Optimizing information flow in small genetic networks. IV. Spatial coupling.

We typically think of cells as responding to external signals independently by regulating their gene expression levels, yet they often locally exchange information and coordinate. Can such spatial coupling be of benefit for conveying signals subject to gene regulatory noise? Here we extend our information-theoretic framework for gene regulation to spatially extended systems. As an example, we consider a lattice of nuclei responding to a concentration field of a transcriptional regulator (the input) by expressing a single diffusible target gene. When input concentrations are low, diffusive coupling markedly improves information transmission; optimal gene activation functions also systematically change. A qualitatively different regulatory strategy emerges where individual cells respond to the input in a nearly steplike fashion that is subsequently averaged out by strong diffusion. While motivated by early patterning events in the Drosophila embryo, our framework is generically applicable to spatially coupled stochastic gene expression models.

[1]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[2]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[3]  L. Wolpert Positional information and the spatial pattern of cellular differentiation. , 1969, Journal of theoretical biology.

[4]  H. Berg,et al.  Physics of chemoreception. , 1977, Biophysical journal.

[5]  B. Bainbridge,et al.  Genetics , 1981, Experientia.

[6]  H. Meinhardt Models of biological pattern formation , 1982 .

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

[8]  AC Tose Cell , 1993, Cell.

[9]  L Wolpert,et al.  Positional information and pattern formation in development. , 1994, Developmental genetics.

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

[11]  A. Mccarthy Development , 1996, Current Opinion in Neurobiology.

[12]  H. Tuckwell,et al.  Statistical properties of stochastic nonlinear dynamical models of single spiking neurons and neural networks. , 1996, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[13]  L Wolpert,et al.  One hundred years of positional information. , 1996, Trends in genetics : TIG.

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

[15]  김삼묘,et al.  “Bioinformatics” 특집을 내면서 , 2000 .

[16]  Kevin Barraclough,et al.  I and i , 2001, BMJ : British Medical Journal.

[17]  S. Leibler,et al.  Establishment of developmental precision and proportions in the early Drosophila embryo , 2002, Nature.

[18]  N. Barkai,et al.  Robustness of the BMP morphogen gradient in Drosophila embryonic patterning , 2022 .

[19]  Naama Barkai,et al.  Elucidating mechanisms underlying robustness of morphogen gradients. , 2004, Current opinion in genetics & development.

[20]  J. Elf,et al.  Spontaneous separation of bi-stable biochemical systems into spatial domains of opposite phases. , 2004, Systems biology.

[21]  Manu , 2005, Chasing Neotropical Birds.

[22]  Johan Hattne,et al.  Stochastic reaction-diffusion simulation with MesoRD , 2005, Bioinform..

[23]  W. Bialek,et al.  Physical limits to biochemical signaling. , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[24]  Hideo Hasegawa N-Dependent Multiplicative-Noise Contributions in Finite N-Unit Langevin Models: Augmented Moment Approach , 2006 .

[25]  Y. Kalaidzidis,et al.  Kinetics of Morphogen Gradient Formation , 2007, Science.

[26]  W. Bialek,et al.  Probing the Limits to Positional Information , 2007, Cell.

[27]  W. Bialek,et al.  Stability and Nuclear Dynamics of the Bicoid Morphogen Gradient , 2007, Cell.

[28]  Hideo Hasegawa Stationary and dynamical properties of finite N-unit Langevin models subjected to multiplicative noises , 2007 .

[29]  W. Bialek,et al.  The Role of Input Noise in Transcriptional Regulation , 2006, PloS one.

[30]  W. Bialek,et al.  Information flow and optimization in transcriptional regulation , 2007, Proceedings of the National Academy of Sciences.

[31]  Gasper Tkacik,et al.  Information capacity of genetic regulatory elements. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[32]  A. Kicheva,et al.  Precision of the Dpp gradient , 2008, Development.

[33]  P. R. ten Wolde,et al.  Role of spatial averaging in the precision of gene expression patterns. , 2009, Physical review letters.

[34]  Gasper Tkacik,et al.  Optimizing information flow in small genetic networks. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[35]  R. Rosenfeld Nature , 2009, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.

[36]  F. Tostevin,et al.  Mutual information between input and output trajectories of biochemical networks. , 2009, Physical review letters.

[37]  W. Bialek,et al.  Diffusion, dimensionality, and noise in transcriptional regulation. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[38]  David H. Sharp,et al.  Canalization of Gene Expression in the Drosophila Blastoderm by Gap Gene Cross Regulation , 2009, PLoS biology.

[39]  A. Kicheva,et al.  Morphogen gradient formation. , 2009, Cold Spring Harbor perspectives in biology.

[40]  Filipe Tostevin,et al.  Mutual information in time-varying biochemical systems. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[41]  Aleksandra M. Walczak,et al.  Optimizing Information Flow in Small Genetic Networks. II. Feed-forward Interactions , 2010 .

