Brivaëla Moriceau
email: moriceau@univ-brest.fr

Madeleine Goutx

Catherine Guigue

Cindy Lee

Robert Armstrong

Marie Duflos

Christian Tamburini

Bruno Charrìère

Olivier Ragueneau

Bruno Charrière

Si-C interactions during degradation of the diatom Skeletonema marinoi

Keywords: Biogenic silica, dissolution, carbon, amino acids, lipids, degradation, diatom

come

Introduction

Organic carbon produced in the ocean's surface layer by phytoplankton is conveyed to depth by particle sedimentation, and fluxes of carbon and minerals (CaCO 3 , SiO 2 and aluminosilicates) are highly correlated in the deep water column. Based on these observations, Armstrong et al. (2002) highlighted the importance of modeling both carbon and mineral fluxes at the same time.

Mineral ballast (CaCO 3 of coccolithophorids; SiO 2 of diatoms; aluminosilicates in dust) provide excess density needed for organic matter to sink; bSiO 2 and carbonate sedimentation are also linked through the ability of phytoplankton to aggregate and through grazing by zooplankton.

The combination of these processes strongly increases the sedimentation rate of phytoplankton (e.g., [START_REF] Gehlen | Reconciling surface ocean productivity, export fluxes and sediment composition in a global biogeochemical ocean model[END_REF][START_REF] Moriceau | Importance of particle dynamics on reconstructed water column biogenic silica fluxes[END_REF].

The role of mineral ballast in carbon transport is more complex than a simple impact on excess density [START_REF] Lee | Particulate matter fluxes in time-series and settling velocity sediment traps in the northwestern Mediterranean Sea[END_REF]), but we are far from fully understanding the processes involved.

Lee et al. (2000) and Hedges et al. (2001) hypothesized that mineral ballast could protect organic carbon from degradation; their hypothesis is consistent with the observation of Ingalls et al. (2006) that organic matter was more degraded in areas where diatoms were not the dominant bloom species when compared to sites where diatoms were the main phytoplankton group. Engel et al. (2008) also showed that the presence of the calcite test in coccolithophorids lowers the POC degradation rate during the recycling of these cells. Continuously increasing pressure reduced rates of bSiO 2 dissolution of diatom detritus relative to rates measured under atmospheric pressure conditions [START_REF] Tamburini | Pressure effects on surface Mediterranean prokaryotes and biogenic silica dissolution during a diatom sinking experiment[END_REF]. In parallel, naturally collected sinking particles, were also less degraded by prokaryotes when pressure was continuously increased to simulate descent from 200 to 1500 [START_REF] Tamburini | Microbial alteration of sinking fecal pellets: Effects of a continuous increase in pressure that simulates descent in the water column[END_REF]. Despite all these findings, few studies (e.g., [START_REF] Ingalls | The role of biominerals in the sinking flux and preservation of amino acids in the Southern Ocean along 170°W[END_REF]2006) have investigated both organic matter degradation and biogenic mineral dissolution in natural settings. The work of Engel et al. (2008) investigated the role of CaCO 3 in carbon degradation, while the present study aims to better understand the role of Si-C interactions during diatom degradation.

Diatoms are the dominant species in many ecosystems; they are responsible for up to 35% of the total primary production in oligotrophic oceans and up to 75% in coastal waters and the Southern Ocean [START_REF] Nelson | Production and dissolution of biogenic silica in the ocean: Revised global estimates, comparison with regional data and relationship to biogenic sedimentation[END_REF][START_REF] Tréguer | The silica Balance in the World Ocean: A Reestimate[END_REF]. [START_REF] Jin | Diagnosing the contribution of phytoplankton functional groups to the production and export of particulate organic carbon, CaCO3, and opal from global nutrient and alkalinity distributions[END_REF] estimated their global contribution to net primary production and to carbon export to be 15% and 40%, respectively. The high diatom contributions to primary production and carbon export, could potentially explain the empiric relation established by [START_REF] Ragueneau | Si/C decoupling in the world ocean: is the Southern Ocean different?[END_REF]. This relation shows that Si/C ratios decrease with depth and follow the same pattern everywhere in the world ocean. Is there a link between bSiO 2 dissolution and POC degradation such as the one hypothesized in the work cited above?

The objective of the present study was to understand how biogenic silica influences the degradation of diatom organic carbon, and conversely the role of organic compounds in bSiO 2 dissolution. With this aim, a monospecific culture of the diatom Skeletonema marinoi was incubated in the presence of a natural coastal bacterial community and allowed to degrade over a 102-day period. bSiO 2 dissolution and the quantity and composition of organic compounds, including amino acids and lipids, were assessed throughout the incubation period and used to investigate Si-C interactions during decomposition. Three dissolution/degradation models were applied to the experimental data to elucidate the dissolution/degradation pattern of the components of S. marinoi. This modeling experiment yields a better understanding of the structure of the diatom frustule in S. marinoi and of the role of Si-C interactions during diatom recycling.

Material and methods

Biodegradation experiment

Skeletonema marinoi (CCAP 1077/3) obtained from IFREMER (Argenton station, France) was grown in f/2 medium [START_REF] Guillard | Studies of marine planktonic diatoms. I. Cyclotella nana Hustedt and Detonula confervacae (Cleve)[END_REF][START_REF] Guillard | Culture of phytoplankton for feeding marine invertebrates[END_REF] under 12/12 dark/light illumination. When cells reached stationary growth phase (6.5 x 10 6 cells ml 1 -), they were transferred into a 4°C chamber and kept in the dark for 5 days. During this period, cells sank to the bottom of the flask, and previous tests showed that diatom viability (number of living cells versus total cells) decreased (unpublished data, method described in [START_REF] Garvey | Applicability of the FDA assay to determine the viability of marine phytoplankton under different environmental conditions[END_REF]). The supernatant was poured off, and the overlying medium was replaced with natural seawater that had been passed through a 0.7-µm GFF filter to preserve the natural bacteria assemblage. The seawater was collected from a small inlet (Endoume) near Marseille, France, at the end of fall, when the water is naturally poor in silicic acid (dSi~2.5 µM). The mixture of S. marinoi and filtered sea water was then transferred to an incubation flask equipped with a magnetic stirrer and a stopper through which gas exchange could occur via a 0.2-µm Swinnex® filter. The diatoms were incubated for 102 days in the dark at 20°C. Using a peristaltic pump, samples were taken daily for the first 21 days and then at 23, 25, 46, 50, and 102 days; triplicate samples were taken at 0, 5, 11, 46, 50, and 102 days. The sampled solution was well-mixed, allowing the ratio of solid matter to solution to remain constant [START_REF] Dixit | Processes controlling solubility of biogenic silica and porewater build up of silicic acid in marine sediments[END_REF]. Ten percent of the liquid volume remained at the end of the experiment. Chemical parameters measured were biogenic silica (bSiO 2 ), silicic acid (dSi), particulate organic carbon and nitrogen (POC, PON), dissolved organic carbon (DOC), total particulate lipids (TLip), and total hydrolyzable amino acids (THAA). In addition total bacterial abundances (diamidinophenylindole: DAPI counts) were counted. Si contamination by dissolution of glassware was measured by analyzing dSi in an incubation bottle with no cells added. We also sampled controls poisoned with 20 mg l -1 HgCl 2 at 4 times (0, 2, 5, and 11 days) to verify that degradation was due to bacteria and not abiotic factors.

