Team:Toronto/Demonstrate

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Demonstrate

Solid phase separation is important in many waste water processing contexts. In many practical industrial contexts, large volumes of water must be processed. Typical methods are largely mechanical (e.g. centrifugation) which are energy inefficient and costly. Even alternative methods like reverse osmosis require pressurization, which can require a great deal of energy for large volumes. Our Policy and Practices Team identified the need for a renewable, energy efficient bioremediation technique within the industries of mining operations and wastewater treatment plants. Developing a biological platform for solid phase extraction was the main goal of our project.

In this project, we explored the application of gas vesicles as a synthetic biology tool for bioremediation. Inspired by promising results from Bordeau et al., who noticed cellular flotation when investigating a synthetic gas vesicle construct for ultrasound imaging. Previous iGEM teams’ experimental results from genetic modification of E. coli cells to express gas vesicles and perform floatation has been inconsistent and inconclusive. To our knowledge, there has been no scientific research or experimentation, outside of iGEM, that optimizes the protocol for cellular floatation in the context of bioremediation.

One of the main goals of our team was to develop an optimized flotation assay for ARG1 in BL21(DE3) strain of E. coli. A secondary goal was to definitively observe cellular flotation. In order to do this, making use of the flotation assay, BL21(DE3) with ARG1 was induced in a 50ml centrifuge tube, and in a second 50ml centrifuge tube the same strain was added but not induced. These tubes were left for 25 hours and then OD600 readings on 1ml aliquots from the surface of each tube were taken over the span of an hour. OD600 measurements from the induced sample were significantly higher than that of the uninduced sample. For more information on the protocol see buoyancy assay (link to protocols page). We used a two-sample t-test to check whether the mean of the induced and uninduced cultures significantly differed. The null hypothesis was that there is no difference between the two samples, while the alternative hypothesis was that there is a difference. With a p-value of p = 0.000027, alpha = 0.01 and n = 28, we were able to reject the null hypothesis in favour of the alternative hypothesis. Our conclusion from this data is that the higher OD600 from the surface aliquots in the induced sample resulted due to buoyancy from gas vesicle expression caused flotation. Ideally, we wanted to create an optimized system that could be applicable to multiple waste water processing contexts involving bioremediation. This is particularly emulated by our dry lab’s bioreactor model. This model is modular in that it has many adjustable parameters that can be set based on empirical values pertaining to different bioremediation tasks (e.g. the rate constant for binding of particles to engineered cell surface receptors), allowing for prediction of efficiency and performance for many different bioremediation tasks.

Based on the results of our differential bioreactor model, we postulate that a bioreactor of this design could perform at appropriately small time-scales with a sufficiently optimized flotation construct in a bioremediation context. This is useful for model validation, and proof of concept. This bodes well for future laboratory endeavours where the bioreactor schema along with an engineered cell-line optimized for flotation from gas vesicle formation could be tested in a small scale laboratory model of the system to test its empirical performance. For future application-based analysis using the bioreactor model, Goempertz coefficients could be determined for a biomass of industrially relevant size for the volume demands dictated by the industry requiring bioremediation using a similar experimentation and analysis technique as described in the Growth Dynamics section (link to models page). We also designed a stochastic temporal tracking algorithm to acquire real flotation data (images) to estimate the buoyant force for ARG1 and compare different modifications of ARG1 to determine an optimal gene combination for flotation. To further enrich the analysis of the behaviour of the biomass in the bioreactor model, in addition to the existing sensitivity analysis, identification and characterization of stable points resulting from different combinations of parameter values (like maximum carrying capacity of biomass) could be performed to model a system where biomass performs functions like binding to organic or inorganic molecules of interest, before floatation based separation.

The theoretical framework built by our team can be used in the future to test and produce an effective and efficient bioremediation method that far surpasses conventional methods in use today. This innovative approach to facing waste water provides the world with a more independence and variety in the compounds that can be extracted. As global water security is becoming a pressing concern, our project is relevant to both issues facing our local communities and the entire world as a whole.