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超高通量吸光式液滴分选技术在千赫兹频率下进行酶筛选。

Ultra-High-Throughput Absorbance-Activated Droplet Sorting for Enzyme Screening at Kilohertz Frequencies.

机构信息

Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, CB2 1GA Cambridge, United Kingdom.

Department of Molecular Biology, Institute of Biochemistry, Faculty of Biology, University of Warsaw, Miecznikowa 1, 02-096 Warsaw, Poland.

出版信息

Anal Chem. 2023 Mar 14;95(10):4597-4604. doi: 10.1021/acs.analchem.2c04144. Epub 2023 Feb 27.

Abstract

Droplet microfluidics is a valuable method to "beat the odds" in high throughput screening campaigns such as directed evolution, where valuable hits are infrequent and large library sizes are required. Absorbance-based sorting expands the range of enzyme families that can be subjected to droplet screening by expanding possible assays beyond fluorescence detection. However, absorbance-activated droplet sorting (AADS) is currently ∼10-fold slower than typical fluorescence-activated droplet sorting (FADS), meaning that, in comparison, a larger portion of sequence space is inaccessible due to throughput constraints. Here we improve AADS to reach kHz sorting speeds in an order of magnitude increase over previous designs, with close-to-ideal sorting accuracy. This is achieved by a combination of (i) the use of refractive index matching oil that improves signal quality by removal of side scattering (increasing the sensitivity of absorbance measurements); (ii) a sorting algorithm capable of sorting at this increased frequency with an Arduino Due; and (iii) a chip design that transmits product detection better into sorting decisions without false positives, namely a single-layered inlet to space droplets further apart and injections of "bias oil" providing a fluidic barrier preventing droplets from entering the incorrect sorting channel. The updated ultra-high-throughput absorbance-activated droplet sorter increases the effective sensitivity of absorbance measurements through better signal quality at a speed that matches the more established fluorescence-activated sorting devices.

摘要

液滴微流控技术是一种在高通量筛选(如定向进化)中“反败为胜”的有效方法,在高通量筛选中,有价值的命中事件很少,且需要较大的文库规模。基于吸光度的分选通过将可能的测定法扩展到荧光检测之外,从而扩展了可以进行液滴筛选的酶家族范围。然而,吸光度激活的液滴分选(AADS)的速度比典型的荧光激活的液滴分选(FADS)慢约 10 倍,这意味着,由于通量的限制,与后者相比,更大一部分的序列空间无法访问。在这里,我们通过组合使用折射率匹配油来提高 AADS 的速度,使其在之前的设计基础上提高了一个数量级,达到了 kHz 的分选速度,同时保持了接近理想的分选精度。这是通过以下三种方法实现的:(i)使用折射率匹配油,通过去除侧散射来提高信号质量(提高吸光度测量的灵敏度);(ii)一种能够以这种增加的频率进行分选的排序算法,该算法由 Arduino Due 实现;(iii)一种芯片设计,通过在没有假阳性的情况下更好地将产物检测传输到分选决策中,即采用单层入口来进一步分离液滴,并注入“偏置油”,形成一个流体屏障,防止液滴进入错误的分选通道。更新后的超高速吸光激活液滴分选器通过更好的信号质量提高了吸光度测量的有效灵敏度,其速度与更成熟的荧光激活分选设备相匹配。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0986/10018449/aed5778c3620/ac2c04144_0001.jpg

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