André Helena Junqueira

Pierre Schroder
email: schroder@unistra.fr

Fabrice Thalmann

Andrey Klymchenko

Yves Mély

Mauricio S Baptista

Carlos M Marques

André P Schroder

Molecular organization in hydroperoxidized POPC bilayers

Keywords: phospholipid hydroperoxidation, bilayer structure, hydroperoxide localization, hydroxyflavone probes, MARTINI simulations

niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Lipid oxidation occurs during mitochondrial respiration and inflammation, and in several other cellular processes, [START_REF] Ames | Oxidants, antioxidants, and the degenerative diseases of aging[END_REF][START_REF] Halliwell | Free radicals in biology and medicine[END_REF][START_REF] Crockett | The cold but not hard fats in ectotherms: consequences of lipid restructuring on susceptibility of biological membranes to peroxidation, a review[END_REF] it is also the unavoidable consequence of metabolic activity under light. [START_REF] Sies | Biochemistry of oxidative stress[END_REF][START_REF] Stratton | Determination of singlet oxygen-specific versus radical-mediated lipid peroxidation in photosensitized oxidation of lipid bilayers: effect of β-Carotene and α-Tocopherol[END_REF][START_REF] Pratt | Theoretical calculations of carbon-oxygen bond dissociation enthalpies of peroxyl radicals formed in the autoxidation of lipids[END_REF] Although a controlled amount of oxidized lipids is required for proper cell signaling, cell maturation and differentiation, and for cell apoptosis, the products of lipid oxidation, if uncontrolled, can have a deleterious effect on the functioning of the cell. Indeed, lipid oxidation products are known to be involved in a variety of neurodegenerative diseases including Parkinson's and Alzheimer's, hypertension and cancer. [START_REF] Deigner | Oxidized phospholipids: emerging lipid mediators in pathophysiology[END_REF][START_REF] Sohal | Oxidative stress, caloric restriction, and aging[END_REF] Hydroperoxides are the primary products of lipid peroxidation, which then in vivo serve as substrates for enzymes such as peroxidases and phospholipases, undergoing several secondary reactions. [START_REF] Niki | Lipid peroxidation: mechanisms, inhibition, and biological effects[END_REF] The last decade has seen an increased interest in the effect of lipid hydroperoxidation on the properties of phospholipid membranes. At the molecular level, numerical simulations predicted that insertion of the -OOH groups changes the statistical distribution of phospholipid conformations, leading noticeably to an increase of the area per lipid. [START_REF] Wong-Ekkabut | Effect of lipid peroxidation on the properties of lipid bilayers: a molecular dynamics study[END_REF][START_REF] Guo | Peroxidised phospholipid bilayers: insight from coarsegrained molecular dynamics simulations[END_REF] Experimentally, oxidation under conditions where hydroperoxides are formed showed consistently an increase in the area per lipid. [START_REF] Caetano | Marques, Photo-Induced Destruction of Giant Vesicles in Methylene Blue Solutions[END_REF][START_REF] Mertins | Physical damage on giant vesicles membrane as a result of methylene blue photoirradiation[END_REF][START_REF] Riske | Giant vesicles under oxidative stress induced by a membrane-anchored photosensitizer[END_REF][START_REF] Heuvingh | Asymmetric oxidation of giant vesicles triggers curvature-associated shape transition and permeabilization[END_REF][START_REF] Mojzisova | Photosensitizing properties of chlorins in solution and in membrane-mimicking systems[END_REF][START_REF] Kerdous | Photo-dynamic induction of oxidative stress within cholesterol-containing membranes: Shape transitions and permeabilization[END_REF][START_REF] Sankhagowit | The dynamics of giant unilamellar vesicle oxidation probed by morphological transitions[END_REF][START_REF] Weber | Lipid oxidation induces structural changes in biomimetic membranes[END_REF][START_REF] Aoki | Bioadhesive giant vesicles for monitoring hydroperoxidation in lipid membranes[END_REF] Using for instance a specific Chlorin-derived amphiphilic probe, the in-situ interaction of singlet oxygen 1 O2 with model membranes of the unsaturated lipids POPC or DOPC (1,2-dioleoyl-sn-glycero-3-phosphocholine) has been studied. [START_REF] Weber | Lipid oxidation induces structural changes in biomimetic membranes[END_REF] Under these conditions the membrane integrity was preserved allowing to measure the area increase associated with the hydroperoxidation of DOPC and POPC bilayers, as well as the reduction of the stretching modulus of partially or totally hydroperoxidized membranes. [START_REF] Weber | Lipid oxidation induces structural changes in biomimetic membranes[END_REF] These results point to possible dramatic changes of the inner structure of the membrane, and in particular to strong changes in polarity, which would have a significant impact on the insertion of membrane proteins or on the interactions with membrane active peptides.

The actual polarity at a given membrane depth, which reflects the local dielectric constant across the direction normal to the bilayer, can be measured using solvatochromic membrane probes. [START_REF] Demchenko | Monitoring biophysical properties of lipid membranes by environment-sensitive fluorescent probes[END_REF][START_REF] Klymchenko | Solvatochromic and fluorogenic dyes as environment-sensitive probes: design and biological applications[END_REF] Particularly interesting in this respect are membrane probes based on 3-hydroxyflavone (3HF). [START_REF] Klymchenko | Hydroxychromone Probes Precisely Located and Oriented in Lipid Bilayers: A Toolkit for Biomembrane Research[END_REF] Due to excited state intramolecular proton transfer (ESIPT), they exhibit dual emission highly sensitive to the micro-environment. [START_REF] Klymchenko | Hydroxychromone Probes Precisely Located and Oriented in Lipid Bilayers: A Toolkit for Biomembrane Research[END_REF][START_REF] Klymchenko | Multiparametric probing of intermolecular interactions with fluorescent dye exhibiting excited state intramolecular proton transfer[END_REF][START_REF] Demchenko | Excited-state proton coupled charge transfer modulated by molecular structure and media polarization[END_REF] Moreover, these dyes can be precisely located at different depths in lipid membranes [START_REF] Klymchenko | Novel two-band ratiometric fluorescence probes with different location and orientation in phospholipid membranes[END_REF] and they can simultaneously report about polarity as well as hydration (distribution of water across the direction normal to the bilayer). [START_REF] Klymchenko | Simultaneous probing of hydration and polarity of lipid bilayers with 3-hydroxyflavone fluorescent dyes[END_REF] Important examples are the probes used in this study, F2N12S, [START_REF] Shynkar | Fluorescent biomembrane probe for ratiometric detection of apoptosis[END_REF] F66, [START_REF] Darwich | Rational design of fluorescent membrane probes for apoptosis based on 3-hydroxyflavone[END_REF] and PPZ8 [START_REF] Shynkar | Two-color fluorescent probes for imaging the dipole potential of cell plasma membranes[END_REF] (Fig. 1) that bear zwitterion groups and alkyl chains, which ensures high affinity to lipid and cell membranes and increased sensitivity to their biophysical properties.

In the present work we use F2N12S, F66 and PPZ8 to study membrane polarity at different depths of fully or partially hydroperoxidized POPC bilayers, and coarse-grained Martini numerical simulations to build average z-distributions of the -OOH group in the corresponding membranes.

Our results show that the hydroperoxide group migrates preferentially to the bilayer interface but also populates significantly the inner membrane region for membrane compositions with more than 50% of hydroperoxidized lipid content.

Figure 1: Chemical structures of the three 3-hydroxyflavone (3HF) probes (F2N12S, F66, and PPZ8) and their expected location with respect to lipids in membranes.

Materials and methods

Materials

POPC (1-palmitoyl-2-oleoyl-sn-glycero-phosphocholine) was purchased from Avanti Polar Lipids (Alabaster, AL, USA) as a powder. Two POPC in chloroform solutions were prepared; one, of 10 mg/mL concentration, was used for liposome fabrication. The second, of 16 mg/mL concentration, was used for HP-POPC fabrication. Both solutions were stored at -22°C. All solvents were HPLC grade, and were purchased from Sigma-Aldrich (St. Louis, MO, USA). Methylene blue (MB) was purchased from Synth (Diadema, Sao Paulo, Brazil) in the powder form, and diluted in methanol to a final 0.3 mM concentration. The fluorescent membrane probes F2N12S, F66, and PPZ8 were synthesized as described elsewhere. [START_REF] Shynkar | Fluorescent biomembrane probe for ratiometric detection of apoptosis[END_REF][START_REF] Darwich | Rational design of fluorescent membrane probes for apoptosis based on 3-hydroxyflavone[END_REF][START_REF] Shynkar | Two-color fluorescent probes for imaging the dipole potential of cell plasma membranes[END_REF] Their chemical structures are presented in Figure 1.

Lipid oxidation procedure

Hydroperoxidized POPC (HP-POPC) was produced as following: first, 80 mg of POPC were dissolved in 5 mL of chloroform, a solution to which was added 1 mL of a 0.3 mM MB in methanol solution, leading to a final mixture of 17.5 mM of POPC and 50 µM of MB. This solution was kept in a balloon, under constant stirring and refrigeration using an ice bath, while it was irradiated during 8 h using a tungsten lamp (500 W). Then the solvents were rotoevaporated. Finally 1 mL of methanol was added to the dry residue, and the whole was agitated until its complete dissolution. The solutes of this methanol solution were separated and analyzed with a HPLC-MS (Shimadzu, Kyoto, Japan) system consisting of a shim-pack prep ODS column (150 x 4.6 mm, 5 mm), coupled to an Esquire ESI-MS spectrometer. The product that was characterized as POPC hydroperoxide (HP-POPC) had an elution time of 7 min in a 1 mL/min flux and a measured mass of m/z 792.7. After elution, the HP-POPC solution was evaporated, re-dissolved in chloroform to a final concentration of 10 mg/mL, and stored at -22°C.

Liposome fabrication

Large unilamellar vesicles (LUVs) of POPC, HP-POPC, or of mixtures of both were prepared by the extrusion method. We prepared and studied LUVs made of the following relative POPC/HP-POPC concentrations: 1/0 (pure POPC), 1/1, 3/7, and 0/1 (pure HP-POPC). For that pur-pose, we first mixed (when necessary) the appropriate quantities of POPC and HP-POPC chloroform solutions. The mixture was spread in a small flask, and the solvent was evaporated under constant nitrogen flux. Milli-Q water was then added to the dry residue, so to obtain a 200 µM lipid suspension. The mixture was gently agitated until the whole residue dispersed in water. This suspension was then extruded 21 times (Avanti Lipids micro extruder) through a 0.1 µm filter, obtaining a transparent LUVs suspension. Adding one fluorescent probe (see Fig. 1) to a LUV suspension was achieved by adding the right volume of a 0.3 mM probe-in-DMSO solution, so to reach an overall 0.5 µM concentration of the probe (this corresponded for example to the addition of 1.6 µL of the probe-in-DMSO solution into 1 mL of a 200 µM LUV suspension), corresponding to a probe/ lipid molar ratio of 0.25%. Addition of a probe was always done just prior to the measurements, as explained below.

