Cédric Le Bris

Julia Mougin

Roxane Roquigny

Christophe Flahaut

Maryse Bonnin-Jusserand

Thierry Grard

Cédric Le Bris

Gaber Abdellrazeq
email: gaber.abdellatif@alexu.edu.eg

Sadok Khouadja
email: khouadja_sadok@yahoo.fr

Jung-Lim Lee
email: jlee@desu.edu

Jale Korun
email: jalekorun@yahoo.com

Dr Cedric Le Bris
email: cedric.le-bris@univ-littoral.fr

Cedric Sincerely

PhD Le Bris

Cédric Le Bris

Cédric Le Bris

Abundance and spatial patterns over time of Vibrionaceae and Vibrio harveyi in water and biofilm from a seabass aquaculture facility

Keywords: Aquaculture, MALDI-TOF MS, Vibrio harveyi, Vibrionaceae, real-time PCR Aquaculture, MALDI-TOF MS, Vibrio harveyi, Vibrionaceae, real-time PCR 9

Abundance and spatial patterns over

especially Vibrio harveyi. This disease can result in important economic losses or severe public 13 health problems. Furthermore, bacteria can form biofilms on the walls of aquaculture tanks, 14 leading to the persistence of potentially pathogenic bacteria on fish farms. Given the relationship 15 between abundance in the surrounding environment and prevalence in fish, monitoring the 16 presence of V. harveyi in rearing water and biofilms over time may help better understand the 17 dynamics of the pathogen and factors that increase the risk of vibriosis outbreaks. 18

In this study, the dynamics and spatial patterns of cultivable Vibrionaceae and V. harveyi in water 19 and biofilms from rearing tanks and in the cold-and hot-water inlets supplying the farm were 20 monitored for 7 months. Several potential seabass pathogens were isolated: 21

Photobacterium damselae, Vibrio alginolyticus, V. harveyi, Vibrio owensii and 22

Vibrio rotiferianus. However, V. harveyi remained the most problematic pathogen. Its relatively 23 constant presence in water and biofilm samples throughout the sampling campaign represents a 24 2 risk for vibriosis outbreaks. Moreover, the correlation between water temperature and the 25 abundance of V. harveyi suggests that the risk fluctuates throughout the year. Obtaining 26 qualitative data regarding the relative diversity of viable culturable Vibrionaceae and quantitative 27 data on the abundance of V. harveyi over time in a seabass aquaculture facility is the essential 28 first step for designing new solutions to manage vibriosis. 29

Introduction 30

In the context of rapid world population growth and the steep decline in marine fisheries catches, 31 the development of aquaculture is of significant interest for ensuring global food security and the 32 conservation of wild marine stocks. In Europe, seabass (Dicentrarchus labrax) is currently one of 33 the most farmed fish species and this high-value species is heavily traded [START_REF] Bostock | An assessment of the economic 497 contribution of EU aquaculture production and the influence of policies for its sustainable 498 development[END_REF]34 FAO, 2018). Bacterial diseases such as pasteurellosis (Photobacterium damselae subsp. 35 piscicida), photobacteriosis (Photobacterium damselae subsp. damselae), tenacibaculosis 36 (Tenacibaculum spp.), and vibriosis (Vibrio spp.) represent severe threats to the seabass 37 aquaculture sector [START_REF] Buchmann | Fish 503 diseases-an introduction[END_REF]Muniesa et al., 2020). They may not only result in 38 mass mortality events and highly negative economic effects, but are also potential zoonotic 39 sources and may pose a risk for human health [START_REF] Austin | Vibrios as causal agents of zoonoses[END_REF]. 40 Among them, vibriosis , caused by certain species of Vibrio, stand as the most significant disease, 41 affecting seabass at all stages of production chain [START_REF] Korun | Marine vibrios associated with diseased sea bass (Dicentrarchus 536 labrax) in Turkey[END_REF][START_REF] Le-Breton | Mediterranean finfish pathologies: present status and new developments in 538 prophylactic methods[END_REF]42 Muniesa et al., 2020;[START_REF] Pujalte | Virulence and molecular typing of Vibrio harveyi strains 587 isolated from cultured dentex, gilthead sea bream and European sea bass[END_REF]. This disease is characterized by anorexia, erratic 43 swimming behavior, exophthalmos, darkening of body color, pale gills, hemorrhages, ulcers, and 44 skin lesions [START_REF] Korun | Marine vibrios associated with diseased sea bass (Dicentrarchus 536 labrax) in Turkey[END_REF]. Several Vibrio species have been reported in seabass 45 infections: Vibrio alginolyticus, Vibrio anguillarum,Vibrio harveyi,Vibrio ordalii,46 Vibrio parahaemolyticus and Vibrio vulnificus [START_REF] Ghittino | 516 Emerging pathologies in aquaculture: effects on production and food safety[END_REF][START_REF] Kahla-Nakbi | Virulence and 524 enterobacterial repetitive intergenic consensus PCR of Vibrio alginolyticus strains isolated 525 from Tunisian cultured gilthead sea bream and sea bass outbreaks[END_REF]47 Khouadja et al., 2013;[START_REF] Korun | Marine vibrios associated with diseased sea bass (Dicentrarchus 536 labrax) in Turkey[END_REF]. Vibrio anguillarum has been the main significant 48 4 water sanitizers and may induce the persistence of potentially pathogenic bacteria in the 73 aquaculture facility [START_REF] Bourne | Biofilm development within a 500 larval rearing tank of the tropical rock lobster, Panulirus ornatus[END_REF][START_REF] Karunasagar | Biofilm formation by Vibrio harveyi on surfaces[END_REF]. Thus, the release of 74 V. harveyi from biofilms in the rearing water or the contact of fish with the walls of aquaculture 75 tanks may increase the prevalence of bacteria in fish and increase the risk of vibriosis outbreaks. 76 Therefore, monitoring the abundance of V. harveyi in the surrounding environment, such as in the 77 rearing water and biofilms, may be an indicator of the V. harveyi contamination of seabass and 78 thus of the probability of vibriosis outbreaks. Moreover, greater understanding of the correlation 79 between the abundance, dynamics, and spatial patterns of V. harveyi and environmental biotic 80 and abiotic factors might help to control vibriosis in aquaculture facilities. 81

Here, we report the dynamics and spatial patterns of cultivable Vibrionaceae and V. harveyi, 82 monitored in 2018 from April to October (months when vibriosis is most likely to strike). The 83 study was conducted on a semi-closed seabass farm, located in Northern France. The bacterial 84 abundance and relative diversity were determined from water and biofilm in rearing tanks, and in 85 the cold-and hot-water inlets supplying the farm. The dynamics of cultivable Vibrionaceae was 86 assessed by culturing them on selective media at 37°C. Presumptive cultivable Vibrionaceae were 87 then identified using matrix-assisted laser desorption/ionization-time of flight mass spectrometry 88 (MALDI-TOF MS) using an in-house database, called Luvibase, previously and specifically 89 designed to identify Vibrio species from the Harveyi clade (Mougin et al., 2020b). The 90 abundance of V. harveyi was estimated using a mreb-targeted real-time PCR (Mougin et al., 91 2020a). Environmental parameters and fish density and/or mortality were recorded through the 92 sampling campaign to identify the environmental factors that best correlate with bacterial 93 abundance. Overall, the objective was to gain a greater understanding regarding the dynamics 94 over time and spatial pattern of potentially pathogenic bacteria for seabass. This understanding 95 can help design prophylactic measures to better manage vibriosis outbreaks. 96