Analytical Methods

Biogenic Silica (bSiO 2 ) was determined at the beginning and end of the experiment using a variation of the method of [START_REF] Ragueneau | Determination of biogenic silica in coastal waters: applicability and limits of the alkaline digestion method[END_REF]. As no lithogenic silica was present in the algal culture, the second digestion step using HF was not necessary. Ten-ml samples were filtered onto 0.2-µm polycarbonate filters. Filters were analyzed for bSiO 2 and the filtrate for dSi. For bSiO 2 , filters were digested in 20 ml of 0.2N NaOH for three hours at 95°C to ensure the dissolution of all bSiO 2 ; dSi concentrations in the solution remained far below the solubility equilibrium of bSiO 2 at all times. After cooling, the solution was acidified with 5 ml of 1N HCl, centrifuged to remove remaining solids, and analyzed for dSi. The precision for triplicate measurements of bSiO 2 was < 5%.

Silicic acid (dSi) concentrations were determined on 10-ml filtered samples and on digested bSiO 2 samples using the molybdate blue spectrophotometric method of [START_REF] Mullin | The spectrophotometric determination of silicate-silicon in natural waters with special reference to seawater[END_REF], as adapted by [START_REF] Tréguer | Manuel d'analyse des sels nutritifs dans l'eau de mer: utilisation de l'auto-analyseur Technicon II[END_REF] and modified by Gordon et al. (1993) for use in segmented flow colorimetry. We used a Bran and Luebbe Technicon Autoanalyzer (<1% precision).

POC and PON concentrations were measured using a Carlo Erba NA 2100 CN analyzer coupled to a Finnigan Delta S mass spectrometer. Five-ml samples were filtered through 0.7-µm GFF filters. The filters were desiccated overnight in an oven at 50°C and then placed in tin capsules to be introduced into the oven of the analyzer. The precision for triplicate N analyses was ± 1-6%, and for C analysis ± 1-5%.

DOC was analyzed after filtration through 0.7-µm GFF filters; 10 ml of each sample was transferred into glass ampoules and sealed after addition of H 3 PO 4 as preservative. All glassware was pre-rinsed with 1N HCl and Milli-Q water before being combusted at 465°C; care was taken to minimize contamination during sampling and handling. DOC was measured by hightemperature catalytic oxidation using a Shimadzu TOC 5000 Analyzer [START_REF] Sempéré | Distribution and cycling of total organic carbon across the Almeria-Oran Front in the Mediterranean Sea: Implications for carbon cycling in the western basin[END_REF][START_REF] Sohrin | Seasonal variation in total oranic carbon in the northeast Atlantic in 2000-2001[END_REF]. Samples were acidified to pH 1 with 85% phosphoric acid and bubbled for 10 minutes with CO 2 -free air to purge them of inorganic carbon. Three or four 100 µl replicates of each sample were injected into the 680 °C column. The precision of these replicates was ≤ 6%.

Total particulate lipids were analyzed after filtering 10 ml samples onto 0.7-µm GFF glass fiber filters. Filters were extracted according to [START_REF] Bligh | A rapid method for total lipid extraction and purification[END_REF]. Lipid extracts were separated into classes of compounds and quantified on an Iatroscan model MK-6s (Iatron, Tokyo; H 2 flow 160 ml min 1 -

; air flow 2 l min -1

) as described by [START_REF] Goutx | Composition and degradation of marine particles with different settling velocities in the Northwestern Mediterranean sea[END_REF]. The elution scheme allows reliable separation and quantification of degradation metabolites from acyl-lipid classes [START_REF] Striby | Improvement in the Iatroscan thin-layer chromatography-flame ionisation detection analysis of marine lipids. Separation and quantitation of mono-and diacylglycerols in standards and natural samples[END_REF]. Total particulate lipids (TLip) are the sum of the separated lipid classes (Table 1). In the present work, the variability within triplicates was < 13%.

Amino acids were analyzed on 0.7-µm GFF filters after filtration of 10-ml samples.

Thawed filters were treated as described in the study of [START_REF] Ingalls | The role of biominerals in the sinking flux and preservation of amino acids in the Southern Ocean along 170°W[END_REF]. Individual compounds were separated by HPLC using pre-column OPA derivatization after acid hydrolysis as described in [START_REF] Lee | The vertical flux of particulate organic nitrogen in the sea: Decomposition of amino acids in the Peru upwelling area and the equatorial Atlantic[END_REF] and [START_REF] Lee | Composition and flux of particulate amino acids and chloropigments in equatorial Pacific seawater and sediments[END_REF]. Amino acids were detected by fluorescence and identified by comparison to retention times of standards made from an amino acid mixture (Pierce, Standard H). The non-protein amino acids β-alanine and γ-aminobutyric acid (BALA and GABA) were added individually to the standard mixture. Aspartic acid (ASP)

and glutamic acid (GLU) measurements include the hydrolysis products of asparagine and glutamine. THAA is the sum of the 16 characterized amino acids (Table 1). Variation among replicates was generally 15-30%. LYS replicates, however, varied more greatly at times, e.g., 50% at day 11.

Total bacterial abundances (DAPI counts): Subsamples for bacterial cell counts were fixed immediately with buffered formalin (final volume 2%). Cells were collected onto a 25-mm 0.2-µm polycarbonate Nuclepore® membrane and stained with diamidinophenylindole (DAPI; [START_REF] Porter | The Use of DAPI for Identifying and Counting Aquatic Microflora[END_REF]. Slides were stored frozen until counting by epifluorescence microscopy (Olympus, BH2).

Kinetics

Kinetic parameters were calculated over the first 25 days where experimental data are available every 1-2 days. For each compound of interest we tested three degradation/dissolution models. Model 1 is a simple first-order rate equation as described in [START_REF] Greenwood | Biogenic silica dissolution in seawater -in vitro chemical kinetics[END_REF] and used in many dissolution studies (e.g. [START_REF] Kamatani | Rate dissolution of diatom silica walls in seawater[END_REF][START_REF] Kamatani | The dissolution of opaline silica of diatom tests in seawater[END_REF][START_REF] Kamatani | Dissolution Rates of silica from diatoms decomposing at various temperature[END_REF]:

ˆ C (t) = C 0 exp(-k t) , (1)
where ˆ C (t) is the concentration (µM) estimated at time t (d), C 0 is the initial concentration, and k is the dissolution/degradation rate constant ( 1 d -

).

Model 2 assumes simultaneous dissolution/degradation of two phases. The equation used is similar to that used for carbon degradation in the study of [START_REF] Westrich | The role of sedimentary organic matter in bacterial sulfate reduction: The G model tested[END_REF]:

ˆ C (t) = C 1 exp(-k 1 t) + C 2 exp(-k 2 t) (2)
In Model 2, four parameters are estimated: C 1 and C 2 are concentrations (µM) of phase or pool 1 and 2, and k 1 and k 2 ( 1 d -

) are their respective dissolution or degradation rate constants.

As it uses 2 more parameters, Model 2 always gives a better fit than Model 1 except when the initial degradation rate is slower than later rates. In this specific case Model 2 performs no better than Model 1. We therefore developed Model 3, which employs one firstorder equation initially, and a second first-order equation after that. The time at which the dissolution/degradation rate constant changes is called the substitution time ( t s ), and is allowed to take on any value >0.

ˆ

C (t) = C 0 exp(-k 1 t) , 0 < t < t s ; (3a) ˆ C (t) = C(t s ) exp(-k 2 t) , t > t s . ( 3b
)
Model 3 also contains 4 parameters.

If dissolution/degradation for a given compound is best reconstructed using Model 2, this compound is constituted by at least two phases or pools; on the other hand if Model 3 gives a better description of the dissolution/degradation pattern, either the compound studied is present in 2 phases/pools remineralizing one after the other, or a change in environmental parameters provoked a change in the dissolution/degradation rate constant at time ts.

In addition, to allow direct comparison of the degradation/dissolution pattern among all compounds, and between this study and previous studies, an initial disappearance rate constant was calculated for each compound over the first 10 days using Model 1.

