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在经济高效的微流控芯片上进行自动化纳升体积分析优化

Automated Nanoliter Volume Assay Optimization on a Cost-Effective Microfluidic Disc.

作者信息

Nouwairi Renna L, Jones Carter K, Charette Maura E, Holmquist Emilee, Golabek Zoey, Landers James P

机构信息

Department of Chemistry, University of Virginia, Charlottesville, Virginia 22904, United States.

Department of Mechanical Engineering, University of Virginia, Charlottesville, Virginia 22904, United States.

出版信息

Anal Chem. 2025 Jan 14;97(1):300-311. doi: 10.1021/acs.analchem.4c04210. Epub 2024 Dec 28.

Abstract

Optimizing multireagent assays often requires successive titration of individual components until the optimal combination of conditions is achieved. This process is time-consuming, laborious, and often expensive since parallelized experimentation requires bulk consumption of reagents. Microfluidics presents a solution through miniaturization of standard processes by reducing reaction volume, executing multiple parallel workflows, and enabling automation. While single-digit microliter reactions can be effective, scaling to nanoliter volumes without employing droplets is difficult. We describe a cost-effective, customizable centrifugal microdisc for optimizing assays pertinent to a broad array of applications. An automated two-stage metering process leverages tunable, laser-actuated valves that retain defined fluidic volumes upon opening and meter discrete nanoliter volumes into downstream architecture. We demonstrate that ∼150 nL volumes could be metered and tuned for specific applications. We illustrate the potential for controlled metering of up to four reagents with high parallelization for rapid, cost-effective assay optimization with minimal manual intervention.

摘要

优化多试剂分析通常需要对各个组分进行连续滴定,直到达到最佳条件组合。这个过程既耗时又费力,而且往往成本高昂,因为并行实验需要大量消耗试剂。微流控技术通过缩小标准流程的规模,减少反应体积、执行多个并行工作流程并实现自动化,提供了一种解决方案。虽然单微升量级的反应可能有效,但在不使用液滴的情况下将反应体积缩小到纳升量级却很困难。我们描述了一种经济高效、可定制的离心微盘,用于优化与广泛应用相关的分析。一种自动化的两级计量过程利用了可调谐的激光驱动阀,这些阀在打开时能保持确定的流体体积,并将离散的纳升体积计量到下游结构中。我们证明,可以针对特定应用计量和调整约150纳升的体积。我们展示了对多达四种试剂进行可控计量的潜力,通过高度并行化实现快速、经济高效的分析优化,同时将人工干预降至最低。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ebd/11740179/622f64271cc7/ac4c04210_0001.jpg

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