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Molecular insights on dissolved organic matter transformation by supraglacial microbial communities Runa Antony, Amanda S. Willoughby, Amanda M. Grannas, Victoria Catanzano, Rachel L Sleighter, Meloth Thamban, Patrick G. Hatcher, and Shanta Nair Environ. Sci. Technol., Just Accepted Manuscript • Publication Date (Web): 22 Mar 2017 Downloaded from http://pubs.acs.org on March 22, 2017
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Molecular insights on dissolved organic matter transformation by supraglacial microbial communities
Runa Antony1*, Amanda S. Willoughby2, Amanda M. Grannas3, Victoria Catanzano3, Rachel L. Sleighter2,4, Meloth Thamban1, Patrick G. Hatcher2, and Shanta Nair5
1
National Centre for Antarctic and Ocean Research, Headland Sada, Vasco-Da-Gama, Goa 403 804, India 2
Old Dominion University, Department of Chemistry and Biochemistry, Norfolk, VA 23529, USA 3
Villanova University, Department of Chemistry, Villanova, PA 19085, USA 4
FBSciences, Inc. (Research and Development), Norfolk, VA 23508
5
National Institute of Oceanography, Dona Paula, Goa 403 004, India
*Correspondance to: Runa Antony, National Centre for Antarctic and Ocean Research, Headland Sada, Vasco-Da-Gama, Goa 403 804, India. Office phone: +91 832 2525632, Fax: +91 832 2520877, E-mail:
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Abstract
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Snow overlays the majority of Antarctica and is an important repository of dissolved organic
3
matter (DOM). DOM transformations by supraglacial microbes are not well understood. We use
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ultrahigh resolution mass spectrometry to elucidate molecular changes in snowpack DOM by in
5
situ microbial processes (up to 55 days) in a coastal Antarctic site. Both autochthonous and
6
allochthonous DOM is highly bio-available and is transformed by resident microbial
7
communities through parallel processes of degradation and synthesis. DOM thought to be of a
8
more refractory nature, such as dissolved black carbon and carboxylic-rich alicyclic molecules,
9
was also rapidly and extensively reworked. Microbially reworked DOM exhibits an increase in
10
the number and magnitude of N-, S-, and P-containing formulas, is less oxygenated, and more
11
aromatic when compared to the initial DOM. Shifts in the heteroatom composition suggest that
12
microbial processes may be important in the cycling of not only C, but other elements such as
13
N, S, and P. Microbial reworking also produces photo-reactive compounds, with potential
14
implications for DOM photochemistry. Refined measurements of supraglacial DOM and their
15
cycling by microbes is critical for improving our understanding of supraglacial DOM cycling and
16
the biogeochemical and ecological impacts of DOM export to downstream environments.
17 18
Introduction
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Supraglacial (on the surface of glaciers and ice sheets) organic matter is highly complex.
20
Microbially-derived proteins, lipids, and other organic molecules are dominant, together with
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organic compounds derived from the deposition of marine aerosols, vascular plant material,
22
fossil fuel combustion, and biomass burning by-products.1-5 Dissolved organic matter (DOM) in
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supraglacial environments is biologically available6 and provides carbon to resident microbial
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communities as well as to downstream ecosystems.4 DOM uptake by microbial communities, in
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turn, results in organic metabolites with different properties.7,8 These transformations modify
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the properties of DOM and exert a strong influence on the nature of supraglacial DOM,3 a
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portion of which is exported to downstream aquatic ecosystems. At one extreme, highly
28
refractory DOM molecules could contribute to carbon storage in the ice sheets until melting
29
processes transport the stored carbon to downstream ecosystems. At the other extreme, bio-
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available DOM would form an important resource for supraglacial heterotrophs.2,6 Additionally,
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the inorganic nutrients regenerated during the decomposition of DOM may stimulate
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autotrophic microbial communities.9 This in turn could impact the uptake of atmospheric
33
carbon dioxide and sustenance of heterotrophic bacterial communities through production of
34
new carbon. Although supraglacial environments contain significant stores of organic carbon,10
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which merits consideration in studies addressing both regional and global carbon cycle, very
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little is understood about the diversity of compounds that comprise supraglacial DOM and their
37
interactions
38
transformations of DOM beyond bulk examination and compound specific analyses are lacking.
