Measuring concentrations of medically relevant metabolites in the blood may have just gotten easier - requiring mere minutes and just microliters of blood - thanks to an approach involving a bioengineered protein that lights up, and a digital camera. The paper-based method can do its work in just about 15 minutes, say the authors, compared to existing methods for metabolite detection, which require more time-consuming lab-based spectrometry.
Many diseases and injuries result in characteristic changes in the metabolite blood concentration. Ischemic strokes, for example, are generally followed by increased levels of glutamate. However, measurements of metabolites require clinical lab-based analyses and cannot be reliably monitored at the point-of-care (POC), slowing the diagnosis and management of underlying medical conditions.
To address this problem, researchers designed a semisynthetic, bioluminescent sensor protein for use in paper-based metabolic assays. The protein, which changes color in the presence of a compound called NADPH, the product of oxidized metabolites, can be quantified using a digital camera; the brighter the sensor protein shines, as detected by a digital camera, the higher the concentration of a given metabolite.
The method allowed the authors to measure the levels of Phenylalanine in the blood of phenylketonuria patients at the POC within minutes using only .5 microliters of blood. To validate their POC assay, researchers analyzed whole blood samples spiked with phenylalanine and compared it to parallel measurements made using lab-based methods. The results of the POC assay closely matched those run in a standard clinical lab setting, demonstrating the accuracy of the method.
The authors suggest that the approach is suitable for a variety of metabolites, including carbohydrates, alcohols, lipids, amino acids and cholesterols. What's more, the simplicity of the procedure may one day allow for patient self-testing.
http://science.sciencemag.org/content/361/6407/1122
Quick, paper-based method for detecting medically relevant metabolites
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