School of Pharmacy, Shenyang Pharmaceutical University, Shenyang, 110016, China.
Department of Chemistry, Institute of Microanalytical Systems, Zhejiang University, Hangzhou, 310058, China.
Anal Chem. 2020 Jul 7;92(13):8759-8767. doi: 10.1021/acs.analchem.0c00007. Epub 2020 Jun 16.
The further miniaturization of liquid-phase microextraction (LPME) systems has important significance and major challenges for microscale sample analysis. Herein, we developed a rapid and flexible droplet-droplet microfluidic microextraction approach to perform nanoliter-scale miniaturized sample pretreatment, by combining droplet-based microfluidics, robotic liquid handling, and LPME techniques. Differing from the previous microextraction methods, both the extractant and sample volumes were decreased from the microliter scale or even milliliter scale to the nanoliter scale. We utilized the ability of a liquid-handling robot to manipulate nanoliter-scale droplets and micrometer-scale positioning to overcome the scaling effect difficulties in performing liquid-liquid extraction of nanoliter-volume samples in microsystems. Two microextraction modes, droplet-in-droplet microfluidic microextraction and droplet-on-droplet microfluidic microextraction, were developed according to the different solubility properties of the extractants. Various factors affecting the microextraction process were investigated, including the extraction time, recovery method of the extractant droplet, static and dynamic extraction mode, and cross-contamination. To demonstrate the validity and adaptability of the pretreatment and analysis of droplet samples with complex matrices, the present microextraction system coupled with MALDI-TOF mass spectrometry (MS) detection was applied to the quantitative determination of 7-ethyl-10-hydroxylcamptothecin (SN-38), an active metabolite of the anticancer drug irinotecan, in 800-nL droplets containing HepG2 cells. A linear relationship ( = 0.0305 + 0.376, = 0.984) was obtained in the range of 4-100 ng/mL, with the limits of detection and quantitation being 2.2 and 4.5 ng/mL for SN-38, respectively.
液相微萃取（LPME）系统的进一步微型化对微尺度样品分析具有重要意义和重大挑战。在此，我们通过结合基于液滴的微流控技术、机器人液体处理和 LPME 技术，开发了一种快速灵活的液滴-液滴微流控微萃取方法，以执行纳升级微型化样品预处理。与以前的微萃取方法不同，萃取剂和样品的体积都从微升到甚至毫升缩小到纳升。我们利用液体处理机器人操纵纳升级液滴和微米级定位的能力，克服了在微系统中进行纳升级样品液液萃取时的缩放效应困难。根据萃取剂的不同溶解度性质，开发了两种微萃取模式，即液滴内液滴微流控微萃取和液滴上液滴微流控微萃取。研究了影响微萃取过程的各种因素，包括萃取时间、萃取剂液滴的回收方法、静态和动态萃取模式以及交叉污染。为了证明具有复杂基质的液滴样品预处理和分析的有效性和适应性，本研究将微萃取系统与 MALDI-TOF 质谱（MS）检测相结合，应用于在含有 HepG2 细胞的 800-nL 液滴中定量测定抗癌药物伊立替康的活性代谢产物 7-乙基-10-羟基喜树碱（SN-38）。在 4-100ng/mL 的范围内，获得了线性关系（ = 0.0305 + 0.376， = 0.984），SN-38 的检出限和定量限分别为 2.2 和 4.5ng/mL。