39
This necessitates a more fundamental assessment of DOM composition and reactivity, in order
40
to better understand carbon cycling on ice sheets.
with
resident
microbial
communities.
Assessments
of
biogeochemical
41 42
We use ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry
43
(FTICR-MS) coupled to electrospray ionisation (ESI), to detect molecular changes in DOM
44
associated with microbial processes. FTICR-MS has the unique ability to resolve peaks and
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determine the exact masses of the thousands of individual components present in a single DOM
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sample, thereby providing an opportunity to explore their reactivity within biogeochemical
47
processes.1,7,11-13 This study provides novel molecular insights on the microbial processing of
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supraglacial DOM. The new information gained on DOM transformation on the ice sheet
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surface will help elucidate the drivers of DOM dynamics and improve our ability to predict the
50
fate of this material in supraglacial and downstream environments. Such information from
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glaciers worldwide is crucial to better constrain the role of glaciers in the global carbon cycle,
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especially as climate warming accelerates ice loss14,15 and associated carbon is released to
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downstream environments.15
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Materials and methods
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Study site and sampling
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Surface snow samples were collected from the Princess Elizabeth Land region (69°28'S, 76°09'E)
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in East Antarctica. Snowpack DOM in this region is characterised by a complex mixture of both
59
autochthonous DOM (derived from in situ microbial metabolism) and allochthonous DOM
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(derived from local as well as distant sources).5 Surface snow in this region also harbours
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diverse microbial communities.16 A clean site (ca. 50 m upwind from the helicopter landing site)
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was selected and surface snow (ca. 10 cm depth) was homogenously mixed using a sterile
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spatula. This snow was sub-sampled into 14 acid-cleaned (1 M HCl), pre-combusted (475 °C for
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4 h) 650 mL capacity sterile quartz tubes with Teflon caps.
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Field incubations and sample processing
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One set of tubes consisting of snow samples with the naturally occurring microbial assemblages
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was covered with aluminium foil to prevent light penetration. This set of tubes was incubated in
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the field (in the snowpack) under ambient conditions to assess the microbial processing of
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snowpack DOM. Another set consisting of control snow samples poisoned with sodium azide
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(NaN3, ca. 6.5 mg L-1) and wrapped in aluminium foil, was incubated as above. NaN3 was
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injected into the snow samples using a sterile Hamilton microliter syringe in several line
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injections. After injection, the snow samples were mixed homogenously using a sterile spatula.
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Field blanks consisted of pre-cleaned sterile quartz tubes containing ultrapure water were
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exposed to the sampling site conditions for the same length of time as the sample. All samples
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were incubated in the field and retrieved after 10, 15, 35, 45, and 55 days. Ambient average
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daily air temperatures varied from -4.4°C to +5.1°C. The snow samples before incubation, and
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those retrieved from the field at specific time points, were processed immediately on site. DOM
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was extracted by solid-phase extraction (SPE) using PPL cartridges (Agilent Bond Elut-PPL)
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following the method outlined in Dittmar et al.17
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Sample volumes of approximately 300 ml at an average DOC concentration of 69 ± 20 μg L-1
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were loaded onto fresh PPL cartridges. Although sample processing through SPE can have a
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molecular bias and a somewhat selective view of the total DOM pool, SPE is widely used for OM
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desalting and concentration, with PPL cartridges reported as the most effective sorbent for
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DOM extraction from a wide range of environments.18 SPE has been routinely used in
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environmental studies involving molecular characterisation of DOM by FTICR-MS for
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compositional assessments of the DOM pool,1,2 as well as to characterise the reactivity of
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specific molecules in biogeochemical processes.7,8 PPL cartridges were thus selected based on
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their ability to extract both non-polar and polar solutes from the environment, and for their
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high extraction efficiencies compared to other SPE sorbents,17 thereby providing improved
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selectivity for the vast range of compounds constituting the bulk of this supraglacial DOM. PPL
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cartridges after desalting were dried and shipped at -20ᵒC to Old Dominion University and
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stored under the same conditions until elution, which occurred immediately prior to FTICR-MS
95
analysis.
