Xing Su

Label-free electrical detection of pyrophosphate generated from DNA polymerase reactions on field-effect devices.

We introduce a label-free approach for sensing polymerase reactions on deoxyribonucleic acid (DNA) using a chelator-modified silicon-on-insulator field-effect transistor (SOI-FET) that exhibits selective and reversible electrical response to pyrophosphate anions. The chemical modification of the sensor surface was designed to include rolling-circle amplification (RCA) DNA colonies for locally enhanced pyrophosphate (PPi) signal generation and sensors with immobilized chelators for capture and surface-sensitive detection of diffusible reaction by-products. While detecting arrays of enzymatic base incorporation reactions is typically accomplished using optical fluorescence or chemiluminescence techniques, our results suggest that it is possible to develop scalable and portable PPi-specific sensors and platforms for broad biomedical applications such as DNA sequencing and microbe detection using surface-sensitive electrical readout techniques.

Surface immobilizable chelator for label-free electrical detection of pyrophosphate

A new pyrophosphate (PPi) chelator was designed for surface-sensitive electrical detection of biomolecular reactions. This article describes the synthesis of the PPi-selective receptor, its surface immobilization and application to label-free electrical detection on a silicon-based field-effect transistor (FET) sensor.

16.1 A nanogap transducer array on 32nm CMOS for electrochemical DNA sequencing

In this paper, we have demonstrated a highly scalable all-electronic approach towards DNA sequencing using CMOS readout electronics coupled with post-processed nanogap transducers. While this test chip demonstrated a small array of 8,192 pixels, a 25mm2 chip could theoretically contain over 12 million pixels including I/O pads. Through careful architectural design choices and selection of a novel transduction scheme, we demonstrate that biosensing, such as DNA sequencing, can be performed on advanced CMOS process nodes.

Scalable Nanogap Sensors for Non-redox Enzyme Assays

Clinical diagnostic assays that monitor redox enzyme activity are widely used in small, low-cost readout devices for point-of-care monitoring (e.g., a glucometer); however, monitoring non-redox enzymes in real-time using compact electronic devices remains a challenge. We address this problem by using a highly scalable nanogap sensor array to observe electrochemical signals generated by a model non-redox enzyme system, the DNA polymerase-catalyzed incorporation of four modified, redox-tagged nucleotides. Using deoxynucleoside triphosphates (dNTPs) tagged with para-aminophenyl monophosphate (pAPP) to form pAP-deoxyribonucleoside tetra-phosphates (AP-dN4Ps), incorporation of the nucleotide analogs by DNA polymerase results in the release of redox inactive pAP-triphosphates (pAPP3) that are converted to redox active small molecules para-aminophenol (pAP) in the presence of phosphatase. In this work, cyclic enzymatic reactions that generated many copies of pAP at each base incorporation site of a DNA template in combination with the highly confined nature of the planar nanogap transducers ( z = 50 nm) produced electrochemical signals that were amplified up to 100,000×. We observed that the maximum signal level and amplification level were dependent on a combination of factors including the base structure of the incorporated nucleotide analogs, nanogap electrode materials, and electrode surface coating. In addition, electrochemical signal amplification by redox cycling in the nanogap is independent of the in-plane geometry of the transducer, thus allowing the nanogap sensors to be highly scalable. Finally, when the DNA template concentration was constrained, the DNA polymerase assay exhibited different zero-order reaction kinetics for each type of base incorporation reaction, resolving the closely related nucleotide analogs.

Sensitive and selective gas/VOC detection using MOS sensor array for wearable and mobile applications

We demonstrate a monolithic, micro-fabricated metal-oxide semiconductor (MOS) sensor array comprising of different metal oxides, allowing for independent temperature controls and readouts from individual pixels in a multiplexed fashion. The sensor pixels are designed on an ultrathin membrane to minimize heat dissipation, thereby significantly lowering the overall power consumption (<10μW). The use of such an array at varying temperatures results in multidimensional data, which we use to train neural network machine learning algorithms to determine unique fingerprints of individual gases within a homogenous mixture. Our findings indicate that a multiplicity of MOS elements together with the ability to vary and measure at various temperatures can identify individual gases or VOCs within mixtures. The small form-factor and microfabrication approach of our sensor array also lends itself to CMOS integration, paving the way for a sensitive and selective gas/VOC platform for wearable and portable applications.