Molecular Structure Characterization of Riverine and Coastal

Jun 5, 2018 - For ESI+ mode, mobile phase A was H2O with 0.1% (v/v) formic acid, and B ..... Figure 4b) were separated by IM with a difference of 0.47...
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Characterization of Natural and Affected Environments

Molecular structure characterization of riverine and coastal dissolved organic matter with ion mobility quadrupole time of flight LCMS (IM Q-TOF LCMS) Kaijun Lu, Wayne S. Gardner, and Zhanfei Liu Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b00999 • Publication Date (Web): 05 Jun 2018 Downloaded from http://pubs.acs.org on June 5, 2018

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Molecular structure characterization of riverine and coastal dissolved organic

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matter with ion mobility quadrupole time of flight LCMS (IM Q-TOF LCMS)

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Kaijun Lu, Wayne S. Gardner, and Zhanfei Liu*

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Marine Science Institute, The University of Texas at Austin, Port Aransas, Texas, United

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States

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Corresponding author: Zhanfei Liu ([email protected])

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Keywords:

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Dissolved organic matter (DOM), multi-dimensional characterization of DOM, inland

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and coastal waters, liquid chromatography-mass spectrometry, non-target liquid

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chromatography-tandem mass spectrometry, ion mobility, isomers

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Abstract

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Deciphering molecular structures of dissolved organic matter (DOM) components is

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key to understanding the formation and transformation of this globally important carbon

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pool in aquatic environments. Such a task depends on the integrated use of

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complimentary analytical techniques. We characterize the molecular structure of natural

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DOM using an Ion Mobility Quadrupole Time of Flight Liquid Chromatography Mass

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Spectrometer (IM Q-TOF LC/MS), which provides multidimensional structural

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information of DOM molecules. Geometric conformation of DOM molecules is

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introduced into molecular-level analysis via the ion mobility (IM) in the system, and an

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actual measurement of isomers is achieved for the first time. Our data show that natural

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DOM molecules from several south Texas rivers and adjacent coastal waters have smaller

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geometric conformation compared with standard biomolecules. Furthermore, of all DOM

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molecules resolved within the detection limit of IM-MS, from 4.7% to 12.3% under

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electrospray ionization (ESI) + mode, and from 6.4% to 13.1% under ESI- mode,

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respectively, had at least one but no more than four isomers. With acquired geometric and

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isomeric information, we established a multidimensional database containing 89 natural

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DOM compounds. This database provides a foundation to expand further, or compare,

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with data from different seasons and locations.

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Abstract Graphic CCS vs. m/z (Positive) 500 450

Peptides

Lipids

400

Tetraalkylammonium Salt Cation

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Ω (Å2)

300

Carbohydrates

250 200 150

Natural DOM

100 50 0 0

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500

1000

1500 m/z

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Introduction

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Dissolved organic matter (DOM) is an important carbon pool in the ocean, containing

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660 × 1015 grams of carbon, similar in magnitude to atmospheric carbon and over 1000

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times more than all living organisms in the oceans combined.1 This large marine carbon

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pool exchanges constantly with atmospheric carbon through processes such as

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photosynthesis and respiration. Therefore, small disturbances of the DOM pool could

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impact global climate substantially. Despite its potential climatic significance, molecular

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information of DOM is not well defined. Also unclear is why a major fraction of this

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reduced organic carbon persists in an environment enriched with electron acceptors for

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millennial time scales.1,2 Given the small size (≤ 1000 Da) of the most refractory DOM,

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an intriguing question is why is it not assimilated efficiently by bacteria?3 This paradox

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relates to our limited understanding of the DOM at the molecular level. In fact, less than

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30% of DOM in surface ocean and only about 5% in deep water has been characterized.4

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Deciphering molecular-level information of DOM is key to understanding this important

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carbon pool and its interactions with pollutants5,6 and greenhouse gases.7,8

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Precise molecular-level analyses of DOM rely on the integrated use of complimentary

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analytical techniques. The current capacity to resolve DOM at the molecular-level can be

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described in the form of a three-dimensional analytical space comprising 108 to 1014

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individual voxels, which is constrained by the resolution of three complementary

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techniques of (1) nuclear magnetic resonance (NMR; resolution 102 to 105), (2) ultrahigh-

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resolution Fourier Transform Ion Cyclotron Resolution Mass Spectrometry (FTICR MS;

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resolution 104 to 105), and (3) high-performance separation (resolution 102 to 104).9

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However, our understanding is still not comprehensive even though thousands of distinct

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molecular formulas can be resolved from the intricate mixture of DOM with the

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combination of NMR and ultrahigh resolution MS.10

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An important deficiency is our limited knowledge of the isomeric information of DOM

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molecules, and thereby the total number of compounds in natural DOM. Knowing the

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total number of different structural units is crucial in exploring reasons behind the long-

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term stability of DOM, such as the recently-ignited dilution hypothesis.1 Because high

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resolution MS only provides isomer-filtered information of complex DOM mixtures,

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estimation of the number of isomers in DOM mixture currently relies on calculation and

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modelling,9,11,12 ranging from over a hundred thousand11,13 to several million.9,14 A recent

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study calculated that the number of DOM isomers may be over 10-fold of the detected

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individual formulas by modelling based on intrinsic averaging theory.11 Another study

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further suggested that the total number of isomers in natural DOM could be over 107

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because a maximum of theoretically possible structural isomers exists at the observed

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level of H-saturation in DOM, and the intensities of the mass spectral peaks are a

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function of the abundance of isomers.9 However, modelling results alone cannot explain

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why the molecular size range of DOM has a unimodal distribution with the maximum

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intensity reached at around 400 Da.14 Based on this hypothesis, the mass spectra should

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have a monotonous increasing trend, as the number of isomers should increase

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exponentially with molecular size. The actual measurement of isomers in natural DOM,

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therefore, may be critical in explaining this paradox.

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Ion mobility mass spectrometry (IM-MS) provides structural and isomeric information

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of molecules as a unique dimension in molecular-level DOM studies. Ions are separated

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in the IM chamber through low-energy interactions with inert buffer gas (N2 or He)

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during the transit,15,16 as ions with larger collision cross section (CCS) areas are delayed

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with longer drift times than smaller ones due to more frequent collisions with buffer gas

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molecules.17–19 Molecular-level structural information in the form of CCS values can help

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characterize the target compound and differentiate isomers.15 The coupling of IM and MS

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in elucidating complex mixtures was reported during the past decade (e.g., 20–22).

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However, the use of IM-MS focused mainly on either standard biomolecule mixtures or

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using drift time as a supportive tool (i.e., using IM to unravel the existence of multiple

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charged compounds in the standard Suwannee River Fulvic Acids21). No calibrated CCS

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values were reported, which made these applications laboratory and instrument

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dependent. These limitations prevented accurate cross-lab comparisons to generate

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effective information in molecular-level DOM studies. With recent commercialization of

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traveling-wave IM-MS and drift tube IM-MS,16,22 IM-MS now offers a standardized

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measurement of compounds with calibrated CCS values using standards with high

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precision and confidency.23 However, to date, the system has not been applied to

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obtaining systematic structural and isomeric information of natural DOM.