96 97
FTICR-MS analysis
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Samples were analysed using a Bruker Daltonics 12 T Apex Qe FTICR-MS instrument, operated
99
in both negative and positive electrospray ionisation modes, using parameters consistent with
100
those described previously.5 Specific details of sample preparation, and instrument parameters,
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are available as Supplemental Information. The large and complex data sets arising from FTICR-
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MS analysis and the significant amount of time required for data processing made replicate
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incubations untenable. Solid-phase PPL extractions of environmental DOM samples have been
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shown to be highly replicable with standard deviations of less than 6%.17 Also, prior molecular
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characterisation of DOM from Antarctic snowpack5 and other samples19 has shown that FTICR
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mass spectra are very reproducible and generate consistent mass lists for replicate analyses.
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Because the same exact extraction procedure and same instrumental parameters were
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employed for all samples collected during the present study, we can assume that the mass
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spectra generated for each sample would be representative and reproducible, allowing for
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reliable elemental formula assignments.
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Following formula assignments, molecules were categorised by compound class using various
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chemical metrics. Double bond equivalent (DBE) values are calculated as DBE = 1 + C − 0.5H +
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0.5N + 0.5P.13 Molecular formulas with DBE/C < 0.3 and H/C ≥ 1 are unambiguously assigned as
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aliphatics.13 The modified aromaticity index (AImod), which is a measure of the probable
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aromaticity for a given molecular formula assuming that half of the oxygen atoms are doubly
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bound and half are present as σ bonds was calculated as: AImod = (1 + C - 0.5O - S - 0.5[N + P +
118
H])/(C - 0.5O - N – S - P).20 Formulas with AImod ≥ 0.5 and < 0.67 are assigned as aromatics, while
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formulas with AImod ≥ 0.67 are assigned as condensed aromatics21 and are referred to here as
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dissolved black carbon-like (DBC-like). The following compound classes were defined based on
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Hockaday et al.12 and Ohno et al.22: lipids (O/C = 0−0.2, H/C = 1.7−2.2), proteins (O/C = 0.2−0.6,
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H/C = 1.5−2.2, N/C ≥ 0.05), lignin (O/C = 0.1−0.6, H/C = 0.6−1.7, AImod < 0.67), carbohydrates
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(O/C = 0.6−1.2, H/C = 1.5−2.2), tannins (O/C = 0.6−1.2, H/C = 0.5−1.5, AImod < 0.67), and
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unsaturated hydrocarbons (O/C = 0−0.1, H/C = 0.7−1.5). Carboxylic-rich alicyclic molecules
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(CRAM) were defined as having DBE/C = 0.30−0.68; DBE/H = 0.20−0.95; DBE/O = 0.77−1.75.11
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We use the DBE-O parameter (obtained by subtracting the number of oxygen atoms from DBE
127
value) for a simple approximation for pure C-C unsaturation.23,24
128 129
After exact elemental formulas had been assigned, formulas present in the microbe treatment
130
and the control were compared. Following incubation, any formula present in the microbe
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treatment that was also present in the control (but not in the initial sample) was attributed to
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abiotic dark reactions and was not considered further. These constituted up to 30% of the total
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identified formulas. Similarly, following incubation, any formula that disappeared in the
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microbe treatment and also in the control was attributed to abiotic dark reactions and was not
135
considered further. These constituted up to 3% of the total identified formulas. We conclude
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that the formulas that were commonly produced and/or disappeared between the microbe
137
treatment and the control are due to abiotic processes and that the unique formulas in the
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microbe treatment are due to biological activity within this treatment. Thus, formulas detected
139
solely in the microbe treatment were regarded as present due to microbial processing and were
140
assigned as microbe-only. Further discussions of data with respect to changes in DOM
141
composition are from the microbe-only assignments. A comparison of molecular species
142
detected using negative and positive ion modes shows that 9), compared to only 9% of the formulas in the
467
initial DOM. In addition, the contribution of aromatic formulas to the total DOM pool increased
468
by 43% in the 55-day time point. Microbial reworking may be an important mechanism for the
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production of photo-labile DOM, which may aid in faster and more extensive degradation of
