Cranfield University , Advanced Diagnostics and Sensors Group, Cranfield, Bedford, MK43 0AL, United Kingdom.
Department of Biochemistry, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia , 43400 UPM Serdang, Selangor, Malaysia.
ACS Sens. 2018 Feb 23;3(2):418-424. doi: 10.1021/acssensors.7b00850. Epub 2018 Jan 26.
Food recalls due to undeclared allergens or contamination are costly to the food manufacturing industry worldwide. As the industry strives for better manufacturing efficiencies over a diverse range of food products, there is a need for the development of new analytical techniques to improve monitoring of the presence of unintended food allergens during the food manufacturing process. In particular, the monitoring of wash samples from cleaning in place systems (CIP), used in the cleaning of food processing equipment, would allow for the effective removal of allergen containing ingredients in between food batches. Casein proteins constitute the biggest group of proteins in milk and hence are the most common milk protein allergen in food ingredients. As such, these proteins could present an ideal analyte for cleaning validation. In this work, molecularly imprinted polymer nanoparticles (nanoMIPs) with high affinity toward bovine α-casein were synthesized using a solid-phase imprinting method. The nanoMIPs were then characterized and incorporated into label free surface plasmon resonance (SPR) based sensor. The nanoMIPs demonstrated good binding affinity and selectivity toward α-casein (K ∼ 10 × 10 M). This simple affinity sensor demonstrated the quantitative detection of α-casein achieving a detection limit of 127 ± 97.6 ng mL (0.127 ppm) which is far superior to existing commercially available ELISA kits. Recoveries from spiked CIP wastewater samples were within the acceptable range (87-120%). The reported sensor could allow food manufacturers to adequately monitor and manage food allergen risk in food processing environments while ensuring that the food produced is safe for the consumer.
由于未申报的过敏原或污染而导致的食品召回对全球食品制造业来说代价高昂。随着食品制造业在各种食品产品上追求更好的制造效率，需要开发新的分析技术来提高对食品加工过程中意外食品过敏原存在的监测。特别是，对就地清洗（CIP）系统清洁用冲洗样品的监测，可以有效地去除食品批次之间含过敏原的成分。酪蛋白是牛奶中最大的蛋白质组，因此是食品成分中最常见的牛奶蛋白过敏原。因此，这些蛋白质可以作为清洁验证的理想分析物。在这项工作中，使用固相印迹法合成了对牛α-酪蛋白具有高亲和力的分子印迹聚合物纳米颗粒（nanoMIPs）。然后对 nanoMIPs 进行了表征，并将其纳入无标记表面等离子体共振（SPR）基传感器中。nanoMIPs 对α-酪蛋白表现出良好的结合亲和力和选择性（K∼10×10M）。这种简单的亲和传感器实现了对α-酪蛋白的定量检测，检测限为 127±97.6ng/mL（0.127ppm），远优于现有的商业 ELISA 试剂盒。从加标 CIP 废水样品中的回收率在可接受范围内（87-120%）。所报道的传感器可以让食品制造商在确保生产的食品对消费者安全的同时，充分监测和管理食品加工环境中的过敏原风险。
