Noise in biological circuits.

Noise biology focuses on the sources, processing, and biological consequences of the inherent stochastic fluctuations in molecular transitions or interactions that control cellular behavior. These fluctuations are especially pronounced in small systems where the magnitudes of the fluctuations approach or exceed the mean value of the molecular population. Noise biology is an essential component of nanomedicine where the communication of information is across a boundary that separates small synthetic and biological systems that are bound by their size to reside in environments of large fluctuations. Here we review the fundamentals of the computational, analytical, and experimental approaches to noise biology. We review results that show that the competition between the benefits of low noise and those of low population has resulted in the evolution of genetic system architectures that produce an uneven distribution of stochasticity across the molecular components of cells and, in some cases, use noise to drive biological function. We review the exact and approximate approaches to gene circuit noise analysis and simulation, and review many of the key experimental results obtained using flow cytometry and time-lapse fluorescent microscopy. In addition, we consider the probative value of noise with a discussion of using measured noise properties to elucidate the structure and function of the underlying gene circuit. We conclude with a discussion of the frontiers of and significant future challenges for noise biology.

[1]  B. Ingalls,et al.  Deterministic characterization of stochastic genetic circuits , 2007, Proceedings of the National Academy of Sciences.

[2]  M. L. Simpson,et al.  Nano-enabled synthetic biology , 2007, Molecular systems biology.

[3]  L. Serrano,et al.  Engineering stability in gene networks by autoregulation , 2000, Nature.

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

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

[6]  A. E. Hirsh,et al.  Noise Minimization in Eukaryotic Gene Expression , 2004, PLoS biology.

[7]  M. Thattai,et al.  Intrinsic noise in gene regulatory networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

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

[9]  Indrani Bose,et al.  Noise characteristics of feed forward loops , 2004, Physical biology.

[10]  Nagiza F. Samatova,et al.  The sorting direct method for stochastic simulation of biochemical systems with varying reaction execution behavior , 2006, Comput. Biol. Chem..

[11]  Anne E Carpenter,et al.  Dynamic proteomics in individual human cells uncovers widespread cell-cycle dependence of nuclear proteins , 2006, Nature Methods.

[12]  D. Gillespie Approximate accelerated stochastic simulation of chemically reacting systems , 2001 .

[13]  Michael A. Gibson,et al.  Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many Channels , 2000 .

[14]  Farren J. Isaacs,et al.  Phenotypic consequences of promoter-mediated transcriptional noise. , 2006, Molecular cell.

[15]  H. McAdams,et al.  Circuit simulation of genetic networks. , 1995, Science.

[16]  J. Paulsson Summing up the noise in gene networks , 2004, Nature.

[17]  Simon V. Avery,et al.  Microbial cell individuality and the underlying sources of heterogeneity , 2006, Nature Reviews Microbiology.

[18]  Naama Brenner,et al.  Genome-wide transcriptional plasticity underlies cellular adaptation to novel challenge , 2007, Molecular systems biology.

[19]  Tianhai Tian,et al.  A multi-scaled approach for simulating chemical reaction systems. , 2004, Progress in biophysics and molecular biology.

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

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

[22]  M. L. Simpson,et al.  Gene network shaping of inherent noise spectra , 2006, Nature.

[23]  M. L. Simpson,et al.  Frequency domain chemical Langevin analysis of stochasticity in gene transcriptional regulation. , 2004, Journal of theoretical biology.

[24]  C. Lumsden,et al.  Stochastic Simulation of Coupled Reaction-Diffusion Processes , 1996 .

[25]  Gregory D. Peterson,et al.  Accelerating Gene Regulatory Network Modeling Using Grid-Based Simulation , 2004, Simul..

[26]  P. R. ten Wolde,et al.  Exact results for noise power spectra in linear biochemical reaction networks. , 2005, The Journal of chemical physics.

[27]  Rajan P Kulkarni,et al.  Tunability and Noise Dependence in Differentiation Dynamics , 2007, Science.

