Magnetic Biosensing

Golden Gopher Magnetic Biosensing Team

GMR biosensing

 

What is GMR?

Electrical resistance in a specially engineered tri-layered magnetic thin film changes when a magnetic field is applied. This phenomenon is known as “giant magnetoresistance” (GMR). GMR nanosensor has been widely and successfully used in hard disk drives for over 20 years. Its applications in bimolecular diagnostics just emerged in recent years. To date, chip based GMR along with magnetic nanoparticles (MNPs) have become a powerful tool for high sensitivity, real-time electrical readout, and rapid biomolecule detection. It could be visualized that this GMR technology should have great application prospects in disease monitor and prevention areas by virtue of its powerful diagnostic capability. 

 

What can we do with GMR?

GMR-based biosensing system in our group has successfully detected protein biomarkers for human disease such as lung cancer, prostate cancer, heart disease, and environmental issues such as mercury pollution. Previous works are based on in-lab bench top system testing and never worked on virus. Now we are aiming at bringing accurate and sensitive biosensing into non-laboratory settings like point-of-care clinics and homes. Furthermore, this GMR biosensor is expected to be an easy-to-use sensor and able to test multiple diseases in one simple body fluid sample and in one step.

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Handhold device developed by Wang’s group.

 

Fabrication of GMR spin valves

The multilayer GMR spin valve films with top-down structure of Ta (50 Å)/NiFe (20 Å)/CoFe(10 Å)/Cu(33 Å)/CoFe(25 Å)/IrMn(80 Å)/Ta (25 Å) were deposited by a Shamrock Magnetron Sputter System onto Si/SiO2 (1000 Å) substrate at the University of Minnesota. A 4-inch GMR wafer containing 21 usable chips is manufactured by photolithography, ion beam milling, and electron beam evaporation techniques. An 18nm thick Al2O3 layer was coated onto chip surface by atomic layer deposition (ALD) followed by a 20nm SiO2 layer by plasma-enhanced chemical vapor deposition (PECVD) in order to prevent current leakage and in the meanwhile SiO2 layer paves the way for future surface functionalization. 
Each GMR chip is in the size of 16mm × 16mm with 8 × 8 sensor array in its center. Each sensor is in the size of 120µm × 120µm containing 5 GMR strip groups connected in series and each group contains 10 GMR strips connected in parallel. Each strip with the size of 120µm × 750nm is separated by 2µm. All the GMR chips were annealed at 200o C under an applied magnetic field of 0.5 Tesla along the minor axis for 1 hour then naturally cooled down to room temperature in order to fully align the magnetization in the pinned layer.

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(a) GMR chip with attached reaction well was placed on the chip holder. The size of GMR chip is about 16×16 mm. (b) 8×8 sensor array in the center area of GMR chip, and the distance between adjacent sensors is 400 μm. (c) Optical image of one GMR sensor. (d) The strips in parallel.

 

GMR biosensor surface functionalization

GMR chips are first exposed to ultraviolet light and ozone (UVO) for 15 minutes to remove organic material from the sensor surface as well as to expose the hydroxyl group bonding sites. Each chip is then soaked in 5mL anhydrous toluene mixed with 1% of 3-aminopropyltriethoxy silane (APTES) for 1 hour at room temperature to allow APTES to covalently bind to the hydroxyl group from silica layer that is on-top-of GMR biosensors. Chips are thoroughly rinsed with acetone followed by ethanol and dried with nitrogen gas. The surface of APTES modified chips contain amino groups. To attach aldehyde groups onto sensor surface, the 64-sensor-array area of each chip is covered with 5% glutaraldehyde (Glu) solution (100µL) and incubated at room temperature for 5 hours under a relative humidity of ~97%. The terminal aldehyde groups generated on the sensor surface allow subsequent covalent bonding of biomolecules containing amino groups onto GMR sensor.

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Schematic diagram of GMR biosensor surface functionalization.

