bioRxiv preprint doi: https://doi.org/10.1101/115808; this version posted March 10, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
1 Linking the chemistry and reactivity of dissolved organic matter from low-latitude glaciers
2 and rock glaciers
3
4
5 Fegel, Timothy1, Boot, Claudia M.1,2, Baron, Jill S.1,3, Hall, Ed K.1,4
6 1. Natural Resource Ecology Laboratory, Colorado State University, 2. Department of
7 Chemistry, Colorado State University 3. U.S. Geological Survey 4. Department of Ecosystem
8 Science and Sustainability, Colorado State University
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21 Keywords: glaciers, dissolved organic matter, chemodiversity, GC-MS, DOM, molecular
22 composition, lability, bacterial growth efficiency, BGE, subsidies, heteroptrophy, alpine
23
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24 Abstract
25 As glaciers in the western United States thaw in response to warming, they release dissolved
26 organic matter (DOM) to alpine lakes and streams. Biological availability of DOM from small
27 mountain glaciers is unknown. Differences in DOM bioavailability between glacier types like
28 rock and ice glaciers remains undefined, yet rock glaciers outnumber ice glacier approximately
29 ten to one at low latitudes. To assess which components of aquatic DOM are most reactive and
30 the potential for glacial DOM from low latitude glaciers to subsidize heterotrophy in alpine
31 headwaters we evaluated reactivity and molecular composition of DOM from ice glaciers and
32 rock glaciers from four paired catchments (each with a glacier and rock glacier at their
33 headwaters). Biological reactivity was linked to molecular composition by evaluating the
34 chemical characteristics of each DOM pool pre- and post-incubation using common microbial
35 community laboratory assays paired with untargeted mass spectrometry-based metabolomics.
36 Glacier and rock glacier DOM was similar in concentration and chemodiversity, but differed in
37 composition. When incubated with a common microbial community, DOM from ice glacier
38 meltwaters contained a higher proportion of bioavailable DOM (BDOM), and resulted in greater
39 bacterial growth efficiency. Differences in DOM reactivity between glacier types was
40 determined by differences in the relative abundance of only a few dozen compounds. Though
41 BDOM was lower in rock glaciers, because rock glaciers are more abundant and are expected to
42 have greater longevity, we propose that both glacial types will be important sources of
43 bioavailable DOM to alpine headwaters over the coming years to decades.
44
2 bioRxiv preprint doi: https://doi.org/10.1101/115808; this version posted March 10, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
45 Introduction
46 Glaciers bridge the atmospheric-terrestrial-aquatic interface, integrating atmospherically
47 deposited chemicals with weathering products and releasing reactive solutes to adjacent surface
48 waters (Williams et al. 2007; Dubnick et al. 2010; Fellman et al. 2010; Stibal et al. 2010;
49 Stubbins et al. 2012). Between continental and mountain glaciers, mountain glaciers release the
50 largest flux of carbon from melting ice annually (Hood et al. 2015). Dissolved organic matter
51 (DOM) from these large mountain glaciers of the European Alps and Alaska has been shown to
52 stimulate heterotrophic respiration (Hood et al. 2009; Singer et al. 2012). Glaciers and rock
53 glaciers, each with distinct geophysical attributes, are common in many of the alpine headwaters
54 of the western U.S. (Fegel et al. 2016). Glaciers are massive ice bodies that form and persist in
55 areas where annual snow accumulation is greater than annual snow ablation at decadal or longer
56 time spans. Rock glaciers are flowing bodies of permafrost, composed of coarse talus and
57 granular regolith both bound and lubricated by interstitial ice (Berthling, 2011). In the western
58 United States, rock glaciers are an order of magnitude more abundant than ice glaciers and are
59 more resistant to warming temperatures than ice glaciers (Fegel et al. 2016). Yet little is known
60 about the quantity or quality of DOM being released from smaller glaciers or rock glaciers in
61 mountain headwater ecosystems or their potential to affect low-latitude alpine ecosystems.
62 The chemical composition of DOM from natural aquatic systems is complex (Hedges et al.
63 2000; Kim et al. 2006; Hockaday et al. 2009), and glacier and rock glacier meltwaters are not
64 likely to be an exception. Previously, assessment of the bioavailability of DOM relied on
65 bioassays that measure the rate and amount of DOM consumed over time (e.g. Amon and Benner
66 1996; del Giorgio and Cole 1998; Guillemette and del Giorgio 2011). While some coarse
67 characterizations of molecular composition (Benner 2002; Berggren and del Giorgio 2015) or the
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68 lability of individual compounds (del Giorgio and Cole 1998) have previously been applied to
69 characterize bioavailable DOM (BDOM), only recently has the research community begun to
70 apply high-resolution analytical chemistry to assess the molecular characteristics of
71 environmental DOM (e.g. Kellerman et al. 2014, 2015; Andrilli et al. 2015). Whereas no single
72 method can identify the entire spectrum of compounds present in an environmental DOM pool
73 (Derenne and Tu 2014), mass spectrometry allows for molecular identification of thousands of
74 specific DOM compounds, simultaneously yielding a more specific and broader metric for DOM
75 analysis compared to spectroscopic techniques such as fluorescence or ultraviolet absorption.
76 Simultaneous identification and quantification of total BDOM is not an easy task. Difficulties
77 in experimentally connecting molecular characterization of DOM pools to their bioavailability
78 are partly due to the highly diverse constituent compounds that compose natural DOM (Derenne
79 and Tu 2014). The effects of individual compounds identified to be bioavailable (e.g. amino
80 acids in glacial meltwaters (Fegel et al. 2016) may not be representative of the total BDOM pool.
81 It is also possible that DOM with a high diversity of labile compounds may have positive
82 feedbacks on the bioavailability of the total DOM pool by asserting priming effects on the total
83 pool (Guenet et al. 2010). In addition, certain metabolites within DOM pools may not be
84 bioavailable individually, but may act as cofactor metabolites that allow for a mutualistic
85 increase in bioavailability [Hilker 2014]. Thus, the relationship between DOM pool
86 characteristics and lability remains largely unknown in most natural systems. However, some
87 patterns are beginning to emerge, like the consistently high lability of proteinaceous DOM that
88 has been found in glacial, estuarine, and marine environments [Andrilli et al. 2015]. Defining
89 these fundamental relationships between chemical composition of DOM and lability has the
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90 potential to provide a better understanding for how DOM pools contribute to heterotrophy across
91 a broad spectrum of aquatic ecosystems.
92 There are defining characteristics in the origin of DOM that differentiate glaciers from rock
93 glaciers. DOM derived from ice glaciers is structured by in situ microbial activity and can be an
94 important source of chemical energy to headwater ecosystems (Hood et al. 2009; Singer et al.
95 2012; Fellman et al. 2015; Fegel et al. 2016). DOM derived from rock glaciers is a
96 conglomeration of carbon compounds percolated through from vegetation growing on the rock
97 glacier surface and microbial processing within the rock glacier itself (Wahrhaftig and Cox,
98 1959; Williams et al. 2007; Fegel et al. 2016). Previous research has shown that DOM released
99 from glaciers and rock glaciers in the western United States differ in their optical properties
100 (Fegel et al. 2016). Whether or not these differences in the optical properties of DOM between
101 glacial types translates to differences in their reactivity or proportion of BDOM remains
102 unknown.
103 To address this, we asked whether differences in the composition of DOM between ice
104 glaciers and rock glaciers affected differences in microbial metabolism and whether DOM
105 chemistry in ice and rock glacier meltwater in the western United States is similar to what has
106 been reported for other glacial meltwaters. Here we present the results of laboratory incubations
107 of DOM from ice glacier and rock glacier meltwaters with a common microbial community.
108 Incubations were bookended (i.e. analyzed before and after incubation) with non-targeted
109 metabolomic analysis of DOM via gas chromatography mass spectrometry (GC-MS) to
110 determine differences in the specific chemical compounds metabolized by microbial processing.
111 By exposing DOM from different sources to a common microbial community we were able to
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112 assess the lability of each DOM source and analyze which differences in the molecular
113 composition of DOM affected its lability and carbon use efficiency.
114 Methods
115 Site Description
116 Paired ice glaciers and rock glaciers within four watersheds on the Front Range of Northern
117 Colorado were selected based on their size (>0.5km2) and the proximity to each other within the
118 watershed, forming pairs of features with similar geographic parameters (Figure 1). We collected
119 samples of glacier meltwater in the late summer to capture the greatest contribution of ice melt
120 and minimize annual snowmelt contribution. We sampled the four pairs in September 2014.
121 Sample sites were: Isabelle Glacier (-105.640994,40.063373) and Navajo Rock Glacier (-
122 105.636092,40.061200), Arapaho Glacier (-105.646351,40.023378) and Arapaho Rock Glacier
123 (-105.637699, 40.022482), Peck Glacier (-105.663810,40.068332) and Peck Rock Glacier (-
124 105.664310,40.071642) in the Indian Peaks Wilderness west of Boulder, CO; and Andrews
125 Glacier (-105.680639,40.288370) and Taylor Rock Glacier (-105.671197,40.275568) in the Loch
126 Vale Watershed in Rocky Mountain National Park (Figure 1a). A complete site description for
127 each site is given in Fegel et al. (2016).
128 Field extraction of DOM
129 At each glacier, meltwaters were collected in the early to mid-morning (0500-1000) to
130 minimize diurnal variability in ice melt from solar radiation. DOM was extracted from 20 L of
131 meltwater collected at the terminus of each feature in the field using a slightly modified protocol
132 established by Dittmar et al. (2008, Supplemental Information). Briefly, meltwater samples were
133 passed through pre-combusted (450° C, 5hr) Whatman GF/F filters (GE Whatman, Pittsburg,
134 PA, USA), acidified to ~ pH 2 with 32% HCl, and concentrated using Bond Elut PPL carbon
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135 extraction cartridges (Agilent, Santa Clara, CA, USA). Concentrated DOM was eluted in the
136 field with 10mL HPLC grade methanol per cartridge into cleaned, combusted, and pre-weighed
137 120mL borosilicate bottles.
138 Metabolite Analyses
139 Once in the laboratory, pre-incubation DOM samples were dried under a clean N2 stream and
140 weighed (http://www.nrel.colostate.edu/projects/lvws/data.html). Each sample (n=8) was
141 prepared for metabolomic analysis by dissolving the dried OM into fresh HPLC-grade methanol
142 to a final concentration of 2 mg ml-1.
143 After the microbial bioassays (in which all samples were run in duplicate), post-incubation
144 DOM samples were collected separately from each individual microcosm (n=16). Water from
145 each microcosm was filtered through pre-leached 0.2 μm Millipore filters (EMD Millipore,
146 Billerica, MA, USA) to remove microbial biomass, freeze-dried, and the total remaining DOM
147 was weighed and re-dissolved into HPLC-grade methanol
148 (http://www.nrel.colostate.edu/projects/lvws/data.html). In order to increase the volatility of
149 molecules analyzed through GC-MS, samples were derivatized with trimethylsilane (TMS) using
150 standard protocols (Supplemental Materials) (Pierce, 1968).
151 Metabolomics
152 Both pre- and post- incubation OM samples were analyzed with inline gas chromatography-
153 mass spectroscopy (GC-MS) at the Proteomics and Metabolomics Facility at Colorado State
154 University. Metabolites were detected using a Trace GC Ultra coupled to a Thermo ISQ mass
155 spectrometer (Thermo Scientific, Waltham, MA, USA). Samples were injected in a 1:10 split
156 ratio twice in discrete randomized blocks. Separation occurred using a 30 m TG-5MS column
157 (0.25 mm i.d., 0.25 μm film thickness, Thermo Scientific, Waltham, MA, USA) with a 1.2 mL
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158 min-1 helium gas flow rate, and the program consisted of 80°C for 30 sec, a ramp of 15°C per
159 min to 330°C, and an 8 min hold. Masses between 50-650 m/z were scanned at 5 scans sec-1 after
160 electron impact ionization (Broeckling et al. 2014).
