Emergent Lévy behavior in single-cell stochastic gene expression.

Single-cell gene expression is inherently stochastic; its emergent behavior can be defined in terms of the chemical master equation describing the evolution of the mRNA and protein copy numbers as the latter tends to infinity. We establish two types of "macroscopic limits": the Kurtz limit is consistent with the classical chemical kinetics, while the Lévy limit provides a theoretical foundation for an empirical equation proposed in N. Friedman et al., Phys. Rev. Lett. 97, 168302 (2006)PRLTAO0031-900710.1103/PhysRevLett.97.168302. Furthermore, we clarify the biochemical implications and ranges of applicability for various macroscopic limits and calculate a comprehensive analytic expression for the protein concentration distribution in autoregulatory gene networks. The relationship between our work and modern population genetics is discussed.

[1]  Chen Jia Simplification of irreversible Markov chains by removal of states with fast leaving rates. , 2016, Journal of theoretical biology.

[2]  Hannah H. Chang,et al.  Non-genetic heterogeneity — a mutation-independent driving force for the somatic evolution of tumours , 2009, Nature Reviews Genetics.

[3]  John Wakeley,et al.  The limits of theoretical population genetics. , 2005, Genetics.

[4]  P. Anderson More is different. , 1972, Science.

[5]  M. Delbrück Statistical Fluctuations in Autocatalytic Reactions , 1940 .

[6]  Niraj Kumar,et al.  Exact distributions for stochastic gene expression models with bursting and feedback. , 2014, Physical review letters.

[7]  T. Kepler,et al.  Stochasticity in transcriptional regulation: origins, consequences, and mathematical representations. , 2001, Biophysical journal.

[8]  Shasha Chong,et al.  Mechanism of Transcriptional Bursting in Bacteria , 2014, Cell.

[9]  W. Ewens Mathematical Population Genetics : I. Theoretical Introduction , 2004 .

[10]  J. Newby Bistable switching asymptotics for the self regulating gene , 2014, 1407.4344.

[11]  Chen Jia,et al.  Simplification of Markov chains with infinite state space and the mathematical theory of random gene expression bursts. , 2017, Physical review. E.

[12]  Jürg Bähler,et al.  Coordinating genome expression with cell size. , 2012, Trends in genetics : TIG.

[13]  N. Friedman,et al.  Stochastic protein expression in individual cells at the single molecule level , 2006, Nature.

[14]  Paul C. Bressloff,et al.  Stochastic switching in biology: from genotype to phenotype , 2017 .

[15]  D. Applebaum Lévy Processes and Stochastic Calculus: Preface , 2009 .

[16]  A. Raj,et al.  Single mammalian cells compensate for differences in cellular volume and DNA copy number through independent global transcriptional mechanisms. , 2015, Molecular cell.

[17]  Hong Qian,et al.  Stochastic phenotype transition of a single cell in an intermediate region of gene state switching. , 2013, Physical review letters.

[18]  T. Kurtz The Relationship between Stochastic and Deterministic Models for Chemical Reactions , 1972 .

[19]  Johan Paulsson,et al.  Models of stochastic gene expression , 2005 .

[20]  Nir Friedman,et al.  Linking stochastic dynamics to population distribution: an analytical framework of gene expression. , 2006, Physical review letters.

[21]  Chen Jia Reduction of Markov chains with two-time-scale state transitions , 2013, 1311.2196.

[22]  M. Ehrenberg,et al.  Random signal fluctuations can reduce random fluctuations in regulated components of chemical regulatory networks. , 2000, Physical review letters.

[23]  Charles R Doering,et al.  Gene expression dynamics with stochastic bursts: Construction and exact results for a coarse-grained model. , 2015, Physical review. E.

[24]  Vahid Shahrezaei,et al.  Analytical distributions for stochastic gene expression , 2008, Proceedings of the National Academy of Sciences.

[25]  X. Xie,et al.  Probing Gene Expression in Live Cells, One Protein Molecule at a Time , 2006, Science.

[26]  Michael Q. Zhang,et al.  Stochastic fluctuations can reveal the auto-regulatory characteristics of gene networks at the single-molecule level , 2017 .

[27]  H. Qian Cooperativity in cellular biochemical processes: noise-enhanced sensitivity, fluctuating enzyme, bistability with nonlinear feedback, and other mechanisms for sigmoidal responses. , 2012, Annual review of biophysics.

[28]  O. Berg A model for the statistical fluctuations of protein numbers in a microbial population. , 1978, Journal of theoretical biology.

[29]  H. Qian Nonlinear stochastic dynamics of mesoscopic homogeneous biochemical reaction systems—an analytical theory , 2011 .

[30]  J. Peccoud,et al.  Markovian Modeling of Gene-Product Synthesis , 1995 .