Quartz crystal microbalance-based biosensors as rapid diagnostic devices for infectious diseases

Abstract

Infectious diseases are the ever-present threats to public health and the global economy. Accurate and timely diagnosis is crucial to impede the progression of a disease and break the chain of transmission. Conventional diagnostic techniques are typically time-consuming and costly, making them inefficient for early diagnosis of infections and inconvenient for use at the point of care. Developments of sensitive, rapid, and affordable diagnostic methods are necessary to improve the clinical management of infectious diseases. Quartz crystal microbalance (QCM) systems have emerged as a robust biosensing platform due to their label-free mechanism, which allows the detection and quantification of a wide range of biomolecules. The high sensitivity and short detection time offered by QCM-based biosensors are attractive for the early detection of infections and the routine monitoring of disease progression. Herein, the strategies employed in QCM-based biosensors for the detection of infectious diseases are extensively reviewed, with a focus on prevalent diseases for which improved diagnostic techniques are in high demand. The challenges to the clinical application of QCM-based biosensors are highlighted, along with an outline of the future scope of research in QCM-based diagnostics.

Keywords: Biosensor; Diagnosis; Infectious disease; Influenza; Quartz crystal microbalance; Virus.

Fig. 1

Principle of detection in a QCM-based immunosensor. The graph shows the frequency responses of the biosensor at different stages of the assay: (I) frequency baseline of a QCM crystal with immobilised antibody receptors; (I-II) binding of target molecules to the receptors; (II-III) binding of nanoparticles labelled with secondary antibodies; (IV) regeneration of the sensor surface.

Fig. 2

Hybridisation of target nucleic acids to ssDNA probes on the QCM surface. Illustration adapted from Afzal et al. (2017).

Fig. 3

Principle of recognition in a MIP-based biosensor: (a) formation of recognition cavities in MIPs; (b) binding of target molecules to the recognition cavities on the MIP-functionalised crystal surface.

Fig. 4

Hydrogel aptasensor for the detection of AIV H5N1: (a) chemical modification of the QCM surface with a nanoporous gold film; (b) QCM electrode before (I) and after (II) the surface modification; (c) scanning electron microscopy (SEM) image of an AIV H5N1 bound to the nanowell structure on the crystal surface; (d) frequency shifts of the aptasensor to 2 HAU of different AIV subtypes; (e) frequency responses to tracheal swab samples spiked with 2^-4 to 2⁰ HAU of AIV H5N1. Reprinted with permission from Wang et al. (2017). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 5

RCA-QCM biosensor: (a) hybridisation of a circular probe with a target strand results in the circularisation and ligation of the probe, whereas RCA does not occur for a single-mismatch strand. The RCA product then binds to the crystal surface via the complementary capture probes; (b) real-time frequency response of the biosensor during the RCA reaction; (c) frequency shifts of the biosensor (with and without RCA reaction) in response to the negative control, HBV DNA target, and single-mismatch strand. Reprinted with permission from Yao et al. (2013).

Fig. 6

DNA biosensor for dengue detection: (a) frequency responses of the biosensor at each stage of the detection process; (b) frequency shifts for spiked blood samples. SEM images of the QCM crystal surface: (c) after the hybridisation of target DNA; (d) after the binding of the first layer of AuNPs; (e) after the binding of the second layer of AuNPs. Reprinted with permission from Chen et al. (2009). Copyright IOP 2009.

Fig. 7

Polydopamine-based biosensor for the detection of HIV gp41 glycoproteins: (a) schematic representation of the epitope imprinting process; (b) real-time frequency responses of the biosensor to injections of the target peptide; (c) a Scatchard plot showing the linear range of the biosensor to the target peptide. Reprinted with permission from Lu et al. (2012).

Fig. 8

Research opportunities in QCM-based diagnostics: (a) design of a microfluidic ATPS for the selective extraction of virus-like particles from cell cultures; (b) 3D design of a microfluidic QCM sensor for the detection of C-reactive protein; (c) a tetra-electrode QCM system connected to four channels for sample delivery; (d) a portable QCM platform for point-of-care genetic testing. Reprinted with permissions from Jacinto et al. (2015), Thies et al. (2017), Latif et al. (2011) (Copyright Springer 2011), and Papadakis et al. (2019) (Copyright ACS 2019), respectively.