(Invited) Graphene-Based Micro Biosensors
Authors: Ueno Yuko 
Published: July 2021

On the surface of graphene, energy transfer occurs when molecules are located close to the surface. The energy transfer yield depends on the degree of molecular interaction between the adsorbed molecules and the graphene surface. For example, when a fluorescent molecule such as a dye is located very close to the graphene surface, the dye does not exhibit fluorescence because of the efficient fluorescence resonance energy transfer (FRET). The degree of energy transfer varies when the molecules on the surface changes their molecular states and structures. This allows us to visualize biological/chemical reactions by converting those invisible molecular interactions into the measurable physical quantities such as light and electricity. This makes graphene a promising material for a novel biosensor.

We have created a unique type of biosensor, which works on a graphene surface by modifying it with a specific DNA called an aptamer, for the detection of biologically important proteins such as cancer markers. One end of the aptamer is labeled with a fluorescent dye and the other end is connected to a pyrene linker molecule, which shows a strong affinity to the graphene. Thus, the aptamer is firmly fixed to the graphene surface. The graphene aptasensor detection mechanism is as follows. In the initial stage, the dye-conjugated aptamer is adsorbed on the graphene surface via physical adsorption (π-π interactions), and thus the dye is located close to the graphene surface. Here, the fluorescence of the dye is well quenched by graphene via FRET and is barely observable (Fig. 1(a)). If the target of the aptamer is present in the system, the aptamer forms a complex with the target and leaves the graphene surface. At the same time, the dye molecule also leaves the graphene surface and the dye recovers its fluorescence (Fig. 1(b)). We can detect the target molecule by observing the fluorescence [1]. The system allows us to perform molecular detection on a solid surface, which is a powerful tool to realize a two-dimensional (2D) on-chip sensor. By using the on-chip sensor, detection of the target protein is possible simply by adding a sample smaller than 1 μL to a sensor chip and is completed in about a minute. The system also allows us to perform real-time molecular detection, the simultaneous detection of multiple target molecules on a single chip [2], and the molecular design of a probe for enhancing the sensitivity by using single-stranded DNA spacer (Fig. 2)[3].

We then extend the biosensing platform from a 2D plane to a hollow three-dimensional (3D) space by building the protein detection system on the inner surfaces of flexible layered polymer films. The different strain gradients of the polymeric bilayer are used as the driving force behind the 3D transformation [4]. Detection of human serum albumin (HAS) in a 3D aptasensor has been successfully demonstrated (Fig. 1(e-f)). Since the formation of the micro-roll avoids any cytotoxic processes, they can be used for encapsulating cells in vitro [4, 5]. Our sensor is expected to be applied to spatiotemporal detection of several secreted proteins such as growth factors in near future.

References

[1] K. Furukawa, Y. Ueno, M. Takamura, H. Hibino, Graphene FRET Aptasensor, ACS Sensors, 1 (2016) 710-716. doi:10.1021/acssensors.6b00191.

[2] Y. Ueno, K. Furukawa, K. Matsuo, S. Inoue, K. hayashi, H. Hibino, On-chip graphene oxide aptasensor for multiple protein detection, Anal Chim Acta, 866 (2015) 1-9. doi: 10.1016/j.aca.2014.10.047.

[3] Y. Ueno, K. Furukawa, K. Matsuo, S. Inoue, K. Hayashi, H. Hibino, Molecular design for enhanced sensitivity of a FRET aptasensor built on the graphene oxide surface, Chem. Commun. 49 (2013) 10346-10348. doi:10.1039/C3CC45615C.

[4] T. F. Teshima, H. Nakashima, Y. Ueno, S. Sasaki, C. S. Henderson, S. Tsukada, Cell Assembly in Self-foldable Multilayered Soft Micro-rolls, Sci. Rep., 7 (2017) 17376. doi:10.1038/s41598-017-17403-0.

[5] K. Sakai, T. F. Teshima, H. Nakashima, Y. Ueno, Graphene-Based Neuron Encapsulation with Controlled Axonal Outgrowth, Nanoscale, 11 (2019) 13249-13259. doi:10.1039/C9NR04165F.

Ackowledgements

This work was supported by JSPS KAKENHI Grant Number JP17H02759.

Figure 1