Dynamic Nuclear Polarization NMR as a new tool to investigate the nature of organic compounds occluded in plant silica particles

Abstract : The determination of the chemical nature of the organic matter associated with phytoliths remains a challenge. This difficulty mainly stems from amounts of organic carbon (C) that are often well below the detection limit of traditional spectroscopic tools. Conventional solid-state 13 C Nuclear Magnetic Resonance (NMR) is widely used to examine the nature and structure of organic molecules, but its inherent low sensitivity prohibits the observation of diluted samples. The recent advent of commercial microwave source in the terahertz range triggered a renewed interest in the Dynamic Nuclear Polarization (DNP) technique to improve the signal to noise ratio of solid-state NMR experiments. With this technique, the 13 C spectrum of a phytolith sample containing 0.1% w/w C was obtained overnight with sufficient quality to permit a semi-quantitative analysis of the organic matter, showing the presence of peptides and carbohydrates as predominant compounds. Considering the natural abundance of the 13 C isotope, this experiment demonstrates that DNP NMR is sufficiently sensitive to observe spin systems present in amounts as low as a few tens of ppm. The molecular analysis of natural organic matter in organisms, soils or sediments is a challenging field for our understanding of the processes involved in the carbon cycle. Among the many challenges to be met is the difficulty in obtaining a quantitative or semi-quantitative speciation of the organic carbon, with the least possible preparation steps. Indeed, several chemical steps are often required to purify the molecular compounds to be analyzed , from the minerals they are associated with 1-3. Unfortunately these steps can modify the molecular nature of the compounds to be analyzed, especially when HF is involved 4. In this context, 13 C Nuclear Magnetic Resonance (NMR), is an attractive method since it is element specific and therefore does not necessarily require prior extraction of the organic C, as long as the mineral matrix is free from paramagnetic elements (e.g. Fe(II), Fe(III), Cu(II), etc.) which cause substantial signal loss by broadening the lines beyond detection 5-7. Furthermore, 13 C NMR provides a detailed analysis of the nature of the organic C from its surrounding matrix, and the quantitative exploitation can be easily performed using an internal or external reference, or without calibration when only relative proportions are needed. This technique has been successfully used to investigate plant tissuese.g 8. and transformation of organic matter in soils e.g. refs 9-11. In this context, 13 C NMR analysis of organics associated with biogenic silica is a favorable case. In higher plants, silicon is acquired by roots from soils and precipitated in or between the cells as micrometric hydrous amorphous biosilica particles called phytoliths. Phytolith abundances range from <1% of dry weight (dwt) in many plants to several % dwt in grasses that are Si-accumulators 12, 13. Phytoliths contain small amounts (<0.5% of dry weight) of carbon (C) occluded during silica precipitation 14-17 , commonly termed as phytC. Recently, the phytC content, nature, origin and impact in the global C cycle have become the subject of increasing debate 14, 15, 18-23. Based on the assumptions that phytC is of photosynthetic origin and is preserved from mineralization in soils, claims were recently made that phytoliths from several agriculturally important monocotyledonous species play a significant role in atmospheric CO 2 sequestration 14, 15, 18-23. However, comparative isotopic measurements (14 C and δ 13 C) of phytC, plant tissues, atmospheric CO 2 , and soil
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Scientific Reports, Nature Publishing Group, 2017, 7 (1), 〈10.1038/s41598-017-03659-z〉
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Armand Masion, Anne Alexandre, Fabio Ziarelli, Stéphane Viel, Guaciara Santos. Dynamic Nuclear Polarization NMR as a new tool to investigate the nature of organic compounds occluded in plant silica particles. Scientific Reports, Nature Publishing Group, 2017, 7 (1), 〈10.1038/s41598-017-03659-z〉. 〈hal-01909490〉

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