161 DOM lability experiments
162 Concentrated DOM samples from each of the eight study sites were diluted to 4 mg L-1 C and
163 incubated in vitro with a natural microbial community collected from The Loch, a small sub-
164 alpine lake in Rocky Mountain National Park, CO, USA, (-105.6455, 40.2976). Unfiltered lake
165 water collected from The Loch was aged for 2 years at 5 °C in order to remove the majority of
166 the bioavailable carbon. At the start of the experiment DOM concentration of the lake water was
167 0.7 mg L-1 C. At the initiation of the incubations 2 L of aged lake water was filtered through a
168 pre-combusted (450° C, 5hr) Whatman GF/C filter (1.2μm nominal pore size) (GE Whatman,
169 Pittsburg, PA, USA) to remove bacterial grazers (e.g. protists and metazoans). Three aliquots of
170 filtered-aged lake water was preserved with 2% formalin (37% formaldehyde), and set aside for
171 enumeration of bacteria at the initiation of the experiment (i.e. t=0), and a second set of three
172 aliquots (7mL) was used for initial DOC/TN analysis on a Shimadzu TOC-VWS analyzer
173 (Shimadzu Corp., Kyoto, Japan). To create normalized concentrations (4 mg L-1 C), in each
174 incubation bottle we added 60.96 mL of unfiltered Loch water, between 3.80 and 9.06mL of
175 concentrated DOC solution (depending on the initial concentration), and filled to 70mL total
176 volume with DI; resulting in standardized concentrations of 4 mg L-1 C in each incubation bottle.
177 During the experiment, microcosms that received DOM from ice glacier and rock glacier sites
178 were incubated alongside control incubations that contained lake water and the common
179 microbial community but with no added DOM (i.e. experimental control). In addition, an
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180 analytical blank of MilliQ water was incubated to correct for any instrumental drift that occurred
181 during the experiment.
182 All microcosms were incubated simultaneously at 15 °C for 10 weeks. To calculate microbial
183 respiration, we measured changes in dissolved oxygen (DO) at 1-minute intervals in each
184 microcosm using an Oxy-4 fiber-optic dissolved oxygen probe (PreSens, Regensburg, Germany).
185 The incubation was terminated when the fastest metabolizing microcosm approached 4mg L-1
186 DO to avoid hypoxia and the potential for anaerobic metabolism. All measurements with
187 amplitude less than 20000 amps were removed because of the potential for inaccurate readings of
188 DO. Absolute values from the raw fiber optic measurements were corrected for analytical drift
189 by subtraction of changes in signal from the MilliQ water analytical control over the course of
190 the experiment.
191 Bacterial Cell Counts and Bulk Chemistry
192 From each microcosm we collected a 2 mL aliquot post-incubation and preserved it with 2%
193 formalin (final concentration) to assess changes in cell abundance during the course of the
194 incubation. Aliquots were filtered onto 0.2 μm Millipore polycarbonate filters (EMD Millipore,
195 Billerica, MA, USA) and stained with Acridine Orange (Hobbie et al. 1977, Supplemental
196 Information) for enumeration. Post-incubation we assessed TOC and TDN
197 (http://www.nrel.colostate.edu/projects/lvws/data.html) for each microcosm. To ensure that
198 filtration did not contribute significant additional carbon to the dissolved carbon pool, a subset of
199 blank Millipore filters flushed with MilliQ was analyzed for TOC and TN. All filtration of
200 microcosm water for chemical analysis was conducted on pre-leached Millipore filters that
201 contributed insignificant amounts of carbon to the filtrate
202 (http://www.nrel.colostate.edu/projects/lvws/data.html).
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203 Data Analysis
204 Metabolite Analysis
205 Compound annotation was prioritized based on order of normalized intensity and statistical
206 difference between glacier types. Putative identification (candidate compounds based on
207 physicochemical characteristics and spectral similarity with spectral libraries (Sumner et al.
208 2007), was made using spectral matching to in-house, NISTv12, Golm, Metlin, and Massbank
209 metabolite databases. Clustered features assigned candidate compounds in our study had high
210 similarity (>90%) to spectra from known standard compounds within the databases used
211 (Supplemental Information). Molecular rank was calculated by ordering candidate compounds
212 by their normalized ion intensity for pre- and post- incubation sample averages for all features.
213 Chemical diversity was calculated using the Shannon-Wiener diversity index (Shannon 1948) by
214 treating each unique chemical compound identified though GC-MS as a ‘species’. This was done
215 for DOM composition both before and after incubation in order to estimate changes in chemical
216 diversity through microbial metabolism.
217 Analysis of DOM Reactivity
218 Oxygen consumption rates were fit to a Berner-Multi-G two-pool decay model to estimate the
219 size of the labile pool (BDOM) and the recalcitrant pool. Oxygen consumption was averaged for
220 each glacier type and confidence intervals were calculated at α=0.05. Data were smoothed using
221 a third order polynomial (R2>0.999) and 95% confidence intervals were plotted. Berner’s Multi-
222 G model was used to model carbon pool bioavailability (Berner 1980; Guillemette and del
223 Giorgio 2011), using SAS. Dissolved oxygen curves generated from the incubation were fit to
224 the Equation:
225
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푘푡 226 푌 = 퐵1 + 퐵0
227
228 where Y is the total carbon pool, B1 is the bioavailable carbon pool, k is the decay rate
229 constant of the bioavailable pool, t is time, and B0 is the recalcitrant carbon pool. We used a least
230 square means to test for statistical differences between ice glaciers and rock glaciers in the size
231 of the B1 and B0 pools. Total C consumed was calculated as the difference in pre- and post-
232 incubation DOC values.
233 To address the metabolic quality of consumed carbon we calculated Respiratory Quotient
-1 -1 234 (RQ) as the carbon consumed (in mg L ) divided by the oxygen (as O2) consumed (in mg L ).
235 Bacterial growth efficiency (BGE) was calculated to examine how efficiently each carbon
236 source was incorporated into bacterial biomass. To calculate BGE we divided bacterial
237 production (BP) by the sum of bacterial respiration and bacterial production (BR + BP)(del
238 Giorgio and Cole 1998). Thus, BGE is a ratio of carbon incorporated into biomass relative to
239 total carbon consumed for the bacterial community. BP was measured as change in cell number
240 over time and converted to units C using an estimate of 20 fg C per bacterial cell (Borsheim and
241 Bratbak 1987) as a conversion. Carbon consumption rate was measured as carbon consumed
242 during the course of the incubation by measuring DOC content in each filtered pre- and post-
243 incubation sample using a TOC/TDN analyzer.
244
245
246
247
248
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249 Statistical Analyses
250 The DOM composition for each treatment (glaciers vs. rock glaciers) was compared with
251 ANOVA for each compound using the aov function in R, and p-values were adjusted for false
252 positives using the Bonferroni-Hochberg method in the p.adjust function. Post-incubation
253 samples were corrected for compounds added by the lake water by subtracting the peak
254 intensities for each chemical candidate within the lake water (i.e. experimental control) from
255 each post incubation sample.
256 We identified differences in compounds present in each sample using PCA conducted on
257 mean-centered and pareto variance-scaled data using the pcaMethods package in R. We analyzed
258 GC-MS spectra using principal component analysis (PCA) in R (R Core Team, 2014). For each
259 sample, raw data files were converted to .cdf format, and a matrix of molecular features as
260 defined by retention time and mass to charge ratio (m/z) was generated using XCMS package in
261 R for feature detection and alignment. Raw peak areas were normalized to total ion signal,
262 outlier features were detected based on total signal and PC1 of PCA, and the mean area of the
263 chromatographic peak was calculated among replicate injections (n=2). We grouped all spectral
264 features based on an in-house clustering tool, RAMClustR, which uses spectra based coelution
265 and covariance across the full dataset groups features (Broeckling et al. 2014). We used the t-test
266 configured for non-parametric Welch-Satterthwaite test to compare differences in RQ, BGE,
267 chemodiversity, and loss of chemodiversity between glacier types. Our use of a Welch-
268 Satterthwaite test allowed for comparison of samples of unequal variance and distribution.
269
270
271
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272 Results
273 Ice glacier and rock glacier DOM composition
274 Neither the chemical diversity (mean=2.82), nor the C:N ratio (mean=2.1) differed between
275 glaciers and rock glaciers (Table 1). In addition, the molecular composition was similar in each
276 glacier type for the top 25 most abundant molecules. Combined, the glacier and rock glacier
277 DOM molecular composition consisted of 2033 compounds. Each individual compound
278 consisted of 3 to170 individual mass spectral features, for a total of 14,571 unique mass spectral
279 features in the complete dataset. Of the 2033 compounds, 328 were chosen for annotation based
280 either on high ion intensity (n=278) or significantly different relative abundances between glacier
281 and rock glacier sources (n=33). Annotated compounds consisted primarily of simple sugars,
282 amino acids and other organic acids (http://www.nrel.colostate.edu/projects/lvws/data.html).
283 There were significant differences between glacier types in the molecular composition of less
284 abundant compounds (Table 2), although the C:N ratio, chemical diversity, and compounds with
285 greatest ion intensity were similar. PCA analysis of the complete dataset suggested 33 key
286 compounds, ordinated on axes three and five of our PCA analysis (Figure 2A), were responsible
287 for differences in the ice and rock glacier DOM pools (Table 2). Of those 33 compounds, 5 were
288 assigned putative structures (Table 2, also see
289 http://www.nrel.colostate.edu/projects/lvws/data.html) with ice glacier meltwaters significantly
290 enriched in the simple sugar maltose and the amino acid glutamate, and rock glacier meltwaters
291 enriched in the primary organic acids, glycolate, threonate and quinate (Table 2). The other 28
292 compounds represented components of the DOM pool that differentiated DOM composition
293 from each glacier type, but were not present in the databases we employed and had no known
294 structural analogs.
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295 Incubations
296 The bacterial respiration rates of DOM from each glacier type were not significantly different,
297 as estimated by the decay constant k (Table 3). However, a significantly larger portion of ice
298 glacier DOM was bioavailable, (i.e. BDOM, B1 = 58.8 ± 9.7%) compared to rock glacier DOM
299 (B1= 37.3 ± 10.2%, p <0.01, Table 3). Bacterial growth efficiency (BGE) was higher for
300 microbial communities incubated with ice glacier DOM compared to rock glacier DOM (G =
301 0.26 ± 0.13, RG = 0.16 ± 0.16, Table 3). In general, more oxygen was consumed per mg organic
302 carbon metabolized in incubations that contained glacial DOM compared to those that contained
303 rock glacier DOM, even though the amount of carbon consumed between treatments was similar
304 (Figure 4, Table 3). This resulted in a lower respiratory quotient (RQ) for glacial derived DOM
305 compared to rock glacier derived DOM overall.
