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Carbon cycling in benthic diatom mats: Novel applications of LC/IRMS

Moerdijk-Poortvliet, T.C.W.

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Citation for published version (APA):Moerdijk-Poortvliet, T. C. W. (2016). Carbon cycling in benthic diatom mats: Novel applications of LC/IRMS.

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Download date: 29 Jun 2020

Seasonal changes in the production of extracellular polymeric substances and its fate to the heterotrophic bacterial community in an intertidal diatom mat In preparation for Limnology and Oceanography Tanja C.W. Moerdijk-Poortvliet1, Olivier Beauchard1, Lucas J. Stal1,2, Henricus T.S. Boschker1 1NIOZ Royal Institute for Sea Research and Utrecht University, PO Box 140, 4401 AC Yerseke, the Netherlands. 2University of Amsterdam, Department of Aquatic Microbiology, PO Box 94248, 1090 GE Amsterdam, The Netherland

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Abstract

In this in-situ study, the seasonal dynamics of extracellular polymeric substances (EPS) and short chain organic acids (SCOA) exuded by benthic diatoms and the use of these exudates as a carbon source by heterotrophic bacteria were investigated. By using an in-situ 13C pulse-chase method the fate of EPS was followed for 5 consecutive days. These labeling experiments were done at 2-month intervals during one year. The EPS were recovered from the sediment as two operational defined fractions (i.e. water-extractable and EDTA-extractable EPS). In addition, a variety of environmental parameters and photosynthetic characteristics was measured. The EPS consisted mostly of carbohydrates with a small contribution from amino acids. The production rates of the carbohydrates and amino acids in the EPS fractions were remarkably different between seasons. This resulted in a more heterogeneous composition of the EPS in spring and summer when compared to the rest of the year and suggested a different function for these exopolymers. The seasonal differences of EPS production correlated to differences in light intensity and temperature. The role of the extracellular amino acids was conceived as to interconnect polysaccharide chains in the EPS and hence forms a structure that is important for adhesion of the diatom cell and for defense against grazing. In order to compare our results with other studies that use another operational defined fraction (e.g. the artificial seawater/DOWEX cation-exchange protocol), a comparison of EPS extraction protocols was made. No difference was found between water-extractions using Milli-Q or artificial seawater, however large differences were found between EDTA and DOWEX extractions. Although both methods extracted the same type of EPS in terms of composition, the EDTA extraction was 4-fold more efficient compared to the DOWEX agent. From February until June the biomass and production of diatoms and bacteria were closely coupled. It was concluded that SCOA were the most important substrates for the bacteria. Especially sulfate reducing bacteria (SRB) benefited from associating with SCOA-releasing diatoms. From August on, the coupling of biomass and production of diatoms and bacteria became less strong and was almost lost in December. During the period of August until December, EPS produced by diatoms promoted the growth of other bacterial taxa rather than SRB, and the production of SCOA was low. The seasonal variation of exudates produced by diatoms therefore played an important role in shaping the community composition and diversity of the associated bacteria.

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Introduction

Intertidal sediments support extensive and diverse populations of microorganisms, which develop complex microbial communities. In temperate regions benthic diatoms are the dominant organisms of the microphytobenthic communities and they contribute a major part of the total autotrophic production in these intertidal benthic ecosystems (Admiraal et al., 1984; MacIntyre & Cullen, 1996; Underwood & Kromkamp, 1999). Diatoms may be abundantly present and the biofilms they produce color the sediment surface brown. These benthic diatom mats exhibit high rates of photosynthesis and a substantial proportion of the inorganic carbon they fix may be exuded into the environment as extracellular polymeric substances (EPS) or short chain organic acids (SCOA) (Mc Kew et al., 2013; Underwood & Paterson, 2003). EPS and SCOA-releasing diatoms stimulate bacterial growth and the variety of compounds produced likely plays a role in generating and maintaining bacterial diversity (Amin, 2012).

EPS are exuded as a mechanism to allow motility of diatoms, which is essential for epipelic species because it enables them to migrate in and out the photic zone, following the tides (Consalvey et al., 2004). However, EPS are also exuded through other mechanisms and play an important role in the ecology of diatom mats (Edgar & Pickett-Heaps, 1984). EPS are sometimes produced as the result of unbalanced growth (i.e. growth that does not lead into proportional synthesis of the cell’s structural components because the essential nutrients (e.g. nitrogen, phosphorus, sulfur and iron) are lacking or limiting and components are synthesized that lack these nutrients (e.g. carbohydrates and lipids)) (Stal, 2010). Because the cell’s storage capacity is limited, excess fixed carbon is exuded as EPS. After exudation, EPS cumulate in the surficial sediments where they can be degraded by bacteria, or washed away during tidal immersion and/or become part of the sediment structure (Yallop et al., 1994; Stal, 2010; Taylor et al., 2013). Depending on environmental conditions and the nutrient concentrations, EPS are low-molecular dissolved compounds or consist of more complex colloidal or gel-like material, such as mucilage. The diatoms and this mucilage form together with the sediment particles a coherent structure - the biofilm or mat - that stabilizes the sediment surface and avoids re-suspension of the diatoms. In addition, the EPS may act as a protector of the diatoms from environmental stresses, such as changes in temperature, salinity, nutrient availability, desiccation and UV radiation (Hoagland et al., 1993; Underwood & Paterson, 2003). EPS does provide a carbon source to the

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benthic food web, which includes heterotrophic bacteria (Middelburg et al., 2000).

There is no universal EPS extraction method available and many different protocols have been published in the literature. Extracted EPS should therefore be considered as operationally defined and results between studies that used different protocols are therefore difficult to compare. In this study, water- and ethylenediaminetetraacetic acid (EDTA) extraction protocols were used. These extracts differ considerably in their composition and their production seems to be under a different metabolic control (Miyatake et al., 2014). Water-extractable EPS (in literature also referred to as colloidal EPS) are thought to be intimately associated with the diatoms or occur as colloid material in the (pore) water and are probably readily used by heterotrophic bacteria. EDTA-extractable EPS (in literature also referred to as bound EPS) are tightly bound to the sediment, and are thought to be more recalcitrant to microbial degradation (Stal, 2003). The EDTA-extractable EPS contain acid moieties such as uronic acids and sulfate-groups that interconnect the polymers by multivalent cations such as Ca2+. The addition of EDTA to the samples removes these cations and the cation bridges, resulting in the release of this type of EPS. Another protocol uses a cation-exchange resin as a substitute for EDTA (Takahashi et al., 2010) and was applied in-situ by Pierre et al. (2010, 2012, 2014).

The EPS formation by benthic diatoms has been extensively studied, however, thus far most studies were done in pure cultures and/or focused on the measurement of the content of EPS fractions thereby neglecting effects of community interactions, production and turnover rates of these exudates (Smith & Underwood, 1998; Pierre et al., 2014). Most research has been carried out on the dominant carbohydrate component of these exudates, which is undoubtedly important in sediment carbon cycling (Bellinger et al., 2009; Oakes et al., 2010; Taylor et al., 2013). However, EPS may also contain proteins, lipids, nucleic acids and other biopolymers such as humic substances (Flemming & Wingender, 2010). Carbohydrates are known to be major intermediates in the rapid transfer of carbon between diatoms and heterotrophic bacteria (Middelburg et al., 2000; Evrard et al., 2008; Bellinger et al., 2009; Taylor et al., 2013). Besides gaining knowledge on EPS dynamics, understanding interactions between diatoms and heterotrophic bacteria is important as they modify each other’s behavior and eventually impact biogeochemical cycles (Bruckner et al., 2011; Amin et al., 2012).

The aim of this study was to characterize the biochemical composition and production patterns of EPS from an intertidal benthic

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diatom mat through their carbohydrate and amino acid content, and to trace the carbon flow to the heterotrophic bacteria in-situ and follow the seasonal changes of these processes. By using an in-situ 13C pulse-chase method (Middelburg et al., 2000) in combination with liquid chromatography isotope ratio mass spectrometry (LC/IRMS) it was possible to follow the fate of the applied 13C label from carbon fixation to EPS and SCOA excretion and subsequent utilization by heterotrophic bacteria (Moerdijk-Poortvliet et al., 2013). Phospholipid-derived fatty acid (PLFA) biomarker analysis was used to differentiate between benthic diatoms and different groups of heterotrophic bacteria.

