Literature DB >> 24966234

Nonlinear signalling networks and cell-to-cell variability transform external signals into broadly distributed or bimodal responses.

Maciej Dobrzyński1, Lan K Nguyen2, Marc R Birtwistle3, Alexander von Kriegsheim2, Alfonso Blanco Fernández4, Alex Cheong5, Walter Kolch6, Boris N Kholodenko7.   

Abstract

We show theoretically and experimentally a mechanism behind the emergence of wide or bimodal protein distributions in biochemical networks with nonlinear input-output characteristics (the dose-response curve) and variability in protein abundance. Large cell-to-cell variation in the nonlinear dose-response characteristics can be beneficial to facilitate two distinct groups of response levels as opposed to a graded response. Under the circumstances that we quantify mathematically, the two distinct responses can coexist within a cellular population, leading to the emergence of a bimodal protein distribution. Using flow cytometry, we demonstrate the appearance of wide distributions in the hypoxia-inducible factor-mediated response network in HCT116 cells. With help of our theoretical framework, we perform a novel calculation of the magnitude of cell-to-cell heterogeneity in the dose-response obtained experimentally.
© 2014 The Author(s) Published by the Royal Society. All rights reserved.

Entities:  

Keywords:  bimodality; cell heterogeneity; dose–response; signalling networks

Mesh:

Substances:

Year:  2014        PMID: 24966234      PMCID: PMC4233687          DOI: 10.1098/rsif.2014.0383

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.118


  43 in total

1.  Bimodal gene expression in noncooperative regulatory systems.

Authors:  Anna Ochab-Marcinek; Marcin Tabaka
Journal:  Proc Natl Acad Sci U S A       Date:  2010-12-06       Impact factor: 11.205

Review 2.  Hypoxia-inducible factors in physiology and medicine.

Authors:  Gregg L Semenza
Journal:  Cell       Date:  2012-02-03       Impact factor: 41.582

3.  Dynamic proteomics of individual cancer cells in response to a drug.

Authors:  A A Cohen; N Geva-Zatorsky; E Eden; M Frenkel-Morgenstern; I Issaeva; A Sigal; R Milo; C Cohen-Saidon; Y Liron; Z Kam; L Cohen; T Danon; N Perzov; U Alon
Journal:  Science       Date:  2008-11-20       Impact factor: 47.728

4.  A stochastic spectral analysis of transcriptional regulatory cascades.

Authors:  Aleksandra M Walczak; Andrew Mugler; Chris H Wiggins
Journal:  Proc Natl Acad Sci U S A       Date:  2009-04-07       Impact factor: 11.205

5.  Information flow and optimization in transcriptional regulation.

Authors:  Gasper Tkacik; Curtis G Callan; William Bialek
Journal:  Proc Natl Acad Sci U S A       Date:  2008-08-21       Impact factor: 11.205

6.  Mammalian protein expression noise: scaling principles and the implications for knockdown experiments.

Authors:  Marc R Birtwistle; Alexander von Kriegsheim; Maciej Dobrzyński; Boris N Kholodenko; Walter Kolch
Journal:  Mol Biosyst       Date:  2012-11

7.  RNA dynamics in live Escherichia coli cells.

Authors:  Ido Golding; Edward C Cox
Journal:  Proc Natl Acad Sci U S A       Date:  2004-07-26       Impact factor: 11.205

8.  Reactivating HIF prolyl hydroxylases under hypoxia results in metabolic catastrophe and cell death.

Authors:  D A Tennant; C Frezza; E D MacKenzie; Q D Nguyen; L Zheng; M A Selak; D L Roberts; C Dive; D G Watson; E O Aboagye; E Gottlieb
Journal:  Oncogene       Date:  2009-08-31       Impact factor: 9.867

9.  Emergence of bimodal cell population responses from the interplay between analog single-cell signaling and protein expression noise.

Authors:  Marc R Birtwistle; Jens Rauch; Anatoly Kiyatkin; Edita Aksamitiene; Maciej Dobrzyński; Jan B Hoek; Walter Kolch; Babatunde A Ogunnaike; Boris N Kholodenko
Journal:  BMC Syst Biol       Date:  2012-08-24

10.  Exploring the contextual sensitivity of factors that determine cell-to-cell variability in receptor-mediated apoptosis.

