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Synthetic Biology

Synthetic Biology

Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
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A Multilayer Microfluidic Platform for the Conduction of Prolonged Cell-Free Gene Expression

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Field-programmable biological circuits and configurable (bio)logic blocks for distributed biological computing.

Miha Moškon¹, Žiga Pušnik¹, Nikolaj Zimic¹

¹Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.

Computers in Biology and Medicine

|November 22, 2020

Summary

This study introduces programmable biological circuits configurable in vivo without genetic engineering, analogous to field-programmable gate arrays (FPGAs). This innovation simplifies programming synthetic biology systems.

Keywords:

Biological wires Configurable (bio)logic blocks Distributed computation Field-programmable biological circuits Memory Multiplexer

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Area of Science:

Synthetic Biology
Computational Biology
Bioengineering

Background:

Synthetic biology often requires complex genetic engineering for programmable computing structures.
Current methods for programming biological circuits are time-consuming and involve extensive trial-and-error.
This is analogous to the design challenges faced with application-specific integrated circuits (ASICs) in electronics.

Purpose of the Study:

To design and model programmable biological circuits that can be configured without additional genetic engineering.
To introduce a novel biological computing unit, the configurable (bio)logical block (CBLB).
To demonstrate in vivo configurability, akin to field-programmable gate arrays (FPGAs).

Main Methods:

Development of a computational model for the configurable (bio)logical block (CBLB).
Analysis of CBLB response using biologically feasible kinetic parameter values.
Simulation of CBLB behavior under various conditions, including stochastic simulations.

Main Results:

The proposed CBLB design allows for in vivo configuration via programming inputs that alter protein degradation rates.
The computational model demonstrates correct behavior across a wide range of kinetic parameters and population ratios.
The CBLB design maintains its programmed response even in stochastic simulations.

Conclusions:

Programmable biological circuits can be designed for in vivo configuration, reducing the need for genetic engineering.
The configurable (bio)logical block (CBLB) offers a flexible and robust platform for synthetic biology applications.
This approach provides an alternative to traditional genetic engineering methods, similar to FPGAs in electronics.