Statistics

Each fit was optimized by maximizing the likelihood statistic log(L) as described in equation 4 (Armstrong et al., 2002, and references therein). Eq. ( 4) is based on a Gaussian distribution with a constant variance on a logarithmic scale:

        ∑ - × = N C C 2 N - (L) j j 2 )) log( ) (log( log log , ( 4
)
where N is the number of data points, C j is a measured concentration for data point j, and the ˆ C j is the corresponding model prediction. The difference in log(L) ( ) log( L

∆

) between fits of two different models to the same data gives the goodness of fit of one model compared to the other.

If one model gives a value for log(L) that is at least 2 points higher per added parameter than another model, it is considered to fit the data better [START_REF] Hilborn | The ecological detective : Confronting Models with Data[END_REF]. In the present work, the simplest model (Model 1) was considered to be the best fit unless Model 2 or Model 3 yielded a log(L) more than 4 points better than that of Model 1.

Results

3.1 Change in biochemical composition of the diatom Skeletonema marinoi over time between days 0 and 14 was 2%. Bacterial carbon made up a maximum of 2.4 ± 0.6% of the POC.

TOC concentrations over time showed a pattern similar to those of POC (Fig. 3). DOC concentrations increased slightly (5.6 ± 0.2 mg C L -1

) but much less than POC decreased (62 ± 3 mg C L -1

). The bacterial carbon (C bact ) is so low compared to the algal organic carbon that the mineralization rate for POC algal (POC+DOC-C bact ) is the same as for the total organic carbon (Corg = POC+DOC). This rate calculated as the slope of TOC change over time (Fig. 3) was

2.68 mg C L -1 1 d -
during the first 20 days of the experiment and was equivalent to 91% of the POC loss.

Initial biochemical composition

At the beginning of the experiment, the Si/POC ratio was 0.09 ± 0.01, which is slightly lower than the value of 0.13 measured in fresh diatoms by [START_REF] Brzezinski | the Si:C:N ratio of marine diatoms: interspecific variability and the effect of some environmental variables[END_REF] but in the range of coastal diatoms measured by [START_REF] Rousseau | Diatom succession, silicification and silicic acid availability in Belgian coastal waters (Southern North Sea)[END_REF]. TLip made up 19 ± 2% of S. marinoi organic carbon which is a little bit higher that Lip/POC ratios measured previously for the same specie (Lavens and Sorgeloos, 1996). TLip mainly included FFA and other degradation metabolites (ALC and MG; see Table 1 for abbreviations) (Fig. 4a). Cellular membrane phospholipids (PE, DPG+PG) and chloroplast membrane glycolipids (MGDG) accounted for 10 ± 1% and 13 ± 1% of TLip, respectively. FFA were the most abundant lipid degradation metabolites (24.8 ± 0.5%) among those present. PIG included both chlorophyll a and its degradation products [START_REF] Striby | Improvement in the Iatroscan thin-layer chromatography-flame ionisation detection analysis of marine lipids. Separation and quantitation of mono-and diacylglycerols in standards and natural samples[END_REF]; PIG was the largest lipid class (initially 41 ± 5%; Fig. 4a). ST are involved in membrane rigidity [START_REF] Parrish | Dissolved and particulate marine lipid classes: a review[END_REF]; they were initially minor components of S. marinoi.

THAA constituted a larger portion (36 ± 9%) of total organic carbon than the lipids, similar to the 45% found in Thalassiosira weissflogii by [START_REF] Cowie | Digestion and alteration of the biochemical constituents of a diatom (Thalassiosira weissflogii) ingested by an herbivorious copepod (Calanus pacificus)[END_REF] and the 25% observed in diatom-rich sediments by [START_REF] Ingalls | Seasonal trends in the pigments and amino acid compositions of sinking particles in biogenic CaCO3 and SiO2 dominated regions of the Pacific sector of the Southern Ocean along 170°W[END_REF]. THAA include the monomer constituents of protein as well as adsorbed amino acids and peptides. Sixteen amino acids were quantified. GLU, ASP and LEU (see Table 1 for abbreviations) together made up one third of the THAA, each more than 11 ± 3% (Table 2). Other amino acids were between 2.1 ± 0.6% and 9.3 ± 2.8% of the THAA except for MET and GABA, which were less than 0.8%. As GABA and MET concentrations were very low throughout the incubation, they are not described in the following paragraphs. The initial mole% amino acid compositions we found for S. marinoi (Table 2) were very similar in pattern to those of cultured diatoms reported by Ingalls et al.

( 2003) and [START_REF] Cowie | Digestion and alteration of the biochemical constituents of a diatom (Thalassiosira weissflogii) ingested by an herbivorious copepod (Calanus pacificus)[END_REF], with highest mole% values for ASP, GLU, and GLY. S. marinoi was higher in mole% LEU than in reports of other diatoms. THAA do not include the amino acids incorporated inside the silica frustule, unless part of the frustule is dissolved during acid hydrolysis (see later discussion). We define Si-bound amino acids as Si-THAA as in [START_REF] Ingalls | The role of biominerals in the sinking flux and preservation of amino acids in the Southern Ocean along 170°W[END_REF]. The THAA composition was relatively constant throughout the degradation experiment except between days 15 and 20 where we observed a strong peak of GLY, which increased from 13 ± 2% to 33 ± 8% (Fig. 4b). The relative concentrations of HIS (data not shown) and LYS also peaked slightly between days 15 and 20. Relative proportions of other amino acids especially ASP decreased at this time in response to the increases in HIS, GLY and LYS.

Change in biochemical composition during degradation

3.2 Dissolution and degradation kinetics of S. marinoi constituents

Silica kinetics

The experiment was conducted in glass bottles to eliminate carbon contamination.

Controls showed that after 102 days, dSi due to leaching from the glass was a maximum of 5% of the dSi due to dissolution of diatom frustules. From an initial concentration of 680 ± 30 µmol L -1 , bSiO 2 decreased rapidly during the first 3 to 5 days of the experiment and then more slowly (Fig. 1). After 25 days, 52% of the initial bSiO 2 was dissolved and 76% of the initial was dissolved at the end of the experiment (102 d). The comparison between the log(L) of the three models describing bSiO 2 dissolution showed that Model 2 is 4. 4). For direct comparison with POC and PON, the initial loss rate constant of the total bSiO 2 was calculated using Model 1 over 10 days as , respectively (Table 4). At day 11 when on average 49 ± 10 % of the THAA had degraded, all concentrations except ARG and SER suddenly increased by 6 to 58 % in 1 to 2 days (Fig. 6b). The largest releases were observed for HIS, GLY and LYS, which increased by 39 ± 13 %, 58 ± 10 % and 46 ± 12 %, respectively. For every amino acid except TYR, degradation rate constants increased after this peak. For ASP and SER the increase occurred earlier at day 5, and for TYR the degradation rate constant decreased from 0.070 to 0.012 4).

Amino acid kinetics

3.3 Relation between bSiO 2 dissolution and degradation of individual organic compounds or compound classes

Lipid degradation versus bSiO 2 dissolution

There was a strong linear relationship between total bSiO 2 and TLip over the whole range of bSiO 2 concentrations (r 2 = 0.85, n = 26) measured. There was no correlation between bSiO 2

and PIG, so that the relationship between bSiO 2 and TLip became even better when pigments were excluded from the other lipids (r 2 = 0.94, n = 26). FFA were well correlated with total bSiO 2 concentrations (r 2 = 0.95, n = 26); they were completely degraded during the dissolution of the second bSiO 2 phase, when bSiO 2 concentrations eventually reached 260 µmol L -1 .