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Methods

Study site and in situ 13C labeling experiments In 2011, in-situ 13C-labeling experiments were carried out at approximately 2 months intervals at the Zandkreek intertidal mudflat, which is situated along the southern shore of the Oosterschelde estuary in the Southwest of the Netherlands (51°32'41”N, 3°53'22”E). The sampling site was located 0.15 m below the mean tidal level and the emersion period was approximately 6 h per tidal cycle. Bioturbating fauna such as the amphipod shrimp Corophium volutator and the hydrobiid snail Peringia ulvae became active starting late spring (June) gaining higher grazing rates resulting in a more mixed sediment top layer during summer. Detailed information on the study site and its sampling is described in chapter 7.

Experiments started immediately after emersion of the mudflat. Two 500×500 mm stainless steel frames were pushed into the sediment to a depth of 80 mm in order to constrain the labeling and the sampling area. The two frames were treated as duplicates (n =2) and were divided in a 100×100 mm sampling grid. Unlabeled control samples were taken just outside the frames as described below. The in-situ labeling experiment started by spraying the surface of the sediment within each frame with 200 mL of [13C] sodium bicarbonate (99 % 13C; Cambridge Isotope Laboratories, Andover, USA) with ambient salinity (30 ‰) to obtain a final concentration of 1 g 13C m-2 (Middelburg et al., 2000) .

The labeled sediment was sampled 2 and 4 h after label addition during the first low tide (the pulse-labeling period), and subsequently at 12h, 1 d, 2 d, 3 d, and 5 d exactly at low tide (the chase period). At each sampling time, pore water was collected from two randomly chosen positions within the sampling grid of each stainless steel frame using porous polymer sippers (Rhizon Soil Moisture Sampler; Eijkelkamp Agrisearch Equipment) inserted into the upper 15 mm of the sediment and these two samples were combined (total ~5 ml). For each stainless steel frame, 1 mL of pore water was injected into airtight headspace vials and analyzed for 13C-DIC (dissolved inorganic carbon) and the remainder was used for inorganic nutrient analysis and short chain organic acid (SCOA) analysis. Water column nutrient data were obtained from the NIOZ monitoring program from a station 500 m away from our experimental site.

Sediment samples were collected and mixed from two randomly chosen positions within the sampling grid of each steel frame. The top 15 mm of the sediment was collected by pushing a core liner (inside diameter

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10 cm) into the sediment to a depth of 50 mm and subsequently the top 15 mm of the sediment was sampled with a spatula (Middelburg et al., 2000). The corer was removed and the sampling hole was filled with unlabeled sediment collected just outside the experimental area. The two sediment samples taken from each steel frame area were homogenized and subsampled for the various analyses. Samples for fatty acids (FA) were directly frozen in liquid nitrogen and subsequently lyophilized and stored at -20 oC until analysis. Pigment samples were also directly frozen in liquid nitrogen and were subsequently stored at -80 oC prior to analysis. Sediment samples for EPS extraction were transported to the laboratory and processed as described in Miyatake et al. (2014) within 30 min after sampling. For all experiments, two operationally defined EPS were extracted: water-extractable EPS (EPS MQ) using freshly prepared Milli-Q water (MQ, 18.2 MΩ, DOC free, Millipore, Bedford, MA, USA) and EDTA-extractable EPS (EPS EDTA). To ~4 g wet weight of the homogenized sample 4.5 mL Milli-Q water was added for EPS MQ extraction as described in de Brouwer and Stal (2001). Samples were shaken for 1 h at 30 oC in the dark and the supernatant was collected after centrifugation at 4,000 × g for 15 min and stored at -20 oC. The sediment pellet was re-extracted with 4.5 mL of 0.1 M EDTA by shaking for 4 h in the dark at room temperature. The supernatant was collected after centrifugation at 4000 × g for 15 min and stored at -20 oC. Both extracts were analyzed for carbohydrates (CHO) and amino acids (AA). In total four operationally defined EPS fractions were distinguished: CHO MQ, CHO EDTA, AA MQ and AA EDTA.

In order to compare our results with those of studies that use the DOWEX cation-exchange resin instead of EDTA, a comparison of both EPS extraction protocols was made. Hence, an additional 13C in-situ labeling experiment was performed in May 2012. Two experimental areas were treated with labeled substrate and were divided in a 100 × 100 mm sampling grid. Initially, unlabeled control samples were taken just outside the stainless steel frames (t = 0 h). Sampling of the labeled sediment was 24 h after label exposure. Sediment samples were collected and mixed from two randomly chosen positions within the sampling grid in decuple (n = 10). Samples were extracted for EPS according the method described above and in addition according to the method described in Pierre et al. (2010). For the latter method, ~4 g wet weight of the homogenized sample was extracted by adding 4.5 mL artificial seawater (ASW, salinity 30). Samples were shaken in the dark for 1 h at 4 oC and the supernatant was collected after centrifugation at 4,000 × g for 15 min and stored at -20 oC. The sediment pellet was re-extracted with 4.5 mL of ASW and 1 g of

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activated Dowex Marathon C (cations exchange resin, activated in phosphate buffered saline (PBS) for 1 h in the dark), and shaken for 1 h in the dark at 4 oC. The supernatant was collected after centrifugation at 4,000 × g for 15 min and stored at -20 oC. The carbon content and isotopic composition of carbohydrates of the EPS fractions were analyzed by LC/IRMS (Boschker et al., 2008). Four operationally defined EPS fractions were obtained: EPS MQ, EPS EDTA, EPS extracted by artificial seawater (EPS ASW) and EPS extracted by activated Dowex Marathon C resin (EPS DOWEX). EPS MQ and EPS ASW were considered to represent the EPS that is associated with diatoms and loosely bound to the sediment and which can be readily used by heterotrophic bacteria. EPS EDTA and EPS DOWEX were considered to represent EPS that is tightly bound to the sediment and is to some extend recalcitrant to microbial degradation. Because the two EPS extraction protocols applied different temperatures, for comparison the extractions were done at 4 oC as well as at 30 oC.

In order to study dark fixation by chemoautotrophic and heterotrophic bacteria, two cores (70 mm inner diameter) were taken outside the experimental area and incubated in the dark for 4 h with the same amount of 13C-label (per m2) as used in the experimental area added to the top of the sediment. The top 15 mm of these cores was sampled and analyzed for PLFA labeling.

Miniaturized pulse amplitude modulated (PAM) fluorimetry (Mini-PAM, Walz GmbH, Effeltrich, Germany) was used to measure photosynthetic parameters. Intact sediment cores of the diatom mat were taken in duplicate. Rapid light curves (RLCs) were recorded simultaneously with the pulse-labeling period. Prior to RLCs recording, samples were dark adapted for 15 min to relax photochemical quenching. Subsequently, RLCs were recorded with 12 incremental irradiance steps of 20 s. From these data the relative maximum photosynthetic electron transport, the light affinity coefficient (alpha), and the light saturation irradiance were determined (Serôdio et al., 2005).

During the 13C label incorporation and RLCs recordings, PAR (400-700 nm) was measured on site every 15 min by a LICOR light meter (LI-250A) connected to a quantum sensor (Li-cor, Lincoln, NE, USA). Throughout the year a PAR sensor (Licor, LI 191) connected to a data logger (Licor, LI-1000), located 10 km from the study area, measured PAR values every minute; data were averaged and logged hourly.

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Analytical procedures For DIC analysis, pore water samples were acidified by adding 0.1 mL of 19 M phosphoric acid (Miyajima et al., 1995) and headspace gas was analyzed by elemental analyzer/isotope ratio mass spectrometry (EA/IRMS) in order to determine the concentration and isotopic composition of DIC (Boschker et al., 1999).

Carbon content and isotopic composition of EPS and SCOA were analyzed by LC/IRMS. For carbohydrates, 4 mL EPS extract were hydrolyzed to monosaccharides under acidic conditions using a modified method according to Cowie and Hedges (1984). The method was modified by neutralizing the hydrolyzed samples with barium carbonate instead of strontium carbonate, which resulted in an increased yield of the extract. For the EPS EDTA extracts the EDTA was removed from the hydrolyzed samples as described in Moerdijk-Poortvliet et al. (2013). Carbohydrates were analyzed by LC/IRMS as described in Boschker et al. (2008). For amino acids, 4 mL EPS extract were hydrolyzed with 6 M HCl for 20 h at 110 oC and subsequently purified by cation exchange chromatography (Veuger et al., 2005) and analyzed by LC/IRMS as described in McCullagh et al. (2006). SCOA were analyzed without additional sample preparation and analyzed by LC/IRMS equipped with an Aminex HPX-87H cation exchange column (Bio-Rad Laboratories, Hercules, USA). The eluent was 8 mM sulfuric acid at a flow rate of 0.4 mL min-1 (Krumback & Conrad, 1991). Liquid chromatography was carried out using a Surveyor liquid chromatograph connected to an LC Isolink interface and a Delta V Advantage IRMS (all from Thermo Fisher Scientific, Bremen, Germany).

