RESEARCH ARTICLE


Modeling Gene Expression and Protein Delivery as an End-to-End Digital Communication System



Yesenia Cevallos1, Tadashi Nakano2, Luis Tello-Oquendo1, *, Deysi Inca1, Ivone Santillán3, Amin Zadeh Shirazi4, Ahmad Rushdi5, Nicolay Samaniego1
1 College of Engineering, Universidad Nacional de Chimborazo, Riobamba Canton, Ecuador
2 Graduate School of Frontier Biosciences, Osaka University, Suita, Japan
3 Department of Medicine and Surgery, University of Pavia, Pavia, Italy
4 Centre for Cancer Biology, SA Pathology and the University of South of Australia, SA, 5000, Australia
5 Sandia National Laboratories, Albuquerque NM, USA


© 2021 Cevallos et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at College of Engineering, Universidad Nacional de Chimborazo, Riobamba Canton, Ecuador; E-mail: lptelloq@ieee.org


Abstract

Introduction:

Digital communication theories have been well-established and extensively used to model and analyze information transfer and exchange processes. Due to their robustness and thoroughness, they have been recently extended to the modeling and analyzing data flow, storage, and networking in biological systems.

Methods:

This article analyses gene expression from a digital communication system perspective. Specifically, network theories, such as addressing, error control, flow control, traffic control, and Shannon's theorem are used to design an end-to-end digital communication system representing gene expression. We provide a layered network model representing the transcription and translation of deoxyribonucleic acid (DNA) and the end-to-end transmission of proteins to a target organ. The layered network model takes advantage of digital communication systems' key features, such as efficiency and performance, to transmit biological information in gene expression systems.

Results:

Thus, we define the transmission of information through a bio-internetwork (LAN-WAN-LAN) composed of a transmitter network (nucleus of the cell, ribosomes and endoplasmic reticulum), a router (Golgi Apparatus), and a receiver network (target organ).

Conclusion:

Our proposal can be applied in critical scenarios such as the development of communication systems for medical purposes. For instance, in cancer treatment, the model and analysis presented in this article may help understand side effects due to the transmission of drug molecules to a target organ to achieve optimal treatments.

Keywords: Biological communication, Digital communication, DNA, Gene expression, Proteins, RNA.