GUV fabrication

Giant unilamellar vesicles (GUVs) of pure POPC or of pure HP-POPC were prepared by the electroformation method. [START_REF] Angelova | Liposome electroformation, Faraday Discuss[END_REF] Briefly, 5 µL of a 1 mg/mL lipid/chloroform solution were spread onto the conductive side of an ITO covered glass slide (PGO, Germany), forming a lipid stack after the solvent has been evaporated (30 minutes under primary vacuum). Then an electroformation chamber was built by joining this slide, a 1 mm thick teflon spacer, and a second ITO covered slide, the two conductive sides facing each other. The cell was then filled with a 100 mOsm sucrose/water solution, and an electric alternate field was applied to the cell during 2 hours (1 V, 10 Hz). Finally, the GUVs were extracted from the growing cell and dispersed into a glucose-containing microtube (Eppendorf, Germany) for further use (approximate dilution 1/1). Sucrose and glucose solutions were osmotically matched (100 mOsm), using a cryoscopic osmometer (Osmomat 030, Gonotec, Germany). Thanks to a difference in density, the sucrose-containing GUVs sedimented rapidly in their environing glucose-sucrose solution, facilitating their further use and observation. It is worth to note that, contrary to the case of LUVs (see above), the phospholipid quantity present in a GUV suspension is not known, since part of the initial lipid remains attached to the ITO glass surface.

Just before their observation, a DMSO solution containing a flavone-based probe was added to the GUV suspension assuming that 20% of the lipids initially present in the growing chamber have been collected, with the aim of reaching a final probe/lipid molar fraction of 0.25%. The GUV suspension was then transferred into an observation chamber, and observed under the spectral imag-ing confocal Nikon microscope (see below). Since the real probe/lipid fraction could not be controlled precisely, no quantitative measurements of fluorescence intensity were done on GUVs.

Spectral imaging was therefore performed with the purpose of checking the effectiveness of probe insertion in the bilayers and of qualitatively comparing with fluorescence analysis on LUVs.

Spectral imaging confocal microscopy

We used a TE2000 inverted microscope, equipped with a 100x oil-immersion objective, and a C1 confocal scanning head connected to a 32-channel Spectral Imaging C1-si System (Nikon, Japan). The device enabled us to create in a single scan of the laser a 32 channels spectral image of the sample. We acquired sets of 32 images of flavone-based probe-containing GUVs in the range 435-745 nm (i.e. with 10 nm broad channels). Excitation wavelength was set at 408 nm. Figure 2 shows spectra of pure POPC GUVs and pure HP-POPC GUVs labeled with the F66 probe, each spectrum being the average over ten GUVs. ImageJ software (https://imagej.nih.gov/ij/) was first used to integrate the light intensity along each GUV perimeter and then used to extract the GUV spectrum. Inset in Fig. 2 shows typical F66-containing GUVs (here made of HP-POPC). Please note that we never observed any sign of in situ oxidation during fluorescence imaging, something that can eventually take place with some fluorescent probes, as for example rhodamine-and NBD-based probes. [START_REF] Ayuyan | Lipid Peroxides Promote Large Rafts: Effects of Excitation of Probes in Fluorescence Microscopy and Electrochemical Reactions during Vesicle Formation[END_REF][START_REF] Zhao | Phase studies of model biomembranes: Macroscopic coexistence of Lα+Lβ, with light-induced coexistence of Lα+Lo Phases[END_REF] Figure 2: Normalized fluorescence spectra of giant unilamellar vesicles incorporating the F66 probe. Averaged spectra of ten pure, 100% POPC, and of ten pure, 100% HP-POPC GUVs. The curves are normalized to their T* pick value. Inset: a typical fluorescence image, here obtained as the sum of the 32 images measured by the 32-channels of the C1-si spectral microscope (HP-POPC GUVs are shown here).

Fluorescence spectra of LUVs, acquisition and analysis

Adding one of our 3-hydroxyflavone probes in a LUV suspension (see above) was done directly in a dedicated, 1-cm path length quartz cuvette (HELLMA, Müllheim, Germany). After probe addition, the cuvette was gently agitated. Then, fluorescence spectra were immediately recorded on an Agilent Cary Eclipse Fluorescence Spectrophotometer (USA), with an excitation wavelength of 408 nm. All experiments were performed at room temperature. A typical fluorescence spectrum is given in Figure 3. Deconvolution of the spectra into three bands (N*, H-N* and T*) was done with a homemade program developed in python (https://www.python.org/). The program is based on an iterative nonlinear least-squares method, that is itself based on the Fletcher-Powell algorithm, following a procedure already reported. [START_REF] Siano | Band shapes of the electronic spectra of complex molecules[END_REF] The individual emission bands were approximated by a lognormal function that accounts for several parameters (maximal amplitude, Imax, spectral maximum position, λmax, and positions of half-maximum amplitudes, λ1 and λ2, for the blue and red parts of the band, respectively). The program operates with the shape parameters of a log-normal function, such as the full width at the half-maximum, FWHM (λ1 -λ2), and band asymmetry, P = (λ1 -λmax)/ (λmax -λ2), and allows approximating the asymmetric bands in absorption and fluorescence spectra.

To obtain more stable results for the deconvolution, several parameters were fixed based on previous data in organic solvents and LUVs. [START_REF] Klymchenko | Bimodal distribution and fluorescence response of environment-sensitive probes in lipid bilayers[END_REF] Thus, the FWHM of the two short-wavelength bands (N* and H-N*) were fixed at 3000 cm -1 . For the H-N* band, the asymmetry was fixed at 0.9, whereas the band position was fixed at 18,400 cm -1 . The other parameters, i.e., asymmetry of N* and T* bands, width of the T* band and relative intensities of the bands, were allowed to vary. An example of deconvolution is presented in Figure 3 [START_REF] Klymchenko | Simultaneous probing of hydration and polarity of lipid bilayers with 3-hydroxyflavone fluorescent dyes[END_REF] As a matter of fact, HYD parameter is related to free water molecules available for H-bonding with the probe, the H-N* form of the probe being located shallow in the glycerol ester region of the bilayer, reflecting the membrane hydration. [START_REF] Klymchenko | Simultaneous probing of hydration and polarity of lipid bilayers with 3-hydroxyflavone fluorescent dyes[END_REF] On the contrary, N* and T* correspond to a deeply inserted form of the probe, the POL parameter being related to dipoles present in the inner membrane environment, including both free and bound water, and carbonyl or hydroperoxide (-OOH) groups. [START_REF] Klymchenko | Simultaneous probing of hydration and polarity of lipid bilayers with 3-hydroxyflavone fluorescent dyes[END_REF][START_REF] Klymchenko | Bimodal distribution and fluorescence response of environment-sensitive probes in lipid bilayers[END_REF]

Fluorescence lifetime

A Time-resolved Confocal Fluorescence Microscope (Olympus IX71) with Unique Single Molecule Sensitivity (Picoquant, Microtime 200, PicoQuant, Berlin, Germany) equipped with a FLIM system (pulsed laser diode LDH 405, operating at 405 nm, with a pulse width < 64 ps, frequency 80 MHz) and with a 60x water immersion objective was used (UPlanSApo, water immersion, WD = 0.28 mm). Fluorescence was directed through a 50 µm pinhole and detected with a single-photon avalanche diode (SPAD, SPCM-AQR-13, PerkinElmer, Waltham, USA), after passing through a 580/70-BP filter (corresponding to the wavelength range 545..615 nm). Time-resolved records were made in single-photon counting mode using the TimeHarp 260 PICO platform (Pico-Quant, Berlin, Germany), resolution < 25 ps. Experiments were done on LUV suspensions prepared as described above. Briefly, a 50 µL droplet of a 3HF-labelled LUV suspension was dropped in an observation chamber made of a coverslip, a 1 mm thick silicon spacer, and a top glass slide. Image acquisition was done using the SymPhoTime64 software version 2.1.3813. Thanks to the small (100 nm) size of LUVs, the FLIM images showed an equally distributed fluorescence over the whole observation field. The lifetimes were thus calculated by averaging over the whole observation field.

Numerical simulations

We performed molecular dynamics simulations of a bilayer comprising POPC and hydroperoxidized HP-POPC. We use the Martini Coarse-Grained model, for which a model of POPC is available [START_REF] Marrink | The MARTINI force field: coarse grained model for biomolecular simulations[END_REF] and a recently introduced coarse-grained (CG) model of hydroperoxide described in reference. [START_REF] Guo | Peroxidised phospholipid bilayers: insight from coarsegrained molecular dynamics simulations[END_REF] Both coarse-grained molecules are shown in Fig. 4, while details regarding the coarsegraining procedure can be found in. [START_REF] Marrink | The MARTINI force field: coarse grained model for biomolecular simulations[END_REF] We briefly list here the chemical nature of the beads appearing in Fig. 4. For POPC: bead 1 choline, 2 phosphate, 3 and 4 glycerol and ester groups, 5-8, 9-10, 12-13 butane like tail components, 11 cis-butene group with 120° bending angle. For HP-POPC: same groups except but 11 trans-butene, and 11p hydroperoxide OOH. Martini-like coarse graining does not distinguish between 2n and 2n+2 carbons in the aliphatic chains. As emphasized in, [START_REF] Guo | Peroxidised phospholipid bilayers: insight from coarsegrained molecular dynamics simulations[END_REF] peroxidation reactions create a mixture of compounds with hydroperoxide groups added either above or below the oleoyl insaturated bonds. Our model aims at representing both species as one. [START_REF] Guo | Peroxidised phospholipid bilayers: insight from coarsegrained molecular dynamics simulations[END_REF] we used a larger number of water molecules, i.e. 4272 water beads corresponding to 8.25 water beads (or 33 water molecules) per lipid in this coarse-graining scheme. As a matter of fact it was realized since [START_REF] Guo | Peroxidised phospholipid bilayers: insight from coarsegrained molecular dynamics simulations[END_REF] that hydroperoxidized lipid bilayers require more water to be fully hydrated than usual bilayers.

