BioFET-SIM: A Tool for the Analysis and Prediction of Signal Changes in Nanowire-Based Field Effect Transistor Biosensors

  • Martin R. Hediger
  • Karen L. Martinez
  • Jesper Nygård
  • Mads Brandbyge
  • Jan H. Jensen
  • Luca De Vico
Chapter
Part of the Lecture Notes in Nanoscale Science and Technology book series (LNNST, volume 19)

Abstract

Biosensors based on nanowire field effect transistor (FET) have received much attention in recent years as a way to achieve ultra-sensitive and label-free sensing of molecules of biological interest. The BioFET-SIM computer model permits the analysis and interpretation of experimental sensor signals through its web-based interface www.biofetsim.org. The model also allows for predictions of the effects of changes in the experimental setup on the sensor signal. After an introduction to nanowire-based FET biosensors, this chapter reviews the theoretical basis of BioFET-SIM models describing both single and multiple charges on the analyte. Afterwards the usage of the interface and its relative command line version is briefly shown. Finally, possible applications of the BioFET-SIM model are presented. Among the possible uses of the interface, the effects on the predicted signal of pH, buffer ionic strength, analyte concentration, and analyte relative orientation on nanowire surface are illustrated. Wherever possible, a comparison to experimental data available in literature is given, displaying the potential of BioFET-SIM for interpreting experimental results.

Notes

Acknowledgements

This work has been partially funded by the Danish Research Council for Technology and Production Sciences (FTP), the Danish Natural Science Research Council (FNU), and by UNIK Synthetic Biology program, funded by the Danish Ministry for Science, Technology and Innovation. The authors acknowledge fruitful discussions with Lars Iversen, Noémie Loret, Rune S. Frederiksen, and Shivendra Upadhyay.

