IGEM:IMPERIAL/2007/Cell By Date/Design
Cell by Date
This is the main page for Cell By Date 2 this page will be split up into various sections in the future.
1. Our Target : Beef
We all know that beef goes off. The dominant organisms leading to the spoilage of beef depend of the beef's composition and the environmental conditions under which the beef is stored. For refrigerated packaged beef Pseudomonas spp. were dominate areobically while Lactobacillus was dominant anaerobically. (12.Labuza,1993)
There also seems to be a general rule for beef that when the bacterial count reaches 10^7cm^-2 , off odours and slime production occour and the beef is considered off. (13.Food Hygiene,Microbiology and HACCP)&(10.Leak,1999)
The Gompertz's model is widely used when considering beef spoilage as it has been shown to fit growth data very well(12.Labuza,1993). Using the Gompertz model we can get the specific growth rate, Lag phase duration (LPD) and maximum population density (MPD) for bacterial growth at a particular constant temperature. And then using these we can determine the Activation Energy Ea, for the beef spoilage rxn. For U2 grade Argentinian beef stored in polyethylene and SARAN PVC the Ea ranged from 80kJmol^-1 to 220kJmol^-1 for a range of bacteria. (11.Giannuzzi,1997)
One contary value for the Ea of the beef spoilage rxns is given by Leak (10.Leak,1999) who calculated Ea=30kJmol^1. The difference between Leak's value and that of Giannuzzi probably lies in their packaging methods, i do not know Leak's packaging methods so this is just a guess.
2. Our System : pTET mimicing a TTI
Several Technologies have already been developed to addressed the problem of monitoring the heat exposure of products in the cold chain. One particular family of these products are called Temperature Time Integrators (TTI).(2.Labuza,2006)
The key aspect of a TTI is that they are based on a phenomenon which can act as a signal to a consumer for example, eg. a colour change. The rate at which this change occours needs to be temperature dependant so it can mimic the effect temperature has on the spoiling of meat eg. change happens quicker at higher temperatures. In order for a TTI to accurate report the spoilage rxn of beef the activation energy of the two rxns needs to be similar. For example a difference between the two Ea's less than 20kJmol^-1 would result in the TTI estimating the thermal history of the beef to be within 1 degree C of the actual history.).(1.Taoukis,2006)
I have tried to calculate the Ea of our system, pTET linked to Mut3BGFP, and have got a value of 1.5kJmol^-1. If we take the Leak's Ea of the spoilage rxn to be 30kJmol^-1 then our TTI will be accurate to 2 Degrees. However if we take the Giannuzzi's highest value of 220kJmol^-1 and assuming Taoukis estimation rule to be linear, our TTI will be accurate to 10 degrees C of the thermal history of the beef.
