Analyzing Solid-Phase Natural Organic Matter Using Laser Desorption

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Analyzing Solid-Phase Natural Organic Matter using Laser Desorption Ionization Ultrahigh Resolution Mass Spectrometry Nissa Nurfajrin Solihat, Thamina Acter, Donghwi Kim, Alain F. Plante, and Sunghwan Kim Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.8b04032 • Publication Date (Web): 28 Nov 2018 Downloaded from http://pubs.acs.org on December 3, 2018

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Analytical Chemistry

Analyzing Solid-Phase Natural Organic Matter using Laser Desorption Ionization Ultrahigh Resolution Mass Spectrometry Nissa Nurfajrin Solihat[a],[b], Thamina Acter[a], Donghwi Kim[a], Alain F. Plante[c], and Sunghwan Kim[a],[d]* [a]

Department of Chemistry, Kyungpook National University, Daegu 41566, Republic of Korea Research Center for Biomaterials, Indonesian Institute of Sciences (LIPI), Cibinong 16911, Indonesia [c] University of Pennsylvania, 240 South 33rd St., Philadelphia, PA 19104, USA [d] Green-Nano Materials Research Center, Daegu 41566, Republic of Korea [b]

ABSTRACT: Extensive sample preparation procedures are required to analyze natural organic matter (NOM) in soil and sediment samples due to the mineral matrix. The preparation procedure not only requires a large amount of sample (typically more than 50 mg) but also incomplete extraction of the organic can be done. In this study, 2–5 μg solid NOM or 500 μg unprocessed soil samples were fixed on a metal plate using double adhesive tape and analyzed directly using laser desorption ionization (LDI) and ultrahigh resolution mass spectrometry (UHR-MS). Most of the peaks reported in previous LDI UHR-MS studies using NOM solutions were observed, and an additional ~2200 unique peaks were found by analyzing the fulvic acids direct solid phase. Differences among soils origin in their molecular compositions were seen clearly with minimum sample preparation. Lignin and tannin-type molecules were detected in both Elliott soil and topsoil from Kyungpook National University campus. The data presented in this study demonstrate a proof-of-principle that highly sensitive, direct, molecular level analysis of solid-phase NOM from unprocessed soil samples and minimum sample preparation is possible.

Natural organic matter (NOM) in soils and sediments plays a crucial role in climate change and the global carbon cycle1-3, and is thus a subject of numerous studies devoted to understanding its chemical composition and biogeochemical stability against microbial decomposition.4-6 Many analytical techniques have been used to characterize the chemical composition of NOM 7,8, including high resolution mass spectrometry.9-11 For example, nuclear magnetic resonance and Fourier transform-infrared (FTIR) spectroscopy provide the overall distribution of chemical functional groups that exist in NOM.12-15 Gas chromatography–mass spectrometry (GC-MS) can provide data on the non-polar compounds.16,17 However, since it is a complex and heterogeneous mixture, one analytical technique cannot provide complete information. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) is an important technique used to analyze complex mixtures. FT-ICR MS can provide the composition of the elements that make up the compounds in complex mixtures such as crude oil and dissolved NOM.18-24 FT-ICR MS has been mostly used with negative mode electrospray ionization ((-) (ESI)) in NOM analysis. (-) ESI is particularly effective at ionizing compounds with acidic functional groups, and it has been combined with a series of solvent extraction techniques to cover the wide range of chemicals present in dissolved NOM 10,25-28 and dissolved organic matter (DOM).29,30 However, all ionization techniques are inherently selective and thus limited in simultaneously analyzing the wide range of different chemicals in NOM.31 Each ionization method is also effective for a specific type of molecule such as ESI suitable to ionize polar component within NOM, atmospheric pressure photoionization (APPI) and