[42]  Johannes Jaeger,et al.  Cellular and Molecular Life Sciences REVIEW The gap gene network , 2022 .

[43]  S. Bergmann,et al.  Precision and scaling in morphogen gradient read-out , 2010, Molecular systems biology.

[44]  W. Bialek,et al.  Optimizing information flow in small genetic networks. II. Feed-forward interactions. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[45]  A. Walczak,et al.  Information-optimal transcriptional response to oscillatory driving. , 2010, Physical review letters.

[46]  F. Tostevin,et al.  Effect of feedback on the fidelity of information transmission of time-varying signals. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[47]  Thomas Gregor,et al.  The Onset of Collective Behavior in Social Amoebae , 2010, Science.

[48]  Luciano da Fontoura Costa,et al.  Gene Expression Noise in Spatial Patterning: hunchback Promoter Structure Affects Noise Amplitude and Distribution in Drosophila Segmentation , 2011, PLoS Comput. Biol..

[49]  Satoshi Sawai,et al.  Collective oscillations in developing cells: Insights from simple systems , 2011, Development, growth & differentiation.

[50]  Aleksandra M Walczak,et al.  Information transmission in genetic regulatory networks: a review , 2011, Journal of physics. Condensed matter : an Institute of Physics journal.

[51]  Lewis Wolpert,et al.  Positional information and patterning revisited. , 2011, Journal of theoretical biology.

[52]  Qing Nie,et al.  Noise drives sharpening of gene expression boundaries in the zebrafish hindbrain , 2012, Molecular systems biology.

[53]  Peter S Swain,et al.  Stochastic branching-diffusion models for gene expression , 2012, Proceedings of the National Academy of Sciences.

[54]  Manu,et al.  Drosophila blastoderm patterning. , 2012, Current opinion in genetics & development.

[55]  Pieter Rein ten Wolde,et al.  Mutual Repression Enhances the Steepness and Precision of Gene Expression Boundaries , 2012, PLoS Comput. Biol..

[56]  S. Shvartsman,et al.  Temporal dynamics, spatial range, and transcriptional interpretation of the Dorsal morphogen gradient. , 2012, Current opinion in genetics & development.

[57]  Yoshihiro Morishita,et al.  Encoding and decoding of positional information in morphogen-dependent patterning. , 2012, Current opinion in genetics & development.

[58]  Current Biology , 2012, Current Biology.

[59]  H. Stone,et al.  Spatial-temporal dynamics of collective chemosensing , 2012, Proceedings of the National Academy of Sciences.

[60]  Shawn C. Little,et al.  Precise Developmental Gene Expression Arises from Globally Stochastic Transcriptional Activity , 2013, Cell.

[61]  Sebastian J Maerkl,et al.  Mapping the fine structure of a eukaryotic promoter input-output function , 2013, Nature Genetics.

[62]  Hernan G. Garcia,et al.  Quantitative Imaging of Transcription in Living Drosophila Embryos Links Polymerase Activity to Patterning , 2013, Current Biology.

[63]  Julien O. Dubuis,et al.  Accurate measurements of dynamics and reproducibility in small genetic networks , 2013, Molecular systems biology.

[64]  Bo Sun,et al.  Network characteristics of collective chemosensing. , 2013, Physical review letters.

[65]  Gasper Tkacik,et al.  Positional information, in bits , 2010, Proceedings of the National Academy of Sciences.

[66]  Shawn C. Little,et al.  Maternal Origins of Developmental Reproducibility , 2013, Current Biology.

[67]  Julien O. Dubuis,et al.  Morphogenesis at criticality , 2013, Proceedings of the National Academy of Sciences.

[68]  Julien O. Dubuis,et al.  Positional Information, Positional Error, and Readout Precision in Morphogenesis: A Mathematical Framework , 2014, Genetics.

[69]  Gašper Tkačik,et al.  Noise and information transmission in promoters with multiple internal States. , 2013, Biophysical journal.

[70]  L. Tsimring,et al.  Accurate information transmission through dynamic biochemical signaling networks , 2014, Science.

[71]  F. Tostevin,et al.  The Berg-Purcell limit revisited. , 2014, Biophysical journal.

[72]  Pieter Rein ten Wolde,et al.  Lower bound on the precision of transcriptional regulation and why facilitated diffusion can reduce noise in gene expression. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

[73]  L. Tsimring Noise in biology , 2014, Reports on progress in physics. Physical Society.

[74]  Konrad Basler,et al.  Coordination of Patterning and Growth by the Morphogen DPP , 2014, Current Biology.

[75]  Thibaud Taillefumier,et al.  Optimal Census by Quorum Sensing , 2014, PLoS Comput. Biol..

[76]  Q. Nie,et al.  Robust and precise morphogen-mediated patterning: trade-offs, constraints and mechanisms , 2015, Journal of The Royal Society Interface.

[77]  A. Spirov,et al.  Mid-Embryo Patterning and Precision in Drosophila Segmentation: Krüppel Dual Regulation of hunchback , 2015, PloS one.