Rapid fingerprinting of lignin by ambient ionization high resolution mass spectrometry and simplified data mining

Anal Chim Acta. 2017 Nov 22:994:38-48. doi: 10.1016/j.aca.2017.09.012. Epub 2017 Sep 13.

Abstract

Ambient ionization techniques are typically used to analyze samples in their native states with minimal or no sample pretreatment prior to mass spectrometric (MS) analysis. Desorption electrospray ionization (DESI) and direct analysis in real time (DART) were systematically investigated in this work for direct solid analysis of depolymerized lignin samples, with the goal of rapidly fingerprinting these samples, to efficiently characterize the subunits of this renewable energy source. High resolution MS was required for enhanced selectivity in this study due to the inherent structural complexity of lignin. DESI provided results across a broader mass range (up to m/z 700) than DART and also ionized saturated compounds of low oxygen-to-carbon (O/C) ratios and low double bond equivalents (DBE). While DART detected the same core lignin monomeric and dimeric compounds as seen with DESI and electrospray ionization (ESI), results were restricted to a narrower mass range to m/z 500, due to thermal degradation and losses of methoxy groups. In contrast to DESI and ESI, the DART spectra were nearly void of saturated components. On a structural level, the core lignin compounds were visually fingerprinted and ionization method performances critically assessed by employing simplified Kendrick-based data mining approaches. A novel simplified data visualization approach was developed in this work based on modified Kendrick mass defect (KMD) filtering for lignin subunits and plotting the mass defect values against the degree of unsaturation. Direct visualization of monomeric, dimeric and trimeric lignin species was simplified by the KMD separation plots, easily allowing the core lignin compounds to be visually identified and compared. Modified KMD bases, namely methoxy and phenol bases, which represent monomer-specific lignin constituents, were successfully used to classify and group the complex mixture of lignin species. Further separation of methoxy-related lignin species was successfully achieved by employing the more specific phenolic KMD base.

Keywords: Ambient ionization; High resolution mass spectrometry; Lignin characterization; Mass defect filtering; Sustainable chemistry.

MeSH terms

  • Data Mining*
  • Lignin / chemistry*
  • Spectrometry, Mass, Electrospray Ionization*

Substances

  • Lignin