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Related Experiment Video

Updated: Dec 27, 2025

Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy

Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy

Published on: April 27, 2021

Programming Escherichia coli to function as a digital display.

Jonghyeon Shin¹, Shuyi Zhang¹, Bryan S Der¹

¹Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.

Molecular Systems Biology

|March 7, 2020

Summary

This summary is machine-generated.

Scientists encoded a full electronic chip into the DNA of bacteria. This synthetic biology advance enables complex biological computation, displaying digits 0-9 using engineered Escherichia coli (E. coli) circuits.

Keywords:

Escherichia coli design automation genetic circuits logic gates synthetic biology

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Area of Science:

Synthetic Biology
Computational Biology
Bioengineering

Background:

Synthetic genetic circuits are limited by mathematical model accuracy.
Engineering complex biological computations requires advanced design tools.

Purpose of the Study:

To encode a complete electronic chip, a binary-coded digit (BCD) to 7-segment decoder, into Escherichia coli (E. coli) DNA.
To demonstrate the capability of design automation in creating complex synthetic genetic circuits.

Main Methods:

Utilized design automation to construct seven E. coli strains, each housing a genetic circuit with up to 12 repressors and two activators.
Engineered circuits to accept binary-encoded molecular inputs representing digits and output segment states as fluorescence.
Developed an advanced gate model accounting for dynamics, promoter interference, and RNA polymerase (RNAP) flux.

Main Results:

Successfully encoded a functional BCD to 7-segment decoder chip within E. coli DNA.
Demonstrated the visualization of digits 0-9 through engineered fluorescent outputs.
Circuits comprised up to 63 regulators and 76,000 base pairs of DNA.

Conclusions:

Design automation significantly enhances the complexity of synthetic genetic circuits beyond manual engineering capabilities.
This work exemplifies the potential of automated design in realizing advanced biological computation.
Advances in modeling, including dynamics and RNAP flux, are crucial for complex synthetic biology implementations.