Enhancement of plant metabolite fingerprinting by machine learning

Plant Physiology

Volumn 153, Issue 4, 2010, Pages 1506-1520

  Scott, Ian M ^a   Vermeer, Cornelia P ^a   Liakata, Maria ^b   Corol, Delia I ^c   Ward, Jane L ^c   Lin, Wanchang ^d   Johnson, Helen E ^a   Whitehead, Lynne ^a   Kular, Baldeep ^e   Baker, John M ^c   Walsh, Sean ^e   Dave, Anuja ^d   Larson, Tony R ^d   Graham, Ian A ^d   Wang, Trevor L ^e   King, Ross D ^b   Draper, John ^a   Beale, Michael H ^c  

^a ABERYSTWYTH UNIVERSITY   (United Kingdom)

^b ABERYSTWYTH UNIVERSITY   (United Kingdom)

^c ROTHAMSTED RESEARCH   (United Kingdom)

^d UNIVERSITY OF YORK   (United Kingdom)

^e JOHN INNES CENTRE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARABIDOPSIS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; INFRARED SPECTROSCOPY; MASS SPECTROMETRY; METABOLISM; METABOLOMICS; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY; PHENOTYPE; PRINCIPAL COMPONENT ANALYSIS;

ALGORITHMS; ARABIDOPSIS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; MAGNETIC RESONANCE SPECTROSCOPY; MASS SPECTROMETRY; METABOLOMICS; PHENOTYPE; PRINCIPAL COMPONENT ANALYSIS; SPECTROSCOPY, FOURIER TRANSFORM INFRARED;

EID: 77955681638     PISSN: 00320889     EISSN: 15322548     Source Type: Journal    
DOI: 10.1104/pp.109.150524     Document Type: Article

References (64)

