www.sciencemag.org/cgi/content/full/science.1258955/DC1

Supplementary Material for

Dilution limits dissolved organic carbon utilization in the deep ocean

Jesús M. Arrieta,* Eva Mayol, Roberta L. Hansman, Gerhard J. Herndl, Thorsten Dittmar, Carlos M. Duarte

*Corresponding author. E-mail: txetxu@mail.com

Published 19 March 2015 on Science Express

DOI: 10.1126/science.1258955

This PDF file includes:

Materials and Methods Figs. S1 to S9 Tables S1 and S2 Full Reference List

Materials and Methods Sampling sites

A total of 14 bacterial growth experiments were conducted using deep-water samples collected at different locations in the Tropical Eastern Pacific, the Tropical Western Atlantic and the North Atlantic from depths between 1,000 and 4,200 m (Experiments labeled A through N). Two additional DOC characterization experiments were carried out using water collected in the North Atlantic (Experiments O and P, Fig. S1, Table S1).

Preparation of DOC extracts

Deep seawater samples (10 L) were collected using Niskin bottles. Particulate matter including microbes were removed by filtration through 0.2µm PES cartridges (Vivaflow 200TM, Sartorius) prior to absorbing the dissolved organic carbon (DOC) onto 1g Bond-Elut-PPL solid-phase extraction (SPE) columns (Agilent) following the protocol described in Dittmar et al. (7). Following absorption, DOC was eluted from the columns using 6 mL of HPLC grade methanol and the methanol was completely evaporated by blowing synthetic air over the surface of the extract.

Microbial growth at different concentrations of natural DOC

The DOC extract corresponding to 10 L of seawater was finally dissolved in 100 mL untreated seawater from the original location. Triplicate 100 mL cultures containing untreated seawater from the corresponding location were spiked with 2, 8 or 18 mL of the DOC extract in order to obtain a final DOC concentration approximately 2, 5 and 10 times the in situ DOC concentration, assuming a ~40% extraction efficiency for deep oceanic DOC (7). Triplicate cultures containing only untreated seawater were used as controls. In three of the stations (H,I and J), additional extraction controls were prepared by adding 18 mL of an “extract” from fresh SPE columns treated in the same manner. These controls served as a check for procedural contamination due to the manipulations and the materials used for extraction (Fig. S2). In experiments K-N, additional cultures were established to measure respiration in the middle of the exponential growth. Thus, for these 4 experiments bacterial growth measurements were performed in quadruplicates. All glass- and plastic-ware used for these experiments was acid-washed and rinsed with Milli-Q type water prior to use. The seawater cultures were incubated in the dark at in situ temperature and followed for 10 to up to 22 days. In addition, the cultures from experiments K-N were left in the incubators after the end of the cruise and a last abundance and DOC sample were obtained after the ship arrived in the harbour nearly a month later.

DOC concentrations

Samples for DOC analysis (10 mL) were collected in the beginning and at the end of the experiments, sealed in muffled glass ampoules containing 50 µL of concentrated phosphoric acid and stored for later analysis by high-temperature catalytic oxidation/NDIR detection (28) using a Shimadzu TOC-VCSH.

Microbial Growth

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Samples for bacterial abundance (1 mL) were collected every two to four days, fixed with paraformaldehyde (1% final concentration), stained with SYBRGreen I and analyzed on board using a flow cytometer (29). Microbial abundances were transformed into C equivalents by using a conversion factor of 12 fg C cell-1 (30) for the calculation of PGE and other derived variables. Specific growth rates in the cultures were estimated from abundance data by linear regression as the slope of the line representing the natural logarithm of bacterial abundance against time during the exponential growth phase (31).

Some of the experiments showed almost undetectable growth in the controls, thus, we chose a modified formulation of the Monod model (32) which allows for a term expressing the maintenance costs of microbial metabolisms and thus allowing for zero bacterial growth in the presence of significant amounts of DOC such as those observed in the controls

[1] Where µmax represents the maximum specific growth rate, b represents the

maintenance coefficient as the rate of consumption of endogenous biomass necessary to cover maintenance requirements, and KS the half-velocity constant of the classical Monod formulation of growth (32). These parameters were estimated by fitting the observed growth rates (µ) to the measured initial DOC concentrations (S) by least squares nonlinear regression. Solving equation 1 for µ=0, yields Smin, the minimum amount of substrate below which all the substrate taken up is channeled to cover maintenance costs and no growth is possible.

