ; validation ; Partial least square discriminant analysis (PLSDA) ; Mass spectrometry ; Gas chromatography ; Biomarker discovery
• 刊名：Metabolomics
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：12
• 期：3
• 全文大小：881 KB
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• 作者单位：Alberto Pasamontes (1)
  William H. K. Cheung (1)
  Jason Simmons (1)
  Alexander A. Aksenov (1)
  Daniel J. Peirano (1)
  Elizabeth E. Grafton-Cardwell (2)
  Therese Kapaun (2)
  Abhaya M. Dandekar (3)
  Oliver Fiehn (4)
  Cristina E. Davis (1)
  
  1. Department of Mechanical and Aerospace Engineering, University of California, Davis, One Shields Avenue, Davis, CA, 95616, USA
  2. University of California, Lindcove Research and Extension Center (LREC), 22963 Carson Avenue, Exeter, CA, 93221, USA
  3. Department of Plant Sciences, University of California, Davis, One Shields Avenue, Davis, CA, 95616, USA
  4. UC Davis Genome Center-Metabolomics, University of California, Davis, 451 Health Sciences Drive, Davis, CA, 95616, USA
  
• 刊物主题：Biochemistry, general; Molecular Medicine; Cell Biology; Developmental Biology; Biomedicine general;
• 出版者：Springer US
• ISSN：1573-3890

文摘

Citrus tristeza virus (CTV) (genus Closterovirus) is a plant pathogen which infects economically important citrus crops, resulting in devastating crop losses worldwide. In this study, we analyzed leaf metabolite extracts from six sweet orange varieties and a mandarin × tangor cross infected with CTV collected at the Lindcove Research and Extension Center (LREC; Exeter, CA). In order to analyze low volatility small molecules, the extracts of leaf metabolites were derivatized by N-methyl-N-trimethylsilyl-trifluoracetamide (MSTFA). Chemical analysis was performed with gas chromatography/mass spectrometry (GC/MS) to assess metabolite changes induced by CTV infection. Principal Component Analysis (PCA) and Hotelling’s T2 were used to identify outliers within the set of samples. Partial Least Square Discriminant Analysis (PLS-DA) was applied as a regression method. A cross-validation strategy was repeated 300 times to minimize possible bias in the model selection. Afterwards, a representative model was built with a sensitivity of 0.66 and a specificity of 0.71. The metabolites which had the strongest contribution to differentiate between healthy and CTV-infected were found to be mostly saccharides and their derivatives such as inositol, d-fructose, glucaric and quinic acid. These metabolites are known to be endogenously produced by plants, possess important biological functions and often found to be differentially regulated in disease states, maturation processes, and metabolic responses. Based on the information found in this study, a method may be available that can identify CTV infected plants for removal and halt the spread of the virus. Keywords Citrus tristeza virus (CTV) Feature selection Cross-validation Partial least square discriminant analysis (PLSDA) Mass spectrometry Gas chromatography Biomarker discovery