Lipids were extracted from 4 g dry weight of sediment with a modified Bligh and Dyer extraction (Boschker et al., 1999). The lipid extract was fractionated on silicic acid (60, Merck) into different polarity classes by sequential eluting with chloroform, acetone and methanol. The chloroform fraction contained mainly neutral lipid-derived fatty acids, while the acetone and methanol fraction contained polar lipids-derived fatty acids (i.e. mainly glycolipids-derived fatty acids and phospho-lipid-derived fatty acids (PLFA), respectively, but both fractions also contained other lipids such as betaine lipids and sulfolipids) (Heinzelmann et al., 2014). The methanol fraction was denoted as the PLFA fraction and converted into fatty-acid methyl esters, and the carbon content and isotopic composition of these derivatives were measured by gas chromatography isotope ratio mass spectrometry (Middelburg et al., 2000; Boschker, 2004).

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Pigments were extracted with acetone (90 %, buffered with 5 % ammonium acetate) from freeze-dried sediment and analyzed by reverse-phase high-performance liquid chromatography (Dijkman & Kromkamp, 2006).

Nutrients were measured using a segmented continuous flow analyzer (SEAL QuAAtro XY-2 autoanalyzer, Bran and Luebbe, Norderstedt, Germany) according to the instructions provided by the manufacturer.

Data analysis The absolute amount of 13C incorporated into EPS fractions, SCOA and PLFA in excess of the background was displayed. This value is expressed as excess 13C and is calculated from δ 13Csample as:

Excess 13C (mol 13C m-2) =

where δ13Cbackground denotes the δ13C value of the unlabeled sample and Csample denotes the pool size in mol of carbon per square meter sediment (mol C m-2). Production rates of various EPS fractions and PLFA biomarkers were quantified by calculating the regression slope from sample data (at 0, 2, and 4 h) (expressed in µmol 13C m-2 h-1).

Excess 13C into bacterial biomass was estimated from the label incorporated in bacterial-biomarker PLFA as excess 13C-bacterial biomass (mol 13C m-2) = Σ excess 13C PLFAbact/(0.056 × 0.23), where 13C PLFAbact

is 13C in bacterial-biomarker PLFA (i.e. i14:0, i15:0, ai15:0, i17:0, 17:1ω6c, cy-19:0, i17:1ω7c, 10Me16:0, and i17:1ω5c), 0.056 represents the average PLFA content in bacteria in terms of carbon and 0.23 ± 0.06 is the average fraction of these bacterial PLFA among total PLFA in bacteria-dominated marine sediments (Middelburg et al., 2000). Excess 13C into diatom biomass was calculated from the difference between excess 13C into all PLFA and excess 13C into bacterial PLFA and was also corrected for the typical PLFA content of diatoms: excess 13C-diatom biomass (mol13C m-2) = (Σ excess 13C PLFAall-Σ excess13C PLFAbact)/0.035, where 13C PLFAall is 13C in all individual PLFA measured and 0.035 represents the average PLFA content of diatoms (Middelburg et al., 2000). Diatom and bacterial biomass were calculated as above in terms of carbon per m2 sediment using the PLFA concentrations instead of excess 13C values.

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The relative photosynthetic electron transport rate (rETR) was calculated by multiplying the Mini PAM measured quantum yield (i.e. ‘efficiency’ of photosynthesis) and the applied irradiance (E) during the recording of the RLCs (Kromkamp & Forster, 2003). From the RLCs the relative maximum photosynthetic electron transport rate (ETRmax), the light affinity coefficient in the light limited region of the rapid light curve (alpha), and the light saturating irradiance (Ek= ETRmax/alpha) were determined by fitting the RLCs to a modified version of the equation of Eilers and Peeters (1988): rETR=E/aE2 + bE + c), where a=(alpha ×Ek

2)-1 -2 × (alpha × Ek)-1; c=alpha-1.

A multivariate statistic method was applied in order to identify the relationships between environmental, photosynthetic, and pigment parameters (i.e. explanatory variables; Supplementary Table 8.S1) and production rates of the EPS fractions (Supplementary Table 8.S2). The various EPS fractions might originate from different processes and were correlated to the explanatory variables in such a way that the variables of the EPS fractions were kept in separate tables (samples x variables). The relationships between the explanatory variables and the different EPS fractions were explored by Concordance Analysis (Lafosse & Hanafi, 1997). This approach is an extension of Co-Inertia analysis (Dolédec & Chessel, 1994) that matches one table to several others. The inherent logics of Co-Inertia enables to proceed with a large number of variables (Dray et al., 2003). Concordance Analysis searches combinations of variables in each EPS fraction that co-vary and vary with combinations of explanatory variables. The number of variables does not affect the strength of the correlation because the tables are weighted by the inverse of their respective inertia. Prior to Concordance Analysis, the correlation between the explanatory variables and each EPS fraction was assessed by the Rv coefficient (Robert & Escoufier, 1976). The significance was tested by a randomization procedure of 9999 permutations of table lines (Heo & Ruben Gabriel, 1998). Hence, only the significantly correlated part of EPS to explanatory variables was considered in the Concordance Analysis. In the case of a single significantly correlated EPS table, the Concordance analysis was a simple Co-Inertia analysis. Concordance Analyses were run with ADE-4 software (Thioulouse et al., 1997) and associated graphical representations were made with the “ade4” package (Chessel et al., 2004) in R version 3.2.3 (Team, 2015).

One-way Anova was used to test whether the determined concentration and excess values between EPS MQ and EPS ASW fractions on the one hand and EPS EDTA and EPS DOWEX fractions on the other hand showed significant differences (significance levels p<0.05).

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Results Seasonal dynamics of exudation and heterotrophic consumption of EPS and SCOA An overview of the 13C label dynamics of determined excreted carbon pools by benthic diatoms, i.e. EPS and SCOA, is given (Fig. 8.1). In the two operational defined EPS extracts (i.e. EPS MQ and EPS EDTA) carbohydrates (CHO) and amino acids (AA) were detectable resulting in four EPS fractions are depicted (CHO MQ, CHO EDTA, AA MQ an AA EDTA). We also show the 13C labeling of bacteria (through the analysis of PLFA biomarkers) that originates from the heterotrophic consumption of the extracellular carbon compounds released by diatoms.

For all excreted carbon compounds, different 13C labeling patterns were observed. Most of the 13C label was recovered in CHO MQ, followed by CHO EDTA, AA MQ, AA EDTA and SCOA. The highest amount of 13C label in all pools was observed in February and April (Fig. 8.1). Especially in February and April an initial steep increase of 13C label was observed in excreted carbon compounds followed by a steep decrease. EPS and SCOA were exuded and consumed at lower rates during the rest of the year. During all months the amount of 13C label incorporated into the EPS and SCOA was highest between 4 - 12 h and disappeared to a large extent during the course of the experiment (Fig. 8.1). Although the number of sampling time points was limited, the data suggest that the initial release of exudates was followed by a second release (between 24 - 48 h) and in some cases by a third release (between 48 - 72 h). Labeling in bacterial PLFA increased sharply during the first 4 h of the experiment and was followed by a more gradual and alternating decrease and increase during the course of the experiment. The increases of 13C label in bacterial biomarkers coincided to a greater or lesser extent with the release of EPS and SCOA.

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Figure 8.1. An overview of 13C label dynamics of excreted carbon pools (i.e. EPS and SCOA) and bacteria derived from heterotrophic consumption of these excreted carbon pools. In the two operational defined EPS extracts (i.e. EPS MQ and EPS EDTA) carbohydrates and amino acids were detectable.

Exudation and fate of carbohydrates and amino acids originating from EPS and SCOA In figure 8.2 the results of the carbohydrates and amino acids originating from the two EPS extracts are depicted. Throughout the year, carbohydrates formed the main component of the extracellular fractions while amino acids represented a minor component (Fig. 8.2A). Carbohydrates also explained most of production rate of EPS (Fig. 8.2B). In contrast to the EPS content of the sediment, EPS production was strongly seasonal. EPS production reflects the actual metabolic activity

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and therefore emphasis was put on the seasonal variation of EPS production. Figure 8.2. Annual carbohydrate and amino acid (A) concentrations and (B) productions originated from EPS MQ and EPS EDTA.

