High-Resolution Droplet-Based Fractionation of Nano-LC Separations onto Microarrays for MALDI-MS Analysis

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• 作者：Simon K. K眉ster ; Martin Pabst ; Konstantins Jefimovs ; Renato Zenobi ; Petra S. Dittrich
• 刊名：Analytical Chemistry
• 出版年：2014
• 出版时间：May 20, 2014
• 年：2014
• 卷：86
• 期：10
• 页码：4848-4855
• 全文大小：328K
• 年卷期：v.86,no.10(May 20, 2014)
• ISSN：1520-6882

文摘

We present a robust droplet-based device, which enables the fractionation of ultralow flow rate nanoflow liquid chromatography (nano-LC) eluate streams at high frequencies and high peak resolution. This is achieved by directly interfacing the separation column to a micro T-junction, where the eluate stream is compartmentalized into picoliter droplets. This immediate compartmentalization prevents peak dispersion during eluate transport and conserves the chromatographic performance. Subsequently, nanoliter eluate fractions are collected at a rate of one fraction per second on a high-density microarray to retain the separation with high temporal resolution. Chromatographic separations of up to 45 min runtime can thus be archived on a single microarray possessing 2700 sample spots. The performance of this device is demonstrated by fractionating the separation of a tryptic digest of a known protein mixture onto the microarray chip and subsequently analyzing the sample archive using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). Resulting peak widths are found to be significantly reduced compared to standard continuous flow spotting technologies as well as in comparison to a conventional nano-LC-electrospray ionization-mass spectrometry interface. Moreover, we demonstrate the advantage of our high-definition nanofractionation device by applying two different MALDI matrices to all collected fractions in an alternating fashion. Since the information that is obtained from a MALDI-MS measurement depends on the choice of MALDI matrix, we can extract complementary information from neighboring spots containing almost identical composition but different matrices.