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DOM on the glacier surface during the summer when much of the glacier surface is exposed to
471
longer hours of direct sunlight. Microbial processes are an important mechanism for cycling of
472
supraglacial DOM and may play a crucial role in determining the composition of bulk DOM in
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this environment. However, it is important to note that while the snowpack harbours diverse
474
and active microbial communities, the metabolic potential for utilising the wide diversity of
475
DOM compounds may not be uniformly distributed in all locations. As our analyses are limited
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to a single location on the coastal Antarctic ice sheet, and there are a number of environmental
477
variables (such as light, new DOM inputs, etc.) that were controlled and that may have
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influenced microbial transformation of DOM, it is suggested that the findings presented here
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should be interpreted as a ‘snapshot’ of DOM transformations within the snowpack in late
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summer conditions in coastal East Antarctica. Nevertheless, given the presence of
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autochthonous and allochthonous DOM on glacier and ice sheet surfaces, we believe that the
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processes investigated here under in situ conditions should be generally applicable across
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similar supraglacial environments. This invites further comparative studies to determine DOM
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transformation processes in response to spatial, temporal, and environmental variation. A
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comprehensive compositional and structural characterisation of DOM from differing glacier
486
environments using powerful tools such as FTICR-MS and high field NMR would aid in a better
487
understanding of specific DOM molecules that participate in biogeochemical processes or that
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are specifically linked to glacier ecosystems or microbial metabolism. This will ultimately lead to
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novel insights into the supraglacial carbon cycle and assist in identifying markers for microbially
490
modified DOM. This is especially relevant as annual release of DOC from the Antarctic ice sheet
491
to downstream marine ecosystems is significant10 and is expected to continue increasing in
492
coming decades14,15 with unforeseen impacts on marine food webs.
493 494
Acknowledgements
495
We thank the Ministry of Earth Sciences (India) and the Director, NCAOR for support. We are
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grateful for the support from the members and crew of the 33rd Indian Scientific Expedition to
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Antarctica. Shri M. J. Beg, Director (Logistics), NCAOR, is thanked for providing all necessary
498
logistic support for the sampling, as well as, for the safe transport of samples to Old Dominion
499
University. We thank Progress station (Russia) for providing the temperature data. We also
500
thank the College of Sciences Major Instrumentation Cluster at ODU for their assistance with
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the FTICR-MS data acquisition. AMG also gratefully acknowledges the Henry Dreyfus Teacher-
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Scholar Awards Program of the Camille and Henry Dreyfus Foundation for financial support. The
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FTICR-MS analysis was funded by the National Science Foundation (Antarctic Glaciology
504
Program #0739691).
505
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Additional Information
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The authors declare no competing financial interests.
508 509
Author Contributions Statement
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R.A. designed the research and performed the field experiments. A.S.W. carried out the FTICR-
511
MS analysis. A.M.G., A.S.W., V.C and R.A. processed the FTICR-MS data. R.A. wrote the
512
manuscript. A.M.G., A.S.W., R.L.S., T.M., P.G.H. and S.N. contributed to the discussion and
513
interpretations, as well as edited the manuscript.
514 515
Supporting Information
516
Specific details of sample preparation and instrument parameters, Table S1-S2, and 3 figures
517
(Figures S1–S3), are available as Supplemental Information.
518 519
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Table legends
734
Table 1. Numbers of all assigned molecular formulas for snowpack DOM before and after dark
735
incubation.
736 737
Table 2. Properties of Bio-labile, Bio-resistant, and Bio-produced DOM identified in the
738
snowpack*.
739
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740
Figure legends
741
Figure 1. Change in DOC concentrations in the snow sample during the field incubation.
742 743
Figure 2. van Krevelen distributions of dissolved organic matter molecular formulas containing
744
C, H, O, N, S, and P, which were identified in the original snowpack. Boxes designate
745
biomolecular compound classes, as described in the manuscript. The different compound
746
categories are plotted in decreasing order of abundance (CHO followed by CHOS, CHON, others,
747
and CHOP).
748 749
Figure 3. van Krevelen diagram showing all identified DOM formulas in the initial snow sample
750
as well as bio-labile, bio-produced, and bio-resistant DOM formulas identified at the various
751
dark incubation time points. Lines drawn to describe aromaticity are based on the modified
752
aromaticity index, as described in the manuscript.
