Abstract
The search of an alternative is always a major concern of human for sustaining life effectively. The green flora described by the agriculture is the source of many such life attaining processes and products that are essential for human population. In addition to this, the constantly growing number of Homo sapiens has to be fed with increase yield of agriculture products. To meet the demands of growing population and relieve the pressure of yield, the use of fertilizers comes into action, while the constant use of chemical fertilizers has deteriorated the heath of soil, environment, and human collectively calling “phytobiome.” Thus, the urge of finding alternatives to replace the toxic chemical fertilizers has given a way to search exhaustively the naturally occurring microbiomes for their beneficial effect on the agri-flora. Moreover, the available advancements in the computational and system-level approaches with omics data have provided us the genomes and also genome-level metabolic models for many beneficial/effective bacteria. The naturally synthesized metabolites (primary and secondary) can be easily exploited nowadays for any intended use in the fields as inoculants or bio fertilizers. In addition the available kinetic model has paved the way to commercially synthesize desired metabolite (through amendments in pathway either genetic or environmental) on large scale as biofuels, etc. Despite of these advances, several challenges still coexist with approaches that have to be exploited in the near future. Some of the challenges have been discussed in present work with a brief account of in silico kinetic models available.
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References
Alberts B, Johnson A, Lewis J, Raff M, Roberts K, Walter P (2002) Molecular biology of the cell, 4th edn. Garland Science (Taylor & Francis Group), New York
Ao P, Lee LW, Lidstrom M, Yin L, Zhu XM (2008) Towards kinetic modeling of global metabolic networks with incomplete experimental input on kinetic parameters. arXiv preprint arXiv:0808.0220
Babalola OO (2010) Beneficial bacteria of agricultural importance. Biotechnol Lett 32:1559–1570
Babalola OO, Sanni AI, Odhiambo GD, Torto B (2007) Plant growth-promoting rhizobacteria do not pose any deleterious effect on cowpea and detectable amounts of ethylene are produced. World J Microbiol Biotechnol 23(6):747–752
Blazeck J, Alper H (2010) Systems metabolic engineering: genome-scale models and beyond. Biotechnol J 5(7):647–659
Burns RG (2010) Albert Rovira and a half-century of rhizosphere research. In: Proceedings of the Rovira rhizosphere symposium, p 1
Chance B (1943) The kinetics of the enzyme substrate compound of peroxidase. J Biol Chem 151(2):553–577
Chassagnole C, Raïs B, Quentin E, Fell DA, Mazat JP (2001) An integrated study of threonine pathway enzyme kinetics in escherichia coli. Biochem J 356(Pt 2):415–423
Chassagnole C, Noisommit Rizzi N, Schmid JW, Mauch K, Reuss M (2002) Dynamic modeling of the central carbon metabolism of Escherichia coli. Biotechnol Bioeng 79(1):53–73
Csete M, Doyle J (2004) Bow ties, metabolism and disease. Trends Biotechnol 22(9):446–450
Dhar P, Meng TC, Somani S, Ye L, Sairam A, Chitre M, Hao Z, Sakharkar K (2004) Cellware-a multi-algorithmic software for computational systems biology. Bioinformatics 20(8):1319–1321
Doornbos RF, van Loon LC, Bakker PA (2012) Impact of root exudates and plant defense signaling on bacterial communities in the rhizosphere. A Rev Agron Sustain Dev 32(1):227–243
Egamberdieva D (2008) Plant growth promoting properties of rhizobacteria isolated from wheat and pea grown in loamy sand soil. Turk J Biol 32(1):9–15