atmospheric pressure chemical ionization (APCI) suitable to analyze smaller and less polar compound present in NOM.19 Laser desorption ionization (LDI) and matrix-assisted laser desorption–ionization (MALDI) are another important ionization technique that has been combined with FT-ICR MS to analyze complex mixtures.32-35 There have been many studies in which MALDI was used in the solid-phase analysis of tissues, pharmaceuticals, and cells 36-39 and LDI for analysis organic aerosols.40 The solid-phase analysis of NOM can eliminate the need for laborious and expensive extraction procedures. 37 In addition, these extraction procedures potentially introduce substantial fractionation because it has been reported that less than 30% of NOM from soil is extracted under alkaline conditions.41 The extraction efficiency of soil by water (H2O), methanol (MeOH), acetonitrile (ACN), and hexane were estimated between 2─15% 25 and more than 50% organic carbon was removed from soil after sodium hydroxide and sodium pyrophosphate solution (NaOH+ NaPP) extraction.42 Recently, the applicability of LDI FT-ICR MS for analyzing NOM has been evaluated and reported by Blackburn et al.9 However, in their study, the standard reference Suwannee River Fulvic Acid (SRFA) from the International Humic Substance Society (IHSS) was dissolved into solution and loaded onto a metal plate for analysis. We believe that direct, solid-phase analysis of solid NOM using laser desorption is also possible. Although this idea has been presented as a conference poster43, the potential for direct solid-phase analysis of NOM, either alone as dried extracts or associated with a mineral matrix such as soil or sediment has not been fully explored. Therefore, this study seeks to provide the proof-of-concept evidence for

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the potential of using LDI FT-ICR MS to analyze solid-phase NOM alone and in predominantly mineral environmental samples.

EXPERIMENTAL Sample Preparation Suwannee River Fulvic Acid (SRFA), Suwannee River Humic Acid (SRHA), Elliott Soil Fulvic Acid (ESFA), Elliott Soil Humic Acid (ESHA), and Elliott soil bulk (ES) were obtained from the International Humic Substance Society (IHSS). SRHA, SRFA, ESFA, ESHA, and ES were analyzed to compare the molecular formula from the same river and same soil. L-Arginine (Sigma–Aldrich, St. Louis, MO, USA) was used as the mass standard. Sea sand was obtained from Duksan (Ansan, South Korea). HPLC-grade acetonitrile (ACN) and water were purchased from J. T. Baker (Deventer, Holland). A natural surface soil was collected from a garden near the department of chemistry at Kyungpook National University (KNU) (Figure S1) by removing surface plant litter and digging to 0–5 cm depth. The collected soil was air-dried, ground, and sieved with a mesh size of 53 μm. The obtained powder was used for further analysis. SRFA and SRHA samples were dissolved to a concentration of 5 mg/mL in 65% acetonitrile/water. The SRFA and SRHA samples were analyzed using (-) LDI FT-ICR MS with four different sample loading methods (Figure S-2). First, 1 μL of the dissolved SRFA and SRHA sample solutions were deposited onto a MTP 384 ground steel plate, and dried at room temperature (25 ± 2ºC). Second, separate aliquots of the solutions were loaded onto approximately 500 μg sand that had been preloaded with 3 × 3 mm double-sided tape (Tapex Co., Ltd., Republic of Korea) on the metal plate. The wet sand was dried before LDI analyses. Third, 2–5 μg of the SRFA and SRHA powders was loaded directly onto preplaced double-sided tape. Lastly, the solid SRFA and SRHA powders were loaded onto pre-loaded sand on double-sided tape. Approximately 2–5 μg of the ESFA and ESHA powders, 500 μg of blank sand, Elliott soil bulk, and local soil samples were also loaded onto preplaced double-sided tape. Large particles in each sample were removed as much as possible by use air dust blower DR-88 (HumanTech, Republic of Korea). Each sample was loaded onto three LDI targets and a spectrum was obtained from each target. A photograph illustrating the loaded LDI metal plate prepared with some of these different sample loading methods is provided in the supporting information (Figure S-3). Instrumentation Spectrometric analyses were performed with a (-) LDI solariX 2XR FT ICR mass spectrometer (Bruker Daltonic, Bremen, Germany) equipped with a 7 T refrigerated actively shielded superconducting magnet and a dual-mode ESI/Matrix Assisted Laser Desorption/Ionization ion source with a frequency–tripled Nd: YAG laser emitting at 355 nm. The broadband spectra were acquired between m/z 100–1000 in 4 MW free induction decays (2 omega), and 200 spectra were averaged to improve the signal to noise ratio. For SRFA, SRHA, ESFA, and soil samples the laser power was adjusted by 40% and each spectrum was exposed to 30 laser shots at 500 Hz. For ESHA, the laser power was set 30%, each scan had 100 laser shots at 500 Hz. The selected precursor ions were accumulated with an ion accumulation time of 0.05 s and a time of flight of 0.7 ms.