An integration step of 40 fs was used, along with a Parinello-Rahman semi-isotropic barostat and velocity-rescale thermostat, as provided by the molecular dynamics engine Gromacs, version 4.6.2. Lipid parameter files were martini_v2.1.itp, and martini_v2.0_lipids.itp. A total of 4 x 10 7 steps corresponding to 0.16 µs of CG simulation time was used to compute the density distribution of the bead 12, representative of the hydroperoxide groups in our model (Fig. 4). Frames were recorded every 1000 steps, out of which a density profile was calculated with the Gromacs tool g_density. Each trajectory was split into 4 parts. For each part (10 7 steps), the bilayer center was estimated and shifted in order to obtain histograms exactly centered around z=0, where z represents the axis perpendicular to the membrane mid-plane. This is because a slight drift of the bilayer along the z direction may occur as a result of spontaneous random crossing events of water beads, facilitated by hydroperoxidation. A total of 50 bins was used for the z-distribution in each histogram. Partitioning of the hydroperoxide groups between core and interface was derived from the above histograms, with the core region arbitrarily defined by the geometrical condition |z| < zc= 0.8 nm. The interface corresponds in our model to the region characterized by zc < |z| < zi= 2.5 nm.

The deuterium order parameter, , is a measure for the order of the lipid tails in the bilayer. [START_REF] Van Der Paal | Effect of lipid peroxidation on membrane permeability of cancer and normal cells subjected to oxidative stress[END_REF] is itself defined from the order parameter of an individual C-D bond :

(

being the angle between the n-th C-D (or C-H) bond and the normal to the bilayer, the z-axis.

Thus defined, ranges between -1/2 (segments lying in the xy plane) and 1/4 (segments parallel to z). Such definition can be extended to the molecular representation in a CG method. First, consider that, if one excepts terminal methyl (-CH3) groups, the CnH bond orientation associated with any 3 consecutive carbon atoms Cn-1,Cn,Cn+1 along a chain can be related to the segment orientation Cn-1Cn+1. As coarse-grained models do not explicitly feature hydrogen atoms and cluster together many carbon atoms into one bead, we take the bead segments Bn-1Bn+1 as representative of the car-

S CD S CD S CD,n S CD,n = 1 2 ( 3 ⟨cos 2 ( θ CD,n) ⟩ -1 ) θ CD,n S CD,n
bon-carbon segments (C-C), with Bn the bead number n according to Fig. 4. Denoting the angle between the segment Bn-1Bn+1 and the bilayer normal z, an index dependent order parameter can be defined similarly to eq.( 1) :

(

Thus defined, ranges between 1 (segments lying in the xy plane) and -1/2 (segments parallel to z). One thus gets the relation :

. Similarly to , a global order parameter for a given POPC:HP-POPC composition was computed by averaging (eq. 2) over the index and over the chemical species concentrations. For both POPC and HP-POPC molecules, the statistics is performed on beads number 5,6,7,9,10,11,12 (Fig. 4). In practice, the gmx order Gromacs software utility was used to compute . For convenience, will be given here, so that our values can be directly compared to those of literature.

Results and discussion

Fluorescence analysis

The three probes are non-fluorescent in water and become highly fluorescent on binding to phospholipid membranes. [START_REF] Shynkar | Fluorescent biomembrane probe for ratiometric detection of apoptosis[END_REF] This was in our case confirmed by imaging GUVs by confocal microscopy: GUVs appear as fluorescent capsules in a dark, non-fluorescent environment (inset in Fig. 2). The fluorescence of the three probes bound to lipid membranes is characterized by two emission bands, which, according to previous studies of 3-hydroxyflavones, [START_REF] Klymchenko | Novel two-band ratiometric fluorescence probes with different location and orientation in phospholipid membranes[END_REF][START_REF] Klymchenko | Simultaneous probing of hydration and polarity of lipid bilayers with 3-hydroxyflavone fluorescent dyes[END_REF][START_REF] Klymchenko | Bimodal distribution and fluorescence response of environment-sensitive probes in lipid bilayers[END_REF] can be assigned to N* and T* forms for the short and long-wavelength bands, respectively. Figure 2 compares a set of pure POPC and a set of pure HP-POPC GUVs incorporating the F66 probe, each spectrum being an average over ten GUVs. In HP-POPC, the emission spectrum of F66 is dominated by the N* band, while in POPC bilayers, the T* band is dominant. Similar results were obtained with the two other flavone-based probes. However, although averaged over several GUVs, the confocal microscopy spectra lack precision, due partly to the variation of the probe/lipid fraction in the bilayers.

More reproducible results were obtained from spectral analysis of LUVs suspensions by fluorescence spectroscopy. Figure 5 shows the normalized fluorescence spectra of probe-containing LUVs.

Relative POPC/HP-POPC molar ratios 1/0, 1/1, 3/7, and 0/1 have been studied. For each probe, increasing HP-POPC concentration in the bilayer results in a significative modification of the fluorescence spectra, with a clear increase of the intensity in the 500 nm region (Fig. 5). Deeper analysis was obtained from the deconvolution of the spectra into the three N*, T* and H-N* bands (typical example in Fig. 3). The overall modification of the spectra with HP-POPC fraction (Fig. 5) appeared to be mostly related to a significative increase of the N*/T* ratio, while some increase in the intensity of the H-N* pic was also observed (not shown). Results of deconvolutions expressed in parameters of polarity (POL) and hydration (HYD) are given in Figure 6. Each probe reports a nonlinear (roughly quartic) increase of the local polarity as a function of HP-POPC concentration, as shown in Figure 6A. PPZ8, the probe most deeply inserted in the membrane (Fig. 1), exhibits a polarity value close to zero for low HP-POPC fractions and the highest relative increase in the polarity parameter (Fig. 6A). Contrary to polarity, the hydration parameter remains unchanged (within experimental error) with increase in the HP-POPC fraction (Fig. 6B).

Relative variations of the N* and the T* band intensities of 3HF probes inserted in model membranes have been widely reported for different membrane compositions. [START_REF] Klymchenko | Simultaneous probing of hydration and polarity of lipid bilayers with 3-hydroxyflavone fluorescent dyes[END_REF][START_REF] Klymchenko | Bimodal distribution and fluorescence response of environment-sensitive probes in lipid bilayers[END_REF][START_REF] Klymchenko | Visualization of lipid domains in giant unilamellar vesicles using an environment-sensitive membrane probe based on 3-hydroxyflavone[END_REF] For example, increase of the unsaturated/saturated lipid fraction results in the increase of the N*/T* ratio, while increase of the cholesterol content results in the decrease of the N*/T* ratio. [START_REF] Klymchenko | Simultaneous probing of hydration and polarity of lipid bilayers with 3-hydroxyflavone fluorescent dyes[END_REF] Also, transition from gel to fluid state induces a strong increase of N*/T*, while increasing the temperature of a fluid bilayer results in the increase of HYD parameter only, POL remaining unchanged. [START_REF] Klymchenko | Simultaneous probing of hydration and polarity of lipid bilayers with 3-hydroxyflavone fluorescent dyes[END_REF] As a matter of fact, hydration and polarity are not always coupled, as seen with the latter example, and as reported in some other particular cases. [START_REF] Klymchenko | Simultaneous probing of hydration and polarity of lipid bilayers with 3-hydroxyflavone fluorescent dyes[END_REF][START_REF] Klymchenko | Bimodal distribution and fluorescence response of environment-sensitive probes in lipid bilayers[END_REF] POL parameter, i.e. N*/T*, reflects the polarity changes in the close environment of the deeply inserted probe, including water presence, that is known to be related to the order parameter of the lipids. HYD parameter, that is calculated as a relative increase of the H-N* band with respect to a weighted sum of both N* and T* (see MM section) reflects the bilayer hydration in the interface region, H-N* corresponding to a shallow conformation of the probe. [START_REF] Klymchenko | Simultaneous probing of hydration and polarity of lipid bilayers with 3-hydroxyflavone fluorescent dyes[END_REF] Here, depending on its position with respect to the membrane depth, a grafted OOH may either create an H-bond with a probe in its shallow form, changing its H-N* state, or modify strongly the polar environment of a deeply inserted probe, influencing N*/T*. The shallow region is highly polar and hydrated, we observe that HYD parameter is not influenced by the OOH/H-N* interaction in that region (Fig 6B). Deeper in the membrane, the presence of OOH might induce a modification of the local disorder, and thus increase the quantity of water, something predicted to some extent by simulations, see below. Also, OOH groups may interact directly with the probe, or modify their polar environment, both influencing N*/T*. The observed POL variation (Fig. 6A) may thus have several origins, OOH group acting certainly as the driver. Thus, Fig. 6A tells us that only for HP-POPC molar fractions above 50% does the polarity in the membrane start to increase, suggesting that at lower HP-POPC fractions, the hydroperoxides mainly populate the interface.

A B

Dependance of POL and HYD parameters on local micro-environment for various 3-HF probes have already been observed in other cases. For example, the sensitivity of F2N8 and FN4, the first with a charged anchor group, binding preferentially to the lipid membrane interface, and the second highly hydrophobic, have been compared in three model environments : the DOPC bilayer, Hepatitis B surface antigen (HBsAg) particles, and low density lipoproteins (LDLs) [39]. Fig. 5 for F2N8 (resp. Fig. 6 for FN4) in [39] show variations of a factor of 2 (resp. 3) for the POL parameter, when the probes are inserted in LDL or in HBsAg. This is coherent with the compositions of those particles : LDLs contain a hydrophobic fluid core with mainly triglycerides and fatty acids, while the core of HBsAg is mainly composed of proteins. POL is then clearly related to local polarity, that is expected to be higher around proteins than inside triglycerides. Also, FN4, the most hydrophobic probe, is more sensitive than F2N8 to the core composition of LDLs and HBsAg [39],

similarly to what is observed here with PPZ8, when compared to F2N12S and F66.

To gain further information on the HP-POPC-containing membranes, the fluorescence lifetimes of the T* band of the 3HF probes were recorded (Figure 7B). In the case of F2N12S, these lifetimes were shown to be exquisitely sensitive to the lipid order phase, with a two-fold increase in the fluorescence lifetime for the liquid order (Lo) phase as compared to the liquid disorder (Ld)

phase. [START_REF] Kilin | Fluorescence lifetime imaging of membrane lipid order with a ratiometric fluorescent probe[END_REF] This two-fold increase was related to the restriction by the highly packed Lo phase of the relative motions of the two aromatic moieties of the 3HF fluorophore, which favors the highly emissive flat conformation of the probes. [START_REF] Kilin | Fluorescence lifetime imaging of membrane lipid order with a ratiometric fluorescent probe[END_REF] For membranes with a molar fraction of HP-POPC lower than 80% the three probes exhibit one unique lifetime, equal to τ=3.7 ± 0.1 ns, which is typical of the Ld phase. However, for pure HP-POPC membrane, the three probes exhibit a second, longer lifetime (also detected for the 20/80 composition for F2N12S), typical of Lo phase. [START_REF] Kilin | Fluorescence lifetime imaging of membrane lipid order with a ratiometric fluorescent probe[END_REF] As seen in Fig. 7B, the uncertainty on this second lifetime is high, due its low contribution to the total FLIM signal (see Fig. 7A, for a typical example). The minimal changes in the lifetime observed here for 0-80 % of HP-POPC indicate that the probes did not detect strong variation in the lipid order. Thus, the observed ratiometric response of these probes to the presence of HP-POPC (Fig. 6A) should be mainly connected with the increase in the environment polarity. .615] nm respectively. Dashed line is the best fit for a single time decrease, i.e. A exp(-t/τ), while continuous line is for the best fit with a 2-lifetimes function, i.e. A1 exp(-t/τ1)+A2 exp(-t/τ2). (B): lifetimes for pure and mixed membranes of POPC and HP-POPC. Only at the higher HP-POPC fractions does appear a second, longer lifetime in the FLIM signal (as exemplified in A).

