rudge, t. j. | bioRxiv Science

bioRxiv2021

Accurate reconstruction of dynamic gene expression and growth rate profiles from noisy measurements

Cells face changing environments to which they sense and respond in complex ways, changing their rates of gene expression and growth. Measuring these dynamics is therefore essential to understanding natural and synthetic regulatory networks that give rise to functional phenotypes. However, reconstruction of gene expression and growth rate profiles from typically noisy measurements of cell populations is difficult due to the effects of noise at low cell densities among other factors. We present here a method for estimation of dynamic gene expression rates and biomass growth rates from noisy measurement data, and show that it is several times more accurate than current approaches. We applied our method to multiple promoter-reporter fusion genes. Gene expression rates of such promoter-reporter fusions are typically used as a proxy for transcription rates. However, using our method we show that fusion gene expression rate dynamics are determined at least by the promoter of interest and the downstream reporter. O_FIG O_LINKSMALLFIG WIDTH=192 HEIGHT=200 SRC="FIGDIR/small/435606v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@eded2corg.highwire.dtl.DTLVardef@6e1778org.highwire.dtl.DTLVardef@1c6e853org.highwire.dtl.DTLVardef@1bee0a1_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2020

Novel tunable spatio-temporal patterns from a simple genetic oscillator circuit

Multicellularity, the coordinated collective behaviour of cell populations, gives rise to the emergence of self-organized phenomena at many different spatio-temporal scales. At the genetic scale, oscillators are ubiquitous in regulation of multicellular systems, including during their development and regeneration. Synthetic biologists have successfully created simple synthetic genetic circuits that produce oscillations in single cells. Studying and engineering synthetic oscillators in a multicellular chassis can therefore give us valuable insights into how simple genetic circuits can encode complex multicellular behaviours at different scales. Here we develop a study of the coupling between the repressilator synthetic genetic ring oscillator and constraints on cell growth in colonies. We show in silico how mechanical constraints generate characteristic patterns of growth rate inhomogeneity in growing cell colonies. Next, we develop a simple one-dimensional model which predicts that coupling the repressilator to this pattern of growth rate via protein dilution generates travelling waves of gene expression. We show that the dynamics of these spatio-temporal patterns are determined by two parameters; the protein degradation and maximum expression rates of the repressors. We derive simple relations between these parameters and the key characteristics of the travelling wave patterns: firstly, wave speed is determined by protein degradation and secondly, wavelength is determined by maximum gene expression rate. Our analytical predictions and numerical results were in close quantitative agreement with detailed individual based simulations of growing cell colonies. Confirming published experimental results we also found that static ring patterns occur when protein stability is high. Our results show that this pattern can be induced simply by growth rate dilution and does not require transition to stationary phase as previously suggested. Our method generalizes easily to other genetic circuit architectures thus providing a framework for multi-scale rational design of spatio-temporal patterns from genetic circuits. We use this method to generate testable predictions for the synthetic biology design-build-test-learn cycle.

bioengineering↗