Authors:  Suzanne Gaudet; Sabrina L Spencer; William W Chen; Peter K Sorger
Journal:  PLoS Comput Biol       Date:  2012-04-26       Impact factor: 4.475

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  14 in total

Review 1.  New insights into RAS biology reinvigorate interest in mathematical modeling of RAS signaling.

Authors:  Keesha E Erickson; Oleksii S Rukhlenko; Richard G Posner; William S Hlavacek; Boris N Kholodenko
Journal:  Semin Cancer Biol       Date:  2018-03-05       Impact factor: 15.707

Review 2.  Unsupervised machine learning for exploratory data analysis in imaging mass spectrometry.

Authors:  Nico Verbeeck; Richard M Caprioli; Raf Van de Plas
Journal:  Mass Spectrom Rev       Date:  2019-10-11       Impact factor: 10.946

3.  MarcoPolo: a method to discover differentially expressed genes in single-cell RNA-seq data without depending on prior clustering.

Authors:  Chanwoo Kim; Hanbin Lee; Juhee Jeong; Keehoon Jung; Buhm Han
Journal:  Nucleic Acids Res       Date:  2022-07-08       Impact factor: 19.160

Review 4.  The dynamic control of signal transduction networks in cancer cells.

Authors:  Walter Kolch; Melinda Halasz; Marina Granovskaya; Boris N Kholodenko
Journal:  Nat Rev Cancer       Date:  2015-08-20       Impact factor: 60.716

5.  ZERO-INFLATED QUANTILE RANK-SCORE BASED TEST (ZIQRANK) WITH APPLICATION TO SCRNA-SEQ DIFFERENTIAL GENE EXPRESSION ANALYSIS.

Authors:  Wodan Ling; Wenfei Zhang; Bin Cheng; Ying Wei
Journal:  Ann Appl Stat       Date:  2021-12-21       Impact factor: 2.083

6.  Species differential regulation of COX2 can be described by an NFκB-dependent logic AND gate.

Authors:  Lan K Nguyen; Miguel A S Cavadas; Boris N Kholodenko; Till D Frank; Alex Cheong
Journal:  Cell Mol Life Sci       Date:  2015-02-20       Impact factor: 9.261

7.  A statistical approach for identifying differential distributions in single-cell RNA-seq experiments.

Authors:  Keegan D Korthauer; Li-Fang Chu; Michael A Newton; Yuan Li; James Thomson; Ron Stewart; Christina Kendziorski
Journal:  Genome Biol       Date:  2016-10-25       Impact factor: 13.583

Review 8.  Multiplicity of Mathematical Modeling Strategies to Search for Molecular and Cellular Insights into Bacteria Lung Infection.

Authors:  Martina Cantone; Guido Santos; Pia Wentker; Xin Lai; Julio Vera
Journal:  Front Physiol       Date:  2017-08-30       Impact factor: 4.566

9.  DYVIPAC: an integrated analysis and visualisation framework to probe multi-dimensional biological networks.

Authors:  Lan K Nguyen; Andrea Degasperi; Philip Cotter; Boris N Kholodenko
Journal:  Sci Rep       Date:  2015-07-29       Impact factor: 4.379

10.  Bistability in the Rac1, PAK, and RhoA Signaling Network Drives Actin Cytoskeleton Dynamics and Cell Motility Switches.

Authors:  Kate M Byrne; Naser Monsefi; John C Dawson; Andrea Degasperi; Jimi-Carlo Bukowski-Wills; Natalia Volinsky; Maciej Dobrzyński; Marc R Birtwistle; Mikhail A Tsyganov; Anatoly Kiyatkin; Katarzyna Kida; Andrew J Finch; Neil O Carragher; Walter Kolch; Lan K Nguyen; Alex von Kriegsheim; Boris N Kholodenko
Journal:  Cell Syst       Date:  2016-01-27       Impact factor: 10.304

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