References

  1. 1.
    Thévenot, D.R., Toth, K., Durst, R.A., Wilson, G.S.: Electrochemical biosensors: recommended definitions and classification. Biosens. Bioelectron. 16(1–2), 121 (2001). DOI 10.1016/S0956-5663(01)00115-4CrossRefGoogle Scholar
  2. 2.
    Hermanson, G.T.: Bioconjugate Techniques. Academic, San Diego (1996)Google Scholar
  3. 3.
    Stern, E., Klemic, J.F., Routenberg, D.A., Wyrembak, P.N., Turner-Evans, D.B., Hamilton, A.D., LaVan, D.A., Fahmy, T.M., Reed, M.A.: Label-free immunodetection with CMOS-compatible semiconducting nanowires. Nature 445, 519 (2007). DOI 10.1038/nature05498CrossRefGoogle Scholar
  4. 4.
    Vacic, A., Criscione, J.M., Rajan, N.K., Stern, E., Fahmy, T.M., Reed, M.A.: Determination of molecular configuration by Debye length modulation. J. Am. Chem. Soc. 133(35), 13886 (2011). DOI 10.1021/ja205684aCrossRefGoogle Scholar
  5. 5.
    Chen, Y., Wang, X., Erramilli, S., Mohanty, P., Kalinowski, A.: Silicon-based nanoelectronic field-effect pH sensor with local gate control. Appl. Phys. Lett. 89(22), 223512 (2006). DOI 10.1063/1.2392828CrossRefGoogle Scholar
  6. 6.
    Cui, Y., Wei, Q., Park, H., Lieber, C.M.: Nanowire nanosensors for highly sensitive and selective detection of biological and chemical species. Science 293, 1289 (2001). DOI 10.1126/science.1062711CrossRefGoogle Scholar
  7. 7.
    Gao, X.P., Zheng, G., Lieber, C.M.: Subthreshold regime has the optimal sensitivity for nanowire FET biosensors. Nano Lett. 10(2), 547 (2009). DOI 10.1021/nl9034219CrossRefGoogle Scholar
  8. 8.
    Tian, R., Regonda, S., Gao, J., Liu, Y., Hu, W.: Ultrasensitive protein detection using lithographically defined Si multi-nanowire field effect transistors. Lab Chip 11, 1952 (2011). DOI 10.1039/C0LC00605JCrossRefGoogle Scholar
  9. 9.
    Wong, I.Y., Melosh, N.A.: Directed hybridization and melting of DNA linkers using counterion-screened electric fields. Nano Lett. 9(10), 3521 (2009). DOI 10.1021/ nl901710nCrossRefGoogle Scholar
  10. 10.
    Dorvel, B.R., Reddy, B., Go, J., Duarte Guevara, C., Salm, E., Alam, M.A., Bashir, R.: Silicon nanowires with high-k Hafnium oxide dielectrics for sensitive detection of small nucleic acid oligomers. ACS Nano 6(7), 6150 (2012). DOI 10.1021/nn301495kGoogle Scholar
  11. 11.
    Chang, H.K., Ishikawa, F.N., Zhang, R., Datar, R., Cote, R.J., Thompson, M.E., Zhou, C.: Rapid, label-free, electrical whole blood bioassay based on nanobiosensor systems. ACS Nano 5(12), 9883 (2011). DOI 10.1021/nn2035796CrossRefGoogle Scholar
  12. 12.
    Berthing, T., Sørensen, C.B., Nygård, J., Martinez, K.L.: Applications of nanowire arrays in nanomedicine. J. Nanoneurosci. 1(1), 3 (2009). DOI 10.1166/jns.2009.001CrossRefGoogle Scholar
  13. 13.
    Patolsky, F., Zheng, G., Lieber, C.M.: Nanowire-based biosensors. Anal. Chem. 78(13), 4260 (2006). DOI 10.1021/ac069419jGoogle Scholar
  14. 14.
    Shinwari, M.W., Deen, M.J., Landheer, D.: Study of the electrolyte-insulator-semiconductor field-effect transistor (EISFET) with applications in biosensor design. Microelectron. Reliab. 47(12), 2025 (2007). DOI 10.1016/j.microrel.2006.10.003CrossRefGoogle Scholar
  15. 15.
    Curreli, M., Zhang, R., Ishikawa, F.N., Chang, H.K., Cote, R.J., Zhou, C., Thompson, M.E.: Real-time, label-free detection of biological entities using nanowire-based FETs. IEEE Trans. Nanotechnol. 7(6), 651 (2008). DOI 10.1109/TNANO.2006.880908CrossRefGoogle Scholar
  16. 16.
    Neizvestny, I.G.: Semiconductor nanowire sensors. Russ. Microelectron. 38(4), 223 (2009). DOI 10.1134/S1063739709040015CrossRefGoogle Scholar
  17. 17.
    Roy, S., Gao, Z.: Nanostructure-based electrical biosensors. Nano Today 4(4), 318 (2009). DOI 10.1016/j.nantod.2009.06.003CrossRefGoogle Scholar
  18. 18.
    Nair, P.R., Alam, M.A.: Performance limits of nanobiosensors. Appl. Phys. Lett. 88(23), 233120 (2006). DOI 10.1063/1.2211310CrossRefGoogle Scholar
  19. 19.
    Nair, P.R., Alam, M.A.: Screening-limited response of nanoBiosensors. Nano Lett. 8(5), 1281 (2008). DOI 10.1021/nl072593iCrossRefGoogle Scholar