Relationships among individual lipid classes and bSiO 2 phases showed three distinct periods (Fig. 7a andb), which were related to bSiO 2 dissolution using the bSiO 2 model (Figure 5a). Period 1 (P1) is the time corresponding to dissolution of 85% of the first bSiO 2 phase and 10% of the second bSiO 2 phase; Period 2 (P2) is the time corresponding to dissolution of most of the remaining bSiO 2 from the first phase and another 10% of the second bSiO 2 phase; and Period 3 (P3) is the time when less than 1.5% of the first phase remained and 60% of the second phase dissolved. At the end of P3 20% of the bSiO 2 from the second phase remained. On average, 26- 34% of the TLip degraded during Period 1; only 14-19% of TLip remained at the beginning of Period 3. The slow decrease of concentrations observed for each lipid class except PIG, during P1 and P3 compared to P2 despite the fact that the three periods lasted the same time (~7 days, Fig. 5a), might show that most TLip except PIG degraded during P1 were associated with the first bSiO 2 phase, and most TLip except PIG degraded during P3 with the second bSiO 2 phase.

These specific lipids are denoted as Si(1)-Lip and Si(2)-Lip; their composition is shown Table 3. Degradation of MG, ALC, PE and ST mainly occurred in P2. PE and ST concentrations dropped in P2 and ALC degradation was even faster; Model 3 gave a higher k 1 and a longer ts for ALC than for PE and ST. After the precipitous drop, which corresponded to the beginning of P3, 80% of ALC, FFA and PE and 40% of ST were degraded. MG were completely degraded so quickly at the beginning of P2 that the loss is more likely due to sudden release of MG adsorbed onto particles or dissolution (i.e. involving chemical mechanisms) rather than degradation (i.e. biological mechanisms).

DPG+PG were not well correlated with bSiO 2 ; generally there was a 36%-degradation during P1, then a fast release of DPG+PG in P2 (40-50%), possibly when the first bSiO 2 phase is completely dissolved. Due to the release in P2, 80% of the initial DPG+PG remained at the beginning of P3.

Amino acid degradation versus bSiO 2 dissolution

The relationship of THAA with the two bSiO 2 phases showed changes at the same times as many of the lipid classes, so we used the same three periods. During Period 1, when the first bSiO 2 phase was dissolving, only 3-22 % of the THAA degraded. For the reason described in the previous section for lipids (3.3.1), this portion of the THAA is referred to as Si(1)-THAA. GLY and LYS lost less than 10 % of their initial concentrations; ASP and GLU lost 40 % of their initial concentrations. GLU, ASP, and LEU constituted most of the pool degrading during P1;

LYS is not correlated to the first bSiO 2 phase (Table 2).

At the end of period 2, a pool of THAA was released when 95 % of the first bSiO 2 phase was dissolved (Fig. 8a andb). THAA concentrations decreased by 32 % compared to initial values. Measurement of THAA does not release Si-bound amino acids so that they would not be observed until the bSiO 2 dissolved; the THAA released (Si(2)-THAA) may have been trapped

between the 2 phases. The amount of Si(2)-THAA can be calculated from the difference between the concentrations of amino acids at and before the peak maximum (Table 2). In total, THAA concentration increased by 11-16 % (in µmol C L -1

); the Si(2)-THAA were composed mainly of GLY (23 ± 8 %) and LYS (23 ± 8 %; see Table 2).

During P3, relative THAA concentrations declined from 34 % to 5 % of the original THAA. The THAA lost during P3 are called Si(3)-THAA, they had a composition similar to that of total THAA, except that the contribution of GLY was higher (Table 2).

Discussion

Importance of bacteria in S. marinoi degradation

The very high concentration of algae, when compared to the bacterial concentrations, and the continued degradation in the presence of HgCl 2 , suggest that the loss of organic matter was due not only to biological degradation, but also to physical and chemical factors (dissolution). In the presence of HgCl 2 , organic matter turned over with a low rate constant (0.02 1 d - , r² = 0.86, n = 8), which appeared to decrease even more after day 5 (0.007 1 d - , n = 4; 2 replicates). This could be due to initial dissolution of organic matter as the cell begins to fall apart; smaller rate constants after some time would then be due to the absence of bacterial degradation. However, the lack of appropriate samples makes this observation tentative. The slower increase of DOC concentrations compared to the decrease in POC (Fig. 3) suggests that most of the POC loss may be due to bacterial degradation despite the similar degradation rate measured in HgCl 2 -poisoned batches. Degradation of particulate matter in the presence of HgCl 2 has been noted before (Liu et al., 2006).

It was not clear why bacteria grew so slowly after day 14 in the unpoisoned experiment.

Three factors could have contributed to the decrease and stabilization of bacterial growth. First, O 2 could have been a limiting factor. We did not measure O 2 during the experiment but we calculated average TOC loss, R loss = 221.6 µmol L -1

. Change in oxygen concentrations (C O2 )

with time (t) can be reconstructed from O 2 consumption rate (R loss ) and O 2 diffusion rate (R diff )

(eq. 5). The latter is given by the Whitman film model [START_REF] Gladyshev | Biophysics of the surface Microlayer of Aquatic Ecosystems[END_REF]eq. 6).

loss diff O R R dt dC - = 2 (5) ) C (Cs V S δ D R O O diff 2 2 - × × = (6)
where δ is the thickness of the diffusion layer, and is strongly dependent on stirring; D is the O 2 diffusion coefficient (1.83 cm 2 d -1

, [START_REF] Ploug | Small-scale oxygen fluxes and remineralization in sinking aggregates[END_REF]; S is the surface of contact between air and water (415.5 cm 2 ); V is the volume of the solution, which changed progressively during sampling; and Cs O2 is the saturation concentration of the O 2 in seawater (229.9 µM). Using these equations and parameters, we estimated the maximum δ above which the solution will be anoxic.

Considering that the risk of consuming all O 2 is greater for a larger volume of solution (with the same surface area), we conservatively used the volume of solution at the beginning of the experiment V=V 0 (8100 cm 3 ).

We seek a value of δ max , at which dt dC O2 will always be positive when C O2 approaches 0 so that the system can never go anoxic. This condition is met when

2 SO diff loss C V S D R R × × = ≤ δ (7) or whenever O2 0 loss Cs V S R D × × = max δ (8)
We calculated that when the volume is at its maximum in the flask (8100 cm 3 at the beginning of the experiment), the depth of the diffusive layer must be less than 0.1 cm for the solution to remain oxic. The thickness of the diffusion layer is 0.27 cm with no stirring and can be as small as 0.0015 cm when the stirring is intense [START_REF] Gladyshev | Biophysics of the surface Microlayer of Aquatic Ecosystems[END_REF]. Since our flasks were well mixed, it is very unlikely that O 2 was a limiting factor. A second explanation is that degradation products built up in the flask and poisoned the bacteria [START_REF] Westrich | The role of sedimentary organic matter in bacterial sulfate reduction: The G model tested[END_REF][START_REF] Aller | The effect of biogenic irrigation intensity and solute exchange on diagenetic reaction rates in marine sediments[END_REF]. We cannot exclude this possibility, but calculating kinetic parameters over only 25 days should alleviate some of this problem. This period of time is a reasonable compromise between the need to follow the degradation of S. marinoi as long as possible so as to better understand reactions in the water column and the risk of accumulating inhibiting metabolites. Finally, the bacteria might have stopped growing due to viral lysis, grazing or a lack of labile substrate fuelling their growth (Fig. 2).