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Further detailed instrumentation information is given in Table 𝑚 S-1. An average resolving power ( ) at m/z ~400 was cal∆𝑚50%

culated to be about 300 000. The instrument was externally calibrated with a 20 mM arginine solution. The obtained data were further calibrated with internal calibrants composed of 40 mM arginine and tuning mix (Agilent Technologies, Santa Clara, CA, USA) in a 1:1 ratio (v:v). The solution was mixed with 5 mg/mL fulvic or humic solution in a 1:1 ratio (v:v). Soil samples were doped with 1 μL of 20 mM arginine for internal calibration of the soil analyses. 200 spectra were obtained from each spot and they were coadded. As a result, three co-added spectra were obtained from each sample. Data Processing Peak lists were generated based on S/N ≥ 4 with Data Analysis 4.4 (Bruker Daltonik, Germany). The peak lists were exported to in-house developed C-language software with an automated peak picking algorithm for molecular formula assignment.44,45 Peaks ranging from m/z 150–1000 were assigned to elemental limits of C (1–100), H (1–200), O (0–30), and N (0– 3) within a mass error of +/- 1 ppm. Three peak lists were obtained for each sample loaded on the LDI sample plate. The three peaks lists obtained from each sample were compared and only the peaks appearing in all the lists were selected and used for further data processing. Between 1000~2000 out of 8000~9000 peaks observed from Suwannee river samples and 10000~11000 Elliott soil samples were removed during the process. The relative abundance of unassigned peak of each humic and fulvic spectra less than 6%, the list of these is given in supporting information (Table S-2). Venn diagram produced with the FunRich 3.1.3 46 and van Krevelen plots generated with the software44,45 were used to compare the obtained data.

RESULTS AND DISCUSSION The clean sand fixed with double-sided tape was analyzed by LDI FT-ICR MS and the data obtained are presented in the supporting information (Figure S-4). No substantial peaks are observed. The results show that the tape used as a fixative under the sample did not contribute to the observed spectra of subsequent samples described below. In addition, the sand matrix did not affect the results obtained for the fulvic or humic acid. This suggests that the support matrix of tape and sand can assist in the direct solid-phase analysis of NOM using LDI-FT ICR MS, without concern for artifacts. Ultrahigh resolution mass spectra were obtained from the SRFA and SRHA loaded using the various methods. The time domain spectra are presented in Figure S-5 and the broadband m/z domain spectra are presented in Figure 1. The expanded spectra showing an ~0.4 Dalton window are shown as insets to Figure 1. Over 6,000 peaks were observed in the spectra presented in Figure 1; a list of these is given in the supporting information (Table S-2). Right-hand panel in Figure 1 shows differences peak distribution between SRHA and SRFA. However, the overall spectra and peak distribution obtained from the same samples in the different loading methods (Figure 1) showed similar results. Van Krevelen diagrams of O x class compounds were generated to visually compare the spectra obtained with different sample loading methods and are presented


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in Figure 2. It is notable that the van Krevelen diagrams in Figure 2 show the difference between the SRFA and SRHA analyzed. High Ox class compounds with high O/C ratios (e.g., 0.6 < O/C < 0.8) are more abundant in SRFA compared to SRHA. However, similar peak distribution among the data obtained from the same sample with the different sample loading methods was observed. (a)

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Figure 1. (Left-hand panel) Fourier transform ion cyclotron resonance mass spectra obtained by negative laser desorption ionization Fourier transform ion cyclotron resonance mass spectrometry in four different sample loading methods. (Right-hand panel) The scale expanded spectra at nominal m/z 361 Da. (a) Suwannee River Fulvic Acid (SRFA), (b) Suwannee River Humic Acid (SRHA).

