Skip to main content
eScholarship
Open Access Publications from the University of California

UCLA

UCLA Previously Published Works bannerUCLA

Phenylalanine Monitoring via Aptamer-Field-Effect Transistor Sensors

Abstract

Determination of the amino acid phenylalanine is important for lifelong disease management in patients with phenylketonuria, a genetic disorder in which phenylalanine accumulates and persists at levels that alter brain development and cause permanent neurological damage and cognitive dysfunction. Recent approaches for treating phenylketonuria focus on injectable medications that efficiently break down phenylalanine but sometimes result in detrimentally low phenylalanine levels. We have identified new DNA aptamers for phenylalanine in two formats, initially as fluorescent sensors and then, incorporated with field-effect transistors (FETs). Aptamer-FET sensors detected phenylalanine over a wide range of concentrations (fM to mM). para-Chlorophenylalanine, which inhibits the enzyme that converts phenylalanine to tyrosine, was used to induce hyperphenylalaninemia during brain development in mice. Aptamer-FET sensors were specific for phenylalanine versus para-chlorophenylalanine and differentiated changes in mouse serum phenylalanine at levels expected in patients. Aptamer-FETs can be used to investigate models of hyperphenylalanemia in the presence of structurally related enzyme inhibitors, as well as naturally occurring amino acids. Nucleic acid-based receptors that discriminate phenylalanine analogs, some that differ by a single substituent, indicate a refined ability to identify aptamers with binding pockets tailored for high affinity and specificity. Aptamers of this type integrated into FETs enable rapid, electronic, label-free phenylalanine sensing.

Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.

Main Content
For improved accessibility of PDF content, download the file to your device.
Current View