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The goal of this study is to provide multidimensional information for natural DOM

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from multiple coastal sites. We report the results of natural DOM analysis using an online

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combination of IM, high-performance liquid chromatogram (HPLC), and Quadrupole

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Time-Of-Flight mass spectrometry (Q-TOF MS). Natural DOM samples were collected

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from five South Texas rivers and adjacent coastal waters near the University of Texas

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Marine Science Institute (UTMSI). We aim to explore a new dimension (geometric

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conformation or “shape” of DOM molecules) in molecular-level DOM analysis. More

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importantly, we use the IM-MS to obtain actual measurement of isomers in DOM which

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is not available otherwise.1,9,12,14 Our results from respective riverine and coastal waters

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illustrate that natural DOM molecules have lower CCS values compared with standard

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biomolecules of same molecular weights, indicating that their geometric conformations

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are more compact. With actual measurement, we demonstrate for the first time that 4.7%

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to 12.3% (positive mode) and 6.4% to 13.1% (negative mode) of the detected natural

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DOM molecules have at least one isomer, but no more than four.

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Materials and Methods

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Sampling sites and sample preparation. Samples were collected from 7 sites in five

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south Texas rivers (Aransas River, AR: N 28.13°, W 97.43°; Lavaca River 1, LR1: N

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28.96°, W 96.68°; Lavaca River 2, LR2: N 28.83°, W 96.58°; Mission River, MR: N

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28.29°, W 97.28°; Nueces Dam, DAM: N 27.88°, W 97.63°; San Antonio River 1, SR1:

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N 28.53°, W 97.04°; San Antonio River 2, SR2: N 28.48°, W 96.86°; Figure S1,

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Supporting Information) in May 2016 using a 2-L Van Dorn sampler. Samples were also

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collected from the Ship Channel (SC: N 27.84°, W 97.05°; Figure S1, Supporting

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Information) connected to the open Gulf in September 2016. One-L samples were filtered

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(0.2 µm pore size) to remove suspended particles. Bulk DOC concentration was

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measured on 20 mL of the filtrate. DOM was isolated from the rest of filtered water and

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prepared for LC/MS analysis by solid-phase extraction (SPE) using a PPL cartridge

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(Agilent Bond Elut PPL cartridge, P/N 12105006) following the established protocol.24

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DOM extracts were eluted with methanol and stored at -20 °C until further analysis. They

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were diluted 10-fold with methanol prior to analysis. The recovery rate of DOM

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extraction ranged from 31% to 44% on a carbon basis. All solvents and chemicals were

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LC/MS grade (acquired from Fisher or Sigma Aldrich).

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Instrumentation. The instrumentation includes an HPLC coupled with an IM-QTOF

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MS with an orthogonal electrospray ionization (ESI) source (Agilent 6560, see Figure S2,

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Supporting Information). Ion mobility separation occurs in a 78-cm uniform field drift

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tube with high purity N2 as the buffer gas. Ions traverse the drift tube under a weak

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electric field (10 to 20 V·cm-1)15 to ensure that the mobility of ions depends solely on

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their structures and interactions with the buffer gas. The estimated resolving power

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(calculated as t/∆t, in which t is drift time and ∆t is the peak width measured in

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milliseconds at half height) of ion mobility exceeds 60 at drift time of 30 ms.15 The TOF

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MS alone has resolving power greater than 40 000 at m/z of 1200,15 while the whole

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instrument IM Q-TOF LC/MS can resolve up to 2 000 000 at m/z of 300.

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The MassHunter LC/MS Data Acquisition (Version B.07.00) provided the LC/MS

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parameters setup and monitored the acquisition process. Both positive and negative ion

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ESI modes were applied. However, because the IM data of most biomolecules were

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acquired under ESI+ mode,15,19,25 we focus on the ESI+ mode here for comparison with

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published data (details for ESI- data are provided in Supporting Information). MS and

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MS/MS data were acquired with the acquisition mode of QTOF-Only, while IM data

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were acquired under the IM-QTOF mode.

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HPLC settings. For ESI+ mode, mobile phase A was H2O with 0.1% (v/v) formic

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acid, and B was acetonitrile. One-µL of each sample was eluted through a Stablebond C18

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column (Poroshell 120 SB-C18; 2.7 µm, 2.1 × 100 mm; Agilent P/N 685775-902) at a

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flow rate of 0.5 mL·min-1. During the 21-min run, mobile phase B was increased from

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3% to 90% during the first 15 min, and held at 90% from 15 min to 20 min, and then

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dropped to 3% from 20 min to 21 min. A post-run time of 4 min allowed the column to

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reach equilibrium.

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The same C18 column used in ESI+ mode was tested in negative mode, but it offered

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inadequate resolution, with most of the compounds co-eluting in humps (data not shown).

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Hydrophilic interaction chromatography (HILIC) column, on the other hand, separates

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small polar analytes efficiently.26 Thus, a HILIC column (2.7 µm, 15 cm × 4.6 mm

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SUPELCO, P/N 53981-U) was used in ESI- mode. Mobile phase A was H2O with 10

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mM ammonium acetate, and mobile phase B was acetonitrile. Formation of a stable

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aqueous layer on the surface of a HILIC column is crucial for achieving optimal

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separation power. Therefore, the column was equilibrated before analysis. At a flow rate

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of 0.4 mL·min-1, mobile phase B was increased from 80% to 97% during the first 15 min,

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dropped to 84% at 18 min, 72% at 21 min, and 60% at 24 min, increased back to 97% at

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30 min and held at 97% until 60 min. For sample analysis, 1 µL of samples was eluted

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through the HILIC column at a flow rate of 0.5 mL·min-1. During the 10-min run, mobile

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phase B was held at 98% during the first 1 min, and dropped to 95% from 1 min to 10

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min. A post-run period of 15 min allowed the column to reach equilibrium before

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injection of next sample.

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Data acquisition. The MS, non-targeted MS/MS, and IM-MS acquisition parameters

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are detailed in Supporting Information. Specifically, the MS acquisition rate was 4

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spectra/s, and acquisition time was 250 ms/spectrum. The MS/MS acquisition rate was 2

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spectra/s, and acquisition time was 500 ms/spectrum. This high frequency of acquisition

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ensures the application of non-targeted LC-MS/MS.27

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MS data analysis. Data analysis employed MassHunter Qualitative Analysis (Version

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B.07.00, Service Pack 2), MassHunter IM-MS Browser (Version B.07.01), and

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MassHunter Molecular Structure Correlator (Version B.07.00). The built-in function

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“Find by Molecular Feature” in MassHunter Qualitative Analysis identified compounds

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in the MS results. +H was allowed in positive data, while –H, +HCOO, and +CH3COO

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were allowed in negative data. A neutral loss of H2O was enabled in both modes. The

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mass inaccuracy tolerance was set at ≤ 1.5 ppm (< 0.9 mDa at a mass range of 150-600

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Da). Possible formulas were computed with the function “Generate Formulas”, which

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takes the exact mass,

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Generated formulas were further screened manually with the following basic criteria28–31:

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(1) Double Bond Equivalent (DBE) = 1+ ½(2C-H+N+P) ≥ 0; (2) O:C ≤ 1; (3) N ≤ 4 and

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N:C ≤ 1; (4) 0.333 ≤ H/C ≤ 2.25; (5) Nitrogen Rule; and (6) isotopic spacing and

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abundance (detail in Supporting Information).

