Elsevier

Biosensors and Bioelectronics

Volume 61, 15 November 2014, Pages 357-369
Biosensors and Bioelectronics

Sensing strategies for influenza surveillance

https://doi.org/10.1016/j.bios.2014.05.024Get rights and content

Highlights

  • Influenza viruses cause respiratory diseases in birds and mammals.

  • With seasonal epidemics, influenza spreads all over the world, resulting in pandemics that cause millions of deaths.

  • Emergence of various types and subtypes of influenza requires effective surveillance.

  • Diagnostic probes (glycans, aptamers, and antibodies) allow discrimination among the influenza strains.

  • Several sensors have been developed to augment influenza detection.

Abstract

Influenza viruses, which are RNA viruses belonging to the family Orthomyxoviridae, cause respiratory diseases in birds and mammals. With seasonal epidemics, influenza spreads all over the world, resulting in pandemics that cause millions of deaths. Emergence of various types and subtypes of influenza, such as H1N1 and H7N9, requires effective surveillance to prevent their spread and to develop appropriate anti-influenza vaccines. Diagnostic probes such as glycans, aptamers, and antibodies now allow discrimination among the influenza strains, including new subtypes. Several sensors have been developed based on these probes, efforts made to augment influenza detection. Herein, we review the currently available sensing strategies to detect influenza viruses.

Introduction

Flu is a severe illness caused by influenza viruses, which infect mainly the upper respiratory tract (nose, throat, bronchi, and lungs). Influenza viruses are spherical, enveloped, and range in diameter from 80 to 120 nm (Noda et al., 2006) (Fig. 1a). The three major types of influenza viruses are influenza A, B, and C. Influenza A commonly circulates among birds and mammals, often causing death (Fig. 1b), whereas influenza B occurs mainly in humans. Although influenza C is not very common, it also causes illness. Two major surface glycoproteins [hemagglutinin (HA) and neuraminidase (NA)] play an important role in influenza infection (Fig. 1a). Influenza A is classified according to its H number (HA) or N number (NA). So far, 17HA and 10NA viruses have been reported (Gopinath et al., 2013c and references therein). Two antigenic and genetic lineages (Yamagata and Victoria) of influenza B virus have been circulating since the 1980s, but they have caused lesser problems than influenza A. New influenza strains are continuously emerging. For example, the “pandemic swine flu” is caused by the H1N1 viral strain (pdm/09). “Bird flu” is mainly a subtype of H5N1 that causes illness mainly in birds. On April 1, 2013, a new bird influenza, A H7N9, was reported in China by the World Health Organization.

HA and NA antigens are the dominant targets for the host antibody response. However, frequent mutations in the amino acid sequences of these surface antigens (a process called antigenic drift) enable the viruses to evade the host immune system. HA is the main viral antigen required for membrane fusion with host cells to mediate early infection (Skehel and Wiley, 2000). HA binds to sialic acid residues (α-2,6 and α-2,3 sialic acids) on the surface of human and bird cells via three important amino acid regions (Fig. 2a and b). Traditionally, biological assays have been utilized to determine the involvement of these molecules in the infection of host cells. Commonly used biological assays for sensing influenza viruses are the hemagglutination assay, hemagglutination inhibition (HI) assay, plaque assay, and microneutralization assay.

Section snippets

Biological assays

The hemagglutination assay is used to indirectly quantify the titer of influenza virus, and it is based on the specific interaction of the virus HA with the host cell surface glycan (Killian, 2008). Upon binding of the HA to the sialylated glycans of either avian or mammalian erythrocytes, a diffuse lattice is formed due to the formation of cross-bridges between red blood cells (RBCs), and this process causes agglutination (Fig. 2c). Agglutination is mediated either by whole virus or trimeric

Influenza detection using glycans

The surface antigen (HA) of an influenza virus particle binds terminal sialic acid residues on the host cell surface, which induces uptake of the infecting virus. These glycan chains link the HA molecules on the surface of the viruses to the host cells. The two most common glycan chains are α-2,6 and α-2,3 sialic acids (Gambaryan et al., 1997, Gambaryan et al., 2004, Subbarao and Katz, 2000, Matrosovich et al., 2001, Suzuki, 2005, Kale et al., 2008, Neumann et al., 2009, Liao et al., 2010).

Sensors for influenza detection

The development of biosensors that can be used to analyze the influenza recognition elements remains a challenge in the field of medical diagnosis (Table 1). Various biosensors have been developed using different anti-influenza probes for use in diagnostic immunoassays (Gopinath et al., 2006a, Gopinath et al., 2006b, Gopinath et al., 2010, Gopinath et al., 2013a, Gopinath et al., 2013b, Gopinath et al., 2013c, Bahgat et al., 2009, Wang et al., 2009, Watanabe et al., 2009, Watcharatanyatip et

Lateral flow test

The lateral flow test, also known as the lateral flow immunochromatography test (ICT), is designed to detect the presence of a particular target within a complex mixture (Hara et al., 2008, Mori et al., 2012, Mitamura et al., 2013). ICT is used in medical diagnosis from the home to the field, especially in the detection of influenza viruses. The efficiency and reliability of an ICT relies mainly on the use of the correct lateral flow. Prior to detection, a solution containing detergents is used

Colorimetric analyses

Colorimetric assays are another tool for naked eye visualization of influenza viral interactions. Colorimetry is a solution-based assay that can be used to indirectly determine the concentration of the target via absorbance of light at a certain wavelength. Tannock et al. (1989) measured the release of neutral red from influenza virus-infected MDCK cells in an automated neutralization test for influenza B virus. Using crystal violet, MTT [3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium

Kretschmann configurations

Biological, ICT, and colorimetric assays display visible results. In addition to these methods, real-time monitoring is another popular way of measuring influenza virus interactions (Fig. 5a and b). Kretschmann configuration-based strategies, which include SPR, waveguide mode are examples for real-time monitoring.

Interferometry-based platform: BioDVD

Interferometry is the principle of superimposition of electromagnetic waves with similar or different phases. Superimposition of electromagnetic waves that are similar in phase yields constructive interference, whereas superimposition of waves with different phases results in destructive interference. Immobilization or interaction between biomolecules affects the interference, in which the changes in interference indicate the interaction events (Hariharan, 2007). Interferometry-based platform

Strategies for enhancing the efficiency of influenza detection

Most of the current diagnostic methods suffer from low sensitivity, high cost, and the need for species-specific reagents. Thus, new, rapid, reliable, and sensitive systems are needed for influenza diagnostics (Negri et al., 2011). Sensitivity of the sensing system can be improved in several ways, including the use of a sandwich configuration with two different probes, use of fluorescent/chemical tags/metals or other nanoparticles, and physical modifications on sensing surface.

Future perspectives

Surveillance is an important approach for influenza control. A rapid and accurate diagnostic method is necessary for influenza surveillance and to prevent the spread of the virus. Further, the design and structure of sensing systems should be suitable for home-to-field applications with high sensitivity. Several sensitive systems are currently available and in use in clinical practice. Although these sensing systems are able to differentiate between influenza A and B, differentiation within

Acknowledgements

We thank Universiti Sains Malaysia (USM) for awarding an Academic Staff Training Scheme to Citartan M for this study, and we acknowledge the support provided by the Advanced Medical and Dental Institute, USM, to cover his travelling and subsistence costs while in Japan. Tang TH was supported by USM Research University Grant 1001/CIPPT/813043. Y. Chen was supported by UM.C/625/1/HIR/MOHE/MED/16/5. We thank AMDI Research committee for supporting the manuscript for English editing services.

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