The peaks observed for SRFA powder and SRFA solution in this study (Table S-2) were compared with ones reported in Blackburn et al.9, who analyzed IHSS SRFA and reported the list of Ox class compounds. Blackburn et al. dissolved the NOM samples into solution and loaded the sample on a metal plate for (-) LDI-FT ICR MS analyses. The comparison is summarized and presented as a Venn diagram in Figure 3a. About 1400 of 1671 the peaks assigned in Blackburn et al.9 are also observed in both SRFA powder dan SRFA solution, and approximately additional 2200 unique peaks were observed in SRFA solution and the solid-phase analysis of the SRFA powder. The van Krevelen diagrams of the 1400 overlapping peaks and 2200 unique peaks in SRFA powder are presented in Figure 3b and c. Based on the previous interpretations of van Krevelen plots47,

Figure 2. Van Krevelen diagrams constructed using formulas O1–O20 identified by (-) LDI-FTICR MS. (a) Suwannee River Fulvic Acid (SRFA), (b) Suwannee River Humic Acid (SRHA).

it is apparent broad range of peaks including lignin and tannin derived peaks are observed in this study. The data presented in Figures 1–3 clearly show that NOM powder can be directly analyzed by LDI-FT ICR MS. This can provide a critical advantage when direct solid phase analysis eliminates prior treatment such as extraction of NOM into liquid phase. In addition, the suggested method can be very useful when the amount of sample is limited. For an example, the LDIbased techniques are well known for their sensitivity and minimal consumption of samples;9 only micrograms of fulvic and humic acid were used to obtain the data presented in Figure 1. (-) LDI-FT ICR MS spectra were obtained from Elliott soil fulvic acid (ESFA), Elliott soil humic acid (ESHA), and IHSS Elliott soil (ES) loaded onto a plate with double tape. Obtained time domain and m/z domain spectra with expanded spectra at nominal 361 Da were presented in the supporting information (Figure S-6). The list of compounds observed from each spectrum are shown in Table S-2. Over 8,000 unique elemental for-



mulae were observed from each spectrum. The spectra of exhibit m/z distribution between 100 and 1000 (Figure S-6). It is notable that the peaks marked with * are very abundant in the

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Figure 3. Venn diagram displaying the number of O2–O16 formulae identified in SRFA powder direct solid phase and SRFA solution in this study compared to the previous one by Blackburn et al. (a); van Krevelen diagrams of the overlapping peaks between SRFA powder direct solid phase, SRFA solution, and SRFA solution by Blackburn et al. (b); and unique peaks in SRFA powder direct solid phase (c).

spectrum and they are assigned, based on accurate mass numbers, to C16H32O2, C18H36O2 and C20H28O2. Of these, C16H32O2 and C18H36O2 each has the same elemental composition as palmitic acid and stearic acid, the most common saturated fatty acids existing in nature.48 C20H28O2 have the same elemental composition as nordinone which have been observed in fungi. 49 Therefore, the abundant peaks observed in Elliott soil (Figure S-6c) could be originated from microorganisms in the soil sample. Direct LDI analysis has been widely used for microbial identification.50 Van Krevelen diagrams were constructed with Ox class compounds from the data shown in Table S-2 and presented in Figure 4. Based on the previous interpretations of van Krevelen plots47, peaks corresponding to lignin, tannin, carbohydrate and condensed hydrocarbons were abundant in the spectra. It is notable that peaks assigned to condensed hydrocarbons are more abundant in ESFA and ESHA than SRFA and SRHA (compare Figure 2 and 4). The van Krevelen plots show that H/C ratios of Ox class compounds are mainly distributed between 0.1 and 0.6 for NOM from Elliott. In contrast, H/C ratios of major O x class compounds are located between 0.2 and 0.9 for NOM from Suwanee River. Malcolm51 compared NOM samples from different origins by 1H and 13C NMR and concluded that NOM from soil had more aromatic characteristic than that from stream. The 13 C NMR data listed in the IHSS website52 also shows that the aromatic carbons are more abundant in Elliott samples than in Suwanee River samples. Comparison of diagrams in Figure 4a shows that lignin and condensed aromatic peaks are most abundant in ESFA, and lignin, tannin and condensed aromatic compounds are in ESHA. In the case of ES, lipid, lignin, and tannin compounds are abun-