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C isotope abundance and

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C isotope spacing into account.

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MS/MS data analysis. Compounds in MS/MS results were revealed by the function

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“Find by Auto MS/MS” in MassHunter Qualitative Analysis with the following settings:

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retention time window of 0.2 min, set to be comparable to the full width of a typical

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chromatogram peak (Figure 1 and S3); an MS/MS TIC threshold of 1,000 for both

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positive and negative modes; mass match tolerance of 0.05 m/z. Possible formulas were

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assigned to the found compounds using the function “Search Database”. The +H, +Na,

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and –H2O ion species were selected in positive data, while –H, +HCOO, +CH3COO, and

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–H2O were selected in negative data. The database used was a standalone version of

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METLIN Metabolites.32 MS/MS data were examined in detail using Molecular Structure

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Correlator, which provided fragmentation information by comparing results with

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ChemSpider and METLIN Metabolites database.

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IM-MS data analysis. IM-MS data were analyzed with the IM-MS Browser. Drift

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times, which represent the total transit time of the ions, including the mobility drift time

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and the flight time through the interfacing IM-MS ion optics and MS,15 were acquired

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using the function “Find Features (IMFE)” with the following settings: isotope model

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common organic (no halogens); charge state ≤ 1; ion intensity ≥ 50. Compound drift

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times were calibrated with reference ions to determine the gas-phase momentum transfer

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collision cross section (CCS).15,33

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Results and Discussion

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LC for powerful preliminary separation of DOM molecules. HPLC is an important

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tool in molecular-level analysis of complex samples,9 and has been used to isolate and

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identify biomolecules in many studies.34–36 Here, the C18 column provides a preliminary

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separation of natural DOM molecules based on their hydrophobicity. The retention

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mechanism of the HILIC column is still under debate,37 but may involve partitioning of

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analytes from the bulk eluent through multimodal retention mechanisms including ion-

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exchange, hydrogen-bonding, hydrophobic and hydrophilic interactions with the

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immobilized water-rich layer on HILIC stationary phases.37–40 Figures 1 and S3 show

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typical chromatograms for our sampling sites (Rivers and Ship Channel) measured under

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both ESI modes. The HPLC chromatograms were highly reproducible, with retention

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times differing less than 0.05 min between replicate samples (data not shown). The

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chromatograms are divided further into different fractions (F1 to F5) based on mobile

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phase and the distribution of peaks. Note that signal intensity of the marine Ship Channel

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sample was higher than that of riverine samples in ESI+ mode, but lower in ESI- mode

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(Figures 1 and S3).

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A complete MS dataset of both ESI+ and ESI- data was acquired (Supporting

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Information). In order to compare with published IM data mainly in ESI+ mode, we here

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focus on the positive mode. ESI+ mode is not used as commonly in most DOM studies,

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based on the assumption that DOM primarily contains molecules with carboxyl groups

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that can be ionized efficiently in negative mode.41 However, neither ESI- mode nor ESI+

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mode provides a holistic projection of the complex DOM mixture.12 Our primary goal

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here is to demonstrate multidimensional information on the size, structure and

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composition of DOM.

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Briefly, our data shows that compounds annotated in ESI+ mode generally have a

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higher average value of H/C (paired t test, df = 7, t = 14.602, p < 0.05) but lower O/C

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ratios (paired t test, df = 7, t = -2.4629, p < 0.05; Table S1, Supporting Information). The

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most prominent difference in O/C ratios observed in marine samples, agrees with the

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conclusion from previous literature that oxygenated molecules are preferentially ionized

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in negative mode.12,31,41 On average, 4959 and 2331 peaks are found in ESI+ and ESI-

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mode, with 2816 and 1629 formulas assigned, respectively. The formula assignment

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percentage in this work is 56.4% in ESI+ mode, and 68.4% in ESI-.

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The van Krevelen diagrams are shown in Figure S4 (Supporting Information). H/C =

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1.5 is defined as molecular lability boundary (MLB) to differentiate natural DOM into

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labile and less labile groups, with H/C ≥ 1.5 corresponding to more labile material.42

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Using this standard, about one half of the compounds (43.4% in ESI+ and 67.9% in ESI-)

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were below the MLB in both ESI modes, indicating that DOM collected from rivers and

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coastal waters is an intricate mixture of relatively “labile” and “recalcitrant” constituents.

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Lipid-, protein-, cellulose-, and lignin-like biomolecules12,30,43–45 are present in the van

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Krevelen diagrams, but overall very few compositions of natural DOM are observed in

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the specific sectors of the diagram anticipated for these biomolecules (Figure S4,

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Supporting Information). The majority of natural DOM is positioned between different

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groups of biomolecules (Figure S4, Supporting Information). In agreement with previous

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studies,3,9,12,46 this observation indicates that the covalent bonding between different

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classes of biochemical precursor molecules may be an important source of natural

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DOM.12 Note that the van Krevelen diagrams in this work are different from those

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reported previously in direct infusion experiments, but consistent with a previous LC-MS

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study.36

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Most previous DOM studies using ultrahigh resolution MS technique such as FTICR-

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MS have applied direct infusion. However, the application of HPLC prior to the DOM

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analysis is still desirable because combining HPLC with MS alleviates ion

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competition/suppression effects during ionization.27,36 In the mixture of DOM, the

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ionization of the low efficiency compounds is suppressed by high efficiency

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compounds.41,47 For instance, in ESI- mode carboxyl-rich alicyclic molecules (CRAM)48

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would be ionized preferentially due to their high carboxyl-group content, thus in direct

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infusion other types of compounds would be suppressed.12 With the addition of HPLC,

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high ionization efficiency molecules can be separated from low efficiency molecules in a

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certain degree due to their different physical properties. Many compounds with higher

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H/C and/or O/C ratios were revealed in this work (Figure S4, Supporting Information)

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compared with other direct-infusion DOM studies.30,42,43,48 This result is consistent with

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previous findings that fractionated DOM covers a larger area of van Krevelen diagrams

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than non-fractionated.12

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The other advantage of using HPLC is the separation of compound mixtures by the

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column and hence the enhanced resolving ability in annotating DOM molecules, even

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isomers, because it introduces a near-orthogonal dimension for molecular-level