Material and methods 97

Sampling site 98

This study was conducted from April to October 2018 in Aquanord Ichtus, a fish farm located in 99 Gravelines, France along the southwestern coast of the North Sea. Because the aquaculture 100 system is situated near a nuclear power plant, the site is monitored annually in order to detect any 101 abnormalities in the development of the natural marine environment [START_REF] Antajan | Surveillance 484 écologique du site de production électronucléaire de Gravelines Novembre[END_REF]. 102

The farm is an intensive semi-closed system managed by a private company. This company 103 currently raises seabass (Dicentrarchus labrax) and seabream (Sparus aurata) during the on-104 growing phase in flow-through tanks constructed from concrete. The water supply is regulated 105 via two water inlets: a "cold-water inlet" from the natural marine environment and a "hot-water 106 inlet" from the cooling system of a nuclear power plant nearby (Fig. 1). Water flow into the 107 rearing tanks is regulated using a valve to maintain uniform water quality and temperature 108 through the year. Overall, from mid-July to mid-September, the rearing tanks are supplied by the 109 cold-water inlet only. During the rest of the year, the rearing tanks are supplied by both cold-and 110 hot-water inlets. Fish are fed daily and aeration is provided to maintain an optimal level of 111 dissolved oxygen (DO). Farmers use a commercial vaccine against V. anguillarum and an annual 112 autogenous vaccine against V. harveyi. The latter is developed annually from pathogens isolated 113 from the spleens of moribund fish during previous outbreaks. 114 Three similar rearing tanks were chosen for this study. The water capacity of each tank was 75 115 m 3 , with a water column of 1.3 m and a holding capacity of around 30 000 seabass. Average fish 116 stock density was 48.13 kg.m -3 , with an average fish weight of 200 g. During the sampling 117 campaign, the aquaculture facility provided weekly biomass and mortality data from each rearing 118 tank. 119

Sample collection and environmental parameters 120

Two types of samples, water and biofilm, were collected from three tanks containing seabass and 121 from the cold-and hot-water inlets. Water samples were collected weekly from tanks and hot-122 and cold-water inlets. Biofilm samples were collected every two weeks from tanks. Both types of 123 samples were harvested as previously detailed in Mougin et al. (2020a). Briefly, a volume of 1 L 124 of water was collected in a sterile bottle in triplicate, from both water inlets and from the three 125 rearing tanks, just below the surface of the water. Pieces of concrete, made of the same material 126 used to build the tanks and placed 20 cm below the surface of the water, were collected in 127 triplicate from the three rearing tanks (Appendix A). Samples were maintained on ice during 128 transport to the laboratory. A total of 465 water samples and 144 biofilm samples were thus 129 collected during the sampling campaign. 130

During sample collection, water temperature, pH, salinity, and conductivity were measured in 131 each tank and in both inlets, within 50 cm of the water surface using a multi-parameter probe 132 (Odeon Open X, Aqualabo, Champigny-sur-Marne, France). DO concentration was also 133 measured in rearing tanks only using a Handy Polaris DO meter (OxyGuard, Farum, Denmark). 134

Sample preparation 135

Samples were processed as previously described in Mougin et al. (2019) and Mougin et al. 136 (2020a). Briefly, water samples were filtered through 0.45 μm pore-size nitrocellulose filters 137 (Sartorius, Göttingen, Germany). Filters were then immersed in 25 mL of Luria-Bertani broth 138 supplemented with 20% NaCl (LBS) and 20% glycerol, and stored at -80 °C until analysis. 139

Biofilms from the concrete samples were collected using a homemade sterile stainless steel jig by 140 swabbing with two 2.34 cm 2 swabs. The swabs (150C, Copan, Brescia, Italy) were then 141 immersed in 3 mL of LBS with 20% glycerol and stored at -80 °C until analysis. Subsequently, 142 both types of samples were defrosted at room temperature and vortexed for 3 min to dislodge 143 bacteria from the filters and swabs. Filters and swabs were removed the LBS-glycerol solution 144 and the liquid was centrifuged at 8000×g for 10 min. The cell pellets were then dissolved in 3 mL 145 of physiological water (0.9% NaCl) and centrifuged at 8000×g for 10 min. Supernatants were 146 removed and the cell pellets were dissolved in 2 mL of physiological water. Samples were then 147 split into two subsamples. One subsample of 1800 µL was used to quantify V. harveyi using real-148 time PCR. The other 200 µL subsample was used for relative quantification and identification of 149 presumptive cultivable Vibrionaceae by plating on selective agar media and by MALDI TOF MS. 150

Quantification of V. harveyi using real-time PCR 151

The 1800 µl subsample was centrifuged at 8000×g for 10 min and the supernatant was removed. 152

Total DNA was extracted from the cell pellet, using the DNeasy PowerBiofilm kit (Qiagen,153 Hilden, Germany) in accordance with manufacturer's protocol, selected according to Mougin et 154 al. (2020a). Relative quantification of V. harveyi based on a standard curve was performed 155 according to the previously optimized real-time PCR protocol in Mougin et al. (2020a), using 156

V. harveyi-specific primers targeting the mreB gene (synthesized by TIB MOLBIOL 157 Syntheselabor GmbH, Berlin, Germany). Briefly, pure DNA of the collection strain V. harveyi 158 LMG 4044 was extracted using the DNeasy Blood&Tissue kit (Qiagen, Hilden, Germany). Purity 159 was verified on a DeNovix DS-11 spectrophotometer (UV spectroscopy, Clinisciences, Nanterre, 160 France) and the quantity was determined using a Qubit 3.0 fluorometer (dsDNA High-Sensitivity 161 assay), (Invitrogen, Carlsbad, CA, USA). Then, standard curves were generated from a series of 162 10-fold dilutions of pure DNA of the collection strain V. harveyi LMG 4044. For each assay, the 163 calibration curve was plotted using the means of the threshold cycle (CT) values from two 164 replicate series versus the logarithm of each dilution factor. Each extracted environmental DNA 165 template was analyzed at a 10-fold dilution to avoid the effects of real-time PCR inhibitors. 166 Genome copy equivalent (GE) concentrations were then estimated, taking the dilution factor into 167 account. All quantitative PCR reactions were run on a LightCycler ® 480 (Roche Diagnostics, 168

France) with a positive control (LMG 4044 V. harveyi DNA), a negative control (CIP 70.67 169 V. campbellii DNA), and a no template control (NTC), DNA-free. Melting curve analysis was 170 performed to confirm the specificity of the fluorescent signals. Each extracted environmental 171 DNA template was analyzed at least twice to ensure robust measurements. 172