753 754
Figure 4. van Krevelen plots of the formulas containing N, S, and P for the initial and 55-day
755
microbially altered snowpack DOM. Color represents the relative peak magnitude of associated
756
peaks (as the percentage of the summed total magnitude of all peaks assigned formulas). Points
757
are colored by the logarithm (base 10) of peak magnitude. Note that formulas with N, S, and P
758
atoms comprise these elements present alone or in combination with each other.
759 760
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761
Table 1. Numbers of all assigned molecular formulas for snowpack DOM before and after dark
762
incubation. Molecular class*
Initial DOM
After dark incubation**
(No. of formulas)
(No. of formulas) Day 10
Day 15
Day 35
Day 45
Day 55
All identified formulas
2338
543
394
1038
659
494
Terrestrial OM
1139
236
201
475
310
222
Autochthonous OM
821
196
113
355
279
147
CRAM
414
74
71
171
83
61
Unsaturated hydrocarbons
181
23
29
72
36
42
Carbohydrates
75
58
17
37
10
26
Aliphatic
1404
364
194
560
456
275
Aromatic
86
24
40
76
22
26
Condensed aromatic
44
22
16
48
15
26
763
* Note that the number of formulas listed in each column do not add up to the total, because formulas can fall into
764
multiple categories (i.e., the aliphatic and aromatic formulas also include formulas belonging to the terrestrial,
765
autochthonous, CRAM, unsaturated hydrocarbon, and/or carbohydrate classes).
766
** Reported identified formulas after dark incubation includes compounds in the initial sample that resisted
767
degradation as well as new compounds formed during the incubation.
768 769 770 771 772 37 ACS Paragon Plus Environment
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773
Page 38 of 43
Table 2. Properties of Bio-labile, Bio-resistant, and Bio-produced DOM identified in the snowpack*. Property
Compound category Bio-resistant
Total identified formulas
Bio-labile
Bio-produced
1
3351
2242
C
20.00
24.33
23.87
O
10.00
6.94
6.64
H
36.00
35.93
35.30
P
0.00
0.06
0.07
S
1.00
0.29
0.27
N
0.00
0.42
0.46
O/C
0.50
0.31
0.31
H/C
1.80
1.51
1.52
DBE
3.00
7.66
7.56
DBE/C
0.15
0.31
0.31
DBE-O
-7.00
0.72
0.92
AImod
0.00
0.19
0.19
MW
467
460
449
774
* Parameters are the number of assigned molecular formulas, number-average atomic numbers per formula,
775
atomic O/C and H/C ratios, double bond equivalents (DBE), average DBE/C ratios, DBE minus the number of oxygen
776
atoms (DBE-O), modified aromaticity index (AImod), and number-averaged molecular weight (MW).
777 778
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Figure 1. Change in DOC concentrations in the snow sample during the field incubation. 106x127mm (300 x 300 DPI)
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Environmental Science & Technology
Figure 2. van Krevelen distributions of dissolved organic matter molecular formulas containing C, H, O, N, S, and P, which were identified in the original snowpack. Boxes designate biomolecular compound classes, as described in the manuscript. The different compound categories are plotted in decreasing order of abundance (CHO followed by CHOS, CHON, others, and CHOP). 66x51mm (300 x 300 DPI)
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Figure 3. van Krevelen diagram showing all identified DOM formulas in the initial snow sample as well as bio-labile, bio-produced, and bio-resistant DOM formulas identified at the various dark incubation time points. Lines drawn to describe aromaticity are based on the modified aromaticity index, as described in the manuscript. 106x63mm (300 x 300 DPI)
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Environmental Science & Technology
Figure 4. van Krevelen plots of the formulas containing N, S, and P for the initial and 55-day microbially altered snowpack DOM. Color represents the relative peak magnitude of associated peaks (as the percentage of the summed total magnitude of all peaks assigned formulas). Points are colored by the logarithm (base 10) of peak magnitude. Note that formulas with N, S, and P atoms comprise these elements present alone or in combination with each other. 131x101mm (300 x 300 DPI)
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Table of contents (TOC) art 55x49mm (300 x 300 DPI)
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