Numerical simulations

As discussed above, the increase of the N* band with HP-POPC fraction (Fig. 5) is certainly associated to an increase of the number of dipoles in the deep membrane. Both water molecules or hydroperoxide groups can induce the corresponding increase of POL parameter shown in Fig. 6A.

Numerical simulations aim at clarifying this point. On the one hand, an increased water presence in the deep membrane is associated to an increased disorder of the bilayer. As a matter of fact our simulations show a slight decrease in lipid order with peroxydation (Fig. 8A): decreases in the range [0.21..0.14] for increasing HP-POPC fraction from 0% to 100%. Data in Fig. 8A can be compared to those obtained by Van der Paal et al. [START_REF] Van Der Paal | Effect of lipid peroxidation on membrane permeability of cancer and normal cells subjected to oxidative stress[END_REF] using All Atom simulations (AA), see Fig. 9 shows the z-dependent density curves for the -OOH group (thick lines). They suggest that at low oxidation ratio, hydroperoxyl groups are attracted to the interfacial region of the membrane, while for fully oxidized bilayers, they spread evenly between hydrophobic core (frontier being arbitrarily set to zc = +/-0.8 nm) and interfacial region (zc < z < zi =2.5 nm) (Fig. 9). As a consequence, the local density of hydroperoxides in the hydrophobic core increases non-linearly with the oxidation rate as shown in Fi--S CD,n gure 10 that reports the partitioning between core and interface. Note for example that at 50% HP-POPC content, roughly only 30% of the OOH groups are located deep in the membrane (Fig. 10B). disorder-induced water/N* interaction), our numerical data (Fig. 8, 9, 10) are consistent with a nonlinear dependence of those properties with the oxidation ratio, something clearly highlighted by POL evolution with HP-POPC fraction (Fig. 6A).

Other studies based on numerical simulations have pointed out such non-linear evolution of the density distribution of the peroxide group along the z-direction. A good example is given in [START_REF] Rems | The contribution of lipid peroxidation to membrane permeability in electropermeabilization: A molecular dynamics study[END_REF] for DLPC, a lipid with two doubly unsaturated carbon chains, where it is shown how the position of the -OOH group along the chain influences that distribution. In particular, for -OOH localized on the ninth position (EE9 in [START_REF] Rems | The contribution of lipid peroxidation to membrane permeability in electropermeabilization: A molecular dynamics study[END_REF] ), the peroxide group preferentially locates at the membrane-water interface whatever the peroxidation degree, corresponding thus to a stronger trend of expulsion of the -OOH towards the interface than what is observed for POPC (Fig. 9). On the contrary, for -OOH localized on the thirteenth position (EE13 in [START_REF] Rems | The contribution of lipid peroxidation to membrane permeability in electropermeabilization: A molecular dynamics study[END_REF] ), -OOH distribution shows a stronger localization probability in the core region than the one observed for POPC (Fig. 9). Thus, the behavior of POPC depicted in Fig. 9 appears as intermediate between the EE6 and EE13 cases studied in [START_REF] Rems | The contribution of lipid peroxidation to membrane permeability in electropermeabilization: A molecular dynamics study[END_REF] .

The discussion about location of the -OOH groups is of course of utmost importance, as for it has direct consequences for the membrane structural features. Rare studies have yet been performed that track the distribution of the peroxide group along the membrane z-direction. In particular, De Rosa et al. confirmed the migration to the membrane interface of -OOH groups, but with no evidence for inner membrane enrichment. [START_REF] Rosa | Hydroperoxide and carboxyl groups preferential location in oxidized T biomembranes experimentally determined by small angle X-ray scattering: Implications in membrane structure[END_REF] We also note that another coarse-grained model of HP-POPC was introduced by Siani et al. [START_REF] Siani | An overview of molecular dynamics simulations of oxidized lipid systems, with a comparison of ELBA and MARTINI force fields for coarse grained lipid simulations[END_REF] This model, based on the ELBA lipid force-field [START_REF] Orsi | The ELBA force field for coarse-grain modeling of lipid membranes[END_REF] differs first in the way water molecules are represented, and secondly on the representation of the peroxide group. Indeed, hydroperoxidation of POPC in Siani et al. does not consist in adding an extra -OOH side chain, but in changing one of the oleoyl chain bead, analogue to bead number 10 of POPC in Figure 4. The resulting distribution of -OOH for a fully peroxidized chain is narrower than in Fig. 9, and unimodal (maximum probability located at 9 nm). [START_REF] Siani | An overview of molecular dynamics simulations of oxidized lipid systems, with a comparison of ELBA and MARTINI force fields for coarse grained lipid simulations[END_REF] However, Siani et al. do not show the density probability evolution with peroxidation degree, limiting the comparison between our two models.

The water distribution across the bilayer is represented in Fig. 8B and Fig. 9. The normalized water densities for 3% and 100% peroxidation are shown in Fig. 9, the intermediate values being not shown. One notes a significative increase of water density in the interface region, together with an increase of circa 0.1 nm of the penetration depth with peroxidation, see arrow on Fig. 9.

Fig. 8B presents the evolution of the z-position of the glycerol bead with HP-POPC fraction and the concomitant evolution of the water/lipid fraction. Glycerol position decreases from 1.75 nm to circa 1.6 nm, corresponding to a slight thinning of the bilayer with hydroperoxidation, in agreement with previous studies. [START_REF] Guo | Peroxidised phospholipid bilayers: insight from coarsegrained molecular dynamics simulations[END_REF] The number of water beads per thousand lipids in the inner part of the bilayer, i.e. as limited by the glycerol bead position, is roughly doubled for a 100% hydroperoxidized membrane (Fig. 8B). Water representation in Martini-type simulations should be considered with care. In particular, each bead in the present model represents four water molecules. Knowing that the energy barrier for a water molecule to cross a bilayer is in the order of a few tens of , [START_REF] Marrink | Permeation process of small molecules across lipid membranes studied by molecular dynamics simulations[END_REF] the calculated numbers in Fig. 8B, particularly as far as the core region is concerned, should only be used as an indication of a qualitative trend, i.e. that though water presence in the core region increases with peroxidation, remaining however at a low level overall. This assertion is thus in agreement with the slight decrease of the order parameter (Fig. 8A).

k B T

-S CD

Conclusions

Hydroperoxidation of unsaturated lipids induces important changes in bilayer structure and properties. [START_REF] Wong-Ekkabut | Effect of lipid peroxidation on the properties of lipid bilayers: a molecular dynamics study[END_REF][START_REF] Guo | Peroxidised phospholipid bilayers: insight from coarsegrained molecular dynamics simulations[END_REF][START_REF] Caetano | Marques, Photo-Induced Destruction of Giant Vesicles in Methylene Blue Solutions[END_REF][START_REF] Riske | Giant vesicles under oxidative stress induced by a membrane-anchored photosensitizer[END_REF][START_REF] Heuvingh | Asymmetric oxidation of giant vesicles triggers curvature-associated shape transition and permeabilization[END_REF][START_REF] Mojzisova | Photosensitizing properties of chlorins in solution and in membrane-mimicking systems[END_REF][START_REF] Kerdous | Photo-dynamic induction of oxidative stress within cholesterol-containing membranes: Shape transitions and permeabilization[END_REF][START_REF] Weber | Lipid oxidation induces structural changes in biomimetic membranes[END_REF][START_REF] Van Der Paal | Effect of lipid peroxidation on membrane permeability of cancer and normal cells subjected to oxidative stress[END_REF][START_REF] Rems | The contribution of lipid peroxidation to membrane permeability in electropermeabilization: A molecular dynamics study[END_REF][START_REF] Rosa | Hydroperoxide and carboxyl groups preferential location in oxidized T biomembranes experimentally determined by small angle X-ray scattering: Implications in membrane structure[END_REF][START_REF] Siani | An overview of molecular dynamics simulations of oxidized lipid systems, with a comparison of ELBA and MARTINI force fields for coarse grained lipid simulations[END_REF] Experimental evidence suggests that the average lipid area is not simply related to the fraction of hydroperoxidized lipids in the bilayer. [START_REF] Weber | Lipid oxidation induces structural changes in biomimetic membranes[END_REF][START_REF] Rosa | Hydroperoxide and carboxyl groups preferential location in oxidized T biomembranes experimentally determined by small angle X-ray scattering: Implications in membrane structure[END_REF] For instance, the hydroperoxidation of DOPC bilayers should be accompanied by a much larger increase in area than POPC bilayers, the unsaturation number being twice larger for the first, which is not seen experimentally. [START_REF] Weber | Lipid oxidation induces structural changes in biomimetic membranes[END_REF] As a matter of fact, SAXS analysis on liposomes show that the -OOH moiety preferentially locates towards the polar region of each monolayer of HP-POPC membranes, inducing an area per lipid increase well above the value expected from the geometrical rule that correlates an isotropic volume increase to the corresponding area increase. [START_REF] Rosa | Hydroperoxide and carboxyl groups preferential location in oxidized T biomembranes experimentally determined by small angle X-ray scattering: Implications in membrane structure[END_REF] The present work demonstrates that POPC bilayers are subject to significant structural reorganization as the ratio of hydroperoxidized molecules increases, and that the changes are not marginal neither just proportional to the average density of hydroperoxide groups. Martini numerical simulations show that in HP-POPC bilayers, the grafted organic hydroperoxide group -OOH not only migrates to the lipid bilayer-water interface but also populates deeper regions of the hydrophobic part of the bilayer for the higher -OOH fractions. Fluorescence emission deconvolution for the three fluorescent probes F2N12S, F66, and PPZ8, designed to incorporate at various depths in the membrane, all report a non linear increase of the local polarity, consistent with such concentration-dependant distribution of the -OOH groups along the z-direction of the bilayer. Interestingly, simulations and fluorescence are consistent i) with a relatively low modification of the lipid ordering, and ii) with low water penetration, whatever the peroxidation degree. POPC is abundant in many membranes of eukariotic species. As far as the biological realm is concerned, our results anticipate a strong influence of hydroperoxidation on the interaction of biomembranes with membrane proteins and with membrane-active biomolecules. [START_REF] Libardo | How does membrane oxidation affect cell delivery and cell killing?[END_REF] Indeed, while enrichment of the head region by -OOH groups will likely enhance the affinity of charged species with the membrane, an increased polarity of the inner membrane is expected to facilitate membrane crossing by species such as cell penetrating peptides.

