Skip to main content
SpringerLink
Log in

Metabolic Pathway Analysis Employing Bioinformatic Software

  • Chapter
  • First Online:
Current trends in Bioinformatics: An Insight

  • 1273 Accesses

Abstract

Metabolomics can be defined as the entire content of metabolites in a system and their roles and interactions in various metabolic pathways reflecting the genetic information encrypted in a genome. Of late, various biochemical and metabolic studies are being applied for monitoring the dynamics of growth and development of model plants. Observed variations in composition of metabolites are used for understanding course of gene expression in stress-affected plants. Critical analysis of metabolic pathways in a system when challenged with stress, for example, comparison of metabolic flux with data obtained from physiological, genetic, genomic studies, is helping plant researchers in identification of candidate genes responsible for regulation of a given trait. In this chapter attempts have been made to describe recent developments in plant metabolomics, and application of bioinformatics and databases in metabolic pathway analysis is reviewed.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Akiyama K et al (2008) PRIMe: a web site that assembles tools for metabolomics and transcriptomics. In Silico Biol 8:339–345

    PubMed  CAS  Google Scholar 

  • Beckmann M et al (2007) Representation, comparison, and interpretation of metabolome fingerprint data for total composition analysis and quality trait investigation in potato cultivars. J Agric Food Chem 55:3444–3451

    Article  CAS  PubMed  Google Scholar 

  • Bono H et al (1998) Reconstruction of amino acid biosynthesis pathways from the complete genome sequence. Genome Res 8:203–210

    Article  CAS  PubMed  Google Scholar 

  • Caspi R, Karp PD (2007) Using the MetaCyc pathway database and the BioCyc database collection. Curr Protoc Bioinform. https://doi.org/10.1002/0471250953.bi0117s20

  • Caspi R et al (2006) MetaCyc: a multiorganism database of metabolic pathways and enzymes. Nucleic Acids Res 34:D511–D516

    Article  CAS  PubMed  Google Scholar 

  • Caspi R et al (2014) The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Res 44(D1):D471–D480

    Article  CAS  Google Scholar 

  • Chang A et al (2009) BRENDA, AMENDA and FRENDA the enzyme information system: new content and tools in 2009. Nucleic Acids Res. https://doi.org/10.1093/nar/gkn820

    Article  CAS  PubMed  Google Scholar 

  • Christensen B, Nielsen J (2000) Metabolic network analysis of Penicillium chrysogenum using (13)C-labeled glucose. Biotechnol Bioeng 68:652–659

    Article  CAS  PubMed  Google Scholar 

  • Ciocchetta F, Hillston J (2008) Bio-PEPA: an extension of the process algebra PEPA for biochemical networks. Electron Notes Theor Comput Sci 194:103–117

    Article  Google Scholar 

  • Clark BL (1998) Stability of complex reaction network analysis. Cell Biophys 12:237–253

    Article  Google Scholar 

  • Consortium, I. H. G. S (2001) Initial sequencing and analysis of the human genome. Nature 412:860–921

    Article  Google Scholar 

  • DellaPenna D (2007) Biofortification of plant-based food: enhancing folate levels by metabolic engineering. Proc Natl Acad Sci U S A 104:3675

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • DellaPenna D, Pogson BJ (2006) Vitamin synthesis in plants: tocopherols and carotenoids. Annu Rev Plant Biol 57:711–738

    Article  CAS  PubMed  Google Scholar 

  • Edwards JS, Palsson BO (2000a) Metabolic flux balance analysis and the in silico analysis of Escherichia coli K-12 gene deletions. BMC Bioinforma 1:1

    Article  CAS  Google Scholar 

  • Edwards JS, Palsson BO (2000b) The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities. Proc Natl Acad Sci U S A 97:5528–5533

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Edwards D et al (2007) BarleyBase/PLEXdb a unified expression profiling database for plants and plant pathogens. Plant Bioinforma 406:347–363

    Google Scholar 

  • Fell DA (1993) In: Chuster S, Rigoulet M, Ouhabi R, Mazat JP (eds) Modern trends in Biothermakinetics. Plenum Press, New York, pp 97–101

    Chapter  Google Scholar 

  • Fernie AR, Tadmor Y, Zamir D (2006) Natural genetic variation for improving crop quality. Curr Opin Plant Biol 9:196–202