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Figure 4. (a) Van Krevelen diagrams of ESFA powder, ESHA powder, and Elliott soil constructed using formulas O 1–O20 identified by (-) LDI-FTICR, (b) Venn diagram of ESFA powder, ESHA powder and Elliott soil bulk in direct solid phase (-) LDI-FTICR MS, (c) van Krevelen diagram constructed using ~2800 common peaks observed from ESFA, ESHA, and Elliott soil in direct solid phase (-) LDIFTICR MS (1); the unique ~3600 peaks appeared only in Elliott soil (2); the ~4200 peaks observed only in ESFA (3); and the ~3200 unique peaks observed only in ESHA.


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dant. To further compare the spectra, a Venn diagram was constructed and presented in Figure 4b. Overall, ~2800 peaks were commonly observed from ESFA, ESHA, and ES. The van Krevelen diagram of the common peaks appearing in all three sample is shown in Figure 4c-1. Lignin type molecules especially the ones with condensed aromatic structures were observed from all the three samples. About 3600 peaks were found only in the ES sample and they were assigned as lipid, lignin and highly oxygenated tannin (or carbohydrate) compounds in the van Krevelen diagram (Figure 4c-2). The van Krevelen diagrams of the unique peaks found only in ESFA (~4200 peaks) and ESHA (~3200 peaks) are each provided in Figure 4c-3 and 4. In the case of ESHA, compounds with condensed aromatic structures are uniquely observed, while larger numbers of lignin and tannin type molecules are found in ESFA. In summary, the data presented in Figure 4 and Table S-2 show that direct analysis of soil with LDI-FTICR MS can be effective in obtaining molecular level information of soil organic without extensive extraction procedure from sub milligram of soil samples. The data presented in Figure 4 show the similarity and difference between soil NOM and extracted soil NOM. The question remains on why the difference between ESFA, ESHA and ES were observed. Since the same analytical technique of laser desorption was used for the analysis, it is not likely that ionization efficiency is an issue for the observed difference. The obvious cause of difference from HA vs. FA in general would be the differences in solubility at different pHs, which is how these are separated. Similarly, the differences between the HA/FA and bulk sample is in the fractionation that occurs during solubilization. In other words, the extraction process may accumulate specific type of molecules and hence the choice of extraction procedures can alter the observed composition of NOM.53 To demonstrate different molecular composition from different soil origin, (-) LDI FT-ICR MS spectra were obtained from the KNU top soil sample from a garden near the department of chemistry at Kyungpook National University (KNU). The highresolution MS spectra and van Krevelen diagrams constructed from Ox class compounds are presented in Figure 5. The time domain spectrum and observed peak lists are provided in Figure S-7 and Table S-3. More than 4000 unique elemental formulae were observed from the KNU soil sample. In the spectra (Figure 5a), the abundant peaks (marked with *) have the elemental formulae of C20H28O2, C22H28O14, and C23H29O15 are assigned as lignin/tannin type molecules. They are likely to be generated from trees in the garden (refer to the picture shown in Figure S1). The same molecular formulae was observed in a previous study on dissolved organic matter.54 Figure 5b shows the van Krevelen plot generated from the Ox classes. Lignin- and tannin-type molecules are most abundant in the soil spectrum. Comparison of two soil spectra presented in Figures 4 and 5 show that direct analysis with (-) LDI FT-ICR MS can reveal differences among soil samples at the molecular level, with minimum sample preparation and using sub milligram of sample. The Venn diagram to compare the differences and commonalities between KNU topsoil and Elliott soil bulk is shown in Figure S-8a. The van Kravelen diagram of the common peaks appearing in Elliott soil bulk and the KNU top soil is shown in Figure S-8b-1, unique peaks appeared only in Elliott soil bulk and KNU topsoil are each provided in Figure S-8b-2 and 3. Carbohydrate, lignin, and tannin-like molecule are common in KNU topsoil and Elliot soil bulk (Figure S-8b-

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1), while condense aromatic structures are unique found in Elliott soil (Figure S-8b-2). Unique peaks of highly oxygenated tannin peaks are more abundant in KNU topsoil (Figure S-8b3).