In figure 8.3 details of the carbohydrates and amino acids

originating from EPS MQ and EPS EDTA extracts are presented after initial 13C label incorporation (t = 4 h) (Fig. 8.3A, B, C, D), and how this 13C label was distributed after 3 days (Fig. 8.3E, F, G, H). Time-point day 3 was chosen, because from day 3 onwards 13C label distribution remained more or less the same. For carbohydrate as well as for amino acids, the relative 13C label distribution in the monomers of the extracted EPS was different. For the CHO MQ fraction most of the 13C label was incorporated into glucose (80±11 %) while in the CHO EDTA the 13C label was more evenly distributed between the monomeric carbohydrates (Fig. 8.3A, B). For the AA MQ fraction most of the 13C label was incorporated into proline (54±11 %) while for the AA EDTA the 13C label incorporation was varying depending on the season and the highest amounts of 13C label were found in threonine, serine and valine (Fig. 8.3C, D). Due to the elution of an unknown impurity in the chromatogram of the AA EDTA fraction (which was substantial and chromatically comprised a wide elution area), the amino acids glycine, proline and alanine could not be determined. Despite this limitation, it was ascertained that the AA EDTA fraction contained aspartate, serine, threonine and methionine, which were not retrieved in the AA MQ fraction. Similarly, the AA MQ fraction contained phenylalanine, lysine and tyrosine, which were absent in the AA EDTA fraction. Besides the variation of monomers in the different EPS fractions, also the 13C label distribution in the monomers of the EPS fractions varied seasonally (Fig 8.3A, B, C, D, pie charts).

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A E

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Figure 8.3. Annual monomeric carbohydrate and amino acid details of 13C label content of EPS MQ and EPS EDTA fractions. Details of 13C label are presented for respectively 4 h (i.e. after initial 13C label incorporation) and d3 (i.e. 13C label distribution after 3 days). For panel A, B, C and D the dotted line represents the percentage of carbon initially fixed as respectively carbohydrate and amino acids and excreted as EPS. For panel E, F, G and H the dotted line represents the percentage of 13C label remained in EPS after 3 days compared to the amount of 13C label incorporated at t = 4h.

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Up to 23±4 % of the total fixed carbon in the carbohydrate pool was exuded as EPS MQ and up to 6±1 % as EPS EDTA. Similarly, most of the total fixed carbon in the amino acid pool was exuded as EPS MQ rather than as EPS EDTA (46±25 % and 7±2 %, respectively). The percentage of carbon that was initially fixed as carbohydrate and amino acid and subsequently exuded as EPS was in general lowest in June (on average 3±2 %) (Fig 8.3A, B, C, D, dotted line).

The 13C label incorporated into the EPS during the first 4 h of the experiment disappeared to a large extent during the course of the experiment (Fig. 8.3E, F, G, H). This was particularly the case for CHO MQ in which only 20±9 % of the 13C label remained after 3 days (Fig. 8.3E). For CHO EDTA and AA MQ the decrease of 13C label after 3 days was less (59±21 % and 75±32 % of the incorporated 13C label remained, respectively). For AA EDTA 39.3 ±19.2 % remained after 3 days, except in December when a substantial net label increase was found (Fig. 8.3H). For EPS MQ and EPS EDTA an increase in the proportioning of deoxy-sugars (fucose and rhamnose) was found while glucose decreased (Fig. 8.3E, F). Similarly, a shift in the distribution of amino acids was observed.

Seasonal differences were observed for the 13C label loss of the different EPS fractions. For CHO MQ and AA MQ more label remained after 3 days in April and June compared to other months (Fig. 8.3E, G, dotted line). For CHO EDTA less 13C label remained 3 days after the start of the experiment in February and April, whereas for the AA EDTA fraction less 13C label remained in February and August compared to other months.

SCOA in the pore water included formate, acetate, oxalate, malate, lactate and succinate. Lactate and succinate could not be separated sufficiently by the applied LC protocol and are therefore reported as the sum of both. Considerable seasonal changes in the 13C labeling of succinate/lactate, formate and acetate were observed. Other SCOA were below the detection limit; hence, only succinate+lactate, formate and acetate are depicted in figure 8.4. Pore water concentrations of succinate+lactate (range 2.7-5.7 µM, formate (range 3.7-13.6 µM), and acetate (range 1.0-5.8 µM) were high. Labeling of succinate/lactate, formate and acetate were highest in February and gradually decreased during the year. By contrast, the percentage of 13C label that remained after 3 days in all SCOA increased during the year and ranged from 5 % in February to 42 % in December.

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Figure 8.4. Annual short chain organic acid (SCOA) details. Details are presented for respectively 4 h (i.e. after initial 13C label incorporation) and d3 (i.e. 13C label distribution after 3 days). The dotted line represents the percentage of 13C label remained in EPS after 3 days compared to the amount of 13C label incorporated at t = 4h. Lower panels represent an enlargement of the upper panels. Explanatory variables Pore water nutrient concentrations were always higher than nutrient concentrations in the water column above the sediment (during immersion) (Supplementary Table 8.S1). Inorganic nitrogen was predominantly present as ammonium in the pore water and as nitrate in the overlying water. Average pore water inorganic nitrogen concentrations were lower in summer (June and August) compared to the rest of the year (respectively 27.9±0.1 and 72±27 µmol L-1). N:P ratios above Redfield (i.e. 16) were observed from February until June (26±5). In August and October N:P ratios were below Redfield (7±1) and in December near Redfield (17±1) (Supplementary Table 8.S1). Likewise, inorganic nitrogen concentrations in the overlying water were lower in summer (June and August) compared to the rest of the year (respectively 14±3 and 38±16 µmol L-1). The seasonal trend of nutrient N:P ratios in the overlying water was similar as in the pore water and were above Redfield from February until June and in December (46±30) and below Redfield in August and October (12±2) (Supplementary Table 8.S1). The pigment fingerprints were typical for diatoms, including β-carotene, chlorophyll a,

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EPS fraction Explanatory vs Explanatory vs

Production EPS13

C label day 3 EPS

CHO MQ 0.41 0.41CHO EDTA 0.66 0.56

AA MQ 0.72 0.80AA EDTA 0.73 0.52

chlorophyll c, fucoxanthin, diadinoxanthin and diatoxanthin (Supplementary Table 8.S1). The photosynthetic parameters Ek and ETRmax were higher in spring and summer, while α was higher in autumn and winter (Supplementary Table 8.S1). PAR values correlated to sediment temperatures and were higher in summer than in winter. The average temperature and integrated photon irradiance during the 4 h of 13C labeling of the diatom mat were the lowest in February (3.7 oC and 1314 µmol photons m-2 and the highest in August (20.5 oC and 7492 µmol photons m-2) (Supplementary Table 8.S1).

Production and fate of EPS in relation to explanatory variables Concordance analysis was performed on the dataset of 13C label incorporation rate of monomeric carbohydrates and monomeric amino acids originating from the EPS extracts (i.e. CHO MQ, CHO EDTA, AA MQ and AA EDTA) (Supplementary Table 8.S2) and explanatory variables (Supplementary Table 8.S1). The Rv coefficients between the explanatory variables and the four EPS fractions were significant (Table 8.1). Results from the concordance analysis are displayed in figure 8.5. The two first axes expressed the major dynamics among four seasonal clusters (i.e. February, April, June/August and October/December).

For all four EPS fractions (i.e. CHO MQ, CHO EDTA, AA MQ, and AA EDTA), the first axis of the concordance analysis opposed autumn and winter months (i.e. October, December and February) from spring and summer months (i.e. April, June and August), whereas the second axis opposed months having a high EPS production (i.e. February and April) to months with a lower EPS production (i.e. June, August, October and December) (Fig. 8.4). The predominant monomeric carbohydrates and amino acids characterized the seasonal clusters (Fig. 8.4).

Table 8.1. Rv coefficients between the explanatory table and each EPS table. Bold values indicate significance at the rejection level α = 0.05.

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Figure 8.5. Concordance analysis of explanatory data and production details of both carbohydrates and amino acids originated from EPS MQ and EPS EDTA extracts. Bar diagram, Eigenvalues: axis 1 (horizontal), 63 %; axis 2 (vertical), 30 %. The first two rows of the graph display the variable interplays of the different EPS fractions. The second row displays the positions of months; black dots, reference ordination of months induced by explanatory variables (bottom graph); arrow tips, positions induced by EPS variables; arrow lengths indicate the lack of fitting. “d” indicates the grid scale. The notation of the various parameters is explained in table 8.2.

