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Variable cellular decision-making behavior in a constant synthetic network topology.

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Altering component properties or numbers in cellular networks, even without changing their structure, significantly impacts function. This study shows how modifying repression strength, operator sites, or gene dosage affects decision-making in synthetic yeast networks.

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Area of Science:

  • Synthetic biology
  • Systems biology
  • Biochemical network analysis

Background:

  • Cellular functions rely on interacting component networks with specific topologies.
  • Network function can be modulated by altering component numbers or biochemical properties, even with a constant structure.
  • The effects of such perturbations on cellular response dynamics are not well understood.

Purpose of the Study:

  • To investigate how topology-preserving perturbations influence decision-making behavior in a synthetic cross-antagonism with autoregulation network in yeast.
  • To understand how changes in repression strength, operator site number, and gene dosage affect network dynamics.

Main Methods:

  • Synthetic construction of a cross-antagonism with autoregulation network in yeast using a single protein building block (TetR).
  • Engineering TetR variants and fusion partners to create network components.
  • Systematic study of topology-preserving perturbations: repression strength, operator site number, and gene dosage.
  • Experimental quantification of gene copy numbers and phenotypic responses.
  • Stochastic simulations to model network dynamics.

Main Results:

  • Reducing TetR repression strength led to a loss of mutually exclusive cell responses.
  • Increasing the number of operator sites unexpectedly impeded decision-making exclusivity.
  • Increasing gene dosage reduced response exclusivity, even in networks with strong repression and few operator sites.
  • Experimental validation confirmed the impact of gene copy number on phenotypic responses.

Conclusions:

  • Parameters that do not alter network topology can significantly influence response dynamics.
  • Findings inform the study of natural biological networks and the engineering of synthetic ones.
  • Understanding these influences is crucial for robust synthetic network design and interpreting native motif behavior.