306 Post-incubation DOM analysis
307 Analysis of DOM after the incubation period allowed us to assess how microbial metabolism
308 altered the composition of DOM. Incubation with a common microbial community both rarified
309 and homogenized DOM between glacier types, resulting in fewer compounds with high ion
310 intensities, and more compounds with low ion intensities (Figure 3). This reorganized the
311 molecular rank-abundance curve, resulting in a different set of compounds with the highest
312 relative abundance in the pre vs. post-incubation dataset (Table 4). However, similar to pre-
313 incubation DOM composition, post-incubation ice glacier and rock glacier derived DOM shared
314 the same abundant compounds (Figure 2B)
315 (http://www.nrel.colostate.edu/projects/lvws/data.html). Interestingly, the chemical diversity of
316 DOM between glacier types diverged during the course of the incubation. At the end of the
317 incubation glacial DOM had significantly higher diversity and rock glacier DOM had
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318 significantly lower diversity compared to pre-incubation DOM for the same glacial type (Table
319 1, Figure 2C). Combined with molecular rank abundance data (ordered on ion intensity), this
320 change in chemical diversity resulted in an increase in the richness of glacier DOM pools by
321 microbial metabolism and a decrease in richness in rock glacier DOM during the incubation. For
322 both DOM sources, many of the organic acids and sugars present pre-incubation were consumed
323 while amino acids that were present at lower intensities in pre-incubation DOM pools increased
324 in relative abundance in post-incubation DOM pools. While there were differences in the
325 chemical diversity of rock and ice glacier derived DOM post-incubation, PCA suggested were no
326 differences in the overall molecular composition between glacier types (Figure 2B). This trend
327 did not follow for all rock glaciers, as one replicate of Taylor Rock Glacier (lowest left point,
328 Figure 2A & 2B) saw few changes in its principal components after the incubation. Interestingly,
329 while no significant difference was seen in GC-MS compounds between glacier type post
330 incubation (Figure 2B), both replicates of Peck Rock Glacier (lower rightmost points Figure 2B)
331 showed separation along the y-axis (PC1) of their PCA, a separation that was not seen before
332 microbial metabolism (Figure 2A). The reasons for this remain unclear, but may be due
333 geographical separation (climatological differences) between Peck Rock Glacier and all other
334 sites.
335 Discussion
336 Our results demonstrate that chemically complex DOM released from Rocky Mountain ice
337 glaciers and rock glaciers stimulated bacterial respiration and productivity. Each DOM source
338 had unique molecular characteristics that reflected their quality as an energy source for microbial
339 metabolism. Glacier and rock glacier DOM shared many of the same organic compounds, but
340 differences in the relative concentrations of just 33 compounds appeared to drive differences in
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341 the bioavailability of DOM between glacier types. Enrichment in simple sugars of glacier DOM
342 contributed to higher bioavailability of glacier DOM as measured by size of the BDOM pool and
343 bacterial growth efficiency (BGE). The DOM from rock glaciers, was enriched in less
344 bioavailable, primary organic acids. In spite of these differences, the bacteria homogenized
345 DOM from both sources during the incubations, resulting in more similar DOM composition at
346 the end of the incubation compared to the composition of the DOM before the incubation. In our
347 experiment, the source of the DOM affected its composition and reactivity and interaction with
348 the microbial community metabolism re-structured its chemistry.
349 Glaciers are a source of labile DOM
350 The results from our study of glaciers in Colorado showed similar patterns to previous studies
351 of glacial DOM in the Arctic and the European Alps, where bioavailable carbon from glaciers
352 also stimulated microbial production (Hood et al. 2009; Singer et al. 2012; Fellman et al. 2015).
353 Carbon concentrations in meltwaters from ice and rock glaciers in our study were low (0.5- 1.5
354 mg C L- 1), but similar to the global average of 0.97 mg C L-1 that has been previously reported
355 for glaciers (Dubnick et al. 2010; Stubbins 2012; Singer et al. 2012; Hood et al. 2015). The
356 percentage of DOM that was bioavailable (BDOM) from ice glacier DOM in our study (~50%)
357 was comparable to values of BDOM seen in DOM derived from glaciers in the European Alps
358 (58%), and within the range of values reported from glaciers in the Alaskan Range (23-66%)
359 (Hood et al. 2009; Singer et al. 2012). In all of these studies, including the results reported here,
360 glaciers had higher BDOM concentrations than other surficial freshwaters (Volk et al. 1997).
361 Previous reports on freshwater noted 16.5-34.5% of BDOM, which more closely resembled the
362 amount of BDOM we report from rock glacier BDOM (37% on average).
16 bioRxiv preprint doi: https://doi.org/10.1101/115808; this version posted March 10, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
363 We propose that ice glaciers have higher proportions of BDOM compared to rock glaciers for
364 two reasons. First, rock glaciers host mosses, lichens, and vascular plants, including woody
365 shrubs and trees (Wahrhaftig and Cox, 1959; Cannone and Gerdol 2003; Burga et al. 2004).
366 Dissolved organic compounds released from these allochthonous phototrophs include a wide
367 variety of complex organic acids and polymers that are potentially difficult for microbes in
368 freshwaters to metabolize, resulting in a higher proportion of recalcitrant DOM within rock
369 glaciers (Wetzel 1992, Rovira and Vallejo 2002). The potential for the development of protosoils
370 within the rock glacier matrix may promote the presence of liquid pore water. DOM from rock
371 glaciers may already be partially processed by microbes within this protosoil environment by the
372 time it reaches the sub-rock-glacial surface water. This pre-processing may result in DOM with a
373 level of lability more similar to what is delivered to inland surface waters and derived from the
374 soil SOM matrix (Fellman et al. 2010). Conversely, BDOM in ice glaciers comes from
375 autocthonous sources (i.e. microbial production and processing on the ice surface and within the
376 ice interstitial space (Fellman et al. 2009) and atmospherically deposited aerosols (Hood et al.
377 2012), both of which appear to be more biologically available than terrestrial sources. Ice glacier
378 BDOM may be preserved in the ice matrix and physically inaccessible to microbial degradation.
379 In contrast, rock glacier DOM may be in contact with intraglacial sediments and liquid water,
380 allowing for further processing through microbial metabolism. In addition, sub-glacial
381 environments below ice glaciers are often anoxic (Tranter et al. 2005), allowing some
382 compounds to remain in a chemically reduced state until released with ice melt. This would
383 allow for rapid metabolism of these energetically-preferable, reduced compounds once unlocked
384 from the ice and released to an oxic environment (Hood et al. 2009). Thus the production of
385 DOM within each feature differs and pathways by which that DOM is delivered to the glacial
17 bioRxiv preprint doi: https://doi.org/10.1101/115808; this version posted March 10, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
386 meltwater differ. These mechanisms would result in the differences in the proportion of BDOM
387 we observed in our bioassays of DOM lability.
388 The molecular structure of glacial DOM from large glaciers has been mechanistically linked to
389 its lability and shown to be more labile than marine or freshwater derived material due to the
390 presence of protein and amino-sugar components of microbial origin (Andrilli et al. 2015). This
391 is consistent with studies from other inland waters that show that higher DOM bioavailability
392 correlates with enrichment of amino acids and simple sugars (Lafreniere and Sharp 2004;
393 Williams et al. 2007; Dubnick et al. 2010). Taken together with the results presented here, we
394 suggest that DOM enriched in amino acids and simple sugars may be a key trait that defines
395 BDOM and be characteristic of glacial meltwaters worldwide.
396 Glacier DOM Diversity
397 The diversity of compounds in organic matter released from glaciers in this study was similar
398 to the DOM diversity found in other freshwater systems (Dubnick et al. 2010, Guillemette and
399 del Giorgio 2011, Kellerman et al. 2014). We found that chemical diversity was very similar
400 between ice glaciers and rock glaciers. However, the diversity of DOM between glacial types
401 was altered by microbial metabolism in different ways when incubated. Chemical diversity in
402 incubations with glacial DOM increased during the course of the incubation, whereas chemical
403 diversity decreased in incubations with rock glacier DOM. This suggests that when BDOM is a
404 smaller fraction of total DOM, microbial communities may use previously processed DOM to
405 fuel their own heterotrophic metabolism. This would reduce chemical diversity through the
406 consumption of primary metabolites (i.e. simple organic acids).
407 Our study expands the understanding of DOM complexity in inland waters by assessing the
408 glacial contribution of DOM to alpine headwaters and moving beyond broad functional groups
18 bioRxiv preprint doi: https://doi.org/10.1101/115808; this version posted March 10, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
409 and compound classes identification to identification of specific compounds (Dubnick et al.
410 2010; Fellman et al. 2010; Singer et al. 2012, Fegel et al. 2016). By using a mass spectrometry
411 based technique we were able to identify individual candidate compounds through metabolomics
412 paired with total chemical pool complexity. Our results are more detailed, but consistent with
413 previous analyses that used a fluorescence index (Fegel et al. 2016). Results from Fegel et al.
414 (2016) showed higher fluorescence index (FI) values in ice glacier meltwaters compared to that
415 of rock glaciers, indicating a higher presence of proteinaceous (i.e. nitrogen containing)
416 compounds in ice glacier meltwaters. Here, using metabolomics, we identified higher
417 proportions of specific amino acids within ice glacier meltwaters compared to rock glaciers that
418 are likely the cause of the increased FI values observed (Fegel et al. 2016). Application of a
419 community level analytical approach such as mass spectrometry-based metabolomics provides
420 the opportunity to disentangle the critically important components of complex DOM pools for
421 aquatic C cycling, however only a few studies have used metabolomic approaches to address the
422 bioavailability of DOM as a heterotrophic subsidy (see Kujawinski 2011 for a review; Logue et
423 al. 2015).
424 Whereas our results provide unambiguous evidence that differences in bioavailability are due
425 to chemical differences between DOM that differ in origin from glacier types, some components
426 of the DOM pool are likely not assessed by the GC-MS we employed. GC-MS measures
427 molecules up to 1200 amu with electron impact ionization, leaving larger molecules unidentified.
428 Further, some of the components important for glacial C processing could not be identified using
429 the most current databases. While we were unable to determine exactly what those compounds
430 were, we are able to say what they were not. Many of the unannotated compounds that were
431 significantly different between glaciers and rock glaciers had m/z (mass to charge ratio) values
19 bioRxiv preprint doi: https://doi.org/10.1101/115808; this version posted March 10, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
432 greater than 200 (Table 2), indicative of secondary metabolites with large molecular weights
433 relative to primary metabolites, most of which have mass to charge (m/z) values between 60 and
434 205. Products of primary metabolism, e.g. amino acids, organic acids, sugars and peptides are
435 well represented in mass spectrometry databases and therefore more easily identified with a GC-
436 MS approach. Less well represented are larger molecular weight products of secondary
437 metabolism such as terpenes, alkaloids, polyketides, aromatic structures, and products of mixed
438 biosynthesis. Known metabolites are often a small portion of data obtained through mass
439 spectrometry (<10%), with much of the data reflecting unknown metabolites or those yet to be
440 verified with standards (Jansson et al. 2009). Yet, the quality of mass spectrometry databases and
441 representation is rapidly improving, and this will likely be a critically important source of
442 information for understanding the relationship between molecular composition of DOM and its
443 lability in future research. The high proportion of compounds that could not be annotated with
444 candidate assignments in our study reflects the infancy of using mass spectrometry databases in
445 environmental applications. It exposes the need for more environmentally derived spectra and
446 standards from secondary metabolism to be added to the current metabolite databases. With the
447 expansion of metabolic databases, and the verification of environmentally-derived spectra to
448 known standard compounds, metabolomic techniques will provide the ability to directly assess
449 the functionality of in situ metabolic pathways from natural systems.