ElMansi EMT, Dawson GC, Bryce CFA (1994) Steady-state modelling of metabolic flux between the tricarboxylic cycle and the glyoxylate bypass in Escherichia coli. CABIOS (now Bioinformatics) 10(3):295–299
Funahashi A, Matsuoka Y, Jouraku A, Morohashi M, Kikuchi N, Kitano H (2008) Cell designer 3.5: a versatile modeling tool for biochemical networks. Proc IEEE 96(8):1254–1265
Galazzo JL, Bailey JE (1990) Fermentation pathway kinetics and metabolic flux control in suspended and immobilized saccharomyces cerevisiae. Enzym Microb Technol 12(3):162–172
Higa T (1991) Effective microorganisms: a biotechnology for mankind. In: Parr JF, Hornick SB, Whitman CE (eds) Proceedings of the first international conference on Kyusei Nature Farming. U.S. Department of Agriculture, Washington, DC, pp 8–14
Higa T (1994) Effective microorganisms: a new dimension for nature farming. In: Parr JR, Hornick SB, Simpson ME (eds) Proceedings of the second international conference on Kyusei Nature Farming. U.S. Department of Agriculture, Washington, DC, pp 20–22
Higa T, Wididana GA (1991a) The concept and theories of effective microorganisms. In: Parr, Hornick SB, Whitman CE (eds) Proceedings of the first international conference on Kyusei Nature Farming. U.S. Department of Agriculture, Washington, DC, pp 118–124
Higa T, Wididana GA (1991b) Changes in the soil microflora induced by effective microorganisms. In: Parr JF, Hornick SB, Whitman CE (eds) Proceedings of the first international conference on Kyusei Nature Farming. U.S. Department of Agriculture, Washington, DC, pp 153–162
Hoefnagel MHN et al (2002) Metabolic engineering of lactic acid bacteria, the combined approach: kinetic modelling, metabolic control and experimental analysis. Microbiology 148(Pt 4):1003–1013
Hoops S, Sahle S, Gauges R, Lee C, Pahle J, Simus N, Singhal M, Xu L, Mendes P, Kummer U (2006) COPASI-a complex pathway simulator. Bioinformatics 22(24):3067–3074
Hynne F, Danø S, Sørensen PG (2001) Fullscale model of glycolysis in Saccharomyces cerevisiae. Biophys Chem 94:121–163
Ishii N, Robert M, Nakayama Y, Kanai A, Tomita M (2004) Toward large scale modeling of the microbial cell for computer simulation. J Biotechnol 113:281–294
Jamshidi N, Palsson BO (2008) Formulating genome scale kinetic models in the postgenome era. Mol Syst Biol 4:171
Kaymak HC, Guvenc I, Yarali F, Donmez MF (2009) The effects of bio-priming with PGPR on germination of radish (Raphanus sativus L.) seeds under saline conditions. Turk J Agric For 33(2):173–179
Klipp E et al (2005) Integrative model of the response of yeast to osmotic shock. Nat Biotechnol 23(8):975–982
Knudsen M, Sondergaard D, Tofting-Olesen C, Hansen FT, Brodersen DE, Pedersen CN (2015) Computational discovery of specificity-conferring sites in non-ribosomal peptide synthetases. Bioinformatics. https://doi.org/10.1093/bioinformatics/btv600
Kumar KV, Srivastava S, Singh N, Behl HM (2009) Role of metal resistant plant growth promoting bacteria in ameliorating fly ash to the growth of Brassica juncea. J Hazard Mater 170(1):51–57
Ma H, Zeng AP (2003) Reconstruction of metabolic networks from genome data and analysis of their global structure for various organisms. Bioinformatics 19(2):270–277
Morgan JAW, Whipps JM (2000) Methodological approaches to the study of rhizosphere carbon flow and microbial population dynamics. In: The rhizosphere: biochemistry and organic substance at the soil-plant interface: biochemistry and organic substance at the soil-plant interface, p 373
