First-Of-Its-Kind Technology Maps Out Diverse Protein Interactions in Cells Using DNA Barcodes

Protein interactions drive critical functions in health and disease, and decoding these interactions can enhance predictions of cell behavior and offer significant clinical applications, from improved diagnostics to more effective therapies. However, current methods for studying protein interactions have limitations, such as producing false results and failing to capture the full range of protein interactions. For example, the widely used yeast-two hybrid assays focus on pairwise binary interactions and require genetic manipulation, making them unsuitable for clinical samples. Similarly, mass spectrometry-based proteomics often misses weak interactions due to extensive sample processing and evaluates protein interactions in a binary fashion. These existing methods fall short in detecting complex, higher-order interactions where multiple proteins form large functional assemblies—crucial in aggressive cancers.

Now, a team of researchers from the NUS Institute for Health Innovation & Technology (iHealthtech, Singapore) has developed a novel technology called TETRIS to map out diverse protein interactions in cells using DNA barcodes. This innovative approach allows the identification and quantification of multiple interacting partners in large protein assemblies. By capturing the complex hierarchy of protein interactions within tumor cells, TETRIS uncovers the molecular mechanisms driving disease progression. This leads to more accurate diagnostics, enabling the sub-typing of cancers and identifying aggressive forms of the disease within hours, a capability previously unavailable. Additionally, TETRIS offers insights for personalized treatment strategies by pinpointing specific proteins and their interactions that drive cancer growth, opening the door to targeted therapies that can improve patient outcomes.

TETRIS leverages DNA nanotechnology to map protein interactions directly in patient samples. It uses hybrid molecular structures as smart encoders, each carrying a target-recognizing antibody and a templated DNA barcode. These encoders bind to interacting proteins and fuse their barcodes with neighboring units, capturing both the molecular identity and spatial relationships of the proteins. Unlike traditional methods, TETRIS can measure both pairwise and higher-order protein interactions, providing a comprehensive view of the complex protein interaction network, or interactome. A key feature of TETRIS is its ability to encode and decode protein interactions directly in clinical samples. The technology has been successfully tested on human breast cancer tissue biopsies, where it accurately diagnosed cancer subtypes and revealed higher-order protein interactions linked to cancer aggressiveness. These findings were published in the scientific journal Nature Biomedical Engineering.

TETRIS offers a more detailed and accurate understanding of the molecular mechanisms behind diseases, greatly benefiting cancer diagnostics and treatment. By detecting changes in higher-order protein interactions—often markers of aggressive cancers—this technology enables more personalized clinical decisions. Designed for scalability and adaptability, TETRIS can process large numbers of samples and deliver rapid results using existing lab infrastructure, making it suitable for integration into routine clinical workflows. For instance, in a doctor’s office, samples obtained through fine-needle aspiration—a minimally invasive biopsy—can be quickly analyzed to guide treatment decisions. The researchers plan to expand TETRIS to other types of cancers and neurological diseases, potentially leading to new diagnostic tools and treatments for a range of illnesses.

“Think of proteins as delegates at a scientific conference. Each delegate spots a name tag with a unique barcode,” said Associate Professor Brian Lim, who led the development of algorithms used to process the data collected by TETRIS. “When they interact, or ‘shake hands’, TETRIS captures these interactions by linking their barcodes together. This creates a chain of interactions that we can subsequently read and decode via algorithms. Just like seeing who is chatting to whom at the conference, TETRIS enables us to see how proteins interact within cells, providing us with a lens through which we can understand and diagnose diseases more effectively.”

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