Molecular circuits for associative learning in single-celled organisms.
We demonstrate how a single-celled organism could undertake associative learning. Although to date only one previous study has found experimental evidence for such learning, there is no reason in principle why it should not occur. We propose a gene regulatory network that is capable of associative learning between any pre-specified set of chemical signals, in a Hebbian manner, within a single cell. A mathematical model is developed, and simulations show a clear learned response. A preliminary design for implementing this model using plasmids within Escherichia coli is presented, along with an alternative approach, based on double-phosphorylated protein kinases.
Fernando
Chrisantha T
CT
Systems Biology Centre, University of Birmingham, Birmingham B15 2TT, UK.
Liekens
Anthony M L
AM
Bingle
Lewis E H
LE
Beck
Christian
C
Lenser
Thorsten
T
Stekel
Dov J
DJ
Rowe
Jonathan E
JE
D004926:Escherichia coli / Q000235:genetics* / Q000502:physiology; D015964:Gene Expression Regulation, Bacterial; D008954:Models, Biological; D010766:Phosphorylation; D010957:Plasmids / Q000235:genetics; D011494:Protein Kinases / Q000235:genetics / Q000378:metabolism; D015398:Signal Transduction / Q000235:genetics / Q000502:physiology*
D011494:Protein Kinases