    Article  PubMed  Google Scholar 

  • Friel E, Green S, Matich A, Beuning L, Yauk YK, Wang M, MacRae E (2006) Pathway analysis in horticultural crops: linalool as an example. Dev Food Sci 43:93–96

    Article  CAS  Google Scholar 

  • Génard M et al (2007) Towards a virtual fruit focusing on quality: modelling features and potential uses. J Exp Bot 58:917–928

    Article  CAS  PubMed  Google Scholar 

  • Hatzimanikatis V, Lee KH, Bailey JE (1999) A mathematical description of regulation of the G1-S transition of the mammalian cell cycle. Biotechnol Bioeng 65:631–637

    Article  CAS  PubMed  Google Scholar 

  • Hirai MY et al (2004) Integration of transcriptomics and metabolomics for understanding of global responses to nutritional stresses in Arabidopsis thaliana. Proc Natl Acad Sci U S A 101:10205–10210

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Iijima Y et al (2008) Metabolite annotations based on the integration of mass spectral information. Plant J 54:949–962

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • International Human Genome Sequencing Consortium (2004) International human genome sequencing consortium. Finishing the euchromatic sequence of the human genome. Nature 431:931–945

    Article  CAS  Google Scholar 

  • Jonsson P et al (2004) A strategy for identifying differences in large series of Metabolomic samples analyzed by GC/MS. Anal Chem 76:1738–1745

    Article  CAS  PubMed  Google Scholar 

  • Kopka J et al (2005) GMD@CSB.DB: the Golm metabolome database. Bioinformatics 21:1635–1638

    Article  CAS  PubMed  Google Scholar 

  • Kose F et al (2001) Visualizing plant metabolomic correlation networks using clique-metabolite matrices. Bioinformatics 17:1198–1208

    Article  CAS  PubMed  Google Scholar 

  • Küffner R, Zimmer R, Lengauer T (2000) Pathway analysis in metabolic databases via differential metabolic display (DMD). Bioinformatics 16:825–836

    Article  PubMed  Google Scholar 

  • Larkin P, Harrigan GG (2007) Opportunities and surprises in crops modified by transgenic technology: metabolic engineering of benzylisoquinoline alkaloid, gossypol and lysine biosynthetic pathways. Metabolomics 3:371–382

    Article  CAS  Google Scholar 

  • Laurentin H, Ratzinger A, Karlovsky P (2008) Relationship between metabolic and genomic diversity in sesame (Sesamum indicum L.) BMC Genomics 9:250

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lee TH et al (2009) RiceArrayNet: a database for correlating gene expression from transcriptome profiling, and its application to the analysis of coexpressed genes in rice. Plant Physiol 151:16–33

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lisec J et al (2008) Identification of metabolic and biomass QTL in Arabidopsis thaliana in a parallel analysis of RIL and IL populations. Plant J 53:960–972

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Magrath R et al (1993) The inheritance of aliphatic glucosinolates in Brassica napus. Plant Breed 111:55–72

    Article  CAS  Google Scholar 

  • Marla S (2006) Comparative structure analysis of chorismate synthase comparative structure analysis of Chorismate synthase. Online J Bioinforma 7(1):35–45

    Google Scholar 

  • Marla S (2014) Annotation of genome of Sessamun radiatum, ICAR.NBPGR, New Delhi, Unpublished, Personal communication

    Google Scholar 

  • Marla S et al (2010) Classification of rice seed storage proteins using neural networks. J Plant Biochem Biotechnol, 19:123–126

    Article  CAS  Google Scholar 

  • Maruyama K et al (2009) Metabolic pathways involved in cold acclimation identified by integrated analysis of metabolites and transcripts regulated by DREB1A and DREB2A. Plant Physiol 150:1972–1980

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Matsuda F et al (2009) MS/MS spectral tag-based annotation of non-targeted profile of plant secondary metabolites. Plant J 57:5550–5577

    Google Scholar 

  • Mendes P (2002) Emerging bioinformatics for the metabolome. Brief Bioinform 3:134–145

    Article  CAS  PubMed  Google Scholar 

  • Mochida K et al (2009) Correlation exploration of metabolic and genomic diversity in rice. BMC Genomics 10:568

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Moco S et al (2006) A liquid chromatography-mass spectrometry-based metabolome database for tomato. Plant Physiol 141:1205–1218

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Mohanty B et al (2015) Identification of candidate network hubs involved in metabolic adjustments of rice under drought stress by integrating transcriptome data and genome-scale metabolic network. Plant Sci 241:224–239

