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Cellular Computing$
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Martyn Amos

Print publication date: 2004

Print ISBN-13: 9780195155396

Published to Oxford Scholarship Online: November 2020

DOI: 10.1093/oso/9780195155396.001.0001

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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 16 October 2021

The Device Science of Whole Cells as Components in Microscale and Nanoscale Systems

The Device Science of Whole Cells as Components in Microscale and Nanoscale Systems

(p.74) 5 The Device Science of Whole Cells as Components in Microscale and Nanoscale Systems
Cellular Computing

Michael L. Simpson

Gary S. Sayler

Oxford University Press

Intact whole cells may be the ultimate functional molecular-scale machines, and our ability to manipulate the genetic mechanisms that control these functions is relatively advanced when compared to our ability to control the synthesis and direct the assembly of man-made materials into systems of comparable complexity and functional density. Although engineered whole cells deployed in biosensor systems provide one of the practical successes of molecular-scale devices, these devices explore only a small portion of the full functionality of the cells. Individual or self-organized groups of cells exhibit extremely complex functionality that includes sensing, communication, navigation, cooperation, and even fabrication of synthetic nanoscopic materials. Adding this functionality to engineered systems provides motivation for deploying whole cells as components in microscale and nanoscale devices. In this chapter we focus on the device science of whole cell components in a way analogous to the device physics of semiconductor components. We consider engineering the information transport within and between cells, communication between cells and synthetic devices, the integration of cells into nanostructured and microstructured substrates to form highly functional systems, and modeling and simulation of information processing in cells. Even a casual examination of the information processing density of prokaryotic cells produces an appreciation for the advanced state of the cell’s capabilities. A bacterial cell such as Escherichia coli ( 2 μm2 cross-sectional area) with a 4.6 million basepair chromosome has the equivalent of a 9.2-megabit memory. This memory codes for as many as 4300 different polypeptides under the inducible control of several hundred different promoters. These polypeptides perform metabolic and regulatory functions that process the energy and information, respectively, made available to the cell. This complexity of functionality allows the cell to interact with, influence, and, to some degree, control its environment. Compare this to the silicon semiconductor situation as described in the International Technology Roadmap for Semiconductors (ITRS). ITRS predicts that by the year 2014, memory density will reach 24.5 Gbits/cm2, and logic transistor density will reach 664 M/cm2. Assuming four transistors per logic function, 2 μm2 of silicon could contain a 490-bit memory or approximately three simple logic gates.

Keywords:   Action potential, Biocide, Cardiomyocyte, Disease, Electron, Fabrication, Hill repression, Inhibitor, Latch

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