 

Application areas

Our group has demonstrated a novel sensing strategy employing GMR biosensor and DNA chemistry for the detection of mercuric ion (Hg2+). This assay takes advantages of high sensitivity and real-time signal readout of GMR biosensor and high selectivity of thymine−thymine (T−T) pair for Hg2+. The assay has a detection limit of 10 nM in both buffer and natural water, which is the maximum mercury level in drinking water regulated by U.S. Environmental Protection Agency (EPA). The magnitude of the dynamic range for Hg2+ detection is up to three orders (10 nM to 10 μM). Herein, GMR sensing technology is first introduced into a pollutant monitoring area. It can be foreseen that the GMR biosensor could become a robust contender in the areas of environmental monitoring and food safety testing.

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Schematic illustration of Hg2+ detection using the GMR biosensor

We also developed multiplexed, real-time electrical readout based on our GMR sensor array to detect a panel of protein biomarkers simultaneously. PAPP-A, PCSK9, and ST2 have been regarded as promising candidate biomarkers for cardiovascular diseases. Early detection of multiple biomarkers for a disease could enable accurate prediction of a disease risk. 64 nano-size GMR sensors were assembled onto one 16 mm×16 mm chip with a reaction well, and they could work independently and be monitored simultaneously. A detect limit of 40 pg/mL for ST2 antigen had been achieved, and the dynamic ranges for the three proteins detection were up to four orders of magnitude. The GMR sensing platform was also selective enough to be directly used in serum samples. In addition, a lab-based probe station has been designed to implement quick labon-a-chip experiments instead of wire bonding. It has a potential application in clinical biomarkers identification and screening, and can be extended to fit other biosensing schemes.

 

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Comparison of proteins detection in buffer and biological environment (spiked proteins in human serum). Columns: mean; bars: standard deviation; p>0.05 means they showed no statistically significant difference; p<0.01 means they showed statistically significant difference.

We also developed a simple and sensitive method for the detection of influenza A virus (IAV) based on our GMR biosensor. This assay employs monoclonal antibodies to viral nucleoprotein (NP) in combination with magnetic nanoparticles (MNPs) to capture and detect virus. Binding of MNPs onto the GMR sensor, which is proportional to the concentration of influenza virus, cause change in the resistance of sensor. GMR biosensor detected as low as 1.5 × 102 TCID50/mL virus and the signal intensity increased with increasing concentration of virus up to 1.0 × 105 TCID50/mL. The sensitivity of this assay is relevant for diagnostic application since the virus concentration in nasal samples of influenza virus infected swine was found to be in the range of 103 to 105 TCID50/mL.

 

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GMR biosensor showed higher sensitivity than ELISA for detection of IAV. IAV H3N2v or control (mock) were treated with 1% IGEPAL CA-630 to disrupt virus particle and used for detection by GMR biosensor and ELISA. (a) Binding curves in real-time on GMR biosensor; (b) Averaged signals from different concentrations of IAV and negative control (mock) in GMR biosensor and; (c) Antigen capture ELISA with different concentrations of IAV. Dotted line indicates the cut off value. Error bars represent SEM.

 

Search coil based biosensing

Brownian and Néel relaxation of magnetic nanoparticles (MNPs) can be characterized by a highly sensitive mixing-frequency method using a search-coil based detection system. The unique magnetic properties of MNPs have been used for biomarkers detection. MNPs are driven into the saturation region by a low frequency sinusoidal magnetic field. A high frequency sinusoidal magnetic field is then applied to generate mixing-frequency signals that are highly specific to the magnetization of MNPs. These highly sensitive mixing-frequency signals from MNPs are picked up by a pair of balanced built-in detection coils. 
We have developed a technique to detect the real-time relaxation of MNPs by using the mixing-frequency method. Correlation between the phase of the mixing frequency term and the Brownian relaxation of the MNPs was theoretically derived. Experimentally three MNPs (SHP35, IPG35, and IPG35-Ab) have been measured, and the results were fitted by Debye model with the consideration of MNPs size distribution. Real-time measurement of binding process between MNP-labeled protein G and antibody was demonstrated along with a control experiment. This study shows the potential capability of the developed technique for fundamental biological research, disease diagnostic and drug discovery.

