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<p class="about-para"><font size="3">17.Borek E, Ponticorvo L, & Rittenberg D (1958) Protein turnover in microorganisms. Proceedings of the National Academy of Sciences 44(1):369-374.</p> | <p class="about-para"><font size="3">17.Borek E, Ponticorvo L, & Rittenberg D (1958) Protein turnover in microorganisms. Proceedings of the National Academy of Sciences 44(1):369-374.</p> | ||
− | <p class="about-para"><font size="3">Attributions: Frank Eardley, Luke Waller, Umar Farooq</p> | + | <p class="about-para"><font size="3"><b>Attributions: Frank Eardley, Luke Waller, Umar Farooq/<b></p> |
Revision as of 11:13, 21 September 2018
Alternative Roots
Naringenin Pathway
RATIONALE & AIM
We have chosen to use Pseudomonas fluorescens (DSM 25356) as a chassis organism due to its rapid and abundant colonisation abilities within the rhizosphere. To ensure P. fluorescens can colonise effectively, the metabolic load and resource drain of our system on the cell must be kept to a minimum in order to conserve natural homeostasis and minimise waste. As our system utilises enzymes found in flavonoid production, our naringenin synthesis pathway will be most taxing on resources used to maintain the natural homeostasis of flavonoid pathways. Some of these resources (ATP, CoA and Malonyl CoA, for example) are included but not restricted to flavonoid production. If we are to program a cell to produce an amount of naringenin per unit time, we need to consider what range of output works best in terms of maintaining the cells homeostasis.
On top of maintaining the cells homeostasis, sufficient naringenin needs to be produced by the pathway to attract the desired nitrogen fixing bacteria. The results of our chemotaxis experiments and previous research have shown higher concentrations of naringenin to inhibit growth of multiple soil microbes (1). It is therefore important that production by our system is stable in variable environmental conditions such that there are no detrimental effects on the rhizosphere community. By creating an enzymatic model of the pathway, we aimed to alter the operon design in order to minimise resource drain and stabilise naringenin production as a means of increasing system optimisation and robustness.
The chemotaxis modelling and wetware element to our project characterise the production rate of naringenin required for chemotaxis to occur. When the production rates of naringenin by our endophytic chassis have been characterised, the pathway model will give us the tools to alter the operon in order to optimise production.
BACKGROUND
The core of the model uses enzymatic turnover rates (Kcat) to simulate the relative rate (molecules per second) of conversion from substrate to product for each enzymatic reaction in the pathway. Each reaction is split into two parts, formation of the enzyme substrate complex (Substrate binding) and conversion of the complex to the reaction products (Catalysis). The formation of the substrate enzyme complex is reversible whilst the conversion of the complex to the reaction products is not. In the case of 4CL and CHS, for which more than one substrate is required for catalysis of the product, additional steps are coded as separate reversible reactions to emulate these circumstances.
MODEL DESIGN
Core Enzyme Kinetics
Naringenin, our chemoattract of choice, is synthesised from L-tyrosine via the enzymatic action of tyrosine ammonia lyase (TAL), 4-coumarayl ligase (4CL), chalcone synthase (CHS) and chalcone isomerase (CHI) (Figure1). These four enzymes are contained within the iGEM part BBa_1497017. Within this part all four enzymes are under the control of a single strong T7 promoter (BBa_I712074), with each enzyme having the same strong RBS (BBa_B0034). This system gives equal expression of each of the four enzymes. Previous research has identified that changing relative expression of each enzyme in the pathway improved naringenin production (2). We intended to optimise our system by using a model to explore how we could redesign the operon in order to maximise flux through the pathway whilst minimising resource consumption and waste.
The model was built on Matlab using differential equations which employ mass action kinetics to describe the behaviour of reactants and products for each reaction step. Mass action kinetics describes the behaviour between a substrate and reactant as an equation where the velocity or rate of a chemical reaction is directly proportional to the concentration of the reactants. These kinetics are used for substrate binding in which substrate and enzyme diffuse towards each other to dimerise via the formation of a covalent bond, and catalysis in which the covalent bond breaks to produce two or more products (excluding the reverse reaction of substrate binding which represents failed substrate binding).
Mass Action kinetics are used due to the fact that we have not fully characterised all aspects of molecular biology with respect to enzyme mechanics. Mass action kinetics are also deterministic in contrast to the stochastic nature of biochemical systems. Deterministic models don’t account for the variety of outcomes that can occur when a low molecular count is used as the probability of collision changes under low molecular counts due to the fact that conversion become event dependant and not rate dependant (5).
