Real-Time Monitoring of Insulin Using a Graphene ... - ACS Publications

Aug 3, 2017 - James Hone,. † and Qiao Lin*,†. †. Department of Mechanical Engineering, Columbia University, New York, New York 10027, United Sta...
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Real-Time Monitoring of Insulin Using a Graphene Field-Effect Transistor Aptameric Nanosensor Zhuang Hao,†,‡ Yibo Zhu,† Xuejun Wang,† Pavana G. Rotti,§,∥ Christopher DiMarco,† Scott R. Tyler,§ Xuezeng Zhao,‡ John F. Engelhardt,§,∥ James Hone,† and Qiao Lin*,† †

Department of Mechanical Engineering, Columbia University, New York, New York 10027, United States Department of Mechanical Engineering, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China § Department of Anatomy and Cell Biology and ∥Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa 52242, United States Downloaded via UNIV OF TOLEDO on June 18, 2018 at 14:46:01 (UTC). See https://pubs.acs.org/sharingguidelines for options on how to legitimately share published articles.



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ABSTRACT: This paper presents an approach to the realtime, label-free, specific, and sensitive monitoring of insulin using a graphene aptameric nanosensor. The nanosensor is configured as a field-effect transistor, whose graphene-based conducting channel is functionalized with a guanine-rich IGA3 aptamer. The negatively charged aptamer folds into a compact and stable antiparallel or parallel G-quadruplex conformation upon binding with insulin, resulting in a change in the carrier density, and hence the electrical conductance, of the graphene. The change in the electrical conductance is then measured to enable the real-time monitoring of insulin levels. Testing has shown that the nanosensor offers an estimated limit of detection down to 35 pM and is functional in Krebs−Ringer bicarbonate buffer, a standard pancreatic islet perfusion medium. These results demonstrate the potential utility of this approach in label-free monitoring of insulin and in timely prediction of accurate insulin dosage in clinical diagnostics. KEYWORDS: affinity sensing, aptamer, G-quadruplex, graphene field-effect transistor (GFET), insulin at physiologically relevant levels (lower than 270 pM)3 without pretreatment of samples. In this paper, we developed an aptameric nanosensor for the real-time monitoring of insulin levels. The nanosensor is based on a graphene field-effect transistor (GFET) and exploits the affinity binding between insulin and its specific aptameric receptor IGA3 (Figure 1). The short time required for monolayer aptamer−insulin binding and the rapid response of graphene to external stimuli allow the nanosensor to respond to changes in the insulin level within 260 s. Furthermore, physiologically relevant levels of insulin, as low as 35 pM, can be detected. This is attributable to the high sensitivity of the GFET to the changes in the charge distribution on and in the immediate vicinity of the graphene surface, which is offered by the high mobility and large surface-to-volume ratio of graphene. Moreover, as aptamers can discriminate between insulin and other closely related analogues on the basis of subtle structural differences, the aptameric nanosensor showed significant improvements in the specificity to insulin over devices based on the antigen−antibody binding.10 The aptameric nanosensor

1. INTRODUCTION Control of glucose levels in blood is critical for patients suffering from both type 1 and 2 diabetes.1 Most of the therapeutic options for glucose control require the administration of insulin, an endocrine peptide hormone promoting absorption of blood sugar. Although insulin can be injected or inhaled by patients, it remains challenging to choose a correct dose schedule, as the effective durations and strengths of different types of insulins vary significantly.2,3 Blood sugar levels are usually measured to assist in determining the dosage of insulin injection. This lacks accuracy because there is a lag from insulin introduction to effective glucose regulation.4 Therefore, the correct and timely use of insulin is strongly dependent on accurate predictions of insulin levels in the human body. Conventional antigen−antibody-based methods to quantify insulin concentrations, such as the radioimmunoassay and enzyme-linked immunosorbent assay, are time-consuming and not amenable to real-time monitoring.5 Electrochemical or optical sensors have been developed to reduce the required detection time (