450 Distribution of Glaciers and Rock Glaciers
451 Complete mapping of rock glaciers has only been completed for the contiguous United States
452 and portions of South America, yet early results suggest rock glaciers may be exceptionally more
453 abundant than ice glaciers in headwater ecosystems (Falaschi et al. 2013; Rangecroft et al. 2015;
454 Fegel et al. 2016). In addition to their ubiquity, rock glacier derived DOM may contribute to
20 bioRxiv preprint doi: https://doi.org/10.1101/115808; this version posted March 10, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
455 ecosystem productivity for much longer than ice glaciers due to the slower recession of rock
456 glaciers compared to ice glaciers (Woo 2012). At similar carbon concentrations and with only
457 ~15% less BDOM (~37% in rock glaciers compared to 52% in glacier derived DOM), as
458 observed in our study, rock glaciers may play a role in heterotrophic metabolism of alpine
459 headwaters. Current glacial carbon modeling neglects the contribution of rock glacial carbon
460 (Hood et al. 2015), yet our results suggest that rock glaciers supply a significant source of
461 organic matter for metabolism and will continue to do so for decades to come.
462 In conclusion, the work presented here suggests that as long as the cryosphere is present,
463 DOM entering alpine streams and lakes from both glacier and rock glaciers is likely to continue
464 to contribute to ecosystem heterotrophy during summer melt. We found clear differences in the
465 proportion of BDOM and microbial growth efficiency between glacier and rock glaciers DOM.
466 This suggests a higher potential for secondary production in systems with glacial headwaters
467 compared to those with rock glacier headwaters. The applicability of metabolomics to the
468 analysis of natural DOM provides the potential to expand the application of our results for the
469 prediction of BDOM beyond glaciated ecosystems to a broad range of inland waters. At the same
470 time our approach exposes the need for better metabolite database development for ecological
471 metabolomic approaches. In the coming decades, the DOM inputs to alpine lakes and streams
472 will increasingly be dominated by rock glacier-like DOM inputs, as ice glaciers are lost and rock
473 glaciers continue to contribute to alpine hydrology due to their slower ablation rates. Despite
474 differences in chemical compounds and BDOM pool sizes between glacier types, both glaciers
475 and rock glaciers represent an important heterotrophic subsidy of organic carbon to alpine
476 headwaters that will fuel ecosystems processes from the bottom up for years to come.
477
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644 Acknowledgements
645 The authors would like to thank Edward Stets and Ann Hess for their for help with DOM pool
646 modeling, Corey Broeckling and Sarah Lyons for their help interpreting metabolomic data, and
647 Gunnar Johnson for his help in the field and with figures. This project is a product of the
648 Western Mountain Initiative (WMI) and is funded by the United States Geological Survey.
649 Edward K Hall was supported by NSF award DEB#1456959 during the preparation of this
650 manuscript. All data are available to the public and reside with Loch Vale Watershed long-term
651 ecological research and monitoring program database at
652 http://www.nrel.colostate.edu/projects/lvws/data.html.
653
29 bioRxiv preprint doi: https://doi.org/10.1101/115808; this version posted March 10, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
654 Figure Legends 655 656 Figure 1 A) Stars note the approximate location of each glacier feature that was sampled for this
657 study within the state of Colorado. In total four pairs of glaciers and rock glaciers were sampled
658 along the Front Range of Colorado. (B) Isabelle Glacier and Navajo Rock Glacier form a pair
659 of a glacier and a rock glacier from the same watershed are shown here to illustrate the
660 differences between the two types of features.
661
662
663 Figure 2 PCA GC-MS Analysis DOM compounds A) PCA plots showing separation along PC5
664 between glaciers (blue) and rock glaciers (red) before incubation and B) no significant difference
665 between glacier types after incubation (p-value of 0.119 and 0.0681 for PC1 and PC2,
666 respectively). C) The Shannon-Wiener Index (SW) for chemical diversity was similar between
667 glaciers and rock glaciers before incubation, however microbial metabolism increased chemical
668 diversity in glacier DOM and decreased chemical diversity in rock glacier DOM.
669
670
671 Figure 3 Molecular distribution of GC-MS identified compounds A) Distribution of
672 compounds by ion intensity pre- (orange) and post-incubation (brown). Many of the compounds
673 present before incubation that were of intermediate abundance were metabolized. The most
674 abundant molecules were different between pre- and post- incubation metabolomics analysis (see
675 Table 4).
676
677
30 bioRxiv preprint doi: https://doi.org/10.1101/115808; this version posted March 10, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
678 Figure 4 Dissolved oxygen consumption curves from glaciated watersheds (n=8). Values were
679 averaged for each of the glaciers (blue) and rock glaciers (red), and the analytical control (dotted
680 black). All curves were smoothed using a third order polynomial regression function (R2=0.999).
681 Here we show 95% Confidence Intervals in light blue for glaciers and in pink for rock glaciers.
682 Glaciers consumed a larger portion of available DOM during the course of the incubation.
683 684 685 686 687 688 689
31 bioRxiv preprint doi: https://doi.org/10.1101/115808; this version posted March 10, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
690 A. B.
691 692 Figure 1 A) Stars note the approximate location of each glacier feature that was sampled for this
693 study within the state of Colorado. In total four pairs of glaciers and rock glaciers were sampled
694 along the Front Range of Colorado. (B) Isabelle Glacier and Navajo Rock Glacier form a pair
695 of a glacier and a rock glacier from the same watershed are shown here to illustrate the
696 differences between the two types of features.
697 698 699
32 bioRxiv preprint doi: https://doi.org/10.1101/115808; this version posted March 10, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
700 Scores Scores Loadings Loadings 701 Scores Scores Loadings Loadings Scores Scores Loadings Loadings
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0 B.
4
4
4
4 .
. ice ice
0
0
0
0 0
Succinic acid, 3−chlorophenyl 4−methoxybenzyl ester Succinic acid, 3−chlorophen0 yl 4−methoxybenzyl ester 7
rock rock 7 blank rock blank blank rock blank 0
0 1,2,4−Triazole, 3−mercapto−4−phenyl−5−methyl− 1,2,4−Triazole, 3−mercapto−4−phenyl−5−methyl−
3
3
5
5 2 A. B. freezeBlank C. freezeBlank 2
Disiloxane, hexamethyl− Disiloxane, hexamethyl− 1
1 Maltose( Threonic(acid( Maltose( Threonic(acid(
.
2 2
. ice Serineice (3TMS) Serine (3TMS)
7
7
7
7
.
.
0
0
0
0 0
0 1,2,4−Triazole, 3−mercapto−4−phen1,2,4yl−T−r5iaz−methole, 3yl−−mercapto−4−phenyl−5−methyl− =
= 1,2,4−Triazole, 3−mercapto−4−phen1,2,4yl−T−r5iaz−methole, 3yl−−mercapto−4−phenyl−5−methyl− 3
3 rock rock
5
5 .
. freezeBlank freezeBlank freezeBlank freezeBlank
2
2 0
0 Disiloxane, hexamethyl− Disiloxane, hexamethyl− .
. ice ice BenzSerineenecarbothioic (3TMS) acid, 2,4,6pyroglutamate−triethyl−, S−(2−phenylethyl) ester BenzSerineenecarbothioic (3TMS) acid, 2,4,6pyroglutamate−triethyl−, S−(2−phenylethyl) ester
0
0
.
.
3
3
3
3 0
3rock.2 rock 0
5
5
= 5
5 glycine glycine
= 2
2 aspartate aspartate
2
2
2
2 0
0 Disiloxane, hexamethyl− Disiloxane, hexamethyl−
.
. .
ice . ice ice ice 4
Diiodoacetylene Diiodoacetylene 4 0
0 Serine (3TMS) Serine (3TMS) 0 0 blank blankBenzenecarbothioic acid, 2,4,6 −triethyl−, S−(2−phenylethyl) ester Benzenecarbothioic acid, 2,4,6 −triethyl−, S−(2−phenylethyl) ester
Glutamate( Quinic(acid( . Glutamate( Quinic(acid( pyroglutamate.
. pyroglutamate . rock betarock−alanine beta−alanine
= Sucrose, 8TMS derivative Sucrose, 8TMS derivative
=
0
0 ^
^ glycine glycine
2
2 2
aspar 2 tate aspartate 0
Pentadecan−1−ol, n− (1TMS) Pentadecan−1−ol, n− (1TMS) 0 Disiloxane, hexamethyl− Disiloxane, hexamethyl− Disiloxane, hexamethyl− Disiloxane, hexamethyl−
=
=
0
0 0
0 Serine (3TMS) 7
Homosalate, TMS derivative Homosalate, TMS derivative 7 pBenzyroglutamateenecarbothioiclactate acid, 2,4,6 −triethyl−, S−(2−phenSerylethineyl) (3TMS) esterpBenzyroglutamateenecarbothioiclactate acid, 2,4,6 −triethyl−, S−(2−phenylethyl) ester
r
r
.
. 0
rock 0 rock rock rockpyroglutamate1,2,4−Triazole, 3−mercapto−4−phenyl−5−methyl− pyroglutamate1,2,4−Triazole, 3−mercapto−4−phenyl−5−methyl−
=
=
0
0 0
0 beta−alanine glycine beta−alanine 2
freezeBlank 2 Sucrose, 8TMS derivative glycine 2
freezeBlank 2 Sucrose, 8TMS derivative
2
2 ^ ^ asparNorthreonineleucinetate (3TMS) asparthreoninetate
Norleucine (3TMS)
0
0 BenzSerineenecarbothioic (3TMS) acid, 2,4,6glutamate−Sertriethineyl −(3TMS), S−ser(2−inephen3,5yleth−Diyl)−ter estert−butylBenzSer−4ineenecarbothioic−h ydro(3TMS)xybenzoic acid, acid, 2,4,6 glutamateTMS−Sertr deriethineivylativ −(3TMS), Se−ser(2−inephen3,5yleth−Diyl)−ter estert−butyl−4−hydroxybenzoic acid, TMS der ivative
2
.
. . Diiodoacetylene .