  . The fluorescence intensities of the separated N*, H-N* and T* bands (IN*, IH-N*, and IT*) were used for calculation of i) the hydration parameter HYD and ii) the membrane polarity POL. HYD was expressed as the ratio of the emission intensity of the hydrated (H-N*) form to the summed intensities of the non-hydrated (N* and T*) forms, taking into account that the FWHM for the T* band is 2.5-fold narrower than for the N* and H-N* bands. Thus one gets HYD = IH-N*/(IN* + 0.4xIT*), and POL = IN* / IT*, as derived elsewhere.

Figure 3 :

 3 Figure 3: Black circles : normalized emission spectrum of F2N12S-incorporating LUVs made of 1/1 POPC/HP-POPC. Continuous red line : best fit. Dashed, dotted, dot-dashed lines correspond to the decomposition of the best fit into the three (log-normal) N*, H-N* and T* bands respectively.

Figure 4 :

 4 Figure 4: Coarse graining of POPC and hydroperoxidized HP-POPC molecules. The POPC lipid corresponds to the standard Martini model, with a 4 beads tail for the palmitoyl and a 5 beads tail for the oleoyl fatty acids. Upon peroxidation, the POPC bead 11 (cis-butene) is replaced by a hydrophilic-hydrophobic pair of beads (11,11p in the HP-POPC model). The "hydroperoxide" bead 11p serves to determine the local density of hydroperoxide groups in the membrane. See text for a detailed list of bead chemical correspondence.

Figure 5 :

 5 Figure 5: Fluorescence spectra of LUVs incorporating the 3HF probes. Four membrane compositions are studied, expressed as the POPC/HP-POPC relative fraction: 1/0, i.e. a pure POPC membrane (full line), 1/1 (dashed), 3/7 (dot-dashed), and 0/1 (dotted), corresponding to a pure HP-POPC membrane. Signals from the three probes F2N12S, F66, and PPZ8 are normalized to their value for the T* pick.

Figure 6 :

 6 Figure 6: (A) local polarity coefficient (POL) for each of the 3HF probes, as a function of the HP-POPC fraction. Dashed lines correspond to best fits with a quartic polynomial. (B) hydration coefficient (HYD) for each of the 3HF probes, as a function of the HP-POPC fraction.

Figure 7 :

 7 Figure 7: (A): FLIM signal for pure HP-POPC LUVs, incorporating F66 probe. Excitation and emission wavelength were 405 nm and [545..615] nm respectively. Dashed line is the best fit for a

  3d in their article: their decreases over a comparable range, namely [0.16..0.12]. We give in Supplementary Information the evolution of individual for each of the beads of the carbon chain of both POPC and HP-POPC, with HP-POPC fraction in the bilayer (Fig. S1). While for beads of the saturated (sn-1) chain (beads 5,6,7), decreases slightly over the range [0.3..0.2] with peroxidation for both POPC and HP-POPC, beads of the unsaturated chain (sn-2) of HP-POPC (beads 9-12) surprisingly evolve oppositely, i.e. from a more disordered configuration for a membrane with low HP-POPC fraction, towards a more ordered configuration for a fully peroxidized -S CD -S CD -S CD,n -S CD,n A B bilayer. Note that for the sn-2 chain of POPC, values are similar to their sn-1 counterpart, except for bead 12 (Fig. S1). On the other hand, hydroperoxyl groups (-OOH) are known to significantly modify the polarity of their environment. Even though our coarse grained (CG) simulations cannot predict the local dielectric constant, closely related to the local polarity, they report a non homogeneous distribution of the hydroperoxides along the z-direction in the hydrophobic region of the bilayer. Predictions from our model are summarized in Figures 9 and 10.Fig.

Figure 8 :

 8 Figure 8: A) Average order parameter (see 2.8), for various fractions of HP-POPC in the membrane. B) Average z-position of the glycerol bead (bead n°3, see Fig. 4) and number of water beads per thousand lipids in the inner region of the bilayer, i.e. limited by the glycerol bead.

Figure 9 :

 9 Figure 9: Number density of hydroperoxide groups for various oxidation ratio (thick lines), i.e. statistics of positions of beads 12, see Figure 4. Density of hydroperoxides are normalized in such a way that their integration with respect to z equals the percentage N of oxidized lipids (N=3, 25, 50, 70 and 100). Dotted vertical lines are for z=0 (midplane), z=zc=±0.8 nm (core limits), and z=zi=±2.5nm (bilayer interfaces). Thin continuous lines: normalized density of water beads for the 3% and 100% peroxidized membrane (arrow oriented from 3% towards 100%).

Figure 10 :

 10 Figure10:(A) number of hydroperoxide groups in core (red 'v' triangles) and interfacial region (blue '^' triangles), for various fractions of HP-POPC. The sum of the two curves is equal to the percentage N of hydroperoxidation. (B) partition probabilities between core and interface as a function of the oxidized fraction. In both figures, the dotted line corresponds to an homogeneous distribution over the z-direction. At low concentration, most hydroperoxides stay at the interface while at large concentration they distribute evenly between core and interface. Note the affine increase of the core partitioning probability as a function of the hydroperoxidation fraction (B), consistent with a non-linear increase of the hydroperoxide density in the core region (A).Thus, assuming that changes in the probe fluorescence properties are related to the close proximity of hydroperoxyl groups (either through a direct OOH/N* interaction, or through a lipid

Acknowledgments

The authors thank Pr. Rosangela Itri for insightful discussions and for sharing non published material. Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (2012/50680, 2013/07937-8, 2013/11640-0) and NAP-Phototech are acknowledged for financial support. Y. M. is grateful to the Institut Universitaire de France (IUF) for support and providing additional time to be dedicated to research.

Conflict of interest

There are no conflicts to declare.


Lúcia Fernandes Sanches
email: sanches1983@gmail.com

Bertrand Guenet
email: bertrand.guenet@ens.fr

Nicholas Dos Anjos

Cristiano Marino

Francisco De

Assis Esteves

Lúcia Fernandes Sanches

Francisco De Assis Esteves

Exploring the Drivers Controlling the Priming Effect and Its Magnitude in Aquatic Systems

come

Introduction

Both freshwater and marine ecosystems receive and process large amounts of organic matter that are exported from terrestrial and in-stream primary production (1.9 Pg C yr -1 , of which 0.9 Pg C yr -1 reaches the continental shelf [START_REF] Cole | Plumbing the Global Carbon Cycle: Integrating Inland Waters into the Terrestrial Carbon Budget[END_REF]). This organic matter is highly heterogeneous in its resistance to degradation [START_REF] Jiao | Microbial production of recalcitrant dissolved organic matter: long-term carbon storage in the global ocean[END_REF], with highly recalcitrant organic matter generally originating from terrestrial vegetation inputs [START_REF] Amon | Bacterial Utilization of Different Size Classes of Dissolved Organic Matter[END_REF][START_REF] Thorp | Dominance of autochthonous autotrophic carbon in food webs of heterotrophic rivers[END_REF]. More reactive or 'labile' molecules tend to be sourced from in-stream or 'autochtonous' primary production (R.L. [START_REF] Sinsabaugh | Integrating Dissolved Organic Matter Metabolism and Microbial Diversity[END_REF], although this is also a source of the most persistent organic matter [START_REF] Kothawala | Controls of dissolved organic matter quality: Evidence from a large-scale boreal lake survey[END_REF][START_REF] Kellerman | Persistence of dissolved organic matter in lakes related to its molecular characteristics[END_REF]. As such, aquatic systems are sites of intense loading and processing of organic matter [START_REF] Regnier | Anthropogenic perturbation of the carbon fluxes from land to ocean[END_REF].

Through a process known as the "priming effect", labile organic matter (LOM) can interact with stable organic matter (SOM), altering the latter's rate of mineralization [START_REF] Fontaine | The priming effect of organic matter: a question of microbial competition?[END_REF][START_REF] Kuzyakov | Review of mechanisms and quantification of priming effects[END_REF]. As such, the metabolic activity of microorganisms can be stimulated or inhibited by labile carbon (C) inputs, respectively referred to as positive or negative priming [START_REF] Kuzyakov | Review of mechanisms and quantification of priming effects[END_REF]. This process was first described for soils [START_REF] Löhnis | Nitrogen availability of green manures[END_REF], with studies demonstrating that it can play a significant role in the soil carbon budget and nutrient cycling [START_REF] Fontaine | Carbon input to soil may decrease soil carbon content[END_REF][START_REF] Finzi | Rhizosphere processes are quantitatively important components of terrestrial carbon and nutrient cycles[END_REF][START_REF] Keiluweit | Mineral protection of soil carbon counteracted by root exudates[END_REF][START_REF] Guenet | Impact of priming on global soil carbon stocks[END_REF]. In terrestrial ecosystems, positive priming is reported more frequently in laboratory incubations [START_REF] Kuzyakov | Review of mechanisms and quantification of priming effects[END_REF], though positive priming has also been demonstrated in field studies [START_REF] Xiao | Priming of soil organic matter decomposition scales linearly with microbial biomass response to litter input in steppe vegetation[END_REF].

Positive priming may therefore under certain conditions reduce soil C storage by enhancing the rate at which soil carbon is metabolised by soil microbiota [START_REF] Fontaine | Carbon input to soil may decrease soil carbon content[END_REF]. In addition, priming dynamics depend on the interactive effects of abiotic and biotic factors such as substrate availability and accessibility, soil physical-chemical properties, and microbial community structure and activity [START_REF] Fontaine | The priming effect of organic matter: a question of microbial competition?[END_REF][START_REF] Blagodatskaya | Mechanisms of real and apparent priming effects and their dependence on soil microbial biomass and community structure: critical review[END_REF][START_REF] Kuzyakov | Priming effects: Interactions between living and dead organic matter[END_REF]. Priming in aquatic ecosystems became a topic of discussion some decades ago [START_REF] De Haan | Effects of benzoate on microbial decomposition of fulvi acids in Tjeukemeer (The Netherlands)[END_REF], but has recently received renewed interest from freshwater and marine ecosystems researchers (Guenet, et al., 2010a;[START_REF] Bianchi | The role of terrestrially derived organic carbon in the coastal ocean: A changing paradigm and the priming effect[END_REF][START_REF] Lane | Cycling of two carbon substrates of contrasting lability by heterotrophic biofilms across a nutrient gradient of headwater streams[END_REF]. The main mechanisms proposed to explain priming are, firstly, that microbial competition between LOM and SOM specialists can push SOM specialists to feed exclusively on SOM when LOM is added, causing the LOM-specialist populations to grow [START_REF] Fontaine | The priming effect of organic matter: a question of microbial competition?[END_REF]. Secondly, priming may be caused by nutrient mining, whereby microorganisms increase SOM decomposition in order for them to obtain specific growth-limiting nutrients. Co-metabolism of aquatic microorganisms may be a further explanatory factor [START_REF] De Haan | Effects of benzoate on microbial decomposition of fulvi acids in Tjeukemeer (The Netherlands)[END_REF]. In this study, we defined priming effect in aquatic ecosystems as it was defined in soils, i.e., the modification (acceleration or slowdown) of the mineralization rate of the SOM initially present induced by addition of LOM.

