Cell-based biosensors: Recent trends, challenges and future perspectives

纳米技术 生物传感器 灵活性(工程) 计算机科学 微流控 生化工程 材料科学 工程类 数学 统计
作者
Niharika Gupta,V. Renugopalakrishnan,Dorian Liepmann,Ramasamy Paulmurugan,Bansi D. Malhotra
出处
期刊:Biosensors and Bioelectronics [Elsevier]
卷期号:141: 111435-111435 被引量:199
标识
DOI:10.1016/j.bios.2019.111435
摘要

Existing at the interface of biology and electronics, living cells have been in use as biorecognition elements (bioreceptors) in biosensors since the early 1970s. They are an interesting choice of bioreceptors as they allow flexibility in determining the sensing strategy, are cheaper than purified enzymes and antibodies and make the fabrication relatively simple and cost-effective. And with advances in the field of synthetic biology, microfluidics and lithography, many exciting developments have been made in the design of cell-based biosensors in the last about five years. 3D cell culture systems integrated with electrodes are now providing new insights into disease pathogenesis and physiology, while cardiomyocyte-integrated microelectrode array (MEA) technology is set to be standardized for the assessment of drug-induced cardiac toxicity. From cell microarrays for high-throughput applications to plasmonic devices for anti-microbial susceptibility testing and advent of microbial fuel cell biosensors, cell-based biosensors have evolved from being mere tools for detection of specific analytes to multi-parametric devices for real time monitoring and assessment. However, despite these advancements, challenges such as regeneration and storage life, heterogeneity in cell populations, high interference and high costs due to accessory instrumentation need to be addressed before the full potential of cell-based biosensors can be realized at a larger scale. This review summarizes results of the studies that have been conducted in the last five years toward the fabrication of cell-based biosensors for different applications with a comprehensive discussion on the challenges, future trends, and potential inputs needed for improving them.
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