Silicon nanowire (SiNW) biosensors are small, portable and sensitive, and are able to detect DNA and diagnose diseases earlier than conventional methods. So far, however, the intensity of the analytical signal from these sensors has been low.

These devices consist of a length of either DNA or a peptide nucleic acid (PNA) attached to silicon nanowires, which provide hybridization sites for the target DNA.

The sensing mechanism is based on the change in the charge density caused by the DNA being detected, which induces a change in the electric field at the SiNW surface. The sensitivity of the signal detected depends on the distance of the DNA charge layer from the SiNW.

Here, Guo-Jun Zhang and colleagues, from the Institute of Microelectronics in Singapore, investigated how to fine-tune the distance between the DNA charge layer and SiNW to optimize the sensitivity of the biosensor.1

Fig. 1: The experimental change in resistance (|ΔR/R0|) versus the calculated distance of the DNA strands to the SiNW. (Inset) Schematic diagram of the variation of the field effect of the SiNW sensor caused by varying the hybridization sites of target DNA to PNA.

They used PNA as the probe molecule because its neutrality yields ultralow background charges, and thus produced a higher signal-to-noise ratio. The authors chose PNA with specific amino acid sequences so that a range of complementary DNAs — all having the same number of charges — could be hybridized to it in specific positions along its length, thereby determining the distance of the charge layer from the SiNW surface. The field effect of the SiNW was different for each cDNA, showing an increase in the detection sensitivity of the device with increasing proximity of the cDNA charge layer (Fig. 1).

This work shows that the sensitivity of the SiNW sensor can be increased by judicious choice of the amino acid sequences of the PNA probe molecule. At present, the team are engaged in developing a multiplexed platform, where the SiNW sensor is integrated with a PC for read-out and data management.