Along the first axis of the concordance analysis, the carbohydrates

originating from the exuded EPS (i.e. CHO MQ and CHO EDTA) in spring and summer (April, June, and August) had higher production rates of fucose, rhamnose, xylose, and mannose, relative to a lower production rate of glucose (and for CHO EDTA also a lower rate of galactose production) (Fig. 8.5; panel CHO MQ and CHO EDTA). In contrast, in autumn and winter (October, December, and February) high production rates of glucose (and for the CHO EDTA fraction also a high rate of galactose production) and low production rates of fucose, rhamnose,

CHO MQ

CHO MQ CHO EDTA

CHO EDTA

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xylose, and mannose were observed (Fig. 8.5; panel CHO MQ and CHO EDTA). Along the second axis, months with a high EPS production (i.e. February and April) show a high rhamnose and a low galactose production for the CHO MQ fraction and a high fucose and a low mannose production for the CHO EDTA fraction (Fig. 8.5; panel CHO MQ and CHO EDTA). The months with a low EPS production (i.e. June, August, October, and December) show a high galactose and a low rhamnose production for the CHO MQ fraction and high mannose and a low fucose production for the CHO EDTA fraction (Fig. 8.5; panel CHO MQ and CHO EDTA).

Similar as was found for the exuded carbohydrates, along the first axis of the concordance analysis the excreted AA MQ showed a higher production rate in spring and summer for most of the amino acids in contrast to a lower production rate of glycine and proline (Fig. 8.5; panel AA MQ). Along the first axis, autumn and winter showed a high production rate of glycine and proline and a low production rate of all other measured amino acids (Fig. 8.5; panel AA MQ). Along the second axis a high production rate of tyrosine and a low production rate of valine were observed (Fig. 8.5; panel AA MQ). Different than for the CHO MQ, CHO EDTA and AA MQ fractions, the AA EDTA fraction showed a high production rate for most amino acids during June, August, October, and December (i.e. when the production of EPS was low) except for threonine (Fig. 8.5; panel AA EDTA). Threonine production rates were high in February and April (i.e. when EPS production was high).

The first axis of the concordance analysis was strongly characterised by temperature and positively associated to PAR, ETRmax, and Ek (Fig. 8.5; panel explanatory variables). Subsequently, these parameters decreased from June/August to October/December with associated increases in alpha (i.e. the photosynthetic parameter that represents the affinity for light), β-carotene content, phosphate concentrations and ammonium concentration in the overlying water (Fig. 8.5; panel explanatory variables). Along the first axis the increased synthesis rates of the majority of monomeric carbohydrates and amino acids for the CHO MQ, CHO EDTA, and AA MQ fractions were mainly covariant with the high light intensity and, to a lesser extent, with the high sediment temperature, Ek and ETRmax (Fig. 8.5). In contrast, along the second axis increased synthesis rates of amino acids were observed in the AA EDTA fraction. These increased synthesis rates were consistently associated with a low content of light-harvesting pigments and possibly with insufficient ammonium in the pore water or nitrate in the water column (Fig. 8.5). Moreover, the high rates of EPS production in February

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Explanatory variables EPS parameters

PAR Photosynthetically Active Radiation (400-700 nm) Extracellular Polymeric Substances (EPS) Amino Acids (AA)during labeling EPS MQ Water-extractable EPS Asp aspartine

Tsed Sediment Temperature EPS EDTA EDTA-extractable EPS Ser serineThr threonine

Photosynthetic Parameters Operational defined EPS fractions Gly glycineETRMax Relative maximum reached Electron Transport rate Pro prolineα Light affinity coefficient in the light limited region CHO MQ Water-extractable Carbohydrates Ala alanine

of the rapid light curve CHO EDTA EDTA-extractable Carbohydrates Val valineEk (minimum) Light saturation irradiance AA MQ Water-extractable Amino Acids Met methionine

AA EDTA EDTA-extractable Amino Acids Ile isoleucinePigments Leu leucineβ-CARO β-Carotene M Water-extractable Tyr tyrosineCLA Chlorophyll a E EDTA-extractable Lys lysineCLC Chlorophyll c His histineDIAD Diadinoxanthine Carbohydrates (CHO) Phe phenylalanineDIAT Diatoxanthine FUC fucose Arg argininePHOR Pheophorbide RHA rhamnoseFUCO Fucoxanthine GAL galactosePHYT Pheophytine GLC glucose

XYL xyloseNutrients MAN mannosew-NH4 Water column Ammonium w-NO2 Water column Nitrite w-NO3 Water column Nitratew-PO4 Water column Phosphatew-Si Water column Silicatepw-NH4 Pore water Ammonium pw-NO2 Pore water Nitrite pw-NO3 Pore water Nitratepw-PO4 Pore water Phosphatepw-Si Pore water Silicate

and April were consistently associated to a high content of light harvesting pigments and high concentrations of ammonium in the pore water or nitrate in the water column (Fig. 8.5).

Table 8.2. Explanatory variables and EPS parameter notation

At day 3, the relationship between the proportioning of 13C label in the CHO EDTA, AA MQ, and AA EDTA fractions (Supplementary Table 8.S3) and explanatory variables (Supplementary Table 8.S1) were significant (Table 8.1). The pattern resulting from the concordance analysis was expressed along two main axes (Fig. 8.6). There was no relationship between the 13C label proportioning of the CHO MQ fraction at day 3 and explanatory variables. For the CHO EDTA, AA MQ, and AA EDTA fractions the 13C label distribution pattern at day 3 was similar to the one for the distribution pattern at t = 4h (Fig. 8.5), except for serine and tyrosine for the AA MQ fraction and leucine, methionine, isoleucine and valine for the AA EDTA fraction (Fig. 8.6; panel AA MQ and AA EDTA). At t = 4h those amino acids were positioned in respectively the

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June/August and October/December cluster of the concordance plot (Fig. 8.5; panel AA MQ and AA EDTA). At day 3 those amino acids were positioned in the February and April clusters (Fig. 8.6; panel AA MQ and AA EDTA). This implies that serine and tyrosine (AA MQ fraction), and leucine, methionine, isoleucine and valine (AA EDTA fraction) 13C label dynamics were different than for the other amino acids and 13C label loss of these amino acids in February and April was low.

Figure 8.6. Concordance analysis of explanatory data and details of 13C label content of carbohydrates and amino acids originated from EPS MQ and EPS EDTA at t = 3 days. Eigenvalue diagram: axis 1 (horizontal), 92 %; axis 2 (vertical), 8 %. See figure 8.4 for complementary explanations. The notation of the various parameters is explained in table 8.2.

CHO EDTA

CHO EDTA

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Comparison of EPS extraction methods The carbohydrate content of EPS MQ and EPS ASW was similar (Table 8.3) (Anova, p>0.05). However, the carbohydrate yield was on average 22±6 % higher when extracted at 30 oC than at 4 oC. No significant differences were found in natural abundance δ13C values of the carbohydrate monomers of EPS MQ and EPS ASW (Anova, p>0.05) (Table 8.3). Similarly, no significant differences of Δδ13C values and excess 13C values were found between the EPS MQ (extracted at 30 oC) and EPS ASW (extracted at 4 oC) fractions (Anova, p>0.05) except for galactose (Anova, p<0.05).

Large and significant differences were found in the carbohydrate concentration and excess 13C values between the EPS EDTA and EPS DOWEX fractions (Table 8.3). The carbohydrate content and excess 13C values of EPS EDTA were on average 4 times higher than those of EPS DOWEX. No significant differences were found in natural abundance δ13C values of the carbohydrate monomers of EPS EDTA and EPS DOWEX (Anova, p>0.05) (Table 8.3). However, in most cases Δδ13C values were significantly higher for DOWEX extracted carbohydrates than for those extracted by EDTA (Anova, p<0.05) (Table 8.3). Extraction temperature had no significant effect, neither on the carbohydrate content derived from EPS extracted by DOWEX, nor on that of EPS extracted by EDTA, except in the case of galactose and xylose extracted by EDTA (Anova, p<0.05). For these carbohydrates the yield at 30 oC was on average 24±5 % higher compared to the yield at 4 oC.

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3.6

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TA

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26-1

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86

53.

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SW4

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73

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WEX

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6.6

2.4

187

41.

3M

Q30

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-15.

82.

618

64

1.3

EDT

A25

706

-16.

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39

2.5

ASW

3018

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175

31.

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183

-16.

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43

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173

-15.

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89

2.5

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00.

833

1430

12A

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162

-15.

02.

536

96

1.3

DO

WEX

422

3-1

5.0

1.2

338

82

MQ

3022

3-1

5.6

2.4

447

112.

8ED

TA

2510

98

-15.

51.

331

737

12A

SW30

214

-16.

01.

131

87

2.6

DO

WEX

2522

2-1

6.1

1.4

264

61

gluc

ose

MQ

421

5-1

3.9

2.1

141

3834

15.1

EDT

A4

7515

-14.

91.

411

529

9324

ASW

420

5-1

5.5

3.8

140

3631

8.7

DO

WEX

419

5-1

4.5

1.4

148

4830

13M

Q30

246

-13.

