Highly Sensitivity Detection Of Label-Free H1n1 Influenza A Virus On Electrical Impedance Spectroscopy Using Microsystems Technologies

Background: H1N1 Influenza virus A is a common human pathogenic agent that caused serious respiratory illness and death over the past century. It always causes widespread pandemics whenever a new type of Influenza strain appeared in the human population and then spread person to person easily. Diagnosis of influenza is important for initiation of antiviral therapy and implementation of infection control strategies. Reverse-transcriptase polymerase chain reaction (RT-PCR) is considered the reference test for diagnosis of influenza because of its high sensitivity and specificity as well as its rapid turnaround time. However, RT-PCR is expensive and requires trained expertise and batch testing, which delays reporting. To overcome this problem, we develop a Lab-on-a-Chip (LoC) type Micro Electromechanical Systems (MEMS) scale non-invasive biosensor for detecting and differentiating infectious cells at single cell level based on their electrical properties. Methods & Materials: Finite element method (FEM) simulations were conducted in COMSOL Multi physics software to verify and optimize device design. Devices were fabricated on 4” silicon wafers with <100> orientation. Cells from four cell lines (H1N1-pdm09 and PR8-H1N1cells) were used in experiments. Cell flow through the micro fluidic channel was monitored through a video camera connected to the probe-station microscope. Impedance measurements were always taken at a low and a high frequency pair in order to obtain impedance data at two frequencies. Results: Cells from tested cell lines and latex beads were successfully detected and differentiation was demonstrated. Using linear regression, opacity (real impedance at high frequency/real impedance at low frequency) was calculated to be 0.814(latex beads), 0.200(H1N1-pdm09), 0.625(PR8-H1N1) cells respectively. R2 for data clusters were 0.777, 0.719 and 0.943 for latex beads, H1N1-pdm09 and PR8-H1N1 cells respectively. The different cell lines form clusters that are easily differentiable, thus device can be used not only to detect, but also to differentiate between the tested cell lines. Conclusion: Device exhibits potential to be developed into a LoC biosensor capable of rapid detection and analyzing different infection in blood. It requires no cell labelling, no cell immobilization or device functionalization and mean time it is very cost effective.