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analysis.9,27 When re-examining the van Krevelen diagram based on the retention time

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(Table S2, Figure S5, and S6, Supporting Information), the H/C ratios increase and O/C

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ratios decrease progressively as the solvent shifts from hydrophilic to hydrophobic in

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ESI+ mode, while H/C ratios increase as the solvent becomes less hydrophobic in ESI-

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mode (Table S2, Supporting Information). The retention time information can also

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differentiate structural isomers. For example, more than one peak with m/z of 437.1943

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were detected in Ship Channel samples but not in riverine samples under ESI+ mode

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(Figure 2). Of the several m/z 437.1943 peaks, one compound eluted at about 11.3 min at

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fraction F3, as compared to ca. 18.5 min at fraction F4 for the other compound (Figure

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2a). Although the two compounds had identical m/z and isotopic features (Figure 2b & c),

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their drastically different elution times indicate that they are isomers, with the second

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compound being more hydrophobic. MS/MS results further confirm that these two

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compounds had different fragments after collision, with the first compound having

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fragments with an m/z of 59, 87, and 421, as compared to fragments of 112, 114, 130 and

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364 for the latter (Figure 2d & e). Note that this isomeric information would be buried

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without the previous separation by HPLC.

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Molecular formula assignments based on non-targeted LC-MS/MS results. In the

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MS/MS mode, selected ions are fragmented automatically by the applied collision energy.

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Using targeted tandem MS to obtain detailed structural information of certain compounds

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is common in molecular-level DOM studies. Here we take advantage of the high

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acquisition speed (2 spectra/s, as mentioned above in Methods and Supporting

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Information) to do a non-targeted full scan LC-MS/MS analysis of natural DOM. We use

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the fragment information as a holistic method to annotate the DOM molecules based on

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METLIN Metabolites database. This non-targeted LC-MS/MS approach has been

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reviewed extensively in metabolomics studies,49–52 but was applied in DOM analysis only

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very recently.27 Additionally, the Molecular Structure Correlator (Version B.07.00) can

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calculate the likelihood of the fragmentation pathway. On average, in ESI+ mode, 176

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and 224 compounds were assigned with a match based on the METLIN Metabolites

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database for riverine and marine samples, respectively. In ESI- mode, 180 and 74

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compounds were assigned with a match, respectively. The assignment rate based on

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MS/MS ranged from 56.4% to 62.5% in ESI+ mode and from 68.4% to 70.4% in ESI-

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mode. The van Krevelen diagrams based on MS/MS data (Figure S7, Supporting

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Information) resemble those generated from MS data. From these samples we assembled

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a database of 89 DOM molecules with holistic structures based on non-targeted LC-

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MS/MS in appendix, and two example molecules are further shown in Figure S8

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(Supporting Information).

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The 3D size of DOM molecules from IM results: CCS-based characterization.

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Currently,

ion

mobility

instrumentation

is

used

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characterization and differentiation of chemical isomers with high resolution, high

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sensitivity, and broad sample compatibility.16 The existing IM database was acquired

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mainly under ESI+ mode,15,19,25 so only ESI+ data of natural DOM is shown and

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discussed here to compare with the existing database. Species, m/z, drift time and CCS

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values of the biomolecules standards were obtained from published studies using the

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same model of IM instrument that is calibrated with standards.15 The number of

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compounds detected through IM-MS varies among different samples, but remains quite

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constant among replicates. The average number of features ranged from 46 in Lavaca

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River 2 (LR2) to 460 in Lavaca River 1 (LR1) under ESI+ mode (Table S3, Supporting

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Information), and they are about one order of magnitude lower than those in MS and

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MS/MS due to the ion loss during IM. The fact that LR1 has the most features detected in

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IM-MS is consistent with HPLC chromatograms, in which LR1 has chromatogram peaks

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not detected in other samples at retention time of ~ 6.4 min and ~ 7.2 min (Figure 1). It

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remains unclear why such a great difference in the number of features occurred from the

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two sites of the same river (Figure S1, Supporting Information). One possible explanation

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is that LR2 is on the downstream of LR1, the abiotic/biotic modifications during

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transportation may have caused this change, as the low flow is typical for south Texas

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rivers.53 In addition, the downstream LR2 is influenced by a major stream branch sourced

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from Lake Texana from north, so the difference on the features between LR1 and LR2 is

329

not surprising. Of the 266 compounds in marine sample, 180 and 76 were assigned with a

330

formula with MS and MS/MS, respectively. For riverine samples, the number varied

331

from 27 to 293 with MS, and 4 to 20 with MS/MS (Table S3, Supporting Information).

332

The van Krevelen diagrams based on IM-MS data in ESI+ mode (Figure S9, Supporting

333

Information) again assemble those generated from MS data and MS/MS data.

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334

IM separations are based on the ion’s interaction with neutral buffer gas, which is

335

proportional to “apparent ion surface area”.19 When coupled with MS, IM can provide

336

gas-phase separations in one dimension on the basis of structure, and a second dimension

337

on the m/z value. The CCS data of standard biomolecules and tetraalkylammonium were

338

acquired from published database.15 As shown by the CCS-m/z diagram (Figure 3), CCS

339

increases with an increasing m/z. For standard biomolecules, the CCS value at a

340

particular m/z increases in the order of carbohydrates < peptides < lipids
100 resolving

427

power is rarely reported.60 A similar system (LC-ESI-IM-TOF-MS) was capable of

428

resolving over 70% of the constitutional isomers from a 4000-peptide mixture.61 A more

429

recent study has reported that with a resolving power of 60, IM-MS alone (without LC)

430

resolved over 30% of the isomers of leucine (C6H13NO2), with most constitutional

431

isomers (i.e., ethyl ester vs. tertleucine vs. norleucine) resolvable, but some diastereomers

432

(i.e., L-allo-isoleucine vs. L-isoleucine) and most enantiomers (L-leucine vs. D-leucine

433

and L-isoleucine vs. D-isoleucine) unresolvable.62 Nevertheless, our IM-MS result clearly

434

points out that, in contrast to what modelling studies hypothesized, the number of isomers

435

is lower than modelled in DOM molecules. While more work is needed to reconcile the

436

discrepancy between our measurement and modelling data, this dataset provides the first

437

quantitative information about DOM isomers based on actual measurements, and it opens

438

a new direction in molecular-level DOM analysis.

