Engineered Bacteria Convert a 3-Bit Binary Code to a 3-Bit Gray Code by Multicellular Artificial-Neural-Network-Type Architecture

The neuromorphic computing with genetically engineered cells is still in its infancy and shows great promise to solve various complex computational problems. The success of such computing is dependent on the expansion of its capability to build new and versatile computation functions. The conversion of a binary code to a Gray code is a fundamental concept in digital electronics and computer science. In this work, by using genetically engineered <i>E. coli</i> cells, we created a single-layer artificial neural network (ANN) that works as a 3-bit-binary to Gray code converter. The ANN architecture is built by five engineered <i>E. coli</i> populations in a liquid culture, where a binary input in chemical form is given by adding or not adding (1/0) three chemical inputs, and the converted codes are manifested by the appropriate expression of three fluorescent proteins. The work may have significance in biocomputer technology development, bacterial ANN, and synthetic biology.

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Publication Details

Journal
ACS Synthetic Biology
Published
2025-05-07
DOI
https://doi.org/10.1021/acssynbio.5c00145
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Engineered Bacteria Convert a 3-Bit Binary Code to a 3-Bit Gray Code by Multicellular Artificial-Neural-Network-Type Architecture

Sangram Bagh, Saswata Chakraborty
ACS Synthetic Biology
Cell Image Analysis Techniques
article

Engineered Bacteria Convert a 3-Bit Binary Code to a 3-Bit Gray Code by Multicellular Artificial-Neural-Network-Type Architecture

Sangram Bagh, Saswata Chakraborty
article en

Abstract

The neuromorphic computing with genetically engineered cells is still in its infancy and shows great promise to solve various complex computational problems. The success of such computing is dependent on the expansion of its capability to build new and versatile computation functions. The conversion of a binary code to a Gray code is a fundamental concept in digital electronics and computer science. In this work, by using genetically engineered <i>E. coli</i> cells, we created a single-layer artificial neural network (ANN) that works as a 3-bit-binary to Gray code converter. The ANN architecture is built by five engineered <i>E. coli</i> populations in a liquid culture, where a binary input in chemical form is given by adding or not adding (1/0) three chemical inputs, and the converted codes are manifested by the appropriate expression of three fluorescent proteins. The work may have significance in biocomputer technology development, bacterial ANN, and synthetic biology.

ACS Synthetic BiologyVol. 14(9)
Saha Institute of Nuclear Physics (IN), Homi Bhabha National Institute (IN)
Saha Institute of Nuclear Physics, Department of Atomic Energy, Government of India
Openalex Percentile: Top 92%
Cell Image Analysis Techniques
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