Team:Wageningen UR/project/model overview

Modeling Overview

The performance of BananaGuard as biological control agent is defined three factors: its ability to destroy fusarium upon detection, the stability and performance of the genetic circuit and its ability to compete with other micro-organisms in the soil. The ability to destroy fusarium has be tested in vitro. This leaves the remaining two questions to be answered. For the performance and stability of the genetic circuit two perspectives were considered. An a priori design of the Kill-switch was modeled aiming to optimize its stability. Including different parts of the genetic circuit the optimized version was subsequently modeled over time . This allowed for the quantification and characterization of the stability and performance of the BananaGuard system. Before this quantification could be done however a parameter was needed. This parameter was provided in the process of answering the competitiveness query. In total three models were made:

(II) To ascertain our hosts competitiveness the rate of cell division needs to be investigated on a metabolic level. Cell growth rate is a key factor in the competition between our engineered Pseudomonas putida and the wildtype P. putida found in the rhizosphere of the banana plant roots[1,2]. The integrated genetic circuit uses metabolic resources that would otherwise be dedicated to cellular maintenance or growth. Should this divergence of resources be too large our host will be out competed. A genome scale metabolic model was extended, investigating and outlining the price that has to be paid for introducing our synthetic genes on a metabolic level. The resulting average growth rate has been used in the stochastic model.

(III) A stochastic model was made in order to quantify and characterize the stability and performance of the introduced genetic circuit. The model takes into account growth rates predicted by the metabolic model, cell division, the anti-gene transfer toxin antitoxin systems effect on cell growth and the kill-switch.

Key results

Promoter Design

Before the optimal configuration of repressor binding sites could be determined, the behaviour of the system had to be assigned scores representing a functioning or non-functioning toggle switch. Clustered, three different behaviours could be identified:

In total eight different configurations of repressor binding sites that were tested (Figure 1).Two, F and H, were found to be moderately robust towards variations in binding strengths and production rates. H was chosen as a base to design new promoters for the kill-switch. Biologically it meant there be two TetR repressor binding sites on the LacI promoter, two LacI and one CIλ repressor binding site on the TetR promoter and Two TetR one CIλ repressor binding site in for the toxin promoter

More information and results of promoter design can be found here

Cost

To check if BananaGuard is still viable in its resting and active state (activated by fusaric acid), a comparison was made between BananaGuard and the wild type P. Putida. The results of this comparison indicates the impact of the synthetic pathway on its metabolism and the metabolic stress when anti-fungal production has been activated. To get the most realistic approach the carbon composition and ratio of the banana roots exudates are used. Figure 1 depicts how BananaGuard compares to the wild type P. Putida depending on the carbon uptake rate. For bacteria in the rhizosphere of the banana roots a carbon uptake rate of 4 mmol gDW^-1hr^-1 is expected. This shows a growth rate of >99% compared to the wild type for the resting state and still over 50% for the active state. This indicates that BananaGuard is not outcompeted by other rhizosphere-populating microorganisms and that metabolic stress is not a bottleneck for the production of anti-fungals in our activated system.

More information and results of the system cost can be found here

Performance

Overall the results derived from the stochastic model indicates a large distribution of division times in the population. These distributions can be attributed to the free toxins in the cell caused by stochastic fluctuations in the native toxin antitoxin system and a varying basal production rate on the kill-switch. Figure 3.A indicates that a basal CIλ production rate of 50nM or higher will be devastating to the stability of the genetic circuit in a large portion of the population. The long division times caused by the leaking toxins which in turn is caused by the slow CIλ build-up, result in the kill-switch to change state. Figure 3.B shows that slower growth rates activate the system more efficiently because CIλ is not diluted as much. Given the growth rate obtained from the metabolic model an activation efficiency of 98% is achieved. This means that the vast majority of our reengineered P. putida population will activate in the soil according to the model.

More information and results about the stability and performance of the system can be found here

Implications for the experimentalist and the system

Promoter Design: The statistical mechanics model has led to the experimentalists decision to opt for a new set of designed promoters and build two kill-switches in parallel. The model has predicted the newly designed promoters to have a higher stability. These needs to be verified experimentally.

Cost: To check if BananaGuard is still viable in its resting and active state (activated by fusaric acid), a comparison was made between BananaGuard and the wild type P. Putida. The results of this comparison indicates the impact of the synthetic pathway on its metabolism and the metabolic stress when anti-fungal production has been activated. The results for both the resting and active state show that BananaGuard is not outcompeted by other rhizosphere-populating microorganisms and that metabolic stress is not a bottleneck of the anti-fungal production relatively. This means that for our application it is not necessary to change the proteins in the kill switch or produce less or different anti-fungals.
The calculated growth rate for BananaGuard for a doubling time of 3 h^-1 for the wild type P. Putida is used to calculate the system performance.

Performance: The results have shown that leakiness of promoters on the input/output plasmid (CIλ and Zeta-toxin) can be detrimental to the performance of our reengineered P. putida. A point of attention when the entire system is tested.

The activation of our system is limited by the production of CIλ and not the influx of fusaric acid. The fusaric acid detection experiments has shown the fusaric acid dependent promoter to be activated with a limited amount of fusaric acid present. The activation occurs more efficiently if the cell growth rate is low. This means that it is highly probable that the majority of BananaGuards population will activate given a generally slower growth rate in stressful environments