2 Diiodoacetylene pyroglutamatepalmitelaidicpyroglutamate acid 02 pyroglutamatepalmitelaidicpyroglutamate acid 02
3
=
=
3 =
= lactate r
r lactate
;
;
0
0
0
0 5
C996( Glycolic(acid(( C996( Glycolic(acid(( 5 beta−alanine glycinephosphoric acid Sucrose, 8TMSbeta− alaninederivative glycinephosphoric acid Sucrose, 8TMS derivative
2
2 ^ ^ aspartate HydroScopoletin,xylamine TBDMS xylose/lyxose(3TMS)glucosedisacchar der ivatividee aspartate Hydroxylamine xylose/lyxose(3TMS)glucosedisaccharide
0 Scopoletin, TBDMS der ivative 0 threonine . threonine . ice ice Norleucine (3TMS) Norleucine (3TMS) 3 Benzenecarbothioic acid,1,2 2,4,6−Ethenediol,−Benztriethenecarbothioicyl− ,2TMS S−(2− derpheniv 3,5acid,ativyleth−eDi 2,4,6yl)−ter estert−−trbiethutylBenzyl−4−enecarbothioic−, Shydro−(2−xybenzphenyleth oicacid, yl)acid,1,2 2,4,6ester− TMSEthenediol,−Benztr iethderenecarbothioicyliv−ativ ,2TMS Se−(2− derpheniv 3,5acid,ativyleth−eDi 2,4,6yl)−ter estert−−trbiethutylyl−4−−, Shydro−(2−xybenzphenylethoic yl)acid, ester TMS der ivative
^ pyroglutamate pyroglutamate
^ Dibenz[d,f]cycloheptane , 5−amino−1,2,3,8−tetramethoxy− Dibenz[d,f]cycloheptane , 5−amino−1,2,3,8−tetramethoxy− pyroglutamate lactateglutamate serine pyroglutamate lactatepglutamateyroglutamate serine pyroglutamate
r
r
0
0 0
Methanone, (2−amino−5−chlorophenyl)(2−fluorophenyl)− Methanone, (2−amino−5−chlorophenyl)(2−fluorophenyl)− beta−alanine glycinepalmitelaidic acid 02 betaglycine−alanine 0 glycinepalmitelaidic acid 02 glycine
2
2 2 2 Boric acid, 3TMSSucrose der ivativ, 8TMSe derivative
; Boric acid, 3TMSSucrose der ivativ, 8TMSe derivative
; trisiloxane, 1,1,1,5,5,5 −hexamethyl−3−[(trimethylsilyl)oxy]− trisiloxane, 1,1,1,5,5,5−hexamethyl−3−[(trimethylsilyl)oxy]−
9
^ 9
C349 C349 ^ aspartate phosphoric acid aspartate aspartate phosphoric acid aspartate 1 Silane, diethyl(2−phenylethoxy)tetradecyloxy− Silane, diethyl(2−phenylethoxy)tetradecyloxy− threonine 1 xylose/lyxoseglucosedisaccharDisiloxaneide , hexamethyl− xylose/lyxoseglucosedisaccharDisiloxaneide , hexamethyl− Terephthalic acid, octyl 2,4,40 −trimethylpentyl ester threonine Terephthalic acid, octyl 2,4,40 −trimethylpentyl ester r Norleucine (3TMS) r Succinic acid, 2−fluorophenyl 2,4−dimethylpent−3−yl ester Norleucine (3TMS) Succinic acid, 2−fluorophenyl 2,4−dimethylpent−3−yl ester HydroScopoletin,xylamine TBDMS (3TMS) der ivative HydroScopoletin,xylamine TBDMS (3TMS) der ivative
0 3,5−Di−tert−butyl−4−hydroxybenzoic acid, TMS der ivative 3−pyrazolidinone, 4,4−dimethyl−1−phenyl−2−(trimethylsilyl)− 3−pyrazolidinone, 4,4−dimeth0 yl−1−phenrockyl−2−(trimethylsilyl)− pyroglutamate rocklactate glutamate1,2−Ethenediol,ser ine2TMS der ivative pyroglutamate lactate glutamate1,2−Ethenediol,ser ine2TMS3,5 der−Di−ivterativt−ebutyl−4−hydroxybenzoic acid, TMS der ivative Silane, diethyldodecylohomoserxypentyloiner xy−
SuccinicCyclodisilazaneSilane acid,, di(2dimeth, 2,2,4,4−fluorophenyl(dimeth−tetramethyl)yldecylo esteryl−xysilylo1,3−diphenxy)decyloyl− xy− SuccinicSilaneCyclodisilazaneSilane, diethacid,,yldodecylo di(2dimethhomoser, 2,2,4,4−fluorophenyl(dimethxypentyloine−r tetramethyl)yldecylo esterxy−yl−xysilylo1,3−diphenxy)decyloyl− xy− beta−alanine betapalmitelaidic−alanine acid 02 Sucrose, 8TMSbeta−alanine derivative Sucrose, 8TMSbetapalmitelaidic− alaninederivativ acide 02 Sucrose, 8TMS derivative Sucrose, 8TMS derivative
;
^
^
;
^
^ 2
phosphortrBorisiloicxane acid,ic acid, 1,1,1,5,5,5 3TMS2 der −ivheativxamethe yl−3−[(trimethylsilyl)oxy]− phosphortrBorisiloicxane acid,ic acid, 1,1,1,5,5,5 3TMS der−ivheativxamethe yl−3−[(trimethylsilyl)oxy]−
9 9
1 Phenol, 2,4,6−tri−terxylose/lyxoset−butyl−
1 3−pyrazglucosedisaccharolidinone,ide 4,4−dimethyl−1−phenyl−2−(trimethPhenol,ylsilyl)− 2,4,6−tri−terxylose/lyxoset−butyl−
0
0 0 C884( C589( C884( C589( 0 threonine 3−pyrazglucosedisaccharolidinone,ide 4,4−dimethyl−1−phenyl−2−(trimethylsilyl)−
1 threonine
Norleucine (3TMS) 1 Serine (3TMS) HydroScopoletin,xylaminepalmitic3,5 TBDMS− (3TMS)Di acid−ter dert−bivutylativ−e4−hydroxybenzoic acid,Serine TMSNor (3TMS)leucine der ivativ Hydro(3TMS)Scopoletin,e xylaminepalmitic TBDMS (3TMS) acid der ivative ; 3,5−Di−tert−butyl−4−hydroxybenzoic acid, TMS der ivative ; pyroglutamate 1,2−Ethenediol,pyroglutamate 2TMS der ivative 1,2−Ethenediol, 2TMS der ivative
. serine pyroglutamate pyroglutamate
glutamatelactate . lactate glutamate serine r
r lactate lactate
r r
similar to Cyclohexasiloxane, dodecamethyl C Silane, diethyldecylosimilarxyoctylo to xyCyclohe− xasiloxane, dodecamethyl Silane, diethyldecyloxyoctyloxy− palmitelaidic acid 02 C
= palmitelaidic acid 02
Siloxane hydroxybenzoic acid 3−Methyl−3−(N−methylSilo−2−xanepyrrolyl)−1,2−diphenhydroylcyclopropenexybenzoic acid = 3−Methyl−3−(N−methyl−2−pyrrolyl)−1,2−diphenylcyclopropene ;
similar to Cyclopentasiloxane, decamethyl similar to Cyclopentasiloxane, decameth; yl phosphorictr Boracidisiloicxane acid,, 1,1,1,5,5,5 3TMS der−ivheativxamethe yl−3−[(trimethylsilyl)oxy]phosphor− ictr Boracidisiloicxane acid,, 1,1,1,5,5,5 3TMS der−ivheativxamethe yl−3−[(trimethylsilyl)oxy]− 9
Cyclooctasiloxane, heSilanexadecameth, diethyldodecyloyl− xy(2−methoxyethoxy)− Cyclooctasiloxane, heSilanexadecameth, diethyldodecyloyl− 9 xy(2−methoxyethoxy)− threonine xylose/lyxoseglucosedisaccharide threonine threonine xylose/lyxoseglucosedisaccharide threonine
Norleucine (3TMS) Norleucine (3TMS)
Norleucine (3TMS) Norleucine (3TMS) 1 Hydroxylamine (3TMS) 1 1 Phenol, 2,4,6−3−trpi−yrterazt−olidinonebutyl− , 4,4−dimethyl−1−phenylHydro−2−(trxylamineimethylsilyl) (3TMS)−
1 Scopoletin, TBDMS der ivative Phenol, 2,4,63−−trpi−yrterazt−olidinonebutyl− , 4,4−dimethyl−1−phenyl−2−(trimethylsilyl)− 1 1 Benzenecarbothioic acid, 2,4,6palmitic3,5−−trDiieth −acidteryl−t−, Sbutyl−(2−4phen−hydroylethxybenzyl) 3,5esteroic−Di Benzacid,−terScopoletin,enecarbothioict −TMSbutyl der−4 −ivTBDMShativydro eacid,xybenz der 2,4,6ivpalmiticoicativ3,5− acid,e−trDiieth −acid terTMSyl−t−, Sb derutyl−(2iv−4ativphen−heydroylethxybenzyl) 3,5esteroic−Di acid,−tert −TMSbutyl der−4−ivhativydroexybenzoic acid, TMS der ivative
0 serine serine
0 1,2−glutamateEthenediol, 2TMS derpyroglutamateivative glutamate 1,2−glutamateEthenediol, 2TMSser derinepyroglutamateivative glutamate serine
0 8
0 palmitelaidic acid 02 palmitelaidic acid 02 palmitelaidic acid 02 palmitelaidic acid 02
8
0
2
0
2
3
; ;
Silane, dimethyl(octadecyloxy)propyl− C
3
; ;
phosphoric acid phosphorSilaneic acid, dimethyl(octadecyloxy)propyl− glycine C glycine 2
2 phosphoric acid phosphoric acid
. phosphoric acid phosphoric acid
. trBorisiloicxane acid,, 1,1,1,5,5,5 aspar3TMState der−ivheativxamethe yl−3−[(trimethylsilyl)oxy]− trBorisiloicxane acid,, 1,1,1,5,5,5 aspar3TMState der −ivheativxamethe yl−3−[(trimethylsilyl)oxy]−
9 .
9 xylose/lyxosedisaccharide xylose/lyxosedisaccharide . P glucose glucose xylose/lyxose xylose/lyxose 2−Phenoxathiinamine−10,10P −dioxide 2−Phenoxathiinamineglucosedisacchar−10,10ide −dioxide glucosedisaccharide
2.8 1 Hydroxylamine (3TMS) Hydroxylamine (3TMS) 1 Hydroxylamine (3TMS) Hydroxylamine (3TMS) 1 Scopoletin,Phenol, TBDMS 2,4,63−−tr pderi−yrterazivtativ−olidinonebutyle Scopoletin,− , 4,4−dimeth TBDMSyl−1 −derphenivativyl−e2−(trimethScopoletin,ylsilyl)− TBDMS der ivative Scopoletin, TBDMS der ivative
1 Phenol, 2,4,63−−trpi−yrterazt−olidinonebutyl− , 4,4−dimethyl−1−phenyl−2−(trimethylsilyl)− .
5H−Pyrano[2,3,4,5−lmn]phenanthridin−5−one 5H−Pyrano[2,3,4,5−lmn]phenanthridin−5−one 1,2−Ethenediol, 2TMSpalmitic der ivacidativ1,2e −. Ethenediol, 2TMS der ivative 1,2−Ethenediol, 2TMSpalmitic der ivacidativ1,2e −Ethenediol, 2TMS der ivative 1 C815( C531( Scopoletin,C815 TBDMS( der ivativCe 531( Scopoletin, TBDMS der1 ivative
C beta−alanine NA C beta−alanine
0 NA 0
2 Sucrose, 8TMS derivative
2 3−Dimethyl(phenyl)silyloxypentadecane Sucrose, 8TMS derivative 2
3−Dimethyl(phenyl)silyloxypentadecane 2 ^
^ trBorisiloicxane acid,, 1,1,1,5,5,5 3TMS der −ivheativxamethe trBorisiloyl−ic3xane −acid,[(tr,imeth 1,1,1,5,5,5 3TMSylsilyl)o der −ivxy]heativxameth−e yltr−Borisilo3−[(tricxane acid,imeth, 1,1,1,5,5,5 3TMSylsilyl)o derxy]−iv−heativxamethe trBorisiloyl−ic3xane −acid,[(tr,imeth 1,1,1,5,5,5 3TMSylsilyl)o der −ivxy]heativxameth−e yl−3−[(trimethylsilyl)oxy]−
9
9
9
9
.
.
0
0
1
1
1
1
0
0
P
P
1 0 1 Phenol, 2,4,623−−trPhenopi−yrterazt−olidinonexathiinaminebutyl− , 4,4−−dimeth10,10−yldio−1xide−phenyl−2−(trimethPhenol,ylsilyl)− 2,4,6 −tri−tert−butyl−
0 23−Phenopyrazolidinonexathiinamine, 4,4−−dimeth10,10−yldio−1xide−phenyl−2−(trimethylsilyl)− C
C palmitic acid palmitic acid
1
1
.
. 0 pyroglutamate 0 pyroglutamate
r lactate lactate
r
:
:
C
C 2
Phenylethylmalonamide, 2TMS derivative Phenylethylmalonamide, 2TMS derivative 2
0
0
3
3 .