71.

714

525

3915

.1ED

TA

2578

8-1

5.0

2.9

8018

6722

ASW

3025

5-1

3.9

1.5

112

3830

11.3

DO

WEX

2517

4-1

4.5

1.7

9626

1810

xylo

seM

Q4

71

-14.

94.

632

112

0.7

EDT

A4

365

-11.

82.

317

27

1.6

ASW

47

2-1

2.3

3.4

305

20.

5D

OW

EX4

116

-13.

57.

528

82

0.7

MQ

3010

1-1

2.7

4.0

2911

31.

3ED

TA

2543

4-1

0.7

3.1

166

71.

4A

SW30

117

-12.

03.

335

356

12.4

DO

WEX

259

1-1

5.5

7.1

2113

21.

2

man

nose

MQ

49

2-1

9.4

5.7

4012

41.

6ED

TA

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7.8

2.2

358

154.

3A

SW4

92

-18.

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243

104

0.7

DO

WEX

49

2-1

6.6

7.7

3510

31.

4M

Q30

122

-15.

14.

934

124

2.2

EDT

A25

444

-17.

52.

329

514

2.8

ASW

3010

3-1

6.9

7.2

3511

31.

0D

OW

EX25

92

-16.

36.

930

153

1.6

EP

S M

Q/A

SW

EP

S E

DT

A/D

OW

EX

Table 8.3. Data comparison EPS extraction methods. Analyses were performed in decuple (n=10). ‘sd’ denotes standard deviation

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Seasonal development of the diatom mat Benthic diatoms were visible at the sediment surface during the whole year but varied in density, depending on the time of the year and the time of the day. Both the biomass of benthic diatoms and benthic bacteria as estimated from fatty acids biomarker data were lower during the summer (June and August) (Fig. 8.7A). The decrease in biomass coincided with the activity of bioturbating fauna that grazed and disturbed the diatom mat. The annual ratio of diatoms and bacteria remained constant at 82±1 % and 18±1 %, respectively, of the total biomass (Fig. 8.7A). The production rate of diatoms and bacteria decreased during the year and was lowest in October and December (Fig. 8.7B). During February, April, and June the biomass of diatoms and bacteria seemed to be coupled, as seemed to be the case for the productivity of both groups of organisms. From August on the coupling of the growth of diatoms and bacteria deteriorated and almost disappeared in December (Fig. 8.7B). This pattern was retained until day 3 of the experiment (Fig. 8.7C). On average only 1.7±0.9 % of the initially applied 13C-DIC remained 12 h after the start of the experiment, confirming that most of it was washed out (or exchanged with the atmosphere). In addition, dark fixation of 13C label, as was determined in separate sediment core experiments, indicated that CO2 fixation by chemoautotrophic bacteria or through anaplerotic carbon fixation by heterotrophs was not important and confirmed the conclusions of Miyatake et al. (2014). Hence, the 13C label incorporation in heterotrophic bacteria in this study was mainly due to the transfer of organic matter between diatoms and bacteria.

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Diatom Bacteria

C

Figure 8.7. Annual diatom and bacterial biomass (expressed in mmol C m-2) (A), their 13C labeling content at 4 h (expressed in µmol 13C m-2) (B) and their 13C labeling content at day 3 (expressed in in µmol 13C m-2) (C) calculated from their respective specific phospholipid-derived fatty acids (PLFA).

8

Seasonal changes in the production and fate of EPS

213

0

200

400

600

800

1000

1200

1400

0,0

1,0

2,0

3,0

4,0

5,0

6,0

FEB APR JUN AUG OCT DEC

µmol

13C

m-2

iC14:0 iC15:0 aiC15:0iC17:0 C17:1ω6c cy-C19:0

0

1

2

3

4

5

6

FEB APR JUN AUG OCT DEC

µmol

13C

m-2

iC14:0 iC15:0 aiC15:0iC17:0 C17:1ω6c cy-C19:0

iC14:0 iC15:0 aiC15:0 iC17:0 C17:1ω6ccy-C19:0 iC17:1ω7c 10MeC16:0 iC17:1ω5c % 13C

% b

acte

rial P

LFA

rem

aine

d4h d3

The production and fate of PLFA bacterial biomarkers The 13C label incorporation in bacterial biomarkers was high at the beginning of the year and gradually decreased towards the end of the year (Fig. 8.8, panel 4h). In the first half of the year (i.e. February, April, and June) 13C incorporation was dominated by the iC17:ω7c, 10MeC16:0 and iC17:1ω5c biomarkers, whereas in the second half of the year (i.e. August, October, and December) other PLFA biomarkers took over (Fig. 8.8, panel 4h, pie charts).

During the year the 13C incorporated in the bacterial biomarkers iC17:ω7c, 10MeC16:0 and iC17:1ω5c decreased after 3 days (Fig. 8.8 4h, d3). This was in contrast to other PLFA, which increased their label content (Fig. 8.8A, B). During February, April, and June on average 77±15 % of the initially incorporated 13C label remained after 3 days (Fig. 8.6B, dotted line). This was in contrast to the months August, October, and December when a net gain of label 13C was observed. On average 459±207 % of label was gained compared to the amount of incorporated 13C label at t = 4h (Fig. 8.8 d3, dotted line).

Figure 8.8. Annual distribution of 13C label in bacterial PLFA biomarkers. Details of 13C label are presented for (4h) 4 hours (i.e. after initial 13C incorporation) and (d3) after 3 days of 13C label distribution. The dotted line represents the percentage of 13C label remaining in bacterial specific PLFA after 3 days compared to the amount of 13C label incorporated at t=4h.

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Discussion Production and fate of carbohydrates and amino acids originated from EPS by benthic diatoms The EPS composition and EPS degradation by microorganisms are complex processes that are largely unexplored. The exuded EPS consisted mainly of carbohydrate although amino acids were a consistent component, which is common for diatom dominated biofilms (Granum et al., 2002). In contrast, bacterial biofilm assemblages are dominated by proteins rather than by polymeric carbohydrates (Flemming et al., 2000). The composition of distinguished EPS extracts (EPS MQ and EPS EDTA) was different with respect to the carbohydrates and amino acids. This suggested that their synthesis is under different metabolic control. The carbohydrate composition of EPS MQ was rich in glucose and it was produced faster than the other fractions, suggesting a direct relationship with photosynthesis (de Brouwer & Stal, 2001). Moreover, glucose can be directly incorporated from chrysolaminaran, while other carbohydrates need to be synthesized first from glucose and hence would take longer to exude (Underwood & Paterson, 2003). In general, exudates with high glucose content are a source of easy degradable carbon for microorganisms. In contrast to EPS MQ, EPS EDTA was rich in deoxysugars (e.g. fucose and rhamnose) and pentose (e.g. xylose). Deoxysugars and pentoses contribute to the adhesive properties of EPS (Underwood & Paterson, 2003) and are more refractory towards degradation (Giroldo et al., 2003).

Although amino acids are a minor component of exuded EPS in benthic diatom mats, they can play an important role in maintaining EPS functionality. It is known that lectins (i.e. carbohydrate-binding proteins) link and stabilize polysaccharides in EPS and may be essential for the biofilm structure, adhesion, and stability (Dugdale et al., 2006). For example, it has been suggested that EPS-proline and EPS-glycine cause adhesion between organisms in soils and give elasticity to the EPS matrix (Redmile-Gordon et al., 2015). The amino acid proline is known to be multifunctional and its enhanced synthesis is an important factor in stress acclimation (e.g. salt- and oxidative stress) and plays a role as osmolyte (Van Bergeijk et al., 2003; Szabados & Savoure, 2010). In addition, under extreme cold, such as under polar circumstances, extracellular proline may serve as an anti-freeze allowing the presence of liquid water (Wiencke, 2011). We conceived that similar functions might be ascribed to proline and glycine in diatom mats, particularly because the synthesis of proline and glycine is enhanced in autumn and winter. EPS with a high

8

Seasonal changes in the production and fate of EPS

215

content of proline and glycine may play an important role as anti-freeze and could support elasticity of the EPS matrix of the diatom mat. In this study, we also observed that threonine (in the AA EDTA fraction) was a distinctive and characteristic amino acid because of its high synthesis rate in February and April; i.e. when EPS was produced at high rates. Threonine is known to be associated with algal defense (Buhmann et al., 2016) and therefore might play a role in controlling bacterial activity during the period of high EPS productivity in February and April. Although knowledge about the functionality of the substances exuded by diatoms is limited and needs further study, it is conceived that the exudation of carbohydrates serves mainly to balancing energy and motility of the diatoms. At the ecosystem level these exudations represent the carbon- and energy source. Extracellular amino acids are known to be important to interconnect polysaccharides and form the tertiary structure. In addition, extracellular amino acids are part of enzymes, nutritious polymers or serve as signaling molecules that play a role in diatom cell adhesion and defense processes (Buhmann et al., 2016).