Quantification of presumptive Vibrionaceae and identification using MALDI-TOF MS 173

An aliquot of 100 µL from the second subsample was plated on thiosulfate-citrate-bile salts-174 sucrose (TCBS) agar (Biokar Diagnostics, Beauvais, France). The remaining 100 µL was serially 175 10-fold diluted in physiological water (10 -1 , 10 -2 , 10 -3 ) and 100 µL of each dilution was plated 176 onto TCBS agar. All plates were then incubated at 37 °C overnight. Presumptive cultivable 177

Vibrionaceae colony forming units (CFUs) were counted using a Scan 500 plate reader 178 (Interscience, Saint-Nom-la-Bretèche, France) and the concentration in each sample was 179 estimated taking the dilution factor into account. 180 Different colony morphotypes were screened on the basis of color (green or yellow), color shade, 181 size, circumference (smooth or irregular) and presence/absence of a halo within 10 min after 182 removal from the incubator. One colony of each different morphotype was randomly selected and 183 incubated on LBS agar at 37 °C overnight. The morphological features of each selected colony 184 were recorded. Pure bacteria were stocked in LBS broth supplemented with 20% glycerol at -185 80 °C until identification using MALDI-TOF MS. 186 Subsequently, once defrosted, these bacterial isolates were subcultured on marine agar (MA), 187 (Difco Laboratories, Detroit, MI, USA) and incubated for 24 h, at 37 °C. Then, a single colony 188 was plated on MA (Difco Laboratories) and incubated 24 h, at 37 °C to ensure the purity of the 189 isolate. Preparation of bacterial extracts, target-loading and acquisition of MALDI-TOF MS 190 profiles were performed as previously described in Mougin et al. (2020b). Briefly, the cellular 191 proteins of each bacterial isolate were extracted from bacterial cells according to manufacturer's 192 recommendations (Bruker France, Wissembourg, France). The extracts were stored at -20 °C 193 until use. Then, 1 µL of the supernatant from each protein extract was deposited onto a clean target ground steel microtiter plate (Bruker France) in four replicates. After air drying, 1 µL of a 195 10 mg.mL -1 matrix solution of α-cyano-4-hydroxycinnamic acid (CHCA) in 50% acetonitrile and 196 2.5% trifluoroacetic acid (Sigma-Aldrich, St. Louis, MO, USA) was overlain on each spot. 197 MALDI-TOF MS analysis was performed using an Autoflex SpeedTM (Bruker France), running 198 Flexcontrol 3.4 software (Bruker France). The Bruker bacterial test standard (BTS,Bruker 199 France) was used to calibrate the mass spectrometer before each run, according to the 200 manufacturer's recommendations. Mass spectra were acquired in the positive linear ion mode 201 across a mass/charge (m/z) ratio of 2000-20,000 Da. Mass spectra were acquired using the 202 manufacturer's automatic MBT_FC.par method. For each MALDI-TOF MS profile, mass spectra 203 were obtained from 5000 laser shots in 1000 shot steps performed randomly from different areas 204 of the spot. 205

Each MALDI-TOF MS profile was first compared with the mass spectra profiles (MSPs) of the 206 Bruker BioTyper database ver.9.0.0.0 implemented with the Luvibase, a supplemental, in-house 207

Vibrio database (Mougin et al., 2020b). The degree of concordance between experimental 208 MALDI-TOF MS profiles and the MSPs was evaluated using a log-score calculated using the 209 MALDI BioTyper Compass Explorer ver.4.1 (Bruker France). A log-score exceeding 2.3 210 indicated a highly probable identification at the species level; a log-score between 2.0 and 2.3 211 indicated a probable identification at the species level; a log-score between 1.7 and 2.0 indicated 212 a probable identification at the genus level only; and a log-score below 1.7 indicated no 213 significant similarities between MSPs included in the databases and the unknown profile. 214

Statistical analysis 215

abundance (3.37×10 2 CFU.mL -1 ) was observed in late May at a temperature of 15.0 °C, and water 288 temperature continued to increase slightly (average +0.7 °C each week from April to June). No 289 bacteria were detected in October and April. 290

In the hot-water inlet, the presumptive detected culturable Vibrionaceae followed more or less the 291 same pattern, ranging from 3.11×10 2 to 6.71×10 4 CFU.mL -1 in abundance. Maximum abundance 292 was detected in late June when the temperature reached 24 °C. Then, abundance tended to 293 decrease slightly until mid-October, when a peak of 5.99×10 2 CFU.mL -1 was detected at a 294 temperature of 24.9 °C. As in the cold-water inlet, a peak in abundance (6.43×10 3 CFU.mL -1 ) 295 was detected in late May at a water temperature of 24.7 °C in this compartment. 296

In the rearing tanks, the presumptive culturable Vibrionaceae detected in water ranged from 297 2.28×10 3 to 1.74×10 5 CFU.mL -1 . Presumptive detected culturable Vibrionaceae were enumerated 298 from mid-April until the end of the study. The abundance tended to increase slowly and 299 constantly with an average + 0.20 log per week until August, the warmest month of summer with 300 the maximum recorded temperature (21.7 °C). Subsequently, abundance decreased slightly in 301 September, and hit a peak of 2.50×10 4 CFU.mL -1 in mid-October, when the temperature jumped 302 back to 19.1 °C. The presumptive attached culturable Vibrionaceae detected in biofilms ranged 303 from 2.51×10 5 to 2.03×10 7 CFU.cm -2 . Presumptive attached culturable Vibrionaceae were 304 enumerated from mid-May until the end of the study. As observed in the water samples, 305 abundance tended to increase slowly and constantly with an average + 0.27 log per week until 306 August, then decreased slightly. Interestingly, a peak in the abundance of 2.29×10 6 CFU.cm -2 307 occurred with a peak in temperature in mid-October, similar to the pattern for the water samples 308 and the hot-water inlet. 309

Quantification of V. harveyi using real-time PCR 310

and each sample. According to the statistical analysis, the average abundance of presumptive 312 culturable Vibrionaceae detected in the water from the cold-and hot-water inlets and rearing 313 tanks were significantly different (each p-value < 0.05). In contrast, there were no significant 314 differences between the average abundances observed in the three rearing tanks, for either the 315 water or biofilm samples (each p-value > 0.05). Consequently, for each sampling time, the 316 average abundances detected in the three rearing tanks were pooled together. 317

Overall, the average estimated quantity of V. harveyi was higher in hot-water inlet than in the 318 cold-water inlet. In the cold-water inlet, abundance of detected V. harveyi, ranged from 1.35 to 319 8.57 GE.mL -1 (Fig. 3.a). A few peaks were detected in late May, mid-June, early July, and mid-320

September. 321

Successive screenings for V. harveyi over 5 weeks demonstrated a rapid increase in abundance 322 from mid-July to mid-August, when temperatures reached their highest values. 323

In the hot-water inlet, abundance of detected V. harveyi ranged from 4.62 to 2.11×10 2 GE.mL -1 . 324