. threonine
1
1
l 1
1 Phenol, 2,4,6 −tri−tert−butyl− Phenol, 2,4,6 −tri−tert−butyl− threonine l
P 3−Norpyrleucineazolidinone (3TMS), 4,4−dimethyl−31−−pphenyrazolidinoneyl−2−(trimeth, 4,4Phenol,−ylsilyl)dimeth− 2,4,6yl−1−−phentri−teryl−t−2b−utyl(trimeth− Phenol,ylsilyl)− 2,4,6 −tri−tert−butyl−
P 3−pyrazolidinone, 4,4−dimethyl−31−−pphenyrazolidinoneyl−2−(trimeth, 4,4−ylsilyl)dimeth−yl−1−phenyl−2−(trimethylsilyl)− 2−Phenoxathiinamine−10,10−dioxide Norleucine (3TMS)
0 2−Phenoxathiinamine−10,10−dioxide
0 palmitic acid 3,5−Di−palmitictert−butyl acid−4−hydroxybenzoic acid,palmitic TMS der acidivative 3,5−Di−palmitictert−butyl acid−4−hydroxybenzoic acid, TMS der ivative
1
1 . C716 glutamate 1−Ethoserxyine−2−. propanol, TMS der ivative glutamate serine
. 1−Dibenzofurancarboxylic acid, 3,9b−dihydro−4,9b−dimethyl−, methylC716 ester 1−Ethoxy−2−propanol, TMS der ivative
. 1−Dibenzofurancarboxylic acid, 3,9b−dihydro−4,9b−dimethyl−, methyl ester palmitelaidic acid 02
0 palmitelaidic acid 02
0
C
C C
Silane1−Propanol,, dimeth TMSyl(3 −dermethivativylbeut−2−enyloxy)tridecyloxy− Silane1−Propanol,, dimeth TMSyl(3 −dermethivativylbeut−2−enyloxy)tridecyloxy− C
−
P
P − C1890( C35( NA ; NA
C1890( C35( ;
2
: 2
: phosphoric acid phosphoric acid .
FuranC2146−Phthalic2−carbo xylicacid,Pentadecan acid isobpalmitic [2utyl−−(2,2,6,6 14− acidol,octyl n− ester tetr(1TMS)amethyl−piperidin−4−yl)−ethFuryl]anC2146−amide−Phthalic2−carbo xylicacid,Pentadecan acid isobpalmitic [2utyl−−(2,2,6,6 14−− . acidol,octyl n− ester tetr(1TMS)amethyl−piperidin−4−yl)−ethyl]−amide xylose/lyxoseglucosedisaccharide xylose/lyxoseglucosedisaccharide
P 2 2−Phenoxathiinamine−10,10P −dioxide 2 Hydroxylamine (3TMS) 0 2−PhenoxathiinamineHydro−10,10xylamine−dioxide (3TMS)
0 Scopoletin, TBDMS der ivative Scopoletin, TBDMS der ivative
l
l
1
1
a
1 1 C407 C407 a . 1,2−Ethenediol, 2TMS der ivative
1,3−Dimethyl−2,6−dioxo−2,3,6,7−tetrahydro−1H−purine−8−carbaldeh1,3yde−Dimeth−oximeyl−2,6−dioxo−2,3,6,7−tetrahydro−1H−purine−8−carbaldehyde−oxime . 1,2−Ethenediol, 2TMS der ivative 0
1−Ethoxy−0 2−propanol, TMS der ivative 2
2 1−Ethoxy−2−propanol, TMS der ivative 2
4−Hydroxy−4,5−dihydro−2−methyl−3,3−bis(ethoxycarbonyl)−4−ethoxy−3H−pyrrole 2 0
: 4−Hydroxy−4,5−dihydro−2−methyl−3,3−bis(ethoxycarbonyl)−4−ethoxy−3H−pyrrole 0
stearic acid stearic acid : −
2.6 Boric acid, 3TMS der ivative − Boric acid, 3TMS der ivative .
. trisiloxane, 1,1,1,5,5,5 −hexamethyl−3−[(trimethylsilyl)oxy]− trisiloxane, 1,1,1,5,5,5 −hexamethyl−3−[(trimethylsilyl)oxy]−
.
. 9
C2166 C2166 9 P
Phosphetane, 2,2,3,4,4−pentamethyl−1−phenoxy−, 1−oxide Phosphetane, 2,2,3,4,4−pentamethyl−1−phenoxy−, 1−oxide P
P P
1 2−Phenoxathiinamine−10,10−dio2−xidePhenoxathiinamine−10,10−dioxide
1 2−Phenoxathiinamine−10,10−dio2−xidePhenoxathiinamine−10,10−dioxide
0
0
l
l
.
.
.
.
v
:
v :
− Phthalic acid, octyl 2 −propylpentyl ester
− Phthalic acid, octyl 2 −propylpentyl ester
a
a 0
1−0 Ethoxy−2−propanol, TMS der ivative 1−Ethoxy−2−propanol, TMS der ivative
:
:
−
l l
C1870( C1942( C2165 GMDCA1360021870( C1942( C2165 − 0
0 GMDA136002
0 0 1 Phenol, 2,4,6 −tri−tert−butyl−
Decan−2−yl trimethylsilyl phthalate Decan−2−yl trimethylsilyl1 phthalate 3−pyrazolidinone, 4,4−dimethyl−1−phenyl−2−(trimethPhenol,ylsilyl)− 2,4,63−−trpi−yrterazt−olidinonebutyl− , 4,4−dimethyl−1−phenyl−2−(trimethylsilyl)−
2
2 l
l palmitic acid palmitic acid
0
0
a
a
v
0
0
v
0 0
p 2−Dimethyl(trimethylsilyl)silyloxytetradecane p 2−Dimethyl(trimethylsilyl)silyloxytetradecane
C 1−Ethoxy−2−propanol, TMS der ivative
C 1−Ethoxy−2−propanol, TMS der ivative
:
:
:
:
.
.
−
−
a
a
l
l
l
l
1
1
a
a
v
v
0
0 0 0 1−Ethoxy−2−propanol, TMS der1iv−ativEthoexy−2−propanol, TMS der ivativ1−Ethoe xy−2−propanol, TMS der1iv−ativEthoexy−2−propanol, TMS der ivative
p 2−Dimethyl(trimethylsilyl)silyloxytetradecane
p 2−Dimethyl(trimethylsilyl)silyloxytetradecane
;
2
;
−
−
2
−
−
.
.
0
0
v
v P
2−Phenoxathiinamine−10,10P −dioxide 2−Phenoxathiinamine−10,10−dioxide
.
. a
C1840( C1439( C1840( C1439(a
a
a
v
v 0
0 2.4
p 2−Dimethyl(trimethylsilyl)silyloxytetradecane
p 2−Dimethyl(trimethylsilyl)silyloxytetradecane
0
0
0
0
;
;
1
1
0
0
p
−
p
−
v
v v v Glycerol (3TMS)
0 Glycerol (3TMS)
0
0 0
p 2−Dimethyl(trimethylsilyl)silyloxytetradecane
p 2−Dimethyl(trimethylsilyl)silyloxytetradecane
0
:
0
:
;
;
0
0
0
0
1
1
6
6
l
l
0
0
;
0
0
;
C
C p
p 2−Dimethyl(trimethylsilyl)silyloxytetr2−Dimethadecaneyl(trimethylsilyl)silyloxytetradecane p C1739( C1376( p 1Glycerol−Ethoxy −(3TMS)2−propanol, TMS der ivative 1Glycerol−2Etho−Dimethxy −(3TMS)2−yl(trpropanol,imethylsilyl)silylo TMS der ivxytetrativ2−Dimetheadecaneyl(trimethylsilyl)silyloxytetradecane
C17390 ( C1376(
0
.
−
.
−
;
;
0 0
NA 1
NA 1
0
0
1
1
6
6 a
a Glycerol (3TMS)
0 C
0 Glycerol (3TMS)
3
0
C
0
3
;
; ;
2.2 ;
0
P
0
.
P
.
0
0
1
1
0
0
6
1 6
Silane, diethylisohexyloxy(2−methylpentyloxy)− Silane, diethylisohexyloxy(2−methylpentylo1 xy)−
v
− v − Glycerol (3TMS)
C Glycerol (3TMS)
C
4
4
0
0
0
0
.
. 1
C1655( C1226( 1 1
C1655( C1226( 1
P
0
0
P
0
0
0
0
C
−
C
.
−
.
6
1
6
1 0
0 Glycerol (3TMS) Glycerol (3TMS) Glycerol (3TMS) Glycerol (3TMS)
− C
− 2−Dimethyl(trimethylsilyl)silyloxytetradecane p
C 2−Dimethyl(trimethylsilyl)silyloxytetradecane
p
.
.
0
0
P
0
0
P
0
0
6
6
6
6
0
1
0
1
−
−
0
0
C
C
−
C
C
−
P
0
P
0
;
.
.
;
.
.
P
P
0
0
1
1 1
C1414( C1125( C1414( C1125( 1
−
−
0
0
−
−
− −
0 2
0
P
P
P
P
1
0
0
1 0
−5000 0 5000 −5000 0−0.4 5000−0.2 0.0 0.2 −0.4 0 −0.2 0.0 0.2
−
−
−
− −
− Glycerol (3TMS) Glycerol (3TMS)
6
6 0
−5000 0 0 5000 −5000 0−0.4 5000−0.2 0.0 0.2 −0.4 −0.2 0.0 0.2
6
−
−
6
−
− C
! ! C
.
. −
− −5000 0 5000 −5000 0−0.4 5000−0.2 0.0 0.2 −0.4 −0.2 0.0 0.2 1
−2000 0 2000 −2000 0 −0.12000 0.1 0.3 −0.1 0.1 0.3 1
P
P 0 −5000PC2; pval:0.0681;0 5000 r^2=0.193−5000 0−0.4 5000−0.2 0.0PC2 0.2 −0 0.4 −0.2 0.0 0.2 − PC2; pval:0.0681; r^2=0.193 PC2
−5000 0−50005000 − 0 −50005000 0−−0.450005000−0.2 0−0.40.0 5000−0.20.2 −0.00.4 −0.20.2 −0.40.0 −0.20.2 0.0 0.2 − PC2; pval:0.0681;Scores r^2=0.193 PC2; pval:0.0681; r^2=0.193PC2 Loadings− PC2 PC5; pval:0.0101; r^2=0.066 PC5; pval:0.0101; r^2=0.066PC5 PC2; pval:0.0681;PC5 Scores r^2=0.193 PC2; pval:0.0681; r^2=0.193PC2 Loadings PC2 PC2; pval:0.0681;−5000 r^2=0.193Scores0 5000PC2; pvPral:0.0681;−e5000-Incubat ir^2=0.193on0−0.4Post-PC2I5000−n0.2cubatio0.0n Loadings0.2 −0.4 PC2−0.2 0.0 0.2 Scores Loadings PC2; pval:0.0681;ScoresPC2; r^2=0.193 pval:0.0681;PC2; r^2=0.193 pval:0.0681;PC2; r^2=0.193 pval:0.0681;PC2 r^2=0.193LoadingsPC2 PC2 PC2
702 0 Scores Scores Loadings Loadings
4 0
C. D. 0 PC2; pval:0.0681; r^2=0.193 PC2;b lankpval:0.0681; r^2=0.193PC2 PC2
0
4
7 0 0 blank 1,2,4−Triazole, 3−mercapto−4−phenyl−5−methyl−
0 703 3.4 freezeBlank
0
4
0 7
3 blank 0
5 1,2,4−Triazole, 3−mercapto−4−phenyl−5−methyl−
4 Scores Loadings
0 iceGlacier( Rock(Glacier( freezeBlank
0 0
. ice
4 0
7 blank
0 1,2,4−Triazole, 3−mercapto−4−phenyl−5−methyl− A. B. 3 C. 5 freezeBlank
1 Disiloxane, hexamethyl−
0
4 4
. ice
0 0 704 Figure 2 PCA GC-MS Analysis DOM compounds0 Succinic acid, 3 −A)chlorophen PCAyl 4−metho plotsxybenzyl ester showingblank separationblank along PC5 rock 7 rock
0 1,2,4−Triazole, 3−mercapto−4−phenyl−5−methyl−
3 5 freezeBlank 2 Disiloxane, hexamethyl−
1 Maltose( Threonic(acid( .
2 ice Serine (3TMS)
7
7
.