Enzymatic rates were obtained from literature via the BRENDA enzyme database (6). Enzymatic rates from the origin species of each gene in the operon were used and are displayed in Table 1. Where more than one figure was available, the most cited value was used. The CHI enzyme in the operon originates from Gerbera sp. No rates were identified from this species so the only available rate from Eubacterium rumulus was used.
Table 1. KM constant for each substrate of the four enzymes coded for by the naringenin synthesis operon BBa_1497017 and the source literature used to identify each value.
REFERENCES & Attributions
1.Kumar S & Pandey AK (2013) Chemistry and Biological Activities of Flavonoids: An Overview. The Scientific World Journal 2013.
2.Santos CNS, Koffas M, & Stephanopoulos G (2011) Optimization of a heterologous pathway for the production of flavonoids from glucose. Metabolic Engineering 13(4):392-400.
3.Vannelli T, Wei Qi W, Sweigard J, Gatenby AA, & Sariaslani FS (2007) Production of p-hydroxycinnamic acid from glucose in Saccharomyces cerevisiae and Escherichia coli by expression of heterologous genes from plants and fungi. Metabolic Engineering 9(2):142-151.
4.Fowler Z & Koffas M (2009) Biosynthesis and biotechnological production of flavanones: current state and perspectives. Applied Microbiology and Biotechnology 83(5):799-808.
5.Sayikli C & Bagci EZ (2011) Limitations of Using Mass Action Kinetics Method in Modeling Biochemical Systems: Illustration for a Second Order Reaction (Berlin, Heidelberg: Springer Berlin Heidelberg, Berlin, Heidelberg) pp 521-526.
6.Placzek S, et al. (2017) BRENDA in 2017: new perspectives and new tools in BRENDA. Nucleic acids research 45(D1):D380.
7.Xue Z, McCluskey M, Cantera K, Sariaslani F, & Huang L (2007) Identification, characterization and functional expression of a tyrosine ammonia-lyase and its mutants from the photosynthetic bacterium Rhodobacter sphaeroides. Official Journal of the Society for Industrial Microbiology 34(9):599-604.
8.Ehlting J, et al. (1999) Three 4-coumarate:coenzyme A ligases in Arabidopsis thaliana represent two evolutionarily divergent classes in angiosperms. Plant Journal 19(1):9-20.
9.Stuible HP, Büttner D, Ehlting J, Hahlbrock K, & Kombrink E (2000) Mutational analysis of 4‐coumarate:CoA ligase identifies functionally important amino acids and verifies its close relationship to other adenylate‐forming enzymes. FEBS Letters 467(1):117-122.
10.Hess V, Vitt S, & Muller V (2011) A Caffeyl-Coenzyme A Synthetase Initiates Caffeate Activation prior to Caffeate Reduction in the Acetogenic Bacterium Acetobacterium woodii. The Journal of Bacteriology 193(4):971.
11.Ozeki Y, et al. (1985) Purification and some properties of chalcone synthase from a carrot suspension culture induced for anthocyanin synthesis and preparation of its specific antiserum. Journal of biochemistry 98(1):9.
12.Herles C, Braune A, & Blaut M (2004) First bacterial chalcone isomerase isolated from Eubacterium ramulus. Archives of Microbiology 181(6):428-434.
13.Clancy S (2008) DNA Transcription. Nature Education 1(1):41.
14.Young R & Bremer H (1976) Polypeptide-chain-elongation rate in Escherichia coli B/r as a function of growth rate. The Biochemical journal 160(2):185.
15.Lodish HF (2016) Molecular cell biology (New York : W.H. Freeman Macmillan Learning) Eighth edition..; Global edition.. Ed.
16.Bernstein JA, Khodursky AB, Lin P-H, Lin-Chao S, & Cohen SN (2002) Global Analysis of mRNA Decay and Abundance in Escherichia coli at Single-Gene Resolution Using Two-Color Fluorescent DNA Microarrays. Proceedings of the National Academy of Sciences of the United States of America 99(15):9697-9702.
17.Borek E, Ponticorvo L, & Rittenberg D (1958) Protein turnover in microorganisms. Proceedings of the National Academy of Sciences 44(1):369-374.
Attributions: Frank Eardley, Luke Waller, Umar Farooq/