[28]  D. A. Mcquarrie Stochastic approach to chemical kinetics , 1967, Journal of Applied Probability.

[29]  Linda R. Petzold,et al.  Improved leap-size selection for accelerated stochastic simulation , 2003 .

[30]  David McMillen,et al.  Biochemical Network Stochastic Simulator (BioNetS): software for stochastic modeling of biochemical networks , 2004, BMC Bioinformatics.

[31]  E. O’Shea,et al.  Noise in protein expression scales with natural protein abundance , 2006, Nature Genetics.

[32]  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.

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

[34]  Chris D Cox,et al.  Using noise to probe and characterize gene circuits , 2008, Proceedings of the National Academy of Sciences.

[35]  Alex Groisman,et al.  A microfluidic chemostat for experiments with bacterial and yeast cells , 2005, Nature Methods.

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

[37]  Xavier Darzacq,et al.  Imaging gene expression in single living cells , 2004, Nature Reviews Molecular Cell Biology.

[38]  A. Givan,et al.  Flow Cytometry: First Principles , 1992 .

[39]  M. L. Simpson,et al.  Frequency domain analysis of noise in autoregulated gene circuits , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[40]  Chris D Cox,et al.  Analysis of noise in quorum sensing. , 2003, Omics : a journal of integrative biology.

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

[42]  A. van Oudenaarden,et al.  Noise Propagation in Gene Networks , 2005, Science.

[43]  T. Ideker,et al.  A new approach to decoding life: systems biology. , 2001, Annual review of genomics and human genetics.

[44]  M. DELBRtrCK THE BURST SIZE DISTRIBUTION IN THE GROWTH OF BACTERIAL VIRUSES ( BACTERIOPHAGES ) , 2022 .

[45]  J. Derisi,et al.  Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise , 2006, Nature.

[46]  K. Burrage,et al.  Binomial leap methods for simulating stochastic chemical kinetics. , 2004, The Journal of chemical physics.

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

[48]  Gregory D. Peterson,et al.  Engineering in the biological substrate: information processing in genetic circuits , 2004, Proceedings of the IEEE.

[49]  Nagiza F. Samatova,et al.  Accelerating Exact Stochastic Simulation Using Reconfigurable Computing , 2005, ERSA.

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

[51]  Mads Kærn,et al.  Noise in eukaryotic gene expression , 2003, Nature.

[52]  M. L. Simpson,et al.  Transient-mediated fate determination in a transcriptional circuit of HIV , 2007, Nature Genetics.

[53]  Linda R Petzold,et al.  The slow-scale stochastic simulation algorithm. , 2005, The Journal of chemical physics.

[54]  D. Koshland,et al.  Non-genetic individuality: chance in the single cell , 1976, Nature.

[55]  Larry Lok The need for speed in stochastic simulation , 2004, Nature Biotechnology.

[56]  D. Gillespie The chemical Langevin equation , 2000 .

[57]  R. Milo,et al.  Variability and memory of protein levels in human cells , 2006, Nature.

[58]  C. Pesce,et al.  Regulated cell-to-cell variation in a cell-fate decision system , 2005, Nature.

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

[60]  Hong Li,et al.  Efficient formulation of the stochastic simulation algorithm for chemically reacting systems. , 2004, The Journal of chemical physics.

[61]  Muruhan Rathinam,et al.  Stiffness in stochastic chemically reacting systems: The implicit tau-leaping method , 2003 .

[62]  Jared E. Toettcher,et al.  Stochastic Gene Expression in a Lentiviral Positive-Feedback Loop: HIV-1 Tat Fluctuations Drive Phenotypic Diversity , 2005, Cell.

[63]  M. L. Simpson,et al.  Frequency domain analysis of noise in simple gene circuits. , 2006, Chaos.

[64]  Lukasz Salwinski,et al.  In silico simulation of biological network dynamics , 2004, Nature Biotechnology.