%0 Journal Article
%T Rational programming of history-dependent logic in cellular populations
%+ Centre de Biochimie Structurale [Montpellier] (CBS)
%+ University of Washington [Seattle]
%+ Matière et Systèmes Complexes (MSC)
%+ Laboratoire Charles Coulomb (L2C)
%+ Laboratoire Physico-Chimie Curie [Institut Curie] (PCC)
%A Zúñiga, Ana
%A Guiziou, Sarah
%A Mayonove, Pauline
%A Meriem, Zachary Ben
%A Camacho, Miguel
%A Moreau, Violaine
%A Ciandrini, Luca
%A Hersen, Pascal
%A Bonnet, Jerome
%Z Support was provided by an ERC Starting Grant “Compucell,” the INSERM Atip-Avenir program and the Bettencourt-Schueller Foundation. S.G. was supported by a Ph.D. fellowship from the French Ministry of Research and the French Foundation for Medical Research (FRM) FDT20170437282. Z.B.M. and P.H. were supported by an ERC Consolidator grant “Smartcells.” The CBS acknowledges support from the French Infrastructure for Integrated Structural Biology (FRISBI) ANR-10-INSB-05-01.
%< avec comité de lecture
%@ 2041-1723
%J Nature Communications
%I Nature Publishing Group
%V 11
%N 1
%P 4758
%8 2020-09-21
%D 2020
%R 10.1038/s41467-020-18455-z
%M 32958811
%Z Life Sciences [q-bio]/Cellular BiologyJournal articles
%X Genetic programs operating in a history-dependent fashion are ubiquitous in nature and govern sophisticated processes such as development and differentiation. The ability to systematically and predictably encode such programs would advance the engineering of synthetic organisms and ecosystems with rich signal processing abilities. Here we implement robust, scalable history-dependent programs by distributing the computational labor across a cellular population. Our design is based on standardized recombinase-driven DNA scaffolds expressing different genes according to the order of occurrence of inputs. These multicellular computing systems are highly modular, do not require cell-cell communication channels, and any program can be built by differential composition of strains containing well-characterized logic scaffolds. We developed automated workflows that researchers can use to streamline program design and optimization. We anticipate that the history-dependent programs presented here will support many applications using cellular populations for material engineering, biomanufacturing and healthcare.
%G English
%2 https://inserm.hal.science/inserm-02952457/document
%2 https://inserm.hal.science/inserm-02952457/file/s41467-020-18455-z.pdf
%L inserm-02952457
%U https://inserm.hal.science/inserm-02952457
%~ INSERM
%~ CNRS
%~ CBS
%~ L2C
%~ FNCLCC
%~ CURIE
%~ PCC_UMR168
%~ INC-CNRS
%~ PSL
%~ MIPS
%~ BS
%~ UNIV-MONTPELLIER
%~ SORBONNE-UNIVERSITE
%~ SORBONNE-UNIV
%~ SU-SCIENCES
%~ UNIV-PARIS
%~ UNIVERSITE-PARIS
%~ UP-SCIENCES
%~ TEST-HALCNRS
%~ INSTITUT-CURIE-PSL
%~ SU-TI
%~ ANR
%~ MSC-LAB
%~ ALLIANCE-SU
%~ UM-2015-2021
%~ FRM