Modeling and Optimization Applied to the Design of Fast Hydrodynamic Focusing Microfluidic Mixer for Protein Folding

  • Benjamin Ivorra
  • María Crespo
  • Juana L. Redondo
  • Ángel M. Ramos
  • Pilar M. Ortigosa
  • Juan G. Santiago
Conference paper
Part of the Mathematics in Industry book series (MATHINDUSTRY, volume 26)

Abstract

In this paper, we are interested in the design of a microfluidic mixer based on hydrodynamic focusing which is used to initiate the folding process (i.e., changes of the molecular structure) of a protein by diluting a protein solution to decrease its denaturant concentration to a given value in a short time interval we refer to as mixing time. Our objective is to optimize this mixer by choosing suitable shape and flow conditions in order to minimize its mixing time. To this end, we first introduce a numerical model that enables computation of the mixing time of a considered mixer. Then, we define a mixer optimization problem and solve it using a hybrid global optimization algorithm.

Notes

Acknowledgements

This work was carried out thanks to the financial support of the “Spanish Ministry of Economy and Competitiveness” under projects MTM2011-22658 and MTM2015-64865-P; the “Junta de Andalucía” and the European Regional Development Fund through project P12-TIC301; and the research group MOMAT (Ref.910480) supported by “Banco Santander” and “Universidad Complutense de Madrid”.

References

  1. 1.
    Berg, J., Tymoczko, J., Stryer, L.: Biochemistry, 5th edn. W.H. Freeman, New York (2002)Google Scholar
  2. 2.
    Brody, J., Yager, B., Goldstein, R., Austin, R.: Biotechnology at low Reynolds numbers. Biophys. J. 71(6), 3430–3441 (1996)CrossRefGoogle Scholar
  3. 3.
    Hertzog, D., Michalet, X., Jäger, M., Kong, X., Santiago, J., Weiss, S., Bakajin, O.: Femtomole mixer for microsecond kinetic studies of protein folding. Anal. Chem. 76(24), 7169–7178 (2004)CrossRefGoogle Scholar
  4. 4.
    Hertzog, D., Ivorra, B., Mohammadi, B., Bakajin, O., Santiago, J.: Optimization of a microfluidic mixer for studying protein folding kinetics. Anal. Chem. 78(13), 4299–4306 (2006)CrossRefGoogle Scholar
  5. 5.
    Ivorra, B., Mohammadi, B., Santiago, J., Hertzog, D.: Semi-deterministic and genetic algorithms for global optimization of microfluidic protein folding devices. Int. J. Numer. Methods Eng. 66(2), 319–333 (2006)MathSciNetCrossRefMATHGoogle Scholar
  6. 6.
    Ivorra, B., Redondo, J.L., Santiago, J.G., Ortigosa, P.M., Ramos, A.M.: Two- and three-dimensional modeling and optimization applied to the design of a fast hydrodynamic focusing microfluidic mixer for protein folding. Phys. Fluids 25(3), 032001 (2013)CrossRefMATHGoogle Scholar
  7. 7.
    Ivorra, B., Mohammadi, B., Ramos, A.M.: A multi-layer line search method to improve the initialization of optimization algorithms. Eur. J. Oper. Res. 247(3), 711–720 (2015)MathSciNetCrossRefMATHGoogle Scholar
  8. 8.
    Ivorra, B., Redondo, J.L., Ramos, A.M., Santiago, J.G.: Design sensitivity and mixing uniformity of a micro-fluidic mixer. Phys. Fluids 28(1), 012005 (2016)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2017

Authors and Affiliations

  • Benjamin Ivorra
    • 1
  • María Crespo
    • 1
  • Juana L. Redondo
    • 2
  • Ángel M. Ramos
    • 1
  • Pilar M. Ortigosa
    • 2
  • Juan G. Santiago
    • 3
  1. 1.Instituto de Matemática Interdisciplinar (IMI) & Departamento de Matemática AplicadaUniversidad Complutense de MadridMadridSpain
  2. 2.Dpto. de Arquitectura de Computadores y ElectrónicaUniversidad de Almeria, ceiA3,Ctra. SacramentoAlmeríaSpain
  3. 3.Mechanical Engineering DepartmentStanford UniversityStanfordUSA

Personalised recommendations