[2]

Utilization of different components of the DOC pool A different experimental setup was designed to elucidate which components of the

DOC pool were utilized by bacteria. DOC concentrates were prepared as described earlier from 70 L of seawater using a different PPL column (1g) for every 10 L of sample. Methanolic DOC extracts were pooled, carefully dried and re-dissolved in 115 mL seawater from the same location. Assuming a ~40% extraction efficiency (7), 17 ml of this extract were added to triplicate bottles containing 1L of unfiltered seawater from the same location resulting in a final DOC concentration approximately 5 times higher than the original. Controls consisted of 5L of unamended seawater in triplicate. A second type of control was prepared by adding 17 ml of extract to 1L of 0.2µm filtered seawater, being identical to the 5 times concentrated treatment except for the microbial component. The purpose of this second type of control was to account for the biases caused by abiotic factors such as repeated extraction through PPL columns since different components of the DOC pool are likely to be extracted with different efficiency. Two additional experiments (O and P) were run using this setup for a period of 40 and 37 days, respectively, but the abiotic controls were only kept for 3 days since it was impossible to ensure that they would remain free of prokaryotic growth for several weeks. DOC samples were withdrawn from all samples at the beginning and at the end of the experiment. The DOC remaining at the end of the experiment was extracted again using PPL columns and the methanolic extracts stored at -20ºC for later analysis by FT-ICR-

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MS. Any bias caused by repeated DOC extraction were compensated by using values from the original sample as initial signal for controls and the values from the abiotic control as initial signal for the concentrated samples.

Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) fingerprinting of DOC

FT-ICR-MS characterization of DOC offers the possibility to characterize thousands of different organic molecules simultaneously in natural water samples. Briefly, DOC was concentrated from ~5L of 0.2 µm-filtered seawater using PPL colums as described earlier and the methanolic extracts were stored at -20ºC until analysis. Extracts were diluted to approximately 15 ppm in 1:1 methanol:ultrapure water and then analyzed on a 15 Tesla Solarix FT-ICR-MS (Bruker Daltronics) in electrospray ionization (ESI) negative mode. Resulting spectra were calibrated with an internal calibration list using the Data Analysis software package (Bruker Daltronics), and in-house Matlab routines were used to process the mass-to-charge, resolution, and intensity for each peak in all samples.

This technique is not quantitative but, with appropriate standardization, it allows to compare the relative abundance of the different molecules detected across samples, thus showing which molecules have been consumed or produced. The signals of the DOC fingerprints obtained by FT-ICR-MS between 200 and 700 m/z were normalized by calculating the ‰ contribution of each peak to the total signal in the sample. Using these normalized values, an index of utilization can be estimated for each compound by taking into account the consumption of bulk DOC measured in regular DOC samples. Thus, when a significant loss of bulk DOC is observed, the relative contribution (normalized signal) of a truly recalcitrant molecule (or any molecule that has not been utilized for whatever reason) is expected to increase according to the following equation

[3] where ‰ef is the expected normalized signal at the end of the experiment, ‰i is the

normalized signal of the compound measured at the beginning of the experiment and DOCi and DOCf the measured initial and final concentrations of DOC respectively. Therefore, a utilization index can be constructed for each DOC component by subtracting its expected relative contribution calculated from the measured bulk DOC consumption from the observed relative contribution at the end of the experiment

[4] where ‰f is the normalized signal measured at the end of the experiment. Negative

values of Iu indicate consumption, while positive values indicate production and values equal to 0 are expected for recalcitrant and other compounds that were not consumed.

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Fig. S1. Geographical situation of the sampling stations

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Fig. S2. Prokaryotic abundance in experimental treatments containing approximately 2, 5 and 10 times the in situ DOC concentration vs controls containing unnamended seawater. Error bars represent the standard error of the mean of triplicate cultures.

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Fig. S3. Specific growth rates at different concentrations of DOC, horizontal error bars represent the standard deviation of the mean initial DOC concentration measured in the triplicate cultures and vertical error bars represent the standard deviation of the mean of the specific growth rates estimated for each of the triplicate cultures.

