Use of chemometrics to optimize a glucose assay on a paper microfluidic platform

Abstract

We describe the use of a chemometrics-based computational platform to optimize a glucose assay on a microfluidic paper-based analytical device (μPAD). Glucose is colorimetrically detected in the presence of glucose oxidase (GOx), horseradish peroxidase (HRP), and potassium iodide (KI). Using a Y-shaped paper microfluidic chip, the concentration of glucose, volume of reagents, and the length and width of the microfluidic channel were examined. The responses of the microfluidic chips were analyzed at the halfway point of the channel length. Variables affecting the response were screened by using a 24 factorial design, and among them, volume and concentration of the glucose were optimized by applying a rotatable central composite design (CCD). The optimum and experimental responses are 151.58 and 149.80, respectively, with an absolute error of 1.2%.

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Abbreviations

ANOVA:

Analysis of variance

GOx:

Glucose oxidase

HRP:

Horseradish peroxidase

LOC:

Lab-on-a chip

MD:

Microfluidic device

MEMS:

Microelectromechanical systems

POC:

Point-of-care

μPAD:

Microfluidic paper-based analytical device

References

  1. 1.

    Manz Z, Graber N, Widmer HM. Miniaturized total chemical analysis systems: a novel concept for chemical sensing. Sensor Actuat B Chem. 1990;1:244–8.

    CAS  Article  Google Scholar 

  2. 2.

    Whitesides GM. The origins and future of microfluidics. Nature. 2006;442:368–73.

    CAS  Article  Google Scholar 

  3. 3.

    Martinez AW, Phillips ST, Butte MJ, Whitesides GM. Patterned paper as a platform for inexpensive, low-volume, portable bioassays. Angew Chem Int Ed. 2007;46:1318–20.

    CAS  Article  Google Scholar 

  4. 4.

    Martinez AW, Phillips ST, Carrilho E, Thomas III SW, Sindi H, Whitesides GM. Simple telemedicine for developing regions: camera phones and paper-based microfluidic devices for real-time, off-site diagnosis. Anal Chem. 2008;80:3699–707.

    CAS  Article  Google Scholar 

  5. 5.

    Bruzewicz DA, Reches M, Whitesides GM. Low-cost printing of poly(dimethylsiloxane) barriers to define microchannels in paper. Anal Chem. 2008;80:3387–92.

    CAS  Article  Google Scholar 

  6. 6.

    Martinez AW, Phillips ST, Wiley BJ, Gupta M, Whitesides GM. FLASH: A rapid method for prototyping paper-based microfluidic devices. Lab Chip. 2008;8:2146–50.

    CAS  Article  Google Scholar 

  7. 7.

    Martinez AW, Phillips ST, Whitesides GM, Carrilho E. Diagnostics for the developing world: microfluidic paper-based analytical devices. Anal Chem. 2010;82:3–10.

    CAS  Article  Google Scholar 

  8. 8.

    Schilling KM, Lepore AL, Kurian JA, Martinez AW. Fully enclosed microfluidic paper-based analytical devices. Anal Chem. 2012;84:1579–85.

    CAS  Article  Google Scholar 

  9. 9.

    Cheng CM, Mazzeo AD, Gong JL, Martinez AW, Phillips ST, Jain N, et al. Millimeter-scale contact printing of aqueous solutions using a stamp made out of paper and tape. Lab Chip. 2010;10:3201–5.

    CAS  Article  Google Scholar 

  10. 10.

    Gomez FA. Paper microfluidics in bioanalysis. Bioanalysis. 2014;6:2911–4.

    CAS  Article  Google Scholar 

  11. 11.

    Nie J, Liang Y, Zhang Y, Shangwang L, Li D, Zhang S. One-step patterning of hollow microstructures in paper by laser cutting to create microfluidic analytical devices. Analyst. 2013;138:671–6.

    CAS  Article  Google Scholar 

  12. 12.

    Renault C, Koehne J, Ricco AJ, Crooks RM. Three-dimensional wax patterning of paper fluidic devices. Langmuir. 2014;30:7030–6.

    CAS  Article  Google Scholar 

  13. 13.

    Jang I, Song S. Facile and precise flow control for a paper-based microfluidic device through varying paper permeability. Lab Chip. 2015;15:3405–12.

    CAS  Article  Google Scholar 

  14. 14.

    Wang H, Li J, Wei J–F, Xu J–R, Wang Y–H, Zheng G–X. Paper-based three-dimensional microfluidic device for monitoring of heavy metals with a camera cell phone. Anal Bioanal Chem. 2014;406:2799–807.

    CAS  Article  Google Scholar 

  15. 15.