1. Arita M (2004) Computational resources for metabolomics. Brief Funct Genomics Proteomics 3: 84-93
2. Beckmann M, Parker D, Enot DP, Duval E, Draper J (2008) High-throughput, nontargeted metabolite fingerprinting using nominal mass flow injection electrospray mass spectrometry. Nat Protoc 3: 486-504
3. Beisson F, Koo AJK, Ruuska S, Schwender J, Pollard M, Thelen JJ, Paddock T, Salas JJ, Savage L, Milcamps A, et al (2003) Arabidopsis genes involved in acyl lipid metabolism: a 2003 census of the candidates, a study of the distribution of expressed sequence tags in organs, and a Web-based database. Plant Physiol 132: 681-697
4. Ben-Hur A, Ong CS, Sonnenburg S, Scholkopf B, Ratsch G (2008) Support vector machines and kernels for computational biology. PLoS Comput Biol 4: e1000173
5. Boyes DC, Zayed AM, Ascenzi R, McCaskill AJ, Hoffman NE, Davis KR, Gorlach J (2001) Growth stage-based phenotypic analysis of Arabidopsis: a model for high throughput functional genomics in plants. Plant Cell 13: 1499-1510
6. Broadhurst DI, Kell DB (2006) Statistical strategies for avoiding false discoveries in metabolomics and related experiments. Metabolomics 2: 171-196
7. Bryan K, Brennan L, Cunningham P (2008) MetaFIND: a feature analysis tool for metabolomics data. BMC Bioinformatics 9: 470
8. Caspar T, Lin TP, Kakefuda G, Benbow L, Preiss J, Somerville C (1991) Mutants of Arabidopsis with altered regulation of starch degradation. Plant Physiol 95: 1181-1188
9. Catchpole GS, Beckmann M, Enot DP, Mondhe M, Zywicki B, Taylor J, Hardy N, Smith A, King RD, Kell DB, et al (2005) Hierarchical metabolomics demonstrates substantial compositional similarity between genetically modified and conventional potato crops. Proc Natl Acad Sci USA 102: 14458-14462
10. Clarke R, Ressom HW, Wang A, Xuan J, Liu MC, Gehan EA, Wang Y (2008) The properties of high-dimensional data spaces: implications for exploring gene and protein expression data. Nat Rev Cancer 8: 37-49
11. Conklin PL, Gatzek S, Wheeler GL, Dowdle J, Raymond MJ, Rolinski S, Isupov M, Littlechild JA, Smirnoff N (2006) Arabidopsis thaliana VTC4 encodes L-galactose-1-P phosphatase, a plant ascorbic acid biosynthetic enzyme. J Biol Chem 281: 15662-15670
12. Daub CO, Kloska S, Selbig J (2003) MetaGeneAlyse: analysis of integrated transcriptional and metabolite data. Bioinformatics 19: 2332-2333
13. Davison A (2008) Some challenges for statistics. Stat Methods Appl 17: 167-181
14. Eastment HT, Krzanowski WJ (1982) Cross-validatory choice of the number of components from a principal component analysis. Technometrics 24: 73-77
15. Enot DP, Beckmann M, Overy D, Draper J (2006) Predicting interpretability of metabolome models based on behavior, putative identity, and biological relevance of explanatory signals. Proc Natl Acad Sci USA 103: 14865-14870
16. Enot DP, Lin W, Beckmann M, Parker D, Overy DP, Draper J (2008) Preprocessing, classification modeling and feature selection using flow injection electrospray mass spectrometry metabolite fingerprint data. Nat Protoc 3: 446-470
17. Fahnenstich H, Saigo M, Niessen M, Zanor MI, Andreo CS, Fernie AR, Drincovich MF, Flugge UI, Maurino VG (2007) Alteration of organic acid metabolism in Arabidopsis overexpressing the maize C4 NADP-malic enzyme causes accelerated senescence during extended darkness. Plant Physiol 145: 640-652
18. Frank E, Hall M, Trigg L, Holmes G, Witten IH (2004) Data mining in bioinformatics using Weka. Bioinformatics 20: 2479-2481
19. Fraser PD, Pinto MES, Holloway DE, Bramley PM (2000) Application of high-performance liquid chromatography with photodiode array detection to the metabolic profiling of plant isoprenoids. Plant J 24: 551-558
20. Friedman JH (2006) Recent advances in predictive (machine) learning. J Classif 23: 175-197
21. Gentleman R, Carey V, Bates D, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, et al (2004) Bioconductor: open software development for computational biology and bioinformatics. Genome Biol 5: R80
