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Updated: May 5, 2026

High-throughput Protein Expression Generator Using a Microfluidic Platform

High-throughput Protein Expression Generator Using a Microfluidic Platform

Published on: August 23, 2012

FairyTALE: a high-throughput TAL effector synthesis platform.

Jing Liang¹, Ran Chao, Zhanar Abil

¹Department of Chemical and Biomolecular Engineering, ‡Institute for Genomic Biology, §Department of Biochemistry, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States of America.

ACS Synthetic Biology

|November 19, 2013

Summary

fairyTALE is a new platform for high-throughput synthesis of transcription activator-like effectors (TALEs). This automated system produces hundreds of functional TALEs daily, enabling advanced genome editing and gene regulation research.

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Area of Science:

Molecular Biology
Synthetic Biology
Genomics

Background:

Recombinant transcription activator-like effectors (TALEs) are modular proteins used for targeted DNA manipulation.
Existing TALE synthesis methods can be time-consuming and costly, limiting their widespread application.

Purpose of the Study:

To develop a high-throughput, cost-effective platform for synthesizing various TALE-based proteins.
To demonstrate the efficiency and functionality of the developed TALE synthesis platform.

Main Methods:

Introduction of fairyTALE, a liquid-phase, high-throughput TALE synthesis platform.
Utilized automated robotic liquid handling for TALE production.
Synthesized and tested 90 TALEs targeting 27 bp DNA sequences.

Main Results:

The fairyTALE platform produces TALE-nucleases, activators, and repressors recognizing 14-31 bp DNA sequences.
Achieved over 98% assembly efficiency with a material cost of $5 per TALE.
96% of synthesized TALEs were functional, with non-functional constructs showing correct assembly.

Conclusions:

The fairyTALE platform enables rapid, efficient, and cost-effective production of functional TALEs.
This high-throughput synthesis accelerates applications in genome editing and gene regulation.
The platform's flexibility and automation significantly advance TALE-based research.