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Motif Over-Representation in Transcriptional Networks

This scientific article explores the over-representation of two types of motifs in transcriptional networks: simple expression and auto-regulation. It discusses how these motifs impact response time, reduce cell-cell variation, and generate bistability and hysteresis. Additionally, it examines the role of feed-forward loops and double-positive/negative feedback loops in signaling networks. The article concludes by highlighting the need for better motif identification methods and understanding their effects on network outputs.

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Motif Over-Representation in Transcriptional Networks

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  1. 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 b a c

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

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

  6. Simple expression Negative auto-regulation Positive auto-regulation b a 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 (inducer) Maeda & Sano. J. Mol. Biol. (2006) 359, 1107–1124

  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 ‘Sign-sensitive’ delay element Activating Signal delay comes from need to make Y

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

  12. AND gate: both X AND Y required to activate Z = response delay, but rapid shutoff ‘Sign-sensitive’ delay element: Delay in turning system on buffers against small changes in activating signal Activating Signal 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 Example from review: bacterial flagella production continues despite subtle fluctuations in activator

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

  14. 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.

  15. 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

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