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Super-resolution Fluorescence Microscopy

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Updated: Jun 24, 2026

Genetic Barcoding with Fluorescent Proteins for Multiplexed Applications

Genetic Barcoding with Fluorescent Proteins for Multiplexed Applications

Published on: April 14, 2015

Binary spatial-spectral encoding and decoding for ultra-multiplexed digital PCR: Breaking the fluorescence channel

Jinrong Shen¹, Jingxing Fan¹, Gangwei Xu²

¹State Key Laboratory of Integrated Chips and Systems, College of Integrated Circuits and Micro-Nano Electronics, Fudan University, Shanghai, 200433, China.

Biosensors & Bioelectronics

|June 22, 2026

Summary

This summary is machine-generated.

We developed a novel binary spatial-spectral encoding method to significantly enhance digital PCR multiplexing capacity. This approach allows for the simultaneous detection of multiple targets, overcoming current limitations in fluorescence channels.

Keywords:

Binary spatial-spectral encoding Decoding robustness Partition identity preservation Partition-resolved decoding Ultra-multiplexed digital PCR

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Published on: March 13, 2018

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Last Updated: Jun 24, 2026

Genetic Barcoding with Fluorescent Proteins for Multiplexed Applications

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Multiplexed Isothermal Amplification Based Diagnostic Platform to Detect Zika, Chikungunya, and Dengue 1

Multiplexed Isothermal Amplification Based Diagnostic Platform to Detect Zika, Chikungunya, and Dengue 1

Published on: March 13, 2018

Area of Science:

Molecular Biology
Biotechnology
Analytical Chemistry

Background:

Digital PCR (dPCR) offers high sensitivity and precision for nucleic acid quantification.
Current dPCR methods (ddPCR, cdPCR) are limited in multiplexing by fluorescence channels (N).
Existing multiplexing strategies face challenges with signal variation and spectral crosstalk.

Purpose of the Study:

To introduce a binary spatial-spectral encoding and decoding framework for ultra-multiplexed dPCR.
To overcome the limitations of fluorescence channels in multiplexing capacity.
To demonstrate a scalable strategy for advanced dPCR applications.

Main Methods:

Implemented a binary spatial-spectral encoding and decoding framework on chip-based digital PCR (cdPCR).
Utilized fixed-position microchamber arrays for reliable cross-channel correspondence.
Constructed target identities from binary ON/OFF fluorescence states across channels.

Main Results:

Achieved simultaneous detection of nine respiratory pathogens using only four fluorescence channels.
Demonstrated accurate quantification across four orders of magnitude (R² = 0.9998).
Expanded theoretical detection capacity from N to 2^N-1.

Conclusions:

Binary spatial-spectral decoding is a scalable strategy for multiplex dPCR.
This framework significantly enhances multiplexing capacity beyond current limitations.
Potential for extension to droplet-based digital PCR (ddPCR) with reliable tracking.