PEP-on-DEP: A competitive peptide-based disposable electrochemical aptasensor for renin diagnostics

2016 
Abstract Antibody-based immunosensors are relatively less accessible to a wide variety of unreachable targets, such as low-molecular-weight biomarkers that represent a rich untapped source of disease-specific diagnostic information. Here, we present a peptide aptamer-based electrochemical sensor technology called ‘PEP-on-DEP’ to detect less accessible target molecules, such as renin, and to improve the quality of life. Peptide-based aptamers represent a relatively smart class of affinity binders and show great promise in biosensor development. Renin is involved in the regulation of arterial blood pressure and is an emerging biomarker protein for predicting cardiovascular risk and prognosis. To our knowledge, no studies have described aptamer molecules that can be used as new potent probes for renin. Here, we describe a portable electrochemical biosensor platform based on the newly identified peptide aptamer molecules for renin. We constructed a randomized octapeptide library pool with diversified sequences and selected renin specific peptide aptamers using cDNA display technology. We identified a few peptide aptamer sequences with a K D in the µM binding affinity range for renin. Next, we grafted the selected peptide aptamers onto gold nanoparticles and detected renin in a one-step competitive assay using our originally developed DEP (Disposable Electrochemical Printed) chip and a USB powered portable potentiostat system. We successfully detected renin in as little as 300 ng mL −1 using the PEP-on-DEP method. Thus, the generation and characterization of novel probes for unreachable target molecules by merging a newly identified peptide aptamer with electrochemical transduction allowed for the development of a more practical biosensor that, in principle, can be adapted to develop a portable, low-cost and mass-producible biosensor for point-of-care applications.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    25
    References
    13
    Citations
    NaN
    KQI
    []