Universal sensor array for highly selective system identification using two-dimensional nanoparticles.
Universal sensor array for highly selective system identification using two-dimensional nanoparticles.
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DOI：
10.1039/c7sc01522d
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发表时间：
2017-08-01
期刊：
影响因子：
8.4
通讯作者：
Yigit MV
中科院分区：
文献类型：
--
作者：
Hizir MS;Robertson NM;Balcioglu M;Alp E;Rana M;Yigit MV
通用传感器阵列由12个荧光沉默的非特异性人工纳米受体（2D-nps）组成，用于识别和分类五种蛋白质，三种类型的乳腺癌细胞和大分子的结构转换事件。典型的锁和钥匙感测策略，仅依赖于探针和目标之间最主要的相互作用，可能过于局限。实际上，感应到的信息要丰富得多。由于各种分子间力的非特异性事件对整体接收到的信息有不同程度的贡献，并且当分析时，可以提供更强大的检测机会。在这里，我们已经组装了一个高度选择性的通用传感器阵列，使用水溶性的二维纳米粒子（nGO，MoS 2和WS 2）和荧光DNA分子。该阵列由12种荧光沉默的非特异性纳米受体（2D-nps）组成，用于识别三种完全不同的系统;五种蛋白质，三种类型的活乳腺癌细胞和一种大分子的结构转换事件。使用偏最小二乘（PLS）判别分析处理每个系统的数据矩阵。在所有系统中，传感器阵列都能够以95%的置信度将每个物体或事件识别为单独的集群，并且没有任何重叠。在测试的15个未知蛋白浓度的未知实体中，其中14个成功预测了正确的浓度。来自三种细胞类型的9个未知实体中的8个乳腺癌细胞样品被正确预测。在每个纳米探针的组装过程中，利用了未修饰的2D纳米颗粒和ssDNA之间的固有非共价相互作用。未修饰的2D材料在布局上提供了显着的简单性，并且ssDNA作为探针的使用提供了无限的可能性，因为ssDNA和2D表面的自然相互作用可以通过核碱基组成、寡核苷酸长度和2D纳米材料的类型进行微调。因此，这里描述的方法可以被无限期地推进和微调以满足特定的感测标准。虽然我们只研究了三个不同的元素，但这种方法具有足够的通用性，可以应用于广泛的系统。
The universal sensor array is composed of 12 fluorescently silent non-specific artificial nanoreceptors (2D-nps) for the identification and classification of five proteins, three types of breast cancer cells and a structure-switching event of a macromolecule. A typical lock-and-key sensing strategy, relying only on the most dominant interactions between the probe and target, could be too limiting. In reality, the information received upon sensing is much richer. Non-specific events due to various intermolecular forces contribute to the overall received information with different degrees, and when analyzed, could provide a much more powerful detection opportunity. Here, we have assembled a highly selective universal sensor array using water-soluble two-dimensional nanoparticles (nGO, MoS2 and WS2) and fluorescent DNA molecules. The array is composed of 12 fluorescently silent non-specific nanoreceptors (2D-nps) and used for the identification of three radically different systems; five proteins, three types of live breast cancer cells and a structure-switching event of a macromolecule. The data matrices for each system were processed using Partial Least Squares (PLS) discriminant analysis. In all of the systems, the sensor array was able to identify each object or event as separate clusters with 95% confidence and without any overlap. Out of 15 unknown entities with unknown protein concentrations tested, 14 of them were predicted successfully with correct concentration. 8 breast cancer cell samples out of 9 unknown entities from three cell types were predicted correctly. During the assembly of each nanoprobe, the intrinsic non-covalent interactions between unmodified 2D nanoparticles and ssDNAs were exploited. The unmodified 2D materials offer remarkable simplicity in the layout and the use of ssDNAs as probes provides limitless possibilities because the natural interaction of a ssDNA and 2D surface can be fine-tuned with the nucleobase composition, oligonucleotide length and type of 2D nanomaterial. Therefore, the approach described here can be advanced and fine-tuned indefinitely for meeting a particular sensing criterion. Though we have only studied three distinct elements, this approach is universal enough to be applied to a wide-range of systems.
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