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25 OCTOBER 2002 VOL 298 SCIENCE Two types of motifs heavily over-represented in transcriptional networks: 2

Simple expression Negative auto-regulation Positive auto-regulation 3

Simple expression Negative auto-regulation Positive auto-regulation a b c 4

Up to 40% of E. coli TFs negatively regulate their own expression. Rosenfeld, Elowitz, & Alon. J. Mol. Biol. (2002) 323, 785–793 Negative Autoregulation (NAR) speeds response time (relative to steady state) Anhydrotetracycline (aTc) inactivates TetR repressor Constitutive TetR TetR represses its own expression 5

To reach the *same steady state* NAR requires a stronger promoter Concentration of aTc Auto-feedback doesn’t kick in until reach aTc threshold 6

Simple expression Negative auto-regulation Positive auto-regulation a b c 7

NAR can reduce cell-cell variation, PAR can accentuate it (even = bimodal distribution) Bimodal distribution = Bistability: cells in a population can exist in TWO DIFFERENT states given the SAME ENVIRONMENT 8

Bistability can also give rise to hysteresis: history-dependent response to environmental cues Maeda & Sano. J. Mol. Biol. (2006) 359, 1107–1124 (inducer) 9

Feed-forward loops are also recurring network motifs 8 possible structures, each can be AND or OR gate = 16 possibilities 10

AND gate: both X AND Y required to activate Z = response delay, but rapid shutoff Activating Signal delay comes from need to make Y ‘Sign-sensitive’ delay element 11

Mangan, Zaslaver, Alon. J. Mol. Biol. (2003) 334, 197–204 vs. FFL was significantly slower turning on in response to cAMP … but same kinetics switching off 12

AND gate: both X AND Y required to activate Z = response delay, but rapid shutoff Activating Signal ‘Sign-sensitive’ delay element: Delay in turning system on buffers against small changes in activating signal OR gate: opposite trends: Rapid on (need EITHER X OR Y) … but delay in shut-off … resistant to fluctuations in input signal once the system is on Activating Signal Example from review: bacterial flagella production continues despite subtle fluctuations in activator 13

Activating Signal Generates a pulse of output Also speeds up response time (similar to negative auto-regulation of TFs) 14

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Signaling networks in development tend to be more complicated Double-positive feedback loops: can activate persistent states (‘memory’) even after activating signal is gone. Double-negative feedback loops: can activate persistent states (‘memory’). Often acts as a ‘toggle’ switch between two states. 16

Combination of network motifs into larger signaling networks can generate a myriad of outputs: pulses oscillations ultra-sensitive fate switches toggle switches and more Future directions: - better methods for motif identification in large datasets - identification of motifs unique to different types of data/biology - better understanding of motif effects … prediction of outputs 17