Comparison of Methodologies Used to Determine Monolignol Ratios in Lignocellulosic Biomass

Abstract

BackgroundMultiple analytical methods have been developed to determine the ratios of monolignol monomers, particularly the syringyl/guaiacyl (S/G) ratio, of lignin biopolymers in plant cell walls. Chemical degradation methods yield monomers that are either selective of certain linkages, such as thioacidolysis, or induce chemical changes rendering it impossible to distinguish and determine the source of specific monomers, such as nitrobenzene oxidation. NMR methods provide powerful tools used to analyze cell walls for lignin monomeric composition and linkage information. Pyrolysis-mass spectrometry methods are also widely used, particularly as a high-throughput method. However, the different techniques used to analyze lignin monolignol ratios frequently yield different results within particular studies, making it difficult to interpret and compare results, and to obtain meaningful insights relating these measurements to other characteristics of plant cell walls that may impact biomass sustainability and conversion metrics for the production of bio-derived fuels and chemicals.ResultsThe authors compared the S/G monolignol ratios of pine, several genotypes of poplar, and corn stover biomass obtained from thioacidolysis, pyrolysis-molecular beam mass spectrometry (py-MBMS), HSQC liquid-state NMR and solid-state (ss) NMR methodologies. An underutilized approach to deconvolute ssNMR spectra was implemented to derive S/G ratios. The S/G ratios obtained for the samples did not agree across the different methods, but trends were similar with the most agreement among the py-MBMS, HSQC NMR and deconvoluted ssNMR methods. The relationship between monolignol S/G, thioacidolysis yields, and linkage analysis determined by HSQC is also addressed.ConclusionsThis work demonstrates that different methods using chemical, thermal, and nondestructive NMR techniques to determine native monolignol S/G ratios in plant cell walls may yield different results depending on species and linkage abundances. Spectral deconvolution likely applies well to many hardwoods that are S and G dominant, but results may not be reliable for some woody and grassy species for which the lignin composition is more diverse. HSQC may be a better method for analyzing lignin in those species given the wealth of information provided on additional aromatic moieties and bond linkages. Careful consideration is required when choosing a method to measure S/G ratios and the benefits and shortcomings of each method discussed here are summarized.