A growing number of studies have shown that priming effects can occur across a wide range of aquatic ecosystems [START_REF] De Haan | Effects of benzoate on microbial decomposition of fulvi acids in Tjeukemeer (The Netherlands)[END_REF][START_REF] Shimp | Influence of easily degradable naturally occurring carbon substrates on biodegradation of monosubstituted phenols by aquatic bacteria[END_REF][START_REF] Carlson | Effect of nutrient amendments on bacterioplankton production, community structure, and DOC utilization in the northwestern Sargasso Sea[END_REF]van Nugteren et al., 2009;[START_REF] Farjalla | Synergy of fresh and accumulated organic matter to bacterial growth[END_REF][START_REF] Danger | Benthic algae stimulate leaf litter decomposition in detritus-based headwater streams : a case of aquatic priming effect ?[END_REF][START_REF] Bianchi | Positive Priming of Terrestrially-Derived Dissolved Organic Matter in a Freshwater Microcosm System[END_REF], and that the rate of the attendant carbon metabolization may be of a similar magnitude to that observed in terrestrial ecosystems (Guenet, et al., 2010a). Concurrently however, these studies also present contrasting and apparently contradicting results, with some suggesting a significant positive priming effect and others a negative or non-existent one [START_REF] Danger | Benthic algae stimulate leaf litter decomposition in detritus-based headwater streams : a case of aquatic priming effect ?[END_REF][START_REF] Franke | Mineralisation of dissolved organic matter by heterotrophic stream biofilm communities in a large boreal catchment[END_REF][START_REF] Bengtsson | No evidence of aquatic priming effects in hyporheic zone microcosms[END_REF][START_REF] Guenet | Fast mineralization of land-born C in inland waters: First experimental evidences of aquatic priming effect[END_REF][START_REF] Catalán | Absence of a priming effect on dissolved organic carbon degradation in lake water[END_REF]. The drivers of these differences in labile-stable organic matter interactions, as well as the relative importance and magnitude of priming within and across different aquatic ecosystems has remained unclear. Indeed, a recent synthesis on the topic concluded that the priming effect may not be a significant phenomenon in aquatic ecosystems [START_REF] Bengtsson | Interactive effects on organic matter processing from soils to the ocean: are priming effects relevant in aquatic ecosystems?[END_REF]. However, [START_REF] Bengtsson | Interactive effects on organic matter processing from soils to the ocean: are priming effects relevant in aquatic ecosystems?[END_REF] focused only on primary research studies that explicitly mentioned the term 'priming'. While this is a valid first approximation, it ignores those studies whose methodology and data collection could have been used to test the priming effect, but which were not originally designed for this purpose. There exists a wealth of prior studies investigating the response of microbial mechanisms to a mix of labile and a native substrates that are appropriate for the inference of the priming effect [START_REF] Carlson | Organic carbon partitioning during spring phytoplankton blooms in the Ross Sea polynya and the Sargasso Sea[END_REF][START_REF] Farjalla | Synergy of fresh and accumulated organic matter to bacterial growth[END_REF]. Therefore, the amount of data available to conduct such meta-analysis may be substantially larger than that considered by [START_REF] Bengtsson | Interactive effects on organic matter processing from soils to the ocean: are priming effects relevant in aquatic ecosystems?[END_REF], meaning their conclusions with respect to the plausibility of aquatic system priming may be premature. Indeed in this vein [START_REF] Bengtsson | Interactive effects on organic matter processing from soils to the ocean: are priming effects relevant in aquatic ecosystems?[END_REF] considered whether much of the observed PE variability might also result from issues in defining the priming effect.

In this study, we compiled literature data from experimental studies on C mineralization in aquatic ecosystems that either directly tested the priming effect, or contained data from which we could recalculate the priming effect. We then applied a meta-analytic approach to investigate the study-level characteristics most likely to explain the variation in the occurrence and magnitude of priming in aquatic ecosystems.

More specifically we aimed at determining: (1) the overall magnitude of priming across studies; (2) the extent of heterogeneity in results across studies; and (3) the possible biogeochemical and methodological drivers behind the observed differences in priming.

We also discuss whether the term 'priming effect' should be modified or not as suggested by [START_REF] Bengtsson | Interactive effects on organic matter processing from soils to the ocean: are priming effects relevant in aquatic ecosystems?[END_REF].

Materials and methods

Literature search, inclusion criteria and data extraction

To find published data directly or indirectly related to the priming effect, we searched the ISI Web of Science for primary research studies using the terms "organic matter AND priming AND aquatic" OR "carbon AND priming AND aquatic" OR "organic matter AND carbon AND aquatic" in the title, abstract, author keywords, or keywords plus. This research was performed on 13 th February 2020. We also included the data studied in previous compilations on the PE (Guenet, et al., (2010a); [START_REF] Bengtsson | No evidence of aquatic priming effects in hyporheic zone microcosms[END_REF][START_REF] Blanchet | When riverine dissolved organic matter (DOM) meets labile DOM in coastal waters: changes in bacterial community activity and composition[END_REF] ), resulting in a total of 125 studies considered initially.

In addition, for a study to be included in our meta-analysis it had to meet four criteria: (1) the experimental study was designed to explicitly test the priming effect on C mineralization or had a design through which the priming effect could be calculated a posteriori (i.e. the possibility to measure SOM mineralization or microbial activity support by SOM mineralization with or without LOM); (2) the study established a control treatment containing only SOM and an experimental treatment containing both LOM and SOM; (3) the outcome reported by the experiment was a proxy of microbial activity under both priming/no-priming treatments (bacterial growth, bacterial production, bacterial respiration, CO 2 production, DOC (dissolved organic carbon) consumed, extracellular enzyme activity or POC (particulate organic carbon) removed); (4) the study reported the mean, a measure of variability (e.g.., standard error, variance or confidence intervals) and the sample size for each of the two treatments. Following these criteria, we included 877 results from experimental treatments from 36 published studies out of the initial 125 in the meta-analysis.

From these, we extracted a number of measures for diagnosing the different outcomes reported across studies (CO 2 production, bacterial production, DOC or POC degradation, enzymatic activities, O 2 consumption), as well as a number of factors detailed below that we hypothesized a priori could be drivers of the priming outcome in each study. First, we extracted the statistical means, sample sizes and sample variabilities for each of the two treatments from each experiment in our meta-analysis. We extracted these data directly from the text and tables, or used the software Engauge Digitizer v4.1 in cases where such data was presented in figures. Then, for each study, we recorded from the papers text or tables the several factors that could be drivers for priming. We collected the type of ecosystem studied (four levels: lake, lagoon, river/stream or marine/sea), the experimental venue (two levels: in situ or laboratory experiments) and the identity of the priming-inducing LOM (four levels: glucose, algae, diatoms or other (referring to any LOM not in the three previous categories; the category diatoms was created separately from alga level due high number of experiments that used specifically this taxa as priming inductor, in general used diatom detritus as LOM). We also collected the presence or absence of particulate organic carbon (POC; two levels), whether nutrients were added to the medium (four levels: no addition, N addition, P addition, N and P addition), the temperature (Celsius) and the duration of the experiment (in days).

Vote counting and effect size calculation

We used two approaches to analyze the extent of occurrence and the variation in the magnitude of the priming effect across studies. First, we used the results reported by the authors from each study to code a categorical variable indicating whether the priming effect occurred or not and, if it occurred, whether it accelerated (positive priming) or slowed down C mineralization (negative priming). Nevertheless, not all the studies used in our analysis were designed to study the PE and thus, this information was sometimes missing. Moreover, in the studies we gathered, the authors do not use a common metric and the comparison between studies is therefore difficult. Thus, in our second approach, we calculated a metric for quantifying the magnitude of priming for each observation in each study and at each time step. We chose the log response ratio as the effect size metric, a measure commonly used in ecological meta-analysis [START_REF] Rosenberg | Effect sizes: convetional choices and calculations[END_REF]. This metric quantifies, for each observation in each study, the log of the ratio between the outcome in the experimental treatment (i.e., SOM + LOM) and the control treatment (i.e., SOM only), with positive values indicating that the priming effect accelerated C mineralization, and negative values indicating the opposite. From here on, we refer to this priming magnitude metric as the priming response ratio (PRR) according to

PRR = log (Rpt/Rct) (1)
Where PRR refers to priming effect in absolute values, Rpt to the difference of OM degradation in the priming treatment (SOM + LOM) between beginning and end of experiment, and Rct to the difference of OM degradation in the control treatment (only SOM) between beginning and end of experiment. PRR calculation allowed us compare OC degradation reported in a variety of different units (e.g. DOC removed, C respired, leaf mass loss).

Statistical analyses

Estimation of the overall priming magnitude

We used a mixed-effects meta-analysis model to determine the overall magnitude of the priming effect and to quantify its heterogeneity across studies, with PRR as the dependent variable and the inclusion of a random intercept term to account for the nonindependence of observations coming from the same study following eq. 2:

(2)

with the fixed effect of j-th variable, being the value of the j-th moderator variable for the i-th study and being the rand effect associated to the i-th study. Several observations lacked an error term, which prevented us from calculating the sampling variance related to each PRR and, therefore, from being able to weight each observation by its precision. We used an unweighted approach which was not qualitatively different from the weighed approach (supporting information). We verified the assumptions of the model by visual inspection of data and residuals. We then extracted the overall priming effect magnitude across studies and its 95% confidence intervals to test the null hypothesis that the size of an effect is homogenous across studies. We also extracted the Q T and I 2 statistical heterogeneity measures. Q T and I 2 describe both the percentage of variation across studies due heterogeneity rather than chance [START_REF] Cochran | The Combination of Estimates from Different Experiments[END_REF][START_REF] Higgins | Quantifying heterogeneity in a metaanalysis[END_REF]. Although Q T is a classical indicator of heterogeneity, it is sensitive to the number of studies, which is not the case with I 2 .