  20. 20.
    Nair, P.R., Alam, M.A.: Theory of “Selectivity” of label-free nanobiosensors: A geometro-physical perspective. J. Appl. Phys. 107(6), 064701 (2010). DOI 10.1063/1. 3310531CrossRefGoogle Scholar
  21. 21.
    Heitzinger, C., Klimeck, G.: Computational aspects of the three-dimensional feature-scale simulation of silicon-nanowire field-effect sensors for DNA detection. J. Comput. Electron. 6, 387 (2007). DOI 10.1007/s10825-006-0139-xCrossRefGoogle Scholar
  22. 22.
    Ringhofer, C., Heitzinger, C.: Multi - scale modeling and simulation of field-effect biosensors. ECS Trans. 14(1), 11 (2008). DOI 10.1149/1.2956012Google Scholar
  23. 23.
    Heitzinger, C., Kennell, R., Klimeck, G., Mauser, N., McLennan, M., Ringhofer, C.: Modeling and simulation of field-effect biosensors (BioFETs) and their deployment on the nanoHUB. J. Phys. Conf. Ser. 107, 012004 (2008). DOI 10.1088/1742-6596/107/ 1/012004Google Scholar
  24. 24.
    Chen, H., Mukherjee, S., Aluru, N.: Charge distribution on thin semiconducting silicon nanowires. Comput. Methods Appl. Mech. Eng. 197(41–42), 3366 (2008). DOI 10.1016/j.cma.2008.02.007CrossRefGoogle Scholar
  25. 25.
    Heitzinger, C., Mauser, N.J., Ringhofer, C., Liu, Y., Dutton, R.W.: Proceedings of the Simulation of Semiconductor Processes and Devices (SISPAD 2009) (San Diego, CA, USA, 2009), pp. 86–90 (2009). DOI 10.1109/SISPAD.2009.5290244Google Scholar
  26. 26.
    Heitzinger, C., Mauser, N.J., Ringhofer, C.: Multiscale modeling of planar and nanowire field-effect biosensors. SIAM J. Appl. Math. 70(5), 1634 (2010). DOI 10.1137/080725027CrossRefGoogle Scholar
  27. 27.
    Windbacher, T., Sverdlov, V., Selberherr, S.: Biomedical engineering systems and technologies. In: Fred, A., Filipe, J., Gamboa, H. (eds.) Communications in Computer and Information Science, vol. 52, pp. 85–95. Springer, Berlin (2010). DOI 10.1007/ 978-3-642-11721-3\{∖_\}6Google Scholar
  28. 28.
    Park, H.H., Zeng, L., Buresh, M., Wang, S., Klimeck, G., Mehrotra, S.R., Heitzinger, C., Haley, B.P.: Nanowire, NanoHUB website (2006). DOI 10254/nanohub-r1307. 8. URL http://nanohub.org/resources/1307. Accessed Mar 2013
  29. 29.
    Nair, P.R., Go, J., Landells, G.J., Pandit, T.R., Alam, M.A.: BioSensorLab, NanoHUB website (2008). DOI 10254/nanohub-r2929. 5. URL http://nanohub.org/resources/2929. Accessed Mar 2013
  30. 30.
    Medici: Two Dimensional Device Simulation Program (2003). SynopsisGoogle Scholar
  31. 31.
    Sørensen, M.H., Mortensen, N.A., Brandbyge, M.: Screening model for nanowire surface-charge sensors in liquid. Appl. Phys. Lett. 91(10), 102105 (2007). DOI 10.1063/1.2779930CrossRefGoogle Scholar
  32. 32.
    De Vico, L., Sørensen, M.H., Iversen, L., Rogers, D.M., Sørensen, B.S., Brandbyge, M., Nygård, J., Martinez, K.L., Jensen, J.H.: Quantifying signal changes in nano-wire based biosensors. Nanoscale 3, 706 (2011). DOI 10.1039/C0NR00442AGoogle Scholar
  33. 33.
    De Vico, L., Iversen, L., Sørensen, M.H., Brandbyge, M., Nygård, J., Martinez, K.L., Jensen, J.H.: Predicting and rationalizing the effect of surface charge distribution and orientation on nano-wire based FET bio-sensors. Nanoscale 3, 3635 (2011). DOI 10.1039/C1NR10316DGoogle Scholar
  34. 34.
    Hediger, M.R., Jensen, J.H., De Vico, L.: BioFET-SIM Web Interface: Implementation and Two Applications. PLoS One 7(10), e45379 (2012). DOI 10.1371/ journal.pone.0045379Google Scholar
  35. 35.
    Punzet, M., Baurecht, D., Varga, F., Karlic, H., Heitzinger, C.: Determination of surface concentrations of individual molecule-layers used in nanoscale biosensors by in situ ATR-FTIR spectroscopy. Nanoscale 4, 2431 (2012). DOI 10.1039/C2NR12038KCrossRefGoogle Scholar
  36. 36.
    Hakim, M.M.A., Lombardini, M., Sun, K., Giustiniano, F., Roach, P.L., Davies, D.E., Howarth, P.H., de Planque, M.R.R., Morgan, H., Ashburn, P.: Thin film polycrystalline silicon nanowire biosensors. Nano Lett. 12(4), 1868 (2012). DOI 10.1021/nl2042276Google Scholar
