A powerful two-dimensional chromatography method for the non-target analysis of depolymerised lignin.

BACKGROUND: Lignin is an abundant natural polymer obtained as a by-product from the fractionation of lignocellulosic biomass. In the name of a circular economy, lignin should be valorised into valuable chemicals or biomaterials and utilised instead of petrochemicals. For the development of efficient valorisation processes, the structural characterisation of lignin can be highly beneficial. However, this is an arduous task, as the isolated (and sometimes processed) lignin mainly consists of various neutral monomers but also oligomers. In addition, the material contains isomers, which can be especially problematic to separate and identify. RESULTS: We present a powerful off-line comprehensive two-dimensional (2D) chromatography method combining liquid chromatography (LC), supercritical fluid chromatography (SFC), and high-resolution mass spectrometry for the non-target analysis of depolymerised lignin. The implementation of a 1-aminoanthracene column in the second dimension enabled a class separation of potential lignin monomers, dimers, trimers, and tetramers with an additional separation based on the number of hydroxyl groups and steric effects. The pentafluorophenyl column in the first dimension additionally improved the separation based on hydrophobicity. The comparison of off-line 2D LC × SFC to 1D SFC showed that besides the overall improved performance, the first method is also superior for the separation of isomers. Advanced data analysis methods (MS-DIAL, SIRIUS, and Feature-Based Molecular Network) were integrated into the non-target workflow to rapidly visualise and study the detected compounds, which proved to be especially beneficial for the characterisation of the separated isomers. SIGNIFICANCE: The method yielded the first 2D LC plot demonstrating a classification of lignin compounds, which can be applied to compare various lignin sources and processing methods. In addition, the technique demonstrated improved separation of compounds, including isomers, which was especially beneficial as 77 % of the detected compounds had at least one isomer in the same lignin sample.

Two-dimensional chromatography for the analysis of valorisable biowaste: A review.

Various everyday areas such as agriculture, wood industry, and wastewater treatment yield residual biowastes in large amounts that can be utilised for the purpose of sustainability and circular economy. Depending on the type of biowaste, they can be used to extract valuable chemicals or converted into alternative fuels. However, for efficient valorisation, these processes need to be monitored, for which thorough chemical characterisation can be highly beneficial. For this aim, two-dimensional (2D) chromatography can be favourable, as it has a higher peak capacity and sensitivity than one-dimensional (1D) chromatography. Therefore, here we review the studies published since 2010 involving gas chromatography (GC) or liquid chromatography (LC) as one of the dimensions. For the first time, we present the 2D chromatographic characterisation of various biowastes valorised for different purposes (chemical, fuels), together with future prospects and challenges. The aspects related to the 2D chromatographic analysis of polar, poorly volatile, and thermally unstable compounds are highlighted. In addition, it is demonstrated how different 2D setups can be applied for monitoring the biowaste conversion processes.

Genome-scale metabolic modeling reveals metabolic trade-offs associated with lipid production in Rhodotorula toruloides.

Rhodotorula toruloides is a non-conventional, oleaginous yeast able to naturally accumulate high amounts of microbial lipids. Constraint-based modeling of R. toruloides has been mainly focused on the comparison of experimentally measured and model predicted growth rates, while the intracellular flux patterns have been analyzed on a rather general level. Hence, the intrinsic metabolic properties of R. toruloides that make lipid synthesis possible are not thoroughly understood. At the same time, the lack of diverse physiological data sets has often been the bottleneck to predict accurate fluxes. In this study, we collected detailed physiology data sets of R. toruloides while growing on glucose, xylose, and acetate as the sole carbon source in chemically defined medium. Regardless of the carbon source, the growth was divided into two phases from which proteomic and lipidomic data were collected. Complemental physiological parameters were collected in these two phases and altogether implemented into metabolic models. Simulated intracellular flux patterns demonstrated the role of phosphoketolase in the generation of acetyl-CoA, one of the main precursors during lipid biosynthesis, while the role of ATP citrate lyase was not confirmed. Metabolic modeling on xylose as a carbon substrate was greatly improved by the detection of chirality of D-arabinitol, which together with D-ribulose were involved in an alternative xylose assimilation pathway. Further, flux patterns pointed to metabolic trade-offs associated with NADPH allocation between nitrogen assimilation and lipid biosynthetic pathways, which was linked to large-scale differences in protein and lipid content. This work includes the first extensive multi-condition analysis of R. toruloides using enzyme-constrained models and quantitative proteomics. Further, more precise kcat values should extend the application of the newly developed enzyme-constrained models that are publicly available for future studies.

Off-line two-dimensional separation involving supercritical fluid chromatography for the characterization of the wastewater from algae hydrothermal liquefaction.

