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Updated: May 27, 2026

An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions
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An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions

Published on: March 22, 2018

Closed-Loop Optogenetic Control in a Microplate Reader.

Hari R Namboothiri1, Krishna Pochana2, Bhavya Jaiswal1

  • 1Department of Chemical Engineering, Texas A&M University, College Station, Texas 77843, United States.

ACS Synthetic Biology
|May 25, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces LEMOS, a low-cost optogenetic control platform for cell-silicon systems. It enables rapid prototyping and accurate feedback control in batch cultures, overcoming limitations of previous methods.

Keywords:
LEMOScybergeneticsgrowth-aware gene expression dynamicsoptogenetic feedback control

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Area of Science:

  • Synthetic Biology
  • Biotechnology
  • Bioengineering

Background:

  • Prototyping cell-silicon systems via optogenetics is challenging due to limitations in current tools.
  • Existing optogenetic controllers require constant growth conditions (chemostats/microfluidics) and lack growth-aware models for batch cultures.

Purpose of the Study:

  • To present a novel, low-cost platform (LEMOS) for rapid prototyping and closed-loop optogenetic feedback control in cell-silicon systems.
  • To develop and validate a growth-aware multiscale model for controller design in batch cultures.

Main Methods:

  • Development of LEMOS: a low-cost LED-embedded microplate compatible with commercial microplate readers.
  • Integration of a growth-aware multiscale model for gene expression controller tuning.
  • Demonstration of closed-loop set point tracking of gene expression in batch cultures.

Main Results:

  • LEMOS enables rapid design-build-test-learn cycles for optogenetic systems.
  • The platform successfully demonstrates real-time, closed-loop feedback control of gene expression in batch cultures.
  • Growth dynamics were shown to complicate controller selection and tuning, highlighting the need for growth-aware models.

Conclusions:

  • LEMOS significantly reduces setup overhead and speeds up iteration for developing cell-silicon systems.
  • This platform facilitates accurate, real-time optogenetic feedback control, even in dynamic batch culture environments.
  • The study provides a foundation for advanced controller design that accounts for cellular growth.