V. harveyi was first detected in mid-May when the temperature reached 25.1 °C for the first time 325 in the year. Abundance increased slowly (average + 0.11 log per week) until early June when the 326 concentration reached 1.41×10 2 GE.mL -1 , and then decreased. The average abundance detected in 327 late June and mid-July was relatively high, with abundance decreasing slightly thereafter 328 (average + 0.20 log per week), dropping to an absence of detection until a last peak of 4.62 of 329 GE.mL -1 in mid-October when the temperature reached 24.9 °C. 330

In the rearing tanks, detected V. harveyi abundance ranged from 3.72 to 9.51×10 1 GE.mL -1 (Fig. 331 3.a). V. harveyi was first detected in April when the temperature reached 18.0 °C. The maximal 332 abundances were recorded in mid-May (9.51×10 1 GE.mL -1 ), mid-July (7.88×10 1 GE.mL -1 ), and 333 mid-October (7.65×10 1 GE.mL -1 ), when the rearing water temperatures reached 19.0, 19.6 and 334 19.1°C, respectively. Nevertheless, V. harveyi was detected in April when no Vibrio bacteria 335 were recorded in the cold-and hot-water inlets. The abundance of attached V. harveyi detected in 336 biofilms ranged from 1.45×10 3 to 3.25 ×10 3 GE.cm -2 (Fig. 3.b). Attached V. harveyi were 337 enumerated from mid-May (1.64 ×10 3 GE.cm -2 ) until mid-October (2.43×10 3 GE.cm -2 ), with no 338 detection in early September or in early October. 339

Influence of environmental factors on cultivable Vibrionaceae and V. harveyi dynamics 340

Statistical analysis highlighted correlations between water temperature and the abundance of 341 presumptive Vibrionaceae in the cold-water inlet (p-value=0.0065). A positive correlation was 342 detected between water temperature (p-value=0.0005) and the abundance of presumptive 343 Vibrionaceae in biofilms. 344 Moreover, statistical analyses highlighted a positive correlation between water temperature and 345 the abundance of V. harveyi in the cold-water inlet (p-value=0.0186) and in water from rearing 346 tanks (p-value=0.0198). A positive correlation was also detected between water temperature and 347 the abundance of V. harveyi in biofilms (p-value<0.0001). 348

Discussion 349

The seabass aquaculture sector is being challenged by the emergence of recurring vibriosis 350 outbreaks caused by V. harveyi [START_REF] Vendramin | 615 Fish health in Mediterranean Aquaculture, past mistakes and future challenges[END_REF]. The prevalence of the pathogen in fish 351 is highly correlated with the abundance of the pathogen in the surrounding environment (Kim and 352 Lee, 2017). Although the contamination of fish is not the only factor that can exacerbate the 353 development of the disease, the abundance of V. harveyi, in rearing water and biofilm may be an 354 accurate indicator of the risk of vibriosis outbreaks. Thus, deeper understanding of the dynamics 355 and spatial patterns of V. harveyi in the aquaculture environment is needed. 356

In this study, we assessed the temporal and spatial dynamics of Vibrionaceae, and the 357 presumptive pathogen V. harveyi in particular, from April to October 2018 on a fish farm located 358 in Northern France. Three rearing tanks were chosen from a facility frequently affected by 359 vibriosis. In particular, vibriosis outbreaks, mostly caused by V. harveyi, were recorded in 2017 360 on this fish farm. Furthermore, a few strains of V. jasicida, V. rotiferianus, V. owensii, 361

V. tasmaniensis, and V. gigantis were also isolated from the spleens of moribund seabass 362 (Mougin et al., 2020a;Mougin et al., 2020b). In 2018, vibriosis outbreaks caused by 363 V. anguillarum were recorded (Appendix B). According to the aquaculture facility operators, 364 these latter outbreaks were due to a delay in vaccine delivery and were quickly and successfully 365 managed. Some strains of V. harveyi were isolated from few moribund fish (Appendix B), but no 366 V. harveyi vibriosis outbreak has been recorded on the fish farm, particularly in the three rearing 367 tanks used during our monitoring study. 368 A selective culture method was used during the survey (TCBS for 24 h at 37 °C) in order to 369 mostly isolate Vibrionaceae belonging to the Harveyi clade, which includes the main pathogens 370 for seabass. We are aware that not all Vibrionaceae are able to grow under these conditions and 371 consequently, the diversity and the abundance of the presumptive Vibrionaceae detected could 372 have been underestimated. Among potentially pathogenic bacteria for seabass, P. damselae, 373

V. alginolyticus, V. owensii, V. rotiferianus, and V. harveyi were isolated during our sampling 374 campaign. The species P. damselae is divided into two subspecies with clinical and 375 epidemiological differences, both affecting seabass [START_REF] Essam | Pathogenesis of 511 Photobacterium damselae subspecies infections in sea bass and sea bream[END_REF]Vázquez and Muñoz-376 Cueto, 2014). P. damselae subsp. piscicida (formerly Pasteurella piscicida) is known as the 377 causative agent of a severe aquatic disease called pasteurellosis, and P. damselae subsp. damselae 378 (formerly Vibrio damsela) is responsible for photobacteriosis commonly defined as sporadic 379 pathologies [START_REF] Buchmann | Fish 503 diseases-an introduction[END_REF]. Nonetheless, this latter disease had been recognized as an 380 epizoonotic agent, transmitted by infected fish, and may cause public health problems (Rivas et 381 al., 2013). In our study, presumably, only subspecies damselae was recorded, but the MALDI 382 BioTyper database cannot discriminate between these two subspecies [START_REF] Pérez-Sancho | Differentiation of Photobacterium damselae subspecies using matrix-assisted 578 laser-desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) in fish 579 isolates[END_REF]. 383

Given that no mortalities caused by P. damselae have been recorded, no further analysis was 384 pursued. In the Vibrio genus, the Harveyi cladeespecially V. alginolyticus, V. harveyi 385 V. owensii, and V. rotiferianus were the most frequently isolated species on the fish farm. 386

Importantly, these species have already been isolated from moribund seabass and are considered 387 as potential pathogens on the farm. Nevertheless, V. harveyi remains the main pathogen 388 responsible for recurrent vibriosis outbreaks. 389

Interestingly, even though no vibriosis outbreak was recorded, isolates of V. harveyi were 390 detected in the rearing tanks from water and biofilm, throughout practically the whole sampling 391 campaign. The development of vibriosis occurs due to disruptions between host-pathogen-392 environment interactions [START_REF] Snieszko | The effects of environmental stress on outbreaks of infectious diseases of 597 fishes[END_REF][START_REF] Toranzo | A review of the main bacterial fish diseases 605 in mariculture systems[END_REF]. Thus, many factors, such as the 393 susceptibility and physiological state of the host, the pathogenicity and virulence of the pathogen, 394 and the influence of environmental stress conditions, must be considered. At this fish farm, the 395 absence of vibriosis outbreaks was attributed to the efficiency of the novel annual autogenous 396 vaccine. However, in practical terms, this type of vaccine sometimes appears less efficient from 397 one year to the next and must be regularly renewed, incurring high costs. Another hypothesis is 398 that the strains of V. harveyi present on the farm during 2018 were not highly virulent. Our study 399 focused on the abundance of all V. harveyi strains without distinguishing pathogens from non-400 pathogens. There is thus a possibility that the pathogenic isolates detected and collected in 2018 401 are scarce. 402

