Machine Learning-Assisted Array-Based Detection of Proteins in Serum Using Functionalized MoS2 Nanosheets and Green Fluorescent Protein Conjugates
Machine Learning-Assisted Array-Based Detection of Proteins in Serum Using Functionalized MoS2 Nanosheets and Green Fluorescent Protein Conjugates
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DOI：
10.1021/acsanm.1c00244
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发表时间：
2021-04-02
影响因子：
5.9
通讯作者：
De, Mrinmoy
中科院分区：
文献类型：
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作者：
Behera, Pradipta;Singh, Krishna Kumar;De, Mrinmoy
特定蛋白质的异常浓度或某些生物标志物蛋白质的存在可能表明危及生命的疾病。利用亲和力调节受体对特定分析物进行基于模式的检测是基于特异性抗原-抗体的检测的潜在替代方案之一。在这份报告中，我们设计了一个传感器阵列，通过使用各种功能化的二维（2D）-二硫化钼纳米片和绿色荧光蛋白（GFP）作为受体和信号转导器，分别。二维二硫化钼已被用作一个有前途的候选人识别的生物分析物，因为它的高表面积与体积比相比，其他纳米材料。这种材料的容易的表面可调谐性为分析感兴趣的目标提供了额外的优势。优化的2D-MoS2-GFP缀合物能够在50 nM浓度下区分15种不同的蛋白质，检测限为1 nM。此外，蛋白质的二元混合物中，并在血清的存在下被成功地区分。对血清培养基中10种不同浓度的蛋白质进行了分类，折叶分类准确率为100%，证明了该系统的可行性。我们还实现并讨论了使用不同的机器学习模型对与基于阵列的传感相关的模式识别问题的影响。
Abnormal concentrations of a specific protein or the presence of some biomarker proteins may indicate life-threatening diseases. Pattern-based detection of specific analytes using affinity-regulated receptors is one of the potential alternatives to specific antigen-antibody-based detection. In this report, we have schemed a sensor array by using various functionalized two-dimensional (2D)-MoS2 nanosheets and green fluorescent protein (GFP) as the receptor and the signal transducer, respectively. Two-dimensional MoS2 has been used as a promising candidate for recognition of the bioanalytes because of its high surface-to-volume ratio compared to those of other nanomaterials. Easy surface tunability of this material provides additional advantages to analyze the target of interest. The optimized 2D-MoS2-GFP conjugates are able to discriminate 15 different proteins at 50 nM concentration with a detection limit of 1 nM. Moreover, proteins in the binary mixture and in the presence of serum were discriminated successfully. Ten different proteins in serum media at relevant concentrations were classified successfully with 100% jackknifed classification accuracy, which proves the potentiality of the above system. We have also implemented and discussed the implication of using different machine learning models on the pattern recognition problem associated with array-based sensing.