Team:BIOTEC Dresden/Modeling v2

Modeling

In genetics, FLP-FRT recombination is a site-directed recombination technology used to manipulate an organism's DNA under controlled conditions in vivo. It is analogous to Cre-Lox recombination. It involves the recombination of sequences between short Flippase Recognition Target (FRT) sites by the Flippase recombination enzyme (FLP or Flp) derived from the 2µ plasmid of the baker's yeast Saccharomyces cerevisiae. The 34bp long FRT site sequence is : 5'-GAAGTTCCTATTCtctagaaaGTATAGGAACTTC-3'. Flippase (flp) binds to the 13-bp 5'-GAAGTTCCTATTC-3' and to the reverse complement of 5'-GTATAGGAACTTC-3' (5'-GAAGTTCCTATAC-3'). The FRT site is cleaved just before 5'-tctagaaa-3', the 8bp asymmetric core region, on the top strand and behind this sequence on the bottom strand.[1] Several variant FRT sites exist. Recombination can occur between two identical FRT sites but generally not between non-identical FRT sites Many available constructs include the sequence 5'-GAAGTTCCTATTCC-3' immediately upstream the FRT site (resulting in 5'-GAAGTTCCTATTCCGAAGTTCCTATTCtctagaaaGTATAGGAACTTC-3') but this sequence is dispensable for recombination. Because the recombination activity can be targeted to only one target organ, or a low level of recombination activity can be used to consistently alter the DNA of only a subset of cells, FLP-FRT can be used to construct genetic mosaics in multicellular organisms. Using this technology, the loss or alteration of a gene can be studied in one target organ of interest, even if experimental animals could not survive the loss of the gene in other organs. The effect of altering a gene can also be studied over time, by using an inducible promoter to trigger the recombination activity late in development - this prevents the alteration from affecting overall development of an organ, and allows single cells lacking the gene to be compared to normal neighboring cells in the same environment.

A very similar study using eukaryotic DNA: http://www.ncbi.nlm.nih.gov/pubmed/10581237

kinetic analysis of Flp activity - DNA binding and recombination models: http://www.ncbi.nlm.nih.gov/pubmed/9813124

Thermostability of Flp recombinase (We are using the F70L variant because it is sufficiently slow to give a time course): http://www.ncbi.nlm.nih.gov/pubmed/8932381

http://www.recombineering.net/img/A202_01.gif

pCAGGS-FLPe-IRESpuro expression vector.

Unlike transcriptional regulation, this method gives true all-or-none induction due to covalent modification of DNA by Flp recombinase. Determining the transfer curve of inter-FRT site distance versus average recombination time allows the onset of gene expression to be predicted. We then apply this Flp reporter system as a powerful PoPS measurement device.

(New BioBrick coming soon).

Rule-based modeling of BioBrick parts

We report here a modular framework for modeling BioBrick parts and systems using rule-based modeling. In standard reaction-based modeling, the modeler must declare all of the possible species (molecules and complexes), and the reactions that transform one set of species to another set of species. In rule-based modeling, the modeler must only declare the individual molecules (or smallest granular representation of species that they wish), and a set of reaction rules that govern the formation and transformation of species. If you are familiar with the computer science concept of regular expressions, then it might help to think of rules as regular expressions for reactions.

Take the example of a RNA polymerase molecule binding to a promoter. To the first approximation (and by the modularity and composabiity concepts endorsed by the BioBricks foundation), the polymerase does not know or care what lies downstream of the promoter. Thus, the reaction should be independent of the downstream sequence. In a reaction-based modeling framework, a different reaction must be written for the binding to a particular promoter for each specific sequence that lies downstream of the promoter. For example, if the promoter lies upstream of the cI coding sequence, then we'd have to write the reaction

RNA_polymerase + promoter-RBS-cI_CDS-terminator -> RNA_polymerase-promoter-RBS-cI_CDS-terminator

if the promoter was upstream of the GFP coding sequence, or even the cI coding sequence with a different RBS, then we would have to write a different reaction.

Using a rule-based modeling framework, we can write the generalized reaction rule

RNA_polymerase + promoter-? -> RNA_polymerase-promoter-?

where the question mark means that we don't care what lies downstream of the promoter. This rule will allow the RNA polymerase to bind to the promoter with the same kinetics regardless of what lies downstream of the promoter. If we initialize our model with RNA_polymerase and promoter-RBS-cI_CDS-terminator, then this rule will be equivalent to the above reaction. But if we initialize with another RBS, coding sequence, and/or terminator downstream of the promoter, then this rule will also be applied.

Using this level of modularity, we can construct rules for each BioBrick part independent of the other BioBrick parts that lie upstream or downstream.