Unknown

Dataset Information

0

Rational programming of history-dependent logic in cellular populations.


ABSTRACT: 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.

SUBMITTER: Zuniga A 

PROVIDER: S-EPMC7506022 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

altmetric image

Publications

Rational programming of history-dependent logic in cellular populations.

Zúñiga Ana A   Guiziou Sarah S   Mayonove Pauline P   Meriem Zachary Ben ZB   Camacho Miguel M   Moreau Violaine V   Ciandrini Luca L   Hersen Pascal P   Bonnet Jerome J  

Nature communications 20200921 1


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  ...[more]

Similar Datasets

| S-EPMC539352 | biostudies-literature
| S-EPMC3615990 | biostudies-literature
| S-EPMC5569101 | biostudies-literature
| S-EPMC4190110 | biostudies-literature
| S-EPMC3913550 | biostudies-literature
| S-EPMC4233684 | biostudies-literature
| S-EPMC6078203 | biostudies-literature
2017-12-19 | GSE96719 | GEO
| S-EPMC3753570 | biostudies-literature
| S-EPMC4410912 | biostudies-literature