439 440

Implication

441

This work shows that the IM Q-TOF LC/MS provides a multi-dimensional approach to

442

annotate natural DOM, by combining HPLC, MS, tandem MS and ion mobility. With IM

443

in the system, geometric conformation of DOM molecules is introduced into molecular-

444

level analysis, and a direct measurement of isomers in natural DOM is achieved for the

445

first time. Our data show that natural DOM molecules from several south Texas rivers

446

and coastal waters are more compacted than standard biomolecules, and that higher

447

oxidation state results in larger geometric conformation of DOM molecules. Moreover, of

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448

all DOM molecules resolved within the detection limit of IM-MS, from 4.7% to 12.3%

449

under ESI+ mode, and from 6.4% to 13.1% under ESI- mode, respectively, had at least

450

one isomer. The isomer percentage measured in this study is much lower than that

451

reported in previous modelling efforts. A database containing 89 compounds was

452

established with multidimensional information, including retention times, molecular

453

weight, possible formulas and structures based on MS/MS, CCS, and isomeric

454

information. This database provides a foundation to be further expanded, or compared,

455

with data from different seasons and locations. We expect this preliminary study to serve

456

as a “first spark” to provoke other studies leading to new advancements on elusive

457

organic compound identifications in natural DOM samples. The unique ability of IM-MS

458

to separate isomers will increase our understanding of the complex structure of DOM and

459

its interactions with light, natural ions, and/or contaminants in natural environments.

460

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Supporting Information Instrumentation details; acquisition settings for MS, untargeted LC-MS/MS, and IMMS; criteria for formula assignment; Table S1-4; Figure S1-9.

464 465

Acknowledgements

466

We thank Dr. Ryan Hladyniuk from UTMSI Core Facility Lab for helping assemble

467

and maintain the equipment, and Drs. Carol Haney Ball, Dawn Stickle, Caroline S. Chu,

468

and Daniel Cuthbertson from Agilent Technologies for invaluable technical support.

469

Special thanks to Drs. Robert Dickey and Ed Buskey for making the instrumentation

470

available at UTMSI. This study was supported by NOAA (NA15NOS4780185), and by

471

an Institutional Grant (NA14OAR4170102) to the Texas Sea Grant College Program

472

from the National Sea Grant Office, NOAA.

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References (1) Dittmar, T. Reasons Behind the Long-Term Stability of Dissolved Organic Matter. In Biogeochemistry of Marine Dissolved Organic Matter (Second Edition); Carlson, C. A., Ed.; Academic Press: Boston, 2015; pp 369–388. (2) Dittmar, T.; Paeng, J. A Heat-Induced Molecular Signature in Marine Dissolved Organic Matter. Nat. Geosci. 2009, 2 (3), 175–179. (3) Dittmar, T.; Kattner, G. Recalcitrant Dissolved Organic Matter in the Ocean: Major Contribution of Small Amphiphilics. Mar. Chem. 2003, 82 (1–2), 115–123. (4) Benner, R. Chemical Composition and Reactivity. In Biogeochemistry of Marine Dissolved Organic Matter (First Edition); Hansell, D. A., Carlson, C. A., Eds.; Academic Press: Boston, 2002; pp 59–90. (5) Chiou, C. T.; Malcolm, R. L.; Brinton, T. I.; Kile, D. E. Water Solubility Enhancement of Some Organic Pollutants and Pesticides by Dissolved Humic and Fulvic Acids. Environ. Sci. Technol. 1986, 20 (5), 502–508. (6) De Paolis, F.; Kukkonen, J. Binding of Organic Pollutants to Humic and Fulvic Acids: Influence of PH and the Structure of Humic Material. Chemosphere 1997, 34 (8), 1693–1704. (7) Moran, M. A.; Hodson, R. E. Formation and Bacterial Utilization of Dissolved Organic Carbon Derived from Detrital Lignocellulose. Limnol. Oceanogr. 1989, 34 (6), 1034–1047. (8) Bouillon, S.; Yambélé, A.; Spencer, R. G. M.; Gillikin, D. P.; Hernes, P. J.; Six, J.; Merckx, R.; Borges, A. V. Organic Matter Sources, Fluxes and Greenhouse Gas Exchange in the Oubangui River (Congo River Basin). Biogeosciences Katlenburg-Lindau 2012, 9 (6), 2045. (9) Hertkorn, N.; Ruecker, C.; Meringer, M.; Gugisch, R.; Frommberger, M.; Perdue, E. M.; Witt, M.; Schmitt-Kopplin, P. High-Precision Frequency Measurements: Indispensable Tools at the Core of the Molecular-Level Analysis of Complex Systems. Anal. Bioanal. Chem. 2007, 389 (5), 1311–1327. (10) Hawkes, J. A.; Dittmar, T.; Patriarca, C.; Tranvik, L. J.; Bergquist, J. Evaluation of the Orbitrap Mass Spectrometer for the Molecular Fingerprinting Analysis of Natural Dissolved Organic Matter (DOM). Anal. Chem. 2016, 88 (15), 7698–7704. (11) Zark, M.; Christoffers, J.; Dittmar, T. Molecular Properties of Deep-Sea Dissolved Organic Matter Are Predictable by the Central Limit Theorem: Evidence from Tandem FT-ICR-MS. Mar. Chem. 2017, 191, 9–15. (12) Hertkorn, N.; Frommberger, M.; Witt, M.; Koch, B. P.; Schmitt-Kopplin, P.; Perdue, E. M. Natural Organic Matter and the Event Horizon of Mass Spectrometry. Anal. Chem. 2008, 80 (23), 8908–8919. (13) Hawkes, J. A.; Patriarca, C.; Sjöberg, P. J. R.; Tranvik, L. J.; Bergquist, J. Extreme Isomeric Complexity of Dissolved Organic Matter Found across Aquatic Environments. Limnol. Oceanogr. Lett. 2018, n/a-n/a. (14) Dittmar, T.; Stubbins, A. Dissolved Organic Matter In Aquatic Systems. Treatise Geochem. Second Ed. Elsevier 2014, 125–156. (15) May, J. C.; Goodwin, C. R.; Lareau, N. M.; Leaptrot, K. L.; Morris, C. B.; Kurulugama, R. T.; Mordehai, A.; Klein, C.; Barry, W.; Darland, E.; et al. Conformational Ordering of Biomolecules in the Gas Phase: Nitrogen Collision

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(16) (17) (18) (19)

(20)

(21)

(22)

(23)

(24)

(25)

(26)

(27)

(28)

(29)