Importance of Si-C interactions to bSiO 2 dissolution

Previous dissolution studies have assumed that the diatom frustule is composed of a single bSiO 2 phase (see review in Van Cappellen et al., 2002b). Results from our modelling exercise suggest instead that the frustule of S. marinoi is composed of two phases of bSiO 2 with different dissolution characteristics. This idea, previously hypothesized by [START_REF] Kamatani | Rate dissolution of diatom silica walls in seawater[END_REF] from dissolution rate measurements and by [START_REF] Gallinari | The importance of water column processes on the dissolution properties of biogenic silica in deep seasediments I. Solubility[END_REF] from solubility equilibrium measurements, is consistent with the complexity of the frustule structure. During silicification, polyamines and silaffin proteins catalyze precipitation of organo-silicon particles of different shape and structure that determine the morphology of different diatom species [START_REF] Kröger | Species-specific polyamines from diatoms control silica morphology[END_REF][START_REF] Hildebrand | Biological processing of nanostructured silica in diatoms[END_REF]. As a result of these interactions, diatom frustules have a complex 3-D structure and are shaped like an elliptic or cylindrical box. Each half is composed of a valve and girdle bands that are built at different times in the cell cycle [START_REF] Hildebrand | Components and control of silicification in diatoms[END_REF]. In our study we distinguish two bSiO 2 phases and calculate their dissolution rate constants. Even though we didn't determine a direct relation between these dissolution characteristics and the structure of the frustule, we were able to determine the impact of twophase dissolution on the organic matrix of the cells as discussed below (see section 4.3).

Diatom frustules include organic layers that consist mainly of sugars and amino acids [START_REF] Hildebrand | Nanoscale control of silica morphology and three-dimensional structure during diatom cell wall formation[END_REF]. The major amino acids in this coating are GLY, THR, and SER, suggesting that bonding with silica occurs through SER and THR, using their OH groups [START_REF] Hecky | The amino acids and Sugar Composition of Diatom Cell-Walls[END_REF]. GLY enrichment observed during our study in the refractory (second) bSiO 2 phase might suggest a more important role of GLY. Si-C or Si-O-C interactions are thought to protect silica from dissolution until the organic matrix is removed by bacteria [START_REF] Hecky | The amino acids and Sugar Composition of Diatom Cell-Walls[END_REF][START_REF] Patrick | The effect of bacteria on the solubilization of silica in diatom frustules[END_REF][START_REF] Bidle | Bacterial control of silicon regeneration from diatom detritus: significance of bacterial ectohydrolases and species identity[END_REF]. The different dissolution parameters of the bSiO 2 phases may be due to different associations between silica and organic compounds in different sections of the frustule. Indeed, [START_REF] Abramson | The use of soft X-ray spectromicroscopy to investigate the distribution and composition of organic matter in a diatom frustule and a biomimetic analog[END_REF] observed changes in the distribution of organic compounds inside the frustule that would support this argument. The very slow dissolution rate constant for the second bSiO 2 phase could be due to protection by the organic matrix. We suggest (1) that only a part of the bSiO 2 is protected by the organic coating, and (2) that this protection lasts for a longer time than was previously thought. Low bacterial concentration could also partially explain why the protection of the second bSiO 2 phase lasted so long, while in previous studies the protection was only temporary. The linear correlation between FFA and the total bSiO 2 indicates that these compounds are associated with both phases of bSiO 2 , even though all FFA were completely degraded while 31% of the bSiO 2 still remained.

Few FFA were associated with the intracellular pool of lipids. Because of their amphipathic properties due to the carboxyl group bonded to the long carbon chain, FFA probably play a role in the organization of the organic matrix involved in building the frustule [START_REF] Chevallard | Les matériaux biomimétiques[END_REF]. The relationship between FFA degradation and dissolution of the two bSiO 2 phases, and the fact that FFA were completely degraded before the total dissolution of the bSiO 2 , might also indicate another type of interaction, possibly adsorption of FFA on the silica surface.

In the present study, lipid classes and individual amino acids showed a general correlation with bSiO 2 concentration (Figs. 7 and8). The modelling experiment showed that bSiO 2 and carbon pool degradation followed different patterns; they are represented in our model by different sets of equations. Moreover, in our in vitro experiment, external parameters like temperature were constant and can not be responsible for the relation observed in Figures 7 and8. Thus we can safely suppose that a causal correlation exists between bSiO 2 dissolution and the amino acids or lipids degradation. The turnover of the portion of these organic compounds that is correlated with dissolution of either the first or second bSiO 2 phase (P1 and P3) was very slow compared to the degradation of the remaining pool of these compounds. For example, for the amino acids, the turnover of Si(1)-THAA and Si(3)-THAA was slow compared to the loss of THAA in general. This correlation suggests that there may exist a direct association between each bSiO 2 phase and the corresponding organic compounds (Si(1)-THAA, Si(3)-THAA, Si(1)-Lip and Si(2)-Lip). Since the amounts of Si-THAA and Si-TLip related to each phase were similar (~10-30 %), differences between bSiO 2 dissolution rate constants stem mainly from the compositions of the pools. Some membrane lipids mainly MGDG were mostly associated with the first bSiO 2 phase. DPG+PG still had high concentrations at the end of P2 when most degradation occurred. The second bSiO 2 phase was more strongly correlated with neutral lipid alcohols (ST and ALC) but also with membrane lipids DPG+PG and PE. In the first bSiO 2 phase, GLU, ASP, and LEU constituted most of the Si(1)-THAA pool and this phase contains no LYS at all. In contrast in the second bSiO 2 phase, Si(3)-THAA had a composition similar to the diatom's intracellular THAA, except for an increase of the GLY composition.

It is not clear whether differences in organic carbon content and/or different associations between bSiO 2 and organic carbon in each of the two bSiO 2 phases explains the differences between bSiO 2 dissolution rates and also between solubility equilibria. The organic matter that makes up part of the diatom frustule helps strengthen the structure, thus increasing its resistance to mechanical forces like those from grazers [START_REF] Hamm | Architecture and material properties of diatom shells provide effective mechanical protection[END_REF]. The role of organic compounds in silica dissolution is, however, more difficult to determine. In addition to the bonds between silica and the OH moiety of SER or THR [START_REF] Hecky | The amino acids and Sugar Composition of Diatom Cell-Walls[END_REF], silica particles are linked to organic compounds by nitrogen bonds [START_REF] Sumper | Silica formation in diatoms: the function of long-chain polyamines and silaffins[END_REF]. Indeed, Gendron-Badou et al. (2003) noted that Si-C and Si-N bonds are present in fresh diatoms while only Si-O-Si and Si-O-R bonds are visible in fossilized diatoms. Different associations between silica and organic compounds resist degradation and dissolution differently and may explain the differences we observed between dissolution rate constants and solubility equilibria of the two bSiO 2 phases. The different dissolution rates of the two bSiO 2 phases might also be due to different physico-chemical properties in the silica structure itself. In the presence of some sillafins, silica precipitation of porous blocks has been observed in vitro; in contrast, when silica precipitation is catalyzed by polyamines, spherical silica particles are formed [START_REF] Sumper | Silica formation in diatoms: the function of long-chain polyamines and silaffins[END_REF]. If the first silica phase is more porous due to the presence of organic matter or due to the compounds that catalyzed silica formation, the dissolution rate constant of this bSiO 2 will be higher (Van Cappellen et al., 2002a). Also, when the silica structure is chemically more organized (in mineral form, as opposed to amorphous, like opal), dissolution rate and solubility are lower. Gendron-Badou et al. (2003) determined that the structure of bSiO 2 from fossilized diatoms from sediments is more organized than that of fresh diatom frustules due to condensation processes that continue after they are deposited. It is also possible that fresh diatoms already have a more organized phase, as suggested by the low dissolution rate (in the present study) and the low solubility equilibrium [START_REF] Gallinari | The importance of water column processes on the dissolution properties of biogenic silica in deep seasediments I. Solubility[END_REF] of the second bSiO 2 phase. During dissolution, the two different rate constants will cause an increase of the ratio of the more organized phase to the amorphous phase.

