Literature DB >> 33436729

Engineering calcium signaling of astrocytes for neural-molecular computing logic gates.

Michael Taynnan Barros1,2, Phuong Doan3, Meenakshisundaram Kandhavelu3, Brendan Jennings4, Sasitharan Balasubramaniam4,5.   

Abstract

This paper proposes the use of astrocytes to realize Boolean logic gates, through manipulation of the threshold of [Formula: see text] ion flows between the cells based on the input signals. Through wet-lab experiments that engineer the astrocytes cells with pcDNA3.1-hGPR17 genes as well as chemical compounds, we show that both AND and OR gates can be implemented by controlling [Formula: see text] signals that flow through the population. A reinforced learning platform is also presented in the paper to optimize the [Formula: see text] activated level and time slot of input signals [Formula: see text] into the gate. This design platform caters for any size and connectivity of the cell population, by taking into consideration the delay and noise produced from the signalling between the cells. To validate the effectiveness of the reinforced learning platform, a [Formula: see text] signalling simulator was used to simulate the signalling between the astrocyte cells. The results from the simulation show that an optimum value for both the [Formula: see text] activated level and time slot of input signals [Formula: see text] is required to achieve up to 90% accuracy for both the AND and OR gates. Our method can be used as the basis for future Neural-Molecular Computing chips, constructed from engineered astrocyte cells, which can form the basis for a new generation of brain implants.

Entities:  

Year:  2021        PMID: 33436729      PMCID: PMC7803753          DOI: 10.1038/s41598-020-79891-x

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  23 in total

1.  A synthetic oscillatory network of transcriptional regulators.

Authors:  M B Elowitz; S Leibler
Journal:  Nature       Date:  2000-01-20       Impact factor: 49.962

2.  Programmable single-cell mammalian biocomputers.

Authors:  Simon Ausländer; David Ausländer; Marius Müller; Markus Wieland; Martin Fussenegger
Journal:  Nature       Date:  2012-07-05       Impact factor: 49.962

3.  Synthetic circuits integrating logic and memory in living cells.

Authors:  Piro Siuti; John Yazbek; Timothy K Lu
Journal:  Nat Biotechnol       Date:  2013-02-10       Impact factor: 54.908

4.  Robust multicellular computing using genetically encoded NOR gates and chemical 'wires'.

Authors:  Alvin Tamsir; Jeffrey J Tabor; Christopher A Voigt
Journal:  Nature       Date:  2010-12-08       Impact factor: 49.962

Review 5.  Synthetic biology in mammalian cells: next generation research tools and therapeutics.

Authors:  Florian Lienert; Jason J Lohmueller; Abhishek Garg; Pamela A Silver
Journal:  Nat Rev Mol Cell Biol       Date:  2014-01-17       Impact factor: 94.444

Review 6.  Synthetic mammalian gene circuits for biomedical applications.

Authors:  Haifeng Ye; Dominique Aubel; Martin Fussenegger
Journal:  Curr Opin Chem Biol       Date:  2013-12       Impact factor: 8.822

7.  Genetic programs can be compressed and autonomously decompressed in live cells.

Authors:  Nicolas Lapique; Yaakov Benenson
Journal:  Nat Nanotechnol       Date:  2017-11-13       Impact factor: 39.213

8.  Programmable intracellular DNA biocomputing circuits for reliable cell recognitions.

Authors:  Xue Gong; Jie Wei; Jing Liu; Ruomeng Li; Xiaoqing Liu; Fuan Wang
Journal:  Chem Sci       Date:  2019-01-15       Impact factor: 9.825

9.  Environmental signal integration by a modular AND gate.

Authors:  J Christopher Anderson; Christopher A Voigt; Adam P Arkin
Journal:  Mol Syst Biol       Date:  2007-08-14       Impact factor: 11.429

10.  Controlled Information Transfer Through An In Vivo Nervous System.

Authors:  Naveed A Abbasi; Dilan Lafci; Ozgur B Akan
Journal:  Sci Rep       Date:  2018-02-02       Impact factor: 4.379

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  1 in total

1.  Molecular Communications in Viral Infections Research: Modeling, Experimental Data, and Future Directions.

Authors:  Michael Taynnan Barros; Mladen Veletic; Masamitsu Kanada; Massimiliano Pierobon; Seppo Vainio; Ilangko Balasingham; Sasitharan Balasubramaniam
Journal:  IEEE Trans Mol Biol Multiscale Commun       Date:  2021-04-15
  1 in total

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