Environmental factors may also have an impact on the development of the disease. The 403 correlation between the abundance of V. harveyi and water temperature indicates that the risk of 404 vibriosis outbreaks may vary throughout the year. In the natural marine environment, previous 405 studies have highlighted that the abundance of Vibrio spp. may follow seasonal variation in 406 temperate regions (Johnson et al., 2012;[START_REF] Martinez-Urtaza | Environmental determinants of the occurrence and distribution of Vibrio 541 parahaemolyticus in the rias of Galicia, Spain[END_REF]. Water temperature and 407 salinity are considered as the most effective predictors of temporal and spatial distributions. 408 However, in a semi-closed aquaculture system, even though tanks are supplied with natural 409 marine seawater, water quality is extensively monitored and maintained as constant as possible. 410

Consequently, in our study, the environmental parameters monitored in rearing tanks (i.e. pH, 411 salinity, conductivity, and DO) did not vary widely. Water temperature was generally constant, 412 but the month of June and July showed temperatures above 20 °C. Increased prevalence of 413 V. harveyi in oysters (Crassostrea gigas and Crassostrea virginica) was detected at temperatures 414 above 20 °C [START_REF] Pujalte | Aerobic and facultative anaerobic 590 heterotrophic bacteria associated to Mediterranean oysters and seawater[END_REF]. Moreover, a previous study [START_REF] Pujalte | Virulence and molecular typing of Vibrio harveyi strains 587 isolated from cultured dentex, gilthead sea bream and European sea bass[END_REF] reported 415 increased prevalence of V. harveyi in European seabass and gilthead seabream during warm 416 months. Consequently, the warmer months of summer may represent a higher risk for vibriosis 417 outbreaks. Furthermore, temperature may not only influence the prevalence of the pathogen, but 418 also the virulence and the physiological state of the host, disturbing the host-pathogen 419 relationship [START_REF] Paillard | Effect of temperature on defense parameters in Manila 574 clam Ruditapes philippinarum challenged with Vibrio tapetis[END_REF][START_REF] Travers | Influence of temperature and spawning effort on Haliotis tuberculata mortalities 608 caused by Vibrio harveyi: an example of emerging vibriosis linked to global warming. 609[END_REF]. In the years ahead, the risk of vibriosis 420 may increase with the rise of water temperature, due to global warming [START_REF] Travers | Influence of temperature and spawning effort on Haliotis tuberculata mortalities 608 caused by Vibrio harveyi: an example of emerging vibriosis linked to global warming. 609[END_REF]421 Vezzulli et al., 2015). 422

In the rearing tanks, the abundance of presumptive cultivable Vibrionaceae appeared to follow a 423 seasonal pattern, with the highest values in August and the lowest in April. On the contrary, there 424 was no clear seasonal pattern in the variation of V. harveyi abundance. This difference can be 425 attributed to the divergence between monitoring methods. The real-time PCR method is based on 426 a DNA target and provides an estimation of the quantity of cultivable bacteria, viable but not 427 cultivable (VBNC) bacteria, and residual DNA released by dead bacteria. Quantification by plate 428 count on selective media provides an estimation of the quantity of cultivable bacteria only, and 429 does not allow recovery of VBNC bacteria. However, the quantification of VBNC bacteria in the 430 biofilms in this study. This approach may be the key to designing new control measures that can 455 then be integrated in a preventive holistic strategy including hosts, pathogens, and the 456 environment to control vibriosis. 457

Conclusion 458

In conclusion, the abundance of cultivable Vibrionaceae increased in the rearing tanks during the 459 warm summer months. These bacteria may come from the water inlets, but biofilms may also be 460 a reservoir for potential pathogenic bacteria for seabass. Importantly, several pathogenic bacterial 461 species were isolated from rearing water and biofilm samples: P. damselae, V. alginolyticus, 462

V. harveyi, V. owensii and V. rotiferianus. Overall, V. harveyi is considered as the main pathogen 463 on the fish farm and its constant presence represents a risk for vibriosis outbreaks. The correlation 464 between its abundance and water temperature suggests that this risk may increase with the rise of 465 water temperature, caused by global warming. Moreover, the probability of vibriosis outbreaks 466 may be increased by the presence of V. harveyi in biofilms, which may facilitate resistance 467 against antibiotics, water sanitizers, and environmental fluctuations. 468 Future studies must now assess the pathogenicity of virulence of the isolates collected in this 469 study. The pathogenic strains isolated from biofilms can be then used to study biofilm dynamics 470 and to design and develop anti-biofilm control measures. Because V. harveyi affects not only 471 seabass, but also a wide range of crustaceans, mollusks, and fishes, these measures can be then 472 adapted to other aquaculture facilities. 473 474

Acknowledgements 475

Julia Mougin would like to thank the Hauts-de-France Regional Council for its financial support 476 of her PhD studies. This work was funded by the French government and the Hauts-de-France 477

628Figure 1 .Figure 2 .

 12 Figure 1. Schematic representation of the sampling areas on the fish farm, illustrating the 629

Figure 1 .

 1 Figure 1. Schematic representation of the sampling areas on the fish farm, illustrating the sampling

Figure Table 1 .

 1 Figure

Table 1 .

 1 Means of parameters recorded from April to October 2018 in the aquaculture facilities. 626

	Sampling	Temperature (°C) pH			Salinity		Conductivity		Dissolved		Fish density		Fish mortality per
	months										(ms.cm -1 )		oxygen		(kg.m -3 )		week (%)
														(mg.L -1 )
		Cold-water inlet	Hot-water inlet	Rearing tanks	Cold-water inlet	Hot-water inlet	Rearing tanks	Cold-water inlet	Hot-water inlet	Rearing tanks	Cold-water inlet	Hot-water inlet	Rearing tanks	Tank 1	Tank 2	Tank 3	Tank 1	Tank 2	Tank 3	Tank 1	Tank 2	Tank 3

a study conducted by scientists from the "UMR 1158 BioEcoAgro, Institut Charles Viollette (Univ. Littoral Côte d'Opale), Boulogne-sur-Mer, France".

