Novel quantum dot-based technique sees 100 different molecules in a single cell

Better diagnosis and treatment of cancer could hinge on the ability to rapidly map out networks of dozens of molecules in individual tumor cells
July 16, 2013

New research from the University of Washington offers a more comprehensive way of analyzing a single cell’s unique behavior and could reveal patterns that indicate why a cell will or will not become malignant.

Xiaohu Gua and graduate student Pavel Zrazhevskiy have used an array of distinctly colored quantum dots to illuminate 100 biomarkers, a ten-fold increase from the current research standard, to help analyze individual cells from cultures or tissue biopsies.

Other approaches have measured multiple biomarkers in a single cell, but what makes this technique promising is that it reuses the same precious tissue sample in a cyclical process to measure 100 biomolecules in groups of ten.

How to measure 100 biomolecules

The process starts by pairing a commercially available antibody (left) (known to bind with specific biomolecules) with a quantum dot (center) of distinct size and therefore color.

Once formed, different probes are pooled in a single cocktail (left) and then incubated with cells for parallel multiplexed staining (right)

 

The investigators then inject a solution of ten of these antibody-quantum dot pairs onto a tissue sample and use a fluorescence microscope to quantify which of the constructs bind at the single cell level.

 

Once the measurement is complete, they then wash the tissue sample with a fluid of detergents at low pH to get rid of the antibodies and quantum dots without degrading the tissue sample, and repeat the staining step for different target molecules

The two investigators have shown that they can repeat this process at least ten times without producing any signs of tissue damage.

The researchers note that because this methodology uses commercially available enzymes and standard fluorescence microscopes, it is relatively low cost. They also plan to automate the procedure using microfluidics and automated image processing technologies.

This work, which was supported in part by the National Cancer Institute, is detailed in an open access paper in Nature Communications.

Credit for images: Pavel Zrazhevskiy et al./Nature Communications