Identification of the explaining factors

We then sought to determine which factors were most likely to explain differences in priming magnitude across studies. To this end, we used the same methods described in 2.3.1 but we fitted eight separate models using each of the seven predictor variables extracted (type of ecosystem, experimental venue, identity of the priming inductor, POC presence, nutrient addition, temperature and experimental duration) and a predictor variable coding the type of response variable used by authors to characterize the priming effect in each study used in meta-analysis (categorical, seven levels: bacterial growth, bacterial production, bacterial respiration, CO 2 production, DOC degradation, extracellular enzyme activity or POC removed). We included both a linear and a quadratic term for temperature in the model when using this variable as a predictor, given the non-linear effects of temperature in most biological process [START_REF] Brown | Toward a metabolic theory of ecology[END_REF]. We ran a separate model for each of these predictors, as our main aim was to gain a general understanding of the factors contributing to the variation in priming magnitude, rather than the complex interactions between the predictors. After fitting each of the models, we verified the assumptions of the model by visual inspection of data and residuals, extracted the overall effect size for each level of the non-continuous (i.e. categorical) factors and their 95% confidence intervals, the overall slope of the effect of the continuous factors and, finally, calculated the Q T and I 2 heterogeneity measures for each model. The model tests whether a predictor is significant by comparing the log (PPR) distribution against 0.

If the p-value associated is lower than 0.05 the predictor is considered as significant.

Nevertheless, to take into account the risk of inflating the type 1 error when reproducing those analysis, we corrected the p-value using the Holm-Bonferonni method [START_REF] Holm | A Simple Sequentially Rejective Multiple Test Procedure[END_REF]. We ran all analysis using R v3.5.1, and fitted the mixed-effects meta-analysis models using the function rma.mv available in the package metafor [START_REF] Viechtbauer | Conducting meta-analyses in R with the metafor package[END_REF].

This approach is widely used to perform meta-analysis [START_REF] Schädel | Potential carbon emissions dominated by carbon dioxide from thawed permafrost soils[END_REF][START_REF] Senior | Heterogeneity in ecological and evolutionary meta-analyses: Its magnitude and implications[END_REF][START_REF] Meurer | Tillage intensity affects total SOC stocks in boreo-temperate regions only in the topsoil-A systematic review using an ESM approach[END_REF][START_REF] Chen | Soil carbon loss with warming: New evidence from carbon-degrading enzymes[END_REF][START_REF] Terrer | A trade-off between plant and soil carbon storage under elevated CO2[END_REF]. All the analysis methods are summarized in Table 1.

Results

Is priming observed in aquatic ecosystems? Estimations using vote-

counting approach or mixed-effects meta-analysis model.

Most of the studies analyzed reported an absence of the priming effect (Figure 1).

Specifically, this was the case for 65% out the 877 observations included in our analysis, whereas only 27% of the observations were related to a positive and 7% to a negative priming effect. However, the variability in PRR values across these three categories was very high, especially for reports on positive priming effects (Figure 2).

In contrast to the vote counting approach, the mixed-effects meta-analysis model provided support for a positive priming effect across studies (Figure 3, PRR: 0.43; 95% CI: 0.21 to 0.65), indicating that the addition of LOM accelerates microbial activity on SOM by 53.7% on average (95% CI: 23.4% to 91.6%). Yet, this model also revealed that there is a high heterogeneity in observed outcomes across experiments, with 91.4% of the variation in the overall effect size explained by differences between studies (I 2 metric;

σ 2 study : 0.281).

Identification of the explaining factors

The mixed-effects meta-analysis model indicated that such heterogeneity could be explained by methodological and environmental differences between studies (Figures 4, 5

and 6). First, we found that the proxy used to estimate the priming effect in each experiment may be a key driver determining whether it can be detected or not. This is because the (positive) priming effect was mostly reported when it was estimated via CO 2 production (0.53 [0.22 to 0.84]) or bacterial growth (PRR [95% CI]: 1.27 [0.40 to 2.13]).

We noted that using bacterial production (0.74 [0.20 to 1.28]), extracellular enzyme activities (0.92 [0.10 to 1.74], tends to detect priming but those variables were not significant after the Holm-Bonferonni correction. Other measures such as bacterial respiration, DOC degradation and POC removal were unlikely to detect the priming effect (Figure 3a). Second, experiments conducted in the laboratory often reported a positive priming effect (0.43 [0.19 to 0.67]), while the same did not occur in experiments performed in situ (0.44 [-0.17 to 1.06]) (Figure 4b).

Adding N or P may impact observed priming effect even though the PPR values were generally close. Indeed, only when N and P were simultaneously added to the experiment (0.40 [0.14 to 0.67]) or neither was added (0.45 [0.21 to 0.69]) were effects statistically significant after the Holm-Bonferonni correction (insignificant when N (0.48 [0.12 to 0.83]) or P (0.42 [0.06 to 0.77]) were added in isolation, (Figure 5a)). In addition, the priming effect was not detected when the type of the LOM added was in the form of diatoms (0.43 [-0.11 to 0.97]) or algae (0.41 [-0.02 to 0.83]). A trend was observed for glucose (glucose: 0.36 [0.06 to 0.66]) addition but the effect was not considered significant. Finally, priming was significantly detected with the last categories referring to any LOM not in the three previous categories (other: 0.45 [0.17 to 0.73]) (Figure 5b).

POC addition may impact whether priming is detected (0.39 [0.08 to 0.71]) since the priming was not considered significant after POC addition, whereas it was in experiments in which it was excluded (0.48 [0.16 to 0.79]) (Figure 5c).

We found that the priming effect tends to be reduced when increasing experimental duration (intercept, β 0 : 0.59 [0.33 to 0.86]; β duration : -0.06 [-0.14 to -6.14 10 - 4 ]). Moreover its magnitude seems affected by the temperature at the time of measurement (Figure 6). More specifically, we found a non-linear relationship between temperature and the magnitude of the PE, which was absent or weak when experimental temperatures were below 20 ºC, but became increasingly positive and strong above it (β 0 :

1.68 [-0.55 to 3.91]; β temperature : -0.20 [-0.45 to 0.05]; β temperature 2 : 0.007 [-4.3 10 -6 to 0.01];

Figure 6b). Nevertheless, after Holm-Bonferonni correction these effects were not considered significant. Finally, because of non-orthogonality across the levels of both factors or because some treatment combinations were restricted to a single study, we

were not able to look at interactions between moderators.

Discussion

The overall priming magnitude.

From the meta-analytic approach employed in this study we observed that, when it occurs, the addition of LOM increased C mineralization rates in aquatic ecosystems, on average, by 53.7%, indicating an overall positive priming effect. However, we note that the variability between and even within studies was quite large. This explains why the vote-counting method provides different results compared to the meta-analysis approach.

Indeed the vote-counting approach shows that most of the studies gathered in our database failed to observe priming. Nevertheless, our meta-analysis approach suggests overall positive priming. This apparent contradiction is partly due to the database used.

Indeed, for the vote-counting approach, we can only use studies that calculated priming whereas for the meta-analysis we can post calculated priming when all the necessary data were presented in a paper. Thus, the database used for the meta-analysis is larger than the one used for the vote-counting. Moreover, by using the meta-analysis approach we standardized the way priming effect is calculated and thus the statistical power a largely higher than a single study helping identifying some effect [START_REF] Stewart | Meta-analysis in applied ecology[END_REF]. One of the explanations for this large variability might be the diversity of methods used to detect priming, whereby some measurement proxies barely observe priming while others (bacterial growth, CO 2 production) do (Fig. 4). Because priming is the result of a number of microbial process at the community level or even at the individual level, measuring the direct effect of LOM addition on bacterial growth may be a more straightforward and less variable means for measuring the priming effect compared to other proxies such as enzymatic activities or C mineralization by mass differences. Otherwise microbial respiration didn't show efficiency in measured PE, although is the result of enzymatic activity but also on carbon use efficiency, as well as bacterial growth and bacterial production, which is known to be affected by environmental conditions [START_REF] Manzoni | Environmental and stoichiometric controls on microbial carbon-use efficiency in soils[END_REF][START_REF] Sinsabaugh | Carbon use efficiency of microbial communities: stoichiometry, methodology and modelling[END_REF]. Moreover, an important fraction of the studies available to perform such meta-analysis do not used labeled organic matter to track the mineralization of SOM and LOM separately and performed a control treatment with SOM only and a SOM+LOM treatment but do not perform a control with only LOM. It is therefore difficult to finely estimate priming since the dynamic of both source of OM cannot be tracked in absence of labeling. This is also a source of variability that may explain the apparent discrepancies between studies.

Identification of the explaining factors

It is interesting to note that bacterial respiration and CO 2 production give quite different results as priming predictors, even though CO 2 production is largely the result of microbial respiration. This may be related to the fact that the methods used to estimate both fluxes are quite different. Indeed, bacterial respiration is often inferred from O 2 consumption rates measured using variable methods with traditional Winkler method [START_REF] Winkler | Die Bestimmung des im Wasser gelösten Sauerstoffes[END_REF] and modern approaches [START_REF] Marchand | Linking forest fires to lake metabolism and carbon dioxide emissions in the boreal region of Northern Québec[END_REF][START_REF] Del Giorgio | Coherent patterns in bacterial growth, growth efficiency, and leucine metabolism along a northeastern Pacific inshore-offshore transect[END_REF] whereas CO 2 production is measured using gas chromatography or by being trapped in NaOH. Another explanation for the discrepancies between CO 2 production and O 2 consumption might be a change in respiratory quotient (moles produced CO 2 per mole consumed O 2 ) in response to the use of different OM qualities. Results of respiratory quotient are intimately linked to the elemental composition of the respired substrates [START_REF] Berggren | Magnitude and regulation of bacterioplankton respiratory quotient across freshwater environmental gradients[END_REF]. Priming proxied on bacterial respiration showed higher variability than results based on CO 2 production. Based on those results, we suggest that to detect priming we should use bacterial growth. On the other hand to diagnose the impact of priming on the C balance, CO 2 production may be the appropriate proxy, being potentially sensitive enough to detect it, whilst bearing in mind that CO 2 production may also result from abiotic processes [START_REF] Anesio | Effect of humic substance photodegradation on bacterial growth and respiration in lake water[END_REF]. These suggestions are in line with those of [START_REF] Bengtsson | Interactive effects on organic matter processing from soils to the ocean: are priming effects relevant in aquatic ecosystems?[END_REF] who suggested to focus on microbial activity to better understood the role of LOM inputs on the ecosystem C cycle. The differences in priming response observed in aquatic ecosystems due to divergent methodologies has not been previously identified in soils, where the priming effect concept was originally defined, because in soil science the methods used to study priming are generally quite comparable.

