Dataset Information

Establishing lignin structure-upgradeability relationships using quantitative ¹H-¹³C heteronuclear single quantum coherence nuclear magnetic resonance (HSQC-NMR) spectroscopy.

ABSTRACT: Lignin depolymerization could provide an attractive renewable aromatic feedstock for the chemical industry. Past studies have suggested that lignin structural features such as ether content are correlated to lignin's upgradeability. An obstacle to the development of a conclusive causal relationship between lignin structure and upgradeability has been the difficulty to quantitatively measure lignin structural features. Here, we demonstrated that a modified HSQC-NMR method known as HSQC₀ can accurately quantify lignin functionalities in extracted lignin using several synthetic polymer models. We then prepared a range of isolated lignin samples with a wide range of ether contents (6-46%). By using a simple ether cleavage model, we were able to predict final depolymerization yields very accurately (<4% error), conclusively demonstrating the direct causal relationship between ether content and lignin activity. The accuracy of this model suggests that, unlike in native lignin, ether linkages no longer appear to be randomly distributed in isolated lignin.

SUBMITTER: Talebi Amiri M

PROVIDER: S-EPMC6836972 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Establishing lignin structure-upgradeability relationships using quantitative 1H-13C heteronuclear single quantum coherence nuclear magnetic resonance (HSQC-NMR) spectroscopy.

Talebi Amiri Masoud M Bertella Stefania S Questell-Santiago Ydna M YM Luterbacher Jeremy S JS

Chemical science 20190715 35

Lignin depolymerization could provide an attractive renewable aromatic feedstock for the chemical industry. Past studies have suggested that lignin structural features such as ether content are correlated to lignin's upgradeability. An obstacle to the development of a conclusive causal relationship between lignin structure and upgradeability has been the difficulty to quantitatively measure lignin structural features. Here, we demonstrated that a modified HSQC-NMR method known as HSQC0</sub ...[more]

PMID: 31857880

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Project description:Background: Metabolism is essential for cell survival and proliferation. A deep understanding of the metabolic network and its regulatory processes is often vital to understand and overcome disease. Stable isotope tracing of metabolism using nuclear magnetic resonance (NMR) and mass spectrometry (MS) is a powerful tool to derive mechanistic information of metabolic network activity. However, to retrieve meaningful information, automated tools are urgently needed to analyse these complex spectra and eliminate the bias introduced by manual analysis. Here, we present a data-driven algorithm to automatically annotate and analyse NMR signal multiplets in 2D- 1H, 13C-HSQC NMR spectra arising from 13C - 13C scalar couplings. The algorithm minimises the need for user input to guide the analysis of 2D- 1H, 13C-HSQC NMR spectra by performing automated peak picking and multiplet analysis. This enables non-NMR specialists to use this technology. The algorithm has been integrated into the existing MetaboLab software package. Methods: To evaluate the algorithm performance two criteria are tested: is the peak correctly annotated and secondly how confident is the algorithm with its analysis. For the latter a coefficient of determination is introduced. Three datasets were used for testing. The first was to test reproducibility with three biological replicates, the second tested the robustness of the algorithm for different amounts of scaling of the apparent J-coupling constants and the third focused on different sampling amounts. Results: The algorithm annotated overall >90% of NMR signals correctly with average coefficient of determination ρ of 94.06 ± 5.08%, 95.47 ± 7.20% and 80.47 ± 20.98% respectively. Conclusions: Our results indicate that the proposed algorithm accurately identifies and analyses NMR signal multiplets in ultra-high resolution 2D- 1H, 13C-HSQC NMR spectra. It is robust to signal splitting enhancement and up to 25% of non-uniform sampling.

Project description:Solar radiation has been regarded as a driver of litter decomposition in arid and semiarid ecosystems. Photodegradation of litter organic carbon (C) depends on chemical composition and water availability. However, the chemical changes in organic C that respond to solar radiation interacting with water pulses remain unknown. To explain changes in the chemical components of litter organic C exposed to UV-B, UV-A, and photosynthetically active radiation (PAR) mediated by water pulses, we measured the chemistry of marcescent Lindera glauca leaf litter by solid-state 13C cross-polarization magic angle spinning (CPMAS) nuclear magnetic resonance (NMR) over 494 days of litter decomposition with a microcosm experiment. Abiotic and biotic factors regulated litter decomposition via three pathways: first, photochemical mineralization of lignin methoxyl C rather than aromatic C exposed to UV radiation; second, the biological oxidation and leaching of cellulose O-alkyl C exposed to PAR and UV radiation interacts with water pulses; and third, the photopriming effect of UV radiation on lignin aromatic C rather than cellulose O-alkyl C under the interaction between radiation and water pulses. The robust decomposition index that explained the changes in the mass loss was the ratio of aromatic C to O-alkyl C (AR/OA) under radiation, but the ratio of hydrophobic to hydrophilic C (hydrophobicity), the carbohydrate C to methoxyl C ratio (CC/MC), and the alkyl C to O-alkyl C ratio (A/OA) under radiation were mediated by water pulses. Moreover, the photopriming effect and water availability promoted the potential activities of peroxidase and phenol oxidase associated with lignin degradation secreted by fungi. Our results suggest that direct photodegradation of lignin methoxyl C increases microbial accessibility to lignin aromatic C. Photo-oxidized compounds might be an additional C pool to regulate the stability of the soil C pool derived from plant litter by degrading lignin methoxyl and aromatic C.

Dataset Information

Establishing lignin structure-upgradeability relationships using quantitative ¹H-¹³C heteronuclear single quantum coherence nuclear magnetic resonance (HSQC-NMR) spectroscopy.

Publications

Establishing lignin structure-upgradeability relationships using quantitative <sup>1</sup>H-<sup>13</sup>C heteronuclear single quantum coherence nuclear magnetic resonance (HSQC-NMR) spectroscopy.

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