Literature DB >> 24972876

Cellphone-based detection platform for rbST biomarker analysis in milk extracts using a microsphere fluorescence immunoassay.

Susann K J Ludwig1, Hongying Zhu, Stephen Phillips, Ashutosh Shiledar, Steve Feng, Derek Tseng, Leendert A van Ginkel, Michel W F Nielen, Aydogan Ozcan.   

Abstract

Current contaminant and residue monitoring throughout the food chain is based on sampling, transport, administration, and analysis in specialized control laboratories. This is a highly inefficient and costly process since typically more than 99% of the samples are found to be compliant. On-site simplified prescreening may provide a scenario in which only samples that are suspect are transported and further processed. Such a prescreening can be performed using a small attachment on a cellphone. To this end, a cellphone-based imaging platform for a microsphere fluorescence immunoassay that detects the presence of anti-recombinant bovine somatotropin (rbST) antibodies in milk extracts was developed. RbST administration to cows increases their milk production, but is illegal in the EU and a public health concern in the USA. The cellphone monitors the presence of anti-rbST antibodies (rbST biomarker), which are endogenously produced upon administration of rbST and excreted in milk. The rbST biomarker present in milk extracts was captured by rbST covalently coupled to paramagnetic microspheres and labeled by quantum dot (QD)-coupled detection antibodies. The emitted fluorescence light from these captured QDs was then imaged using the cellphone camera. Additionally, a dark-field image was taken in which all microspheres present were visible. The fluorescence and dark-field microimages were analyzed using a custom-developed Android application running on the same cellphone. With this setup, the microsphere fluorescence immunoassay and cellphone-based detection were successfully applied to milk sample extracts from rbST-treated and untreated cows. An 80% true-positive rate and 95% true-negative rate were achieved using this setup. Next, the cellphone-based detection platform was benchmarked against a newly developed planar imaging array alternative and found to be equally performing versus the much more sophisticated alternative. Using cellphone-based on-site analysis in future residue monitoring can limit the number of samples for laboratory analysis already at an early stage. Therewith, the entire monitoring process can become much more efficient and economical.

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Year:  2014        PMID: 24972876     DOI: 10.1007/s00216-014-7984-4

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  8 in total

1.  Enhanced light collection in fluorescence microscopy using self-assembled micro-reflectors.

Authors:  Zoltán Göröcs; Euan McLeod; Aydogan Ozcan
Journal:  Sci Rep       Date:  2015-06-17       Impact factor: 4.379

Review 2.  Smartphone-Based Food Diagnostic Technologies: A Review.

Authors:  Giovanni Rateni; Paolo Dario; Filippo Cavallo
Journal:  Sensors (Basel)       Date:  2017-06-20       Impact factor: 3.576

3.  The Efficiency of Color Space Channels to Quantify Color and Color Intensity Change in Liquids, pH Strips, and Lateral Flow Assays with Smartphones.

Authors:  Joost Laurus Dinant Nelis; Laszlo Bura; Yunfeng Zhao; Konstantin M Burkin; Karen Rafferty; Christopher T Elliott; Katrina Campbell
Journal:  Sensors (Basel)       Date:  2019-11-21       Impact factor: 3.576

Review 4.  Recent trends in smartphone-based detection for biomedical applications: a review.

Authors:  Soumyabrata Banik; Sindhoora Kaniyala Melanthota; Joel Markus Vaz; Vishak Madhwaraj Kadambalithaya; Iftak Hussain; Sibasish Dutta; Nirmal Mazumder
Journal:  Anal Bioanal Chem       Date:  2021-02-15       Impact factor: 4.142

5.  Smartphone-Based Quantitative Analysis of Protein Array Signals for Biomarker Detection in Lupus.

Authors:  Guang Yang; Yaxi Li; Chenling Tang; Feng Lin; Tianfu Wu; Jiming Bao
Journal:  Chemosensors (Basel)       Date:  2022-08-13

6.  Calling Biomarkers in Milk Using a Protein Microarray on Your Smartphone.

Authors:  Susann K J Ludwig; Christian Tokarski; Stefan N Lang; Leendert A van Ginkel; Hongying Zhu; Aydogan Ozcan; Michel W F Nielen
Journal:  PLoS One       Date:  2015-08-26       Impact factor: 3.240

Review 7.  Consumer-friendly food allergen detection: moving towards smartphone-based immunoassays.

Authors:  Georgina M S Ross; Monique G E G Bremer; Michel W F Nielen
Journal:  Anal Bioanal Chem       Date:  2018-03-26       Impact factor: 4.142

Review 8.  Nano-Biosensing Platforms for Detection of Cow's Milk Allergens: An Overview.

Authors:  Monika Nehra; Mariagrazia Lettieri; Neeraj Dilbaghi; Sandeep Kumar; Giovanna Marrazza
Journal:  Sensors (Basel)       Date:  2019-12-19       Impact factor: 3.576

  8 in total

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