CONCLUSIONS This study demonstrates that LDI FT-ICR MS can be an effective analytical tool for direct solid-phase analysis of complex NOM. Ultrahigh resolution mass spectra, in particular, can be directly obtained from samples such as NOM powder and from soils with minimum pre-treatment, avoiding the extensive extraction and sample desalting steps typically required to analyze soil organic matter using other ionization techniques such as ESI. In addition, a sample size only in the order of micrograms were needed for this direct LDI FT-ICR MS analysis. We expect that the method developed in this study will be very useful to obtain molecular level data on NOM, especially when sample quantities are limited; for example, the method could be used to study the profiles of organic compounds in soil cores, or differences in soil organic matter composition in response to various extraction treatments or in response to environmental disturbances such as land use or climate change.



ASSOCIATED CONTENT

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of Korea (NRF) funded by the Ministry of Science and ICT(MSIT), the Ministry of Environment (ME), and the Ministry of Health and Welfare (MOHW) (2017M3D8A1090658).

Supporting Information The Supporting Information is available free of charge on the ACS Publications website. The supporting information file (File type. MS Word) contains the following information: Figure S-1. The sampling site at the department of chemistry building, Kyungpook National University, from where the topsoil sample was taken. Figure S-2. Schematic diagram illustrating the experimental method. Figure S-3. Laser desorption ionization metal plate with fulvic and humic samples loaded using four different sample methods and soil samples for direct analysis. Figure S-4. Negative laser desorption ionization Fourier transform ion cyclotron resonance mass spectrometry ((-) LDI-FT ICR MS) spectra (left) and the time domain signal (right) of clean sand fixed with double-sided tape. Figure S-5. The free induction decays (FIDs) signals Suwannee River Fulvic Acid (SRFA) (a) and Suwannee River Humic Acid (SRHA) from samples loaded using four different methods (b). Figure S-6. Fourier transform ion cyclotron resonance mass spectra of ESFA powder (a), ESHA powder (b), and Elliott soil (c) obtained by direct solid phase analysis (-) LDI-FTICR-MS. The free induction decays (FIDs) signals of ESFA powder, ESHA powder, and Elliott soil (d). Figure S-7. Time domain spectra of KNU topsoil obtained by negative laser desorption ionization Fourier transform ion cyclotron resonance mass spectrometry. Figure S-8 (a) Venn diagram of Elliott soil bulk and KNU topsoil in direct solid phase (-) LDI-FTICR MS, (b) van Krevelen diagram of the peaks appeared in Elliott soil and KNU topsoil (1); the unique peaks appeared in Elliott soil (2); the peaks observed in KNU topsoil (3). Table S-1. Detailed conditions for negative laser desorption ionization Fourier transform ion cyclotron resonance mass spectrometry. Table S-2. Assigned formula lists of SRFA, SRHA, ESFA, ESHA, and Elliott soil bulk. Table S-3. Assigned formula lists of KNU topsoil.

AUTHOR INFORMATION Corresponding Author * E-mail: [email protected]; Phone: +82-53-950-5333

ORCID Sunghwan Kim: 0000-0002-3364-7367 Alain F. Plante: 0000-0003-0124-6187

Author Contributions The manuscript was written through contributions of all authors.

Notes The authors declare no competing financial interest.