30

Figure 3. Fluctuation in abundance of a. presumptive culturable Vibrionaceae on TCBS agar, 643 37 °C, and b. Vibrio harveyi in the cold-and hot-water inlets, water and biofilm samples from 644 rearing tanks. For inlet samples, abundance values are the mean of three samples, collected 645 simultaneously. For rearing tanks, abundance values are the mean of nine replicates, 646 corresponding to the three replicates collected simultaneously from each of the three rearing 647 tanks. The area around the curves represent the 95% confidence intervals for the abundance 648 index. Water temperature in all compartments are also shown. The on-growing batch of fish was removed and transported to a new rearing tank more suitable for their size, and a new batch of fish of smaller size was put in the rearing tank used in this study

Declaration of interests

☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Conflict of Interest

Supplementary Material

Click here to access/download Supplementary Material Supplemental material.docx


Ioana A Cristea
email: ioana.cristea@unipv.ittel

Florian Naudet
email: floriannaudet@gmail.com

Laura Caquelin
email: lauracaquelin@gmail.com

Meta-research studies should improve and evaluate their own data sharing practices

Keywords: meta-research, data sharing, meta-analysis, reproducibility

Data sharing is gradually becoming a requirement across all fields of science, owing to its key benefits in verifying the reproducibility of findings and reusing existent data for new purposes. Although meta-research studies are complex, time-consuming and hinge on the availability of data produced and curated by others, there has been little focus on how they make their own data available. This is in stark contrast with the heightened attention data sharing has received in clinical research. Yet, as secondary data users par excellence, metaresearchers are ethically bound to both improving and evaluating data sharing practices, as well as correctly sharing their own data. We contrast particularities of data sharing in meta-research and clinical research, such as benefits, barriers, inadequate and potentially pervasive sharing practices. We conclude with an array of concrete and tailored recommendations for improvement.

Meta-research is an evolving scientific discipline covering "a wide range of theoretical, observational, and experimental investigations designed to study research itself and its practice" [START_REF] Ioannidis | Meta-research: Why research on research matters[END_REF], with the aims of evaluating and improving research practices, such as reporting of methods and findings, or sharing data, code and materials for further scrutiny and reuse [START_REF] Ioannidis | Meta-research: Evaluation and Improvement of Research Methods and Practices[END_REF].

Evidence-synthesis studies like systematic reviews and meta-analyses are prototypical metaresearch, but other examples include examinations of journal policies, citations practices or potential sources of bias across research topics or methods. Common across these investigations is the frequent reliance on secondary data, coming from already published reports or public databases and that should at least in theory be available for independent consultation. However, incomplete reporting of primary articles [START_REF] Turner | Consolidated standards of reporting trials (CONSORT) and the completeness of reporting of randomised controlled trials (RCTs) published in medical journals[END_REF], language barriers, and access limitations by publishers often imply that some of the data used in a meta-research study cannot be easily retrieved (e.g., obtained by personal communication from the original authors). Moreover, some meta-research studies require individual participant data (IPD).

Benefits of data sharing

Sharing of data underlying published or unpublished research has numerous and noteworthy benefits [START_REF] Ross | Clinical research data sharing: what an open science world means for researchers involved in evidence synthesis[END_REF][START_REF] Naudet | Medical journal requirements for clinical trial data sharing: Ripe for improvement[END_REF]. It minimizes the possibility of different research groups unknowingly duplicating efforts to collect the same type of data, thereby reducing costs and participant burden. It maximizes the value of already collected data, allowing reutilization to address new research questions. It enables other researchers to verify and replicate findings, or refine and refute them by employing different analyses, as compellingly demonstrated by initiatives such as the SPRINT Data Analysis Challenge (https://challenge.nejm.org/pages/home). It is of crucial importance in uncovering and substantiating data fabrication or fraud [START_REF] Bey | Researchers raise concerns of fraud and ambiguity in two studies authored by Dan Ariely[END_REF][START_REF] Berenbaum | Signing at the beginning makes ethics salient and decreases dishonest self-reports in comparison to signing at the end[END_REF]. Moreover, data sharing brings important indirect advantages, for example, enhancing the visibility and impact of published research. One study J o u r n a l P r e -p r o o f [START_REF] Christensen | A study of the impact of data sharing on article citations using journal policies as a natural experiment[END_REF] showed that articles with data available versus those without accrue almost twice as many citations (increase of 97 citations, standard error 34, over a mean of approximately 100).

Another investigation indicated that articles where data availability statements included a link to data in a repository had an approximately 25% higher citation impact [START_REF] Colavizza | The citation advantage of linking publications to research data[END_REF]. Data sharing can also foster new collaborations and boost opportunities for attracting research funding, as well as for hiring, promotion or tenure as more institutions and funders begin to embrace "responsible metrics". For example, the "responsible indicators for assessing scientists" (RIAS) approach advocates for openness, understood as "facilitating dissemination and use of research data and results by others", as one of its six founding principles [START_REF] Moher | Assessing scientists for hiring, promotion, and tenure[END_REF]. Finally, for metaresearchers in particular, whose scholarship focuses on identifying and correcting deviations from how science ought to be conducted, appropriate data sharing represents a core value. For example, the "Manifesto for Reproducible Science [START_REF] Munafò | A manifesto for reproducible science[END_REF]" mentions open data and materials as key initiatives for encouraging transparency and open science.

The plethora of benefits resulting from data sharing motivated renewed calls to make it a mandatory condition for publishing clinical research [START_REF] Naudet | Medical journal requirements for clinical trial data sharing: Ripe for improvement[END_REF][START_REF] Taichman | Data Sharing Statements for Clinical Trials: A Requirement of the International Committee of Medical Journal Editors[END_REF]. At the same time, initiatives and tools aimed at supporting and facilitating sharing, such as guidelines, practical recommendations and sharing platforms have proliferated [START_REF] Ross | Clinical research data sharing: what an open science world means for researchers involved in evidence synthesis[END_REF][START_REF] Rathi | Sharing of clinical trial data among trialists: a cross sectional survey[END_REF][START_REF] Hutchings | A systematic literature review of researchers' and healthcare professionals' attitudes towards the secondary use and sharing of health administrative and clinical trial data[END_REF]. However, most of the conversation surrounding data sharing has focused on clinical and other primary research.

Nevertheless, data sharing is at least as pertinent for meta-research and evidence synthesis [START_REF] Ross | Clinical research data sharing: what an open science world means for researchers involved in evidence synthesis[END_REF],

fields reliant on already collected and reported data. First, in these domains, researchers directly depend on data produced by other investigators, so have an ethical obligation to reciprocate by sharing their own data. Second, concerns have been amassing about the reproducibility of meta-analyses [START_REF] De Vrieze | The metawars[END_REF], a prototypical type of meta-research. To verify such concerns, access to the underlying data and code is crucial. However, systematic examinations of data sharing practices for meta-research studies have been limited. A recent investigation [START_REF] Page | Reproducible research practices are underused in systematic reviews of biomedical interventions[END_REF] of a cohort J o u r n a l P r e -p r o o f of meta-analyses showed that based on data reported by the studies included in each, it would be theoretically possible to reproduce each meta-analytic estimate, subgroup or sensitivity analyses in 65% of the meta-analyses. However, researchers did not attempt to re-extract the data from the primary studies and reproduce these analyses themselves. Only 29% of the metaanalyses provided access to a file including all data used for the meta-analysis and the code to reproduce the analyses. Conversely, an examination that effectively attempted to reproduce findings [START_REF] Maassen | Reproducibility of individual effect sizes in meta-analyses in psychology[END_REF] in a sample of meta-analyses by re-extracting the necessary data from the primary included studies and employing the effect size calculation method described in the metaanalysis indicated that almost 50% of the primary effect sizes could not be reproduced, leading to (mostly non-consequential) discrepancies in around 40% of the meta-analyses. Third, incomplete reporting implies additional information is often independently retrieved (e.g., through direct contact with investigators) and thus will remain inaccessible to other researchers, unless shared. An ongoing ambitious research program REPRISE (REProducibility and Replicability In Syntheses of Evidence) [START_REF] Page | The REPRISE project: protocol for an evaluation of REProducibility and Replicability In Syntheses of Evidence[END_REF] will shed more light by evaluating the completeness of reporting and data sharing and attempting to computationally reproduce 300 systematic reviews. Though data sharing practices of meta-analyses are clearly wanting, it is unknown whether similar issues plague the field of meta-research more generally.

