Computing within bacteria: Programming of bacterial behavior by means of a plasmid encoding a perceptron neural network
In nature, bacteria exhibit a limited repertoire of behaviors in response to environmental changes. Synthetic biology has now opened up the possibility of programming cells or unicellular organisms in order to enable them to perform certain tasks, which would allow the programming of ’intelligent’ b...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | inglés |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/71548 |
| Acceso en línea: | https://hdl.handle.net/20.500.14352/71548 |
| Access Level: | acceso abierto |
| Palabra clave: | 004.032.26 579.8 Bacterial computing Programming bacterial behavior Neural network computation in bacteria Bio-artificial intelligence Perceptron encoded in a plasmid Biomatemáticas Microbiología (Biología) 2404 Biomatemáticas 2414 Microbiología |
| Sumario: | In nature, bacteria exhibit a limited repertoire of behaviors in response to environmental changes. Synthetic biology has now opened up the possibility of programming cells or unicellular organisms in order to enable them to perform certain tasks, which would allow the programming of ’intelligent’ bacteria. Many of the theoretical ideas that Liberman proposed last century, for example his seminal idea that a cell is a computer, are now being put into practice with bacterial colonies in both wet and in silico experiments. These bacteria may one day be used to solve a wide range of problems whose solution requires their adaptation to external changes either within a bioreactor, organ or tissue of a patient or through the design of microbial-synthetic consortia oriented to their use in bioprocesses to produce medicines, biofuels or biomaterials. In this work, we show the possibility of programming synthetic bacteria with a previously trained perceptron neural network. First, we illustrate how a colony of bacteria endowed with a perceptron is able to solve an optimization problem in silico. Secondly, we study by means of in silico simulations how a perceptron can be applied to program behaviors in bacteria leading to social interactions and to the formation of complex communities that in the future would be useful in biotechnology. Finally, we go a step further, and study how the above perceptron designed to program bacterial behavior is implemented in a genetic circuit designed for this purpose. Once the genetic circuit was obtained, it was engineered into a plasmid. |
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