Microchimica Acta

, 186:757 | Cite as

A microfluidic immunosensor for visual detection of foodborne bacteria using immunomagnetic separation, enzymatic catalysis and distance indication

  • Gaozhe Cai
  • Lingyan Zheng
  • Ming Liao
  • Yanbin Li
  • Maohua Wang
  • Ning Liu
  • Jianhan LinEmail author
Original Paper


A disposable visual microfluidic immunosensor is described for the determination of foodborne pathogens using immunomagnetic separation, enzymatic catalysis and distance indication. Specifically, a sensor was designed to detect Salmonella typhimurium as a model pathogen. Magnetic nanoparticles (MNPs) were modified with the anti-Salmonella monoclonal antibodies and then used to enrich S. typhimurium from the sample. This is followed by conjugation to polystyrene microspheres modified with anti-Salmonella polyclonal antibodies and catalase to form the MNP-bacteria-polystyrene-catalase sandwich. The catalase on the complexes catalyzes the decomposition of hydrogen peroxide to produce oxygen after passing a micromixer. The generated oxygen gas increases the pressure in the chip and pushes the indicating red dye solution to travel along the channel towards the unsealed outlet. The travel distance of the red dye can be visually read and related to the amount of S. typhimurium using the calibration scale. The sensor can detect as low as 150 CFU·mL−1 within 2 h.

Graphical abstract

Schematic representation of the distance-based microfluidic immunosensor for visual detection of foodborne bacteria using immunomagnetic nanoparticles for bacteria separation, catalase for decomposition of hydrogen peroxide to form oxygen which causes a pressure increase, and red dyed particles movement for distance indication.


Microfluidics Distance readout Pathogens detection Enzymatic catalysis Magnetic nanoparticles Polystyrene microspheres Catalase Hydrogen peroxide Chicken samples 



This study was supported in part National Natural Science Foundation of China (31802219) and Walmart Foundation (SA17031161). The authors would like to thank Walmart Food Safety Collaboration Center for its great support.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

604_2019_3883_MOESM1_ESM.docx (5.6 mb)
ESM 1 (DOCX 5711 kb)