0
0 0
3.2 = 1,2,4−Triazole, 3−mercapto−4−phen1,2,4yl−T−r5iaz−methole, 3yl−−mercapto−4−phenyl−5−methyl−
3 rock 5
. freezeBlank freezeBlank 2
0 Disiloxane, hexamethyl−
. ice BenzSerineenecarbothioic (3TMS) acid, 2,4,6pyroglutamate−triethyl−, S−(2−phenylethyl) ester
0
.
3 3
rock 0 5
5 glycine =
2 aspartate
2 2
0 Disiloxane, hexamethyl− . . ice ice Diiodoacetylene 4 0 Serine (3TMS) 0 blank Benzenecarbothioic acid, 2,4,6 −triethyl−, S−(2−phenylethyl) ester Glutamate( Quinic(acid( . pyroglutamate . rock beta−alanine
= Sucrose, 8TMS derivative 0
^ glycine 2 2 aspartate
Pentadecan−1−ol, n− (1TMS) 0 Disiloxane, hexamethyl− Disiloxane, hexamethyl−
=
0 0
Homosalate, TMS derivative 7 Serine (3TMS)pBenzyroglutamateenecarbothioiclactate acid, 2,4,6 −triethyl−, S−(2−phenylethyl) ester
r .
0 rock rock pyroglutamate1,2,4−Triazole, 3−mercapto−4−phenyl−5−methyl−
= 0
0 beta−alanine glycine 2
freezeBlank 2 Sucrose, 8TMS derivative 2
^ asparNorthreonineleucinetate (3TMS)
0 BenzSerineenecarbothioic (3TMS) acid, 2,4,6glutamate−Sertriethineyl −(3TMS), S−ser(2−inephen3,5yleth−Diyl)−ter estert−butyl−4−hydroxybenzoic acid, TMS der ivative
. .
2 Diiodoacetylene 3 pyroglutamatepalmitelaidicpyroglutamate acid 02
3 = = lactate between glaciers (blue) and rock glaciers (red)r before incubation and B) no significant difference
705 ;
0 0
C996( Glycolic(acid(( 5 beta−alanine glycinephosphoric acid Sucrose, 8TMS derivative 2 ^ aspartate HydroScopoletin,xylamine TBDMS (3TMS)xylose/lyxoseglucosedisacchar der ivatividee
0 threonine . ice Norleucine (3TMS) Benzenecarbothioic acid,1,2 2,4,6−Ethenediol,−Benztriethenecarbothioicyl− ,2TMS S−(2− derpheniv 3,5acid,ativyleth−eDi 2,4,6yl)−ter estert−−trbiethutylyl−4−−, Shydro−(2−xybenzphenylethoic yl)acid, ester TMS der ivative
^ Dibenz[d,f]cycloheptane , 5−amino−1,2,3,8−tetramethoxy− pyroglutamate lactatepglutamateyroglutamate serine pyroglutamate
r 0
Methanone, (2−amino−5−chlorophenyl)(2−fluorophenyl)− beta−alanine 0 glycinepalmitelaidic acid 02 glycine 2 2 Boric acid, 3TMSSucrose der ivativ, 8TMSe derivative
; trisiloxane, 1,1,1,5,5,5−hexamethyl−3−[(trimethylsilyl)oxy]− 9 C349 ^ aspartate phosphoric acid aspartate Silane, diethyl(2−phenylethoxy)tetradecyloxy− 1 xylose/lyxoseglucosedisaccharDisiloxaneide , hexamethyl−
Terephthalic acid, octyl 2,4,40 −trimethylpentyl ester threonine r Norleucine (3TMS) Succinic acid, 2−fluorophenyl 2,4−dimeth ylpent−3−yl ester HydroScopoletin,xylamine TBDMS (3TMS) der ivative 3−pyrazolidinone, 4,4−dimeth0 yl−1−phenyl−2−(trimethylsilyl)− rock pyroglutamate lactate glutamate1,2−Ethenediol,ser ine2TMS3,5 −derDi−ivterativt−ebutyl−4−hydroxybenzoic acid, TMS der ivative
SuccinicSilaneCyclodisilazaneSilane, diethacid,,yldodecylo di(2dimethhomoser, 2,2,4,4−fluorophenyl(dimethxypentyloine−r tetramethyl)yldecylo esterxy−yl−xysilylo1,3−diphenxy)decyloyl− xy− beta−alanine betapalmitelaidic−alanine acid 02 Sucrose, 8TMS derivative Sucrose, 8TMS derivative
;
^ ^
2 phosphortrBorisiloicxane acid,ic acid, 1,1,1,5,5,5 3TMS der−ivheativxamethe yl−3−[(trimethylsilyl)oxy]− 9
1 xylose/lyxose 0 C884( C589( 0 threoninePhenol, 2,4,63−−trpi−yrterazglucosetdisacchar−olidinonebutyl− ,ide 4,4−dimethyl−1−phenyl−2−(trimethylsilyl)−
1 Norleucine (3TMS) Serine (3TMS) HydroScopoletin,xylaminepalmitic3,5 TBDMS− (3TMS)Di acid−ter dert−bivutylativ−e4−hydroxybenzoic acid, TMS der ivative ; pyroglutamate 1,2−Ethenediol,pyroglutamate 2TMS der ivative
. glutamatelactate serine lactate r similar to Cyclohexasiloxane, dodecamethyl r Silane, diethyldecyloxyoctyloxy− C palmitelaidic acid 02 Siloxane hydroxybenzoic acid = 3−Methyl−3−(N−methyl−2−pyrrolyl)−1,2−diphenylcyclopropene similar to Cyclopentasilo xane, decameth; yl phosphorictr Boracidisiloicxane acid,, 1,1,1,5,5,5 3TMS der−ivheativxamethe yl−3−[(trimethylsilyl)oxy]−
Cyclooctasiloxane, heSilanexadecameth, diethyldodecyloyl− 9 xy(2−methoxyethoxy)− threonine xylose/lyxoseglucosedisaccharide threonine
Norleucine (3TMS) Norleucine (3TMS) 1
1 HydroScopoletin,xylaminePhenol, TBDMS (3TMS) 2,4,6 der iv3−ativ−trpi−yreterazt−olidinonebutyl− , 4,4−dimethyl−1−phenyl−2−(trimethylsilyl)− 2.8 1 Benzenecarbothioic acid, 2,4,6palmitic3,5−−trDiieth −acidteryl−t−, Sbutyl−(2−4phen−hydroylethxybenzyl) 3,5esteroic−Di acid,−tert −TMSbutyl der−4−ivhativydroexybenzoic acid, TMS der ivative 0 1,2−glutamateEthenediol, 2TMSser derinepyroglutamateivative glutamate serine
0 palmitelaidic acid 02 palmitelaidic acid 02
8
0
2
3
; ; phosphorSilaneic acid, dimethyl(octadecyloxy)propyl− C glycine
2 phosphoric acid phosphoric acid . trBorisiloicxane acid,, 1,1,1,5,5,5 aspar3TMState der−ivheativxamethe yl−3−[(trimethylsilyl)oxy]−
9 xylose/lyxose xylose/lyxose . P 2−Phenoxathiinamineglucosedisacchar−10,10ide −dioxide glucosedisaccharide
1 Hydroxylamine (3TMS) Hydroxylamine (3TMS) 1 Scopoletin,Phenol, TBDMS 2,4,63−−tr pderi−yrterazivtativ−olidinonebutyle Scopoletin,− , 4,4−dimeth TBDMSyl−1 −derphenivativyl−e2−(trimethylsilyl)− 5H−Pyrano[2,3,4,5−lmn]phenanthridin−5−one . 1,2−Ethenediol, 2TMSpalmitic der ivacidativ1,2e −Ethenediol, 2TMS der ivative C815( C531( Scopoletin, TBDMS der1 ivative
NA C beta−alanine 0
2 3−Dimethyl(phenyl)silyloxypentadecane Sucrose, 8TMS derivative 2
^ trBorisiloicxane acid,, 1,1,1,5,5,5 3TMS der −ivheativxamethe trBorisiloyl−ic3xane− acid,[(tr,imeth 1,1,1,5,5,5 3TMSylsilyl)o der−ivxy]heativxameth−e yl−3−[(trimethylsilyl)oxy]− 9
706 between glacier types after incubation (p-value9 of 0.119 and 0.0681 for PC1 and PC2,
.
0
1
1
0 P
1 Phenol, 2,4,6−tri−tert−butyl− 0 32−pPhenoyrazolidinonexathiinamine, 4,4−−dimeth10,10−yldio−1xide−phenyl−2−(trimethylsilyl)−
C palmitic acid
1 .
0 pyroglutamate lactate
r
: C
Phenylethylmalonamide, 2TMS derivative 2
0 3
. threonine
1 1
l Phenol, 2,4,6−tri−tert−butyl− Phenol, 2,4,6−tri−tert−butyl−
P 3−pyrazolidinone, 4,4−dimethyl−31−−pphenyrazolidinoneyl−2−(trimeth, 4,4−ylsilyl)dimeth−yl−1−phenyl−2−(trimethylsilyl)− 2−PhenoNorxathiinamineleucine (3TMS)−10,10−dioxide
0 palmitic acid 3,5−Di−palmitictert−butyl acid−4−hydroxybenzoic acid, TMS der ivative 1 1−C716Dibenzofurancarboxylic acid, 3,9b−dihydro−4,9b−dimethyl−, methyl ester . glutamate 1−Ethoserxyine−2−propanol, TMS der ivative
. palmitelaidic acid 02
0 C
Silane1−Propanol,, dimeth TMSyl(3 −dermethivativylbeut−2−enyloxy)tridecyloxy− C
− P
C1890( C35( NA ; 2 : phosphoric acid
FuranC2146−Phthalic2−carbo xylicacid,Pentadecan acid isobpalmitic [2utyl−−(2,2,6,6 14− . acidol,octyl n− ester tetr(1TMS)amethyl−piperidin−4−yl)−ethyl]−amide xylose/lyxoseglucosedisaccharide P 2 2−Phenoxathiinamine−10,10−dioxide 0 HydroScopoletin,xylamine TBDMS (3TMS) der ivative
2.6 l
1 1 C407 a 1,3−Dimethyl−2,6−dioxo−2,3,6,7−tetrahydro−1H−purine−8−carbaldehyde−oxime . 1,2−Ethenediol, 2TMS der ivative
0 1−Ethoxy−2−propanol, TMS der ivative 2
4−Hydroxy−4,5−dihydro−2−methyl−3,3−bis(ethoxycarbonyl)−4−ethoxy−3H−pyrrole 2 0 stearic acid :
− Boric acid, 3TMS der ivative . . trisiloxane, 1,1,1,5,5,5 −hexamethyl−3−[(trimethylsilyl)oxy]−
C2166 9 P Phosphetane, 2,2,3,4,4−pentamethyl−1−phenoxy−, 1−oxide P
1 2−Phenoxathiinamine−10,10−dio2−xidePhenoxathiinamine−10,10−dioxide
0
l
.
.
v :
− Phthalic acid, octyl 2 −propylpentyl ester a
0 1−Ethoxy−2−propanol, TMS der ivative
: l
C1870( C1942( C2165 GMDA136002 −
0 0
Decan−2−yl trimethylsilyl1 phthalate Phenol, 2,4,63−−trpi−yrterazt−olidinonebutyl− , 4,4−dimethyl−1−phenyl−2−(trimethylsilyl)− 2
l palmitic acid
0
a
v
0 0
p 2−Dimethyl(trimethylsilyl)silyloxytetradecane
C 1−Ethoxy−2−propanol, TMS der ivative
:
:
.