ACKNOWLEDGMENT The authors acknowledge support for this work by the National Research Foundation of Korea (NRF) grant funded by the Korea Government (MSIP), Grant No. 2017R1A2B3003455 and the National Strategic Project-Fine particle of the National Research Foundation

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(46) Pathan, M.; Keerthikumar, S.; Ang, C. S.; Gangoda, L.; Quek, C. Y.; Williamson, N. A.; Mouradov, D.; Sieber, O. M.; Simpson, R. J.; Salim, A.; Bacic, A.; Hill, A. F.; Stroud, D. A.; Ryan, M. T.; Agbinya, J. I.; Mariadason, J. M.; Burgess, A. W.; Mathivanan, S. FunRich: An open Access Standalone Functional Enrichment and Interaction Network Analysis Tool, Proteomics 2015, 15, 2597-2601. (47) Patriarca, C.; Bergquist, J.; Sjoberg, P. J. R.; Tranvik, L.; Hawkes, J. A. Online HPLC-ESI-HRMS Method for the Analysis and Comparison of Different Dissolved Organic Matter Samples, Environ Sci Technol 2018, 52, 2091-2099. (48) Scrimgeour, C. M.; Harwood, J. L.Fatty Acid and Lipid Structure In The Lipid Handbook with CD-ROM, Gunstone, F. D.; Harwood, J. L.; Dijkstra, A. J., Eds.; CRC Press: Boca Raton, 2007, pp 1-36. (49) A.Aver, W.; LuisPeña-Rodriguez. Minor Metabolites of Monocillium nordinii, Phytochemistry 1987, 26, 1353-1355.

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(50) Biswas, S.; Rolain, J. M. Use of MALDI-TOF Mass Spectrometry for Identification of Bacteria that are Difficult to Culture, J Microbiol Methods 2013, 92, 14-24. (51) L. Malcolm, R. The Uniqueness of Humic substances in each of Soil, Stream and Marine Environments, Anal Chim Acta 1990, 232, 19-30. (52) IHSS. International Humic Substances Society, 2018, p 13C NMR Estimates of Carbon Distribution. (53) Fox, P. M.; Nico, P. S.; Tfaily, M. M.; Heckman, K.; Davis, J. A. Characterization of Natural Organic Matter in Low-Carbon Sediments: Extraction and Analytical Approaches, Org Geochem 2017, 114, 12-22. (54) Flerus, R.; Lechtenfeld, O. J.; Koch, B. P.; McCallister, S. L.; Schmitt-Kopplin, P.; Benner, R.; Kaiser, K.; Kattner, G. A Molecular Perspective on the Ageing of Marine Dissolved Organic Matter, Biogeosciences 2012, 9, 1935-1955.

Authors are required to submit a graphic entry for the Table of Contents (TOC) that, in conjunction with the manuscript title, should give the reader a representative idea of one of the following: A key structure, reaction, equation, concept, or theorem, etc., that is discussed in the manuscript. Consult the journal’s Instructions for Authors for TOC graphic specifications.

Insert Table of Contents artwork here


Page 9 of 13

Analytical Chemistry SRFA solution

(a)

Intens. x108

Intens. x108

2.0

spektrum\1: -MS

spektrum\1: -MS

spektrum\2: -MS

spektrum\2: -MS

spektrum\3: -MS

spektrum\3: -MS

spektrum\4: -MS

spektrum\4: -MS

1.5

1.5 1.0

1.0 0.5

0.0 x108

0.0 x108

2.0

SRFA solution + sand 1.5

1.5 1.0

1.0 0.5

0.5

0.0 x108

0.0 x108 1.0

1.2

SRFA powder

1.0

0.8

0.8 0.6

0.6 0.4

0.4 0.2

0.2 0.0 x108

0.0 x108

1.0

SRFA powder + sand

0.8

0.8

0.6

0.6

1.0

0.4

0.4

0.2

0.2

0.0 200

l

I

300

400

200

I

500

400

600

I 800

700

800

600

0.0 360.98 1000 361.00m/z

I

900

I

1000

361.02

I

361.04

361.06

I

361.08

361.10

I

361.12

361.14

m/z

361.12

361.04

m/z Intens. x108

(b)