    Chitnis G, Ding ZW, Chang CL, Savranacde CA, Ziaiz B. Laser-treated hydrophobic paper: an inexpensive microfluidic platform. Lab Chip. 2011;11:1161–5.

    CAS  Article  Google Scholar 

  16. 16.

    Gomez FA. The future of microfluidic point-of-care diagnostic devices. Bioanalysis. 2013;5:1–3.

    CAS  Article  Google Scholar 

  17. 17.

    Weaver AA, Reiser H, Barstis T, Benvenuti M, Ghosh D, Hunckler M, et al. Paper analytical devices for fast field screening of beta lactam antibiotics and antituberculosis pharmaceuticals. Anal Chem. 2013;85:6453–60.

    CAS  Article  Google Scholar 

  18. 18.

    Wang P, Ge L, Ge S, Yu J, Yan M, Huang J. A paper-based photoelectrochemical immunoassay for low-cost and multiplexed point-of-care testing. Chem Comm. 2013;4:3294–6.

    Article  Google Scholar 

  19. 19.

    Rodriguez NM, Wong WS, Liu L, Dewar R, Klapperich CM. A fully integrated paperfluidic molecular diagnostic chip for the extraction, amplification, and detection of nucleic acids from clinical samples. Lab Chip. 2016;16:753–63.

    CAS  Article  Google Scholar 

  20. 20.

    Kim WS, Shin JH, Park HK, Choi S. A low-cost, monometallic, surface-enhanced raman scattering-functionalized paper platform for spot-on bioassays. Sensor Actuat B Chem. 2016;222:1112–8.

    CAS  Article  Google Scholar 

  21. 21.

    Arrastia M, Avoundjian A, Ehrlich PS, Eropkin M, Levine L, Gomez FA. Development of a microfluidic-based assay on a novel nitrocellulose platform. Electrophoresis. 2015;36:884–8.

    CAS  Article  Google Scholar 

  22. 22.

    Ferrer IM, Valadez H, Estala L, Gomez FA. Paper microfluidic-based enzyme catalyzed double microreactor. Electrophoresis. 2014;35:2417–9.

    CAS  Article  Google Scholar 

  23. 23.

    Zhang Y, Zuo P, Ye BC. A low-cost and simple paper-based microfluidic device for simultaneous multiplex determination of different types of chemical contaminants in food. Biosens Bioelectron. 2015;68:14–9.

    CAS  Article  Google Scholar 

  24. 24.

    Ueland M, Blanes L, Taudte RV, Stuart BH, Cole N, Willis P, et al. Capillary-driven microfluidic paper-based analytical devices for lab on a chip screening of explosive residues in soil. J Chromatogr A. 2016;1436:28–33.

    CAS  Article  Google Scholar 

  25. 25.

    Jin SQ, Guo SM, Zuo P, Ye BC. A cost-effective Z-folding controlled liquid handling microfluidic paper analysis device for pathogen detection via ATP quantification. Biosens Bioelectron. 2015;63:379–83.

    CAS  Article  Google Scholar 

  26. 26.

    Gonzalez A, Estala L, Gaines M, Gomez, FG. Mixed thread/paper-based microfluidic chips as a platform for glucose assays. Electrophoresis, 37;1685–1690.

  27. 27.

    Scampicchio M, Mannino S, Zima J, Wang J. Chemometrics on microchips: towards the classification of wines. Electroanalysis. 2005;17:1215–21.

    CAS  Article  Google Scholar 

  28. 28.

    Alvarado J, Hanrahan G, Nguyen HTH, Gomez FA. Implementation of a genetically tuned neural platform in optimizing fluorescence from receptor-ligand binding interactions on microchips. Electrophoresis. 2012;33:2711–7.

    CAS  Article  Google Scholar 

  29. 29.

    Tohid U, Pacheco-Vega A. IMECE 2013, November 15-21, 2013, San Diego, California, USA, P 1-14

  30. 30.

    Jalali-Heravi M, Arrastia M, Gomez FA. How can chemometrics improve microfluidic research? Anal Chem. 2015;87:3544–55.

    CAS  Article  Google Scholar 

  31. 31.

    Birnbaumer GM, Lieberzeit PA, Richtler L, Schirhagl R, Milnera M, Dickert FL, et al. Detection of viruses with molecularly imprinted polymers integrated on a microfluidic biochip using contact-less dielectric microsensors. Lab Chip. 2009;9:3549–56.

    CAS  Article  Google Scholar 

  32. 32.

    Dochow S, Beleite C, Henkel T, Mayer G, Albert J, Clement J, et al. Quartz microfluidic chip for tumour cell identification by Raman spectroscopy in combination with optical traps. Anal Bioanal Chem. 2013;405:2743–6.

