Sources of Variability in a Synthetic Gene Oscillator

Synthetic gene oscillators are small, engineered genetic circuits that produce periodic variations in target protein expression. Like other gene circuits, synthetic gene oscillators are noisy and exhibit fluctuations in amplitude and period. Understanding the origins of such variability is key to building predictive models that can guide the rational design of synthetic circuits. Here, we developed a method for determining the impact of different sources of noise in genetic oscillators by measuring the variability in oscillation amplitude and correlations between sister cells. We first used a combination of microfluidic devices and time-lapse fluorescence microscopy to track oscillations in cell lineages across many generations. We found that oscillation amplitude exhibited high cell-to-cell variability, while sister cells remained strongly correlated for many minutes after cell division. To understand how such variability arises, we constructed a computational model that identified the impact of various noise sources across the lineage of an initial cell. When each source of noise was appropriately tuned the model reproduced the experimentally observed amplitude variability and correlations, and accurately predicted outcomes under novel experimental conditions. Our combination of computational modeling and time-lapse data analysis provides a general way to examine the sources of variability in dynamic gene circuits.

[1]  Jeff Hasty,et al.  Monitoring dynamics of single-cell gene expression over multiple cell cycles , 2005, 2006 Bio Micro and Nanosystems Conference.

[2]  Ertugrul M. Ozbudak,et al.  Regulation of noise in the expression of a single gene , 2002, Nature Genetics.

[3]  J. Collins,et al.  Construction of a genetic toggle switch in Escherichia coli , 2000, Nature.

[4]  P. Swain,et al.  Stochastic Gene Expression in a Single Cell , 2002, Science.

[5]  Benjamin L Turner,et al.  Supporting Online Material Materials and Methods Som Text Figs. S1 to S3 Table S1 References Robust, Tunable Biological Oscillations from Interlinked Positive and Negative Feedback Loops , 2022 .

[6]  Julio O. Ortiz,et al.  Noise Contributions in an Inducible Genetic Switch: A Whole-Cell Simulation Study , 2011, PLoS Comput. Biol..

[7]  Moss,et al.  Bistability driven by colored noise: Theory and experiment. , 1985, Physical review. A, General physics.

[8]  D. Gonze Modeling the effect of cell division on genetic oscillators. , 2013, Journal of theoretical biology.

[9]  M. Elowitz,et al.  Regulatory activity revealed by dynamic correlations in gene expression noise , 2008, Nature Genetics.

[10]  J. Raser,et al.  Control of Stochasticity in Eukaryotic Gene Expression , 2004, Science.

[11]  T. Funatsu,et al.  Kinetic study of de novo chromophore maturation of fluorescent proteins. , 2011, Analytical biochemistry.

[12]  Mehmet Toner,et al.  Asymmetry and Aging of Mycobacterial Cells Lead to Variable Growth and Antibiotic Susceptibility , 2012, Science.

[13]  François Taddei,et al.  In Brief , 2003, Nature Reviews Microbiology.

[14]  Jeffrey W. Smith,et al.  Stochastic Gene Expression in a Single Cell , .

[15]  L. Poulsen,et al.  New Unstable Variants of Green Fluorescent Protein for Studies of Transient Gene Expression in Bacteria , 1998, Applied and Environmental Microbiology.

[16]  Haidong Feng,et al.  Stochastic expression dynamics of a transcription factor revealed by single-molecule noise analysis , 2012, Nature Structural &Molecular Biology.

[17]  M. Bennett,et al.  Microfluidic devices for measuring gene network dynamics in single cells , 2009, Nature Reviews Genetics.

[18]  James P. Gleeson,et al.  Phase Diffusion Coefficient for Oscillators Perturbed by Colored Noise , 2007, IEEE Transactions on Circuits and Systems II: Express Briefs.

[19]  M. Thattai,et al.  Stochastic Gene Expression in Fluctuating Environments , 2004, Genetics.

