Literature DB >> 30340045

Real-Time Genetic Compensation Defines the Dynamic Demands of Feedback Control.

Patrick Harrigan1, Hiten D Madhani2, Hana El-Samad3.   

Abstract

Biological signaling networks use feedback control to dynamically adjust their operation in real time. Traditional static genetic methods such as gene knockouts or rescue experiments can often identify the existence of feedback interactions but are unable to determine what feedback dynamics are required. Here, we implement a new strategy, closed-loop optogenetic compensation (CLOC), to address this problem. Using a custom-built hardware and software infrastructure, CLOC monitors, in real time, the output of a pathway deleted for a feedback regulator. A minimal model uses these measurements to calculate and deliver-on the fly-an optogenetically enabled transcriptional input designed to compensate for the effects of the feedback deletion. Application of CLOC to the yeast pheromone response pathway revealed surprisingly distinct dynamic requirements for three well-studied feedback regulators. CLOC, a marriage of control theory and traditional genetics, presents a broadly applicable methodology for defining the dynamic function of biological feedback regulators.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  closed-loop control; feedback; optogenetics; yeast mating pathway

Mesh:

Substances:

Year:  2018        PMID: 30340045      PMCID: PMC6258208          DOI: 10.1016/j.cell.2018.09.044

Source DB:  PubMed          Journal:  Cell        ISSN: 0092-8674            Impact factor:   41.582


  39 in total

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Authors:  B Ren; F Robert; J J Wyrick; O Aparicio; E G Jennings; I Simon; J Zeitlinger; J Schreiber; N Hannett; E Kanin; T L Volkert; C J Wilson; S P Bell; R A Young
Journal:  Science       Date:  2000-12-22       Impact factor: 47.728

2.  A positive-feedback-based bistable 'memory module' that governs a cell fate decision.

Authors:  Wen Xiong; James E Ferrell
Journal:  Nature       Date:  2003-11-27       Impact factor: 49.962

3.  Systems-level dissection of the cell-cycle oscillator: bypassing positive feedback produces damped oscillations.

Authors:  Joseph R Pomerening; Sun Young Kim; James E Ferrell
Journal:  Cell       Date:  2005-08-26       Impact factor: 41.582

4.  Negative autoregulation linearizes the dose-response and suppresses the heterogeneity of gene expression.

Authors:  Dmitry Nevozhay; Rhys M Adams; Kevin F Murphy; Kresimir Josic; Gábor Balázsi
Journal:  Proc Natl Acad Sci U S A       Date:  2009-03-11       Impact factor: 11.205

5.  Quantitative phosphoproteomics applied to the yeast pheromone signaling pathway.

Authors:  Albrecht Gruhler; Jesper V Olsen; Shabaz Mohammed; Peter Mortensen; Nils J Faergeman; Matthias Mann; Ole N Jensen
Journal:  Mol Cell Proteomics       Date:  2005-01-22       Impact factor: 5.911

6.  Regulation of MAPK function by direct interaction with the mating-specific Galpha in yeast.

Authors:  Metodi V Metodiev; Dina Matheos; Mark D Rose; David E Stone
Journal:  Science       Date:  2002-05-24       Impact factor: 47.728

7.  Genome-scale analysis reveals Sst2 as the principal regulator of mating pheromone signaling in the yeast Saccharomyces cerevisiae.

Authors:  Scott A Chasse; Paul Flanary; Stephen C Parnell; Nan Hao; Jiyoung Y Cha; David P Siderovski; Henrik G Dohlman
Journal:  Eukaryot Cell       Date:  2006-02

8.  Control of Protein Activity and Cell Fate Specification via Light-Mediated Nuclear Translocation.

Authors:  Hayretin Yumerefendi; Daniel J Dickinson; Hui Wang; Seth P Zimmerman; James E Bear; Bob Goldstein; Klaus Hahn; Brian Kuhlman
Journal:  PLoS One       Date:  2015-06-17       Impact factor: 3.240