    CAS  Article  Google Scholar 

  33. 33.

    Wlater A, Marz A, Schumacher W, Rosch P, Popp J. Towards a fast, high specific and reliable discrimination of bacteria on strain level by means of SERS in a microfluidic device. Lab Chip. 2011;11:1013–21.

    Article  Google Scholar 

  34. 34.

    Mariey L, Signolle JP, Amiel C, Travert J. Discrimination, classification, idenfication of microorganisms using FTIR spectroscopy and chemometrics. Vibrat Spectrosc. 2001;26:151–9.

    CAS  Article  Google Scholar 

  35. 35.

    Morgan E. Chemometrics: Experimental Design. London: Wiley; 1991.

    Google Scholar 

  36. 36.

    DC. Montgomery, Design and Analysis of Experiments, 5th ed., Wiley, New York, 2001.

  37. 37.

    Leardi R. Experimental design in chemistry: a tutorial. Anal Chim Acta. 2009;652:161–72.

    CAS  Article  Google Scholar 

  38. 38.

    Box GEP, Hunter WG, Hunter JS. An introduction to design, data analysis, and model building. New York: John Wiley; 1978.

    Google Scholar 

  39. 39.

    Massart DL, Vandeginste BGM, Buydens LMC, De Jongs S, Lewi PJ, Smeyers-Verbeke J. Handbook of chemometrics and qualimetrics: Part A. Amsterdam: Elsevier; 1997.

    Google Scholar 

  40. 40.

    Box GEP, Wilson KB. On the experimental attainment of optimum conditions. J Royal Statistical Society Series B. 1951;13:1–45.

    Google Scholar 

  41. 41.

    Myers RH. Response surface methodology, published by author Blacksburg VA, 1976.

  42. 42.

    Zhi W, Song J, Quyang FJ. Application of response surface methodology to the modeling of alpha-amylase purification by aqueous two-phase systems. Biotechnol. 2005;118:157–65.

    CAS  Google Scholar 

  43. 43.

    Kristo E, Biliaderis CG, Tzanetakis N. Modelling of the acidification process and rheological properties of milk fermented with a yogurt starter culture using response surface methodology. Food Chem. 2003;83:437–46.

    CAS  Article  Google Scholar 

  44. 44.

    Jalali-Heravi M, Parastar H, Ebrahimi-Najafabadi H. Characterization of volatile components of Iranian saffron using factorial-based response surface modeling of ultrasonic extraction combined with gas chromatography-mass spectrometry analysis. J Chromatogr A. 2009;1216:6088–97.

    CAS  Article  Google Scholar 

  45. 45.

    Bezerra MA, Santelli RE, Oliveira EP, Villar LS, Escaleira LA. Response surface methodology (RSM) as a tool for optimization in analytical chemistry. Talanta. 2008;76:965–77.

    CAS  Article  Google Scholar 

  46. 46.

    Dejaegher B, Vander Heyden YJ. Experimental designs and their recent advances in set-up, data interpretation, and analytical applications. Pharm Biomed Anal. 2011;56:141–58.

    CAS  Article  Google Scholar 

  47. 47.

    Dingstad G, Eglandsdal B, Naes T. Modeling methods for crossed mixture experiments-a case study from sausage production. Chemom Intell Lab Syst. 2003;66:175–90.

    CAS  Article  Google Scholar 

  48. 48.

    Dingstad G, Westad F, Naes T. Three case studies illustrating the properties of ordinary and partial least squares regression in different mixture models. Chemom Intell Lab Syst. 2004;71:33–45.

    CAS  Article  Google Scholar 

  49. 49.

    Awad ZK, Aravinthan T, Zhuge Y, Gonzalez F. A review of optimization techniques used in the design of fibre composite structures for civil engineering applications. Mater Des. 2012;24:375–9.

    Google Scholar 

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Acknowledgments

The authors gratefully acknowledge financial support for this research by grants from the National Science Foundation (HRD-0934146, EEC-0812348, IIA-1448166, and HRD-1547723), the W. M. Keck Foundation, and the La Kretz Foundation.

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Correspondence to Frank A. Gomez.

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The authors have no relevant affiliations or financial involvement with an organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. No writing assistance was utilized in the production of this manuscript.

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Avoundjian, A., Jalali-Heravi, M. & Gomez, F.A. Use of chemometrics to optimize a glucose assay on a paper microfluidic platform. Anal Bioanal Chem 409, 2697–2703 (2017). https://doi.org/10.1007/s00216-017-0214-0

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Keywords

  • Paper microfluidics
  • Chemometrics
  • Glucose oxidase
  • Point-of-care diagnostic device