监督学习和质谱预测纳米材料的体内命运。,ACS Nano

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监督学习和质谱预测纳米材料的体内命运。
ACS Nano ( IF 15.8 ) Pub Date : 2019-06-21 00:00:00 , DOI: 10.1021/acsnano.9b02774
James Lazarovits _{1,

2} , Shrey Sindhwani _{1,

2} , Anthony J Tavares _{1,

2} , Yuwei Zhang _{1,

2} , Fayi Song _{1,

2} , Julie Audet _{1,

3} , Jonathan R Krieger ₄ , Abdullah Muhammad Syed _{1,

2} , Benjamin Stordy _{1,

2} , Warren C W Chan _{1,

2,

3,

5,

6}

Affiliation

静脉注射后，纳米颗粒的表面会立即发生变化，因为血液中的蛋白质会吸附在表面。该界面在循环过程中如何变化及其对体内纳米粒子分布的影响尚不清楚。在这里，我们开发了一个工作流程，以显示纳米颗粒表面上蛋白质的进化可预测纳米颗粒在体内的生物命运。。此工作流程涉及从循环中的多个时间点提取纳米粒子，从表面分离蛋白质并进行蛋白质组质谱。质谱蛋白质库用作输入，而血液清除率和器官积累用作输出，以训练可预测纳米粒子生物学命运的受监督的深度神经网络。在一项双盲研究中，我们通过预测纳米级脾脏和肝脏堆积的准确性高达94％来测试了该网络。我们的神经网络发现肝脏和脾脏摄取的机制是由于多种纳米颗粒表面吸附蛋白的模式所致。太多的组合无法使用化学或生物抑制剂来改变清除率，从而手动更改这些蛋白质。所以，我们开发了一种技术，该技术利用宿主作为生物反应器来制备具有可预测的清除模式的纳米颗粒，这些清除模式分别将肝脏和脾脏的摄取减少了50％和70％。这些技术不仅提供了预测纳米粒子行为的机会，而且还提供了对人体专门设计的表面化学进行工程改造的机会。

"点击查看英文标题和摘要"

Supervised Learning and Mass Spectrometry Predicts the in Vivo Fate of Nanomaterials.

The surface of nanoparticles changes immediately after intravenous injection because blood proteins adsorb on the surface. How this interface changes during circulation and its impact on nanoparticle distribution within the body is not understood. Here, we developed a workflow to show that the evolution of proteins on nanoparticle surfaces predicts the biological fate of nanoparticles in vivo. This workflow involves extracting nanoparticles at multiple time points from circulation, isolating the proteins off the surface and performing proteomic mass spectrometry. The mass spectrometry protein library served as inputs, while blood clearance and organ accumulation were used as outputs to train a supervised deep neural network that predicts nanoparticle biological fate. In a double-blinded study, we tested the network by predicting nanoparticle spleen and liver accumulation with upward of 94% accuracy. Our neural network discovered that the mechanism of liver and spleen uptake is due to patterns of a multitude of nanoparticle surface adsorbed proteins. There are too many combinations to change these proteins manually using chemical or biological inhibitors to alter clearance. Therefore, we developed a technique that uses the host to act as a bioreactor to prepare nanoparticles with predictable clearance patterns that reduce liver and spleen uptake by 50% and 70%, respectively. These techniques provide opportunities to both predict nanoparticle behavior and also to engineer surface chemistries that are specifically designed by the body.

更新日期：2019-06-21

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