EPS production often changes with the growth phase of the organism, with the level of irradiance or nutrients, or may be linked to endogenous cell rhythms (Underwood & Paterson, 2003). The carbon fixed by the benthic diatoms in the present study was exuded rapidly (within 2 h), which agrees with the idea of EPS exudation during photosynthesis as has been suggested by Underwood and Paterson (2003). We observed that a substantial proportion (between 9 and 21 %) of the fixed carbon was exuded in the environment as EPS. Other authors reported that this range of fixed carbon released as exudates may be even larger: i.e. between 1.7 to 73 %, with a median value between 30-40 % (Underwood & Paterson, 2003).

EPS exudation followed a seasonal pattern with lower percentages of fixed carbon exuded in summer compared to the rest of the year and showed a significant relation with explanatory variables such as light intensity, temperature and nutrient concentrations. We conceive that the function of EPS exudation may be different depending on the season. A dense diatom mat rapidly depletes the nutrients in the small volume of pore water. A lack of nutrients during photosynthesis makes a balanced synthesis of structural cell material impossible. This will result in a situation of unbalanced growth during which the product of photosynthesis is diverted to carbohydrate. Eventually, when the intracellular pool of the storage carbohydrate chrysolaminaran is filled up, the excess carbohydrate is exuded as EPS (Stal, 2010). Especially in February and April (i.e. high productivity months and a dense diatom mat),

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the production of EPS should be intimately related with the rate of photosynthesis (de Brouwer & Stal, 2001) and EPS exudation served as an overflow valve for excess energy (Stal, 2010). In June and August the diatom mat was less dense and EPS production might be the result of motility because the diatoms are forced to migrate because of sediment burial due to bioturbation and/or in order to escape high light intensities (Consalvey et al., 2004). During the summer the diatoms are exposed to a higher faunal grazing pressure (Pinckney et al., 2003). In October and December bioturbation and grazing are much less and overflow metabolism takes over again. In addition, the produced EPS in summer suggested an increase of heterogeneity because higher synthesis rates of the majority of monomeric carbohydrates as well as monomeric amino acids were observed. Therefore, we conceived that the produced EPS in summer was, besides being more related to motility, different in structure than in other seasons and as consequence the physicochemical properties of the exuded EPS may likely be different. This change in physicochemical properties could result in a different EPS functionality (e.g. hydrophobicity and degradability by heterotrophic bacteria) (Giroldo et al., 2003). For example, an increase in heterogeneity of EPS in terms of monomeric carbohydrates and monomeric amino acids could lead to a more complex structure and a higher recalcitrance to microbial degradation.

The 13C label dynamics of CHO MQ indicated a high turnover. The high loss of CHO MQ can be partially explained by the washout during tidal inundation, which may account for up to 60 % of the EPS loss from the sediment (Underwood & Smith, 1998; Hanlon et al., 2006). However, heterotrophic bacteria can also consume EPS. This was supported by the enrichment of in 13C of bacterial specific PLFA biomarkers coinciding the loss of CHO MQ and this agrees with other studies. (Goto et al., 2001, Miyatake et al., 2014). EPS EDTA was less influenced by tidal washout and was more refractory against bacterial consumption, which explained its slower turnover. This is consistent with previous studies reporting that deoxy-sugar rich EPS are more resistant for bacterial degradation, while hexose-rich polymers are more rapidly degraded (de Brouwer & Stal, 2001; Giroldo et al., 2003; Hanlon et al., 2006). However, despite the losses, continued isotopic enrichment of EPS indicated new production at the expense of another enriched compound. This enriched compound may be an intracellular carbon source such as chrysolaminaran or an extracellular carbon source such as material derived from degradation of more refractory EPS. Chiovitti et al. (2003) suggested the appearance of a pathway by which EPS EDTA becomes

8

Seasonal changes in the production and fate of EPS

217

available in the EPS MQ pool by bacterial degradation. For instance, by selective consumption of glucose-rich parts of EPS MQ the remaining more refractory parts could became available in the EPS EDTA pool. Also Stal (2010) suggests that EPS EDTA might have been derived from initially exuded EPS MQ. These hypotheses are supported by the results of our present study. We observed an increase in the deoxy-sugars of EPS as well as an increase in the isotopic enrichment of EPS EDTA between 12 h and 120 h. The transition from one EPS fraction to the other is probably also depending on the amount of divalent cations present in the sediment, such as Ca2+ and Mg2+, which interact with the EPS (Stal, 2010). The binding capacity of these cations enables part of EPS MQ to eventually be transformed into EPS EDTA. In this study we found seasonal differences within the production and fate of monomeric carbohydrates and monomeric amino acids originating from EPS, however it is more study is needed in order to draw further detailed conclusions about the results.

Comparison of EPS extraction protocols Different protocols for the extraction of EPS from intertidal sediments were compared, namely two water extractions (i.e. EPS MQ versus EPS ASW), and were followed by a second extraction using EDTA (i.e. EPS EDTA) and compared to an extraction method using a cation-exchange resin (i.e. EPS DOWEX). The yield of the water-extracted EPS was mainly influenced by temperature, which is consistent with previous research (Underwood et al., 1995, de Brouwer et al., 2002). The differences in yield for the bound EPS extractions methods were temperature independent and were most likely explained by the difference in extraction efficiency between both extraction agents. Whereas EDTA is strongly chelating divalent cations, the resin works only partly chemical (removal of divalent cations) and partly mechanical (due to applied shear) (Comte et al., 2006). We found a 4-fold lower yield using DOWEX when compared to EDTA and this has also been reported in the literature (Comte et al., 2006). The nature of the extracted EPS using either method seems to be similar because we did not find significant differences in the δ13C natural abundance values of the monomeric carbohydrates, neither in the biochemical monomeric carbohydrate composition. The observed yield difference between the EDTA and DOWEX fraction is unlikely to be the result of cell lysis, which is occasionally suggested as a side effect of EDTA extraction (Takahashi et al., 2010). The observed higher Δδ13C values for DOWEX extracted carbohydrates than for those extracted by EDTA suggests that DOWEX EPS exist more of material formed during

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the experiment and that the EDTA extracted carbohydrates are to a larger extend derived from sediment bound older, and therefore unlabeled material.

EPS and SCOA as carbon source for bacteria Heterotrophic bacteria are omnipresent in diatom mats and utilize organic carbon produced by diatoms (Middelburg et al., 2000, Bellinger et al., 2009). Especially during the first couple of months (February, April and June), the bacterial PLFA biomarkers showed an initial fast uptake of 13C label, which was probably the result of the utilization of low-molecular-weight EPS AND SCOA exuded by diatoms. Exudates were preferentially used by various groups of bacteria as was evidenced by differences in the level of 13C excess values between PLFA biomarkers. The PLFA i17:1ω7c, i17:1ω5c and 10Me16:0 are known to be specific for sulfate reducing bacteria (SRB) (Boschker et al., 1998; Boschker & Middelburg, 2002). From February until June the biomass and production of diatoms and bacteria were coupled. It was concluded that during these months SCOA were the most important substrates for the bacteria. Especially sulfate reducing bacteria (SRB) benefited from associating with SCOA-releasing diatoms. From August on, the coupling of biomass and production of diatoms and bacteria became less strong and was almost lost in December. During the period of August until December, EPS produced by diatoms promoted the growth of other bacterial taxa rather than SRB, and the production of SCOA was low. It seems likely that SRB utilizing SCOA dominated the community the first half the year (i.e. February, April, and June) and had a higher turnover than other bacteria which dominated the community the second half of the year (i.e. August, October, and December). The seasonal variation of exudates produced by diatoms played an important role in shaping the community composition and diversity of the associated bacteria.

With regard to EPS, CHO MQ rather than CHO EDTA appeared to be the most important intermediate in the initial transfer of carbon between diatoms and bacteria, while the amino acids originating from EPS were probably more important in the longer term. We observed after the initial fast transfer of carbon from diatoms to heterotrophic bacteria, a second peak of 13C label incorporation in bacteria coincided with on the one hand the disappearance of 13C label in EPS MQ and on the other hand the second release of 13C label in EPS MQ and EPS EDTA. It was therefore concluded that this second peak of labeling was due to prolonged consumption of EPS MQ, but also probably due to consumption of more recalcitrant EPS (after enzymatic hydrolysis to low-

8

Seasonal changes in the production and fate of EPS

219

molecular-weight compounds) in the long term (Hunter et al., 2006). Degrading complex EPS is slow and the entire process might take as long as a month (Giroldo et al., 2003). CHO EDTA seems a less favorable carbon source for heterotrophic bacteria, which is consistent with other studies (Giroldo et al., 2003).