Cross Sections Measured on a Prototype High Resolution Drift Tube Ion MobilityMass Spectrometer. Anal. Chem. 2014, 86 (4), 2107–2116. May, J. C.; McLean, J. A. Ion Mobility-Mass Spectrometry: Time-Dispersive Instrumentation. Anal. Chem. 2015, 87 (3), 1422–1436. McDaniel, E. W.; Mason, E. A. The Mobility and Diffusion of Ions in Gases; 1973. McDaniel, E. W. Collision Phenomena in Ionized Gases. N. Y. Wiley 1964 1964. Fenn, L. S.; Kliman, M.; Mahsut, A.; Zhao, S. R.; McLean, J. A. Characterizing Ion Mobility-Mass Spectrometry Conformation Space for the Analysis of Complex Biological Samples. Anal. Bioanal. Chem. 2009, 394 (1), 235–244. Baker, E. S.; Clowers, B. H.; Li, F.; Tang, K.; Tolmachev, A. V.; Prior, D. C.; Belov, M. E.; Smith, R. D. Ion Mobility Spectrometry–Mass Spectrometry Performance Using Electrodynamic Ion Funnels and Elevated Drift Gas Pressures. J. Am. Soc. Mass Spectrom. 2007, 18 (7), 1176–1187. Gaspar, A.; Kunenkov, E. V.; Lock, R.; Desor, M.; Perminova, I.; Schmitt-Kopplin, P. Combined Utilization of Ion Mobility and Ultra-High-Resolution Mass Spectrometry to Identify Multiply Charged Constituents in Natural Organic Matter. Rapid Commun. Mass Spectrom. 2009, 23 (5), 683–688. Lanucara, F.; Holman, S. W.; Gray, C. J.; Eyers, C. E. The Power of Ion MobilityMass Spectrometry for Structural Characterization and the Study of Conformational Dynamics. Nat. Chem. 2014, 6 (4), nchem.1889. Hines, K. M.; May, J. C.; McLean, J. A.; Xu, L. Evaluation of Collision Cross Section Calibrants for Structural Analysis of Lipids by Traveling Wave Ion Mobility-Mass Spectrometry. Anal. Chem. 2016, 88 (14), 7329–7336. Dittmar, T.; Koch, B.; Hertkorn, N.; Kattner, G. A Simple and Efficient Method for the Solid-Phase Extraction of Dissolved Organic Matter (SPE-DOM) from Seawater. Limnol Ocean. Methods 2008, 6 (6), 230–235. Tao, L.; McLean, J. R.; McLean, J. A.; Russell, D. H. A Collision Cross-Section Database of Singly-Charged Peptide Ions. J. Am. Soc. Mass Spectrom. 2007, 18 (7), 1232–1238. Buszewski, B.; Noga, S. Hydrophilic Interaction Liquid Chromatography (HILIC)—a Powerful Separation Technique. Anal. Bioanal. Chem. 2012, 402 (1), 231–247. Petras, D.; Koester, I.; Da Silva, R.; Stephens, B. M.; Haas, A. F.; Nelson, C. E.; Kelly, L. W.; Aluwihare, L. I.; Dorrestein, P. C. High-Resolution Liquid Chromatography Tandem Mass Spectrometry Enables Large Scale Molecular Characterization of Dissolved Organic Matter. Front. Mar. Sci. 2017, 4, 405. Kujawinski, E. B.; Behn, M. D. Automated Analysis of Electrospray Ionization Fourier Transform Ion Cyclotron Resonance Mass Spectra of Natural Organic Matter. Anal. Chem. 2006, 78 (13), 4363–4373. Stubbins, A.; Spencer, R. G. M.; Chen, H.; Hatcher, P. G.; Mopper, K.; Hernes, P. J.; Mwamba, V. L.; Mangangu, A. M.; Wabakanghanzi, J. N.; Six, J. Illuminated Darkness: Molecular Signatures of Congo River Dissolved Organic Matter and Its Photochemical Alteration as Revealed by Ultrahigh Precision Mass Spectrometry. Limnol. Oceanogr. 2010, 55 (4), 1467–1477.

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(30) Liu, Z.; Sleighter, R. L.; Zhong, J.; Hatcher, P. G. The Chemical Changes of DOM from Black Waters to Coastal Marine Waters by HPLC Combined with Ultrahigh Resolution Mass Spectrometry. Estuar. Coast. Shelf Sci. 2011, 92 (2), 205–216. (31) Hertkorn, N.; Harir, M.; Koch, B. P.; Michalke, B.; Schmitt-Kopplin, P. High-Field NMR Spectroscopy and FTICR Mass Spectrometry: Powerful Discovery Tools for the Molecular Level Characterization of Marine Dissolved Organic Matter. Biogeosciences 2013, 10 (3), 1583–1624. (32) Smith, C. A.; Maille, G. O.; Want, E. J.; Qin, C.; Trauger, S. A.; Brandon, T. R.; Custodio, D. E.; Abagyan, R.; Siuzdak, G. METLIN: A Metabolite Mass Spectral Database. Ther. Drug Monit. 2005, 27 (6), 747–751. (33) Mason, E. A.; Schamp, H. W. Mobility of Gaseous Lons in Weak Electric Fields. Ann. Phys. 1958, 4 (3), 233–270. (34) Ogawa, H.; Amagai, Y.; Koike, I.; Kaiser, K.; Benner, R. Production of Refractory Dissolved Organic Matter by Bacteria. Science 2001, 292 (5518), 917–920. (35) Leenheer, J. A.; Croué, J.-P. Peer Reviewed: Characterizing Aquatic Dissolved Organic Matter. Environ. Sci. Technol. 2003, 37 (1), 18A-26A. (36) Rathgeb, A.; Causon, T.; Krachler, R.; Hann, S. From the Peat Bog to the Estuarine Mixing Zone: Common Features and Variances in Riverine Dissolved Organic Matter Determined by Non-Targeted Analysis. Mar. Chem. 2017, 194, 158–167. (37) Hao, Z.; Xiao, B.; Weng, N. Impact of Column Temperature and Mobile Phase Components on Selectivity of Hydrophilic Interaction Chromatography (HILIC). J. Sep. Sci. 2008, 31 (9), 1449–1464. (38) Alpert, A. J. Hydrophilic-Interaction Chromatography for the Separation of Peptides, Nucleic Acids and Other Polar Compounds. J. Chromatogr. A 1990, 499, 177–196. (39) Yoshida, T. Peptide Separation by Hydrophilic-Interaction Chromatography: A Review. J. Biochem. Biophys. Methods 2004, 60 (3), 265–280. (40) Guo, Y.; Srinivasan, S.; Gaiki, S. Investigating the Effect of Chromatographic Conditions on Retention of Organic Acids in Hydrophilic Interaction Chromatography Using a Design of Experiment. Chromatographia 2007, 66 (3–4), 223–229. (41) Ohno, T.; Sleighter, R. L.; Hatcher, P. G. Comparative Study of Organic Matter Chemical Characterization Using Negative and Positive Mode Electrospray Ionization Ultrahigh-Resolution Mass Spectrometry. Anal. Bioanal. Chem. 2016, 408 (10), 2497–2504. (42) D’Andrilli, J.; Cooper, W. T.; Foreman, C. M.; Marshall, A. G. An UltrahighResolution Mass Spectrometry Index to Estimate Natural Organic Matter Lability. Rapid Commun. Mass Spectrom. 2015, 29 (24), 2385–2401. (43) Repeta, D. J. Chemical Characterization and Cycling of Dissolved Organic Matter. In Biogeochemistry of Marine Dissolved Organic Matter (Second Edition); Carlson, D. A. H. A., Ed.; Academic Press: Boston, 2015; pp 21–63. (44) Hockaday, W. C.; Grannas, A. M.; Kim, S.; Hatcher, P. G. The Transformation and Mobility of Charcoal in a Fire-Impacted Watershed. Geochim. Cosmochim. Acta 2007, 71 (14), 3432–3445. (45) Mopper, K.; Stubbins, A.; Ritchie, J. D.; Bialk, H. M.; Hatcher, P. G. Advanced Instrumental Approaches for Characterization of Marine Dissolved Organic 26 ACS Paragon Plus Environment

