We developed an interdigitated microelectrode (IME) sensor system for blood-based Alzheimer’s disease (AD) diagnosis based on impedimetric detection of amyloid-β (Aβ) protein, which is a representative candidate biomarker for AD. The IME sensing device was fabricated using a surface micromachining process. For highly sensitive detection of several tens to hundreds of picogram/mL of Aβ in blood, medium change from plasma to PBS buffer was utilized with signal cancellation and amplification processing (SCAP) system. The system demonstrated approximately 100-folds higher sensitivity according to the concentrations. A robust antibody-immobilization process was used for stability during medium change. Selectivity of the reaction due to the affinity of Aβ to the antibody and the sensitivity according to the concentration of Aβ were also demonstrated. Considering these basic characteristics of the IME sensor system, the medium change was optimized in relation to the absolute value of impedance change and differentiated impedance changes for real plasma based Aβ detection. Finally, the detection of Aβ levels in transgenic and wild-type mouse plasma samples was accomplished with the designed sensor system and the medium-changing method. The results confirmed the potential of this system to discriminate between patients and healthy controls, which would enable blood-based AD diagnosis.
Brain-derived neurotrophic factor (BDNF) plays a critical role in cognitive processes including learning and memory. However, it has been difficult to detect BDNF in the brains of behaving animals because of its extremely low concentration, i.e., at the sub-nanogram/mL level. Here, we developed an interdigitated microelectrode (IME) biosensor coated with an anti-BDNF an anti-BDNF antibody in a polydimethylsiloxane (PDMS)-based microfluidic channel chip. This sensor could detect BDNF from microliter volumes of liquid samples even at femtogram/mL concentrations with high selectivity over other growth factors. Using this biosensor, we examined whether BDNF is detectable from periodical collection of cerebrospinal fluid microdialysate, sampled every 10 min from the hippocampus of mice during the context-dependent fear-conditioning test. We found that the IME biosensor could detect a significant increase in BDNF levels after the memory task. This increase in BDNF levels was prevented by gene silencing of BDNF, indicating that the IME biosensor reliably detected BDNF in vivo. We propose that the IME biosensor provides a general-purpose probe for ultrasensitive detection of biomolecules with low abundance in the brains of behaving animals.
Sensitivity and limit of detection (LOD) enhancement are essential criteria for the development of ultrasensitive molecular sensors. Although various sensor types have been investigated to enhance sensitivity and LOD, analyte detection and its quantification are still challenging, particularly for protein-protein interactions with low association constants. To solve this problem, here, we used ion concentration polarization (ICP)-based preconcentration to increase the local concentration of analytes in a microfluidic platform for LOD improvement. This was the first demonstration of a microfluidic device with an integrated ICP preconcentrator and interdigitated microelectrode (IME) sensor to detect small changes in surface binding between antigens and antibodies. We detected the amyloid beta (Aβ) protein, an Alzheimer’s disease marker, with low binding affinity to its antibodies by adopting ICP preconcentration phenomena. We demonstrated that a combination of ICP preconcentrator and IME sensor increased the LOD by 13.8-fold to femtomolar level (8.15 fM), which corresponds to a significant advance for clinical applications.
Graphene has been studied in various fields such as bio-sensing, electrical applications and so on, due to its great electrical1 and mechanical properties.2 Even though the graphene has great properties, the graphene based practical devices has not been realized in daily day. Our group tried to find the reason in the absence of batch process fabrication method of graphene based device. Many method of graphene based device fabrications have low yields and cost-consuming. The synthesis of graphene was also time and cost consuming properties. After achievement of graphene oxide (GO) synthesis in liquid phase by Hummer’s method, the possibility of graphene-usage in low cost was increased. The cost-effective graphene oxide was reduced to utilize the same novel properties of graphene. The mass-productive patterning methods of GO or reduced GO (rGO) is also essential to realize graphene-based devices. The biosensing devices-consuming has been increasing as follows the demand increasing for disposable sensors applications for rapid detection in bio-research as a point of care. For the mass-productive devices, laser writing after forming the GO layer by spin coating3 and spray coating of rGO with shadow mask4 were introduced. However, the method also need huge amount of apparatus for the patterning such as laser and position controlling system. And the controlled thickness of GO is quite thick to have micron scale of thickness which is not sufficient in biological applications. Here, we introduce a cost-effective rGO patterning and biosensor fabrication method based on conventional micro-electro-mechanical systems (MEMS) technique for Alzheimer’s disease diagnosis. The GO layer was formed with meniscus dragging method to accomplish the freely controllable thickness from nanoscale to microscale on silicon dioxide wafer. After formation of GO layer, the GO layer was reduced with chemical reduction method. Photolithography and dry etching in oxygen atmosphere were utilized to form the patterns of the rGO layer. Various rGO patterns with dimensions from sevral ~µm up to several hundred µm achieved through the optimization of patterning with dry etching. The patterns were used as a sensing zone which contains immobilized antibody for detection of amyloid beta (Aβ) peptide. The Aβ is the most remarkable biomarker of Alzheimer's disease. The gold electrodes were also accomplished on the rGO patterns with photolithography and lift-off process. Generally, the graphene based fabrication was done at the forming graphene layer with MEMS technique. However, we could form the additional layer after the forming rGO layer without any deformation of rGO layer. All process of fabrication was proceeded in 4-inch wafer. For the high throughput of sensing, the rGO patterns was formed as an array. The array of sensor might increase the accuracy of biomolecule detection. Finally, the high-uniformly formed rGO-based biosensor arrays on 4-inch wafers was prepared to detect the Aβ as a diagnosis of Alzheimer's disease. The resistance changes or rGO layer according to the reaction of Aβ peptide was measured. The rGO biosensor has reproducible response ranging in 100fg mL-1 to 100pg mL-1 with most of devices from same wafer with high sensitivity. The sensor also detected the Aβ peptide level from mouse and human plasma. The array type of sensing process lead the high throughput of rGO based Aβ detection as a diagnosis of Alzheimer's disease.
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