Monolithic Silica Microbands Enable Thin-Layer Chromatography Analysis of Single Cells.

Monolithic Silica Microbands Enable Thin-Layer Chromatography Analysis of Single Cells.
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DOI:
10.1021/acs.analchem.2c02622
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发表时间:
2022-10-04
影响因子:
7.4
通讯作者:
Allbritton, Nancy L.
Allbritton, Nancy L.
中科院分区:
化学1区
文献类型:
--
作者:
Wang, Yuli;Yao, Ming;Sims, Christopher E.;Allbritton, Nancy L.

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A picoliter thin layer chromatography (pTLC) platform was developed for analyzing extremely miniature specimens, such as assay of the contents of a single cell of 1 picoliter volume. The pTLC chip consisted of an array of microscale bands made from highly porous monolithic silica designed to accept picoliter-scale volume samples. pTLC bands were fabricated by combining sol-gel chemistry and microfabrication technology. The width (60–80 μm) and depth (13 μm) of each band is comparable to the size of single cells and acted to reduce the lateral diffusion and confine the movement of compounds along the microbands. Ultra-small volumes (tens of pL) of model fluorescent compounds were spotted onto the microband by a piezoelectric microdispenser and successfully separated by pTLC. The separation resolution and analyte migration were dependent on the macropore size (ranging from 0.3 to 2.3 μm) which was adjustable by changing the porogen concentration during the sol-gel process. For a 0.3 μm macropore size, attomoles of analyte were detectable by fluorescence using standard microscopy methods. The separation resolution, theoretical plate number and separation times ranged from 1.3–2.1, 4–357, and 2–8 min, respectively for the chosen model biological lipids. To demonstrate the capability of pTLC for separating analytes from single mammalian cells, cells loaded with fluorescent lipophilic dyes or sphingosine kinase reporter were spotted on microbands, and the single-cell contents separated by pTLC were detected from their fluorescence. These results demonstrate the potential of pTLC for applications in many areas where miniature specimens and high throughput parallel analyses are needed.
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