Future advances of artificial biosensor technology in biomedical applications

IF 4.1 Q1 CHEMISTRY, ANALYTICAL Talanta Open Pub Date : 2024-02-27 DOI:10.1016/j.talo.2024.100301
Smriti Gaba , Nidhi Chauhan , Ramesh Chandra , Utkarsh Jain
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Abstract

Recent advancements in synthetic biology have facilitated the concept of a cell-based and cell-free biosensing platform, which enables the identification of molecular signals encompassing metal/chemical to disease biomarkers. The artificial sensing incorporates the concept of both whole-cell and cell-free biosensing strategies, which include highly regulated natural and synthetic components to exhibit genetically encoded molecular sensing properties. These sensors utilize protein expression to release signalling molecules as the result of received input to facilitate the detection of analytes. Intending to use modified living cells or artificial cells in biosensing, the proposed study highlights the importance of cell-based and cell-free sensors in biomedical and diagnostics. The article's first section will explain the biosensing types including cell-free, cell-based, vesicle-based, and paper-based sensing where sensing relies on cell, cellular components, and cell-free systems which mostly involve transcriptional or translational machinery. It highlights the advantages, disadvantages, and challenges of advancing approaches. The second section of the article elaborates on the principle of sensing and the strategies involved. Though very few studies have been reported on this topic, therefore, the current article focuses on the artificial sensors that have been designed for medical and diagnostic purposes. The review also marks the current and future advancements in the field including artificial intelligence, nanotechnology, stem cells, and omics. Sensing recently has a big impact on disease diagnosis as well as drug development and targeted therapies. While newly developed biology-based diagnostics technologies still have high costs, require highly trained personnel, suffer stability issues and reduce sensor performance. Therefore, this review brings readers’ attention to advances and challenges in the following field and promotes the resolution of medical and diagnostics issues in the future.

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人工生物传感器技术在生物医学应用中的未来发展
合成生物学的最新进展促进了基于细胞和无细胞生物传感平台概念的发展,该平台能够识别从金属/化学到疾病生物标志物的分子信号。人工传感结合了全细胞和无细胞生物传感策略的概念,其中包括高度调节的天然和合成成分,以显示基因编码的分子传感特性。这些传感器利用蛋白质表达来释放信号分子,作为接收输入的结果,以促进分析物的检测。拟议的研究打算在生物传感中使用经修饰的活细胞或人工细胞,这凸显了基于细胞和无细胞传感器在生物医学和诊断学中的重要性。文章的第一部分将解释生物传感的类型,包括无细胞传感、细胞传感、囊泡传感和纸质传感,其中传感依赖于细胞、细胞成分和无细胞系统,这些系统大多涉及转录或翻译机制。文章强调了这些先进方法的优缺点和挑战。文章的第二部分阐述了传感原理和相关策略。虽然有关这一主题的研究报告很少,但本文重点讨论了为医疗和诊断目的而设计的人工传感器。综述还介绍了该领域当前和未来的进展,包括人工智能、纳米技术、干细胞和 Omics。最近,传感技术对疾病诊断、药物开发和靶向治疗产生了重大影响。然而,新开发的基于生物学的诊断技术仍存在成本高、需要训练有素的人员、稳定性问题以及传感器性能降低等问题。因此,这篇综述让读者关注以下领域的进展和挑战,促进未来医疗和诊断问题的解决。
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来源期刊
Talanta Open
Talanta Open Chemistry-Analytical Chemistry
CiteScore
5.20
自引率
0.00%
发文量
86
审稿时长
49 days
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