1. Maximise rate.

A primary function of the beads is to maximise reaction rate per bead volume; halving the radius of a sphere doubles its surface area:volume ratio. Many, small, bacteria-embedded agarose beads (to a technical limit) are therefore optimal, as the average bacterium is closer to the surface of each bead and being ‘used’ more efficiently. Substrate molecules which follow Brownian motion are more likely to collide with and be broken down by ‘outer’ bacteria. Similarly, on average, product molecules have a shorter path length to the surface and are likely to diffuse out faster:

Assuming ρ (a coefficient of bacterial density), to be independent of r (distance from bead center) and R (bead radius), avg. bacterium-surface distance =



Oxford iGEM 2014

2. Protect bacteria

For this system and others of its type, it is highly valuable to maximise local substrate concentration to the bacteria within the viable range of toxicity, especially while the viable concentration range to the strain remains a limitation to the breakdown rate (directly or indirectly).

In our case, the diffusion-limiting polymer chosen was cellulose acetate (as its synthesis from cellulose is straightforward and safe) for which we modeled diffusion data for variable polymer thickness (see below). Acetylation stoichiometry or even polymer type entirely, polymer density and methods of bead coating are among many variables that can be further researched and optimised for desirable diffusion coefficients.

As bacteria need direct access to water, yet DCM is water-soluble only up to ~200mM, for limited water-solubility substrates, as part of future research, we propose suspending beads at the interface of a biphasic mixture of the two by exploiting differences in density. In such a system, the immediate substrate ‘reservoir’ is essentially maximised.

For the purposes of this project we opted to construct beads less dense than water, as the aqueous DCM concentration of the biphasic system is more reliable, and we had yet to establish the robustness of the diffusion-limiting system to external fluctuations in [DCM].

3. Physically containing bacteria.

Surrounding bacteria-embedded agarose beads in a diffusion limiting polymer acts as a secondary safeguard to an envisioned genetic killswitch.

It is for ease of use in practice, and this point, that macroscopic beads containing ~10^7 bacteria, rather than attempting to encapsulate individual cells, are conceptually preferred.

Acetylation of cellulose was carried out via Acetyl Chloride esterification, based on methodology by Org. Lett., 2005, 7, 1805-1808. 1cm diameter agarose spheres were then passed through a thin film of the polymer to coat:





The volatility and poor visible absorption of DCM posed a challenge in measuring rates of diffusion though the polymer. We decided to base our modelling on the diffusion of indigo dye from within prepared beads, collecting the following spectrophotometric absorption data:

Alongside the experimental absorption data (red) we have plotted our theoretical lines of best fit. Because we predicted that system behaviour would be governed by Fick’s law, which states that:

i.e. that mass flux is proportional to a concentration gradient, we then predicted that the response of our system would follow the classic exponential asymptotic approach to a maximum value where the concentrations of dye both inside and outside the system were equal.

Thus our lines of best fit take the form:

φ = average concentration outside bead (g/ml)

A = equilibrium concentration (g/ml)

k = variable dictating rate of approach to equilibrium (min^-1)

t = time (min)

The value of k in each system was obtained through our parameter fitting algorithm.

Our results are tabulated below:

From these experiments we could conclude that the polymer coating was indeed diffusion limiting through two simultaneous effects. Firstly, the rate at which the system reaches equilibrium concentration i.e. defined by the variable k which is itself a function of bead surface area, polymer diffusivity and coating thickness, is reduced in each of the systems. Furthermore, the maximum concentration reachable at the equilibrium point is itself a function of the thickness of the coating and decreases as the polymer thickness increases.

Step 1: Designing and visualising the biosensor

To further explore coating thickness – diffusion rate relationship, we used analogous relationships developed for heat diffusion. This is done because the fundamental laws governing mass and heat diffusion are of a similar form; they are both driven by gradients – concentration and temperature respectively:

Step 2: Constructing the components in 123D Design

To construct the complicated shape of the biosensor housing, we had to 3D print two halves of the biosensor individually so that we could have hollow sections. This is because 3D printers can’t easily construct anything that isn’t fully supported. This is the one major drawback of this type of rapid prototyping. The files of this construction are shown below.



Therefore, when we 3D printed the cartridge, we couldn’t go for the fancy designs that are shown above in SolidWorks. Therefore we had to opt for a much more linear design. The files of this construction are shown below.



These files were then transferred into Meshmixer . This planned out the actual printing of the components and performed certain useful features such as strength analysis to allow us to spot any large weaknesses before printing took place.

Step 3: Finished product

Pictures of the finished biosensor are shown below. The idea is that this biosensor can then be used as a very cheap sensor that can give a basic binary answer to the question ‘is there a safe level of chlorinated solvents present?’ This safe level will ideally be the 5ppm that is the maximum safe level for drinking water in the UK.

Oxford iGEM 2014