Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-09T09:05:01.966Z Has data issue: false hasContentIssue false

Nanotextured Material for Applications in CSF Sample Screening and Characterization

Published online by Cambridge University Press:  20 July 2012

Krishna Vattipalli
Affiliation:
Department of Bioengineering, University of Texas at Dallas, Richardson, TX – 75080
Savindra Brandigampala
Affiliation:
Department of Electrical Engineering and Computer Science, Wichita State University, Wichita, KS – 67260
Claire McGraw
Affiliation:
Department of Chemical Engineering, Arizona State University, Tempe, AZ - 85287
Gaurav Chatterjee
Affiliation:
Department of Chemical Engineering, Arizona State University, Tempe, AZ - 85287
Srinath Kasturirangan
Affiliation:
Department of Chemical Engineering, Arizona State University, Tempe, AZ - 85287
Philip Schulz
Affiliation:
Department of Chemical Engineering, Arizona State University, Tempe, AZ - 85287
Michael Sierks
Affiliation:
Department of Chemical Engineering, Arizona State University, Tempe, AZ - 85287
Shalini Prasad*
Affiliation:
Department of Bioengineering, University of Texas at Dallas, Richardson, TX – 75080
*
*Corresponding author: [email protected]
Get access

Abstract

Neurodegenerative disease is primarily characterized by protein misfolding and the resultant protein aggregation. Presence of soluble oligomeric aggregates of proteins including various Aβ and α-syn aggregate species can be correlated to the onset and progression of many neurodegenerative diseases. The ability to detect protein misfolding requires the design of a diagnostics assay the will enable molecular level probing. The use of nanoporous ceramic templates enables size based immobilization of the target proteins and by leveraging the principle of “macromolecular crowding” protein association can be mapped with a high degree of resolution. By tailoring the surface functionalization within nanoporous ceramic templates, macromolecular immobilization can be selectively controlled, which in turn significantly enhances the perturbation to the electrical double layer/. The changes to the electrical double layer are measured with a high degree of sensitivity through impedance spectroscopy.

Pre symptomatic diagnosis and distinction between Alzheimer’s and Parkinson’s diseases can be achieved by the specific detection and quantification of levels of each of these different toxic protein species in cerebrospinal fluid (CSF). Detection using highly selective morphology specific reagents in conjunction with the ultrasensitive nanoporous electronic biosensor showed the presence of different protein morphologies in human CSF samples. Detection is primarily achieved by identifying the specific association of the protein with its receptor using electrochemical impedance spectroscopy. Furthermore, we show that these morphology specific reagents can readily classify between post-mortem CSF samples from AD, PD and cognitively normal sources. These studies suggest that detection of specific oligomeric aggregate species holds great promise as sensitive biomarkers for neurodegenerative disease.

Type
Articles
Copyright
Copyright © Materials Research Society 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1. Alzheimers Dement 6, 2, 158–94 (2010) Google Scholar
2. Petersen, R. C., Doody, R., Kurz, A., Mohs, R. C., Morris, J. C., Rabins, P. V., Ritchie, K., Rossor, M., Thal, L. and Winblad, B., Arch. Neurol., 58, 12, 1985–92 (2001).10.1001/archneur.58.12.1985Google Scholar
3. Jack, C. R. Jr., Lowe, V. J., Weigand, S. D., Wiste, H. J., Senjem, M. L., Knopman, D. S., Shiung, M. M., Gunter, J. L., Boeve, B. F., Kemp, B. J., Weiner, M. and Petersen, R. C., Brain, 132, 5, 1355–65 (2009).10.1093/brain/awp062Google Scholar
4. Hu, W. T., Chen-Plotkin, A., Arnold, S. E., Grossman, M., Clark, C. M., Shaw, L. M., McCluskey, L., Elman, L., Karlawish, J., Hurtig, H. I., Siderowf, A., Lee, V. M., Soares, H. and Trojanowski, J. Q., Acta Neuropathol., 120, 3, 385–99 (2010).10.1007/s00401-010-0723-9Google Scholar
5. De Meyer, G., Shapiro, F., Vanderstichele, H., Vanmechelen, E., Engelborghs, S., De Deyn, P. P., Coart, E., Hansson, O., Minthon, L., Zetterberg, H., Blennow, K., Shaw, L. and Trojanowski, J. Q., Arch. Neurol., 67, 8, 949–56 (2010).10.1001/archneurol.2010.179Google Scholar
6. Bothara, M., Venkatraman, V., Reddy, R. K., Barrett, T., Carruthers, J. and Prasad, S., Nanomedicine, 3, 4, 423–36 (2008).10.2217/17435889.3.4.423Google Scholar
7. Reddy, R. K., Bothara, M. G., Barrett, T. W., Carruthers, J. and Prasad, S., IEEE Sens. J., 8, 5–6, 720723 (2008).10.1109/JSEN.2008.923177Google Scholar
8. Venkatraman, V. L., Reddy, R. K., Zhang, F. Y., Evans, D., Ulrich, B. and Prasad, S., Biosensors & Bioelectronics, 24, 10, 30783083 (2009).10.1016/j.bios.2009.03.029Google Scholar
9. Chang, B. Y. and Park, S. M., Annu. Rev. Anal. Chem., 3, 207–29 (2010).10.1146/annurev.anchem.012809.102211Google Scholar
10. Lisdat, F. and Schafer, D., Anal. Bioanal. Chem., 391, 5, 1555–67 (2008).10.1007/s00216-008-1970-7Google Scholar
11. Zameer, A., Kasturirangan, S., Emadi, S., Nimmagadda, S. V. and Sierks, M. R., J. Mol. Biol., 384, 4, 917–28 (2008).10.1016/j.jmb.2008.09.068Google Scholar
12. Emadi, S., Kasturirangan, S., Wang, M. S., Schulz, P. and Sierks, M. R., J. Biol. Chem., 284, 17, 11048–58 (2009).10.1074/jbc.M806559200Google Scholar
13. Zhou, C., Emadi, S., Sierks, M. R. and Messer, A., Mol. Ther., 10, 6, 1023–31 (2004).10.1016/j.ymthe.2004.08.019Google Scholar