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Environmental Science & Technology

(46)

(47)

(48)

(49)

(50) (51)

(52)

(53)

(54)

(55)

(56)

(57)

(58)

Matter:  Extraction Techniques, Mass Spectrometry, and Nuclear Magnetic Resonance Spectroscopy. Chem. Rev. 2007, 107 (2), 419–442. Hertkorn, N.; Permin, A.; Perminova, I.; Kovalevskii, D.; Yudov, M.; Petrosyan, V.; Kettrup, A. Comparative Analysis of Partial Structures of a Peat Humic and Fulvic Acid Using One- and Two-Dimensional Nuclear Magnetic Resonance Spectroscopy. J. Environ. Qual. Madison 2002, 31 (2), 375–387. Tang, K.; Page, J. S.; Smith, R. D. Charge Competition and the Linear Dynamic Range of Detection in Electrospray Ionization Mass Spectrometry1. J. Am. Soc. Mass Spectrom. 2004, 15 (10), 1416–1423. Hertkorn, N.; Benner, R.; Frommberger, M.; Schmitt-Kopplin, P.; Witt, M.; Kaiser, K.; Kettrup, A.; Hedges, J. I. Characterization of a Major Refractory Component of Marine Dissolved Organic Matter. Geochim. Cosmochim. Acta 2006, 70 (12), 2990–3010. Liesenfeld, D. B.; Habermann, N.; Owen, R. W.; Scalbert, A.; Ulrich, C. M. Review of Mass Spectrometry–Based Metabolomics in Cancer Research. Cancer Epidemiol. Prev. Biomark. 2013, 22 (12), 2182–2201. Viant, M. R.; Sommer, U. Mass Spectrometry Based Environmental Metabolomics: A Primer and Review. Metabolomics 2013, 9 (1), 144–158. Gika, H. G.; Theodoridis, G. A.; Plumb, R. S.; Wilson, I. D. Current Practice of Liquid Chromatography–mass Spectrometry in Metabolomics and Metabonomics. J. Pharm. Biomed. Anal. 2014, 87, 12–25. Rubert, J.; Zachariasova, M.; Hajslova, J. Advances in High-Resolution Mass Spectrometry Based on Metabolomics Studies for Food – a Review. Food Addit. Contam. Part A 2015, 32 (10), 1685–1708. Reyna, N. E.; Hardison, A.; Liu, Z. Influence of Major Storm Events on the Quantity and Composition of Particulate Organic Matter and the Phytoplankton Community in a Subtropical Estuary, Texas. Front. Mar. Sci. 2017, 4, 43. Tobias, D. J.; Brooks, C. L. Conformational Equilibrium in the Alanine Dipeptide in the Gas Phase and Aqueous Solution: A Comparison of Theoretical Results. J. Phys. Chem. 1992, 96 (9), 3864–3870. Chipot, C.; Jaffe, R.; Maigret, B.; Pearlman, D. A.; Kollman, P. A. Benzene Dimer:  A Good Model for Π−π Interactions in Proteins? A Comparison between the Benzene and the Toluene Dimers in the Gas Phase and in an Aqueous Solution. J. Am. Chem. Soc. 1996, 118 (45), 11217–11224. Hanus, M.; Kabeláč, M.; Rejnek, J.; Ryjáček, F.; Hobza, P. Correlated Ab Initio Study of Nucleic Acid Bases and Their Tautomers in the Gas Phase, in a Microhydrated Environment, and in Aqueous Solution. Part 3. Adenine. J. Phys. Chem. B 2004, 108 (6), 2087–2097. Dwivedi, P.; Bendiak, B.; Clowers, B. H.; Hill Jr., H. H. Rapid Resolution of Carbohydrate Isomers by Electrospray Ionization Ambient Pressure Ion Mobility Spectrometry-Time-of-Flight Mass Spectrometry (ESI-APIMS-TOFMS). J. Am. Soc. Mass Spectrom. 2007, 18 (7), 1163–1175. Zhu, M.; Bendiak, B.; Clowers, B.; Hill, H. H. Ion Mobility-Mass Spectrometry Analysis of Isomeric Carbohydrate Precursor Ions. Anal. Bioanal. Chem. 2009, 394 (7), 1853–1867.

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(59) Arrieta, J. M.; Mayol, E.; Hansman, R. L.; Herndl, G. J.; Dittmar, T.; Duarte, C. M. Dilution Limits Dissolved Organic Carbon Utilization in the Deep Ocean. Science 2015, 348 (6232), 331–333. (60) Dodds, J. N.; May, J. C.; McLean, J. A. Correlating Resolving Power, Resolution, and Collision Cross Section: Unifying Cross-Platform Assessment of Separation Efficiency in Ion Mobility Spectrometry. Anal. Chem. 2017, 89 (22), 12176– 12184. (61) Srebalus Barnes, C. A.; Hilderbrand, A. E.; Valentine, S. J.; Clemmer, D. E. Resolving Isomeric Peptide Mixtures:  A Combined HPLC/Ion Mobility-TOFMS Analysis of a 4000-Component Combinatorial Library. Anal. Chem. 2002, 74 (1), 26–36. (62) Dodds, J. N.; May, J. C.; McLean, J. A. Investigation of the Complete Suite of the Leucine and Isoleucine Isomers: Toward Prediction of Ion Mobility Separation Capabilities. Anal. Chem. 2017, 89 (1), 952–959.

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Table 1. Isomer percentages for different samples Sites ESI+ ESIShip Channel 7.5 ± 0.1 % 6.4 ± 2.3 % Aransas River 9.8 ± 0.2 % 13.1 ± 2.2 % Lavaca River 1 9.8 ± 0.2 % 7.2 ± 1.8 % Lavaca River 2 4.7 ± 2.3 % 9.4 ± 0.3 % Mission River 10.2 ± 0.7 % 7.2 ± 2.16 % Nueces Dam 10.2 ± 0.4 % 9.1 ± 2.5 % San Antonio River 1 12.3 ± 1.6 % 10.0 ± 0.7 % San Antonio River 2 9.5 ± 6.5 % 10.0 ± 2.5 %

669

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670

Figure 1. Chromatograms of LC retention time vs. ion intensity under ESI+ mode.

671

Different fractions (F1-F5) are determined based on the mobile phase (see the main text)

672

and the distribution of chromatographic peaks. (a) Riverine samples under ESI+ mode;

673

(b) Ship Channel sample under ESI+ mode.

