Ludwig Susann K J, Zhu Hongying, Phillips Stephen, Shiledar Ashutosh, Feng Steve, Tseng Derek, van Ginkel Leendert A, Nielen Michel W F, Ozcan Aydogan
RIKILT Wageningen UR, P.O. Box 230, 6700 AE, Wageningen, The Netherlands.
Anal Bioanal Chem. 2014 Nov;406(27):6857-66. doi: 10.1007/s00216-014-7984-4. Epub 2014 Jun 28.
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.
目前，整个食物链中的污染物和残留监测是基于在专门的控制实验室进行采样、运输、处理和分析。这是一个效率极低且成本高昂的过程，因为通常超过99%的样本被认定为合格。现场简化预筛查可以提供一种方案，即仅将可疑样本运输并进一步处理。这种预筛查可以通过手机上的一个小附件来进行。为此，开发了一种基于手机的微球荧光免疫分析成像平台，用于检测牛奶提取物中抗重组牛生长激素（rbST）抗体的存在。给奶牛施用rbST可增加产奶量，但在欧盟是非法的，在美国则是一个公共卫生问题。手机监测抗rbST抗体（rbST生物标志物）的存在，这些抗体在施用rbST后内源性产生并随乳汁排出。牛奶提取物中存在的rbST生物标志物被共价偶联到顺磁性微球上的rbST捕获，并用量子点（QD）偶联的检测抗体进行标记。然后使用手机摄像头对这些捕获的量子点发出的荧光进行成像。此外，还拍摄了一张暗场图像，其中所有存在的微球都可见。使用在同一部手机上运行的定制安卓应用程序对荧光和暗场显微图像进行分析。通过这种设置，微球荧光免疫分析和基于手机的检测成功应用于来自经rbST处理和未处理奶牛的牛奶样本提取物。使用这种设置实现了80%的真阳性率和95%的真阴性率。接下来，将基于手机的检测平台与新开发的平面成像阵列替代品进行基准测试，发现其性能与更为复杂的替代品相当。在未来的残留监测中使用基于手机的现场分析可以在早期阶段就限制送往实验室分析的样本数量。由此，整个监测过程可以变得更加高效和经济。
