This is Kevin Plaxco (left) and Alexis Vallée-Bélisle. Credit: Rod Rolle |
Over
their 3.8 billion years of evolution, living organisms have developed
countless strategies for monitoring their surroundings. Chemists at UC
Santa Barbara and University of Rome Tor Vergata have adapted some of
these strategies to improve the performance of DNA detectors. Their
findings may aid efforts to build better medical diagnostics, such as
improved HIV or cancer tests.
Their research is described in an article published this week in the Journal of the American Chemical Society.
Nature
often serves as a source of inspiration for the development of new
technologies. In the field of medical diagnostics, for example,
scientists have long taken advantage of the high affinity and
specificity of biomolecules such as antibodies and DNA to detect
molecular markers in the blood. These molecular markers allow them to
monitor health status and to guide treatments for diseases, including
HIV, cancer, and diabetes.
Kevin
W. Plaxco, a professor of chemistry at UCSB, whose group carried out
the research, notes that despite their great attributes, a main
limitation of such biosensors is their precision, which is confined to a
fixed, well-defined “dynamic range” of target concentrations.
Specifically, the useful dynamic range of typical biomolecule binding
events spans an 81-fold range of target concentrations
“This
fixed dynamic range complicates—or even precludes—the use of
biosensors in many applications,” said Plaxco. “To monitor HIV
progression and provide the appropriate medication, for example,
physicians need to measure the levels of viruses over five orders of
magnitude. Likewise, the two orders-of-magnitude range displayed by most
biosensors is too broad to precisely monitor the concentrations of the
highly toxic drugs used to treat many cancers. Our goal was, therefore,
to create sensors with extended (for applications needing a broad
dynamic range) or narrowed (for applications needing high measurement
precision) dynamic ranges at will.”
By mimicking natural sensors, Vallée-Bélisle, Ricci and Plaxco have created biosensors that are highly precise (ideal for monitoring the concentration of highly toxic drugs used to treat many cancers) or that can detect a very large change in target concentrations (ideal to monitor HIV virus progression). The researchers believe that these strategies can be applied to a wide range of biosensors, which may significantly impact efforts to build better point-of-care biosensors for the detection of disease biomarkers. Credit: UCSB |
The
key breakthrough underlying their new approach came from the simple
observation of nature. “All living organisms monitor their environments
in an optimized way by using sensing molecules that respond to either
wide or narrow change in target concentrations,” said Alexis
Vallée-Bélisle, a postdoctoral fellow and the first author of the study.
“Nature does so by combining in a very elegant way multiple receptors,
each displaying a different affinity for their common target”.
Inspired
by the optimized behaviors of these natural sensors, the UCSB research
group teamed up with Francesco Ricci, professor at the University of
Rome Tor Vergata to do their own mixing and matching of biomolecules to
manipulate biosensors’ dynamic ranges. To validate their approach, they
used a widely employed DNA-based biosensor used for detecting mutations
in DNA called a “molecular beacon.”
By
combining sets of molecular beacons all binding the same target
molecule but with differing affinities, the international team was able
to create sensors with rationally “tuned” dynamic ranges. In one case,
they developed a sensor that monitors DNA concentrations over a six
orders of magnitude range. In another example, they developed an
ultrasensitive sensor that precisely detects small changes in target
concentration over only a five-fold dynamic range. Finally, they also
built sensors characterized by complex, “custom-made” dynamic ranges in
which the sensor is insensitive within a window of desired
concentrations (e.g., the clinically “normal” concentration range of a
drug) and very sensitive above or below this “appropriate” concentration
range. The researchers believe that these strategies can be in
principle applied to a wide range of biosensors, which may significantly
impact efforts to build better point-of-care biosensors for the
detection of disease biomarkers.
This
work was funded by the National Institute of Health, the Fond Québécois
de la Recherche sur la Nature et les Technologies, the Italian Ministry
of University, and Research (MIUR) project “Futuro in