|Light-generating DNA "nanomachine" illustrated in action, |
bound to an antibody. (Credit: Marco Tripodi)
New research may revolutionize the slow, cumbersome and expensive process of detecting the antibodies that can help with the diagnosis of infectious and auto-immune diseases such as rheumatoid arthritis and HIV.
An international team of researchers have designed and synthetized a nanometer-scale DNA "machine" whose customized modifications enable it to recognize a specific target antibody. Their new approach, which they described this month in Angewandte Chemie, promises to support the development of rapid, low-cost antibody detection at the point-of-care, eliminating the treatment initiation delays and increasing healthcare costs associated with current techniques.
The binding of the antibody to the DNA machine causes a structural change (or switch), which generates a light signal. The sensor does not need to be chemically activated and is rapid - acting within five minutes - enabling the targeted antibodies to be easily detected, even in complex clinical samples such as blood serum.
One of the advantages of this approach is its versatility. The DNA nanomachine can be custom-modified so that it can detect a huge range of antibodies, making the platform adaptable for many different diseases.
"Our modular platform provides significant advantages over existing methods for the detection of antibodies," the researchers 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 platform is also low-cost. The materials needed for one assay cost about 15 cents, making the approach very competitive in comparison with other quantitative approaches.
Although excited about the preliminary results, the researchers are still looking to improve the platform even more. They are even working on adapting the platform to the use of mobile phones, making it available to anyone.
Based on material originally posted by University of Montreal.