Synthetic mammalian transgene negative autoregulation - Vinay Shimoga; Jacob T White; Yi Li; Eduardo Sontag; Leonidas Bleris (Molecular Systems Biology, 2013)
Abstract Biological networks contain overrepresented small‐scale topologies, typically called motifs. A frequently appearing motif is the transcriptional negative‐feedback loop, where a gene product represses its own transcription. Here, using synthetic circuits stably integrated in human kidney cells, we study the effect of negative‐feedback regulation on cell‐wide (extrinsic) and gene‐specific (intrinsic) sources of uncertainty. We develop a theoretical approach to extract the two noise components from experiments and show that negative feedback results in significant total noise reduction by reducing extrinsic noise while marginally increasing intrinsic noise. We compare the results to simple negative regulation, where a constitutively transcribed transcription factor represses a reporter protein. We observe that the control architecture also reduces the extrinsic noise but results in substantially higher intrinsic fluctuations. We conclude that negative feedback is the most efficient way to mitigate the effects of extrinsic fluctuations by a sole regulatory wiring.