  37. 37.
    Duan, X., Li, Y., Rajan, N., Routenberg, D., Modis, Y., Reed, M.: Quantification of the affinities and kinetics of protein interactions using silicon nanowire biosensors. Nat. Nanotechnol. 7(6), 401 (2012). DOI 10.1038/nnano.2012.82CrossRefGoogle Scholar
  38. 38.
    Elnathan, R., Kwiat, M., Pevzner, A., Engel, Y., Burstein, L., Khatchtourints, A., Lichtenstein, A., Kantaev, R., Patolsky, F.: Biorecognition layer engineering: Overcoming screening limitations of nanowire-based FET devices. Nano Lett. 12(10), 5245 (2012). DOI 10.1021/nl302434wCrossRefGoogle Scholar
  39. 39.
    Lloret, N., Frederiksen, R.S., Møller, T.C., Rieben, N.I., Upadhyay, S., De Vico, L., Jensen, J.H., Nygård, J., Martinez, K.L.: Effects of buffer composition and dilution on nanowire field-effect biosensors. Nanotechnology 24(3), 035501 (2013). DOI 10.1088/0957-4484/24/3/035501Google Scholar
  40. 40.
    Magliulo, M., Mallardi, A., Mulla, M.Y., Cotrone, S., Pistillo, B.R., Favia, P., Vikholm-Lundin, I., Palazzo, G., Torsi, L.: Electrolyte-gated organic field-effect transistor sensors based on supported biotinylated phospholipid bilayer. Adv. Mater. 25(14), 2090 (2013). DOI 10.1002/adma.201203587CrossRefGoogle Scholar
  41. 41.
    Hammock, M.L., Knopfmacher, O., Naab, B.D., Tok, J.B.H., Bao, Z.: Investigation of protein detection parameters using nanofunctionalized organic field-effect transistors. ACS Nano 7(5), 3970 (2013). DOI 10.1021/nn305903qCrossRefGoogle Scholar
  42. 42.
    Baumgartnerth, S., Heitzinger, C., Vacic, A., Reed, M.A.: Predictive simulations and optimization of nanowire field-effect PSA sensors including screening. Nanotechnology 24(22), 225503 (2013). DOI 10.1088/0957-4484/24/22/225503CrossRefGoogle Scholar
  43. 43.
    Nitzan, A., Galperin, M., Ingold, G.L., Grabert, H.: On the electrostatic potential profile in biased molecular wires. J. Chem. Phys. 117(23), 10837 (2002). DOI 10.1063/1.1522406CrossRefGoogle Scholar
  44. 44.
    Liang, G.C., Ghosh, A.W., Paulsson, M., Datta, S.: Electrostatic potential profiles of molecular conductors. Phys. Rev. B 69, 115302 (2004). DOI 10.1103/PhysRevB.69. 115302CrossRefGoogle Scholar
  45. 45.
    Zhang, X.G., Pantelides, S.T.: Screening in nanowires and nanocontacts: Field emission, adhesion force, and contact resistance. Nano Lett. 9(12), 4306 (2009). DOI 10.1021/nl902533n, pMID: 19845331CrossRefGoogle Scholar
  46. 46.
    Sørensen, M.H.: Nanowires for chemical sensing in a liquid environment. Bachelor Thesis (2007)Google Scholar
  47. 47.
    Olver, F.W.J.: In: Abramowitz, M., Stegun, I.A. (eds.) Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables, pp. 355–436. Dover, New York (1973)Google Scholar
  48. 48.
    Ishikawa, F.N., Chang, H.K., Curreli, M., Liao, H.I., Olson, C.A., Chen, P.C., Zhang, R., Roberts, R.W., Sun, R., Cote, R.J., Thompson, M.E., Zhou, C.: Label-free, electrical detection of the SARS virus N-protein with nanowire biosensors utilizing antibody mimics as capture probes. ACS Nano 3(5), 1219 (2009). DOI 10.1021/ nn900086cCrossRefGoogle Scholar
  49. 49.
    Björk, M.T., Schmid, H., Knoch, J., Riel, H., Riess, W.: Donor deactivation in silicon nanostructures. Nat. Nanotechnol. 4(2), 103 (2009). DOI 10.1038/nnano.2008.400CrossRefGoogle Scholar
  50. 50.
    Garnett, E.C., Tseng, Y.C., Khanal, D.R., Wu, J., Bokor, J., Yang, P.: Dopant profiling and surface analysis of silicon nanowires using capacitance–voltage measurements. Nat. Nanotechnol. 4(5), 311 (2009). DOI 10.1038/nnano.2009.43CrossRefGoogle Scholar
  51. 51.
    Stern, E., Wagner, R., Sigworth, F.J., Breaker, R., Fahmy, T.M., Reed, M.A.: Importance of the Debye screening length on nanowire field effect transistor sensors. Nano Lett. 7(11), 3405 (2007). DOI 10.1021/nl071792zCrossRefGoogle Scholar
  52. 52.
    Nair, P.R., Alam, M.A.: Design considerations of silicon nanowire biosensors. IEEE Trans. Electron Devices 54(12), 3400 (2007). DOI 10.1109/TED.2007.909059CrossRefGoogle Scholar
  53. 53.