Potential barriers to data sharing

The concept of data sharing is usually linked to personal identification or health related data, for which there are justified concerns associated with improper data protection, such as confidentiality or security. Conversely, most meta-analyses and meta-research studies involve extracting already reported data from a corpus of sources selected based on pre-specified criteria. The extracted information is usually synthesized in categories, which are then summarized descriptively or aggregated statistically. Often, throughout the process of data

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selection and extraction, multiple independent raters are involved. The process is lengthy, resource-and time-consuming, but in most meta-research studies, it does not require anonymization, and there are no confidentiality restrictions. An important exception is represented by meta-analyses using IPD, where similar concerns apply as for primary clinical research. Precisely because conducting meta-research studies requires a significant concentration of resources and time, it is crucial that all data and other materials generated (e.g., coding manuals, sheets with predefined formulas) are accessible to other researchers, so as to accelerate future data collection, minimize research costs and avoid duplication of the same work.

Most initiatives to encourage and improve data sharing originate in clinical research.

Table 1 lists several barriers and proposed initiatives to encourage and facilitate data sharing identified in this field, inspired by a recent systematic review on the views of researchers and healthcare professionals [START_REF] Hutchings | A systematic literature review of researchers' and healthcare professionals' attitudes towards the secondary use and sharing of health administrative and clinical trial data[END_REF]. Almost all are translatable to sharing data from meta-analyses and meta-research studies generally. For example, knowledge of what should be shared from the data collected or synthesized, as well as which are the most appropriate ways of making the datasets available are important challenges for researchers working with both primary and secondary data. The dearth of procedural standards (Table 1) mandated by journals, funders or other institutions, as well as the lack of technical skills about compiling and curating usable datasets for sharing are both important obstacles. Likewise, concerns related to data misuse, hostile reanalysis initiatives or being placed in a competitive disadvantage by losing some of the opportunities to exploit collected data for subsequent publications are pertinent to both meta-research and clinical research more generally. Indeed, secondary data users like metaresearchers have (in)famously been likened to "data parasites" [START_REF] Longo | Data Sharing[END_REF].

Conversely, some barriers such as the need to anonymize data or protect research participants do not apply to the bulk of meta-research that relies on aggregate data. Relatedly, J o u r n a l P r e -p r o o f the need of additional funding to prepare datasets for sharing is more contained for metaresearch, given there is usually no need to ensure that confidential or sensitive information is properly concealed. Yet, in certain cases such as IPD that are public but not anonymized (e.g., public databases of industry payments to physicians or of scientific productivity), complex data protection issues could still apply. For example, the General Data Protection Regulation (GDPR) laws in Europe could prevent the sharing of a new database resulting from merging already public databases with personal data unless specific conditions are met. Under GDPR, individuals need to be informed about and can deny the use of their non-anonymized personal data, in theory even when it is public, like industry sponsorship or citation counts. Such situations would require additional effort on the part of the investigators and even specialized legal consultancy from data privacy and protection experts. Ethical and legal views about IPD data ownership and sharing [START_REF] Montgomery | Data Sharing and the Idea of Ownership[END_REF][START_REF] Mikk | The Pathway to Patient Data Ownership and Better Health[END_REF][START_REF] Contreras | Patient Data Ownership[END_REF] can apply to both clinical and meta-research and hinge on the degree to which the data is properly anonymized. Such concerns are not germane for metaresearch studies using aggregate data, as the information is theoretically publicly available (though it might not be accessible to all).

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Improved evaluation from funders and institutions using 'Responsible Metrics' Table 1. Potential data-sharing barriers and facilitators in meta-research compared to clinical researc

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Inadequate practices of data sharing

We hypothesize two practices that result in sharing of incomplete data are particularly applicable for meta-research. The first is simply stating that the primary data are publicly available or, in a more restricted fashion, available upon request. A related version is stating all data are available within the paper and the supplementary material. These boilerplates are commonly identified in analyses of data sharing statements, even for journals that mandate data sharing [START_REF] Colavizza | The citation advantage of linking publications to research data[END_REF]. For meta-research in particular, such statements are redundant in the cases where the primary data is available from public databases, like clinical trial registries or public databases like NIH Reporter or Open Payments. Other meta-research studies are based on collections of publications, in theory publicly available, though publisher fees prevent many researchers from accessing them. Standardized data accessibility statements have little value beyond providing superficial reassurance that the meta-research could in theory be replicated, given access to the underlying sources was guaranteed and the methods transparently and completely reported.

Another deleterious practice is exclusively sharing the final database on which analyses were run. Meta-researchers usually organize extracted data into categories, using complex coding schemes and decision trees. There is often a high degree of subjectivity in developing these materials, as for example when ascertaining whether a finding is described in a positive or negative light or detecting spin [START_REF] Yavchitz | A new classification of spin in systematic reviews and meta-analyses was developed and ranked according to the severity[END_REF]. Independent raters frequently make different coding decisions, particularly for ambiguous or borderline (i.e., fitting more or none of the categories) cases. In other situations, computations such as conversion or recalculations of effects need to be undertaken to derive a homogenous dataset for the analyses. Though the formulas for these calculations are usually straightforward, their implementation requires deciding what data to use from the main papers. When data sharing only involves final datasets, after categorizations, conversions and recalculations, crucial steps of study implementation cannot be reproduced.

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Likewise, reuse is restricted as researchers cannot access and implement changes at various stages in the research process, such as making different coding decisions, using other categories or making different decisions about conversion or recalculation.

Formulation of data availability requirements by journals are not specific enough to prevent practices of incomplete or inadequate data sharing. For instance, for PLOS journals, which mandate data sharing, the requirement is that "all data necessary to replicate their study's findings publicly available without restriction at the time of publication" (https://journals.plos.org/plosone/s/data-availability). For BMJ journals, the most stringent data sharing policy ("tier 1") requires "that the data generated by your research that supports your article be made openly and publicly available upon publication of your article" (https://authors.bmj.com/policies/data-sharing/). BMC journals require that "you agree to make the raw data and materials described in your manuscript freely available to any scientist wishing to use them for non-commercial purposes, as long as this does not breach participant confidentiality" (https://www.biomedcentral.com/getpublished/writing-resources/structuringyour-data-materials-and-software). For meta-research studies, these formulations consent an array of heterogeneous and inconsistent data sharing practices, such as simply stating that all data sources are publicly available, sharing only the final, curated datasets or sharing all data extracted and used across all the stages of the study.