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Real time measurement of phase delay of IPG35 in blue (upper curve) and control sample SMG35 in red (lower curve), with antibody injection at the 50th second.

We proposed and demonstrated the feasibility of using a search coil detection system and MNPs to test human serum viscosity in real-time. Glycerol and DI water mixtures were used to simulate in vitro viscosity test processes. It was found that the measurement of the voltage change percentage of the 3rd harmonic works well for the in vitro viscosity test. We tested and plotted the standard graphs that could be used to estimate the viscosity of any unknown liquids. We also tested the viscosity of a male human serum type AB by inserting the collected data into standard graphs. The estimated viscosity of this serum is 2.2 cp at 40 °C and 1.8 cp at 20 °C, compared to the real value of 1.35 cp and 1.74 cp, respectively. 

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The real-time voltage signal of the 3rd harmonic for MNPs in nine mixtures with different viscosities at 20 °C.

References:

  1. Wang, W., Wang, Y., Tu, L., Feng, Y., Klein, T. and Wang, J.P., 2014. Magnetoresistive performance and comparison of supermagnetic nanoparticles on giant magnetoresistive sensor-based detection system.Scientific reports, 4. PDF icon sci_rep._2014_4_5716.pdf
  2. Wang, W., Wang, Y., Tu, L., Klein, T., Feng, Y., Li, Q. and Wang, J.P., 2014. Magnetic detection of mercuric ion using giant magnetoresistance-based biosensing system. Analytical chemistry, 86(8), pp.3712-3716. PDF icon anal._chem._2014_86_8.pdf
  3. Wang, Y., Wang, W., Yu, L., Tu, L., Feng, Y., Klein, T. and Wang, J.P., 2015. Giant magnetoresistive-based biosensing probe station system for multiplex protein assays. Biosensors and Bioelectronics, 70, pp.61-68. PDF icon biosensors_and_bioelectronics_volume_70_15.pdf
  4. Krishna, V.D., Wu, K., Perez, A.M. and Wang, J.P., 2016. Giant Magnetoresistance-based Biosensor for Detection of Influenza A Virus.Frontiers in microbiology, 7. PDF icon front_microbiol._2016_7_400.pdf
  5. Srinivasan, B., Li, Y., Jing, Y., Xing, C., Slaton, J. and Wang, J.P., 2011. A three-layer competition-based giant magnetoresistive assay for direct quantification of endoglin from human urine. Analytical chemistry, 83(8), pp.2996-3002. PDF icon anal._chem._2011_83_8.pdf
  6. Li, Y., Srinivasan, B., Jing, Y., Yao, X., Hugger, M.A., Wang, J.P. and Xing, C., 2010. Nanomagnetic competition assay for low-abundance protein biomarker quantification in unprocessed human sera. Journal of the American Chemical Society, 132(12), pp.4388-4392. PDF icon j._am._chem._soc._2010_132_12.pdf
  7. Tu, L., Jing, Y., Li, Y. and Wang, J.P., 2011. Real-time measurement of Brownian relaxation of magnetic nanoparticles by a mixing-frequency method. Applied Physics Letters, 98(21), p.213702. PDF icon appl._phys._lett._98_213702_2011.pdf
  8. Wu, K., Liu, J., Wang, Y., Ye, C., Feng, Y. and Wang, J.P., 2015. Superparamagnetic nanoparticle-based viscosity test. Applied Physics Letters, 107(5), p.053701. PDF icon appl._phys._lett._107_053701_2015.pdf
  9. Wu, K., Batra, A., Jain, S., Ye, C., Liu, J. and Wang, J.P., 2015. A simulation study on superparamagnetic nanoparticle based multi-tracer tracking. Applied Physics Letters, 107(17), p.173701. PDF icon appl._phys._lett._107_173701_2015.pdf
  10. Wu, K., Klein, T., Krishna, V. D., Su, D., Perez, A. M., & Wang, J. P. (2017). Portable GMR Handheld Platform for the Detection of Influenza A Virus. ACS sensors. PDF icon 10.1021_acssensors.7b00432.pdf