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Ultrasensitive, Multiplexed Buoyant Sensor for Monitoring Cytokines in Biofluids.

Heng Guo¹, Rohit Gupta², Dhavan Sharma¹

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

|November 3, 2023

Summary

We developed a novel buoyant biosensor for real-time, in situ monitoring of protein biomarkers in complex biological samples. This technology achieves attomolar sensitivity for multiplexed cytokine detection without perturbing live cells.

Keywords:

cytokines digital immune biomarkers multiplexed biosensors ultrasensitive protein detection

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Area of Science:

Biomedical Engineering
Analytical Chemistry
Molecular Diagnostics

Background:

Accurate quantification of low-abundance protein biomarkers in biofluids is crucial for research and diagnostics.
In situ sampling of these biomarkers without disrupting biological systems presents a significant challenge.

Purpose of the Study:

To develop a novel buoyant biosensor for ultrasensitive, multiplexed, and in situ quantification of protein biomarkers.
To enable real-time monitoring of cytokine concentrations in cell cultures without cellular perturbation.

Main Methods:

A buoyant biosensor utilizing fluorescent nanolabels was engineered for protein analyte detection.
Digital implementation, involving counting individual nanolabels, was employed to enhance sensitivity.
The biosensor was applied to monitor time-varying concentrations of cytokines (IL-6, TNF-α) in macrophage culture media.

Main Results:

The buoyant biosensor achieved attomolar sensitivity and enabled multiplexed quantification of cytokines.
Real-time monitoring of cytokine dynamics in live cell cultures was successfully demonstrated.
The digital approach significantly improved the low detection limit of the biosensor.

Conclusions:

The developed buoyant biosensor offers a powerful tool for in situ analysis of protein biomarkers in various biofluids and tissues.
Its high sensitivity, multiplexing capability, and non-perturbing nature facilitate a deeper understanding of biological processes.
This technology holds promise for advancing disease diagnosis and treatment strategies.