    Yates, D.E., Levine, S., Healy, T.W.: Site-binding model of the electrical double layer at the oxide/water interface. J. Chem. Soc. Faraday Trans. 1 70, 1807 (1974). DOI 10.1039/F19747001807Google Scholar
  54. 54.
    Li, H., Robertson, A.D., Jensen, J.H.: Very fast empirical prediction and rationalization of protein pKa values. Proteins Struct. Funct. Bioinforma. 61(4), 704 (2005). DOI 110.1002/prot.20660Google Scholar
  55. 55.
    Bas, D.C., Rogers, D.M., Jensen, J.H.: Very fast prediction and rationalization of pKa values for protein-ligand complexes. Proteins Struct. Funct. Bioinforma. 73(3), 765 (2008). DOI 10.1002/prot.22102CrossRefGoogle Scholar
  56. 56.
    Olsson, M.H.M., Søndergaard, C.R., Rostkowski, M., Jensen, J.H.: PROPKA3: Consistent treatment of internal and surface residues in empirical pKa predictions. J. Chem. Theory Comput. 7(2), 525 (2011). DOI 10.1021/ct100578zCrossRefGoogle Scholar
  57. 57.
    Ullmann, G.M., Knapp, E.W.: Electrostatic models for computing protonation and redox equilibria in proteins. Eur. Biophys. J. 28, 533 (1999). DOI 10.1007/ s002490050236CrossRefGoogle Scholar
  58. 58.
    Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Shindyalov, I.N., Bourne, P.E.: The protein data bank. Nucleic Acids Res. 28(1), 235 (2000). DOI 10.1093/nar/28.1.235CrossRefGoogle Scholar
  59. 59.
    Liu, Y., Rieben, N., Iversen, L., Sørensen, B., Park, J., Nygård, J., Martinez, K.: Specific and reversible immobilization of histidine-tagged proteins on functionalized silicon nanowires. Nanotechnology 21, 245105 (2010). DOI 10.1088/0957-4484/21/24/ 245105CrossRefGoogle Scholar
  60. 60.
    Pugliese, L., Coda, A., Malcovati, M., Bolognesi, M.: Three-dimensional structure of the tetragonal crystal form of egg-white avidin in its functional complex with biotin at 2.7 å resolution. J. Mol. Biol. 231(3), 698 (1993). DOI 10.1006/jmbi.1993.1321Google Scholar
  61. 61.
    Weber, P., Ohlendorf, D., Wendoloski, J., Salemme, F.: Structural origins of high-affinity biotin binding to streptavidin. Science 243(4887), 85 (1989). DOI 10. 1126/science.2911722Google Scholar
  62. 62.
    Green, N.M.: Avidin-biotin technology. In: Wilchek, M., Bayer, E.A. (eds.) Methods in Enzymology, vol. 184, pp. 51–67. Academic, London (1990). DOI 10.1016/ 0076-6879(90)84259-JGoogle Scholar
  63. 63.
    Hediger, M.R.: A perspective on bionanosensor simulation & computational enzyme engineering. Ph.D. Thesis, Department of Chemistry, University of Copenhagen (2013)Google Scholar
  64. 64.
    The PyMOL Molecular Graphics System: Version 1.3.0 Schrödinger, LLCGoogle Scholar
  65. 65.
    Harris, L.J., Larson, S.B., Hasel, K.W., McPherson, A.: Refined structure of an intact IgG2a monoclonal antibody. Biochemistry 36(7), 1581 (1997). DOI 10.1021/ bi962514+Google Scholar
  66. 66.
    Macao, B., Johansson, D., Hansson, G., Härd, T.: Autoproteolysis coupled to protein folding in the SEA domain of the membrane-bound MUC1 mucin. Nat. Struct. Mol. Biol. 13(1), 71 (2005). DOI 10.1038/nsmb1035CrossRefGoogle Scholar
  67. 67.
    Goodsell, D.S., Morris, G.M., Olson, A.J.: Automated docking of flexible ligands: Applications of autodock. J. Mol. Recognit. 9(1), 1 (1996). DOI 10.1002/(SICI) 1099-1352(199601)9:1⟨1::AID-JMR241⟩3.0.CO;2-6Google Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Martin R. Hediger
    • 1
  • Karen L. Martinez
    • 2
    • 3
  • Jesper Nygård
    • 4
    • 3
  • Mads Brandbyge
    • 5
  • Jan H. Jensen
    • 1
  • Luca De Vico
    • 1
  1. 1.Department of ChemistryUniversity of CopenhagenCopenhagenDenmark
  2. 2.Bionanotechnology and Nanomedicine Laboratory, Department of ChemistryUniversity of CopenhagenCopenhagenDenmark
  3. 3.Nano-Science CenterUniversity of CopenhagenCopenhagenDenmark
  4. 4.Niels Bohr Institute, Center for Quantum DevicesUniversity of CopenhagenCopenhagenDenmark
  5. 5.DTU Nanotech, Department of Micro and NanotechnologyTechnical University of DenmarkKongens LyngbyDenmark

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