Abstract

Many signal transduction and gene regulatory pathways are highly dynamic resulting in temporally varying activity of signaling proteins and time varying gene expression profiles. These time varying signaling profiles are important as these can direct different cellular phenotypes. Currently, our biophysical understanding of these temporal signaling profiles is very rudimentary and relies on the genetic manipulation of specific proteins or drug treatment regimes. Although protein numbers are often manipulated over a wide dynamic range using an inducible promoter, the activity of these signaling proteins may only be manipulated by mutations or drugs. One drawback of this approach is that genetic protein modification may result in a significant interference with the function of the cell, which may cause lethal phenotypes. Another drawback is that drugs are often not available for proteins of interest or have considerable off-target effect. In order to avoid these limitations, we developed a time varying perturbation approach that utilizes time varying ligand profiles to investigate the temporal properties of signaling and gene regulatory pathways, without genetic manipulation or drug treatments. To demonstrate the feasibility of this approach, we chose to interrogate the evolutionary conserved high-osmolarity glycerol stress response pathway (HOG/p38) in S. Cerevisiae, which enables to manipulate the intensity, duration and temporal activity of the signal transduction pathway in single cells. We are able to quantify signal transduction activation, signal transduction saturation and gene expression activation thresholds at high precision and demonstrate that the signaling dynamics is proportional to the first time derivative of the external perturbation profile. Because this approach is independent of the biological pathway or organism, it presents a general methodology to interrogate and control signaling and gene expression pathways non-invasively without the need for genetic or drug perturbations.

Full Text
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