−
a
l respectively). C) The Shannon-Wiener Index (SW)l for chemical diversity was similar between
707 1
a
v 0
0 1−Ethoxy−2−propanol, TMS der1iv−ativEthoexy−2−propanol, TMS der ivative
p 2−Dimethyl(trimethylsilyl)silyloxytetradecane
;
2
−
−
.
0 v
2.4 P 2−Phenoxathiinamine−10,10−dioxide
C1840( C1439( .
a
a
v 0
p 2−Dimethyl(trimethylsilyl)silyloxytetradecane
0
0
;
1
0
p
−
v
v Glycerol (3TMS)
0 0
p 2−Dimethyl(trimethylsilyl)silyloxytetradecane
0
:
;
0
0
1
6
l
0
0
;
C p
C1739( C1376( p 1Glycerol−2Etho−Dimethxy −(3TMS)2−yl(trpropanol,imethylsilyl)silylo TMS der ivxytetrativ2−Dimetheadecaneyl(trimethylsilyl)silyloxytetradecane
0
.
−
; 0
NA 1
0
1
6
a Glycerol (3TMS)
0
C
0
3
;
;
0
.
P
0 1
2.2 0 6
Silane, diethylisohexyloxy(2−methylpentylo1 xy)− v
− Glycerol (3TMS) C
708 glaciers and rock4 glaciers before incubation, however microbial metabolism increased chemical
0
0
. 1
C1655( C1226( 1
P
0
0
0
C
−
.
1 6
0 Glycerol (3TMS) Glycerol (3TMS)
− C
p 2−Dimethyl(trimethylsilyl)silyloxytetradecane
.
0
0
P
0
6
6
0
1
−
0
C
C
−
P
0
;
.
.
P
0 1
C1414( C1125( 1
−
0
−
−
0
P
P
1 0
2 −5000 0 5000 −0.4 0 −0.2 0.0 0.2
− −
− Glycerol (3TMS) 6
0 −5000 0 5000 −0.4 −0.2 0.0 0.2
6 − Pre-Incubation Post-Incubation −
! C . − 709 diversity in glacier DOM and decreased chemical diversity−5000 in rock0 glacier5000 DOM. −0.4 −0.2 0.0 0.2
−2000 0 2000 −0.1 0.1 0.3 1 P −5000PC2; pval:0.0681;0 5000 r^2=0.193 −0 0.4 −0.2 0.0PC2 0.2 − −5000 0−50005000 0 5000 −0.4 −0.2 −0.40.0 −0.20.2 0.0 0.2 PC2; pval:0.0681; r^2=0.193 − PC2 PC5; pval:0.0101; r^2=0.066 PC5 PC2; pval:0.0681; r^2=0.193 PC2 710 PC2;PC2; pv pval:0.0681;−al:0.0681;5000 PC2; r^2=0.193 r^2=0.193 0pval:0.0681;5000 r^2=0.193 −0.4 PC2−PC20.2 0.0 PC20.2 711 PC2; pval:0.0681; r^2=0.193 PC2
33 bioRxiv preprint doi: https://doi.org/10.1101/115808; this version posted March 10, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
Figure712 713 Figure 3 Molecular distribution of GC-MS identified compounds A) Distribution of
714 compounds by ion intensity pre- (orange) and post-incubation (brown). Many of the compounds
715 present before incubation that were of intermediate abundance were metabolized. The most
716 abundant molecules were different between pre- and post- incubation metabolomics analysis (see
717 Table 4).
718 719 720 721
34 bioRxiv preprint doi: https://doi.org/10.1101/115808; this version posted March 10, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
722
35 bioRxiv preprint doi: https://doi.org/10.1101/115808; this version posted March 10, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
723 Figure 4 Dissolved oxygen consumption curves from glaciated watersheds (n=8). Values were
724 averaged for each of the glaciers (blue) and rock glaciers (red), and the analytical control (dotted
725 black). All curves were smoothed using a third order polynomial regression function (R2=0.999).
726 Here we show 95% Confidence Intervals in light blue for glaciers and in pink for rock glaciers.
727 Glaciers consumed a larger portion of available DOM during the course of the incubation.
728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763
36 bioRxiv preprint doi: https://doi.org/10.1101/115808; this version posted March 10, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
764 Tables 765 766 Table 1 Characteristics of DOM and microbial metabolism fed DOM from glaciers and rock
767 glaciers. C:N is the ratio of carbon to nitrogen for pre-incubation DOM. D.O (dissolved oxygen)
768 and DOC (dissolved organic carbon) represent the change in concentration of each during the
769 course of the incubation (mg L-1). RQ = respiratory quotient, SW = Shannon Wiener Diversity
770 Index, and SW = change is SW of DOM before and after the incubation. Bold values represent
771 significant differences between glaciers and rock glaciers (p<0.05), standard deviations of mean
772 values are listed in parentheses.
773 Site Type C:N D.O. DOC RQ SW SW Isabelle G 1.65 6.03 2.50 0.42 2.92 0.19 Peck G 2.02 3.95 1.89 0.48 2.89 0.88 Andrews G 3.00 4.11 2.64 0.64 2.68 0.13 Arapaho G 2.73 3.97 2.84 0.72 2.84 0.52 Peck RG 2.63 3.52 2.09 0.59 2.80 0.54 Navajo RG 1.48 2.81 1.71 0.61 2.83 -0.32 Arapaho RG 2.45 4.12 3.00 0.73 2.79 -1.10 Taylor RG 0.86 2.69 2.25 0.83 2.80 -0.01 Mean G 2.35 (0.62) 4.51 (1.02) 2.47 (0.41) 0.56 (0.14) 2.83 (0.11) 0.43 Mean RG 1.85 (0.83) 3.29 (0.67) 2.26 (0.54) 0.69 (0.11) 2.80 (0.02) -0.22 774 775
37 bioRxiv preprint doi: https://doi.org/10.1101/115808; this version posted March 10, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
776 777 Table 2 DOM compounds that defined the differences between glaciers and rock glaciers before
778 incubation along PC5 from Figure 3A. Mass to charge ratios (m/z) ratios are the largest ion
779 observed for each compound. Normalized intensities (N.I.), an indicator of compound
780 concentration, are given for glaciers and rock glaciers. Bold values indicate which glacier type
781 had a higher normalized intensity (N.I) on average.
782 783 DOM Peak m/z N.I. Glacier N.I. Rock Glacier Maltose 568.3 4817 2201 Glutamate 365.3 5393 2704 C996 94.2 28959 3589 C884 565.3 14584 1468 C815 419.1 2486 569 C1890 613.2 805 346 C1870 642 1516 1229 C1840 640.1 384 245 C1739 489.1 2407 1376 C1655 480.2 17313 9597 C1414 507.2 550 479 Threonic Acid 411 117 2730 Quinic Acid 409.2 2136 7891 Glycolic Acid 279.2 2920 16696 C589 649.5 1605 1868 C531 343.2 7446 22845 C35 348.2 1422 2188 C1942 535.1 846 1062 C1439 406.2 598 861 C1376 440.2 2623 3610 C1226 634.1 708 1602 C1125 468.1 3550 7504 784 785 786
38 bioRxiv preprint doi: https://doi.org/10.1101/115808; this version posted March 10, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
787 Table 3 Results from carbon decay model where BO represents the size of the recalcitrant pool of
-1 -1 788 DOM (mg C L ), B1 is the size of the bioavailable pool (mg C L ), k is the decay constant (mg
789 C L-1 h-1), and BGE = bacterial growth efficiency. Glaciers had a larger percentage of BDOM
790 compared to rock glaciers and rock glaciers had a larger proportion of recalcitrant C compared to
791 glaciers. BGE was also higher for glaciers than rock glaciers. Bold values represent significant
792 differences between glaciers and rock glaciers (p<0.05) and standard deviations of mean values
793 are listed in parentheses.
794 795 796 Site Type B0 B1 k % BDOM % Recalcitrant BGE Andrews Glacier 3.20 5.59 0.001 48.23 51.77 0.37 Arapaho Glacier 3.72 5.20 0.001 47.74 52.26 0.39 Isabelle Glacier 1.35 7.03 0.001 60.90 39.10 0.39 Peck Glacier 3.78 5.24 0.001 46.06 53.94 0.17 Arapaho Rock Glacier 5.32 3.80 0.002 32.05 67.95 0.13 Navajo Rock Glacier 5.64 3.42 0.001 29.89 70.11 0.03 Peck Rock Glacier 3.31 5.24 0.001 45.74 54.26 0.14 Taylor Rock Glacier 4.69 3.83 0.001 36.59 63.41 0.07 Mean G Glacier 3.38 (1.09) 6.35 (1.06) 0.001 52.83 (9.73) 47.17 (7.03) 0.263 (0.13) (0.000) Mean RG Rock Glacier 4.74 (1.26) 4.07 (1.12) 0.001 37.18 (10.23) 62.82 (6.84) 0.157 (0.16) (0.000) 797 798
39 bioRxiv preprint doi: https://doi.org/10.1101/115808; this version posted March 10, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
799 Table 4 The top 25 compounds present in pre- and post-incubation samples organized by
800 normalized intensity. Glaciers and rock glaciers had the same top 25 compounds before and after
801 incubation. Microbial metabolism altered compounds present, resulting in a different set of
802 compounds post incubation.
803 Pre-Incubation Post-Incubation Succinic Acid Glycerol Octyl 2-propylpentyl ester-phthalic acid 2,4,6-triethyl-, S-(2-phenylethyl) ester- benzenecarbothioic acid Octyl 2,4,4-trimethylpentyl ester-terephthalic acid Pyroglutamate 3-chlorophenyl 4-methoxybenzyl ester-succinic acid 10-dioxide-2-phenoxathiinamine-10 pentadecan-1-ol Serine Hydroxylamine 1-Ethoxy-2-propanol Homosalate Palmitic Acid p-cyanophenyl 4'-heptyl-4-biphenylcarboxylate Sucrose Scopoletin Beta-alanine Diiodoacetylene-1 2,4,6-tri-tert-butyl-phenol Palmitic Acid Aspartate Diiodoacetylene Boric Acid Phosphoric Acid Stearic Acid (2-amino-5-chlorophenyl)(2-fluorophenyl)- Norleucine methanone Stearic Acid Homoserine phenyl ester-2-thiophenecarboxylic acid Glycine phenylethylmalonamide n-pentadecan-1-ol 3-Methyl-3-(N-methyl-2-pyrrolyl)-1,2- D-pinitol diphenylcyclopropene 5-amino-1,2,3,8-tetramethoxy- N-methoxycarbonyl-,isohexyl ester-l-valine deibenz[d,f]cycloheptane Furan-2-carboxylic acid [2-(2,2,6,6-tetramethyl- 3,5-Di-tert-butyl-4-hydroxybenzoic acid piperidin-4-yl)-ethyl]-amide 1,3-Dimethyl-2,6-dioxo-2,3,6,7-tetrahydro-1H- 1-ethyl-1H-Benzimidazole purine-8-carbaldehyde-oxime p-Cyanophenyl p-(2-butoxyethoxy)benzoate Phosphoric acid 2-fluorophenyl 2,4-dimethylpent-3-yl ester-succinic Tyrosine acid Homoserine Sarcosine Pre-Incubation Post-Incubation 804
40 bioRxiv preprint doi: https://doi.org/10.1101/115808; this version posted March 10, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.
805 806 807 808 809 810 811 812 813
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