Computational Sensing of Staphylococcus aureus on Contact Lenses Using 3D Imaging of Curved Surfaces and Machine Learning.
Computational Sensing of Staphylococcus aureus on Contact Lenses Using 3D Imaging of Curved Surfaces and Machine Learning.
复制标题
使用曲面 3D 成像和机器学习对隐形眼镜上的金黄色葡萄球菌进行计算传感。
DOI：
10.1021/acsnano.7b08375
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发表时间：
2018
期刊：
影响因子：
17.1
通讯作者：
Ozcan,Aydogan
中科院分区：
文献类型：
--
作者：
Veli,Muhammed;Ozcan,Aydogan
我们提出了一种基于隐形眼镜的具有成本效益的便携式平台，用于非侵入性检测金黄色葡萄球菌，金黄色葡萄球菌是人类眼部微生物组的一部分，位于角膜和结膜上。使用S.金葡菌特异性抗体和与人类泪液相容的表面化学协议，隐形眼镜被设计为特异性捕获S。在细菌捕获在透镜上之后并且就在其成像之前，用表面官能化的聚苯乙烯微粒标记捕获的细菌。这些微珠提供了足够的信噪比，用于在接触透镜上定量捕获的细菌，而不需要任何荧光标记，通过仅使用一个用无透镜片上显微镜拍摄的全息图对每个透镜的曲面进行3D成像。在使用旋转场变换和全息数字聚焦计算重建接触透镜的3D表面之后，采用机器学习算法来自动计数透镜表面上的珠的数量，从而揭示捕获的细菌的计数。为了证明其概念验证，我们创建了一个现场便携式和具有成本效益的全息显微镜，重77 g，由笔记本电脑控制。使用掺有细菌的日常隐形眼镜，我们证明了这种计算传感平台提供的检测限为1016个细菌/μL。这种基于隐形眼镜的可穿戴传感器可以广泛应用于检测各种细菌，病毒和眼泪中的分析物，使用具有成本效益的便携式计算成像仪，甚至可以在家中使用。
We present a cost-effective and portable platform based on contact lenses for noninvasively detectingStaphylococcus aureus, which is part of the human ocular microbiome and resides on the cornea and conjunctiva. UsingS. aureus-specific antibodies and a surface chemistry protocol that is compatible with human tears, contact lenses are designed to specifically captureS. aureus.After the bacteria capture on the lens and right before its imaging, the captured bacteria are tagged with surface-functionalized polystyrene microparticles. These microbeads provide sufficient signal-to-noise ratio for the quantification of the captured bacteria on the contact lens, without any fluorescent labels, by 3D imaging of the curved surface of each lens using only one hologram taken with a lens-free on-chip microscope. After the 3D surface of the contact lens is computationally reconstructed using rotational field transformations and holographic digital focusing, a machine learning algorithm is employed to automatically count the number of beads on the lens surface, revealing the count of the captured bacteria. To demonstrate its proof-of-concept, we created a field-portable and cost-effective holographic microscope, which weighs 77 g, controlled by a laptop. Using daily contact lenses that are spiked with bacteria, we demonstrated that this computational sensing platform provides a detection limit of ∼16 bacteria/μL. This contact-lens-based wearable sensor can be broadly applicable to detect various bacteria, viruses, and analytes in tears using a cost-effective and portable computational imager that might be used even at home by consumers.