DNA 'Machine' Targets Antibodies, Eliminates Treatment Delays and High Costs

Research may improve the diagnosis of infectious and autoimmune diseases, including rheumatoid arthritis and HIV.

Novel research may resolve the issue of slow and expensive detection of antibodies that can help with the diagnosis of infectious and autoimmune diseases, such as rheumatoid arthritis and HIV.

Researchers from around the world have collaborated to create a nanometer-scale DNA “machine” that is able to recognize a specific target antibody. This new approach will allow the development of rapid, low-cost antibody detection at the point-of-care, eliminating treatment initiation delays and health care costs associated with current techniques.

The antibody binds to the DNA machine, which causes a structural change that generates a light signal. There is no need for the sensor to be chemically activated, as it works quickly to enable targeted antibodies to be easily detected, even in complex clinical samples such as blood serum.

“One of the advantages of our approach is that it is highly versatile,” said study senior co-author Professor Francesco Ricci, of the University of Rome, Tor Vergata. “This DNA nanomachine can be in fact custom-modified so that it can detect a huge range of antibodies, this makes our platform adaptable for many different diseases.”

Professor Vallée-Bélisle of the University of Montreal, the other senior co-author of the paper, noted the nanomachine provides opportunities for patient care that traditional methods do not.

“Our modular platform provides significant advantages over existing methods for the detection of antibodies,” Vallée-Bélisle said. “It is rapid, does not require reagent chemicals, and may prove to be useful in a range of different applications such as point-of-care diagnostics and bioimaging.”

The other great aspect about the device is its low cost compared with traditional methods.

“The materials needed for one assay cost about 15 cents, making our approach very competitive in comparison with other quantitative approaches,” said Professor Kevin Plaxco of the University of California, Santa Barbara.

The device could also be further developed for mobile use to improve accessibility.

“We are excited by these preliminary results, but we are looking forward to improve our sensing platform even more,” said Simona Ranallo, PhD student in the group of Professor Ricci at the University of Rome and first-author of the paper. “For example, we could adapt our platform so that the signal of the nanoswitch may be read using a mobile phone. This will make our approach really available to anyone. We are working on this idea and we would like to start involving diagnostic companies.”