Parr JF, Hornick SB, Kaufman DD (1994) Use of microbial inoculants and organic fertilizers in agricultural production. In: Proceedings of the international seminar on the use of microbial and organic fertilizers in agricultural production. Published by the Food and Fertilizer Technology Center, Taipei, Taiwan
Phytobiomes: A Roadmap for Research and Translation (2016) American Phytopathological Society, St. Paul. www.phytobiomes.org/roadmap
Rizzi M et al (1997) In vivo analysis of metabolic dynamics in Saccharomyces cerevisiae: Ii. Mathematical model. Biotechnol Bioeng 55:592–608
Sauro HM, Hucka M, Finney A, Wellock C, Bolouri H, Doyle J, Kitano H (2003) Next generation simulation tools: the systems biology workbench and BioSPICE integration. Omics A J Integr Biol 7(4):355–372
Schallau K, Junker BH (2010) Simulating plant metabolic pathways with enzyme-kinetic models. Plant Physiol 152(4):1763–1771
Schmidt H, Jirstrand M (2006) Systems biology toolbox for matlab: a computational platform for research in systems biology. Bioinformatics 22(4):514–515
Selkov EE (1968) Self oscillations in glycolysis. Eur J Biochem 4:79–86
Slepchenko BM, Schaff JC, Macara I, Loew LM (2003) Quantitative cell biology with the virtual cell. Trends Cell Biol 13(11):570–577
Teusink B et al (2000) Can yeast glycolysis be understood in terms of in vitro kinetics of the constituent enzymes? Testing biochemistry. Eur J Biochem 267(17):5313–5329
Tomita M, Hashimoto K, Takahashi K, Shimizu TS, Matsuzaki Y, Miyoshi F, Saito K, Tanida S, Yugi K, Venter JC, Hutchison CA 3rd (1999) E-CELL: software environment for whole-cell simulation. Bioinformatics (Oxford, England) 15(1):72–84
Vaseghi S, Baumeister A, Rizzi M, Reuss M (1999) In vivo dynamics of the pentose phosphate pathway in Saccharomyces cerevisiae. Metab Eng 1(2):128–140
Weber T, Kim HU (2016) The secondary metabolite bioinformatics portal: computational tools to facilitate synthetic biology of secondary metabolite production. Synth Syst Biotechnol 1:69–79
Wiechert W, Takors R (2004) Validation of metabolic models: concepts, tools, and problems. In: Kholodenko BN, Westerhoff HV (eds) Metabolic engineering in the post genomic era. Horizon Bioscience, UK, pp 277–320
Wolf J, Passarge J, Somsen OJG, Snoep JL, Heinrich R, Westerhoff HV (2000) Transduction of intracellular and intercellular dynamics in yeast glycolytic oscillations. Biophys J 78:1145–1153
Wright BE, Albe KR (1994) Carbohydrate metabolism in Dictyostelium discoideum: I. model construction. J Theor Biol 169(3):231–241
Wright J, Wagner A (2008) The systems biology research tool: evolvable open source software. BMC Syst Biol 2:55
Wright B, Simon W, Walsh T (1968) A kinetic model of metabolism essential to differentiation in Dictyostelium discoideum. Proc Natl Acad Sci 60:644–651
Wright BE, Butler MH, Albe KR (1992) Systems analysis of the tricarboxylic acid cycle in dictyostelium discoideum. i. The basis for model construction. J Biol Chem 267(5):3101–3105
Zahir ZA, Munir A, Asghar HN, Shaharoona B, Arshad M (2008) Effectiveness of rhizobacteria containing ACC deaminase for growth promotion of peas (Pisum sativum) under drought conditions. J Microbiol Biotechnol 18(5):958–963
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We wish to thank all the authors for helpful discussions and for preparation of figures. SA is supported by ICMR-SRF.
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Ali, M., Ali, S., Ishrat, R. (2018). In Silico Biochemical Pathways for Bacterial Metabolite Synthesis. In: Choudhary, D., Kumar, M., Prasad, R., Kumar, V. (eds) In Silico Approach for Sustainable Agriculture. Springer, Singapore. https://doi.org/10.1007/978-981-13-0347-0_14
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