Acknowledgements

We thank Erwin Moerdijk, Wanda Moerdijk, Jelle Moerdijk, Jurian Brasser and Gerjan de Ruiter for assisting in the field sample collection and processing of samples in the laboratory.

Part 2 Chapter 8, Supporting information

220

Exp

lana

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var

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Supporting information

Supplementary Table 8.S1. Explanatory variables Co-inertia analysis

8

Seasonal changes in the production and fate of EPS

221

Prod

uctio

n va

riabl

es

Sam

ple

Date

Low

FU

C M

RHA

MG

AL M

GLC

MXY

L MM

AN M

FUC

ERH

A E

GAL

EG

LC E

XYL E

MAN

ESe

r MG

ly M

Pro

MAl

a M

Val M

Ile M

Leu

MTy

r MLy

s MHi

s MPh

e M

Arg

MAs

p E

Ser E

Thr E

Val E

Met

EIle

ELe

u E

His E

Arg

ETi

de h

FEB

A21

-02-

1111

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3.9

2.1

11.9

185

5.3

4.8

3.2

1.7

10.0

13.0

1.7

1.5

0.03

0.22

4.00

0.03

0.28

0.05

0.07

0.62

0.05

0.04

0.17

0.09

0.02

0.02

1.78

0.63

0.10

0.06

0.10

0.05

0.23

APR

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1111

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10.9

3.8

6.2

896.

33.

416

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218

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53.

10.

160.

242.

610.

381.

020.

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552.

160.

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103.

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330.

650.

380.

21JU

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51.

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50.

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0.6

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0.07

2.81

0.03

0.29

0.09

0.19

0.26

0.07

0.04

0.40

0.02

0.00

0.01

0.01

0.07

0.01

0.03

0.03

0.06

0.02

FEB

B21

-02-

1111

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7.9

11.3

13.2

104

5.1

4.6

6.3

3.0

19.9

11.4

2.6

2.4

0.05

0.39

5.99

0.07

0.23

0.07

0.13

1.94

0.09

0.04

0.29

0.39

0.01

0.03

2.36

0.86

0.09

0.09

0.16

0.09

0.38

APR

B04

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1111

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90.

200.

333.

600.

491.

541.

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220.

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280.

840.

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180.

310.

100.

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0.3

0.3

0.8

50.

20.

20.

50.

81.

41.

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60.

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010.

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15-0

8-11

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62.

30.

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1.0

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0.7

1.2

0.7

0.4

0.4

0.04

0.05

0.75

0.01

0.35

0.24

0.44

0.50

0.38

0.10

0.48

0.07

0.04

0.55

0.05

0.15

0.00

0.11

0.19

0.03

0.05

OCT

B10

-10-

119:

240.

50.

11.

413

0.2

0.2

0.4

0.3

1.5

2.8

0.3

0.4

0.01

0.04

0.94

0.01

0.16

0.08

0.14

0.15

0.07

0.04

0.23

0.00

0.01

0.01

0.21

0.09

0.00

0.06

0.06

0.05

0.00

DEC

B12

-12-

1110

:25

0.8

0.3

2.3

440.

90.

70.

20.

21.

03.

30.

20.

30.

020.

062.

670.

000.

290.

070.

140.

350.

050.

020.

330.

010.

000.

000.

030.

070.

000.

030.

040.

020.

04

Carb

ohyd

rate

sAm

ino

acid

s

µmol

13C

m-2

h-1

µmol

13C

m-2

h-1

µmol

13C

m-2

h-1

µmol

13C

m-2

h-1

AA M

QAA

EDT

ACH

O M

QCH

O E

DTA

Supplementary Table 8.S2. Production parameters of EPS by their carbohydrates and amino acids (0-4 h)

Part 2 Chapter 8, Supporting information

222

Day

3 va

riabl

es

Sam

ple

Date

FUC

MRH

A M

GAL

MG

LC M

XYL M

MAN

MFU

C E

RHA

EG

AL E

GLC

EXY

L EM

AN E

Ser M

Gly

MPr

o M

Ala

MVa

l MIle

MLe

u M

Tyr M

Lys M

His M

Phe

MAr

g M

Asp

ESe

r ETh

r EVa

l EM

et E

Ile E

Leu

EHi

s EAr

g E

FEB

A24

-02-

1119

.610

.219

.244

.18.

06.

410

.86.

021

.93.

85.

74.

40.

100.

251.

740.

140.

430.

240.

290.

930.

430.

250.

350.

500.

070.

090.

660.

510.

180.

350.

350.

110.

53AP

R A

07-0

4-11

22.1

8.3

14.6

76.0

9.7

7.7

17.2

6.1

13.8

6.6

8.1

3.6

0.17

0.21

3.12

0.05

0.90

0.77

1.03

1.38

1.31

0.37

1.43

0.46

0.06

0.28

0.87

1.58

0.05

0.95

1.13

0.37

0.58

JUN

A17

-06-

110.

40.

61.

93.

50.

00.

32.

12.

54.

01.

61.

51.

50.

060.

470.

030.

240.

230.

380.

250.

620.

180.

430.

210.

000.

030.

000.

050.

000.

030.

030.

170.

07AU

G A

18-0

8-11

1.8

1.4

2.7

21.4

1.1

1.3

2.1

3.3

4.3

0.6

1.9

1.9

0.11

0.19

1.99

0.40

0.85

0.95

1.30

1.63

1.87

0.72

1.63

0.74

0.14

0.29

0.06

0.16

0.04

0.09

0.07

0.14

0.17

OCT

A13

-10-

110.

60.

51.

68.

40.

40.

30.

60.

40.

90.

70.

30.

30.

070.

101.

530.

080.

440.

360.

530.

850.

700.

470.

580.

110.

030.

030.

140.

060.

010.

030.

030.

460.

04DE

C A

15-1

2-11

0.7

0.3

1.3

4.9

0.3

0.3

3.5

4.0

6.0

4.4

3.1

2.6

0.05

0.07

1.09

0.08

0.38

0.19

0.40

0.54

0.55

0.20

0.56

0.10

0.00

0.26

0.05

-0.0

20.

040.

100.

140.

060.

06FE

B B

24-0

2-11

14.1

7.0

23.7

78.4

8.3

7.0

9.0

4.2

15.7

2.7

4.1

3.1

0.06

0.12

1.31

0.06

0.23

0.14

0.20

0.52

0.37

0.14

0.16

0.29

0.00

0.07

0.57

0.71

0.04

0.23

0.33

0.07

0.24

APR

B07

-04-

1121

.510

.015

.982

.910

.07.

415

.85.

913

.77.

07.

63.

50.

610.

7915

.46

0.27

4.94

3.89

7.50

10.1

27.

761.

797.

991.

850.

560.

121.

001.

570.

030.

810.

990.

000.

39JU

N B

17-0

6-11

0.5

0.6

1.4

2.5

0.3

0.4

1.7

2.0

3.5

1.5

1.2

1.2

0.07

0.36

0.06

0.29

0.26

0.49

0.67

0.61

0.19

0.71

0.25

0.00

0.00

0.00

0.00

0.01

0.03

0.03

0.03

0.07

AUG

B18

-08-

111.

41.

32.

510

.91.

11.

33.

34.

24.

30.

62.

72.

70.

050.

080.

470.

060.

290.

270.

520.

450.

670.

240.

800.

300.

010.

080.

050.

06-0

.03

0.03

0.03

0.00

0.06

OCT

B13

-10-

110.

40.

30.

93.

90.

20.

36.

03.

311

.84.

94.

03.

60.

060.

050.

600.

080.

200.

170.

290.

320.

280.

100.

340.

040.

030.

030.

110.

060.

000.

040.

030.

240.

04DE

C B

15-1

2-11

1.3

0.8

2.4

8.2

0.8

0.4

0.8

1.0

1.6

1.6

1.1

1.2

0.30

0.23

5.72

0.32

2.14

1.48

2.59

3.39

4.07

1.11

3.60

1.00

0.01

0.17

0.59

-0.0

90.

020.

620.

970.

180.

43

µmol

13C

m-2

µmol

13C

m-2

µm

ol 13

C m

-2

µmol

13C

m-2

Carb

ohyd

rate

sAm

ino

acid

s

CHO

MQ

CHO

EDT

AAA

MQ

AA E

DTA

Supplementary Table 8.S3. Day 3 13C label content of EPS in their carbohydrate and amino acid components