Mutual Information Upper Bound of Molecular Communication Based on Cell Metabolism

Authors

Massimiliano Pierobon, University of Nebraska - LincolnFollow
Zahmeeth Sakkaff, University of Nebraska-LincolnFollow
Jennie L. Catlett, University of Nebraska-Lincoln
Nicole R. Buan, University of Nebraska-LincolnFollow

Document Type

Article

Date of this Version

2016

Citation

Pierobon^ɤ, M., Sakkaff, Z., Catlett^§, J.L., Buan, N.R. 2016. Mutual Information Upper Bound of Molecular Communication Based on Cell Metabolism. Institute of Electrical and Electronics Engineers (IEEE) 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2016).

DOI: 10.1109/SPAWC.2016.7536835.

Comments

©2016 IEEE. Used by permission.

Abstract

Synthetic biology is providing novel tools to engineer cells and access the basis of their molecular information processing, including their communication channels based on chemical reactions and molecule exchange. Molecular communication is a discipline in communication engineering that studies these types of communications and ways to exploit them for novel purposes, such as the development of ubiquitous and heterogeneous communication networks to interconnect biological cells with nano and biotechnology-enabled devices, i.e., the Internet of Bio-Nano Things. One major problem in synthetic biology stands in the development of reliable techniques to control the engineered cells from the external environment. In this paper, molecular communication concepts are applied to study the potential of cell metabolism, and its regulation, to serve this purpose. In particular, a communication system abstraction is introduced to obtain a binary encoder model of the mechanisms underlying the regulation of the chemical reactions activity within the cell metabolism in function of the chemical composition of the external environment. Stemming from this model, an upper bound to the information theoretic mutual information is obtained through the use of a well-known and computationally efficient metabolic simulation technique. This upper bound stands as a theoretical limit of the ability of a particular cell to internally represent the information contained in the chemical composition of the external environment. Numerical results related to the metabolism of the E. coli bacterium are presented to evaluate the proposed approach.