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Improved Extraction Repeatability and Spectral Reproducibility for Liquid Extraction Surface Analysis-Mass
Joris Meurs1, Morgan R Alexander1, Pavel A Levkin2,3
1Advanced Materials and Healthcare Technology Division, School of Pharmacy , University of Nottingham , University Park, Nottingham , NG7 2RD , United Kingdom.
Analytical Chemistry
|April 28, 2018
Summary
The Droplet Microarray (DMA) improves liquid extraction surface analysis (LESA) by confining solvents, enhancing data reproducibility. This surface-assisted LESA-MS method yields higher quality, more reliable results for various applications.
Area of Science:
- Analytical Chemistry
- Surface Science
- Biomolecular Analysis
Background:
- Reproducible analysis of dried liquid samples using liquid extraction surface analysis (LESA) is hindered by solvent spread.
- Uncontrolled solvent spread leads to unreliable data in LESA array sampling.
Purpose of the Study:
- To evaluate the Droplet Microarray (DMA) as a surface for LESA to improve sample confinement and extraction reproducibility.
- To compare LESA performance on DMA surfaces versus standard glass substrates for complex biological samples.
Main Methods:
- Investigated DMA surfaces with superhydrophilic spots and superhydrophobic borders for sample and solvent confinement.
- Performed LESA-MS analysis on a mixture of biologically relevant compounds and human urine samples.
- Compared LESA-MS data quality and reproducibility between DMA and glass substrates.
Main Results:
- Optimized DMA method significantly reduced relative standard deviations (at least 3-fold) in signal intensities compared to glass.
- Principal component analysis showed tighter clusters, indicating improved spectral reproducibility on DMA.
- Identified more significant ions (145) in human urine samples analyzed using LESA-MS on DMA surfaces.
Conclusions:
- DMA provides a surface-assisted LESA-MS method that significantly improves surface extraction repeatability.
- The DMA enables the acquisition of more robust, higher quality, and reproducible qualitative data.
- DMA shows potential for high-throughput, controlled, and reproducible surface extraction in LESA-MS applications.
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