Recommendations to improve data sharing for meta-research studies.

Tailored initiatives and resources could facilitate more efficient and complete data sharing for meta-research studies. Regarding support for data sharing, specific guidelines are needed to support improved implementation. The new PRISMA 2020 statement for reporting meta-analyses [START_REF] Page | The PRISMA 2020 statement: an updated guideline for reporting systematic reviews[END_REF] could serve as a template. It requires mentioning whether each of the following is publicly available and where: "template data collection forms, data extracted from J o u r n a l P r e -p r o o f included studies, data used for all analyses, analytic code, any other materials used in the review". Beyond guidelines, tools and resources to support both sharing data and accessing shared data need to become more widely available and streamlined. Widely used resources such as Pubmed.gov could support searching data sharing statements, as currently done for conflict of interest statements, streamlining the process of retrieving and accessing available datasets. Platforms frequently used for the prospective registration of meta-research studies, like PROSPERO, could allow the inclusion of data, code and materials together with the protocols, similarly to the trial registration platform clinicaltrials.gov. Another platform frequently used for registration, the Open Science Framework, links shared data to protocol registration under certain circumstances, such as when authors post a preprint, or when they create a project including registrations, shared data and code as elements. A more uniform and straightforward procedure of automatically linking shared data to other open study documents, like protocols or preprints, without requiring further action from authors, would be welcome.

A more complex issue regards the sharing of libraries of articles that were aggregated for the meta-research study. To circumvent copyright issues, it was suggested [START_REF] Ross | Clinical research data sharing: what an open science world means for researchers involved in evidence synthesis[END_REF] to list aggregated articles by DOIs linking to publishers' websites or Pubmed identification numbers (PMIDs).

With regards to practical steps to be taken by meta-researchers and publishers, it is important to make the distinction regards studies using IPD versus aggregated data. Though aggregate data are easier to curate and subsequently share, they are more limited in the range and breadth of research questions that can be answered. Crucial questions about treatment harms, often rare events, disease prognosis or treatment personalization cannot be answered with aggregate data and require access to large samples of IPD. Figure 1 displays a decision tree addressed to researchers, with actionable recommendations at every step of the process: data preparation, organization and sharing. Irrespective of the type of data, properly sharing usable metadata is essential and, again, an ethical obligation for meta-researchers who heavily J o u r n a l P r e -p r o o f rely on metadata themselves. Adequate sharing of meta-data should follow the FAIR (Findability, Accessibility, Interoperability and Reuse) principles [START_REF] Wilkinson | The FAIR Guiding Principles for scientific data management and stewardship[END_REF]. On the journal side, requiring data availability statements needs to ensure these move beyond boilerplates.

Standardized formulations (i.e., available upon request, available in the manuscript and supplementary material) should be rejected in favor of more explicit statements that take study type into account. For example, for meta-research papers, the PRISMA 2020 [START_REF] Page | The PRISMA 2020 statement: an updated guideline for reporting systematic reviews[END_REF] could be used for redacting data sharing statements by indicating exactly where each element is available in the manuscript, supplement or public repositories. Furthermore, shared data and material could be integrated more organically into manuscripts. Data availability statements, often just manuscript codas, could be complemented by in-text citation of shared datasets and material in all points these could be relevant, as customary for supplementary material. Finally, properly sharing data and meta-data is just one necessary but insufficient step toward making meta-research more reproducible and reusable. Sharing the clearly annotated data analysis code is another key piece.

The meta-research community should also actively evaluate the impact of data sharing policies and recommendations on ascertaining the reproducibility of the original findings or the degree to which shared data is reused to generate new results. For example, investigations of existent data availability statements could move beyond classifying these [START_REF] Colavizza | The citation advantage of linking publications to research data[END_REF] or assessing whether any data is accessible or usable (i.e., functional link) [START_REF] Federer | Data sharing in PLOS ONE: An analysis of Data Availability Statements[END_REF][START_REF] Rowhani-Farid | Has open data arrived at the British Medical Journal (BMJ)? An observational study[END_REF][START_REF] Mcdonald | A review of data sharing statements in observational studies published in the BMJ: A cross-sectional study [version 2[END_REF][START_REF] Danchev | Evaluation of Data Sharing After Implementation of the International Committee of Medical Journal Editors Data Sharing Statement Requirement[END_REF] to clarifying whether all steps of the research process are fully supported by publicly available data.

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Conclusions

Data sharing is gradually becoming a requirement across all fields of science, owing to its key benefits in allowing verification of the reproducibility of findings and reuse of existent data for new purposes. For meta-analyses and meta-research studies in particular, most barriers to data sharing boil down to insufficient procedural knowledge or access to guidelines, resources, and other tools. Confidentiality or data protection issues are frequently not applicable, except for studies relying on IPD and for which the primary data was not already publicly and appropriately shared. As secondary data users par excellence, meta-researchers are ethically bound to both improving and evaluating data sharing practices, as well as correctly sharing their own data.

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Figure 1 .

 1 Figure 1. Decision tree for the data-sharing of meta-research studies

  Fear of data misuse / Fear of hostile re-analysis Fear of losing value associated with the cost/effort of data collection (meta-researchers as "research parasites")

			Clinical research		Meta-research
		Data type	Primary data		Individual participant data	Aggregated data
			Data anonymization compliance	Data anonymization compliance with local	No barrier (provided the level of
			with local regulations		regulations (in case of pseudonymized primary data)	aggregation is appropriate for the
		Data protection	Compliance with privacy laws	Compliance with privacy laws	data to be considered anonymized)
	barriers sharing	Resources	Funding Lack of procedural standards and guidelines Lack of knowledge on the ways to efficiently and correctly share data Funding limited to complex situations Time-consuming
	Data	Ethics/Legal	Protection of research subjects Data ownership & consent to reuse	Protection of research subjects (in case of pseudonymized data) Data ownership & consent to reuse	Data privacy and protection issues when creating new datasets All data theoretically publicly available
		Career opportunities	Loss of publication opportunities Loss of opportunities to maximize returns of intellectual property over the data (e.g., by limiting collectors' data reuse)
					Contribution to the advancement of science
	facilitators sharing Data	Values and benefits Resources Ethics	Data are "public good"	Promotion of open science values Increase of research visibility and impact (citations, visualizations) Minimize research overlap Minimize research costs Accelerate scientific discoveries Respond to public health needs Maximize optimal data use for patient benefit Uncover and substantiate cases of data fabrication or fraud Meta-researchers have "debt" as secondary data users
		Career opportunities	Opportunities for collaboration and funding Academic benefit (e.g., recognition as creators of datasets, secondary papers)
						1

Funding: None

Declaration of interest:

The authors declare no financial conflict of interest. All authors are responsible of having used the inappropriate data sharing practices discussed in their own work.

Author contributions: IAC and LC wrote the first draft of the manuscript. FN substantially revised the draft. All authors approved the current version for submission.

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