The difference between dissolution rate constants and between solubility equilibria could be due to chemical bonds between silica and organic matter or to structural characteristics of the bSiO 2 . In any case it may be closely linked to the presence of organic compounds either inside the frustule itself or during the silicification process. This conclusion emphasizes the need to link studies of carbon and silica production and recycling if we are to better understand both C and Si cycles. The following section will accentuate this conclusion by showing the reverse: the importance of bSiO 2 to carbon degradation.

Si-C interactions and their role on carbon degradation

bSiO 2 dissolution was best described by Model 2, while the turnover of each organic compound investigated here was best fit by Model 1 or 3 (Fig. 5). The use of Model 3 to describe compound turnover means that either (1) most organic compounds were present as two pools of matter degrading one after the other or (2) degradation rate constants increased at some point due to a change in environmental factors. In most cases the loss rate constant increased (POC, PON, THAA, PE, and MGDG) or decreased (other lipid classes) when the dissolution of the first bSiO 2 phase was almost complete, from which we conclude that the first bSiO 2 phase must have influenced loss of organic matter.

Most of the ALC, PE and ST present in the intracellular pool of organic compounds seems to have been protected by the first bSiO 2 phase, but due to the high variability of lipid class behaviour the pattern for TLip is less clear than the one for THAA. THAA degradation is consistent with the idea that Si(2)-THAA is encased within diatom frustules, and is released as soon as the first bSiO 2 phase is completely removed. While several amino acids increased in concentration between day 11 and day 20 (Fig. 6b), bacterial numbers peaked at day 13, which corresponds to the THAA maximum (Fig. 1 and Fig. 2). However, bacterial carbon accounted for only 0.2 to 2.4 ± 0.3 % of total carbon (Fig. 3). Bacterial biomass cannot account for the increase of THAA, but the increase of bacterial number could be explained by this input of labile organic carbon. [START_REF] Ingalls | The role of biominerals in the sinking flux and preservation of amino acids in the Southern Ocean along 170°W[END_REF][START_REF] Ingalls | Seasonal trends in the pigments and amino acid compositions of sinking particles in biogenic CaCO3 and SiO2 dominated regions of the Pacific sector of the Southern Ocean along 170°W[END_REF] measured Si-THAA (THAA bound and/or within bSiO 2 ) obtained after complete dissolution of the bSiO 2 using successive treatments with 6N HCl and HF. They found that Si-THAA made up 0.7-7 % of the total THAA in diatoms from plankton tows and sediment trap samples. In our study, Si-THAA was a larger portion of total THAA than in the studies of [START_REF] Ingalls | The role of biominerals in the sinking flux and preservation of amino acids in the Southern Ocean along 170°W[END_REF][START_REF] Ingalls | Seasonal trends in the pigments and amino acid compositions of sinking particles in biogenic CaCO3 and SiO2 dominated regions of the Pacific sector of the Southern Ocean along 170°W[END_REF]. We define three pools of THAA: Si(1)-THAA degradation is correlated to the dissolution of the first bSiO 2 phase; Si(2)-THAA is the pool of THAA that are enclosed between the two bSiO 2 phases. Both of these pools were protected by the first bSiO 2 phase. The third pool, Si(3)-THAA, is attached to the second phase of the frustule; due to the low dissolution rate constant of this phase, it was protected for longer time.

The composition of Si(2)-THAA is dominated by GLY and LYS, which are major components of silaffins (Table 2). As part of the silicification process [START_REF] Hildebrand | Biological processing of nanostructured silica in diatoms[END_REF][START_REF] Sumper | Silica formation in diatoms: the function of long-chain polyamines and silaffins[END_REF], these proteins are present in the silica deposition vesicles (SDV) that become part of the diatom wall at the end of frustule formation [START_REF] Martin-Jézéquel | Silicon metabolism in diatoms: implications for growth[END_REF].

Thus the Si(2)-THAA pool may be assembled during the silicification process, and may result from the integration of the SDV's into the frustule. Similarity between most of the substitution times ts listed in Table 4 and the release time of Si(2)-THAA suggests that k 2 represents the degradation rate constant of this portion of THAA. After being released, Si(2)-THAA turned over very fast (k 2 in Table 4). Most of these amino acids were completely dissolved or degraded shortly after the total dissolution of the first bSiO 2 phase, which suggests that this pool of THAA is not directly bound to bSiO 2 . The high loss rate constant of Si(2)-THAA may suggest that this pool of THAA was dissolved (chemical mechanism) rather than degraded (biological mechanism) as soon as it was exposed. Another possible explanation to this fast turn over rate is a change in degradation mechanism. During degradation, amino acids are released from protein by enzymatic cleavage at the end of the proteins (exopeptidase) or in the middle of the polypeptide chain (endopeptidase). If the proteins are opened up during the silicification process, exopeptidases could act at both ends of the protein and degradation would be faster.

Due to their high turnover rate Si(2)-THAA may have been dissolved during the strong HCl treatment or degraded before analysis in the study of [START_REF] Ingalls | The role of biominerals in the sinking flux and preservation of amino acids in the Southern Ocean along 170°W[END_REF]2006).

Accordingly, the quantification of Si-THAA made by [START_REF] Ingalls | The role of biominerals in the sinking flux and preservation of amino acids in the Southern Ocean along 170°W[END_REF] might have only targeted THAA bound to the second bSiO 2 phase of the frustule (Si(3)-THAA). The composition of Si-THAA in [START_REF] Ingalls | The role of biominerals in the sinking flux and preservation of amino acids in the Southern Ocean along 170°W[END_REF] is similar to our Si(3)-THAA except that LYS is more abundant in Si(3)-THAA and GLY slightly less abundant (Table 2). The low solubility of the second bSiO 2 phase is consistent with the increase in Si-THAA/THAA with depth in their study.

The bSiO 2 protected from degradation the organic matter that was directly associated with the frustule (Si(1)-THAA, Si(3)-THAA and Si-Lip). The first bSiO 2 phase also protected the lipids (some DPG+PG) and amino acids (Si(2)-THAA) trapped inside the frustule possibly between the 2 phases, as shown by the correlation curve (Figs. 7 and8). Moreover, the sudden increase in POC degradation rate (Fig. 1) after release of the trapped material is not associated with an increase in bacterial concentration (Figs. 2 and3) but with the end of the dissolution of the first bSiO 2 phase. It is hardly a coincidence that the end of dissolution of the first bSiO 2 phase occurred exactly when the degradation of the POC, PON and THAA increased. The mechanisms behind this observation are not clear yet; the dissolution of this phase probably gave bacteria better access to the internal carbon of the cell, possibly because the integrity of the frustule can not be maintained without the presence of the first bSiO 2 phase. This could happen through increasing pores size as sometimes shown by pictures of diatom frustules during dissolution, or because the box-shaped frustule opens at the end of the first bSiO 2 phase dissolution as observed after sexual phases [START_REF] Crawford | The role of sex in the sedimentation of a marine diatom bloom[END_REF], both triggering cell lysis. In any case we can safely conclude that the first bSiO 2 phase of the diatom frustule also protects most of the intracellular carbon; at the end of the dissolution of the first bSiO 2 phase 69% of the POC was still not degraded. Due to the very low dissolution rate of the second bSiO 2 phase, the associated organic compounds (Si(3)-THAA and Si(2)-Lip) might be protected for a long period of time; they would even be preserved in the sediment with the bSiO 2 .

