Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Electrical cell counting process characterization in a microfluidic impedance cytometer

Abstract

Particle counting in microfluidic devices with coulter principle finds many applications in health and medicine. Cell enumeration using microfluidic particle counters is fast and requires small volumes of sample, and is being used for disease diagnostics in humans and animals. A complete characterization of the cell counting process is critical for accurate cell counting especially in complex systems with samples of heterogeneous population interacting with different reagents in a microfluidic device. In this paper, we have characterized the electrical cell counting process using a microfluidic impedance cytometer. Erythrocytes were lysed on-chip from whole blood and the lysing was quenched to preserve leukocytes which subsequently pass through a 15 μm × 15 μm measurement channel used to electrically count the cells. We show that cell counting over time is a non-homogeneous Poisson process and that the electrical cell counts over time show the log-normal distribution, whose skewness can be attributed to diffusion of cells in the buffer that is used to meter the blood. We further found that the heterogeneous cell population (i.e. different cell types) shows different diffusion characteristics based on the cell size. Lymphocytes spatially diffuse more as compared to granulocytes and monocytes. The time difference between the cell occurrences follows an exponential distribution and when plotted over time verifies the cell diffusion characteristics. We also characterized the probability of occurrence of more than one cell at the counter within specified time intervals using Poisson counting statistics. For high cell concentration samples, we also derived the required sample dilution based on our particle counting characterization. Buffer characterization by considering the size based particle diffusion and estimating the required dilution are critical parameters for accurate counting results.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

References

  1. F. Arqueros, F. Blanco, B.J. Cisneros, Eur. J. Phys. 25, 399–407 (2004)

  2. C. Berkel, J.D. Gwyer, S. Deane, N. Green, J. Holloway, V. Hollis, H. Morgan, Lab. Chip. 11, 1249 (2011)

  3. K.C. Cheung, M.Di Berardino, G.S. Kampmann, M. Hebeisen, A. Pierzchalski, J. Bocsi, A. Mittag, A. Tarnok, Cytometry, Part A 77A, 648–666 (2010)

  4. W.H. Coulter, Means of counting particles suspended in a fluid. US (1953)

  5. R. DeBlois, R.K. Wesley, J. Virol. 23, 227–233 (1977)

  6. R.W. Glaser, Anal. Biochem. 213, 152–161 (1993)

  7. U. Hassan, N.N. Watkins, C. Edwards, R. Bashir, Lab. Chip. 14, 1469–1476 (2014)

  8. D. Holmes, H. Morgan, Anal. Chem. 82, 1455–1461 (2010)

  9. D. Holmes, D. Pettigrew, C. Reccius, J.D. Gwyer, C. Berkel, J. Holloway, D.E. Davies, H. Morgan, Lab. Chip. 9, 2881–2889 (2009)

  10. J.J. Kasianiwicz, E. Brandin, D. Branton, D.W. Dreamer, Proc. Natl. Acad. Sci. 93, 13770–13773 (1996)

  11. R. Kauffman, STLE 45, 147–153 (1989)

  12. J.F.C. Kingman, Poisson processes (Oxford University Press, New York, 1993)

  13. W.L. Leo, Techniques for nuclear and particle physics experiments (Springer, Berlin, 1994)

  14. L.W. Phipps, F.H.S. Newbould, J. Dairy Res. 33, 51–64 (1996)

  15. S.M. Ross, Simulation. (Academic Press, 2006).

  16. O.A. Saleh, L.L. Sohn, Proc. Natl. Acad. Sci. 100, 820–824 (2003)

  17. T. Sun, H. Morgan, Microfluid. Nanofluid. 8, 423–443 (2010)

  18. H.A. Teass, J. Byrnes, A. Valentine, Master Brewers Association of the Americas 35(2), 101–103 (1998).

  19. N.N. Watkins, S. Sridhar, X. Cheng, S.D. Chen, M. Toner, W. Rodriguez, R. Bashir, Lab. Chip. 11, 1437 (2011)

  20. N.N. Watkins, U. Hassan, G. Damhorst, H. Ni, H., A. Vaid, W. Rodriguez, R. Bashir, Sci. Trans. Med. 5, 214ra170 (2013).

  21. Z. Zhang, J. Zhe, S. Chandra, J. Hu, Atmos. Environ. 39, 5446–5453 (2005)

Download references

Acknowledgments

The authors would like to acknowledge the help of Gregory Damhorst for the blood draw from healthy human donors and Lara Orlandic for help in microfluidic device fabrication.

Funding

R. B. acknowledges the support of the NSF NSEC at OSU grant number EEC-0914790, and funding from the University of Illinois, Urbana-Champaign.

Author information

Correspondence to Rashid Bashir.

Electronic supplementary material

Below is the link to the electronic supplementary material.

MOESM1

(DOCX 140 kb).

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Hassan, U., Bashir, R. Electrical cell counting process characterization in a microfluidic impedance cytometer. Biomed Microdevices 16, 697–704 (2014). https://doi.org/10.1007/s10544-014-9874-0

Download citation

Keywords

  • Microfluidic impedance cytometer
  • Poisson statistics
  • Blood cell counting
  • Buffer characterization