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Adeno-associated virus characterization for cargo discrimination through nanopore responsiveness
Nanoscale ( IF 5.8 ) Pub Date : 2020-11-24 , DOI: 10.1039/d0nr05605g
Buddini Iroshika Karawdeniya 1 , Y M Nuwan D Y Bandara , Aminul Islam Khan , Wei Tong Chen , Hoang-Anh Vu , Adnan Morshed , Junghae Suh , Prashanta Dutta , Min Jun Kim
Affiliation  

Solid-state nanopore (SSN)-based analytical methods have found abundant use in genomics and proteomics with fledgling contributions to virology – a clinically critical field with emphasis on both infectious and designer-drug carriers. Here we demonstrate the ability of SSN to successfully discriminate adeno-associated viruses (AAVs) based on their genetic cargo [double-stranded DNA (AAVdsDNA), single-stranded DNA (AAVssDNA) or none (AAVempty)], devoid of digestion steps, through nanopore-induced electro-deformation (characterized by relative current change; ΔI/I0). The deformation order was found to be AAVempty > AAVssDNA > AAVdsDNA. A deep learning algorithm was developed by integrating support vector machine with an existing neural network, which successfully classified AAVs from SSN resistive-pulses (characteristic of genetic cargo) with >95% accuracy – a potential tool for clinical and biomedical applications. Subsequently, the presence of AAVempty in spiked AAVdsDNA was flagged using the ΔI/I0 distribution characteristics of the two types for mixtures composed of ∼75 : 25% and ∼40 : 60% (in concentration) AAVempty : AAVdsDNA.

中文翻译:

通过纳米孔响应性进行货物识别的腺相关病毒表征

基于固态纳米孔(SSN)的分析方法在基因组学和蛋白质组学中得到了广泛的应用,并对病毒学做出了初步贡献——病毒学是一个重点关注感染性和设计药物载体的临床关键领域。在这里,我们展示了 SSN 能够根据其遗传货物 [双链 DNA (AAV dsDNA )、单链 DNA (AAV ssDNA ) 或无 (AAV)] 成功区分腺相关病毒 (AAV),不含消化步骤,通过纳米孔诱导的电变形(以相对电流变化为特征;Δ I / I 0)。发现变形顺序为AAV>AAV ssDNA >AAV dsDNA。通过将支持向量机与现有神经网络集成开发了一种深度学习算法,该算法成功地从 SSN 电阻脉冲(遗传货物的特征)中对 AAV 进行了分类,准确率 >95%,是临床和生物医学应用的潜在工具。随后,使用由〜75:25%和〜40:60%(浓度)AAV空:AAV dsDNA组成的混合物的两种类型的ΔI / I 0分布特征来标记AAV dsDNAAAV存在。 
更新日期:2020-11-25
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