  1. 1.
    Rubab M, Shahbaz HM, Olaimat AN, Oh D-H (2018) Biosensors for rapid and sensitive detection of Staphylococcus aureus in food. Biosens Bioelectron 105:49–57CrossRefGoogle Scholar
  2. 2.
  3. 3.
    Zhao X, Lin CW, Wang J, Oh DH (2014) Advances in rapid detection methods for foodborne pathogens. J Microbiol Biotechnol 24(3):297–312CrossRefGoogle Scholar
  4. 4.
    Mandal PK, Biswas AK, Choi K, Pal UK (2011) Methods for rapid detection of foodborne pathogens: an overview. Am J Food Technol 6(2):87–102CrossRefGoogle Scholar
  5. 5.
    Wang M, Yang J, Gai Z, Huo S, Zhu J, Li J, Wang R, Xing S, Shi G, Shi F, Zhang L (2017) Comparison between digital PCR and real-time PCR in detection of Salmonella typhimurium in milk. Int J Food Microbiol 266:251–256CrossRefGoogle Scholar
  6. 6.
    Mao Y, Huang X, Xiong S, Xu H, Aguilar ZP, Xiong Y (2016) Large-volume immunomagnetic separation combined with multiplex PCR assay for simultaneous detection of Listeria monocytogenes and Listeria ivanovii in lettuce. Food Control 59:601–608CrossRefGoogle Scholar
  7. 7.
    Kim J, Kim H, Park JH, Jon S (2017) Gold Nanorod-based photo-PCR system for one-step, rapid detection of Bacteria. Nanotheranostics 1(2):178–185CrossRefGoogle Scholar
  8. 8.
    Bennett RW (2005) Staphylococcal enterotoxin and its rapid identification in foods by enzyme-linked immunosorbent assay-based methodology. J Food Prot 68(6):1264CrossRefGoogle Scholar
  9. 9.
    Tu Z, Chen Q, Li Y, Xiong Y, Xu Y, Hu N, Tao Y (2016) Identification and characterization of species-specific nanobodies for the detection of Listeria monocytogenes in milk. Anal Biochem 493:1–7CrossRefGoogle Scholar
  10. 10.
    Ahmed A, Rushworth JV, Hirst NA, Millner PA (2014) Biosensors for whole-cell bacterial detection. Clin Microbiol Rev 27(3):631–646CrossRefGoogle Scholar
  11. 11.
    Magiati M, Sevastou A, Kalogianni DPJMA (2018) A fluorometric lateral flow assay for visual detection of nucleic acids using a digital camera readout. Microchim Acta 185(6):314CrossRefGoogle Scholar
  12. 12.
    Yoo SM, Lee SY (2016) Optical biosensors for the detection of pathogenic microorganisms. Trends Biotechnol 34(1):7–25CrossRefGoogle Scholar
  13. 13.
    Ramon-Marquez T, Medina-Castillo AL, Fernandez-Gutierrez A, Fernandez-Sanchez JF (2016) A novel optical biosensor for direct and selective determination of serotonin in serum by solid surface-room temperature phosphorescence. Biosens Bioelectron 82:217–223CrossRefGoogle Scholar
  14. 14.
    Pastucha M, Farka Z, Lacina K, Mikusova Z, Skladal P (2019) Magnetic nanoparticles for smart electrochemical immunoassays: a review on recent developments. Mikrochim Acta 186(5):312CrossRefGoogle Scholar
  15. 15.
    Nabaei V, Chandrawati R, Heidari H (2018) Magnetic biosensors: Modelling and simulation. Biosens Bioelectron 103:69–86CrossRefGoogle Scholar
  16. 16.
    Rong Z, Wang C, Wang J, Wang D, Xiao R, Wang S (2016) Magnetic immunoassay for cancer biomarker detection based on surface-enhanced resonance Raman scattering from coupled plasmonic nanostructures. Biosens Bioelectron 84:15CrossRefGoogle Scholar
  17. 17.
    Yuan M, Zhang Q, Song Z, Ye T, Yu J, Cao H, Xu F (2019) Piezoelectric arsenite aptasensor based on the use of a self-assembled mercaptoethylamine monolayer and gold nanoparticles. Microchim Acta 186(5):268CrossRefGoogle Scholar
  18. 18.
    Pohanka M (2018) Piezoelectric biosensor for the determination of tumor necrosis factor alpha. Talanta 178:970–973CrossRefGoogle Scholar
  19. 19.
    Chen Y, Chu W, Liu W, Guo X (2018) Distance-based carcinoembryonic antigen assay on microfluidic paper immunodevice. Sensors Actuators B Chem 260:452–459CrossRefGoogle Scholar
  20. 20.
    Tian T, Li J, Song Y, Zhou L, Zhu Z, Yang CJ (2016) Distance-based microfluidic quantitative detection methods for point-of-care testing. Lab Chip 16(7):1139–1151CrossRefGoogle Scholar
  21. 21.
    Wang Y, Zhu G, Qi W, Li Y, Song Y (2016) A versatile quantitation platform based on platinum nanoparticles incorporated volumetric bar-chart chip for highly sensitive assays. Biosens Bioelectron 85:777–784CrossRefGoogle Scholar
  22. 22.
    Xie Y, Wei X, Yang Q, Guan Z, Liu D, Liu X, Zhou L, Zhu Z, Lin Z, Yang C (2016) A Shake&Read distance-based microfluidic chip as a portable quantitative readout device for highly sensitive point-of-care testing. Chem Commun 52(91):13377–13380CrossRefGoogle Scholar
  23. 23.
    Liu D, Li X, Zhou J, Liu S, Tian T, Song Y, Zhu Z, Zhou L, Ji T, Yang C (2017) A fully integrated distance readout ELISA-Chip for point-of-care testing with sample-in-answer-out capability. Biosens Bioelectron 96:332–338CrossRefGoogle Scholar
  24. 24.
    Ansari MA, Kim K-Y, Anwar K, Kim SM (2010) A novel passive micromixer based on unbalanced splits and collisions of fluid streams. J Micromech Microeng 20(5):055007CrossRefGoogle Scholar
  25. 25.
    Chen Y, Xianyu Y, Wu J, Dong M, Zheng W, Sun J, Jiang X (2017) Double-enzymes-mediated bioluminescent sensor for quantitative and ultrasensitive point-of-care testing. Anal Chem 89(10):5422–5427CrossRefGoogle Scholar
  26. 26.
    Li J, Xia G, Li Y (2013) Numerical and experimental analyses of planar asymmetric split-and-recombine micromixer with dislocation sub-channels. J Chem Technol Biotechnol 88(9):1757–1765CrossRefGoogle Scholar
  27. 27.
    Dong J, Zhao H, Xu M, Ma Q, Ai S (2013) A label-free electrochemical impedance immunosensor based on AuNPs/PAMAM-MWCNT-chi nanocomposite modified glassy carbon electrode for detection of Salmonella typhimurium in milk. Food Chem 141(3):1980–1986CrossRefGoogle Scholar
  28. 28.
    Liu K, Yan X, Mao B, Wang S, Deng L (2015) Aptamer-based detection of Salmonella enteritidis using double signal amplification by Klenow fragment and dual fluorescence. Microchim Acta 183(2):643–649CrossRefGoogle Scholar
  29. 29.
    Lei P, Tang H, Ding S, Ding X, Zhu D, Shen B, Cheng Q, Yan Y (2014) Determination of the invA gene of Salmonella using surface plasmon resonance along with streptavidin aptamer amplification. Microchim Acta 182(1–2):289–296Google Scholar
  30. 30.
    Juronen D, Kuusk A, Kivirand K, Rinken A, Rinken T (2018) Immunosensing system for rapid multiplex detection of mastitis-causing pathogens in milk. Talanta 178:949–954CrossRefGoogle Scholar
  31. 31.
    Cheng Y, Xianyu Y, Wang Y, Zhang X, Cha R, Sun J, Jiang X (2015) One-step detection of pathogens and viruses: combining magnetic relaxation switching and magnetic separation. ACS Nano 9(3):3184–3191CrossRefGoogle Scholar
  32. 32.
    Liu CC, Yeung CY, Chen PH, Yeh MK, Hou SY (2013) Salmonella detection using 16S ribosomal DNA/RNA probe-gold nanoparticles and lateral flow immunoassay. Food Chem 141(3):2526–2532CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture and Rural AffairsChina Agricultural UniversityBeijingChina
  2. 2.Key Laboratory of Modern Precision Agriculture System Integration Research, Ministry of EducationChina Agricultural UniversityBeijingChina
  3. 3.College of Veterinary MedicineSouth China Agricultural UniversityGuangzhouChina
  4. 4.Department of Biological and Agricultural EngineeringUniversity of ArkansasFayettevilleUSA

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