9.  Negative feedback that improves information transmission in yeast signalling.

Authors:  Richard C Yu; C Gustavo Pesce; Alejandro Colman-Lerner; Larry Lok; David Pincus; Eduard Serra; Mark Holl; Kirsten Benjamin; Andrew Gordon; Roger Brent
Journal:  Nature       Date:  2008-12-11       Impact factor: 49.962

10.  Automated optogenetic feedback control for precise and robust regulation of gene expression and cell growth.

Authors:  Andreas Milias-Argeitis; Marc Rullan; Stephanie K Aoki; Peter Buchmann; Mustafa Khammash
Journal:  Nat Commun       Date:  2016-08-26       Impact factor: 14.919

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  16 in total

1.  Reverse and Forward Engineering Multicellular Structures with Optogenetics.

Authors:  Thomas R Mumford; Lee Roth; Lukasz J Bugaj
Journal:  Curr Opin Biomed Eng       Date:  2020-10-14

2.  Cell-machine interfaces for characterizing gene regulatory network dynamics.

Authors:  Jean-Baptiste Lugagne; Mary J Dunlop
Journal:  Curr Opin Syst Biol       Date:  2019-02-01

3.  Engineering a Model Cell for Rational Tuning of GPCR Signaling.

Authors:  William M Shaw; Hitoshi Yamauchi; Jack Mead; Glen-Oliver F Gowers; David J Bell; David Öling; Niklas Larsson; Mark Wigglesworth; Graham Ladds; Tom Ellis
Journal:  Cell       Date:  2019-04-04       Impact factor: 41.582

4.  Enhancing bioreactor arrays for automated measurements and reactive control with ReacSight.

Authors:  François Bertaux; Sebastián Sosa-Carrillo; Viktoriia Gross; Achille Fraisse; Chetan Aditya; Mariela Furstenheim; Gregory Batt
Journal:  Nat Commun       Date:  2022-06-11       Impact factor: 17.694

5.  A yeast optogenetic toolkit (yOTK) for gene expression control in Saccharomyces cerevisiae.

Authors:  Jidapas My An-Adirekkun; Cameron J Stewart; Stephanie H Geller; Michael T Patel; Justin Melendez; Benjamin L Oakes; Marcus B Noyes; Megan N McClean
Journal:  Biotechnol Bioeng       Date:  2019-12-18       Impact factor: 4.530

6.  Optogenetic Control Reveals Differential Promoter Interpretation of Transcription Factor Nuclear Translocation Dynamics.

Authors:  Susan Y Chen; Lindsey C Osimiri; Michael Chevalier; Lukasz J Bugaj; Taylor H Nguyen; R A Greenstein; Andrew H Ng; Jacob Stewart-Ornstein; Lauren T Neves; Hana El-Samad
Journal:  Cell Syst       Date:  2020-09-07       Impact factor: 10.304

7.  Biological signal generators: integrating synthetic biology tools and in silico control.

Authors:  Taylor D Scott; Kieran Sweeney; Megan N McClean
Journal:  Curr Opin Syst Biol       Date:  2019-02-27

Review 8.  Steering Molecular Activity with Optogenetics: Recent Advances and Perspectives.

Authors:  Teak-Jung Oh; Huaxun Fan; Savanna S Skeeters; Kai Zhang
Journal:  Adv Biol (Weinh)       Date:  2021-01-14

9.  DeLTA: Automated cell segmentation, tracking, and lineage reconstruction using deep learning.

Authors:  Jean-Baptiste Lugagne; Haonan Lin; Mary J Dunlop
Journal:  PLoS Comput Biol       Date:  2020-04-13       Impact factor: 4.475

10.  Diverse Cell Stimulation Kinetics Identify Predictive Signal Transduction Models.

Authors:  Hossein Jashnsaz; Zachary R Fox; Jason J Hughes; Guoliang Li; Brian Munsky; Gregor Neuert
Journal:  iScience       Date:  2020-09-15
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