22. Gewehr JE, Szugat M, Zimmer R (2007) BioWeka: extending the Weka framework for bioinformatics. Bioinformatics 23: 651-653
23. Gibon Y, Usadel B, Blaesing O, Kamlage B, Hoehne M, Trethewey R, Stitt M (2006) Integration of metabolite with transcript and enzyme activity profiling during diurnal cycles in Arabidopsis rosettes. Genome Biol 7: R76
24. Gidman EA, Stevens CJ, Goodacre R, Broadhurst D, Emmett B, Gwynn-Jones D (2006) Using metabolic fingerprinting of plants for evaluating nitrogen deposition impacts on the landscape level. Glob Change Biol 12: 1460-1465
25. Hall RD (2006) Plant metabolomics: from holistic hope, to hype, to hot topic. New Phytol 169: 453-468
26. Hammer Ø, Harper DAT, Ryan PD (2001) PAST: paleontological statistics software package for education and data analysis. Palaeontol Electron 4: 1.4A
27. Husek P (1998) Chloroformates in gas chromatography as general purpose derivatizing agents. J Chromatogr B Analyt Technol Biomed Life Sci 717: 57-91
28. Izquierdo-Garcia J, Rodríguez I, Kyriazis A, Villa P, Barreiro P, Desco M, Ruiz-Cabello J (2009) A novel R-package graphic user interface for the analysis of metabonomic profiles. BMC Bioinformatics 10: 363
29. Jafari P, Azuaje F (2006) An assessment of recently published gene expression data analyses: reporting experimental design and statistical factors. BMC Med Inform Decis Mak 6: 27
30. Janes KA, Yaffe MB (2006) Data-driven modelling of signal-transduction networks. Nat Rev Mol Cell Biol 7: 820-828
31. Jenkins H, Johnson H, Kular B, Wang T, Hardy N (2005) Toward supportive data collection tools for plant metabolomics. Plant Physiol 138: 67-77
32. Kachroo P, Venugopal SC, Navarre DA, Lapchyk L, Kachroo A (2005) Role of salicylic acid and fatty acid desaturation pathways in ssi2-mediated signaling. Plant Physiol 139: 1717-1735
33. Larson TR, Graham IA (2001) A novel technique for the sensitive quantification of acyl CoA esters from plant tissues. Plant J 25: 115-125
34. Lisec J, Schauer N, Kopka J, Willmitzer L, Fernie AR (2006) Gas chromatography mass spectrometry-based metabolite profiling in plants. Nat Protoc 1: 387-396
35. Lu Y, Savage LJ, Ajjawi I, Imre KM, Yoder DW, Benning C, DellaPenna D, Ohlrogge JB, Osteryoung KW, Weber AP, et al (2008) New connections across pathways and cellular processes: industrialized mutant screening reveals novel associations between diverse phenotypes in Arabidopsis. Plant Physiol 146: 1482-1500
36. Mahoney MW, Drineas P (2009) CUR matrix decompositions for improved data analysis. Proc Natl Acad Sci, USA 106: 697-702
37. Mekhedov S, de Ilarduya OM, Ohlrogge J (2000) Toward a functional catalog of the plant genome: a survey of genes for lipid biosynthesis. Plant Physiol 122: 389-402
38. Messerli G, Partovinia V, Trevisan M, Kolbe A, Schauer N, Geigenberger P, Chen J, Davison AC, Fernie AR, Zeeman SC (2007) Rapid classification of phenotypic mutants of Arabidopsis via metabolite fingerprinting. Plant Physiol 143: 1484-1492
39. Meyer RC, Steinfath M, Lisec J, Becher M, Witucka-Wall H, Torjek O, Fiehn O, Eckardt A, Willmitzer L, Selbig J, et al (2007) The metabolic signature related to high plant growth rate in Arabidopsis thaliana. Proc Natl Acad Sci USA 104: 4759-4764
40. Nachtomy O, Shavit A, Yakhini Z (2007) Gene expression and the concept of the phenotype. Stud Hist Phil Biol Biomed Sci 38: 238-254
41. Nelson DR, Schuler MA, Paquette SM, Werck-Reichhart D, Bak S (2004) Comparative genomics of rice and Arabidopsis: analysis of 727 cytochrome P450 genes and pseudogenes from a monocot and a dicot. Plant Physiol 135: 756-772
42. Neuweger H, Albaum SP, Dondrup M, Persicke M, Watt T, Niehaus K, Stoye J, Goesmann A (2008) MeltDB: a software platform for the analysis and integration of metabolomics experiment data. Bioinformatics 24: 2726-2732
43. Pan X, Liu H, Clarke J, Jones J, Bevan M, Stein L (2003) ATIDB: Arabidopsis thaliana insertion database. Nucleic Acids Res 31: 1245-1251