Intens. x108

spektrum\5: -MS

spektrum\5: -MS

spektrum\6: -MS

spektrum\6: -MS

spektrum\7: -MS

spektrum\7: -MS

spektrum\8: -MS

spektrum\8: -MS

SRHA solution 1.5

1.5 1.0

1.0

Relative Intensity

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

Relative Intensity

0.5

0.5

0.5

0.0 x108

0.0 x108

SRHA solution + sand

2.0

2.0

1.5

1.5

1.0

1.0

0.5

0.5

0.0 x108

0.0 x108

2.0

SRHA powder 1.5

1.5 1.0

1.0

0.5

0.5

0.0 x108 2.0

0.0 x108 2.0

SRHA powder + sand

1.5

1.5

1.0

1.0

ACS Paragon Plus Environment 0.5

0.5

0.0

l

200

200

300

I400

400

500

I 600

600 m/z

700

I

0.0

800

800

900

I I360.981000 361.00

1000

361.02 1100

I

361.04 m/z

361.06

361.04

I

361.08

361.10

I

361.12

361.14

361.12

m/z

Analytical Chemistry -

1.0-

-

0.5-

Relative

-

abundance (%)

Max.

Min.

0 SRFA Powder

SRFA Powder + sand

1.5-

-

1.0-

-

0.5-

Relative

I

I

I

I

I

I

I

I

I

0.4

0.6

0.8

1.0

0.2

0.4

0.6

0.8

1.0

SRHA Solution + sand

SRHA Solution

1.5-

-

1.0-

-

0.5-

Max.

SRHA Powder

1.0-

-

0.5-

-

I

0.4

I

I

I

Max.

Relative

-

I

Min.

SRHA Powder + sand

1.5-

0.2

Relative

-

0

Min.

abundance (%)

(b)

I

0.2

I

I

I

I

0.2 0.4 0.6 0.8 0.6 Paragon 0.8 1.0 ACS Plus Environment O/C O/C

I

1.0

abundance (%)

0

-

abundance (%)

H/C

Max.

H/C

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44

1.5-

H/C

(a)

Page 10 of 13

SRFA Solution + sand

SRFA Solution

Min.

Page 11 of 13 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27


(a) SRFA solution

SRFA powder direct solid phase

SRFA solution by Blackburn et. al

(b)

(c)


(a) 2.2-

-

Page 12 of 13

ESHA Powder

ESFA Powder -

-

-

-

-

0.5-

H/C

I

I

I

I

0.8

1.0

0.2

0.4

I

0.6 O/C

I

I

0.8

1.0

I

0.6 O/C

(2)

Relative I

0.2

I

0.4

0.6 O/C

Min.

I

I

0.8

1.0

I

(3)

-

-

-

-

-

-

-

-

-

-

-

(4)

H/C

-

Elliott soil bulk

I

I

I

I

I

I

0.4

0.6

0.8

1.0

0.2

0.4

O/C

I

I

I

I

I

I

1.0 Plus Environment 0.6 ACS 0.8Paragon 0.2 0.4 0.6

O/C

O/C

Relative

Max.

I

I

I

I

I

I

I

0.8

1.0

0.2

0.4

0.6

0.8

1.0

O/C

abundance (%)

I

0.4

Max. abundance (%)

1 2 3 1.54 5 6 1.07 8 9 0.510 11 I 12 0 0.2 13 14 15 (c) (1) 16 2.217 18 19 201.521 22 231.024 25 26 0.527 28 I 29 0 0.2 30 31 32

(b)

Analytical Chemistry -

Min.

Page 13 of 13

Analytical Chemistry (a)

Intens. x109

1.25

Relative Intensity

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

*

20180807_LDI_N_Chemsoil_100-3000_Scan200_4M_LP40_LS30_0_FQ500_TOF0.7_0_SKIM-45_0_C11_000001.d: -MS

1.00

0.75

0.50

*

*

0.25

0.00 200

l

300

200

I

400

400

500

I600

600

700

I 800

800

m/z

(b)


900

Im/z

1000

Analyzing Solid-Phase Natural Organic Matter Using Laser Desorption

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