[20]  D. Volfson,et al.  Delay-induced stochastic oscillations in gene regulation. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[21]  C. J. Zopf,et al.  Cell-Cycle Dependence of Transcription Dominates Noise in Gene Expression , 2013, PLoS Comput. Biol..

[22]  Drew Endy,et al.  Determination of cell fate selection during phage lambda infection , 2008, Proceedings of the National Academy of Sciences.

[23]  D. Volfson,et al.  Origins of extrinsic variability in eukaryotic gene expression , 2006, Nature.

[24]  D. Gillespie Exact Stochastic Simulation of Coupled Chemical Reactions , 1977 .

[25]  M. Bennett,et al.  A fast, robust, and tunable synthetic gene oscillator , 2008, Nature.

[26]  Johan Paulsson,et al.  Separating intrinsic from extrinsic fluctuations in dynamic biological systems , 2011, Proceedings of the National Academy of Sciences.

[27]  Jeff Hasty,et al.  Delay-induced degrade-and-fire oscillations in small genetic circuits. , 2009, Physical review letters.

[28]  J Hasty,et al.  Cellular growth and division in the Gillespie algorithm. , 2004, Systems biology.

[29]  Benjamin B. Kaufmann,et al.  Contributions of low molecule number and chromosomal positioning to stochastic gene expression , 2005, Nature Genetics.

[30]  Marco Cosentino Lagomarsino,et al.  Concerted control of Escherichia coli cell division , 2014, Proceedings of the National Academy of Sciences.

[31]  LieJune Shiau,et al.  Stochastic Delay Accelerates Signaling in Gene Networks , 2011, PLoS Comput. Biol..

[32]  Julien F. Ollivier,et al.  Colored extrinsic fluctuations and stochastic gene expression , 2008, Molecular systems biology.

[33]  François Taddei,et al.  Asymmetric segregation of protein aggregates is associated with cellular aging and rejuvenation , 2008, Proceedings of the National Academy of Sciences.

[34]  P. Swain,et al.  Gene Regulation at the Single-Cell Level , 2005, Science.

[35]  Xiaodong Cai,et al.  Exact stochastic simulation of coupled chemical reactions with delays. , 2007, The Journal of chemical physics.

[36]  W. Ebeling Stochastic Processes in Physics and Chemistry , 1995 .

[37]  H. Bujard,et al.  Independent and tight regulation of transcriptional units in Escherichia coli via the LacR/O, the TetR/O and AraC/I1-I2 regulatory elements. , 1997, Nucleic acids research.

[38]  N. Kampen,et al.  Stochastic processes in physics and chemistry , 1981 .

[39]  Fox,et al.  Uniform convergence to an effective Fokker-Planck equation for weakly colored noise. , 1986, Physical review. A, General physics.

[40]  Robert Azencott,et al.  Modeling delay in genetic networks: from delay birth-death processes to delay stochastic differential equations. , 2014, The Journal of chemical physics.

[41]  D. Sherrington Stochastic Processes in Physics and Chemistry , 1983 .

[42]  L. Tsimring,et al.  Entrainment of a Population of Synthetic Genetic Oscillators , 2011, Science.

[43]  P. Swain,et al.  Intrinsic and extrinsic contributions to stochasticity in gene expression , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[44]  A. Arkin,et al.  Stochastic kinetic analysis of developmental pathway bifurcation in phage lambda-infected Escherichia coli cells. , 1998, Genetics.

[45]  Y. Lai,et al.  Engineering of regulated stochastic cell fate determination , 2013, Proceedings of the National Academy of Sciences.

[46]  Kresimir Josic,et al.  Engineered temperature compensation in a synthetic genetic clock , 2014, Proceedings of the National Academy of Sciences.

[47]  Tianhai Tian,et al.  Oscillatory Regulation of Hes1: Discrete Stochastic Delay Modelling and Simulation , 2006, PLoS Comput. Biol..

[48]  Antti Häkkinen,et al.  Asymmetric Disposal of Individual Protein Aggregates in Escherichia coli, One Aggregate at a Time , 2012, Journal of bacteriology.