"
Team:Cambridge/Project/DesignProcess
From 2012.igem.org
Contents |
Design Process
Every good design process must have a clear aim. Ours was about taking a step towards realising the full potential of already well-characterised parts, in this case biosensors, by developing a prototype kit which could be used in real-world applications effectively and practically. In other words, engineering user-friendly products from biobricks, aimed at the end user. Our team realised the potential of the plethora of characterised biobricks found in the registry, not only for the distant future but for today by providing humanity with new, useful, biological products.
Market Research
Goals
As stated in our project aims and justified by the market reasearch above we wanted to develop a standard for biosensors that is reliable, affordable, portable, open-source, accessible and relevant. These different attributions require a little more discussion before a formal Design process can begin. The formal design goals for our project are the development of:
- an output that is reliable, reproducible and most importantly quantitative.
- robust, standard platform for biosensing inputs.
- a system for storage and distribution of biosensors for straightforward use in multiple applications.
- a system that is rooted in real world applications that can bring about a positive change in the world
Systems
Inputs
It's common sense that with out a reliable input system, output systems, however robust, cannot be relied upon to give meaningful results. It is therefore important that any input used for a biosensor is well characterised (with response curves) under different conditions. However, for an effective revolution in biosensing we would also like a standard platform for sensing a multitude of analytes. This would allow for better characterisation and all additional information about function under different conditions to be acquired with one less parameter that needs to be changed. We would also like the response curves to be relatively linear across a wide range such that different toxicity thresholds are detectable under the same system. We would also like a system that could be designed "from scratch" in future such that there is no need for an existing sensing mechanism in an organism to be found before implementation in a biosensor can take place. The input must therefore have the following attributes:
- A decoupling between the sensing mechanism and it's interface with the outputs system
- A highly specific analyte detection part
- An output regulation system that is highly proportional to the concentration of analyte present.
- The ability to be designed for specific analytes in a methodical way that could be assisted with software tools
Processing
As all biosensors currently in the registry only use a single output to relay information about the concentration of an analyte, there is great potential for cell growth phase, density, culture inhomogeneity and productivity to vary between assays and this often leads to poorly reproducible and unreliable results. We therefore desire some processing to be performed (without specifying where in the whole system yet) that factors these variables in and allows for a much more accurate readout. With accuracy also comes the ability to provide numerical readouts provided that the output system is geared up for this purpose. We also desire an ability to tune the circuit based on what range of input concentrations we are looking at such that high accuracy can be achieved. The processing system must therefore have the following attributes:
- The ability to compensate for culture variability between assays
- The ability to make calculations over a wide range of concentrations with similar, high levels of precision across this range.
Outputs
In order for commercial success of a project that fits our goals it is absolutely vital that an accurate, quantitative, robust and flexible output exists to relay information to a user that is an accurate representation of the processed input. Outputs fitting this description are commonplace in nearly all other scientific fields where the ability to collect and process data has not only eased interpretation of experiments but also allowed a much faster development of understanding and ultimately technology in those fields. in biology, however, due to the complexity of the systems under scrutiny, it has been difficult to design such outputs and where methods have been found they are normally very expensive. We therefore desire an output with the following characteristics:
- Provides reproducible, quantitative data under many environmental conditions with small error margins.
- Displays data to a user in an intuitive manner that is easy to interpret.
- Be flexible to support use in multiple environments
- Does not require specific environmental domains to leave an undistorted post-processing signal.
- Easy to interface with data processing tools
- The ability to provide support multiple readouts from different assays.
- Cheap
Storage & Distribution
If our project is to have any meaning or impact on sensing applications, suitable plans and design considerations must be in place such that our biosensing platform can be packaged and distributed easily and cheaply, whether it be for high tech testing purposes or field applications in places lacking appropriate infrastructure for e.g. cooling, large or electrical currents.
Detailed investigations
Inputs - Detailed
Processing - Detailed
Outputs - Detailed
Storage & Distribution - Detailed
Solution
We will now try to demonstrate how the developments we have made during our project have tackled the aims we set out to fulfil - within the constraints of a single summer long project run by undergraduates of course!
RiboSense
Ratiometrica
Luciferase and instrumentation
here]]. Below video showing our instrumentation in action can be seen.