An off-line multidimensional method involving liquid chromatography combined with supercritical fluid chromatography was developed for the characterization of the wastewater of hydrothermal liquefaction of microalgae Chlorella sorokiniana. The first dimension consisted of a phenyl hexyl column operated in reversed-phase mode, whereas the second dimension was performed on a diol stationary phase. Optimization of the kinetic parameters of the first and second dimensions were performed, taking into account the fraction collection system. The beneficial effect of working at high flow rate in both dimensions, as well as the need to work with short columns (50 mm) in the second dimension was evidenced. Injection volume was also optimized in both dimensions. The first dimension benefited from on-column focusing, while in the second dimension, untreated water-rich fractions could be injected without peak deformation. The performances of offline LCxSFC were compared to LC-HRMS, SFC-HRMS and LCxLC-HRMS for the analysis of the wastewater. Despite a long analysis time of 3.3h, the off-line separation coupled to high-resolution mass spectrometry exhibited a very large orthogonality with 75 % occupation rate of the separation space, reaching an effective peak capacity of 1050. While other evaluated techniques were faster, one-dimensional techniques failed to separate the numerous isomers while LCxLC exhibited lower orthogonality (45% occupation rate).

Quantitative GC-MS Analysis of Artificially Aged Paints with Variable Pigment and Linseed Oil Ratios.

In this study, quantitative gas chromatography-mass spectrometry (GC-MS) analysis was used to evaluate the influence of pigment concentration on the drying of oil paints. Seven sets of artificially aged self-made paints with different pigments (yellow ochre, red ochre, natural cinnabar, zinc white, Prussian blue, chrome oxide green, hematite + kaolinite) and linseed oil mixtures were analysed. In the pigment + linseed oil mixtures, linseed oil concentration varied in the range of 10 to 95 g/100 g. The results demonstrate that the commonly used palmitic acid to stearic acid ratio (P/S) to distinguish between drying oils varied in a vast range (from especially low 0.6 to a common 1.6) even though the paints contained the same linseed oil. Therefore, the P/S ratio is an unreliable parameter, and other criteria should be included for confirmation. The pigment concentration had a substantial effect on the values used to characterise the degree of drying (azelaic acid to palmitic acid ratio (A/P) and the relative content of dicarboxylic acids (∑D)). The absolute quantification showed that almost all oil paint mock-ups were influenced by pigment concentration. Therefore, pigment concentration needs to be considered as another factor when characterising oil-based paint samples based on the lipid profile.

Experimental and Computational Study of Aminoacridines as MALDI(-)-MS Matrix Materials for the Analysis of Complex Samples.

Monoaminoacridines (1-, 2-, 3-, 4-, and 9-aminoacridine) were studied for suitability as matrices in the negative ion mode matrix-assisted laser desorption/ionization mass spectrometry (MALDI(-)-MS) analysis of various samples. This is the first study to examine 1-, 2-, and 4-aminoacridine as potential matrix material candidates for MALDI(-)-MS. In addition, spectral (UV-Vis absorption and fluorescence), proton transfer-related (basicity and autoprotolysis), and crystallization properties of these compounds were characterized experimentally and/or computationally. For testing the capabilities of these aminoacridines as matrix materials, four samples related to cultural heritage materials-stearic acid, colophony resin, dyer's madder dye, and a resinous case-study sample from a shipwreck-were analyzed with MALDI(-)-MS. A novel algorithm (implemented as an executable Python script) for MS data analysis was developed to compare the five matrix materials and to help mass spectrometrists rapidly identify peaks originating from the sample and matrix material. It was determined that all five of the studied aminoacridines can successfully be used as matrix materials in MALDI(-)-MS analysis. As an interesting finding, in several cases, the best mass spectra were obtained by using a relatively small amount of matrix material mixed with an excess amount of sample. 3- and 4-aminoacridine outperformed the other aminoacridines in the ease of obtaining acceptable spectra, average number of ions identified in the mass spectra, and low dependence of the sample-to-matrix mass ratio on experimental results.

Uncertainty contribution of derivatization in gas chromatography/mass spectrometric analysis.

RATIONALE: The purpose of the current work is to realistically assess the uncertainty contribution in gas chromatography/mass spectrometry (GC/MS) analysis originating from less-than-ideal derivatization efficiency. METHODS: As the exemplary analytical method a two-step derivatization method with KOH and BSTFA (N,O-bis(trimethylsilyl)trifluoroacetamide), applied for the analysis of fatty acid triglycerides (using real measurement data), was selected. The derivatization efficiencies were in the range 0.89-1.04. In this study, two approaches for bottom-up uncertainty evaluation were compared: the traditional GUM approach and the Monte Carlo method (MCM). Both were used with and without taking correlation between input quantities into account. RESULTS: The most reliable uncertainty estimates were in the range 0.07-0.08 (expanded uncertainties at 95% coverage probability). A strong negative correlation was found between the slope and intercept of the calibration graph (r = -0.71) and it markedly influenced the uncertainty estimate of derivatization efficiency. The MCM was found to give somewhat higher uncertainty estimates, which are considered more realistic. CONCLUSIONS: Derivatization directly affects the analysis result. Thus, in the case of this exemplary analysis, just derivatization alone (i.e. if all other uncertainty sources are neglected) causes relative expanded uncertainty around 8%, being thus an important and in some cases the dominant uncertainty contributor.