Molecular Insights on Dissolved Organic Matter Transformation by

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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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Environmental Science & Technology

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: [email protected] 1 ACS Paragon Plus Environment

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Abstract

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Snow overlays the majority of Antarctica and is an important repository of dissolved organic

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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

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situ microbial processes (up to 55 days) in a coastal Antarctic site. Both autochthonous and

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allochthonous DOM is highly bio-available and is transformed by resident microbial

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communities through parallel processes of degradation and synthesis. DOM thought to be of a

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more refractory nature, such as dissolved black carbon and carboxylic-rich alicyclic molecules,

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was also rapidly and extensively reworked. Microbially reworked DOM exhibits an increase in

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the number and magnitude of N-, S-, and P-containing formulas, is less oxygenated, and more

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aromatic when compared to the initial DOM. Shifts in the heteroatom composition suggest that

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microbial processes may be important in the cycling of not only C, but other elements such as

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N, S, and P. Microbial reworking also produces photo-reactive compounds, with potential

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implications for DOM photochemistry. Refined measurements of supraglacial DOM and their

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cycling by microbes is critical for improving our understanding of supraglacial DOM cycling and

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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.

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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,

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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

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refractory DOM molecules could contribute to carbon storage in the ice sheets until melting

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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

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carbon dioxide and sustenance of heterotrophic bacterial communities through production of

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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

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interactions

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transformations of DOM beyond bulk examination and compound specific analyses are lacking.

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This necessitates a more fundamental assessment of DOM composition and reactivity, in order

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to better understand carbon cycling on ice sheets.

with

resident

microbial

communities.

Assessments

of

biogeochemical

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We use ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry

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(FTICR-MS) coupled to electrospray ionisation (ESI), to detect molecular changes in DOM

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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

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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

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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

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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

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analysis.

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FTICR-MS analysis

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Samples were analysed using a Bruker Daltonics 12 T Apex Qe FTICR-MS instrument, operated

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in both negative and positive electrospray ionisation modes, using parameters consistent with

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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 +

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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

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value) for a simple approximation for pure C-C unsaturation.23,24

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After exact elemental formulas had been assigned, formulas present in the microbe treatment

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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

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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

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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

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solely in the microbe treatment were regarded as present due to microbial processing and were

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assigned as microbe-only. Further discussions of data with respect to changes in DOM

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composition are from the microbe-only assignments. A comparison of molecular species

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detected using negative and positive ion modes shows that 9), compared to only 9% of the formulas in the

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initial DOM. In addition, the contribution of aromatic formulas to the total DOM pool increased

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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

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longer hours of direct sunlight. Microbial processes are an important mechanism for cycling of

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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

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and active microbial communities, the metabolic potential for utilising the wide diversity of

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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

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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

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environments using powerful tools such as FTICR-MS and high field NMR would aid in a better

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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

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modified DOM. This is especially relevant as annual release of DOC from the Antarctic ice sheet

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to downstream marine ecosystems is significant10 and is expected to continue increasing in

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coming decades14,15 with unforeseen impacts on marine food webs.

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Acknowledgements

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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

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logistic support for the sampling, as well as, for the safe transport of samples to Old Dominion

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University. We thank Progress station (Russia) for providing the temperature data. We also

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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

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Program #0739691).

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Additional Information

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The authors declare no competing financial interests.

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Author Contributions Statement

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R.A. designed the research and performed the field experiments. A.S.W. carried out the FTICR-

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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

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Specific details of sample preparation and instrument parameters, Table S1-S2, and 3 figures

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(Figures S1–S3), are available as Supplemental Information.

518 519

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732 733

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

35 ACS Paragon Plus Environment

Environmental Science & Technology

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

Environmental Science & Technology

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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