    Google Scholar 

  • Morgan MJ et al (2013) Metabolic engineering of tomato fruit organic acid content guided by biochemical analysis of an introgression line. Plant Physiol 161:397–407

    Article  CAS  PubMed  Google Scholar 

  • Mueller LA, Zhang P, Rhee SY (2003) AraCyc: a biochemical pathway database for Arabidopsis. Plant Physiol 132:453–460

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Nadella KD, Marla SS, Kumar PA (2012) Metabolomics in agriculture. OMICS 16:149–159

    Article  CAS  PubMed  Google Scholar 

  • Naqvi S et al (2009) Transgenic multivitamin corn through biofortification of endosperm with three vitamins representing three distinct metabolic pathways. Proc Natl Acad Sci U S A 106:7762–7767

    Article  PubMed  PubMed Central  Google Scholar 

  • Nicholson JK, Lindon JC, Holmes E (1999) “Metabonomics”: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 29:1181–1189

    Article  CAS  PubMed  Google Scholar 

  • Obayashi T et al (2009) ATTED-II provides coexpressed gene networks for Arabidopsis. Nucleic Acids Res. https://doi.org/10.1093/nar/gkn807

    Article  CAS  PubMed  Google Scholar 

  • Ogata Y et al (2010) CoP: a database for characterizing co-expressed gene modules with biological information in plants. Bioinformatics 26:1267–1268

    Article  CAS  PubMed  Google Scholar 

  • Okazaki Y et al (2009) A chloroplastic UDP-glucose pyrophosphorylase from Arabidopsis is the committed enzyme for the first step of sulfolipid biosynthesis. Plant Cell 21:892–909

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Pfeiffer T et al (1999) METATOOL: for studying metabolic networks. Bioinformatics:251–257

    Google Scholar 

  • Prakash CS, Egnin M (1997) Engineered Sweet potato (Ipomea batatas) plants with a synthetic protein storage gene show high protein and essential amino acid levels. Concurrent session 35. In: Dean JFD (ed) 5th International Congress of Plant Molecular Biology, 21–27 Sept, Singapore, Kluwer Academic Publishers

    Google Scholar 

  • Roberts CW et al (2002) The shikimate pathway and its branches in apicomplexan parasites. J Infect Dis 185(Suppl):S25–S36

    Article  CAS  PubMed  Google Scholar 

  • Saneoka H et al (1995) Salt tolerance of glycinebetaine-deficient and -containing maize lines. Plant Physiol 107:631–638

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Sasaki T, Burr B (2000) International rice genome sequencing project: the effort to completely sequence the rice genome. Curr Opin Plant Biol 3:138–141

    Article  CAS  PubMed  Google Scholar 

  • Schauer N et al (2006) Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement. Nat Biotechnol 24:447–454

    Article  CAS  PubMed  Google Scholar 

  • Schauer N et al (2008) Mode of inheritance of primary metabolic traits in tomato. Plant Cell 20:509–523

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Schilling CH, Palsson BO (2000) Assessment of the metabolic capabilities of Haemophilus influenzae Rd through a genome-scale pathway analysis. J Theor Biol 203:249–283

    Article  CAS  PubMed  Google Scholar 

  • Schilling CH, Edwards JS, Palsson BO (1999) Toward metabolic phenomics: analysis of genomic data using flux balances. Biotechnol Prog 15:288–295

    Article  CAS  PubMed  Google Scholar 

  • Schuster S, Fell DA, Dandekar T (2000) A general definition of metabolic pathways useful for systematic organization and analysis of complex metabolic networks. Nat Biotechnol 18:326–332

    Article  CAS  PubMed  Google Scholar 

  • Schwall GP et al (2000) Production of very-high-amylose potato starch by inhibition of SBE A and B. Nat Biotechnol 18:551–554

    Article  CAS  PubMed  Google Scholar 

  • Scott IM et al (2010) Enhancement of plant metabolite fingerprinting by machine learning. Plant Physiol 153:1506–1520

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Seressiotis A, Bailey JE (1986) MPS: an algorithm and data base for metabolic pathway synthesis. Biotechnol Lett 8:837–842

    Article  CAS  Google Scholar 

  • Simpson TW, Colon GE, Stephanopoulos G (1995) Two paradigms of metabolic engineering applied to amino acid synthesis. Biochem Soc Trans 23:381–387

    Article  CAS  PubMed  Google Scholar 

  • Smytha DA (1998) Some properties of starch branching enzyme from indica rice endosperm (Oryza sativa L.) Plant Sci 57:1–8

