송우영 (광주과학기술원)

김태영 (광주과학기술원)

송우영 (광주과학기술원)

양유리 (강원대학교)

김태영 (광주과학기술원)

Lignin, a highly abundant natural aromatic polymer, offers significant potential as a renewable feedstock for valuable phenolic compounds (PCs). However, the presence of interfering substances, primarily lipids and carbohydrates, which constitute approximately 70% of biomass, poses a challenge in accurately characterizing lignin depolymerization products. This study introduces a novel post-run high-resolution mass defect filtering technique to isolate lignin-derived compounds from interfering substances.

We developed a high-resolution mass defect filter based on a nominal mass defect and multiple Kendrick mass defects, including the base CH₂ and three lignin monomeric units: H (C₉H₁₀O₂), G (C₁₀H₁₂O₃), and S (C₁₁H₁₄O₄). The filter was applied to three softwoods (G-type rich) and three hardwoods (S-type rich), effectively filtering out an average of 41% and 47% of total features for softwoods and hardwoods, respectively. MS/MS-based structural annotation revealed that the major chemical classes of mass defect filtered features included fatty acids, terpenoids, glycosides, and steroids. We highlight the importance of matching Kendrick mass defect types (H, G, and S monomers) to biomass types (softwood and hardwood) for optimal filtering accuracy of large oligomers. The generated list of filtered interferences can serve as an exclusion list for precursor ion selection, potentially enhancing lignin identification capabilities in LC-MS/MS analyses.