Integrated Nano-Opto-Fluidic System on Sapphire towards Single-Molecule Protein Sequencing

项目总结/摘要 通过高通量、低成本的核酸测序技术的发展， 在过去的二十年里，基因组学和转录组学的发展加速，深刻地重塑了 我们的生物学和医学知识。然而，用于快速识别的类似技术尚未出现 和蛋白质的定量。这是由于蛋白质结构复杂，缺乏聚合酶链 反应样扩增方法、细胞异质性等。 如Edman降解和质谱法，是缓慢的，昂贵的，不适合检测低- 蛋白质丰度这样的集合测量也可以掩盖我们对如何 特定基因型的细胞发挥功能并对治疗剂作出反应。单分子蛋白质测序（SMPS） 直接从单个蛋白质或肽中读取氨基酸序列是一个新兴的研究方向 分子。然而，使用荧光测序的有希望的策略仍然依赖于长的Edman降解循环， 体积庞大的荧光显微镜，不适合快速和低成本的读出。电子开关电源技术， 隧道或纳米孔传感器是用于开发便携式和廉价测序的新兴方法 系统.然而，它们仍然面临着精确的纳米纤维，结构不稳定性，高电子 噪声和不能检测所有氨基酸。为了应对下一代的多方面挑战， SMPS，我们将设计一个片上集成的电子系统，该系统采用纳米光流体结构， 将蛋白质指纹转化为电子信号，速度快，成本低，系统占地面积小。 我们的平台具有全蓝宝石纳米孔（AlSaPore）流体装置，其具有小电容和 大大提高了结构稳定性，因此适用于高速、低噪声、高吞吐量、电子 侦测此外，基于氮化镓的超表面集成电路（MIC）结构被创建在半导体衬底上。 AlSaPore光学询问通过纳米孔的荧光标记的单个氨基酸 而不需要传统的荧光显微镜。随后，荧光标签信号通过 波导并由片上集成光电探测器收集。光电通道（IA代表氨基酸 标签）和离子电流通道（IP用于蛋白质一级结构）将被同步记录，分类为 深度学习算法，并结合使用，以提高蛋白质测序的准确性。支持 我们的MIC-AlSaPore是一种成熟的蓝宝石氮化物器件设计和制造技术， 可扩展的紧凑型平台，可实现单分子灵敏度，并有可能读出所有20个氨基酸 acids. MIC-AlSaPore平台的开发将在蛋白质以外的生物医学领域产生深远影响 测序它可用于在单分子水平上研究DNA-蛋白质相互作用， 特定基因、基因组作图和从头组装。此外，它可能会激发未来的多组学（基因组， 转录组学和蛋白质组学）诊断解决方案，具有潜在的临床应用。

PROJECT SUMMARY/ ABSTRACT Enabled by the development of high-throughput, low-cost nucleic acids sequencing technologies, there have been accelerated development in genomics and transcriptomics in the past two decades, profoundly reshaping our knowledge in biology and medicine. However, similar technologies have yet to emerge for rapid identification and quantification of proteins. This is attributed to more complex structures of proteins, lack of polymerase chain reaction-like amplification methods, cellular heterogeneity, etc. Conventional protein sequencing methods, such as Edman degradation and mass spectrometry, are slow, expensive, and not suitable for detecting low- abundance proteins. Such ensemble measurements also can mask our fundamental understandings on how cells of a particular genotype function and respond to therapeutics. Single-molecule protein sequencing (SMPS) is an emerging research direction that directly reads amino acids sequence from individual protein or peptide molecules. Yet, a promising strategy using fluorosequencing still relies on long Edman degradation cycles and bulky fluorescent microscopes, not ideal for fast and low-cost readout. Electronic SMPS technologies using tunneling or nanopore sensors are emerging methods for development of portable and inexpensive sequencing systems. However, they still face challenges in precise nanofabrication, structural instability, high electronic noise, and inability in detection of all amino acids. To address the multi-faceted challenges in next-generation SMPS, we will design an on-chip integrated, electronic system that incorporates nano-opto-fluidic structures to transduce protein fingerprints into electronic signals at a high speed, a low cost and a small system foot-print. Our platform features an all-sapphire nanopore (AlSaPore) fluidic device that has a small capacitance and a greatly improved structural stability, and accordingly suited for high-speed, low-noise, high-throughput, electronic detection. Further, an ultrathin nitride-based metasurface-integrated circuit (MIC) structure is created on the AlSaPore to optically interrogate the fluorescently tagged single amino acids passing through the nanopore without conventional fluorescent microscopy. Subsequently, the fluorescent tag signals are transmitted through the waveguide and collected by on-chip integrated photodetectors. The optoelectronic channel (IA for amino acids tags) and ionic current channel (IP for protein primary structure) will be synchronously recorded, classified by deep learning algorithms, and used in combination to improve the protein sequencing accuracy. Supported by well-established nitride-on-sapphire device design and manufacturing technology, our MIC-AlSaPore is a scalable and compact platform that achieves single-molecule sensitivity with a potential to read out all 20 amino acids. The development of MIC-AlSaPore platform will have far-reaching impact in biomedicine beyond protein sequencing. It may be used for studying DNA-protein interactions at single-molecule levels, classification of specific genes, genome mapping and de novo assembly. Additionally, it may inspire future multi-omic (genomic, transcriptomic, and proteomic) diagnostic solutions with potential clinical applications.