The presence of organic compounds inside the frustule and/or during silicification determines the solubility of the different parts of the frustule. Moreover, intracellular carbon and Si-bound organic compounds may be protected by at least some part of the frustule. These reverse interactions prove that carbon and silica production and recycling must be studied in parallel if we want to improve our understanding of mechanisms driving both POC and bSiO 2 sedimentation. (b) Correlation between concentration of the dissolved bSiO 2 from the second phase relative to its initial concentration (estimated by the model) and each lipid class relative to its initial concentration. Period 1 is the period of time corresponding to the dissolution of 85% of the first bSiO 2 phase and 10% of the second bSiO 2 phase. During period 2, the last 15% of the first bSiO 2 dissolved, and 10% more of the second bSiO 2 phase dissolved. In Period 3 only the second bSiO 2 phase dissolved as less than 1.5% of the first bSiO 2 phase remained. 4: Kinetic parameters and likelihood (log(L)) calculated by the 3 models. C 0 is the initial 924 concentration of the compound. C 1 and C 2 are the initial concentrations of the two phases (for 925 bSiO 2 ) or the two pools (organic compounds). k is the degradation/dissolution rate constant 926 calculated with Model 1. k 1 and k 2 are degradation/dissolution rate constants of C 1 and C 2 in 927 Model 2, respectively, or used before and after the substitution time ts in Model 3, respectively.

928

The last column indicates which model has been chosen in this study to determine the 929 degradation/dissolution rate constant and the initial concentration of each compound. For 930 compounds, see abbreviations table (Table 1

  2 , POC, TLip and THAA concentrations over time are shown in logarithmic scale in Fig.1. While bSiO 2 concentrations decreased smoothly over the first 25 d, POC, PON and THAA concentrations decreased until about day 14, when the loss rate increased, especially for THAA. In contrast, TLip concentration decreased rapidly at the beginning of the experiment and reached a plateau after day 13. bacterial growth efficiency (bacterial carbon increase divided by POC decrease)

  Si/POC decreased from 0.09 ± 0.01 mol of Si/mol of C to 0.06 ± 0.01 mol of Si/mol of C during the first 2 days of incubation and then stabilized until day 15 of the experiment. After increasing to 0.11 ± 0.01 mol of Si/mol of C between days 15 and 21, the Si/POC ratio remained constant until the end of the experiment. TLip/POC varied between 0.13 ± 0.02 mol of C/mol of C and 0.23 ± 0.03 mol of C/mol of C during the first 50 days. Then the ratio decreased to a final value of 0.06 ± 0.01 mol of C/mol of C at day 102. THAA/POC decreased regularly during the whole experiment from 0.36 ± 0.09 mol of C/mol of C initially to 0.10 ± 0.02 mol of C/mol of C after 102 days, except for a sudden increase between day 11 and 15 from 0.28 ± 0.7 mol of C/mol of C to 0.38 ± 0.10 mol of C/mol of C.Most of the change in TLip composition (Fig.4a) occurred between days 0 and 25. Most compounds decreased or remained the same relative to TLip (mol of C/mol of C) except for PIG, which increased from 41 ± 5% to 80 ± 7% of the TLip over the course of the experiment.Relative concentrations (mol of C/mol of C) of FFA, the second most abundant lipid class in the algae, decreased regularly from 24.8 ± 0.5% to 4.0 ± 0.4%. MGDG initially made up 13 ± 1% of TLip, but totally disappeared by day 4. The MG contribution was constant (7.0 ± 0.3%) until day 14, when it was completely degraded. The contribution of membrane lipids, the glycolipid MGDG and the phospholipids (PE and DPG+PG) to TLip was low compared to results from[START_REF] Berge | Reassessment of lipid composition of the diatom, Skeletonema costatum[END_REF][START_REF] Tucci | The role of complex lipids in the synthesis of bioactive aldehydes of the marine diatom Skeletonema costatum[END_REF]. However, lipid composition is highly dependent on culture conditions[START_REF] Tucci | The role of complex lipids in the synthesis of bioactive aldehydes of the marine diatom Skeletonema costatum[END_REF], and in our case the high FFA content probably masked the relative contribution from membrane lipids.

  . bSiO 2 was the only constituent of the diatom with a dissolution pattern that was best described by Model 2 (Fig.5a, Table4) meaning that the frustule is most likely composed of two phases dissolving simultaneously. The first phase of bSiO 2 constituted 31% of the total bSiO 2 and was more soluble, with a dissolution rate constant of 0

.

  The three dissolution constants are within the range (0the review byVan Cappellen et al. (2002b).3.2.2 POC and PON kineticsPOC concentration decreased in two steps from the initial value of 7660 ± 150 µmol L -1 (Fig.1). Even with more parameters Model 2 did not improve the fit to the data obtained by Model 1 (Fig.5b); log(L) calculations for POC loss showed that Model 3 gave the best fit ( ) log( L ∆ = 76.5). This suggests that either two pools of POC exist and are degraded successively, or a change in some parameter not directly linked to POC chemistry provoked an increase of the degradation rate at day 10 from 0.025 to 0.082 1 d

From(,

  the initial THAA concentration of 3020 ± 200 µmol C L -1 , 86 ± 17 % of the THAA were degraded after 25 days; 5.0 ± 0.5 % of the THAA still remained after 102 d. As for POC and PON, Model 3 was the best fit for THAA degradation ( ) log( L ∆ = 9.9 with both Model 1 and Model 2). Concentrations of THAA decreased from day 1 to day 13 with an average degradation rate constant of 0.054 1 d - . After 13 d THAA turned over with a faster degradation rate constant of Table4), before reaching a period of very low rate constants after day 25; THAA concentrations were almost constant until day 102. This last rate was not calculated by models as the modelling exercise was applied only over the first 25 days. The first degradation phase of THAA was similar to that measured on T. weissflogii (0except for ASP and SER, which turned over more slowly with constants of 0.001 and 0.007 1 d -

  Except for TYR, amino acids turned over faster during the second degradation phase, and degradation rate constants ranged between 0.110 and 0

  Of the individual classes, PE, ALC concentrations remained almost constant during P1.In contrast, MGDG was completely degraded within the first 4 days, in P1. Despite the high variability in PE and ST concentration measurements, we determined that ST and MG concentrations decreased only slightly in P1 (>27%). This trend is illustrated by their low degradation constants (0

Fig. 1 .

 1 Fig. 1. Changes in the relative concentrations of POC (closed black diamonds), bSiO 2

Fig. 2 .

 2 Fig. 2. Change in total bacterial concentration over time during the 102-day degradation

Fig. 4 .

 4 Fig. 4. Change in the concentration of (a) 6 of the 8 lipid classes in µmol C L

Fig. 6 .

 6 Fig. 6. Change in organic compound concentrations with time during the degradation of S.

Fig. 8 .

 8 Fig. 8. Si-THAA interactions during the degradation of S. marinoi. (a) Correlation

  Fig.2

  This pattern does not fit any of the models used, and suggests an association of these lipids only with the first bSiO 2 phase, or no association at all.

