论文标题

通过无镜头全息和深度学习对病毒牌匾的快速和无染色定量

Rapid and stain-free quantification of viral plaque via lens-free holography and deep learning

论文作者

Liu, Tairan, Li, Yuzhu, Koydemir, Hatice Ceylan, Zhang, Yijie, Yang, Ethan, Eryilmaz, Merve, Wang, Hongda, Li, Jingxi, Bai, Bijie, Ma, Guangdong, Ozcan, Aydogan

论文摘要

我们使用无透明全息成像和深度学习提出了快速且无染色的定量病毒斑块测定法。这种具有成本效益,紧凑和自动化的设备可显着减少传统斑块测定所需的孵化时间,同时保留其优于其他病毒定量方法的优势。该设备以每次测试井的对象捕获〜0.32 Giga像素/小时相位信息,以〜30x30 mm^2的面积以无标签的方式覆盖,完全消除了染色。我们证明了使用囊泡口腔炎病毒(VSV),单纯疱疹病毒(HSV-1)和脑膜炎病毒(EMCV)的成功方法。使用神经网络,这种无染色装置自动从温育后5小时自动检测到第一个细胞裂解事件,并在<20小时内以100%的特异性在<20个小时内获得100%的特异性,与传统的pla相比,至少需要48岁的488888。同样,此无污渍设备将所需的孵育时间降低了〜48小时,而HSV-1的EMCV降低了约20小时,以100%的特异性达到> 90%的检测率。我们还证明,该数据驱动的斑块测定法具有量化细胞单层感染区域的能力,在10倍大的病毒浓度范围内对PFU和病毒感染区域进行自动计数和定量,而不是标准病毒斑块分析。这种紧凑,低成本,自动化的PFU定量设备可以广泛用于病毒学研究,疫苗开发和临床应用中。

We present a rapid and stain-free quantitative viral plaque assay using lensfree holographic imaging and deep learning. This cost-effective, compact, and automated device significantly reduces the incubation time needed for traditional plaque assays while preserving their advantages over other virus quantification methods. This device captures ~0.32 Giga-pixel/hour phase information of the objects per test well, covering an area of ~30x30 mm^2, in a label-free manner, eliminating staining entirely. We demonstrated the success of this computational method using vesicular stomatitis virus (VSV), herpes simplex virus (HSV-1) and encephalomyocarditis virus (EMCV). Using a neural network, this stain-free device automatically detected the first cell lysing events due to the VSV viral replication as early as 5 hours after the incubation, and achieved >90% detection rate for the VSV plaque-forming units (PFUs) with 100% specificity in <20 hours, providing major time savings compared to the traditional plaque assays that take at least 48 hours. Similarly, this stain-free device reduced the needed incubation time by ~48 hours for HSV-1 and ~20 hours for EMCV, achieving >90% detection rate with 100% specificity. We also demonstrated that this data-driven plaque assay offers the capability of quantifying the infected area of the cell monolayer, performing automated counting and quantification of PFUs and virus-infected areas over a 10-fold larger dynamic range of virus concentration than standard viral plaque assays. This compact, low-cost, automated PFU quantification device can be broadly used in virology research, vaccine development, and clinical applications.

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