674 675

Figure 2. Chromatograms and spectra for ion 437.1943 (m/z). (a) Chromatogram of

676

compounds with different elution times (Green: elution time 11.3 min; Yellow: elution

677

time 18.5 min). (b) Parent ion spectrum of 437.1943 at 11.3 min. (c) Parent ion spectrum

678

of 437.1943 at 18.5 min. (d) Product ions spectrum of 437.1943 at 11.3 min. (e) Product

679

ions spectrum of 437.1943 at 18.5 min.

680 681

Figure 3. Scatter plot of CCS (Ω) vs. m/z. Squares stand for published standard

682

biomolecules (tetraalkylammonium salt cations, carbohydrates, peptides and lipids).15

683

CCS generally increases with an increasing m/z for biomolecules, and the relationship

684

can fit with a power-law function. Natural DOM showed the same trend in the CCS-m/z

685

relationship but possess lower CCS values compared the standard biomolecules given the

686

same molecular weights (p < 0.05). The trend becomes clearer as molecular weight

687

increases.

688 689

Figure 4. (a) Methyl-α-Glucopyranosides (α-MeGlc).57 (b) Methyl-β-Glucopyranosides

690

(β-MeGlc).57 (c) alditols cellobiitol (Glcβ1-4 Glcβ1-4 Glcβ1-4 Glc-ol).58 (d)

691

maltotetraitol (Glcα1-4 Glcα1-4 Glcα1-4 Glc-ol).58 (e) Compounds 249.1556 (± 1.5 ppm)

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shows two isomers with drift times of 29.3 ms and 22.94 ms. (f) Compounds 340.2571 (±

693

0.3 ppm) shows two isomers with drift time of 21.11 ms and 24.31 ms.

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(a) ESI+ Mode Riverine Samples

8.5

Figure 1

― Aransas River (AR) ― Nueces Dam (DAM) ― Mission River (MR) ― Lavaca River 1 (LR1) ― Lavaca River 2 (LR2) ― San Antonio River 1 (SR1) ― San Antonio River 2 (SR2)

8 7.5

F3 (9-15 min)

F2 (3-9 min)

7 6.5 6 5.5 5

F1 (0-3 min)

4.5 4 3.5 3 2.5

F5 (20-21 min)

F4 (15-20 min)

2 1.5 1 0.5 0 0.5

×10 7 7

1

1.5

2

2.5

3

3.5

4

4.5

5

5.5

6

6.5

7

7.5

8

8.5

9

9.5

10

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11

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12

12.5

13

13.5

14

14.5

15

15.5

16

16.5

17

17.5

18

18.5

19

19.5

20

20.5

(b) ESI+ Mode Marine Samples

6.5

F2 (3-9 min)

6 5.5 5 4.5 4 3.5 3 2.5

F3 (9-15 min)

F1 (0-3 min)

2 1.5 1

F5 (20-21 min)

F4 (15-20 min)

0.5 0 0.5

1

1.5

2

2.5

3

3.5

4

4.5

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6

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7

7.5

8

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Counts vs. Acquisition Time (min)

12.5

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x10 6

(a)

3.3

Figure 2

3.2 3.1 3 2.9 2.8 2.7 2.6 2.5 2.4 2.3 2.2 2.1 2 1.9 1.8 1.7 1.6 1.5 1.4 1.3 1.2 1.1 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 8.6

8.8

9

9.2

9.4

9.6

9.8

10 10.2 10.4 10.6 10.8 11 11.2 11.4 11.6 11.8 12 12.2 12.4 12.6 12.8 13 13.2 13.4 13.6 13.8 14 14.2 14.4 14.6 14.8 15 15.2 15.4 15.6 15.8 16 16.2 16.4 16.6 16.8 17 17.2 17.4 17.6 17.8 18 18.2 18.4 18.6 18.8 19 19.2 19.4 19.6 19.8 20 20.2 20.4 20.6 20.8 21 21.2 Counts vs. Acquisition Time (min)

4

x10 4.6 4.4 4.2

x10 4

(b)

2.6 2.5 2.4 2.3 2.2 2.1 2 1.9 1.8 1.7 1.6 1.5 1.4 1.3 1.2 1.1 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

437.1943

4 3.8 3.6 3.4 3.2 3 2.8 2.6 2.4 2.2 2 1.8 1.6

438.1977

1.4 1.2 1 0.8 0.6

439.2005

0.4 0.2 0 434.6

434.8

435

435.2

435.4

435.6

435.8

436

436.2

436.4

436.6

436.8

437

437.2

437.4

437.6 437.8 438 438.2 Counts vs. Mass-to-Charge (m/z)

438.4

438.6

438.8

439

439.2

439.4

439.6

439.8

440

440.2

440.4

440.6

440.8

441

437.1943

438.1976 439.2005

441.2

x10 2 5.2 5 4.8 4.6

(c)

433

433.5

434

434.5

435

435.5

436

436.5

437

437.5 438 438.5 Counts vs. Mass-to-Charge (m/z)

439

439.5

440

440.5

441

441.5

442

442.5

443

x10 2

(d)

7.25 7 6.75 6.5 6.25 6 5.75 5.5 5.25 5 4.75 4.5 4.25 4 3.75 3.5 3.25 3 2.75 2.5 2.25 2 1.75 1.5 1.25 1 0.75 0.5 0.25 0

437.1943

4.4 4.2 4

87.0435

3.8 3.6 3.4 3.2 3 2.8 2.6 2.4 2.2 2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0

59.0485 421.3610

30

40

50

60

70

80

90

100

110 120

130

140 150

160

170

180 190

200

210 220

230 240 250 260 270 280 Counts vs. Mass-to-Charge (m/z)

290

300

310 320

330

340 350

360

370 380

390

400

410 420

430

440 450

460

470 480

(e)

130.0680

112.0573 437.1943

364.3407 90

ACS Paragon Plus Environment

100

110

120

130

140

150

160

170

180

190

200

210

220

230

240

250

260 270 280 290 300 Counts vs. Mass-to-Charge (m/z)

310

320

330

340

350

360

370

380

390

400

410

420

430

440

450

460

470

Environmental Science & Technology

Page 34 of 35

CCS vs. m/z (Positive)

Figure 3

500 450 400 350 Tetraalkylammonium Salt Cation

Ω (Å2)

300

Carbohydrates Peptides

250

Lipids Ship Channel

200

Aransas River Nueces Dam

150

Lavaca River 1 Lavaca River 2

100

Mission River San Antonio River 1

50

San Antonio River 2 0 0

500

1000

1500

m/z ACS Paragon Plus Environment

2000

2500

Page 35 of 35

Environmental Science & Technology

Figure 4

(a): Methyl-α-Glucopyranosides (α-MeGlc)

(b): Methyl-β-Glucopyranosides (β-MeGlc)

(c): maltotetraitol (Glcα1-4 Glcα1-4 Glcα1-4 Glc-ol)

(d): alditols cellobiitol (Glcβ1-4 Glcβ1-4 Glcβ1-4 Glc-ol)

(e)

(f)

ACS Paragon Plus Environment