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Posted: Jun 29, 2012

Nanotechnology sensor detects flu viruses in exhaled breath

(Nanowerk Spotlight) Breath analysis of exhaled breath condensate (EBC) has been increasingly recognized as a promising diagnostic method to link specific gaseous components in human breath to medical conditions and exposure to chemical compounds. Sampling breath is also much less invasive than testing blood, can be done very quickly, and creates as good as no biohazard waste (see our previous Nanowerk Spotlight: "This will take your breath away").
Among the nanotechnology-based platforms for label-free and ultrasensitive virus detection are gold nanoparticles, carbon nanotubes, and silicon nanowires. Using the latter, researchers at Peking University, China have now configured a silicon nanowire field effect transistor as an ultra sensitive influenza virus detection device for exhaled breath samples by chemically linking an antibody to its surface. Upon virus binding to the antibody, the conductance undergoes a discrete change and thereby transforms a biological presence of a certain virus in exhaled breath into electrical signals.
Studies have shown that exhaled breath from a flu patient contains influenza viruses but, although the use of silicon nanowire (SiNW) sensors for virus detection is not new, so far no studies have been conducted to apply silicon nanowire technology to the diagnosis of flu.
"We have successfully demonstrated the direct and selective detection of influenza viruses (H3N2) in diluted exhaled breath condensate samples collected from the flu patients within minutes using our silicon nanowire sensor," Dr. Maosheng Yao, a researcher at the College of Environmental Sciences and Engineering at Peking University, tells Nanowerk. "Our work suggests that the SiNW sensor device, when calibrated by virus standards and exhaled breath condensate controls, can be reliably applied to the diagnosis of flu in a clinical setting with two orders of magnitude less time compared to the gold standard method RT-qPCR."
The team, including Drs. Xuefeng Guo and Tong Zhu, both from Peking University, reports their findings in the June 25, 2012 online edition of Nano Letters ("Rapid Flu Diagnosis Using Silicon Nanowire Sensor").
"Commercialization of the technology described in this work as a hand-held device, which is entirely doable, opens up outstanding opportunities of revolutionizing flu diagnosis in a clinical setting," says Yao.
Influenza virus detection nanowire device set-up
Influenza virus detection nanowire device set-up. (Image: Dr. Maosheng Yao, Peking University)
According to the World Health Organization, annual influenza (mostly H3N2 and H1N1) epidemics worldwide are responsible for three to five million cases of severe illness, eventually leading to 250000 to 500000 deaths. For diagnosis of viral infections, health professionals empirically rely on the white blood cell levels from a routine blood test and accompanying clinical symptoms such as headache, cough, and arthralgia.
However, as Yao points out, this practice lacks scientific evidence. "In certain cases, RT-qPCR, regarded as the gold standard method, was employed for viral detection in nasal swabs and bronchoalveolar lavages, exhibits higher detection rates than culturing and immuno-detection methods. Apart from other compounds, influenza and papilloma viruses previously have been detected in EBC samples by RT-qPCR and ELISA methods. However, these methods are impacted by the false-negatives for low-level influenza viruses and longer detection time of up to several hours as a result of the labor-extensive procedures such as RNA extraction and amplification for RT-qPCR," he says.
Accordingly, this procedure is not practical in a clinical setting given the large number of hospital visits and the patients' limited wait time, especially during an influenza outbreak or a bio-terror attack.
The team fabricated the silicon nanowires for their sensor device using a chemical vapor deposition method. Subsequently, the nanowires were aligned on silicon substrates with microfluidic channels placed over them. Then, electrical contacts to individual SiNWs were formed by standard photolithographic processes and thermal evaporation. After that, these nanosensor devices were functionalized with influenza A H3N2-H1N1 subtype or a biomarker (control) antibodies.
With their sensors, the researchers found they were able to selectively detect influenza A viruses down to ∼30 viruses/µL in clinical exhaled breath condensate samples (diluted by 100-fold) within minutes.
"For 90% of the cases, we have observed that EBC samples tested positive or negative by the RT-qPCR method generated corresponding positive or negative SiNW sensor responses with an unparalleled detection speed," says Yao. "While for those EBC samples with very low quantity of viruses, antibody modified magnetic beads were shown capable of efficiently concentrating the viruses for enhanced direct detection by the SiNW sensor device."
In a previous study published last year ("Integrating Silicon Nanowire Field Effect Transistor, Microfluidics and Air Sampling Techniques For Real-Time Monitoring Biological Aerosols"), the team achieved the detection of airborne flu viruses within minutes by integrating their SiNW sensor with an air sampling device and a microfluidic channel.
Yao notes that one limiting factor with their technologies is the cross-reaction between antibodies and non-target antigens, which is a challenging problem common to immuno-based detection methods. "One of our hurdles to move this technology forward is to develop highly specific virus subtype antibodies that could avoid the cross reactions between viruses and non-specific antibodies" he says.
The researchers at Peking University are confident that their SiNW sensor system can be readily extended to other types of viruses or biomarkers present in EBC samples. "Integration of different virus antibody modified SiNW sensor devices in a single chip using a micropipet technology would offer the opportunity to simultaneously detect different viruses in a single EBC sample," says Yao.
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