    Article  Google Scholar 

  • Souleyre EJF et al (2005) An alcohol acyl transferase from apple (cv. Royal Gala), MpAAT1, produces esters involved in apple fruit flavor. FEBS J 272:3132–3144

    Article  CAS  PubMed  Google Scholar 

  • Stephanopoulos G (1999) Metabolic fluxes and metabolic engineering. Metab Eng 1:1–11

    Article  CAS  PubMed  Google Scholar 

  • Sunita T, Ramadevi S (2004) In silico gene identification and homology modeling of chorismate synthase in clostridium difficile. Online J Bioinforma 5:129–131. 1443–50

    Google Scholar 

  • Swarbreck D et al (2008) The Arabidopsis information resource (TAIR): gene structure and function annotation. Nucleic Acids Res. https://doi.org/10.1093/nar/gkm965

  • The UniProt Consortium (2011) Ongoing and future developments at the universal protein resource. Nucleic Acids Res 39:D214–D219

    Article  CAS  Google Scholar 

  • Thimm O et al (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

    Article  CAS  PubMed  Google Scholar 

  • Tikunov Y et al (2005) A novel approach for nontargeted data analysis for metabolomics. Large-scale profiling of tomato fruit volatiles. Plant Physiol 139:1125–1137

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Tohge T et al (2005) Functional genomics by integrated analysis of metabolome and transcriptome of \emph{Arabidopsis} plants over-expressing an MYB transcription factor. Plant J 42:218–235

    Article  CAS  PubMed  Google Scholar 

  • Tokimatsu T et al (2005) KaPPA-view: a web-based analysis tool for integration of transcript and metabolite data on plant metabolic pathway maps. Plant Physiol 138:1289–1300

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Urano K et al (2009) Characterization of the ABA-regulated global responses to dehydration in Arabidopsis by metabolomics. Plant J 57:1065–1078

    Article  CAS  PubMed  Google Scholar 

  • Urbanczyk-Wochniak E, Sumner LW (2007) MedicCyc: a biochemical pathway database for Medicago truncatula. Bioinformatics 23:1418–1423

    Article  CAS  PubMed  Google Scholar 

  • Womble DD, Rownd RH (1986) Regulation of IncFII plasmid DNA replication. A quantitative model for control of plasmid NR1 replication in the bacterial cell division cycle. J Mol Biol 192:529–547

    Article  CAS  PubMed  Google Scholar 

  • Yonekura-Sakakibara K et al (2008) Comprehensive flavonol profiling and transcriptome coexpression analysis leading to decoding gene-metabolite correlations in Arabidopsis. Plant Cell 20:2160–2176

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zhang P (2005) MetaCyc and AraCyc. Metabolic pathway databases for plant research. Plant Physiol 138:27–37

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zhao X et al (2008) Extracellular Ca2+ regulating stomatal movement and plasma membrane K+ channels in guard cells of Vicia faba under salt stress. Acta Agron Sin 34:1970–1976

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Indian Council of Agricultural Research, National Bureau of Plant Genetic Resources, New Delhi, India

    Soma S. Marla & Neelofar Mirza

  2. Directorate of Knowledge Management Units (DKMU), ICAR, New Delhi, India

    K. D. Nadella

  3. Genetics division, ICAR, IARI, New Delhi, India

    K. D. Nadella

Authors
  1. Soma S. Marla
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Neelofar Mirza
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. K. D. Nadella
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Soma S. Marla .

Editor information

Editors and Affiliations

  1. Department of Biotechnology Apex Bioinformatics Centre, Ministry of Science & Technology, New Delhi, India

    Gulshan Wadhwa

  2. Department of Bioinformatics, Bharathiar University, Coimbatore, Tamil Nadu, India

    P. Shanmughavel

  3. Central Research Facility, Indian Institute of Technology Delhi, New Delhi, India

    Atul Kumar Singh

  4. Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai, India

    Jayesh R. Bellare

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Marla, S.S., Mirza, N., Nadella, K.D. (2018). Metabolic Pathway Analysis Employing Bioinformatic Software. In: Wadhwa, G., Shanmughavel, P., Singh, A., Bellare, J. (eds) Current trends in Bioinformatics: An Insight. Springer, Singapore. https://doi.org/10.1007/978-981-10-7483-7_10

Download citation

Publish with us

Policies and ethics

Search

Navigation