Literature DB >> 31579842

Cell-machine interfaces for characterizing gene regulatory network dynamics.

Jean-Baptiste Lugagne1,2, Mary J Dunlop1,2.   

Abstract

Gene regulatory networks and the dynamic responses they produce offer a wealth of information about how biological systems process information about their environment. Recently, researchers interested in dissecting these networks have been outsourcing various parts of their experimental workflow to computers. Here we review how, using microfluidic or optogenetic tools coupled with fluorescence imaging, it is now possible to interface cells and computers. These platforms enable scientists to perform informative dynamic stimulations of genetic pathways and monitor their reaction. It is also possible to close the loop and regulate genes in real time, providing an unprecedented view of how signals propagate through the network. Finally, we outline new tools that can be used within the framework of cell-machine interfaces.

Entities:  

Year:  2019        PMID: 31579842      PMCID: PMC6774389          DOI: 10.1016/j.coisb.2019.01.001

Source DB:  PubMed          Journal:  Curr Opin Syst Biol        ISSN: 2452-3100


  59 in total

1.  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

2.  Rate of environmental change determines stress response specificity.

Authors:  Jonathan W Young; James C W Locke; Michael B Elowitz
Journal:  Proc Natl Acad Sci U S A       Date:  2013-02-13       Impact factor: 11.205

3.  Characterizing bacterial gene circuit dynamics with optically programmed gene expression signals.

Authors:  Evan J Olson; Lucas A Hartsough; Brian P Landry; Raghav Shroff; Jeffrey J Tabor
Journal:  Nat Methods       Date:  2014-03-09       Impact factor: 28.547

4.  Antithetic Integral Feedback Ensures Robust Perfect Adaptation in Noisy Biomolecular Networks.

Authors:  Corentin Briat; Ankit Gupta; Mustafa Khammash
Journal:  Cell Syst       Date:  2016-01-27       Impact factor: 10.304

Review 5.  Super-resolution fluorescent materials: an insight into design and bioimaging applications.

Authors:  Zhigang Yang; Amit Sharma; Jing Qi; Xiao Peng; Dong Yeop Lee; Rui Hu; Danying Lin; Junle Qu; Jong Seung Kim
Journal:  Chem Soc Rev       Date:  2016-08-22       Impact factor: 54.564

Review 6.  Optogenetic switches for light-controlled gene expression in yeast.

Authors:  Francisco Salinas; Vicente Rojas; Verónica Delgado; Eduardo Agosin; Luis F Larrondo
Journal:  Appl Microbiol Biotechnol       Date:  2017-02-16       Impact factor: 4.813

Review 7.  Understanding Biological Regulation Through Synthetic Biology.

Authors:  Caleb J Bashor; James J Collins
Journal:  Annu Rev Biophys       Date:  2018-03-16       Impact factor: 12.981

8.  Metabolic gene regulation in a dynamically changing environment.

Authors:  Matthew R Bennett; Wyming Lee Pang; Natalie A Ostroff; Bridget L Baumgartner; Sujata Nayak; Lev S Tsimring; Jeff Hasty
Journal:  Nature       Date:  2008-07-30       Impact factor: 49.962

9.  Regulation of Gene Expression and Signaling Pathway Activity in Mammalian Cells by Automated Microfluidics Feedback Control.

Authors:  Lorena Postiglione; Sara Napolitano; Elisa Pedone; Daniel L Rocca; Francesco Aulicino; Marco Santorelli; Barbara Tumaini; Lucia Marucci; Diego di Bernardo
Journal:  ACS Synth Biol       Date:  2018-10-22       Impact factor: 5.110

10.  Synthetic far-red light-mediated CRISPR-dCas9 device for inducing functional neuronal differentiation.

Authors:  Jiawei Shao; Meiyan Wang; Guiling Yu; Sucheng Zhu; Yuanhuan Yu; Boon Chin Heng; Jiali Wu; Haifeng Ye
Journal:  Proc Natl Acad Sci U S A       Date:  2018-07-02       Impact factor: 11.205

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  10 in total

1.  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

Review 2.  Functional roles of microbial cell-to-cell heterogeneity and emerging technologies for analysis and control.

Authors:  Nadia Maria Vieira Sampaio; Mary J Dunlop
Journal:  Curr Opin Microbiol       Date:  2020-09-09       Impact factor: 7.934

3.  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

4.  Dynamic gene expression and growth underlie cell-to-cell heterogeneity in Escherichia coli stress response.

Authors:  Nadia M V Sampaio; Caroline M Blassick; Virgile Andreani; Jean-Baptiste Lugagne; Mary J Dunlop
Journal:  Proc Natl Acad Sci U S A       Date:  2022-03-28       Impact factor: 12.779

5.  A Microfluidic Device for Imaging Samples from Microbial Suspension Cultures.

Authors:  Alexander Letourneau; Jack Kegel; Jehad Al-Ramahi; Emily Yachinich; Harris B Krause; Cameron J Stewart; Megan N McClean
Journal:  MethodsX       Date:  2020-04-24

Review 6.  Autonomous and Assisted Control for Synthetic Microbiology.

Authors:  Alvaro Banderas; Matthias Le Bec; Céline Cordier; Pascal Hersen
Journal:  Int J Mol Sci       Date:  2020-12-03       Impact factor: 5.923

Review 7.  Exploiting Information and Control Theory for Directing Gene Expression in Cell Populations.

Authors:  Lucas Henrion; Mathéo Delvenne; Fatemeh Bajoul Kakahi; Fabian Moreno-Avitia; Frank Delvigne
Journal:  Front Microbiol       Date:  2022-04-25       Impact factor: 5.640

Review 8.  Platforms for Optogenetic Stimulation and Feedback Control.

Authors:  Sant Kumar; Mustafa Khammash
Journal:  Front Bioeng Biotechnol       Date:  2022-06-08

9.  Light-Inducible Recombinases for Bacterial Optogenetics.

Authors:  Michael B Sheets; Wilson W Wong; Mary J Dunlop
Journal:  ACS Synth Biol       Date:  2020-01-21       Impact factor: 5.110

10.  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 in total

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