		(Table 4). PON followed the Using Model 1 we calculated that FFA, PIG, MG and PG+DPG had degradation rate
	same pattern; Model 3 reproduced the data with more accuracy as shown by the constants of 0.104, 0.012, 0.045 and 0.011 1 d -over 25 days respectively. For MGDG, ST, PE, ) log( L ∆ of 37.3
	compare to Models 1 and 2. Model 3 estimated an increase in PON degradation rate at day 12 and ALC, Model 3 gives the best fit to the data (Table 4).
	from 0.03 to 0.094 MGDG turned over slowly (0.078 1 d -(Table 4). The first POC degradation rate constants are similar to rate 1 d -) during the first 2 days, but then much more
	constants measured in previous studies (0.036 quickly (0.52 1 d -; Table 4) and were completely gone after only 4 days. MG were also 1 d -for POC, Lee and Fisher, 1992; 0.035	1 d -	for
	POC and 0.047 completely lost very quickly; the initial degradation rate constant of MG was 0.045 1 d -for PON, Harvey et al., 1995). For comparison with bSiO 2 , we also applied 1 d -, but the
	Model 1 over 10 days to calculate the initial loss rate of POC and PON: 0.025 remaining MG was gone after 14 days.	1 d -	for POC and
	0.029	1 d -	for PON.
		The POC degradation pattern in the Hg-poisoned controls was similar to that in
	unpoisoned flasks during the first 5 days but was lower between days 5 and 11. The degradation
	rate constant measured over the first 11 days using Model 1 was 0.021	1 d -	.
	3.2.3 Lipid kinetics
		From an initial TLip concentration of 1400 ± 70 µmol C L	-1 , almost half (42 ± 4%)
	degraded in 25 days; 7.0 ± 0.3 % of TLip remained after 102 days. The degradation of 7 of the 8
	lipid classes is shown in Fig. 6a. TLip degradation is better described by Model 2 and 3 than by
	Model 1 (	∆	log( L	)	= 15.6 and 17 respectively). With only 1.5 point of log(L) difference between
	Model 2 and 3 but the same degree of complexity (4 parameters each) we chose the best fit from
	the best likelihood which was given by Model 3 (Table 4). The degradation rate constant for
	TLip was 0.048	1 d -	during the first 17 days of the experiment and then decreased to 0.01	1 d -	.
	The initial degradation rate constant was 0.046	1 d -	, slightly higher than the 0.023	1 d -	measured
	in the study of Harvey et al. (1995).

- MGDG, ST, and PE degradation rate constants increased by a factor of 8 to 10 during the experiment. They followed the same pattern as POC and PON. ALC degradation rate constant decreased after 19 days.

Table 1 :

 1 List of abbreviations used in the text to refer to organic and inorganic compounds measured during the degradation experiment.

	Biogenic Silica	bSiO 2	Total Organic Carbon	TOC
	Silicic acid	dSi	Particulate organic carbon	POC
	Particulate organic nitrogen	PON	Dissolved Organic carbon	DOC
	Total Lipid classes	TLip	Total Hydrolyzed Amino Acids THAA
	Alcohols	ALC	Alanine	ALA
	Di-and monophosphatidyl	DPG+PG	Arginine	ARG
	glycerides		Aspartic acid	ASP
	Free fatty acids	FFA	Glutamic acid	GLU
	Monogalactosyldiglycerides	MGDG	Glycine	GLY
	Monoglycerides	MG	Histidine	HIS
	Phosphatidylethanolamines	PE	Isoleucine	ILE
	Pigments	PIG	Leucine	LEU
	Sterols	ST	Lysine	LYS
			Methionine	MET
			Phenylalanine	PHE
			Serine	SER
			Threonine	THR
			Tyrosine	TYR
			Valine	VAL
			γ-Aminobutyric acid	GABA

Table 2 :

 2 Concentration in µmol C L -1and composition in mole% of the different pools of THAA in S. marinoi. The THAA row shows the initial concentration and composition of THAA before dissolution began and does not include Si-THAA. Si(1)-THAA is the pool associated with the first bSiO 2 phase, Si(2)-THAA is the pool of THAA enclosed between the bSiO 2 phases and Si(3)-THAA is the pool associated with the second bSiO 2 phase.

	THAA	ALA ARG ASP GLU GLY HIS ILE LEU LYS PHE SER THR TYR VAL TOT
	THAA	105 223 318 379 139 59 174 317 187 260 128 136 170 174 2769
	% THAA / THAAtot	4% 8% 11% 14% 5% 2% 6% 11% 7% 9% 5% 5% 6% 6%
	Si(1)-THAA	20 31 122 143 12 12 48 92	0	63 16 29 58 45 691
	% Si(1)-THAA/ Si(1)-THAAtot 3% 5% 19% 22% 2% 2% 7% 14% 0% 10% 2% 5% 9% 7%
	Si(2)-THAA	9	0	52 37 92 17 21 19 96 21	0	12 18 21 332
	% Si(2)-THAA/ Si(2)-THAAtot 2% 0% 13% 9% 23% 4% 5% 5% 24% 5% 0% 3% 5% 5%
	Si(3)-THAA	20 28 51 64 72 20 26 43 53 35 29 30 26 26 523
	% Si(3)-THAA/ Si(3)-THAAtot 4% 5% 10% 12% 14% 4% 5% 8% 10% 7% 5% 6% 5% 5%

Table 3 :

 3 Concentration in µmol C L -1 and composition in mole% of the different lipid class in S.marinoi. The lipid row shows the initial concentration and composition of lipid before dissolution began and does not include Si-lipid. Si(1)-Lip is the pool associated with the first bSiO 2 phase, Si(2)-Lip is the pool of THAA associated with the second bSiO 2 phase.

	Lipid class	ALC DPG+PG	FFA	MG	MGDG	PE	PIG	ST	total
	Lipids	30	98	366	104	189	44	604	40	1475
	lipid class/ total lipid	2%	7%	25%	7%	13%	3%	41%	3%
	Si(1)-Lip	0	0-36	180-201	15-25	0	1-19	NC	1-11	386-469
	Si(1)-Lip/ tot Si(1)-Lip	0%	0-8%	43-47%	4-5%	41-49%	0-4%		0-2%
	Si(2)-Lip	0-4	40-69	3	0	0	7-13	NC	9-20	125-175
	Si(2)-Lip/ tot Si(2)-Lip NC: No correlation	0-2%	32-39%	39-55%	0%	0%	6-7%		7-11%

Table

  .04798.7 6884 1412 0.047 0.047 98.7 7614 10 0.025 0.082 174.7 III bSiO 2 591 0.030 70.7 209 462 0.268 0.016 109.0 658 6 0.063 0.019 97.7 II TLip 1232 0.033 27.9 704 724 0.014 0.100 43.5 1420 17 0.048 0.010 44.9 III

	933	Fig. 1
		0 ,
		t /POC
	931	Ln ( bSiO 2,t /bSiO 2,0 , POC THAA t /THAA 0 , TLip						).
		Model 1 C 0 k	Model 2 log(L) C 1 C 2 k 1	k 2	Model 3 log(L) C 0 ts k 1	k 2	log(L)	Best Model fit
	PON	1499 0.050 98.5 26	1473 0.051 0.051 98.5 1364 12 0.030 0.094 135.6 III
	POC 8297 0ALC 44 0.080 9.2	46	5	0.122 0.001 10.1 52	19 0.099 0.001 13.5 III
	FFA	297 0.104 21.8 139 207 0.068 0.214 23.1 330	15 0.125 0.077 25.0 I
	MG	97	0.045 24.5 21	85	0.497 0.033 25.0 107	5 0.094 0.036 25.5 I
	MGDG 199 0.145 9.0	93	107 0.145 0.145 9.0	189	2 0.078 0.520 19.6 III
	PE	54	0.097 22.3 51	3	0.097 0.097 22.3 42	6 0.016 0.119 26.6 III
	PG+DPG 69	0.011 17.9 55	13	0.011 0.011 17.9 65	16 0.001 0.054 19.0 I
	PIG	641 0.012 29.7 32	610 0.012 0.012 29.7 627	5 0.000 0.016 30.4 I
	ST	41	0.031 30.0 11	30	0.031 0.031 30.0 35	13 0.001 0.080 38.3 III

t /TLip

Acknowledgements

We are grateful to Annick Masson for her technical assistance with POC analyses. Thanks to everyone in the LMGEM for their kindness and help during the experimental work. This work was funded by the EU, partly through the ORFOIS (EVK2-CT2001-00100) project and partly through the program Marie Curie, project CARBALIS (MOIF- CT-2006-022278). This is contribution # 1081 of the IUEM and xxx of Stony Brook University. Support was also provided by the MedFlux program of the U.S. NSF Chemical Oceanography division, and this is MedFlux contribution No. XXX.