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Fig. S4. Specific growth rates measured in controls and samples spiked with a “blank extract” of SPE columns processed in the same way as the DOM extracts except that no seawater was applied. The volume of extraction blank was equal to the maximum used in the experiments (18 mL). The bars show the mean ± standard deviation of triplicate seawater cultures and the symbols the specific growth rates measured in each replicate.

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Fig. S5. Prokaryotic growth efficiency calculated from simultaneous measurements of prokaryotic abundance and oxygen consumption during the exponential phase of growth.

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Fig S6. DOC consumption measured in experiments K-N at different concentrations of added DOC. The bars represent the average ± SE of triplicate cultures. Please note the larger axis on panel M.

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Fig. S7. FT-ICR-MS fingerprints of natural DOC at the onset of the experiments. Peaks represent the normalized signal intensity for extractable molecules of different mass in the DOC pool.

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Fig. S8. Bray-Curtis cluster analysis of FT-ICR-MS fingerprints of natural DOC at the beginning and at the end of the experiments in concentrated samples (5x DOC) and in controls (1xDOC). The normalized mass spectrum of DOC components obtained by FT-ICR-MS for each replicate was used separately. The numbers at each node represent the bootstrap probability (green) or approximately unbiased probability (red) obtained in 100,000 bootstrap trials using the pvclust (33) and vegan (34) software packages in R (35). Triplicates appear always clustered together under nodes with 100% probability, indicating strong evidence for consistent and significant differences among treatments.

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Fig. S9. Index of utilization of different organic compounds detected by FT-ICR-MS of DOC extracts. For each experiment, the upper row shows the pattern of utilization in three replicates of natural, unconcentrated DOC. The lower row shows utilization patterns in replicates containing approximately 5 times the original DOC concentration. Values smaller than 0 indicate consumption while values larger than 0 indicate production.

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Table S1. Location and background data describing the water masses used for the experiments. Samples are named with letters A-P throughout the manuscript. Sample Latitude Longitude Depth

m Temperature

°C Salinity Oxygen

µmol l-1 DOC

µmol C l-1 A 17.37° N 130.61° W 2003 2.13 34.64 86 42.2 B 16.63° N 127.54° W 1999 2.08 34.64 88 42.0 C 12.50° N 110.40° W 2002 2.28 34.64 81 44.5 D 8.75° N 93.14° W 2001 2.34 34.65 83 37.7 E 8.14° N 90.37° W 1994 2.34 34.65 84 42.4 F 12.36° N 74.04° W 2346 4.11 34.98 205 48.3 G 18.06° N 57.80° W 1998 3.61 34.98 248 47.7 H 19.00° N 55.15° W 3199 2.57 34.92 243 44.1 I 21.74° N 47.79° W 1002 6.26 34.96 148 47.0 J 23.74° N 41.90° W 2600 3.10 34.97 234 43.9 K 49.03° N 14.13° W 4194 2.51 34.91 225 43.7 L 51.64° N 19.05° W 2800 3.04 34.94 252 48.6 M 51.07° N 25.86° W 3206 2.92 34.95 250 49.8 N 52.45° N 37.02° W 3500 2.66 34.93 258 51.0 O 52.64° N 32.21° W 3218 2.89 34.97 253 51.9 P 54.98° N 29.14° W 2900 2.86 34.97 252 53.4

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Table S2. Estimated parameters of the substrate-dependent growth relationship for each experiment as described in equations 1 and 2.

Experiment

µmax d-1

Ks µmol C L-1

b d-1

Smin µmol C L-1

A 0.754 269.0 0.098 40 B 0.469 108.3 0.133 43 C 0.501 456.4 0.038 37 D 0.583 126.4 0.044 10 E 0.336 147.1 0.000 - F 0.241 74.8 0.000 - G 0.629 83.0 0.068 10 H 0.793 62.3 0.245 28 I 0.713 522.7 0.032 25 J 2.186 1976.0 0.061 57 K 1.581 4.9 1.334 27 L 0.307 184.6 0.000 - M 0.247 273.4 0.000 - N 0.188 135.6 0.000 -

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