BACA THEODOR-STEFAN and SINIAVSCHI RADUMASTER ITEMS 2012

FEED-FORWARD LOOP CENTRAL DATABASE

Based on the article: STRUCTURE AND FUNCTION OF THE FEED-FORWARD LOOP NETWORK MOTIF by S. Mangan and U. Alon

Transcription factor X regulates transcription factor Y, and both jointly regulate Z. Sx and Sy are the inducers of X and Y, respectively. The action of X and Y is integrated at the Z promoter with a cis-regulatory input function , such as AND or OR logic.

Simple regulation of Z by Xand Y.

Feed-forward loop (FFL) is a motif, consisting in a three-gene pattern composed of two input transcription factors. Each of the three interactions in the FFL can be either activating or repressing (coherent or incoherent).

What is a FEED-FORWARD LOOP?

E. coli example:

FFL- Structure

• Decide from fluctuating signal• Filter out pulses• Respond to persistent stimulations• Rapidly shut down

• Easly reverse• Initially reacts strongly• Later comes back to intermediate levels

COHERENT and INCOHERENT FFL type

FFL- Structure

Logic function

AND logic

OR logic

X and Y respond to

external stimuli

Coherent Type-1 FFL – AND logic

Sx appear, X rapidly changes to X*

X* binds to gene Z, but cannot activate it

X* binds to gene Y, and begins to transcript it

Z begins to be expressed after Ton time, when Y* crosses the activation threshold Kyz

Incoherent Type-1 FFL

Equations for Gene Regulation Reactions

MATERIALS AND METHODS

Parameters for Functional FFLs

MATERIALS AND METHODS

RESULTS

RESULTS

RESULTS

RESULTS

The FFL Database

An user-friendly web app that integrates feed forward loops so scientists and other enthusiasts could use the results for educational and scientifical purposes.

The FFL Database

An user-friendly web app that integrates feed forward loops so scientists and other enthusiasts could use the results for educational and scientifical purposes.

The actual FFL Database

Methods of FFL Database

Search where we can get information about the regulatory networks

Get from the information about the regulation by Transcription Factors.

Construct an algorithm to extract the FFL motives different organisms regulatory networks.

Make a hierarchical clasiffication of FFLs elements.

Make a clasiffication acording to the origin of the signal that TFs sense.

Search for differences betwen the data on each position of the FFLs making statistical tests to validate significance.

CONCLUSIONS

Incoherent FFLs – sign-sensitive accelerators.

Coherent FFLs – sign-sensitive delays.

Some FFL occur more often than the others.

Observe how TFs that detect different-origin signals compose

Observe the dinamics on the TRN looking for the formation of specific topological structure, FFL

Search for significative differences on the data by statistical tests on each position of the FFLs.

Thank you for your attention!