44. Pastori GM, Kiddle G, Antoniw J, Bernard S, Veljovic-Jovanovic S, Verrier PJ, Noctor G, Foyer CH (2003) Leaf vitamin C contents modulate plant defense transcripts and regulate genes that control development through hormone signaling. Plant Cell 15: 939-951
45. Rosti J, Barton CJ, Albrecht S, Dupree P, Pauly M, Findlay K, Roberts K, Seifert GJ (2007) UDP-glucose 4-epimerase isoforms UGE2 and UGE4 cooperate in providing UDP-galactose for cell wall biosynthesis and growth of Arabidopsis thaliana. Plant Cell 19: 1565-1579
46. Saeys Y, Inza I, Larrañaga P (2007) A review of feature selection techniques in bioinformatics. Bioinformatics 23: 2507-2517
47. Schauer N, Semel Y, Roessner U, Gur A, Balbo I, Carrari F, Pleban T, Perez-Melis A, Bruedigam C, Kopka J, et al (2006) Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement. Nat Biotechnol 24: 447-454
48. Slawski M, Daumer M, Boulesteix AL (2008) CMA: a comprehensive Bioconductor package for supervised classification with high dimensional data. BMC Bioinformatics 9: 439
49. Stajich JE, Lapp H (2006) Open source tools and toolkits for bioinformatics: significance, and where are we? Brief Bioinform 7: 287-296
50. Stitt M, Muller C, Matt P, Gibon Y, Carillo P, Morcuende R, Scheible WR, Krapp A (2002) Steps towards an integrated view of nitrogen metabolism. J Exp Bot 53: 959-970
51. Suh MC, Samuels AL, Jetter R, Kunst L, Pollard M, Ohlrogge J, Beisson F (2005) Cuticular lipid composition, surface structure, and gene expression in Arabidopsis stem epidermis. Plant Physiol 139: 1649-1665
52. Sweetlove LJ, Last RL, Fernie AR (2003) Predictive metabolic engineering: a goal for systems biology. Plant Physiol 132: 420-425
53. Tarca AL, Carey VJ, Chen X, Romero R, Draghici S (2007) Machine learning and its applications to biology. PLoS Comput Biol 3: e116
54. Thimm O, Blasing O, Gibon Y, Nagel A, Meyer S, Kruger P, Selbig J, Muller LA, Rhee SY, Stitt M (2004) MAPMAN: a user-driven tool to display genomics data sets onto diagrams of metabolic pathways and other biological processes. Plant J 37: 914-939
55. Tissier AF, Marillonnet S, Klimyuk V, Patel K, Torres MA, Murphy G, Jones JDG (1999) Multiple independent defective Suppressor-mutator transposon insertions in Arabidopsis: a tool for functional genomics. Plant Cell 11: 1841-1852
56. Verslues PE, Bray EA (2006) Role of abscisic acid (ABA) and Arabidopsis thaliana ABA-insensitive loci in low water potential-induced ABA and proline accumulation. J Exp Bot 57: 201-212
57. Wang T, Shao K, Chu Q, Ren Y, Mu Y, Qu L, He J, Jin C, Xia B (2009) Automics: an integrated platform for NMR-based metabonomics spectral processing and data analysis. BMC Bioinformatics 10: 83
58. Ward JL, Baker JM, Beale MH (2007) Recent applications of NMR spectroscopy in plant metabolomics. FEBS J 274: 1126-1131
59. Westerhuis JA, Hoefsloot HCJ, Smit S, Vis DJ, Smilde AK, van Velzen EJJ, van Duijnhoven JPM, van Dorsten FA (2008) Assessment of PLSDA cross validation. Metabolomics 4: 81-89
60. Wurtele ES, Li J, Diao LX, Zhang HL, Foster CM, Fatland B, Dickerson U, Brown A, Cox Z, Cook D, et al (2003) MetNet: software to build and model the biogenetic lattice of Arabidopsis. Comp Funct Genomics 4: 239-245
61. Xia JG, Psychogios N, Young N, Wishart DS (2009) MetaboAnalyst: a Web server for metabolomic data analysis and interpretation. Nucleic Acids Res 37: W652-W660
62. Xu C, Yu B, Cornish AJ, Froehlich JE, Benning C (2006) Phosphatidyl glycerol biosynthesis in chloroplasts of Arabidopsis mutants deficient in acyl-ACP glycerol-3-phosphate acyltransferase. Plant J 47: 296-309
63. Zhang C, Lu X, Zhang X (2006) Significance of gene ranking for classification of microarray samples. IEEE/ACM Trans Comput Biol Bioinformatics 3: 312-320
64. Zhang P, Foerster H, Tissier CP, Mueller L, Paley S, Karp PD, Rhee SY (2005) MetaCyc and AraCyc: metabolic pathway databases for plant research. Plant Physiol 138: 27-37