In these, labeled LOM is added to the medium (e.g. [START_REF] Hamer | Interactive priming of black carbon and glucose mineralisation[END_REF][START_REF] Shahzad | Contribution of exudates, arbuscular mycorrhizal fungi and litter depositions to the rhizosphere priming effect induced by grassland species[END_REF][START_REF] Qiao | Carbon and nitrogen additions induce distinct priming effects along an organic-matter decay continuum[END_REF] and CO 2 production is measured, and the subsequent the use of the carbon isotopes and mass balance equations help to discriminate the source of the produced CO 2 . It is possible that by using a single experimental approach, positive priming is more often reported in soils than in the aquatic realm (see [START_REF] Blagodatskaya | Mechanisms of real and apparent priming effects and their dependence on soil microbial biomass and community structure: critical review[END_REF] for review).

It is interesting that nutrient addition in terrestrial ecosystems is often associated with a reduced priming effect due to nutrient mining [START_REF] Blagodatskaya | Priming effects in Chernozem induced by glucose and N in relation to microbial growth strategies[END_REF][START_REF] Fontaine | Carbon input to soil may decrease soil carbon content[END_REF]. However, we observed that adding N and P together give similar results that when nutrients were not added leading in all cases to a positive priming effect.

Nevertheless, when only N or P was added the priming observed was not significant. As such, in contrast to what happens in soils, this result suggests that nutrient mining may not be a major driver of priming in aquatic ecosystems [START_REF] Langley | Priming depletes soil carbon and releases nitrogen in a scrub-oak ecosystem exposed to elevated CO2[END_REF][START_REF] Chen | Soil C and N availability determine the priming effect: Microbial N mining and stoichiometric decomposition theories[END_REF]. Indeed, in soils organic matter may be stored for millennia [START_REF] Balesdent | Atmosphere-soil carbon transfer as a function of soil depth[END_REF] and the stabilization process substantially increases the energetic cost required to obtain nutrients. Thus, when LOM is added to soils it provides enough energy for microbiota to mineralize the nutrients. In aquatic ecosystems, such effect of nutrient seems not to be an important driver [START_REF] Wologo | Stream Dissolved Organic Matter in Permafrost Regions Shows Surprising Compositional Similarities but Negative Priming and Nutrient Effects[END_REF]. Our results therefore suggest that the drivers of priming may be different in terrestrial versus aquatic systems. We also observed that outside of diatom and algae inputs, all types of LOM addition could induce priming but the effect of glucose was not significant after using Holm-Bonferonni correction. It is difficult to understand why priming was significant only for the category 'others' because it represents a large diversity of molecules and not enough data were available to split it up. This should be a future line of inquiry.

Should we keep calling it priming?

Bengtsson et al. (2018) recently published a meta-analysis whose aim was similar

to, yet whose methods were different from this study, and showed no significant effect of LOM addition on C mineralization rates (positive priming of 12.6% with a 95% CI ranging from -5.6% to 34.3%). However, [START_REF] Bengtsson | Interactive effects on organic matter processing from soils to the ocean: are priming effects relevant in aquatic ecosystems?[END_REF] selected studies that used mostly bacterial respiration and carbon mineralization measured by mass differences (either DOC or POC) to measure the priming effect, which our results suggest are methods that can hardly ever detect this phenomenon (Fig. 4). It is unsurprising that massloss methods failed to detect any changes since they are used on relative short-term incubations (few days to few weeks) and, to be detected by classical method, a mass loss must be important enough. As such, this can explain why our work and that of [START_REF] Bengtsson | Interactive effects on organic matter processing from soils to the ocean: are priming effects relevant in aquatic ecosystems?[END_REF] arrived at entirely different conclusions. Yet, it is interesting to note that our 95% CI from the estimate of the mixed-effects model falls within the 95% CI of [START_REF] Bengtsson | Interactive effects on organic matter processing from soils to the ocean: are priming effects relevant in aquatic ecosystems?[END_REF]. This suggests that both studies are mutually consistent, with the addition that this study pulls apart the drivers of priming heterogeneity. Future studies should take into account this heterogeneity of measurement technique in when designing and reporting experiments relating to the priming effect.

Experimental duration was not a significant driver of aquatic priming after Holm-Bonferonni correction. This result is not coherent with results on the priming effect in soils where long-term effect are often observed [START_REF] Šantrůčková | Short-term partitioning of 14C-[U]-glucose in the soil microbial pool under varied aeration status[END_REF][START_REF] Luo | Short term soil priming effects and the mineralisation of biochar following its incorporation to soils of different pH[END_REF][START_REF] Van Groenigen | Faster decomposition under increased atmospheric CO₂ limits soil carbon storage[END_REF][START_REF] Guenet | Impact of priming on global soil carbon stocks[END_REF]. Furthermore, it is important to consider that LOM inputs into ecosystems vary seasonally and inter-annually [START_REF] Giordano | CO2 concentrating mechanisms in algae: mechanisms, environmental modulation, and evolution[END_REF][START_REF] Högberg | Quantification of effects of season and nitrogen supply on tree below-ground carbon transfer to ectomycorrhizal fungi and other soil organisms in a boreal pine forest[END_REF]. This is of particular interest in a global change context where atmospheric CO 2 may induce higher net primary production both in land and aquatic ecosystems [START_REF] Norby | Forest response to elevated CO2 is conserved across a broad range of productivity[END_REF][START_REF] Borchard | Organic matter exudation by Emiliania huxleyi under simulated future ocean conditions[END_REF]. As a consequence, we suggest that if the aim of the experiment is to evaluate the impact of priming under changing conditions on the ecosystem functioning or on C balance, long-term experiments have to be performed that replicate variability in the inputs associated to long-term trends. In the future, global temperatures will increase irrespective of differences between anthropogenic emissions scenarios [START_REF] Anav | Evaluating the Land and Ocean Components of the Global Carbon Cycle in the Cmip5 Earth System Models[END_REF]. We show here that priming tends to be sensitive to temperature, and is positively related to it when incubation temperatures exceed 20°C but this effect was not significant after Holm-Bonferonni correction, the effect of temperature on priming is therefore not clear similarly to results found for the temperature sensitivity of soil priming [START_REF] Ghee | Priming of soil organic matter mineralisation is intrinsically insensitive to temperature[END_REF][START_REF] Luo | A meta-analysis of the temporal dynamics of priming soil carbon decomposition by fresh carbon inputs across ecosystems[END_REF]. This large variability of the results might be due to the use of metabolic proxies (bacterial growth or production) in studies from aquatic ecosystems, which are processes more sensitive to temperature than CO 2 fluxes leading to high variability. However, we are unable to explore this in depth here because we did not look at the interactions between drivers.

Finally, [START_REF] Bengtsson | Interactive effects on organic matter processing from soils to the ocean: are priming effects relevant in aquatic ecosystems?[END_REF] suggested that the term 'priming effect' should be changed to "interactive effect among OC pools" to avoid confusion, and to acknowledge the chemical diversity present in OC, instead of continuing to work in terms of 'labile' and 'recalcitrant' OC pools. This is specially appropriate in aquatic systems where intrinsic properties seem to be more relevant than in soils [START_REF] Kellerman | Persistence of dissolved organic matter in lakes related to its molecular characteristics[END_REF] even though interactions with abiotic and environmental variables such as minerals are now considered as important driver of OC dynamic in aquatic ecosystems [START_REF] Littlefair | Retrogressive thaw slumps temper dissolved organic carbon delivery to streams of the Peel Plateau, NWT, Canada[END_REF][START_REF] Groeneveld | Selective Adsorption of Terrestrial Dissolved Organic Matter to Inorganic Surfaces Along a Boreal Inland Water Continuum[END_REF][START_REF] Kothawala | Organic Matter Degradation across Ecosystem Boundaries: The Need for a Unified Conceptualization[END_REF]. We agree with this proposition and we even consider that grouping several mechanisms into a general term like priming is misleading because the interactive effect observed is the result of more than one mechanisms and the balance between each mechanism explain the intensity of the interactive effect observed. We considered particularly that grouping negative and positive priming under the same "conceptual umbrella" is a source of misunderstanding and confusion. Negative priming is generally a change of substrate by SOM consumers who switch to LOM when enough nutrients are available without a necessary increase in microbial activity. This mechanism is known as preferential substrate utilization hypothesis [START_REF] Sparling | Effect of barley plants on the decomposition of14C-labelled soil organic matter[END_REF] and is often used to explain negative priming [START_REF] Cheng | Rhizosphere feedbacks in elevated CO2[END_REF]Guenet, et al., 2010b). Furthermore, positive priming is necessarily a consequence of an increase in microbial activity, but here again several mechanisms have been proposed to explain priming, adding to the confusion. Priming is therefore a concept grouping together several mechanisms, and we suggest to individually study those mechanisms when possible or at least to measure enough variables to be able to identify the main driving mechanisms (enzymatic activities, nutrient release, microbial community structure and biomass, etc.). What we call priming is therefore not a mechanism, but a pattern; and the mechanisms behind this pattern should be better understood -in particular how the different mechanisms interact with each other.

In conclusion, our study shows that the priming effect may occur in aquatic ecosystems, in contrast to a preceding meta-analysis. The discrepancies between priming effects in the studies included herein result from the methodological and environmental differences between them. Altogether, these findings suggest that how the priming effect is tested and measured by aquatic ecologists has strong implications for its detection, sign and magnitude.

Figures legends

Figure 1 -Number of observations across all studies included in our meta-analysis reporting positive, negative and no priming effects. The coding of a given observation in one of these categories was based on the results reported for that experiment in each published paper, which compared SOM degradation between a control containing only stable organic matter and a treatment containing both stable and labile organic matter.

Figure 2 -

 2 Figure 2 -Boxplots showing the distribution of Priming Response Ratios (PRR) across

Figure 3 -

 3 Figure 3 -Forest plot of the different studies used to estimate the priming response ratio.

Figure 4 -

 4 Figure 4 -Variation in overall effect sizes of PRR estimated according to (a) how the

Figure 5 -

 5 Figure 5 -Variation in overall effect sizes of PRR estimated according to (a) whether

Acknowledgements

This study was made within The "Science Without Borders" program from CNPq (grant number 407155/2013-9). L. F. Sanches acknowledge CNPq for the financial support (grant number PDJ/CNPq 160977/2015-0) and N. A. C. Marino acknowledge CAPES for the financial support (NACM grant number PNPD/CAPES 20130877). The authors acknowledge Nuria Catalán and Simon Bowring for their valuable comments on the paper.

LFS and BG designed the study. LFS compiled and preprocessed the data. NACM wrote and ran the meta-analysis scripts. All the authors analyzed the results and wrote the paper.

The database used in this study is available at https://doi.org/10.5281/zenodo.4900670

Identification of the explaining factores

Unweighted mixed-effects meta-analysis model with p-value corrected using the Holm-Bonferonni method